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Sensors, Volume 15, Issue 11 (November 2015), Pages 27393-29764

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Open AccessArticle Design and Fabrication of a Real-Time Measurement System for the Capsaicinoid Content of Korean Red Pepper (Capsicum annuum L.) Powder by Visible and Near-Infrared Spectroscopy
Sensors 2015, 15(11), 27420-27435; doi:10.3390/s151127420
Received: 17 July 2015 / Revised: 26 October 2015 / Accepted: 26 October 2015 / Published: 29 October 2015
Cited by 1 | PDF Full-text (2969 KB) | HTML Full-text | XML Full-text
Abstract
This research aims to design and fabricate a system to measure the capsaicinoid content of red pepper powder in a non-destructive and rapid method using visible and near infrared spectroscopy (VNIR). The developed system scans a well-leveled powder surface continuously to minimize the
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This research aims to design and fabricate a system to measure the capsaicinoid content of red pepper powder in a non-destructive and rapid method using visible and near infrared spectroscopy (VNIR). The developed system scans a well-leveled powder surface continuously to minimize the influence of the placenta distribution, thus acquiring stable and representative reflectance spectra. The system incorporates flat belts driven by a sample input hopper and stepping motor, a powder surface leveler, charge-coupled device (CCD) image sensor-embedded VNIR spectrometer, fiber optic probe, and tungsten halogen lamp, and an automated reference measuring unit with a reference panel to measure the standard spectrum. The operation program includes device interface, standard reflectivity measurement, and a graphical user interface to measure the capsaicinoid content. A partial least square regression (PLSR) model was developed to predict the capsaicinoid content; 44 red pepper powder samples whose measured capsaicinoid content ranged 13.45–159.48 mg/100 g by per high-performance liquid chromatography (HPLC) and 1242 VNIR absorbance spectra acquired by the pungency measurement system were used. The determination coefficient of validation (RV2) and standard error of prediction (SEP) for the model with the first-order derivative pretreatment method for Korean red pepper powder were 0.8484 and ±13.6388 mg/100 g, respectively. Full article
(This article belongs to the Section Physical Sensors)
Open AccessArticle SITRUS: Semantic Infrastructure for Wireless Sensor Networks
Sensors 2015, 15(11), 27436-27469; doi:10.3390/s151127436
Received: 4 June 2015 / Revised: 13 October 2015 / Accepted: 19 October 2015 / Published: 29 October 2015
Cited by 2 | PDF Full-text (778 KB) | HTML Full-text | XML Full-text
Abstract
Wireless sensor networks (WSNs) are made up of nodes with limited resources, such as processing, bandwidth, memory and, most importantly, energy. For this reason, it is essential that WSNs always work to reduce the power consumption as much as possible in order to
[...] Read more.
Wireless sensor networks (WSNs) are made up of nodes with limited resources, such as processing, bandwidth, memory and, most importantly, energy. For this reason, it is essential that WSNs always work to reduce the power consumption as much as possible in order to maximize its lifetime. In this context, this paper presents SITRUS (semantic infrastructure for wireless sensor networks), which aims to reduce the power consumption of WSN nodes using ontologies. SITRUS consists of two major parts: a message-oriented middleware responsible for both an oriented message communication service and a reconfiguration service; and a semantic information processing module whose purpose is to generate a semantic database that provides the basis to decide whether a WSN node needs to be reconfigurated or not. In order to evaluate the proposed solution, we carried out an experimental evaluation to assess the power consumption and memory usage of WSN applications built atop SITRUS. Full article
Open AccessArticle Advanced Interrogation of Fiber-Optic Bragg Grating and Fabry-Perot Sensors with KLT Analysis
Sensors 2015, 15(11), 27470-27492; doi:10.3390/s151127470
Received: 20 August 2015 / Revised: 19 October 2015 / Accepted: 24 October 2015 / Published: 29 October 2015
Cited by 2 | PDF Full-text (1417 KB) | HTML Full-text | XML Full-text
Abstract
The Karhunen-Loeve Transform (KLT) is applied to accurate detection of optical fiber sensors in the spectral domain. By processing an optical spectrum, although coarsely sampled, through the KLT, and subsequently processing the obtained eigenvalues, it is possible to decode a plurality of optical
[...] Read more.
The Karhunen-Loeve Transform (KLT) is applied to accurate detection of optical fiber sensors in the spectral domain. By processing an optical spectrum, although coarsely sampled, through the KLT, and subsequently processing the obtained eigenvalues, it is possible to decode a plurality of optical sensor results. The KLT returns higher accuracy than other demodulation techniques, despite coarse sampling, and exhibits higher resilience to noise. Three case studies of KLT-based processing are presented, representing most of the current challenges in optical fiber sensing: (1) demodulation of individual sensors, such as Fiber Bragg Gratings (FBGs) and Fabry-Perot Interferometers (FPIs); (2) demodulation of dual (FBG/FPI) sensors; (3) application of reverse KLT to isolate different sensors operating on the same spectrum. A simulative outline is provided to demonstrate the KLT operation and estimate performance; a brief experimental section is also provided to validate accurate FBG and FPI decoding. Full article
(This article belongs to the Section Physical Sensors)
Open AccessArticle Development and Evaluation of a UAV-Photogrammetry System for Precise 3D Environmental Modeling
Sensors 2015, 15(11), 27493-27524; doi:10.3390/s151127493
Received: 15 September 2015 / Revised: 19 October 2015 / Accepted: 20 October 2015 / Published: 30 October 2015
Cited by 11 | PDF Full-text (9294 KB) | HTML Full-text | XML Full-text
Abstract
The specific requirements of UAV-photogrammetry necessitate particular solutions for system development, which have mostly been ignored or not assessed adequately in recent studies. Accordingly, this paper presents the methodological and experimental aspects of correctly implementing a UAV-photogrammetry system. The hardware of the system
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The specific requirements of UAV-photogrammetry necessitate particular solutions for system development, which have mostly been ignored or not assessed adequately in recent studies. Accordingly, this paper presents the methodological and experimental aspects of correctly implementing a UAV-photogrammetry system. The hardware of the system consists of an electric-powered helicopter, a high-resolution digital camera and an inertial navigation system. The software of the system includes the in-house programs specifically designed for camera calibration, platform calibration, system integration, on-board data acquisition, flight planning and on-the-job self-calibration. The detailed features of the system are discussed, and solutions are proposed in order to enhance the system and its photogrammetric outputs. The developed system is extensively tested for precise modeling of the challenging environment of an open-pit gravel mine. The accuracy of the results is evaluated under various mapping conditions, including direct georeferencing and indirect georeferencing with different numbers, distributions and types of ground control points. Additionally, the effects of imaging configuration and network stability on modeling accuracy are assessed. The experiments demonstrated that 1.55 m horizontal and 3.16 m vertical absolute modeling accuracy could be achieved via direct geo-referencing, which was improved to 0.4 cm and 1.7 cm after indirect geo-referencing. Full article
(This article belongs to the Special Issue UAV Sensors for Environmental Monitoring)
Open AccessArticle Improving Ambiguity Resolution for Medium Baselines Using Combined GPS and BDS Dual/Triple-Frequency Observations
Sensors 2015, 15(11), 27525-27542; doi:10.3390/s151127525
Received: 2 September 2015 / Revised: 15 October 2015 / Accepted: 21 October 2015 / Published: 30 October 2015
Cited by 6 | PDF Full-text (1064 KB) | HTML Full-text | XML Full-text
Abstract
The regional constellation of the BeiDou navigation satellite system (BDS) has been providing continuous positioning, navigation and timing services since 27 December 2012, covering China and the surrounding area. Real-time kinematic (RTK) positioning with combined BDS and GPS observations is feasible. Besides, all
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The regional constellation of the BeiDou navigation satellite system (BDS) has been providing continuous positioning, navigation and timing services since 27 December 2012, covering China and the surrounding area. Real-time kinematic (RTK) positioning with combined BDS and GPS observations is feasible. Besides, all satellites of BDS can transmit triple-frequency signals. Using the advantages of multi-pseudorange and carrier observations from multi-systems and multi-frequencies is expected to be of much benefit for ambiguity resolution (AR). We propose an integrated AR strategy for medium baselines by using the combined GPS and BDS dual/triple-frequency observations. In the method, firstly the extra-wide-lane (EWL) ambiguities of triple-frequency system, i.e., BDS, are determined first. Then the dual-frequency WL ambiguities of BDS and GPS were resolved with the geometry-based model by using the BDS ambiguity-fixed EWL observations. After that, basic (i.e., L1/L2 or B1/B2) ambiguities of BDS and GPS are estimated together with the so-called ionosphere-constrained model, where the ambiguity-fixed WL observations are added to enhance the model strength. During both of the WL and basic AR, a partial ambiguity fixing (PAF) strategy is adopted to weaken the negative influence of new-rising or low-elevation satellites. Experiments were conducted and presented, in which the GPS/BDS dual/triple-frequency data were collected in Nanjing and Zhengzhou of China, with the baseline distance varying from about 28.6 to 51.9 km. The results indicate that, compared to the single triple-frequency BDS system, the combined system can significantly enhance the AR model strength, and thus improve AR performance for medium baselines with a 75.7% reduction of initialization time on average. Besides, more accurate and stable positioning results can also be derived by using the combined GPS/BDS system. Full article
(This article belongs to the Section Remote Sensors)
Open AccessArticle Smart Building: Decision Making Architecture for Thermal Energy Management
Sensors 2015, 15(11), 27543-27568; doi:10.3390/s151127543
Received: 20 August 2015 / Revised: 19 October 2015 / Accepted: 23 October 2015 / Published: 30 October 2015
Cited by 3 | PDF Full-text (5865 KB) | HTML Full-text | XML Full-text
Abstract
Smart applications of the Internet of Things are improving the performance of buildings, reducing energy demand. Local and smart networks, soft computing methodologies, machine intelligence algorithms and pervasive sensors are some of the basics of energy optimization strategies developed for the benefit of
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Smart applications of the Internet of Things are improving the performance of buildings, reducing energy demand. Local and smart networks, soft computing methodologies, machine intelligence algorithms and pervasive sensors are some of the basics of energy optimization strategies developed for the benefit of environmental sustainability and user comfort. This work presents a distributed sensor-processor-communication decision-making architecture to improve the acquisition, storage and transfer of thermal energy in buildings. The developed system is implemented in a near Zero-Energy Building (nZEB) prototype equipped with a built-in thermal solar collector, where optical properties are analysed; a low enthalpy geothermal accumulation system, segmented in different temperature zones; and an envelope that includes a dynamic thermal barrier. An intelligent control of this dynamic thermal barrier is applied to reduce the thermal energy demand (heating and cooling) caused by daily and seasonal weather variations. Simulations and experimental results are presented to highlight the nZEB thermal energy reduction. Full article
(This article belongs to the Section Physical Sensors)
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Open AccessArticle Calibration of Kinect for Xbox One and Comparison between the Two Generations of Microsoft Sensors
Sensors 2015, 15(11), 27569-27589; doi:10.3390/s151127569
Received: 3 August 2015 / Revised: 26 October 2015 / Accepted: 27 October 2015 / Published: 30 October 2015
Cited by 18 | PDF Full-text (5213 KB) | HTML Full-text | XML Full-text
Abstract
In recent years, the videogame industry has been characterized by a great boost in gesture recognition and motion tracking, following the increasing request of creating immersive game experiences. The Microsoft Kinect sensor allows acquiring RGB, IR and depth images with a high frame
[...] Read more.
In recent years, the videogame industry has been characterized by a great boost in gesture recognition and motion tracking, following the increasing request of creating immersive game experiences. The Microsoft Kinect sensor allows acquiring RGB, IR and depth images with a high frame rate. Because of the complementary nature of the information provided, it has proved an attractive resource for researchers with very different backgrounds. In summer 2014, Microsoft launched a new generation of Kinect on the market, based on time-of-flight technology. This paper proposes a calibration of Kinect for Xbox One imaging sensors, focusing on the depth camera. The mathematical model that describes the error committed by the sensor as a function of the distance between the sensor itself and the object has been estimated. All the analyses presented here have been conducted for both generations of Kinect, in order to quantify the improvements that characterize every single imaging sensor. Experimental results show that the quality of the delivered model improved applying the proposed calibration procedure, which is applicable to both point clouds and the mesh model created with the Microsoft Fusion Libraries. Full article
(This article belongs to the Section State-of-the-Art Sensors Technologies)
Open AccessArticle Dynamic Performance Comparison of Two Kalman Filters for Rate Signal Direct Modeling and Differencing Modeling for Combining a MEMS Gyroscope Array to Improve Accuracy
Sensors 2015, 15(11), 27590-27610; doi:10.3390/s151127590
Received: 20 August 2015 / Revised: 21 October 2015 / Accepted: 23 October 2015 / Published: 30 October 2015
Cited by 2 | PDF Full-text (1294 KB) | HTML Full-text | XML Full-text
Abstract
In this paper, the performance of two Kalman filter (KF) schemes based on the direct estimated model and differencing estimated model for input rate signal was thoroughly analyzed and compared for combining measurements of a sensor array to improve the accuracy of microelectromechanical
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In this paper, the performance of two Kalman filter (KF) schemes based on the direct estimated model and differencing estimated model for input rate signal was thoroughly analyzed and compared for combining measurements of a sensor array to improve the accuracy of microelectromechanical system (MEMS) gyroscopes. The principles for noise reduction were presented and KF algorithms were designed to obtain the optimal rate signal estimates. The input rate signal in the direct estimated KF model was modeled with a random walk process and treated as the estimated system state. In the differencing estimated KF model, a differencing operation was established between outputs of the gyroscope array, and then the optimal estimation of input rate signal was achieved by compensating for the estimations of bias drifts for the component gyroscopes. Finally, dynamic simulations and experiments with a six-gyroscope array were implemented to compare the dynamic performance of the two KF models. The 1σ error of the gyroscopes was reduced from 1.4558°/s to 0.1203°/s by the direct estimated KF model in a constant rate test and to 0.5974°/s by the differencing estimated KF model. The estimated rate signal filtered by both models could reflect the amplitude variation of the input signal in the swing rate test and displayed a reduction factor of about three for the 1σ noise. Results illustrate that the performance of the direct estimated KF model is much higher than that of the differencing estimated KF model, with a constant input signal or lower dynamic variation. A similarity in the two KFs’ performance is observed if the input signal has a high dynamic variation. Full article
(This article belongs to the Section Physical Sensors)
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Open AccessArticle Sparse Auto-Calibration for Radar Coincidence Imaging with Gain-Phase Errors
Sensors 2015, 15(11), 27611-27624; doi:10.3390/s151127611
Received: 27 July 2015 / Revised: 18 October 2015 / Accepted: 26 October 2015 / Published: 30 October 2015
Cited by 7 | PDF Full-text (1012 KB) | HTML Full-text | XML Full-text
Abstract
Radar coincidence imaging (RCI) is a high-resolution staring imaging technique without the limitation of relative motion between target and radar. The sparsity-driven approaches are commonly used in RCI, while the prior knowledge of imaging models needs to be known accurately. However, as one
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Radar coincidence imaging (RCI) is a high-resolution staring imaging technique without the limitation of relative motion between target and radar. The sparsity-driven approaches are commonly used in RCI, while the prior knowledge of imaging models needs to be known accurately. However, as one of the major model errors, the gain-phase error exists generally, and may cause inaccuracies of the model and defocus the image. In the present report, the sparse auto-calibration method is proposed to compensate the gain-phase error in RCI. The method can determine the gain-phase error as part of the imaging process. It uses an iterative algorithm, which cycles through steps of target reconstruction and gain-phase error estimation, where orthogonal matching pursuit (OMP) and Newton’s method are used, respectively. Simulation results show that the proposed method can improve the imaging quality significantly and estimate the gain-phase error accurately. Full article
(This article belongs to the Section Remote Sensors)
Open AccessArticle A Model-Based Approach to Support Validation of Medical Cyber-Physical Systems
Sensors 2015, 15(11), 27625-27670; doi:10.3390/s151127625
Received: 30 June 2015 / Revised: 11 October 2015 / Accepted: 16 October 2015 / Published: 30 October 2015
Cited by 2 | PDF Full-text (5759 KB) | HTML Full-text | XML Full-text
Abstract
Medical Cyber-Physical Systems (MCPS) are context-aware, life-critical systems with patient safety as the main concern, demanding rigorous processes for validation to guarantee user requirement compliance and specification-oriented correctness. In this article, we propose a model-based approach for early validation of MCPS, focusing on
[...] Read more.
Medical Cyber-Physical Systems (MCPS) are context-aware, life-critical systems with patient safety as the main concern, demanding rigorous processes for validation to guarantee user requirement compliance and specification-oriented correctness. In this article, we propose a model-based approach for early validation of MCPS, focusing on promoting reusability and productivity. It enables system developers to build MCPS formal models based on a library of patient and medical device models, and simulate the MCPS to identify undesirable behaviors at design time. Our approach has been applied to three different clinical scenarios to evaluate its reusability potential for different contexts. We have also validated our approach through an empirical evaluation with developers to assess productivity and reusability. Finally, our models have been formally verified considering functional and safety requirements and model coverage. Full article
(This article belongs to the Special Issue Cyber-Physical Systems)
Open AccessArticle Time-Efficient High-Rate Data Flooding in One-Dimensional Acoustic Underwater Sensor Networks
Sensors 2015, 15(11), 27671-27691; doi:10.3390/s151127671
Received: 6 August 2015 / Revised: 21 October 2015 / Accepted: 28 October 2015 / Published: 30 October 2015
Cited by 1 | PDF Full-text (1159 KB) | HTML Full-text | XML Full-text
Abstract
Because underwater communication environments have poor characteristics, such as severe attenuation, large propagation delays and narrow bandwidths, data is normally transmitted at low rates through acoustic waves. On the other hand, as high traffic has recently been required in diverse areas, high rate
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Because underwater communication environments have poor characteristics, such as severe attenuation, large propagation delays and narrow bandwidths, data is normally transmitted at low rates through acoustic waves. On the other hand, as high traffic has recently been required in diverse areas, high rate transmission has become necessary. In this paper, transmission/reception timing schemes that maximize the time axis use efficiency to improve the resource efficiency for high rate transmission are proposed. The excellence of the proposed scheme is identified by examining the power distributions by node, rate bounds, power levels depending on the rates and number of nodes, and network split gains through mathematical analysis and numerical results. In addition, the simulation results show that the proposed scheme outperforms the existing packet train method. Full article
(This article belongs to the Section Sensor Networks)
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Open AccessArticle A Mixed Approach to Similarity Metric Selection in Affinity Propagation-Based WiFi Fingerprinting Indoor Positioning
Sensors 2015, 15(11), 27692-27720; doi:10.3390/s151127692
Received: 30 September 2015 / Revised: 19 October 2015 / Accepted: 26 October 2015 / Published: 30 October 2015
Cited by 2 | PDF Full-text (676 KB) | HTML Full-text | XML Full-text
Abstract
The weighted k-nearest neighbors (WkNN) algorithm is by far the most popular choice in the design of fingerprinting indoor positioning systems based on WiFi received signal strength (RSS). WkNN estimates the position of a target device by selecting
[...] Read more.
The weighted k-nearest neighbors (WkNN) algorithm is by far the most popular choice in the design of fingerprinting indoor positioning systems based on WiFi received signal strength (RSS). WkNN estimates the position of a target device by selecting k reference points (RPs) based on the similarity of their fingerprints with the measured RSS values. The position of the target device is then obtained as a weighted sum of the positions of the k RPs. Two-step WkNN positioning algorithms were recently proposed, in which RPs are divided into clusters using the affinity propagation clustering algorithm, and one representative for each cluster is selected. Only cluster representatives are then considered during the position estimation, leading to a significant computational complexity reduction compared to traditional, flat WkNN. Flat and two-step WkNN share the issue of properly selecting the similarity metric so as to guarantee good positioning accuracy: in two-step WkNN, in particular, the metric impacts three different steps in the position estimation, that is cluster formation, cluster selection and RP selection and weighting. So far, however, the only similarity metric considered in the literature was the one proposed in the original formulation of the affinity propagation algorithm. This paper fills this gap by comparing different metrics and, based on this comparison, proposes a novel mixed approach in which different metrics are adopted in the different steps of the position estimation procedure. The analysis is supported by an extensive experimental campaign carried out in a multi-floor 3D indoor positioning testbed. The impact of similarity metrics and their combinations on the structure and size of the resulting clusters, 3D positioning accuracy and computational complexity are investigated. Results show that the adoption of metrics different from the one proposed in the original affinity propagation algorithm and, in particular, the combination of different metrics can significantly improve the positioning accuracy while preserving the efficiency in computational complexity typical of two-step algorithms. Full article
(This article belongs to the Special Issue Sensors for Indoor Mapping and Navigation)
Open AccessArticle A Cutting Pattern Recognition Method for Shearers Based on Improved Ensemble Empirical Mode Decomposition and a Probabilistic Neural Network
Sensors 2015, 15(11), 27721-27737; doi:10.3390/s151127721
Received: 22 September 2015 / Revised: 22 October 2015 / Accepted: 27 October 2015 / Published: 30 October 2015
Cited by 2 | PDF Full-text (7802 KB) | HTML Full-text | XML Full-text
Abstract
In order to guarantee the stable operation of shearers and promote construction of an automatic coal mining working face, an online cutting pattern recognition method with high accuracy and speed based on Improved Ensemble Empirical Mode Decomposition (IEEMD) and Probabilistic Neural Network (PNN)
[...] Read more.
In order to guarantee the stable operation of shearers and promote construction of an automatic coal mining working face, an online cutting pattern recognition method with high accuracy and speed based on Improved Ensemble Empirical Mode Decomposition (IEEMD) and Probabilistic Neural Network (PNN) is proposed. An industrial microphone is installed on the shearer and the cutting sound is collected as the recognition criterion to overcome the disadvantages of giant size, contact measurement and low identification rate of traditional detectors. To avoid end-point effects and get rid of undesirable intrinsic mode function (IMF) components in the initial signal, IEEMD is conducted on the sound. The end-point continuation based on the practical storage data is performed first to overcome the end-point effect. Next the average correlation coefficient, which is calculated by the correlation of the first IMF with others, is introduced to select essential IMFs. Then the energy and standard deviation of the reminder IMFs are extracted as features and PNN is applied to classify the cutting patterns. Finally, a simulation example, with an accuracy of 92.67%, and an industrial application prove the efficiency and correctness of the proposed method. Full article
(This article belongs to the Section Physical Sensors)
Open AccessArticle A Neural Network-Based Gait Phase Classification Method Using Sensors Equipped on Lower Limb Exoskeleton Robots
Sensors 2015, 15(11), 27738-27759; doi:10.3390/s151127738
Received: 27 August 2015 / Revised: 21 October 2015 / Accepted: 29 October 2015 / Published: 30 October 2015
Cited by 5 | PDF Full-text (1752 KB) | HTML Full-text | XML Full-text
Abstract
An exact classification of different gait phases is essential to enable the control of exoskeleton robots and detect the intentions of users. We propose a gait phase classification method based on neural networks using sensor signals from lower limb exoskeleton robots. In such
[...] Read more.
An exact classification of different gait phases is essential to enable the control of exoskeleton robots and detect the intentions of users. We propose a gait phase classification method based on neural networks using sensor signals from lower limb exoskeleton robots. In such robots, foot sensors with force sensing registers are commonly used to classify gait phases. We describe classifiers that use the orientation of each lower limb segment and the angular velocities of the joints to output the current gait phase. Experiments to obtain the input signals and desired outputs for the learning and validation process are conducted, and two neural network methods (a multilayer perceptron and nonlinear autoregressive with external inputs (NARX)) are used to develop an optimal classifier. Offline and online evaluations using four criteria are used to compare the performance of the classifiers. The proposed NARX-based method exhibits sufficiently good performance to replace foot sensors as a means of classifying gait phases. Full article
(This article belongs to the Special Issue Sensors for Robots)
Open AccessArticle A Novel Wireless Power Transfer-Based Weighed Clustering Cooperative Spectrum Sensing Method for Cognitive Sensor Networks
Sensors 2015, 15(11), 27760-27782; doi:10.3390/s151127760
Received: 27 July 2015 / Revised: 24 October 2015 / Accepted: 26 October 2015 / Published: 30 October 2015
Cited by 3 | PDF Full-text (819 KB) | HTML Full-text | XML Full-text
Abstract
In a cognitive sensor network (CSN), the wastage of sensing time and energy is a challenge to cooperative spectrum sensing, when the number of cooperative cognitive nodes (CNs) becomes very large. In this paper, a novel wireless power transfer (WPT)-based weighed clustering cooperative
[...] Read more.
In a cognitive sensor network (CSN), the wastage of sensing time and energy is a challenge to cooperative spectrum sensing, when the number of cooperative cognitive nodes (CNs) becomes very large. In this paper, a novel wireless power transfer (WPT)-based weighed clustering cooperative spectrum sensing model is proposed, which divides all the CNs into several clusters, and then selects the most favorable CNs as the cluster heads and allows the common CNs to transfer the received radio frequency (RF) energy of the primary node (PN) to the cluster heads, in order to supply the electrical energy needed for sensing and cooperation. A joint resource optimization is formulated to maximize the spectrum access probability of the CSN, through jointly allocating sensing time and clustering number. According to the resource optimization results, a clustering algorithm is proposed. The simulation results have shown that compared to the traditional model, the cluster heads of the proposed model can achieve more transmission power and there exists optimal sensing time and clustering number to maximize the spectrum access probability. Full article
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Open AccessArticle Multi-UAV Routing for Area Coverage and Remote Sensing with Minimum Time
Sensors 2015, 15(11), 27783-27803; doi:10.3390/s151127783
Received: 27 June 2015 / Revised: 17 September 2015 / Accepted: 27 October 2015 / Published: 2 November 2015
Cited by 10 | PDF Full-text (879 KB) | HTML Full-text | XML Full-text | Supplementary Files
Abstract
This paper presents a solution for the problem of minimum time coverage of ground areas using a group of unmanned air vehicles (UAVs) equipped with image sensors. The solution is divided into two parts: (i) the task modeling as a graph whose vertices
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This paper presents a solution for the problem of minimum time coverage of ground areas using a group of unmanned air vehicles (UAVs) equipped with image sensors. The solution is divided into two parts: (i) the task modeling as a graph whose vertices are geographic coordinates determined in such a way that a single UAV would cover the area in minimum time; and (ii) the solution of a mixed integer linear programming problem, formulated according to the graph variables defined in the first part, to route the team of UAVs over the area. The main contribution of the proposed methodology, when compared with the traditional vehicle routing problem’s (VRP) solutions, is the fact that our method solves some practical problems only encountered during the execution of the task with actual UAVs. In this line, one of the main contributions of the paper is that the number of UAVs used to cover the area is automatically selected by solving the optimization problem. The number of UAVs is influenced by the vehicles’ maximum flight time and by the setup time, which is the time needed to prepare and launch a UAV. To illustrate the methodology, the paper presents experimental results obtained with two hand-launched, fixed-wing UAVs. Full article
(This article belongs to the Special Issue UAV Sensors for Environmental Monitoring)
Open AccessArticle Active-Optical Sensors Using Red NDVI Compared to Red Edge NDVI for Prediction of Corn Grain Yield in North Dakota, U.S.A.
Sensors 2015, 15(11), 27832-27853; doi:10.3390/s151127832
Received: 13 August 2015 / Revised: 22 October 2015 / Accepted: 28 October 2015 / Published: 2 November 2015
Cited by 6 | PDF Full-text (964 KB) | HTML Full-text | XML Full-text
Abstract
Active-optical sensor readings from an N non-limiting area standard established within a farm field are used to predict yield in the standard. Lower yield predictions from sensor readings obtained from other parts of the field outside of the N non-limiting standard area indicate
[...] Read more.
Active-optical sensor readings from an N non-limiting area standard established within a farm field are used to predict yield in the standard. Lower yield predictions from sensor readings obtained from other parts of the field outside of the N non-limiting standard area indicate a need for supplemental N. Active-optical sensor algorithms for predicting corn (Zea mays, L.) yield to direct in-season nitrogen (N) fertilization in corn utilize red NDVI (normalized differential vegetative index). Use of red edge NDVI might improve corn yield prediction at later growth stages when corn leaves cover the inter-row space resulting in “saturation” of red NDVI readings. The purpose of this study was to determine whether the use of red edge NDVI in two active-optical sensors (GreenSeeker™ and Holland Scientific Crop Circle™) improved corn yield prediction. Nitrogen rate experiments were established at 15 sites in North Dakota (ND). Sensor readings were conducted at V6 and V12 corn. Red NDVI and red edge NDVI were similar in the relationship of readings with yield at V6. At V12, the red edge NDVI was superior to the red NDVI in most comparisons, indicating that it would be most useful in developing late-season N application algorithms. Full article
(This article belongs to the Section Remote Sensors)
Open AccessArticle Determination of the Mineral Composition and Toxic Element Contents of Propolis by Near Infrared Spectroscopy
Sensors 2015, 15(11), 27854-27868; doi:10.3390/s151127854
Received: 3 August 2015 / Revised: 16 October 2015 / Accepted: 29 October 2015 / Published: 3 November 2015
Cited by 3 | PDF Full-text (984 KB) | HTML Full-text | XML Full-text
Abstract
The potential of near infrared spectroscopy (NIR) with remote reflectance fiber-optic probes for determining the mineral composition of propolis was evaluated. This technology allows direct measurements without prior sample treatment. Ninety one samples of propolis were collected in Chile (Bio-Bio region) and Spain
[...] Read more.
The potential of near infrared spectroscopy (NIR) with remote reflectance fiber-optic probes for determining the mineral composition of propolis was evaluated. This technology allows direct measurements without prior sample treatment. Ninety one samples of propolis were collected in Chile (Bio-Bio region) and Spain (Castilla-León and Galicia regions). The minerals measured were aluminum, calcium, iron, potassium, magnesium, phosphorus, and some potentially toxic trace elements such as zinc, chromium, nickel, copper and lead. The modified partial least squares (MPLS) regression method was used to develop the NIR calibration model. The determination coefficient (R2) and root mean square error of prediction (RMSEP) obtained for aluminum (0.79, 53), calcium (0.83, 94), iron (0.69, 134) potassium (0.95, 117), magnesium (0.70, 99), phosphorus (0.94, 24) zinc (0.87, 10) chromium (0.48, 0.6) nickel (0.52, 0.7) copper (0.64, 0.9) and lead (0.70, 2) in ppm. The results demonstrated that the capacity for prediction can be considered good for wide ranges of potassium, phosphorus and zinc concentrations, and acceptable for aluminum, calcium, magnesium, iron and lead. This indicated that the NIR method is comparable to chemical methods. The method is of interest in the rapid prediction of potentially toxic elements in propolis before consumption. Full article
(This article belongs to the Special Issue Chemical Sensors based on In Situ Spectroscopy)
Open AccessArticle A Novel Characteristic Frequency Bands Extraction Method for Automatic Bearing Fault Diagnosis Based on Hilbert Huang Transform
Sensors 2015, 15(11), 27869-27893; doi:10.3390/s151127869
Received: 9 July 2015 / Revised: 29 September 2015 / Accepted: 10 October 2015 / Published: 3 November 2015
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Abstract
Because roller element bearings (REBs) failures cause unexpected machinery breakdowns, their fault diagnosis has attracted considerable research attention. Established fault feature extraction methods focus on statistical characteristics of the vibration signal, which is an approach that loses sight of the continuous waveform features.
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Because roller element bearings (REBs) failures cause unexpected machinery breakdowns, their fault diagnosis has attracted considerable research attention. Established fault feature extraction methods focus on statistical characteristics of the vibration signal, which is an approach that loses sight of the continuous waveform features. Considering this weakness, this article proposes a novel feature extraction method for frequency bands, named Window Marginal Spectrum Clustering (WMSC) to select salient features from the marginal spectrum of vibration signals by Hilbert–Huang Transform (HHT). In WMSC, a sliding window is used to divide an entire HHT marginal spectrum (HMS) into window spectrums, following which Rand Index (RI) criterion of clustering method is used to evaluate each window. The windows returning higher RI values are selected to construct characteristic frequency bands (CFBs). Next, a hybrid REBs fault diagnosis is constructed, termed by its elements, HHT-WMSC-SVM (support vector machines). The effectiveness of HHT-WMSC-SVM is validated by running series of experiments on REBs defect datasets from the Bearing Data Center of Case Western Reserve University (CWRU). The said test results evidence three major advantages of the novel method. First, the fault classification accuracy of the HHT-WMSC-SVM model is higher than that of HHT-SVM and ST-SVM, which is a method that combines statistical characteristics with SVM. Second, with Gauss white noise added to the original REBs defect dataset, the HHT-WMSC-SVM model maintains high classification accuracy, while the classification accuracy of ST-SVM and HHT-SVM models are significantly reduced. Third, fault classification accuracy by HHT-WMSC-SVM can exceed 95% under a Pmin range of 500–800 and a m range of 50–300 for REBs defect dataset, adding Gauss white noise at Signal Noise Ratio (SNR) = 5. Experimental results indicate that the proposed WMSC method yields a high REBs fault classification accuracy and a good performance in Gauss white noise reduction. Full article
(This article belongs to the Section Physical Sensors)
Open AccessArticle A Spiking Neural Network in sEMG Feature Extraction
Sensors 2015, 15(11), 27894-27904; doi:10.3390/s151127894
Received: 8 September 2015 / Revised: 16 October 2015 / Accepted: 27 October 2015 / Published: 3 November 2015
PDF Full-text (835 KB) | HTML Full-text | XML Full-text | Supplementary Files
Abstract
We have developed a novel algorithm for sEMG feature extraction and classification. It is based on a hybrid network composed of spiking and artificial neurons. The spiking neuron layer with mutual inhibition was assigned as feature extractor. We demonstrate that the classification accuracy
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We have developed a novel algorithm for sEMG feature extraction and classification. It is based on a hybrid network composed of spiking and artificial neurons. The spiking neuron layer with mutual inhibition was assigned as feature extractor. We demonstrate that the classification accuracy of the proposed model could reach high values comparable with existing sEMG interface systems. Moreover, the algorithm sensibility for different sEMG collecting systems characteristics was estimated. Results showed rather equal accuracy, despite a significant sampling rate difference. The proposed algorithm was successfully tested for mobile robot control. Full article
(This article belongs to the Special Issue Noninvasive Biomedical Sensors)
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Open AccessArticle High Resolution Viscosity Measurement by Thermal Noise Detection
Sensors 2015, 15(11), 27905-27916; doi:10.3390/s151127905
Received: 21 September 2015 / Revised: 26 October 2015 / Accepted: 29 October 2015 / Published: 3 November 2015
Cited by 1 | PDF Full-text (806 KB) | HTML Full-text | XML Full-text
Abstract
An interferometric method is implemented in order to accurately assess the thermal fluctuations of a micro-cantilever sensor in liquid environments. The power spectrum density (PSD) of thermal fluctuations together with Sader’s model of the cantilever allow for the indirect measurement of the liquid
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An interferometric method is implemented in order to accurately assess the thermal fluctuations of a micro-cantilever sensor in liquid environments. The power spectrum density (PSD) of thermal fluctuations together with Sader’s model of the cantilever allow for the indirect measurement of the liquid viscosity with good accuracy. The good quality of the deflection signal and the characteristic low noise of the instrument allow for the detection and corrections of drawbacks due to both the cantilever shape irregularities and the uncertainties on the position of the laser spot at the fluctuating end of the cantilever. Variation of viscosity below 0.03 mPa·s was detected with the alternative to achieve measurements with a volume as low as 50 µL. Full article
(This article belongs to the Section Physical Sensors)
Open AccessArticle Surface Plasmon Resonance Sensor Based on Ethylene Tetra-Fluoro-Ethylene Hollow Fiber
Sensors 2015, 15(11), 27917-27929; doi:10.3390/s151127917
Received: 25 September 2015 / Revised: 25 October 2015 / Accepted: 28 October 2015 / Published: 3 November 2015
Cited by 1 | PDF Full-text (6156 KB) | HTML Full-text | XML Full-text
Abstract
A new kind of hollow fiber surface plasmon resonance sensor (HF-SPRS) based on the silver-coated ethylene tetra-fluoro-ethylene (ETFE) hollow fiber (HF) is presented. The ETFE HF-SPRS is fabricated, and its performance is investigated experimentally by measuring the transmission spectra of the sensor when
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A new kind of hollow fiber surface plasmon resonance sensor (HF-SPRS) based on the silver-coated ethylene tetra-fluoro-ethylene (ETFE) hollow fiber (HF) is presented. The ETFE HF-SPRS is fabricated, and its performance is investigated experimentally by measuring the transmission spectra of the sensor when filled by liquid sensed media with different refractive indices (RIs). Theoretical analysis based on the ray transmission model is also taken to evaluate the sensor. Because the RI of ETFE is much lower than that of fused silica (FSG), the ETFE HF-SPRS can extend the lower limit of the detection range of the early reported FSG HF-SPRS from 1.5 to 1.42 approximately. This could greatly enhance the application potential of HF-SPRS. Moreover, the joint use of both ETFE and FSG HF-SPRSs can cover a wide detection range from 1.42 to 1.69 approximately with high sensitivities larger than 1000 nm/RIU. Full article
(This article belongs to the Section Physical Sensors)
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Open AccessArticle A New Analytic Alignment Method for a SINS
Sensors 2015, 15(11), 27930-27953; doi:10.3390/s151127930
Received: 25 July 2015 / Revised: 3 October 2015 / Accepted: 28 October 2015 / Published: 4 November 2015
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Abstract
Analytic alignment is a type of self-alignment for a Strapdown inertial navigation system (SINS) that is based solely on two non-collinear vectors, which are the gravity and rotational velocity vectors of the Earth at a stationary base on the ground. The attitude of
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Analytic alignment is a type of self-alignment for a Strapdown inertial navigation system (SINS) that is based solely on two non-collinear vectors, which are the gravity and rotational velocity vectors of the Earth at a stationary base on the ground. The attitude of the SINS with respect to the Earth can be obtained directly using the TRIAD algorithm given two vector measurements. For a traditional analytic coarse alignment, all six outputs from the inertial measurement unit (IMU) are used to compute the attitude. In this study, a novel analytic alignment method called selective alignment is presented. This method uses only three outputs of the IMU and a few properties from the remaining outputs such as the sign and the approximate value to calculate the attitude. Simulations and experimental results demonstrate the validity of this method, and the precision of yaw is improved using the selective alignment method compared to the traditional analytic coarse alignment method in the vehicle experiment. The selective alignment principle provides an accurate relationship between the outputs and the attitude of the SINS relative to the Earth for a stationary base, and it is an extension of the TRIAD algorithm. The selective alignment approach has potential uses in applications such as self-alignment, fault detection, and self-calibration. Full article
(This article belongs to the Special Issue Inertial Sensors and Systems)
Open AccessArticle Centrifugal Microfluidic System for Nucleic Acid Amplification and Detection
Sensors 2015, 15(11), 27954-27968; doi:10.3390/s151127954
Received: 18 September 2015 / Revised: 24 October 2015 / Accepted: 29 October 2015 / Published: 4 November 2015
Cited by 5 | PDF Full-text (4342 KB) | HTML Full-text | XML Full-text
Abstract
We report here the development of a rapid PCR microfluidic system comprising a double-shaft turntable and centrifugal-based disc that rapidly drives the PCR mixture between chambers set at different temperatures, and the bidirectional flow improved the space utilization of the disc. Three heating
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We report here the development of a rapid PCR microfluidic system comprising a double-shaft turntable and centrifugal-based disc that rapidly drives the PCR mixture between chambers set at different temperatures, and the bidirectional flow improved the space utilization of the disc. Three heating resistors and thermistors maintained uniform, specific temperatures for the denaturation, annealing, and extension steps of the PCR. Infrared imaging showed that there was little thermal interference between reaction chambers; the system enabled the cycle number and reaction time of each step to be independently adjusted. To validate the function and efficiency of the centrifugal microfluidic system, a 350-base pair target gene from the hepatitis B virus was amplified and quantitated by fluorescence detection. By optimizing the cycling parameters, the reaction time was reduced to 32 min as compared to 120 min for a commercial PCR machine. DNA samples with concentrations ranging from 10 to 106 copies/mL could be quantitatively analyzed using this system. This centrifugal-based microfluidic platform is a useful system and possesses industrialization potential that can be used for portable diagnostics. Full article
(This article belongs to the Special Issue Micro/Nano Fluidic Devices and Bio-MEMS)
Open AccessArticle Automated Identification of River Hydromorphological Features Using UAV High Resolution Aerial Imagery
Sensors 2015, 15(11), 27969-27989; doi:10.3390/s151127969
Received: 29 July 2015 / Revised: 24 October 2015 / Accepted: 28 October 2015 / Published: 4 November 2015
Cited by 10 | PDF Full-text (8992 KB) | HTML Full-text | XML Full-text
Abstract
European legislation is driving the development of methods for river ecosystem protection in light of concerns over water quality and ecology. Key to their success is the accurate and rapid characterisation of physical features (i.e., hydromorphology) along the river. Image pattern
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European legislation is driving the development of methods for river ecosystem protection in light of concerns over water quality and ecology. Key to their success is the accurate and rapid characterisation of physical features (i.e., hydromorphology) along the river. Image pattern recognition techniques have been successfully used for this purpose. The reliability of the methodology depends on both the quality of the aerial imagery and the pattern recognition technique used. Recent studies have proved the potential of Unmanned Aerial Vehicles (UAVs) to increase the quality of the imagery by capturing high resolution photography. Similarly, Artificial Neural Networks (ANN) have been shown to be a high precision tool for automated recognition of environmental patterns. This paper presents a UAV based framework for the identification of hydromorphological features from high resolution RGB aerial imagery using a novel classification technique based on ANNs. The framework is developed for a 1.4 km river reach along the river Dee in Wales, United Kingdom. For this purpose, a Falcon 8 octocopter was used to gather 2.5 cm resolution imagery. The results show that the accuracy of the framework is above 81%, performing particularly well at recognising vegetation. These results leverage the use of UAVs for environmental policy implementation and demonstrate the potential of ANNs and RGB imagery for high precision river monitoring and river management. Full article
(This article belongs to the Special Issue UAV Sensors for Environmental Monitoring)
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Open AccessArticle An Open Source Low-Cost Wireless Control System for a Forced Circulation Solar Plant
Sensors 2015, 15(11), 27990-28004; doi:10.3390/s151127990
Received: 25 August 2015 / Revised: 29 October 2015 / Accepted: 30 October 2015 / Published: 5 November 2015
Cited by 7 | PDF Full-text (2345 KB) | HTML Full-text | XML Full-text
Abstract
The article describes the design phase, development and practical application of a low-cost control system for a forced circulation solar plant in an outdoor test cell located near Milan. Such a system provides for the use of an electric pump for the circulation
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The article describes the design phase, development and practical application of a low-cost control system for a forced circulation solar plant in an outdoor test cell located near Milan. Such a system provides for the use of an electric pump for the circulation of heat transfer fluid connecting the solar thermal panel to the storage tank. The running plant temperatures are the fundamental parameter to evaluate the system performance such as proper operation, and the control and management system has to consider these parameters. A solar energy-powered wireless-based smart object was developed, able to monitor the running temperatures of a solar thermal system and aimed at moving beyond standard monitoring approaches to achieve a low-cost and customizable device, even in terms of installation in different environmental conditions. To this end, two types of communications were used: the first is a low-cost communication based on the ZigBee protocol used for control purposes, so that it can be customized according to specific needs, while the second is based on a Bluetooth protocol used for data display. Full article
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Open AccessArticle A Hybrid Lifetime Extended Directional Approach for WBANs
Sensors 2015, 15(11), 28005-28030; doi:10.3390/s151128005
Received: 4 September 2015 / Accepted: 14 September 2015 / Published: 5 November 2015
Cited by 4 | PDF Full-text (1052 KB) | HTML Full-text | XML Full-text
Abstract
Wireless Body Area Networks (WBANs) can provide real-time and reliable health monitoring, attributing to the human-centered and sensor interoperability properties. WBANs have become a key component of the ubiquitous eHealth (electronic health) revolution that prospers on the basis of information and communication technologies.
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Wireless Body Area Networks (WBANs) can provide real-time and reliable health monitoring, attributing to the human-centered and sensor interoperability properties. WBANs have become a key component of the ubiquitous eHealth (electronic health) revolution that prospers on the basis of information and communication technologies. The prime consideration in WBAN is how to maximize the network lifetime with battery-powered sensor nodes in energy constraint. Novel solutions in Medium Access Control (MAC) protocols are imperative to satisfy the particular BAN scenario and the need of excellent energy efficiency in healthcare applications. In this paper, we propose a hybrid Lifetime Extended Directional Approach (LEDA) MAC protocol based on IEEE 802.15.6 to reduce energy consumption and prolong network lifetime. The LEDA MAC protocol takes full advantages of directional superiority in energy saving that employs multi-beam directional mode in Carrier Sense Multiple Access/Collision Avoidance (CSMA/CA) and single-beam directional mode in Time Division Multiple Access (TDMA) for alternative in data reservation and transmission according to the traffic varieties. Moreover, the impacts of some inherent problems of directional antennas such as deafness and hidden terminal problem can be decreased owing to that all nodes generate individual beam according to user priorities designated. Furthermore, LEDA MAC employs a Dynamic Polled Allocation Period (DPAP) for burst data transmissions to increase the network reliability and adaptability. Extensive analysis and simulation results show that the proposed LEDA MAC protocol achieves extended network lifetime with improved performance compared with IEEE 802.15.6. Full article
Open AccessArticle State Tracking and Fault Diagnosis for Dynamic Systems Using Labeled Uncertainty Graph
Sensors 2015, 15(11), 28031-28051; doi:10.3390/s151128031
Received: 19 July 2015 / Revised: 23 October 2015 / Accepted: 29 October 2015 / Published: 5 November 2015
Cited by 1 | PDF Full-text (1087 KB) | HTML Full-text | XML Full-text
Abstract
Cyber-physical systems such as autonomous spacecraft, power plants and automotive systems become more vulnerable to unanticipated failures as their complexity increases. Accurate tracking of system dynamics and fault diagnosis are essential. This paper presents an efficient state estimation method for dynamic systems modeled
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Cyber-physical systems such as autonomous spacecraft, power plants and automotive systems become more vulnerable to unanticipated failures as their complexity increases. Accurate tracking of system dynamics and fault diagnosis are essential. This paper presents an efficient state estimation method for dynamic systems modeled as concurrent probabilistic automata. First, the Labeled Uncertainty Graph (LUG) method in the planning domain is introduced to describe the state tracking and fault diagnosis processes. Because the system model is probabilistic, the Monte Carlo technique is employed to sample the probability distribution of belief states. In addition, to address the sample impoverishment problem, an innovative look-ahead technique is proposed to recursively generate most likely belief states without exhaustively checking all possible successor modes. The overall algorithms incorporate two major steps: a roll-forward process that estimates system state and identifies faults, and a roll-backward process that analyzes possible system trajectories once the faults have been detected. We demonstrate the effectiveness of this approach by applying it to a real world domain: the power supply control unit of a spacecraft. Full article
(This article belongs to the Section Physical Sensors)
Open AccessArticle A Hybrid Sender- and Receiver-Initiated Protocol Scheme in Underwater Acoustic Sensor Networks
Sensors 2015, 15(11), 28052-28069; doi:10.3390/s151128052
Received: 3 August 2015 / Revised: 21 September 2015 / Accepted: 29 October 2015 / Published: 5 November 2015
Cited by 2 | PDF Full-text (519 KB) | HTML Full-text | XML Full-text
Abstract
In this paper, we propose a method for sharing the handshakes of control packets among multiple nodes, which we call a hybrid sender- and receiver-initiated (HSR) protocol scheme. Handshake-sharing can be achieved by inviting neighbors to join the current handshake and by allowing
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In this paper, we propose a method for sharing the handshakes of control packets among multiple nodes, which we call a hybrid sender- and receiver-initiated (HSR) protocol scheme. Handshake-sharing can be achieved by inviting neighbors to join the current handshake and by allowing them to send their data packets without requiring extra handshakes. Thus, HSR can reduce the signaling overhead involved in control packet exchanges during handshakes, as well as resolve the spatial unfairness problem between nodes. From an operational perspective, HSR resembles the well-known handshake-sharing scheme referred to as the medium access control (MAC) protocol using reverse opportunistic packet appending (ROPA). However, in ROPA the waiting time is not controllable for the receiver’s neighbors and thus unexpected collisions may occur at the receiver due to hidden neighbors, whereas the proposed scheme allows all nodes to avoid hidden-node-induced collisions according to an elaborately calculated waiting time. Our computer simulations demonstrated that HSR outperforms ROPA with respect to both the throughput and delay by around 9.65% and 11.36%, respectively. Full article
(This article belongs to the Special Issue Acoustic Waveguide Sensors)
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Open AccessArticle Smartphone Application for the Analysis of Prosodic Features in Running Speech with a Focus on Bipolar Disorders: System Performance Evaluation and Case Study
Sensors 2015, 15(11), 28070-28087; doi:10.3390/s151128070
Received: 31 July 2015 / Revised: 26 September 2015 / Accepted: 26 October 2015 / Published: 6 November 2015
Cited by 4 | PDF Full-text (1214 KB) | HTML Full-text | XML Full-text | Supplementary Files
Abstract
Bipolar disorder is one of the most common mood disorders characterized by large and invalidating mood swings. Several projects focus on the development of decision support systems that monitor and advise patients, as well as clinicians. Voice monitoring and speech signal analysis can
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Bipolar disorder is one of the most common mood disorders characterized by large and invalidating mood swings. Several projects focus on the development of decision support systems that monitor and advise patients, as well as clinicians. Voice monitoring and speech signal analysis can be exploited to reach this goal. In this study, an Android application was designed for analyzing running speech using a smartphone device. The application can record audio samples and estimate speech fundamental frequency, F0, and its changes. F0-related features are estimated locally on the smartphone, with some advantages with respect to remote processing approaches in terms of privacy protection and reduced upload costs. The raw features can be sent to a central server and further processed. The quality of the audio recordings, algorithm reliability and performance of the overall system were evaluated in terms of voiced segment detection and features estimation. The results demonstrate that mean F0 from each voiced segment can be reliably estimated, thus describing prosodic features across the speech sample. Instead, features related to F0 variability within each voiced segment performed poorly. A case study performed on a bipolar patient is presented. Full article
(This article belongs to the Section Physical Sensors)
Open AccessArticle Quantitative Ethylene Measurements with MOx Chemiresistive Sensors at Different Relative Air Humidities
Sensors 2015, 15(11), 28088-28098; doi:10.3390/s151128088
Received: 5 October 2015 / Revised: 2 November 2015 / Accepted: 3 November 2015 / Published: 6 November 2015
Cited by 1 | PDF Full-text (1198 KB) | HTML Full-text | XML Full-text | Supplementary Files
Abstract
The sensitivity of two commercial metal oxide (MOx) sensors to ethylene is tested at different relative humidities. One sensor (MiCS-5914) is based on tungsten oxide, the other (MQ-3) on tin oxide. Both sensors were found to be sensitive to ethylene concentrations down to
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The sensitivity of two commercial metal oxide (MOx) sensors to ethylene is tested at different relative humidities. One sensor (MiCS-5914) is based on tungsten oxide, the other (MQ-3) on tin oxide. Both sensors were found to be sensitive to ethylene concentrations down to 10 ppm. Both sensors have significant response times; however, the tungsten sensor is the faster one. Sensor models are developed that predict the concentration of ethylene given the sensor output and the relative humidity. The MQ-3 sensor model achieves an accuracy of ±9.2 ppm and the MiCS-5914 sensor model predicts concentration to ±7.0 ppm. Both sensors are more accurate for concentrations below 50 ppm, achieving ±6.7 ppm (MQ-3) and 5.7 ppm (MiCS-5914). Full article
(This article belongs to the Special Issue Gas Sensors—Designs and Applications)
Open AccessArticle Kinematic Model-Based Pedestrian Dead Reckoning for Heading Correction and Lower Body Motion Tracking
Sensors 2015, 15(11), 28129-28153; doi:10.3390/s151128129
Received: 28 August 2015 / Revised: 5 October 2015 / Accepted: 2 November 2015 / Published: 6 November 2015
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Abstract
In this paper, we present a method for finding the enhanced heading and position of pedestrians by fusing the Zero velocity UPdaTe (ZUPT)-based pedestrian dead reckoning (PDR) and the kinematic constraints of the lower human body. ZUPT is a well known algorithm for
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In this paper, we present a method for finding the enhanced heading and position of pedestrians by fusing the Zero velocity UPdaTe (ZUPT)-based pedestrian dead reckoning (PDR) and the kinematic constraints of the lower human body. ZUPT is a well known algorithm for PDR, and provides a sufficiently accurate position solution for short term periods, but it cannot guarantee a stable and reliable heading because it suffers from magnetic disturbance in determining heading angles, which degrades the overall position accuracy as time passes. The basic idea of the proposed algorithm is integrating the left and right foot positions obtained by ZUPTs with the heading and position information from an IMU mounted on the waist. To integrate this information, a kinematic model of the lower human body, which is calculated by using orientation sensors mounted on both thighs and calves, is adopted. We note that the position of the left and right feet cannot be apart because of the kinematic constraints of the body, so the kinematic model generates new measurements for the waist position. The Extended Kalman Filter (EKF) on the waist data that estimates and corrects error states uses these measurements and magnetic heading measurements, which enhances the heading accuracy. The updated position information is fed into the foot mounted sensors, and reupdate processes are performed to correct the position error of each foot. The proposed update-reupdate technique consequently ensures improved observability of error states and position accuracy. Moreover, the proposed method provides all the information about the lower human body, so that it can be applied more effectively to motion tracking. The effectiveness of the proposed algorithm is verified via experimental results, which show that a 1.25% Return Position Error (RPE) with respect to walking distance is achieved. Full article
(This article belongs to the Section Physical Sensors)
Open AccessArticle Frequency-Switchable Metamaterial Absorber Injecting Eutectic Gallium-Indium (EGaIn) Liquid Metal Alloy
Sensors 2015, 15(11), 28154-28165; doi:10.3390/s151128154
Received: 24 September 2015 / Revised: 28 October 2015 / Accepted: 4 November 2015 / Published: 6 November 2015
Cited by 10 | PDF Full-text (930 KB) | HTML Full-text | XML Full-text
Abstract
In this study, we demonstrated a new class of frequency-switchable metamaterial absorber in the X-band. Eutectic gallium-indium (EGaIn), a liquid metal alloy, was injected in a microfluidic channel engraved on polymethyl methacrylate (PMMA) to achieve frequency switching. Numerical simulation and experimental results are
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In this study, we demonstrated a new class of frequency-switchable metamaterial absorber in the X-band. Eutectic gallium-indium (EGaIn), a liquid metal alloy, was injected in a microfluidic channel engraved on polymethyl methacrylate (PMMA) to achieve frequency switching. Numerical simulation and experimental results are presented for two cases: when the microfluidic channels are empty, and when they are filled with liquid metal. To evaluate the performance of the fabricated absorber prototype, it is tested with a rectangular waveguide. The resonant frequency was successfully switched from 10.96 GHz to 10.61 GHz after injecting liquid metal while maintaining absorptivity higher than 98%. Full article
(This article belongs to the Section Physical Sensors)
Open AccessArticle The Synthesis and Anion Recognition Property of Symmetrical Chemosensors Involving Thiourea Groups: Theory and Experiments
Sensors 2015, 15(11), 28166-28176; doi:10.3390/s151128166
Received: 15 October 2015 / Revised: 30 October 2015 / Accepted: 30 October 2015 / Published: 6 November 2015
Cited by 1 | PDF Full-text (1345 KB) | HTML Full-text | XML Full-text
Abstract
The synthesis of four symmetrical compounds containing urea/thiourea and anthracene/nitrobenzene groups was optimized. N,N’-Di((anthracen-9-yl)-methylene) thio-carbonohydrazide showed sensitive and selective binding ability for acetate ion among the studied anions. The presence of other competitive anions including F, H2PO4
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The synthesis of four symmetrical compounds containing urea/thiourea and anthracene/nitrobenzene groups was optimized. N,N’-Di((anthracen-9-yl)-methylene) thio-carbonohydrazide showed sensitive and selective binding ability for acetate ion among the studied anions. The presence of other competitive anions including F, H2PO4, Cl, Br and I did not interfere with the strong binding ability. The mechanism of the host-guest interaction was through multiple hydrogen bonds due to the conformational complementarity and higher basicity. A theoretical investigation explained that intra-molecular hydrogen bonds existed in the compound which could strengthen the anion binding ability. In addition, molecular frontier orbitals in molecular interplay were introduced in order to explain the red-shift phenomenon in the host-guest interaction process. Compounds based on thiourea and anthracene derivatives can thus be used as a chemosensor for detecting acetate ion in environmental and pharmaceutical samples. Full article
(This article belongs to the Section Chemical Sensors)
Open AccessArticle PMHT Approach for Multi-Target Multi-Sensor Sonar Tracking in Clutter
Sensors 2015, 15(11), 28177-28192; doi:10.3390/s151128177
Received: 26 August 2015 / Revised: 18 October 2015 / Accepted: 2 November 2015 / Published: 6 November 2015
Cited by 2 | PDF Full-text (1352 KB) | HTML Full-text | XML Full-text
Abstract
Multi-sensor sonar tracking has many advantages, such as the potential to reduce the overall measurement uncertainty and the possibility to hide the receiver. However, the use of multi-target multi-sensor sonar tracking is challenging because of the complexity of the underwater environment, especially the
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Multi-sensor sonar tracking has many advantages, such as the potential to reduce the overall measurement uncertainty and the possibility to hide the receiver. However, the use of multi-target multi-sensor sonar tracking is challenging because of the complexity of the underwater environment, especially the low target detection probability and extremely large number of false alarms caused by reverberation. In this work, to solve the problem of multi-target multi-sensor sonar tracking in the presence of clutter, a novel probabilistic multi-hypothesis tracker (PMHT) approach based on the extended Kalman filter (EKF) and unscented Kalman filter (UKF) is proposed. The PMHT can efficiently handle the unknown measurements-to-targets and measurements-to-transmitters data association ambiguity. The EKF and UKF are used to deal with the high degree of nonlinearity in the measurement model. The simulation results show that the proposed algorithm can improve the target tracking performance in a cluttered environment greatly, and its computational load is low. Full article
(This article belongs to the Section Physical Sensors)
Open AccessArticle Optimizing the Reliability and Performance of Service Composition Applications with Fault Tolerance in Wireless Sensor Networks
Sensors 2015, 15(11), 28193-28223; doi:10.3390/s151128193
Received: 22 September 2015 / Revised: 18 October 2015 / Accepted: 2 November 2015 / Published: 6 November 2015
Cited by 2 | PDF Full-text (11054 KB) | HTML Full-text | XML Full-text
Abstract
The services composition technology provides flexible methods for building service composition applications (SCAs) in wireless sensor networks (WSNs). The high reliability and high performance of SCAs help services composition technology promote the practical application of WSNs. The optimization methods for reliability and performance
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The services composition technology provides flexible methods for building service composition applications (SCAs) in wireless sensor networks (WSNs). The high reliability and high performance of SCAs help services composition technology promote the practical application of WSNs. The optimization methods for reliability and performance used for traditional software systems are mostly based on the instantiations of software components, which are inapplicable and inefficient in the ever-changing SCAs in WSNs. In this paper, we consider the SCAs with fault tolerance in WSNs. Based on a Universal Generating Function (UGF) we propose a reliability and performance model of SCAs in WSNs, which generalizes a redundancy optimization problem to a multi-state system. Based on this model, an efficient optimization algorithm for reliability and performance of SCAs in WSNs is developed based on a Genetic Algorithm (GA) to find the optimal structure of SCAs with fault-tolerance in WSNs. In order to examine the feasibility of our algorithm, we have evaluated the performance. Furthermore, the interrelationships between the reliability, performance and cost are investigated. In addition, a distinct approach to determine the most suitable parameters in the suggested algorithm is proposed. Full article
(This article belongs to the Special Issue Mobile Sensor Computing: Theory and Applications)
Open AccessArticle A Dynamic Range Enhanced Readout Technique with a Two-Step TDC for High Speed Linear CMOS Image Sensors
Sensors 2015, 15(11), 28224-28243; doi:10.3390/s151128224
Received: 31 August 2015 / Revised: 22 October 2015 / Accepted: 2 November 2015 / Published: 6 November 2015
PDF Full-text (3796 KB) | HTML Full-text | XML Full-text
Abstract
This paper presents a dynamic range (DR) enhanced readout technique with a two-step time-to-digital converter (TDC) for high speed linear CMOS image sensors. A multi-capacitor and self-regulated capacitive trans-impedance amplifier (CTIA) structure is employed to extend the dynamic range. The gain of the
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This paper presents a dynamic range (DR) enhanced readout technique with a two-step time-to-digital converter (TDC) for high speed linear CMOS image sensors. A multi-capacitor and self-regulated capacitive trans-impedance amplifier (CTIA) structure is employed to extend the dynamic range. The gain of the CTIA is auto adjusted by switching different capacitors to the integration node asynchronously according to the output voltage. A column-parallel ADC based on a two-step TDC is utilized to improve the conversion rate. The conversion is divided into coarse phase and fine phase. An error calibration scheme is also proposed to correct quantization errors caused by propagation delay skew within −Tclk~+Tclk. A linear CMOS image sensor pixel array is designed in the 0.13 μm CMOS process to verify this DR-enhanced high speed readout technique. The post simulation results indicate that the dynamic range of readout circuit is 99.02 dB and the ADC achieves 60.22 dB SNDR and 9.71 bit ENOB at a conversion rate of 2 MS/s after calibration, with 14.04 dB and 2.4 bit improvement, compared with SNDR and ENOB of that without calibration. Full article
(This article belongs to the Section Physical Sensors)
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Open AccessArticle A Graphene-Based Biosensing Platform Based on Regulated Release of an Aptameric DNA Biosensor
Sensors 2015, 15(11), 28244-28256; doi:10.3390/s151128244
Received: 12 September 2015 / Revised: 31 October 2015 / Accepted: 4 November 2015 / Published: 9 November 2015
Cited by 4 | PDF Full-text (406 KB) | HTML Full-text | XML Full-text | Supplementary Files
Abstract
A novel biosensing platform was developed by integrating an aptamer-based DNA biosensor with graphene oxide (GO) for rapid and facile detection of adenosine triphosphate (ATP, as a model target). The DNA biosensor, which is locked by GO, is designed to contain two sensing
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A novel biosensing platform was developed by integrating an aptamer-based DNA biosensor with graphene oxide (GO) for rapid and facile detection of adenosine triphosphate (ATP, as a model target). The DNA biosensor, which is locked by GO, is designed to contain two sensing modules that include recognition site for ATP and self-replication track that yields the nicking domain for Nt.BbvCI. By taking advantage of the different binding affinity of single-stranded DNA, double-stranded DNA and aptamer-target complex toward GO, the DNA biosensor could be efficiently released from GO in the presence of target with the help of a complementary DNA strand (CPDNA) that partially hybridizes to the DNA biosensor. Then, the polymerization/nicking enzyme synergetic isothermal amplification could be triggered, leading to the synthesis of massive DNA amplicons, thus achieving an enhanced sensitivity with a wide linear dynamic response range of four orders of magnitude and good selectivity. This biosensing strategy expands the applications of GO-DNA nanobiointerfaces in biological sensing, showing great potential in fundamental research and biomedical diagnosis. Full article
(This article belongs to the Section Biosensors)
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Open AccessArticle The Mine Locomotive Wireless Network Strategy Based on Successive Interference Cancellation
Sensors 2015, 15(11), 28257-28270; doi:10.3390/s151128257
Received: 8 September 2015 / Revised: 24 October 2015 / Accepted: 4 November 2015 / Published: 9 November 2015
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Abstract
We consider a wireless network strategy based on successive interference cancellation (SIC) for mine locomotives. We firstly build the original mathematical model for the strategy which is a non-convex model. Then, we examine this model intensively, and figure out that there are certain
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We consider a wireless network strategy based on successive interference cancellation (SIC) for mine locomotives. We firstly build the original mathematical model for the strategy which is a non-convex model. Then, we examine this model intensively, and figure out that there are certain regulations embedded in it. Based on these findings, we are able to reformulate the model into a new form and design a simple algorithm which can assign each locomotive with a proper transmitting scheme during the whole schedule procedure. Simulation results show that the outcomes obtained through this algorithm are improved by around 50% compared with those that do not apply the SIC technique. Full article
(This article belongs to the Section Sensor Networks)
Open AccessArticle Real-Valued Covariance Vector Sparsity-Inducing DOA Estimation for Monostatic MIMO Radar
Sensors 2015, 15(11), 28271-28286; doi:10.3390/s151128271
Received: 21 July 2015 / Revised: 22 September 2015 / Accepted: 3 November 2015 / Published: 10 November 2015
Cited by 10 | PDF Full-text (310 KB) | HTML Full-text | XML Full-text
Abstract
In this paper, a real-valued covariance vector sparsity-inducing method for direction of arrival (DOA) estimation is proposed in monostatic multiple-input multiple-output (MIMO) radar. Exploiting the special configuration of monostatic MIMO radar, low-dimensional real-valued received data can be obtained by using the reduced-dimensional transformation
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In this paper, a real-valued covariance vector sparsity-inducing method for direction of arrival (DOA) estimation is proposed in monostatic multiple-input multiple-output (MIMO) radar. Exploiting the special configuration of monostatic MIMO radar, low-dimensional real-valued received data can be obtained by using the reduced-dimensional transformation and unitary transformation technique. Then, based on the Khatri–Rao product, a real-valued sparse representation framework of the covariance vector is formulated to estimate DOA. Compared to the existing sparsity-inducing DOA estimation methods, the proposed method provides better angle estimation performance and lower computational complexity. Simulation results verify the effectiveness and advantage of the proposed method. Full article
(This article belongs to the Section Physical Sensors)
Open AccessArticle Prototyping a GNSS-Based Passive Radar for UAVs: An Instrument to Classify the Water Content Feature of Lands
Sensors 2015, 15(11), 28287-28313; doi:10.3390/s151128287
Received: 10 July 2015 / Revised: 30 October 2015 / Accepted: 2 November 2015 / Published: 10 November 2015
Cited by 3 | PDF Full-text (6415 KB) | HTML Full-text | XML Full-text
Abstract
Global Navigation Satellite Systems (GNSS) broadcast signals for positioning and navigation, which can be also employed for remote sensing applications. Indeed, the satellites of any GNSS can be seen as synchronized sources of electromagnetic radiation, and specific processing of the signals reflected back
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Global Navigation Satellite Systems (GNSS) broadcast signals for positioning and navigation, which can be also employed for remote sensing applications. Indeed, the satellites of any GNSS can be seen as synchronized sources of electromagnetic radiation, and specific processing of the signals reflected back from the ground can be used to estimate the geophysical properties of the Earth’s surface. Several experiments have successfully demonstrated GNSS-reflectometry (GNSS-R), whereas new applications are continuously emerging and are presently under development, either from static or dynamic platforms. GNSS-R can be implemented at a low cost, primarily if small devices are mounted on-board unmanned aerial vehicles (UAVs), which today can be equipped with several types of sensors for environmental monitoring. So far, many instruments for GNSS-R have followed the GNSS bistatic radar architecture and consisted of custom GNSS receivers, often requiring a personal computer and bulky systems to store large amounts of data. This paper presents the development of a GNSS-based sensor for UAVs and small manned aircraft, used to classify lands according to their soil water content. The paper provides details on the design of the major hardware and software components, as well as the description of the results obtained through field tests. Full article
(This article belongs to the Special Issue UAV Sensors for Environmental Monitoring)
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Open AccessArticle The Node Deployment of Intelligent Sensor Networks Based on the Spatial Difference of Farmland Soil
Sensors 2015, 15(11), 28314-28339; doi:10.3390/s151128314
Received: 21 August 2015 / Revised: 20 October 2015 / Accepted: 4 November 2015 / Published: 11 November 2015
Cited by 3 | PDF Full-text (2768 KB) | HTML Full-text | XML Full-text
Abstract
Considering that agricultural production is characterized by vast areas, scattered fields and long crop growth cycles, intelligent wireless sensor networks (WSNs) are suitable for monitoring crop growth information. Cost and coverage are the most key indexes for WSN applications. The differences in crop
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Considering that agricultural production is characterized by vast areas, scattered fields and long crop growth cycles, intelligent wireless sensor networks (WSNs) are suitable for monitoring crop growth information. Cost and coverage are the most key indexes for WSN applications. The differences in crop conditions are influenced by the spatial distribution of soil nutrients. If the nutrients are distributed evenly, the crop conditions are expected to be approximately uniform with little difference; on the contrary, there will be great differences in crop conditions. In accordance with the differences in the spatial distribution of soil information in farmland, fuzzy c-means clustering was applied to divide the farmland into several areas, where the soil fertility of each area is nearly uniform. Then the crop growth information in the area could be monitored with complete coverage by deploying a sensor node there, which could greatly decrease the deployed sensor nodes. Moreover, in order to accurately judge the optimal cluster number of fuzzy c-means clustering, a discriminant function for Normalized Intra-Cluster Coefficient of Variation (NICCV) was established. The sensitivity analysis indicates that NICCV is insensitive to the fuzzy weighting exponent, but it shows a strong sensitivity to the number of clusters. Full article
(This article belongs to the Section Sensor Networks)
Open AccessArticle Analysis of the Sensitivity of K-Type Molecular Sieve-Deposited MWNTs for the Detection of SF6 Decomposition Gases under Partial Discharge
Sensors 2015, 15(11), 28367-28384; doi:10.3390/s151128367
Received: 4 August 2015 / Revised: 4 November 2015 / Accepted: 5 November 2015 / Published: 11 November 2015
Cited by 1 | PDF Full-text (1368 KB) | HTML Full-text | XML Full-text
Abstract
Sulfur hexafluoride (SF6) is widely utilized in gas-insulated switchgear (GIS). However, part of SF6 decomposes into different components under partial discharge (PD) conditions. Previous research has shown that the gas responses of intrinsic and 4 Å-type molecular sieve-deposited multi-wall carbon nanotubes (MWNTs) to
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Sulfur hexafluoride (SF6) is widely utilized in gas-insulated switchgear (GIS). However, part of SF6 decomposes into different components under partial discharge (PD) conditions. Previous research has shown that the gas responses of intrinsic and 4 Å-type molecular sieve-deposited multi-wall carbon nanotubes (MWNTs) to SOF2 and SO2F2, two important decomposition components of SF6, are not obvious. In this study, a K-type molecular sieve-deposited MWNTs sensor was developed. Its gas response characteristics and the influence of the mixture ratios of gases on the gas-sensing properties were studied. The results showed that, for sensors with gas mixture ratios of 5:1, 10:1, and 20:1, the resistance change rate increased by nearly 13.0% after SOF2 adsorption, almost 10 times that of MWNTs sensors, while the sensors’ resistance change rate with a mixture ratio of 10:1 reached 17.3% after SO2F2 adsorption, nearly nine times that of intrinsic MWNT sensors. Besides, a good linear relationship was observed between concentration of decomposition components and the resistance change rate of sensors. Full article
(This article belongs to the Section Physical Sensors)
Open AccessArticle Application of Novel Lateral Tire Force Sensors to Vehicle Parameter Estimation of Electric Vehicles
Sensors 2015, 15(11), 28385-28401; doi:10.3390/s151128385
Received: 21 September 2015 / Revised: 27 October 2015 / Accepted: 30 October 2015 / Published: 11 November 2015
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Abstract
This article presents methods for estimating lateral vehicle velocity and tire cornering stiffness, which are key parameters in vehicle dynamics control, using lateral tire force measurements. Lateral tire forces acting on each tire are directly measured by load-sensing hub bearings that were invented
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This article presents methods for estimating lateral vehicle velocity and tire cornering stiffness, which are key parameters in vehicle dynamics control, using lateral tire force measurements. Lateral tire forces acting on each tire are directly measured by load-sensing hub bearings that were invented and further developed by NSK Ltd. For estimating the lateral vehicle velocity, tire force models considering lateral load transfer effects are used, and a recursive least square algorithm is adapted to identify the lateral vehicle velocity as an unknown parameter. Using the estimated lateral vehicle velocity, tire cornering stiffness, which is an important tire parameter dominating the vehicle’s cornering responses, is estimated. For the practical implementation, the cornering stiffness estimation algorithm based on a simple bicycle model is developed and discussed. Finally, proposed estimation algorithms were evaluated using experimental test data. Full article
(This article belongs to the Special Issue Sensors in New Road Vehicles)
Open AccessArticle Optimization Algorithm for Kalman Filter Exploiting the Numerical Characteristics of SINS/GPS Integrated Navigation Systems
Sensors 2015, 15(11), 28402-28420; doi:10.3390/s151128402
Received: 26 August 2015 / Revised: 21 October 2015 / Accepted: 3 November 2015 / Published: 11 November 2015
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Abstract
Aiming at addressing the problem of high computational cost of the traditional Kalman filter in SINS/GPS, a practical optimization algorithm with offline-derivation and parallel processing methods based on the numerical characteristics of the system is presented in this paper. The algorithm exploits the
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Aiming at addressing the problem of high computational cost of the traditional Kalman filter in SINS/GPS, a practical optimization algorithm with offline-derivation and parallel processing methods based on the numerical characteristics of the system is presented in this paper. The algorithm exploits the sparseness and/or symmetry of matrices to simplify the computational procedure. Thus plenty of invalid operations can be avoided by offline derivation using a block matrix technique. For enhanced efficiency, a new parallel computational mechanism is established by subdividing and restructuring calculation processes after analyzing the extracted “useful” data. As a result, the algorithm saves about 90% of the CPU processing time and 66% of the memory usage needed in a classical Kalman filter. Meanwhile, the method as a numerical approach needs no precise-loss transformation/approximation of system modules and the accuracy suffers little in comparison with the filter before computational optimization. Furthermore, since no complicated matrix theories are needed, the algorithm can be easily transplanted into other modified filters as a secondary optimization method to achieve further efficiency. Full article
(This article belongs to the Section Remote Sensors)
Open AccessArticle An Electrochemical NO2 Sensor Based on Ionic Liquid: Influence of the Morphology of the Polymer Electrolyte on Sensor Sensitivity
Sensors 2015, 15(11), 28421-28434; doi:10.3390/s151128421
Received: 29 September 2015 / Revised: 31 October 2015 / Accepted: 4 November 2015 / Published: 11 November 2015
Cited by 7 | PDF Full-text (2149 KB) | HTML Full-text | XML Full-text
Abstract
A systematic study was carried out to investigate the effect of ionic liquid in solid polymer electrolyte (SPE) and its layer morphology on the characteristics of an electrochemical amperometric nitrogen dioxide sensor. Five different ionic liquids were immobilized into a solid polymer electrolyte
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A systematic study was carried out to investigate the effect of ionic liquid in solid polymer electrolyte (SPE) and its layer morphology on the characteristics of an electrochemical amperometric nitrogen dioxide sensor. Five different ionic liquids were immobilized into a solid polymer electrolyte and key sensor parameters (sensitivity, response/recovery times, hysteresis and limit of detection) were characterized. The study revealed that the sensor based on 1-ethyl-3-methylimidazolium bis(trifluoromethylsulfonyl)imide ([EMIM][N(Tf)2]) showed the best sensitivity, fast response/recovery times, and low sensor response hysteresis. The working electrode, deposited from water-based carbon nanotube ink, was prepared by aerosol-jet printing technology. It was observed that the thermal treatment and crystallinity of poly(vinylidene fluoride) (PVDF) in the solid polymer electrolyte influenced the sensitivity. Picture analysis of the morphology of the SPE layer based on [EMIM][N(Tf)2] ionic liquid treated under different conditions suggests that the sensor sensitivity strongly depends on the fractal dimension of PVDF spherical objects in SPE. Their deformation, e.g., due to crowding, leads to a decrease in sensor sensitivity. Full article
(This article belongs to the Special Issue Ionic Liquids)
Open AccessArticle Wearable Goniometer and Accelerometer Sensory Fusion for Knee Joint Angle Measurement in Daily Life
Sensors 2015, 15(11), 28435-28455; doi:10.3390/s151128435
Received: 11 September 2015 / Revised: 30 October 2015 / Accepted: 5 November 2015 / Published: 11 November 2015
Cited by 8 | PDF Full-text (2229 KB) | HTML Full-text | XML Full-text
Abstract
Human motion analysis is crucial for a wide range of applications and disciplines. The development and validation of low cost and unobtrusive sensing systems for ambulatory motion detection is still an open issue. Inertial measurement systems and e-textile sensors are emerging as potential
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Human motion analysis is crucial for a wide range of applications and disciplines. The development and validation of low cost and unobtrusive sensing systems for ambulatory motion detection is still an open issue. Inertial measurement systems and e-textile sensors are emerging as potential technologies for daily life situations. We developed and conducted a preliminary evaluation of an innovative sensing concept that combines e-textiles and tri-axial accelerometers for ambulatory human motion analysis. Our sensory fusion method is based on a Kalman filter technique and combines the outputs of textile electrogoniometers and accelerometers without making any assumptions regarding the initial accelerometer position and orientation. We used our technique to measure the flexion-extension angle of the knee in different motion tasks (monopodalic flexions and walking at different velocities). The estimation technique was benchmarked against a commercial measurement system based on inertial measurement units and performed reliably for all of the various tasks (mean and standard deviation of the root mean square error of 1:96 and 0:96, respectively). In addition, the method showed a notable improvement in angular estimation compared to the estimation derived by the textile goniometer and accelerometer considered separately. In future work, we will extend this method to more complex and multi-degree of freedom joints. Full article
(This article belongs to the Special Issue Sensor Systems for Motion Capture and Interpretation)
Open AccessArticle In Vivo Pattern Classification of Ingestive Behavior in Ruminants Using FBG Sensors and Machine Learning
Sensors 2015, 15(11), 28456-28471; doi:10.3390/s151128456
Received: 10 August 2015 / Revised: 20 October 2015 / Accepted: 30 October 2015 / Published: 11 November 2015
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Abstract
Pattern classification of ingestive behavior in grazing animals has extreme importance in studies related to animal nutrition, growth and health. In this paper, a system to classify chewing patterns of ruminants in in vivo experiments is developed. The proposal is based on data
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Pattern classification of ingestive behavior in grazing animals has extreme importance in studies related to animal nutrition, growth and health. In this paper, a system to classify chewing patterns of ruminants in in vivo experiments is developed. The proposal is based on data collected by optical fiber Bragg grating sensors (FBG) that are processed by machine learning techniques. The FBG sensors measure the biomechanical strain during jaw movements, and a decision tree is responsible for the classification of the associated chewing pattern. In this study, patterns associated with food intake of dietary supplement, hay and ryegrass were considered. Additionally, two other important events for ingestive behavior were monitored: rumination and idleness. Experimental results show that the proposed approach for pattern classification is capable of differentiating the five patterns involved in the chewing process with an overall accuracy of 94%. Full article
(This article belongs to the Section Physical Sensors)
Open AccessArticle Flight Test Result for the Ground-Based Radio Navigation System Sensor with an Unmanned Air Vehicle
Sensors 2015, 15(11), 28472-28489; doi:10.3390/s151128472
Received: 16 September 2015 / Revised: 26 October 2015 / Accepted: 2 November 2015 / Published: 11 November 2015
Cited by 2 | PDF Full-text (2412 KB) | HTML Full-text | XML Full-text
Abstract
The Ground-based Radio Navigation System (GRNS) is an alternative/backup navigation system based on time synchronized pseudolites. It has been studied for some years due to the potential vulnerability issue of satellite navigation systems (e.g., GPS or Galileo). In the framework of our study,
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The Ground-based Radio Navigation System (GRNS) is an alternative/backup navigation system based on time synchronized pseudolites. It has been studied for some years due to the potential vulnerability issue of satellite navigation systems (e.g., GPS or Galileo). In the framework of our study, a periodic pulsed sequence was used instead of the randomized pulse sequence recommended as the RTCM (radio technical commission for maritime services) SC (special committee)-104 pseudolite signal, as a randomized pulse sequence with a long dwell time is not suitable for applications requiring high dynamics. This paper introduces a mathematical model of the post-correlation output in a navigation sensor, showing that the aliasing caused by the additional frequency term of a periodic pulsed signal leads to a false lock (i.e., Doppler frequency bias) during the signal acquisition process or in the carrier tracking loop of the navigation sensor. We suggest algorithms to resolve the frequency false lock issue in this paper, relying on the use of a multi-correlator. A flight test with an unmanned helicopter was conducted to verify the implemented navigation sensor. The results of this analysis show that there were no false locks during the flight test and that outliers stem from bad dilution of precision (DOP) or fluctuations in the received signal quality. Full article
(This article belongs to the Special Issue UAV Sensors for Environmental Monitoring)
Open AccessArticle Performance Evaluation of a Multichannel All-In-One Phantom Dosimeter for Dose Measurement of Diagnostic X-ray Beam
Sensors 2015, 15(11), 28490-28501; doi:10.3390/s151128490
Received: 17 September 2015 / Revised: 26 October 2015 / Accepted: 5 November 2015 / Published: 11 November 2015
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Abstract
We developed a multichannel all-in-one phantom dosimeter system composed of nine sensing probes, a chest phantom, an image intensifier, and a complementary metal-oxide semiconductor (CMOS) image sensor to measure the dose distribution of an X-ray beam used in radiation diagnosis. Nine sensing probes
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We developed a multichannel all-in-one phantom dosimeter system composed of nine sensing probes, a chest phantom, an image intensifier, and a complementary metal-oxide semiconductor (CMOS) image sensor to measure the dose distribution of an X-ray beam used in radiation diagnosis. Nine sensing probes of the phantom dosimeter were fabricated identically by connecting a plastic scintillating fiber (PSF) to a plastic optical fiber (POF). To measure the planar dose distribution on a chest phantom according to exposure parameters used in clinical practice, we divided the top of the chest phantom into nine equal parts virtually and then installed the nine sensing probes at each center of the nine equal parts on the top of the chest phantom as measuring points. Each scintillation signal generated in the nine sensing probes was transmitted through the POFs and then intensified by the image intensifier because the scintillation signal normally has a very low light intensity. Real-time scintillation images (RSIs) containing the intensified scintillation signals were taken by the CMOS image sensor with a single lens optical system and displayed through a software program. Under variation of the exposure parameters, we measured RSIs containing dose information using the multichannel all-in-one phantom dosimeter and compared the results with the absorbed doses obtained by using a semiconductor dosimeter (SCD). From the experimental results of this study, the light intensities of nine regions of interest (ROI) in the RSI measured by the phantom dosimeter were similar to the dose distribution obtained using the SCD. In conclusion, we demonstrated that the planar dose distribution including the entrance surface dose (ESD) can be easily measured by using the proposed phantom dosimeter system. Full article
(This article belongs to the Section Physical Sensors)
Open AccessArticle Acetone Sensing Properties of a Gas Sensor Composed of Carbon Nanotubes Doped With Iron Oxide Nanopowder
Sensors 2015, 15(11), 28502-28512; doi:10.3390/s151128502
Received: 14 September 2015 / Revised: 26 October 2015 / Accepted: 29 October 2015 / Published: 11 November 2015
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Abstract
Iron oxide (Fe2O3) nanopowder was prepared by a precipitation method and then mixed with different proportions of carbon nanotubes. The composite materials were characterized by X-ray powder diffraction, Fourier transform infrared spectroscopy and scanning electron microscopy. A fabricated heater-type
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Iron oxide (Fe2O3) nanopowder was prepared by a precipitation method and then mixed with different proportions of carbon nanotubes. The composite materials were characterized by X-ray powder diffraction, Fourier transform infrared spectroscopy and scanning electron microscopy. A fabricated heater-type gas sensor was compared with a pure Fe2O3 gas sensor under the influence of acetone. The effects of the amount of doping, the sintering temperature, and the operating temperature on the response of the sensor and the response recovery time were analyzed. Experiments show that doping of carbon nanotubes with iron oxide effectively improves the response of the resulting gas sensors to acetone gas. It also reduces the operating temperature and shortens the response recovery time of the sensor. The response of the sensor in an acetone gas concentration of 80 ppm was enhanced, with good repeatability. Full article
(This article belongs to the Section Chemical Sensors)
Open AccessArticle Maximizing Information Diffusion in the Cyber-physical Integrated Network
Sensors 2015, 15(11), 28513-28530; doi:10.3390/s151128513
Received: 25 September 2015 / Revised: 31 October 2015 / Accepted: 3 November 2015 / Published: 11 November 2015
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Abstract
Nowadays, our living environment has been embedded with smart objects, such as smart sensors, smart watches and smart phones. They make cyberspace and physical space integrated by their abundant abilities of sensing, communication and computation, forming a cyber-physical integrated network. In order to
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Nowadays, our living environment has been embedded with smart objects, such as smart sensors, smart watches and smart phones. They make cyberspace and physical space integrated by their abundant abilities of sensing, communication and computation, forming a cyber-physical integrated network. In order to maximize information diffusion in such a network, a group of objects are selected as the forwarding points. To optimize the selection, a minimum connected dominating set (CDS) strategy is adopted. However, existing approaches focus on minimizing the size of the CDS, neglecting an important factor: the weight of links. In this paper, we propose a distributed maximizing the probability of information diffusion (DMPID) algorithm in the cyber-physical integrated network. Unlike previous approaches that only consider the size of CDS selection, DMPID also considers the information spread probability that depends on the weight of links. To weaken the effects of excessively-weighted links, we also present an optimization strategy that can properly balance the two factors. The results of extensive simulation show that DMPID can nearly double the information diffusion probability, while keeping a reasonable size of selection with low overhead in different distributed networks. Full article
(This article belongs to the Section Sensor Networks)
Open AccessArticle High-Temperature SAW Wireless Strain Sensor with Langasite
Sensors 2015, 15(11), 28531-28542; doi:10.3390/s151128531
Received: 11 October 2015 / Revised: 3 November 2015 / Accepted: 4 November 2015 / Published: 11 November 2015
Cited by 4 | PDF Full-text (1623 KB) | HTML Full-text | XML Full-text
Abstract
Two Surface acoustic wave (SAW) resonators were fabricated on langasite substrates with Euler angle of (0°, 138.5°, 117°) and (0°, 138.5°, 27°). A dipole antenna was bonded to the prepared SAW resonator to form a wireless sensor. The characteristics of the SAW sensors
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Two Surface acoustic wave (SAW) resonators were fabricated on langasite substrates with Euler angle of (0°, 138.5°, 117°) and (0°, 138.5°, 27°). A dipole antenna was bonded to the prepared SAW resonator to form a wireless sensor. The characteristics of the SAW sensors were measured by wireless frequency domain interrogation methods from 20 °C to 600 °C. Different temperature behaviors of the sensors were observed. Strain sensing was achieved using a cantilever configuration. The sensors were measured under applied strain from 20 °C to 500 °C. The shift of the resonance frequency contributed merely by strain is extracted from the combined effects of temperature and strain. Both the strain factors of the two SAW sensors increase with rising ambient temperature, and the SAW sensor deposited on (0°, 138.5°, 117°) cut is more sensitive to applied strain. The measurement errors of the two sensors are also discussed. The relative errors of the two sensors are between 0.63% and 2.09%. Even at 500 °C, the hysteresis errors of the two sensors are less than 5%. Full article
(This article belongs to the Special Issue Sensors for Harsh Environments)
Open AccessArticle Modelling the Size Effects on the Mechanical Properties of Micro/Nano Structures
Sensors 2015, 15(11), 28543-28562; doi:10.3390/s151128543
Received: 7 August 2015 / Revised: 20 October 2015 / Accepted: 26 October 2015 / Published: 11 November 2015
Cited by 3 | PDF Full-text (1044 KB) | HTML Full-text | XML Full-text | Correction
Abstract
Experiments on micro- and nano-mechanical systems (M/NEMS) have shown that their behavior under bending loads departs in many cases from the classical predictions using Euler-Bernoulli theory and Hooke’s law. This anomalous response has usually been seen as a dependence of the material properties
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Experiments on micro- and nano-mechanical systems (M/NEMS) have shown that their behavior under bending loads departs in many cases from the classical predictions using Euler-Bernoulli theory and Hooke’s law. This anomalous response has usually been seen as a dependence of the material properties on the size of the structure, in particular thickness. A theoretical model that allows for quantitative understanding and prediction of this size effect is important for the design of M/NEMS. In this paper, we summarize and analyze the five theories that can be found in the literature: Grain Boundary Theory (GBT), Surface Stress Theory (SST), Residual Stress Theory (RST), Couple Stress Theory (CST) and Surface Elasticity Theory (SET). By comparing these theories with experimental data we propose a simplified model combination of CST and SET that properly fits all considered cases, therefore delivering a simple (two parameters) model that can be used to predict the mechanical properties at the nanoscale. Full article
(This article belongs to the Special Issue Nanomechanics for Sensing and Spectrometry)
Open AccessArticle Reusable EGaIn-Injected Substrate-Integrated-Waveguide Resonator for Wireless Sensor Applications
Sensors 2015, 15(11), 28563-28573; doi:10.3390/s151128563
Received: 27 August 2015 / Revised: 12 October 2015 / Accepted: 9 November 2015 / Published: 11 November 2015
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Abstract
The proposed structure in this research is constructed on substrate integrated waveguide (SIW) technology and has a mechanism that produces 16 different and distinct resonant frequencies between 2.45 and 3.05 GHz by perturbing a fundamental TE10 mode. It is a unique method
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The proposed structure in this research is constructed on substrate integrated waveguide (SIW) technology and has a mechanism that produces 16 different and distinct resonant frequencies between 2.45 and 3.05 GHz by perturbing a fundamental TE10 mode. It is a unique method for producing multiple resonances in a radio frequency planar structure without any extra circuitry or passive elements is developed. The proposed SIW structure has four vertical fluidic holes (channels); injecting eutectic gallium indium (EGaIn), also known commonly as liquid metal (LM), into these vertical channels produces different resonant frequencies. Either a channel is empty, or it is filled with LM. In total, the combination of different frequencies produced from four vertical channels is 16. Full article
(This article belongs to the Section Physical Sensors)
Open AccessArticle Development of an Automatic Identification System Autonomous Positioning System
Sensors 2015, 15(11), 28574-28591; doi:10.3390/s151128574
Received: 28 August 2015 / Accepted: 5 November 2015 / Published: 11 November 2015
Cited by 3 | PDF Full-text (2422 KB) | HTML Full-text | XML Full-text
Abstract
In order to overcome the vulnerability of the global navigation satellite system (GNSS) and provide robust position, navigation and time (PNT) information in marine navigation, the autonomous positioning system based on ranging-mode Automatic Identification System (AIS) is presented in the paper. The principle
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In order to overcome the vulnerability of the global navigation satellite system (GNSS) and provide robust position, navigation and time (PNT) information in marine navigation, the autonomous positioning system based on ranging-mode Automatic Identification System (AIS) is presented in the paper. The principle of the AIS autonomous positioning system (AAPS) is investigated, including the position algorithm, the signal measurement technique, the geometric dilution of precision, the time synchronization technique and the additional secondary factor correction technique. In order to validate the proposed AAPS, a verification system has been established in the Xinghai sea region of Dalian (China). Static and dynamic positioning experiments are performed. The original function of the AIS in the AAPS is not influenced. The experimental results show that the positioning precision of the AAPS is better than 10 m in the area with good geometric dilution of precision (GDOP) by the additional secondary factor correction technology. This is the most economical solution for a land-based positioning system to complement the GNSS for the navigation safety of vessels sailing along coasts. Full article
(This article belongs to the Section Remote Sensors)
Open AccessArticle Performance Analysis of the Ironless Inductive Position Sensor in the Large Hadron Collider Collimators Environment
Sensors 2015, 15(11), 28592-28602; doi:10.3390/s151128592
Received: 31 July 2015 / Revised: 27 October 2015 / Accepted: 9 November 2015 / Published: 11 November 2015
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Abstract
The Ironless Inductive Position Sensor (I2PS) has been introduced as a valid alternative to Linear Variable Differential Transformers (LVDTs) when external magnetic fields are present. Potential applications of this linear position sensor can be found in critical systems such as nuclear plants, tokamaks,
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The Ironless Inductive Position Sensor (I2PS) has been introduced as a valid alternative to Linear Variable Differential Transformers (LVDTs) when external magnetic fields are present. Potential applications of this linear position sensor can be found in critical systems such as nuclear plants, tokamaks, satellites and particle accelerators. This paper analyzes the performance of the I2PS in the harsh environment of the collimators of the Large Hadron Collider (LHC), where position uncertainties of less than 20 µm are demanded in the presence of nuclear radiation and external magnetic fields. The I2PS has been targeted for installation for LHC Run 2, in order to solve the magnetic interference problem which standard LVDTs are experiencing. The paper describes in detail the chain of systems which belong to the new I2PS measurement task, their impact on the sensor performance and their possible further optimization. The I2PS performance is analyzed evaluating the position uncertainty (on 30 s), the magnetic immunity and the long-term stability (on 7 days). These three indicators are assessed from data acquired during the LHC operation in 2015 and compared with those of LVDTs. Full article
(This article belongs to the Special Issue Sensors for Harsh Environments)
Open AccessArticle A Novel Scheme for an Energy Efficient Internet of Things Based on Wireless Sensor Networks
Sensors 2015, 15(11), 28603-28626; doi:10.3390/s151128603
Received: 21 September 2015 / Revised: 29 October 2015 / Accepted: 2 November 2015 / Published: 12 November 2015
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Abstract
One of the emerging networking standards that gap between the physical world and the cyber one is the Internet of Things. In the Internet of Things, smart objects communicate with each other, data are gathered and certain requests of users are satisfied by
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One of the emerging networking standards that gap between the physical world and the cyber one is the Internet of Things. In the Internet of Things, smart objects communicate with each other, data are gathered and certain requests of users are satisfied by different queried data. The development of energy efficient schemes for the IoT is a challenging issue as the IoT becomes more complex due to its large scale the current techniques of wireless sensor networks cannot be applied directly to the IoT. To achieve the green networked IoT, this paper addresses energy efficiency issues by proposing a novel deployment scheme. This scheme, introduces: (1) a hierarchical network design; (2) a model for the energy efficient IoT; (3) a minimum energy consumption transmission algorithm to implement the optimal model. The simulation results show that the new scheme is more energy efficient and flexible than traditional WSN schemes and consequently it can be implemented for efficient communication in the IoT. Full article
(This article belongs to the Special Issue Identification, Information & Knowledge in the Internet of Things)
Open AccessArticle Development of a High Irradiance LED Configuration for Small Field of View Motion Estimation of Fertilizer Particles
Sensors 2015, 15(11), 28627-28645; doi:10.3390/s151128627
Received: 27 July 2015 / Revised: 5 November 2015 / Accepted: 6 November 2015 / Published: 12 November 2015
Cited by 3 | PDF Full-text (635 KB) | HTML Full-text | XML Full-text
Abstract
Better characterization of the fertilizer spreading process, especially the fertilizer pattern distribution on the ground, requires an accurate measurement of individual particle properties and dynamics. Both 2D and 3D high speed imaging techniques have been developed for this purpose. To maximize the accuracy
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Better characterization of the fertilizer spreading process, especially the fertilizer pattern distribution on the ground, requires an accurate measurement of individual particle properties and dynamics. Both 2D and 3D high speed imaging techniques have been developed for this purpose. To maximize the accuracy of the predictions, a specific illumination level is required. This paper describes the development of a high irradiance LED system for high speed motion estimation of fertilizer particles. A spectral sensitivity factor was used to select the optimal LED in relation to the used camera from a range of commercially available high power LEDs. A multiple objective genetic algorithm was used to find the optimal configuration of LEDs resulting in the most homogeneous irradiance in the target area. Simulations were carried out for different lenses and number of LEDs. The chosen configuration resulted in an average irradiance level of 452 W/m2 with coefficient of variation less than 2%. The algorithm proved superior and more flexible to other approaches reported in the literature and can be used for various other applications. Full article
(This article belongs to the Section Physical Sensors)
Open AccessArticle HAGR-D: A Novel Approach for Gesture Recognition with Depth Maps
Sensors 2015, 15(11), 28646-28664; doi:10.3390/s151128646
Received: 3 August 2015 / Revised: 28 September 2015 / Accepted: 13 October 2015 / Published: 12 November 2015
Cited by 5 | PDF Full-text (675 KB) | HTML Full-text | XML Full-text
Abstract
The hand is an important part of the body used to express information through gestures, and its movements can be used in dynamic gesture recognition systems based on computer vision with practical applications, such as medical, games and sign language. Although depth sensors
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The hand is an important part of the body used to express information through gestures, and its movements can be used in dynamic gesture recognition systems based on computer vision with practical applications, such as medical, games and sign language. Although depth sensors have led to great progress in gesture recognition, hand gesture recognition still is an open problem because of its complexity, which is due to the large number of small articulations in a hand. This paper proposes a novel approach for hand gesture recognition with depth maps generated by the Microsoft Kinect Sensor (Microsoft, Redmond, WA, USA) using a variation of the CIPBR (convex invariant position based on RANSAC) algorithm and a hybrid classifier composed of dynamic time warping (DTW) and Hidden Markov models (HMM), called the hybrid approach for gesture recognition with depth maps (HAGR-D). The experiments show that the proposed model overcomes other algorithms presented in the literature in hand gesture recognition tasks, achieving a classification rate of 97.49% in the MSRGesture3D dataset and 98.43% in the RPPDI dynamic gesture dataset. Full article
(This article belongs to the Section Physical Sensors)
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Open AccessArticle Using a Novel Wireless-Networked Decentralized Control Scheme under Unpredictable Environmental Conditions
Sensors 2015, 15(11), 28690-28716; doi:10.3390/s151128690
Received: 22 September 2015 / Revised: 29 October 2015 / Accepted: 6 November 2015 / Published: 12 November 2015
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Abstract
The direction of sunshine or the installation sites of environmental control facilities in the greenhouse result in different temperature and humidity levels in the various zones of the greenhouse, and thus, the production quality of crop is inconsistent. This study proposed a wireless-networked
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The direction of sunshine or the installation sites of environmental control facilities in the greenhouse result in different temperature and humidity levels in the various zones of the greenhouse, and thus, the production quality of crop is inconsistent. This study proposed a wireless-networked decentralized fuzzy control scheme to regulate the environmental parameters of various culture zones within a greenhouse. The proposed scheme can create different environmental conditions for cultivating different crops in various zones and achieve diversification or standardization of crop production. A star-type wireless sensor network is utilized to communicate with each sensing node, actuator node, and control node in various zones within the greenhouse. The fuzzy rule-based inference system is used to regulate the environmental parameters for temperature and humidity based on real-time data of plant growth response provided by a growth stage selector. The growth stage selector defines the control ranges of temperature and humidity of the various culture zones according to the leaf area of the plant, the number of leaves, and the cumulative amount of light. The experimental results show that the proposed scheme is stable and robust and provides basis for future greenhouse applications. Full article
(This article belongs to the Section Sensor Networks)
Open AccessArticle First Results of Field Absolute Calibration of the GPS Receiver Antenna at Wuhan University
Sensors 2015, 15(11), 28717-28731; doi:10.3390/s151128717
Received: 23 June 2015 / Revised: 5 October 2015 / Accepted: 7 November 2015 / Published: 13 November 2015
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Abstract
GNSS receiver antenna phase center variations (PCVs), which arise from the non-spherical phase response of GNSS signals have to be well corrected for high-precision GNSS applications. Without using a precise antenna phase center correction (PCC) model, the estimated position of a station monument
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GNSS receiver antenna phase center variations (PCVs), which arise from the non-spherical phase response of GNSS signals have to be well corrected for high-precision GNSS applications. Without using a precise antenna phase center correction (PCC) model, the estimated position of a station monument will lead to a bias of up to several centimeters. The Chinese large-scale research project “Crustal Movement Observation Network of China” (CMONOC), which requires high-precision positions in a comprehensive GPS observational network motived establishment of a set of absolute field calibrations of the GPS receiver antenna located at Wuhan University. In this paper the calibration facilities are firstly introduced and then the multipath elimination and PCV estimation strategies currently used are elaborated. The validation of estimated PCV values of test antenna are finally conducted, compared with the International GNSS Service (IGS) type values. Examples of TRM57971.00 NONE antenna calibrations from our calibration facility demonstrate that the derived PCVs and IGS type mean values agree at the 1 mm level. Full article
(This article belongs to the Section Remote Sensors)
Open AccessArticle Development of a Carbon Nanotube-Based Touchscreen Capable of Multi-Touch and Multi-Force Sensing
Sensors 2015, 15(11), 28732-28741; doi:10.3390/s151128732
Received: 27 August 2015 / Revised: 4 November 2015 / Accepted: 5 November 2015 / Published: 13 November 2015
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Abstract
A force sensing touchscreen, which detects touch point and touch force simultaneously by sensing a change in electric capacitance, was designed and fabricated. It was made with single-walled carbon nanotubes (SWCNTs) which have better mechanical and chemical characteristics than the indium-tin-oxide transparent electrodes
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A force sensing touchscreen, which detects touch point and touch force simultaneously by sensing a change in electric capacitance, was designed and fabricated. It was made with single-walled carbon nanotubes (SWCNTs) which have better mechanical and chemical characteristics than the indium-tin-oxide transparent electrodes used in most contemporary touchscreen devices. The SWCNTs, with a transmittance of about 85% and electric conductivity of 400 Ω per square; were coated and patterned on glass and polyethyleneterephthalate (PET) film substrates. The constructed force sensing touchscreen has a total size and thickness of 62 mm × 100 mm × 1.4 mm, and is composed of 11 driving line and 19 receiving line channels. The gap between the channels was designed to be 20 µm, taking visibility into consideration, and patterned by a photolithography and plasma etching processes. The mutual capacitance formed by the upper and lower transparent electrodes was initially about 2.8 pF and, on applying a 500 gf force with a 3 mm diameter tip, it showed a 25% capacitance variation. Furthermore, the touchscreen can detect multiple touches and forces simultaneously and is unaffected by touch material characteristics, such as conductance or non-conductance. Full article
(This article belongs to the Section Physical Sensors)
Open AccessArticle Near-Field Sound Localization Based on the Small Profile Monaural Structure
Sensors 2015, 15(11), 28742-28763; doi:10.3390/s151128742
Received: 14 September 2015 / Revised: 2 November 2015 / Accepted: 9 November 2015 / Published: 13 November 2015
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Abstract
The acoustic wave around a sound source in the near-field area presents unconventional properties in the temporal, spectral, and spatial domains due to the propagation mechanism. This paper investigates a near-field sound localizer in a small profile structure with a single microphone. The
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The acoustic wave around a sound source in the near-field area presents unconventional properties in the temporal, spectral, and spatial domains due to the propagation mechanism. This paper investigates a near-field sound localizer in a small profile structure with a single microphone. The asymmetric structure around the microphone provides a distinctive spectral variation that can be recognized by the dedicated algorithm for directional localization. The physical structure consists of ten pipes of different lengths in a vertical fashion and rectangular wings positioned between the pipes in radial directions. The sound from an individual direction travels through the nearest open pipe, which generates the particular fundamental frequency according to the acoustic resonance. The Cepstral parameter is modified to evaluate the fundamental frequency. Once the system estimates the fundamental frequency of the received signal, the length of arrival and angle of arrival (AoA) are derived by the designed model. From an azimuthal distance of 3–15 cm from the outer body of the pipes, the extensive acoustic experiments with a 3D-printed structure show that the direct and side directions deliver average hit rates of 89% and 73%, respectively. The closer positions to the system demonstrate higher accuracy, and the overall hit rate performance is 78% up to 15 cm away from the structure body. Full article
(This article belongs to the Section Physical Sensors)
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Open AccessArticle A Unique Self-Sensing, Self-Actuating AFM Probe at Higher Eigenmodes
Sensors 2015, 15(11), 28764-28771; doi:10.3390/s151128764
Received: 3 October 2015 / Revised: 7 November 2015 / Accepted: 9 November 2015 / Published: 13 November 2015
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Abstract
With its unique structure, the Akiyama probe is a type of tuning fork atomic force microscope probe. The long, soft cantilever makes it possible to measure soft samples in tapping mode. In this article, some characteristics of the probe at its second eigenmode
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With its unique structure, the Akiyama probe is a type of tuning fork atomic force microscope probe. The long, soft cantilever makes it possible to measure soft samples in tapping mode. In this article, some characteristics of the probe at its second eigenmode are revealed by use of finite element analysis (FEA) and experiments in a standard atmosphere. Although the signal-to-noise ratio in this environment is not good enough, the 2 nm resolution and 0.09 Hz/nm sensitivity prove that the Akiyama probe can be used at its second eigenmode under FM non-contact mode or low amplitude FM tapping mode, which means that it is easy to change the measuring method from normal tapping to small amplitude tapping or non-contact mode with the same probe and equipment. Full article
(This article belongs to the Special Issue Carbon MEMS and NEMS for Sensor Applications)
Open AccessArticle Multi-Sensor Data Fusion Identification for Shearer Cutting Conditions Based on Parallel Quasi-Newton Neural Networks and the Dempster-Shafer Theory
Sensors 2015, 15(11), 28772-28795; doi:10.3390/s151128772
Received: 18 September 2015 / Revised: 8 November 2015 / Accepted: 10 November 2015 / Published: 13 November 2015
Cited by 4 | PDF Full-text (6226 KB) | HTML Full-text | XML Full-text
Abstract
In order to efficiently and accurately identify the cutting condition of a shearer, this paper proposed an intelligent multi-sensor data fusion identification method using the parallel quasi-Newton neural network (PQN-NN) and the Dempster-Shafer (DS) theory. The vibration acceleration signals and current signal of
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In order to efficiently and accurately identify the cutting condition of a shearer, this paper proposed an intelligent multi-sensor data fusion identification method using the parallel quasi-Newton neural network (PQN-NN) and the Dempster-Shafer (DS) theory. The vibration acceleration signals and current signal of six cutting conditions were collected from a self-designed experimental system and some special state features were extracted from the intrinsic mode functions (IMFs) based on the ensemble empirical mode decomposition (EEMD). In the experiment, three classifiers were trained and tested by the selected features of the measured data, and the DS theory was used to combine the identification results of three single classifiers. Furthermore, some comparisons with other methods were carried out. The experimental results indicate that the proposed method performs with higher detection accuracy and credibility than the competing algorithms. Finally, an industrial application example in the fully mechanized coal mining face was demonstrated to specify the effect of the proposed system. Full article
(This article belongs to the Section Physical Sensors)
Open AccessArticle Conductometric Sensor for Soot Mass Flow Detection in Exhausts of Internal Combustion Engines
Sensors 2015, 15(11), 28796-28806; doi:10.3390/s151128796
Received: 11 September 2015 / Revised: 22 October 2015 / Accepted: 9 November 2015 / Published: 13 November 2015
Cited by 5 | PDF Full-text (1800 KB) | HTML Full-text | XML Full-text
Abstract
Soot sensors are required for on-board diagnostics (OBD) of automotive diesel particulate filters (DPF) to detect filter failures. Widely used for this purpose are conductometric sensors, measuring an electrical current or resistance between two electrodes. Soot particles deposit on the electrodes, which leads
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Soot sensors are required for on-board diagnostics (OBD) of automotive diesel particulate filters (DPF) to detect filter failures. Widely used for this purpose are conductometric sensors, measuring an electrical current or resistance between two electrodes. Soot particles deposit on the electrodes, which leads to an increase in current or decrease in resistance. If installed upstream of a DPF, the “engine-out” soot emissions can also be determined directly by soot sensors. Sensors were characterized in diesel engine real exhausts under varying operation conditions and with two different kinds of diesel fuel. The sensor signal was correlated to the actual soot mass and particle number, measured with an SMPS. Sensor data and soot analytics (SMPS) agreed very well, an impressing linear correlation in a double logarithmic representation was found. This behavior was even independent of the used engine settings or of the biodiesel content. Full article
(This article belongs to the Section Physical Sensors)
Open AccessArticle Vehicle Position Estimation Based on Magnetic Markers: Enhanced Accuracy by Compensation of Time Delays
Sensors 2015, 15(11), 28807-28825; doi:10.3390/s151128807
Received: 3 September 2015 / Revised: 26 October 2015 / Accepted: 11 November 2015 / Published: 13 November 2015
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Abstract
The real-time recognition of absolute (or relative) position and orientation on a network of roads is a core technology for fully automated or driving-assisted vehicles. This paper presents an empirical investigation of the design, implementation, and evaluation of a self-positioning system based on
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The real-time recognition of absolute (or relative) position and orientation on a network of roads is a core technology for fully automated or driving-assisted vehicles. This paper presents an empirical investigation of the design, implementation, and evaluation of a self-positioning system based on a magnetic marker reference sensing method for an autonomous vehicle. Specifically, the estimation accuracy of the magnetic sensing ruler (MSR) in the up-to-date estimation of the actual position was successfully enhanced by compensating for time delays in signal processing when detecting the vertical magnetic field (VMF) in an array of signals. In this study, the signal processing scheme was developed to minimize the effects of the distortion of measured signals when estimating the relative positional information based on magnetic signals obtained using the MSR. In other words, the center point in a 2D magnetic field contour plot corresponding to the actual position of magnetic markers was estimated by tracking the errors between pre-defined reference models and measured magnetic signals. The algorithm proposed in this study was validated by experimental measurements using a test vehicle on a pilot network of roads. From the results, the positioning error was found to be less than 0.04 m on average in an operational test. Full article
(This article belongs to the Special Issue Magnetic Sensor Device-Part 2)
Open AccessArticle Hybrid Molecular and Spin Dynamics Simulations for Ensembles of Magnetic Nanoparticles for Magnetoresistive Systems
Sensors 2015, 15(11), 28826-28841; doi:10.3390/s151128826
Received: 28 September 2015 / Revised: 30 October 2015 / Accepted: 6 November 2015 / Published: 13 November 2015
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Abstract
The development of magnetoresistive sensors based on magnetic nanoparticles which are immersed in conductive gel matrices requires detailed information about the corresponding magnetoresistive properties in order to obtain optimal sensor sensitivities. Here, crucial parameters are the particle concentration, the viscosity of the gel
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The development of magnetoresistive sensors based on magnetic nanoparticles which are immersed in conductive gel matrices requires detailed information about the corresponding magnetoresistive properties in order to obtain optimal sensor sensitivities. Here, crucial parameters are the particle concentration, the viscosity of the gel matrix and the particle structure. Experimentally, it is not possible to obtain detailed information about the magnetic microstructure, i.e., orientations of the magnetic moments of the particles that define the magnetoresistive properties, however, by using numerical simulations one can study the magnetic microstructure theoretically, although this requires performing classical spin dynamics and molecular dynamics simulations simultaneously. Here, we present such an approach which allows us to calculate the orientation and the trajectory of every single magnetic nanoparticle. This enables us to study not only the static magnetic microstructure, but also the dynamics of the structuring process in the gel matrix itself. With our hybrid approach, arbitrary sensor configurations can be investigated and their magnetoresistive properties can be optimized. Full article
(This article belongs to the Special Issue Magnetic Sensor Device-Part 1)
Open AccessArticle A Room-Temperature Operation Formaldehyde Sensing Material Printed Using Blends of Reduced Graphene Oxide and Poly(methyl methacrylate)
Sensors 2015, 15(11), 28842-28853; doi:10.3390/s151128842
Received: 13 September 2015 / Revised: 10 November 2015 / Accepted: 11 November 2015 / Published: 13 November 2015
Cited by 2 | PDF Full-text (776 KB) | HTML Full-text | XML Full-text
Abstract
This work demonstrates a printable blending material, i.e., reduced graphene oxide (RGO) mixed with poly(methyl methacrylate) (PMMA), for formaldehyde sensing. Based on experimental results, 2% RGO/10% PMMA is an optimal ratio for formaldehyde detection, which produced a 30.5% resistance variation in response
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This work demonstrates a printable blending material, i.e., reduced graphene oxide (RGO) mixed with poly(methyl methacrylate) (PMMA), for formaldehyde sensing. Based on experimental results, 2% RGO/10% PMMA is an optimal ratio for formaldehyde detection, which produced a 30.5% resistance variation in response to 1000 ppm formaldehyde and high selectivity compared to different volatile organic compounds (VOCs), humidity, CO, and NO. The demonstrated detection limit is 100 ppm with 1.51% resistance variation. Characterization of the developed formaldehyde sensing material was performed by Fourier-transform infrared (FTIR) spectrometry, scanning electron microscopy (SEM), and Raman spectroscopy. Based on Raman spectroscopy, the basic sensing mechanism is the band distortion of RGO due to blending with PMMA and the adsorption of formaldehyde. This work establishes insights into the formaldehyde sensing mechanism and explores a potential printable sensing material for diverse applications. Full article
(This article belongs to the Section Chemical Sensors)
Open AccessArticle A Timing Estimation Method Based-on Skewness Analysis in Vehicular Wireless Networks
Sensors 2015, 15(11), 28942-28959; doi:10.3390/s151128942
Received: 11 October 2015 / Revised: 9 November 2015 / Accepted: 11 November 2015 / Published: 13 November 2015
Cited by 2 | PDF Full-text (1066 KB) | HTML Full-text | XML Full-text
Abstract
Vehicle positioning technology has drawn more and more attention in vehicular wireless networks to reduce transportation time and traffic accidents. Nowadays, global navigation satellite systems (GNSS) are widely used in land vehicle positioning, but most of them are lack precision and reliability in
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Vehicle positioning technology has drawn more and more attention in vehicular wireless networks to reduce transportation time and traffic accidents. Nowadays, global navigation satellite systems (GNSS) are widely used in land vehicle positioning, but most of them are lack precision and reliability in situations where their signals are blocked. Positioning systems base-on short range wireless communication are another effective way that can be used in vehicle positioning or vehicle ranging. IEEE 802.11p is a new real-time short range wireless communication standard for vehicles, so a new method is proposed to estimate the time delay or ranges between vehicles based on the IEEE 802.11p standard which includes three main steps: cross-correlation between the received signal and the short preamble, summing up the correlated results in groups, and finding the maximum peak using a dynamic threshold based on the skewness analysis. With the range between each vehicle or road-side infrastructure, the position of neighboring vehicles can be estimated correctly. Simulation results were presented in the International Telecommunications Union (ITU) vehicular multipath channel, which show that the proposed method provides better precision than some well-known timing estimation techniques, especially in low signal to noise ratio (SNR) environments. Full article
(This article belongs to the Special Issue Identification, Information & Knowledge in the Internet of Things)
Open AccessArticle An Intrusion Detection System Based on Multi-Level Clustering for Hierarchical Wireless Sensor Networks
Sensors 2015, 15(11), 28960-28978; doi:10.3390/s151128960
Received: 5 July 2015 / Revised: 17 September 2015 / Accepted: 9 November 2015 / Published: 17 November 2015
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Abstract
In this work, an intrusion detection system (IDS) framework based on multi-level clustering for hierarchical wireless sensor networks is proposed. The framework employs two types of intrusion detection approaches: (1) “downward-IDS (D-IDS)” to detect the abnormal behavior (intrusion) of the subordinate (member) nodes;
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In this work, an intrusion detection system (IDS) framework based on multi-level clustering for hierarchical wireless sensor networks is proposed. The framework employs two types of intrusion detection approaches: (1) “downward-IDS (D-IDS)” to detect the abnormal behavior (intrusion) of the subordinate (member) nodes; and (2) “upward-IDS (U-IDS)” to detect the abnormal behavior of the cluster heads. By using analytical calculations, the optimum parameters for the D-IDS (number of maximum hops) and U-IDS (monitoring group size) of the framework are evaluated and presented. Full article
(This article belongs to the Section Sensor Networks)
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Open AccessArticle A Mode Matched Triaxial Vibratory Wheel Gyroscope with Fully Decoupled Structure
Sensors 2015, 15(11), 28979-29002; doi:10.3390/s151128979
Received: 13 October 2015 / Revised: 1 November 2015 / Accepted: 9 November 2015 / Published: 17 November 2015
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Abstract
To avoid the oscillation of four unequal masses seen in previous triaxial linear gyroscopes, a modified silicon triaxial gyroscope with a rotary wheel is presented in this paper. To maintain a large sensitivity and suppress the coupling of different modes, this novel gyroscope
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To avoid the oscillation of four unequal masses seen in previous triaxial linear gyroscopes, a modified silicon triaxial gyroscope with a rotary wheel is presented in this paper. To maintain a large sensitivity and suppress the coupling of different modes, this novel gyroscope structure is designed be perfectly symmetrical with a relatively large size of about 9.8 mm × 9.8 mm. It is available for differentially detecting three-axis angular rates simultaneously. To overcome the coupling between drive and sense modes, numerous necessary frames, beams, and anchors are delicately figured out and properly arranged. Besides, some frequency tuning and feedback mechanisms are addressed in the case of post processing after fabrication. To facilitate mode matched function, a new artificial fish swarm algorithm (AFSA) performed faster than particle swarm optimization (PSO) with a frequency split of 108 Hz. Then, by entrusting the post adjustment of the springs dimensions to the finite element method (FEM) software ANSYS, the final frequency splits can be below 3 Hz. The simulation results demonstrate that the modal frequencies in drive and different sense modes are respectively 8001.1, 8002.6, 8002.8 and 8003.3 Hz. Subsequently, different axis cross coupling effects and scale factors are also analyzed. The simulation results effectively validate the feasibility of the design and relevant theoretical calculation. Full article
(This article belongs to the collection Modeling, Testing and Reliability Issues in MEMS Engineering)
Open AccessArticle Feasibility of Ultra-Thin Fiber-Optic Dosimeters for Radiotherapy Dosimetry
Sensors 2015, 15(11), 29003-29014; doi:10.3390/s151129003
Received: 28 August 2015 / Revised: 11 November 2015 / Accepted: 12 November 2015 / Published: 17 November 2015
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Abstract
In this study, prototype ultra-thin fiber-optic dosimeters were fabricated using organic scintillators, wavelength shifting fibers, and plastic optical fibers. The sensor probes of the ultra-thin fiber-optic dosimeters consisted of very thin organic scintillators with thicknesses of 100, 150 and 200 μm. These types
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In this study, prototype ultra-thin fiber-optic dosimeters were fabricated using organic scintillators, wavelength shifting fibers, and plastic optical fibers. The sensor probes of the ultra-thin fiber-optic dosimeters consisted of very thin organic scintillators with thicknesses of 100, 150 and 200 μm. These types of sensors cannot only be used to measure skin or surface doses but also provide depth dose measurements with high spatial resolution. With the ultra-thin fiber-optic dosimeters, surface doses for gamma rays generated from a Co-60 therapy machine were measured. Additionally, percentage depth doses in the build-up regions were obtained by using the ultra-thin fiber-optic dosimeters, and the results were compared with those of external beam therapy films and a conventional fiber-optic dosimeter. Full article
(This article belongs to the Section Physical Sensors)
Open AccessArticle Selection of Mother Wavelet Functions for Multi-Channel EEG Signal Analysis during a Working Memory Task
Sensors 2015, 15(11), 29015-29035; doi:10.3390/s151129015
Received: 26 August 2015 / Accepted: 4 October 2015 / Published: 17 November 2015
Cited by 8 | PDF Full-text (1680 KB) | HTML Full-text | XML Full-text
Abstract
We performed a comparative study to select the efficient mother wavelet (MWT) basis functions that optimally represent the signal characteristics of the electrical activity of the human brain during a working memory (WM) task recorded through electro-encephalography (EEG). Nineteen EEG electrodes were placed
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We performed a comparative study to select the efficient mother wavelet (MWT) basis functions that optimally represent the signal characteristics of the electrical activity of the human brain during a working memory (WM) task recorded through electro-encephalography (EEG). Nineteen EEG electrodes were placed on the scalp following the 10–20 system. These electrodes were then grouped into five recording regions corresponding to the scalp area of the cerebral cortex. Sixty-second WM task data were recorded from ten control subjects. Forty-five MWT basis functions from orthogonal families were investigated. These functions included Daubechies (db1–db20), Symlets (sym1–sym20), and Coiflets (coif1–coif5). Using ANOVA, we determined the MWT basis functions with the most significant differences in the ability of the five scalp regions to maximize their cross-correlation with the EEG signals. The best results were obtained using “sym9” across the five scalp regions. Therefore, the most compatible MWT with the EEG signals should be selected to achieve wavelet denoising, decomposition, reconstruction, and sub-band feature extraction. This study provides a reference of the selection of efficient MWT basis functions. Full article
(This article belongs to the Section Biosensors)
Open AccessArticle Capacity Model and Constraints Analysis for Integrated Remote Wireless Sensor and Satellite Network in Emergency Scenarios
Sensors 2015, 15(11), 29036-29055; doi:10.3390/s151129036
Received: 9 September 2015 / Revised: 7 November 2015 / Accepted: 11 November 2015 / Published: 17 November 2015
Cited by 3 | PDF Full-text (637 KB) | HTML Full-text | XML Full-text
Abstract
This article investigates the capacity problem of an integrated remote wireless sensor and satellite network (IWSSN) in emergency scenarios. We formulate a general model to evaluate the remote sensor and satellite network capacity. Compared to most existing works for ground networks, the proposed
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This article investigates the capacity problem of an integrated remote wireless sensor and satellite network (IWSSN) in emergency scenarios. We formulate a general model to evaluate the remote sensor and satellite network capacity. Compared to most existing works for ground networks, the proposed model is time varying and space oriented. To capture the characteristics of a practical network, we sift through major capacity-impacting constraints and analyze the influence of these constraints. Specifically, we combine the geometric satellite orbit model and satellite tool kit (STK) engineering software to quantify the trends of the capacity constraints. Our objective in analyzing these trends is to provide insights and design guidelines for optimizing the integrated remote wireless sensor and satellite network schedules. Simulation results validate the theoretical analysis of capacity trends and show the optimization opportunities of the IWSSN. Full article
(This article belongs to the Special Issue Mobile Sensor Computing: Theory and Applications)
Open AccessArticle Self-Learning Embedded System for Object Identification in Intelligent Infrastructure Sensors
Sensors 2015, 15(11), 29056-29078; doi:10.3390/s151129056
Received: 30 September 2015 / Revised: 2 November 2015 / Accepted: 5 November 2015 / Published: 17 November 2015
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Abstract
The emergence of new horizons in the field of travel assistant management leads to the development of cutting-edge systems focused on improving the existing ones. Moreover, new opportunities are being also presented since systems trend to be more reliable and autonomous. In this
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The emergence of new horizons in the field of travel assistant management leads to the development of cutting-edge systems focused on improving the existing ones. Moreover, new opportunities are being also presented since systems trend to be more reliable and autonomous. In this paper, a self-learning embedded system for object identification based on adaptive-cooperative dynamic approaches is presented for intelligent sensor’s infrastructures. The proposed system is able to detect and identify moving objects using a dynamic decision tree. Consequently, it combines machine learning algorithms and cooperative strategies in order to make the system more adaptive to changing environments. Therefore, the proposed system may be very useful for many applications like shadow tolls since several types of vehicles may be distinguished, parking optimization systems, improved traffic conditions systems, etc. Full article
(This article belongs to the Special Issue Sensors in New Road Vehicles)
Open AccessArticle Feasibility Study of EO SARs as Opportunity Illuminators in Passive Radars: PAZ-Based Case Study
Sensors 2015, 15(11), 29079-29106; doi:10.3390/s151129079
Received: 18 September 2015 / Revised: 2 November 2015 / Accepted: 10 November 2015 / Published: 17 November 2015
Cited by 1 | PDF Full-text (2665 KB) | HTML Full-text | XML Full-text
Abstract
Passive radars exploit the signal transmitted by other systems, known as opportunity illuminators (OIs), instead of using their own transmitter. Due to its almost total invulnerability to natural disasters or physical attacks, satellite OIs are of special interest. In this line, a feasibility
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Passive radars exploit the signal transmitted by other systems, known as opportunity illuminators (OIs), instead of using their own transmitter. Due to its almost total invulnerability to natural disasters or physical attacks, satellite OIs are of special interest. In this line, a feasibility study of Earth Observation Synthetic Aperture Radar (EO SAR) systems as OIs is carried out taking into consideration signal waveform, availability, bistatic geometry, instrumented coverage area and incident power density. A case study based on the use of PAZ, the first Spanish EO SAR, is presented. PAZ transmitted waveform, operation modes, orbit characteristics and antenna and transmitter parameters are analyzed to estimate potential coverages and resolutions. The study concludes that, due to its working in on-demand operating mode, passive radars based on PAZ-type illuminators can be proposed as complementing tools during the sensor commissioning phase, for system maintenance and for improving its performance by providing additional information about the area of interest and/or increasing the data updating speed, exploiting other sensors during the time PAZ is not available. Full article
(This article belongs to the Section Physical Sensors)
Open AccessArticle EFPC: An Environmentally Friendly Power Control Scheme for Underwater Sensor Networks
Sensors 2015, 15(11), 29107-29128; doi:10.3390/s151129107
Received: 4 August 2015 / Revised: 3 November 2015 / Accepted: 11 November 2015 / Published: 17 November 2015
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Abstract
In oceans, the limited acoustic spectrum resource is heavily shared by marine mammals and manmade systems including underwater sensor networks. In order to limit the negative impact of acoustic signal on marine mammals, we propose an environmentally friendly power control (EFPC) scheme for
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In oceans, the limited acoustic spectrum resource is heavily shared by marine mammals and manmade systems including underwater sensor networks. In order to limit the negative impact of acoustic signal on marine mammals, we propose an environmentally friendly power control (EFPC) scheme for underwater sensor networks. EFPC allocates transmission power of sensor nodes with a consideration of the existence of marine mammals. By applying a Nash Equilibrium based utility function with a set of limitations to optimize transmission power, the proposed power control algorithm can conduct parallel transmissions to improve the network’s goodput, while avoiding interference with marine mammals. Additionally, to localize marine mammals, which is a prerequisite of EFPC, we propose a novel passive hyperboloid localization algorithm (PHLA). PHLA passively localize marine mammals with the help of the acoustic characteristic of these targets. Simulation results show that PHLA can localize most of the target with a relatively small localization error and EFPC can achieve a close goodput performance compared with an existing power control algorithm while avoiding interfering with marine mammals. Full article
(This article belongs to the Special Issue Underwater Sensor Nodes and Underwater Sensor Networks 2016)
Open AccessArticle Hiding the Source Based on Limited Flooding for Sensor Networks
Sensors 2015, 15(11), 29129-29148; doi:10.3390/s151129129
Received: 25 August 2015 / Revised: 2 November 2015 / Accepted: 11 November 2015 / Published: 17 November 2015
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Abstract
Wireless sensor networks are widely used to monitor valuable objects such as rare animals or armies. Once an object is detected, the source, i.e., the sensor nearest to the object, generates and periodically sends a packet about the object to the base
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Wireless sensor networks are widely used to monitor valuable objects such as rare animals or armies. Once an object is detected, the source, i.e., the sensor nearest to the object, generates and periodically sends a packet about the object to the base station. Since attackers can capture the object by localizing the source, many protocols have been proposed to protect source location. Instead of transmitting the packet to the base station directly, typical source location protection protocols first transmit packets randomly for a few hops to a phantom location, and then forward the packets to the base station. The problem with these protocols is that the generated phantom locations are usually not only near the true source but also close to each other. As a result, attackers can easily trace a route back to the source from the phantom locations. To address the above problem, we propose a new protocol for source location protection based on limited flooding, named SLP. Compared with existing protocols, SLP can generate phantom locations that are not only far away from the source, but also widely distributed. It improves source location security significantly with low communication cost. We further propose a protocol, namely SLP-E, to protect source location against more powerful attackers with wider fields of vision. The performance of our SLP and SLP-E are validated by both theoretical analysis and simulation results. Full article
(This article belongs to the Special Issue Security and Privacy in Sensor Networks)
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Open AccessArticle An Efficient Data-Gathering Routing Protocol for Underwater Wireless Sensor Networks
Sensors 2015, 15(11), 29149-29181; doi:10.3390/s151129149
Received: 15 July 2015 / Revised: 1 November 2015 / Accepted: 11 November 2015 / Published: 17 November 2015
Cited by 12 | PDF Full-text (1498 KB) | HTML Full-text | XML Full-text
Abstract
Most applications of underwater wireless sensor networks (UWSNs) demand reliable data delivery over a longer period in an efficient and timely manner. However, the harsh and unpredictable underwater environment makes routing more challenging as compared to terrestrial WSNs. Most of the existing schemes
[...] Read more.
Most applications of underwater wireless sensor networks (UWSNs) demand reliable data delivery over a longer period in an efficient and timely manner. However, the harsh and unpredictable underwater environment makes routing more challenging as compared to terrestrial WSNs. Most of the existing schemes deploy mobile sensors or a mobile sink (MS) to maximize data gathering. However, the relatively high deployment cost prevents their usage in most applications. Thus, this paper presents an autonomous underwater vehicle (AUV)-aided efficient data-gathering (AEDG) routing protocol for reliable data delivery in UWSNs. To prolong the network lifetime, AEDG employs an AUV for data collection from gateways and uses a shortest path tree (SPT) algorithm while associating sensor nodes with the gateways. The AEDG protocol also limits the number of associated nodes with the gateway nodes to minimize the network energy consumption and to prevent the gateways from overloading. Moreover, gateways are rotated with the passage of time to balance the energy consumption of the network. To prevent data loss, AEDG allows dynamic data collection at the AUV depending on the limited number of member nodes that are associated with each gateway. We also develop a sub-optimal elliptical trajectory of AUV by using a connected dominating set (CDS) to further facilitate network throughput maximization. The performance of the AEDG is validated via simulations, which demonstrate the effectiveness of AEDG in comparison to two existing UWSN routing protocols in terms of the selected performance metrics. Full article
(This article belongs to the Section Sensor Networks)
Open AccessArticle A Refractive Index Sensor Based on a Metal-Insulator-Metal Waveguide-Coupled Ring Resonator
Sensors 2015, 15(11), 29183-29191; doi:10.3390/s151129183
Received: 26 August 2015 / Revised: 16 November 2015 / Accepted: 16 November 2015 / Published: 19 November 2015
Cited by 3 | PDF Full-text (848 KB) | HTML Full-text | XML Full-text
Abstract
A refractive index sensor composed of two straight metal-insulator-metal waveguides and a ring resonator is presented. One end of each straight waveguide is sealed and the other end acts as port. The transmission spectrum and magnetic field distribution of this sensor structure are
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A refractive index sensor composed of two straight metal-insulator-metal waveguides and a ring resonator is presented. One end of each straight waveguide is sealed and the other end acts as port. The transmission spectrum and magnetic field distribution of this sensor structure are simulated using finite-difference time-domain method (FDTD). The results show that an asymmetric line shape is observed in the transmission spectrum, and that the transmission spectrum shows a filter-like behavior. The quality factor and sensitivity are taken to characterize its sensing performance and filter properties. How structural parameters affect the sensing performance and filter properties is also studied. Full article
(This article belongs to the Special Issue Silicon Based Optical Sensors)
Open AccessArticle An Inductorless Self-Controlled Rectifier for Piezoelectric Energy Harvesting
Sensors 2015, 15(11), 29192-29208; doi:10.3390/s151129192
Received: 23 June 2015 / Revised: 7 October 2015 / Accepted: 13 November 2015 / Published: 19 November 2015
Cited by 2 | PDF Full-text (2775 KB) | HTML Full-text | XML Full-text
Abstract
This paper presents a high-efficiency inductorless self-controlled rectifier for piezoelectric energy harvesting. High efficiency is achieved by discharging the piezoelectric device (PD) capacitance each time the current produced by the PD changes polarity. This is achieved automatically without the use of delay lines,
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This paper presents a high-efficiency inductorless self-controlled rectifier for piezoelectric energy harvesting. High efficiency is achieved by discharging the piezoelectric device (PD) capacitance each time the current produced by the PD changes polarity. This is achieved automatically without the use of delay lines, thereby making the proposed circuit compatible with any type of PD. In addition, the proposed rectifier alleviates the need for an inductor, making it suitable for on-chip integration. Reported experimental results show that the proposed rectifier can harvest up to 3.9 times more energy than a full wave bridge rectifier. Full article
Open AccessArticle Toward Higher-Order Mass Detection: Influence of an Adsorbate’s Rotational Inertia and Eccentricity on the Resonant Response of a Bernoulli-Euler Cantilever Beam
Sensors 2015, 15(11), 29209-29232; doi:10.3390/s151129209
Received: 30 September 2015 / Revised: 30 October 2015 / Accepted: 11 November 2015 / Published: 19 November 2015
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Abstract
In this paper a new theoretical model is derived, the results of which permit a detailed examination of how the resonant characteristics of a cantilever are influenced by a particle (adsorbate) attached at an arbitrary position along the beam’s length. Unlike most previous
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In this paper a new theoretical model is derived, the results of which permit a detailed examination of how the resonant characteristics of a cantilever are influenced by a particle (adsorbate) attached at an arbitrary position along the beam’s length. Unlike most previous work, the particle need not be small in mass or dimension relative to the beam, and the adsorbate’s geometric characteristics are incorporated into the model via its rotational inertia and eccentricity relative to the beam axis. For the special case in which the adsorbate’s (translational) mass is indeed small, an analytical solution is obtained for the particle-induced resonant frequency shift of an arbitrary flexural mode, including the effects of rotational inertia and eccentricity. This solution is shown to possess the exact first-order behavior in the normalized particle mass and represents a generalization of analytical solutions derived by others in earlier studies. The results suggest the potential for “higher-order” nanobeam-based mass detection methods by which the multi-mode frequency response reflects not only the adsorbate’s mass but also important geometric data related to its size, shape, or orientation (i.e., the mass distribution), thus resulting in more highly discriminatory techniques for discrete-mass sensing. Full article
(This article belongs to the Special Issue Nanomechanics for Sensing and Spectrometry)
Open AccessArticle An Electrochemical Quartz Crystal Microbalance Multisensor System Based on Phthalocyanine Nanostructured Films: Discrimination of Musts
Sensors 2015, 15(11), 29233-29249; doi:10.3390/s151129233
Received: 10 September 2015 / Revised: 9 October 2015 / Accepted: 13 November 2015 / Published: 19 November 2015
Cited by 3 | PDF Full-text (1391 KB) | HTML Full-text | XML Full-text
Abstract
An array of electrochemical quartz crystal electrodes (EQCM) modified with nanostructured films based on phthalocyanines was developed and used to discriminate musts prepared from different varieties of grapes. Nanostructured films of iron, nickel and copper phthalocyanines were deposited on Pt/quartz crystals through the
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An array of electrochemical quartz crystal electrodes (EQCM) modified with nanostructured films based on phthalocyanines was developed and used to discriminate musts prepared from different varieties of grapes. Nanostructured films of iron, nickel and copper phthalocyanines were deposited on Pt/quartz crystals through the Layer by Layer technique by alternating layers of the corresponding phthalocyanine and poly-allylamine hydrochloride. Simultaneous electrochemical and mass measurements were used to study the mass changes accompanying the oxidation of electroactive species present in must samples obtained from six Spanish varieties of grapes (Juan García, Prieto Picudo, Mencía Regadío, Cabernet Sauvignon, Garnacha and Tempranillo). The mass and voltammetric outputs were processed using three-way models. Parallel Factor Analysis (PARAFAC) was successfully used to discriminate the must samples according to their variety. Multi-way partial least squares (N-PLS) evidenced the correlations existing between the voltammetric data and the polyphenolic content measured by chemical methods. Similarly, N-PLS showed a correlation between mass outputs and parameters related to the sugar content. These results demonstrated that electronic tongues based on arrays of EQCM sensors can offer advantages over arrays of mass or voltammetric sensors used separately. Full article
(This article belongs to the Section Chemical Sensors)
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Open AccessArticle A Passive Testing Approach for Protocols in Wireless Sensor Networks
Sensors 2015, 15(11), 29250-29272; doi:10.3390/s151129250
Received: 12 October 2015 / Revised: 8 November 2015 / Accepted: 13 November 2015 / Published: 19 November 2015
PDF Full-text (1458 KB) | HTML Full-text | XML Full-text
Abstract
Smart systems are today increasingly developed with the number of wireless sensor devices drastically increasing. They are implemented within several contexts throughout our environment. Thus, sensed data transported in ubiquitous systems are important, and the way to carry them must be efficient and
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Smart systems are today increasingly developed with the number of wireless sensor devices drastically increasing. They are implemented within several contexts throughout our environment. Thus, sensed data transported in ubiquitous systems are important, and the way to carry them must be efficient and reliable. For that purpose, several routing protocols have been proposed for wireless sensor networks (WSN). However, one stage that is often neglected before their deployment is the conformance testing process, a crucial and challenging step. Compared to active testing techniques commonly used in wired networks, passive approaches are more suitable to the WSN environment. While some works propose to specify the protocol with state models or to analyze them with simulators and emulators, we here propose a logic-based approach for formally specifying some functional requirements of a novel WSN routing protocol. We provide an algorithm to evaluate these properties on collected protocol execution traces. Further, we demonstrate the efficiency and suitability of our approach by its application into common WSN functional properties, as well as specific ones designed from our own routing protocol. We provide relevant testing verdicts through a real indoor testbed and the implementation of our protocol. Furthermore, the flexibility, genericity and practicability of our approach have been proven by the experimental results. Full article
(This article belongs to the Special Issue Identification, Information & Knowledge in the Internet of Things)
Open AccessArticle A Wireless Sensor Network-Based Approach with Decision Support for Monitoring Lake Water Quality
Sensors 2015, 15(11), 29273-29296; doi:10.3390/s151129273
Received: 9 September 2015 / Revised: 8 November 2015 / Accepted: 11 November 2015 / Published: 19 November 2015
Cited by 3 | PDF Full-text (2252 KB) | HTML Full-text | XML Full-text
Abstract
Online monitoring and water quality analysis of lakes are urgently needed. A feasible and effective approach is to use a Wireless Sensor Network (WSN). Lake water environments, like other real world environments, present many changing and unpredictable situations. To ensure flexibility in such
[...] Read more.
Online monitoring and water quality analysis of lakes are urgently needed. A feasible and effective approach is to use a Wireless Sensor Network (WSN). Lake water environments, like other real world environments, present many changing and unpredictable situations. To ensure flexibility in such an environment, the WSN node has to be prepared to deal with varying situations. This paper presents a WSN self-configuration approach for lake water quality monitoring. The approach is based on the integration of a semantic framework, where a reasoner can make decisions on the configuration of WSN services. We present a WSN ontology and the relevant water quality monitoring context information, which considers its suitability in a pervasive computing environment. We also propose a rule-based reasoning engine that is used to conduct decision support through reasoning techniques and context-awareness. To evaluate the approach, we conduct usability experiments and performance benchmarks. Full article
(This article belongs to the Section Sensor Networks)
Open AccessArticle Concept Design for a 1-Lead Wearable/Implantable ECG Front-End: Power Management
Sensors 2015, 15(11), 29297-29315; doi:10.3390/s151129297
Received: 15 July 2015 / Revised: 9 November 2015 / Accepted: 13 November 2015 / Published: 19 November 2015
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Abstract
Power supply quality and stability are critical for wearable and implantable biomedical applications. For this reason we have designed a reconfigurable switched-capacitor DC-DC converter that, aside from having an extremely small footprint (with an active on-chip area of only 0.04 mm2),
[...] Read more.
Power supply quality and stability are critical for wearable and implantable biomedical applications. For this reason we have designed a reconfigurable switched-capacitor DC-DC converter that, aside from having an extremely small footprint (with an active on-chip area of only 0.04 mm2), uses a novel output voltage control method based upon a combination of adaptive gain and discrete frequency scaling control schemes. This novel DC-DC converter achieves a measured output voltage range of 1.0 to 2.2 V with power delivery up to 7.5 mW with 75% efficiency. In this paper, we present the use of this converter as a power supply for a concept design of a wearable (15 mm × 15 mm) 1-lead ECG front-end sensor device that simultaneously harvests power and communicates with external receivers when exposed to a suitable RF field. Due to voltage range limitations of the fabrication process of the current prototype chip, we focus our analysis solely on the power supply of the ECG front-end whose design is also detailed in this paper. Measurement results show not just that the power supplied is regulated, clean and does not infringe upon the ECG bandwidth, but that there is negligible difference between signals acquired using standard linear power-supplies and when the power is regulated by our power management chip. Full article
(This article belongs to the Special Issue Power Schemes for Biosensors and Biomedical Devices)
Open AccessArticle Pothole Detection System Using a Black-box Camera
Sensors 2015, 15(11), 29316-29331; doi:10.3390/s151129316
Received: 30 September 2015 / Revised: 16 November 2015 / Accepted: 17 November 2015 / Published: 19 November 2015
Cited by 2 | PDF Full-text (2736 KB) | HTML Full-text | XML Full-text
Abstract
Aging roads and poor road-maintenance systems result a large number of potholes, whose numbers increase over time. Potholes jeopardize road safety and transportation efficiency. Moreover, they are often a contributing factor to car accidents. To address the problems associated with potholes, the locations
[...] Read more.
Aging roads and poor road-maintenance systems result a large number of potholes, whose numbers increase over time. Potholes jeopardize road safety and transportation efficiency. Moreover, they are often a contributing factor to car accidents. To address the problems associated with potholes, the locations and size of potholes must be determined quickly. Sophisticated road-maintenance strategies can be developed using a pothole database, which requires a specific pothole-detection system that can collect pothole information at low cost and over a wide area. However, pothole repair has long relied on manual detection efforts. Recent automatic detection systems, such as those based on vibrations or laser scanning, are insufficient to detect potholes correctly and inexpensively owing to the unstable detection of vibration-based methods and high costs of laser scanning-based methods. Thus, in this paper, we introduce a new pothole-detection system using a commercial black-box camera. The proposed system detects potholes over a wide area and at low cost. We have developed a novel pothole-detection algorithm specifically designed to work with the embedded computing environments of black-box cameras. Experimental results are presented with our proposed system, showing that potholes can be detected accurately in real-time. Full article
(This article belongs to the Special Issue Sensors in New Road Vehicles)
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Open AccessArticle Multi-Layer Approach for the Detection of Selective Forwarding Attacks
Sensors 2015, 15(11), 29332-29345; doi:10.3390/s151129332
Received: 22 September 2015 / Revised: 13 November 2015 / Accepted: 16 November 2015 / Published: 19 November 2015
Cited by 1 | PDF Full-text (1333 KB) | HTML Full-text | XML Full-text
Abstract
Security breaches are a major threat in wireless sensor networks (WSNs). WSNs are increasingly used due to their broad range of important applications in both military and civilian domains. WSNs are prone to several types of security attacks. Sensor nodes have limited capacities
[...] Read more.
Security breaches are a major threat in wireless sensor networks (WSNs). WSNs are increasingly used due to their broad range of important applications in both military and civilian domains. WSNs are prone to several types of security attacks. Sensor nodes have limited capacities and are often deployed in dangerous locations; therefore, they are vulnerable to different types of attacks, including wormhole, sinkhole, and selective forwarding attacks. Security attacks are classified as data traffic and routing attacks. These security attacks could affect the most significant applications of WSNs, namely, military surveillance, traffic monitoring, and healthcare. Therefore, there are different approaches to detecting security attacks on the network layer in WSNs. Reliability, energy efficiency, and scalability are strong constraints on sensor nodes that affect the security of WSNs. Because sensor nodes have limited capabilities in most of these areas, selective forwarding attacks cannot be easily detected in networks. In this paper, we propose an approach to selective forwarding detection (SFD). The approach has three layers: MAC pool IDs, rule-based processing, and anomaly detection. It maintains the safety of data transmission between a source node and base station while detecting selective forwarding attacks. Furthermore, the approach is reliable, energy efficient, and scalable. Full article
(This article belongs to the Special Issue Security and Privacy in Sensor Networks)
Open AccessArticle An Analytic Model for the Success Rate of a Robotic Actuator System in Hitting Random Targets
Sensors 2015, 15(11), 29346-29362; doi:10.3390/s151129346
Received: 5 September 2015 / Revised: 10 November 2015 / Accepted: 17 November 2015 / Published: 20 November 2015
Cited by 1 | PDF Full-text (3131 KB) | HTML Full-text | XML Full-text
Abstract
Autonomous robotic systems are increasingly being used in a wide range of applications such as precision agriculture, medicine, and the military. These systems have common features which often includes an action by an “actuator” interacting with a target. While simulations and measurements exist
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Autonomous robotic systems are increasingly being used in a wide range of applications such as precision agriculture, medicine, and the military. These systems have common features which often includes an action by an “actuator” interacting with a target. While simulations and measurements exist for the success rate of hitting targets by some systems, there is a dearth of analytic models which can give insight into, and guidance on optimization, of new robotic systems. The present paper develops a simple model for estimation of the success rate for hitting random targets from a moving platform. The model has two main dimensionless parameters: the ratio of actuator spacing to target diameter; and the ratio of platform distance moved (between actuator “firings”) to the target diameter. It is found that regions of parameter space having specified high success are described by simple equations, providing guidance on design. The role of a “cost function” is introduced which, when minimized, provides optimization of design, operating, and risk mitigation costs. Full article
(This article belongs to the Section Physical Sensors)
Open AccessArticle Early Fault Diagnosis of Bearings Using an Improved Spectral Kurtosis by Maximum Correlated Kurtosis Deconvolution
Sensors 2015, 15(11), 29363-29377; doi:10.3390/s151129363
Received: 8 September 2015 / Revised: 10 November 2015 / Accepted: 17 November 2015 / Published: 20 November 2015
Cited by 4 | PDF Full-text (1349 KB) | HTML Full-text | XML Full-text
Abstract
The early fault characteristics of rolling element bearings carried by vibration signals are quite weak because the signals are generally masked by heavy background noise. To extract the weak fault characteristics of bearings from the signals, an improved spectral kurtosis (SK) method is
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The early fault characteristics of rolling element bearings carried by vibration signals are quite weak because the signals are generally masked by heavy background noise. To extract the weak fault characteristics of bearings from the signals, an improved spectral kurtosis (SK) method is proposed based on maximum correlated kurtosis deconvolution (MCKD). The proposed method combines the ability of MCKD in indicating the periodic fault transients and the ability of SK in locating these transients in the frequency domain. A simulation signal overwhelmed by heavy noise is used to demonstrate the effectiveness of the proposed method. The results show that MCKD is beneficial to clarify the periodic impulse components of the bearing signals, and the method is able to detect the resonant frequency band of the signal and extract its fault characteristic frequency. Through analyzing actual vibration signals collected from wind turbines and hot strip rolling mills, we confirm that by using the proposed method, it is possible to extract fault characteristics and diagnose early faults of rolling element bearings. Based on the comparisons with the SK method, it is verified that the proposed method is more suitable to diagnose early faults of rolling element bearings. Full article
(This article belongs to the Section Physical Sensors)
Open AccessArticle Molecular Electronic Angular Motion Transducer Broad Band Self-Noise
Sensors 2015, 15(11), 29378-29392; doi:10.3390/s151129378
Received: 17 September 2015 / Revised: 10 November 2015 / Accepted: 17 November 2015 / Published: 20 November 2015
Cited by 8 | PDF Full-text (1626 KB) | HTML Full-text | XML Full-text
Abstract
Modern molecular electronic transfer (MET) angular motion sensors combine high technical characteristics with low cost. Self-noise is one of the key characteristics which determine applications for MET sensors. However, until the present there has not been a model describing the sensor noise in
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Modern molecular electronic transfer (MET) angular motion sensors combine high technical characteristics with low cost. Self-noise is one of the key characteristics which determine applications for MET sensors. However, until the present there has not been a model describing the sensor noise in the complete operating frequency range. The present work reports the results of an experimental study of the self-noise level of such sensors in the frequency range of 0.01–200 Hz. Based on the experimental data, a theoretical model is developed. According to the model, self-noise is conditioned by thermal hydrodynamic fluctuations of the operating fluid flow in the frequency range of 0.01–2 Hz. At the frequency range of 2–100 Hz, the noise power spectral density has a specific inversely proportional dependence of the power spectral density on the frequency that could be attributed to convective processes. In the high frequency range of 100–200 Hz, the noise is conditioned by the voltage noise of the electronics module input stage operational amplifiers and is heavily reliant to the sensor electrical impedance. The presented results allow a deeper understanding of the molecular electronic sensor noise nature to suggest the ways to reduce it. Full article
(This article belongs to the Section Physical Sensors)
Open AccessArticle Feature Selection and Predictors of Falls with Foot Force Sensors Using KNN-Based Algorithms
Sensors 2015, 15(11), 29393-29407; doi:10.3390/s151129393
Received: 25 September 2015 / Revised: 4 November 2015 / Accepted: 17 November 2015 / Published: 20 November 2015
Cited by 1 | PDF Full-text (806 KB) | HTML Full-text | XML Full-text
Abstract
The aging process may lead to the degradation of lower extremity function in the elderly population, which can restrict their daily quality of life and gradually increase the fall risk. We aimed to determine whether objective measures of physical function could predict subsequent
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The aging process may lead to the degradation of lower extremity function in the elderly population, which can restrict their daily quality of life and gradually increase the fall risk. We aimed to determine whether objective measures of physical function could predict subsequent falls. Ground reaction force (GRF) data, which was quantified by sample entropy, was collected by foot force sensors. Thirty eight subjects (23 fallers and 15 non-fallers) participated in functional movement tests, including walking and sit-to-stand (STS). A feature selection algorithm was used to select relevant features to classify the elderly into two groups: at risk and not at risk of falling down, for three KNN-based classifiers: local mean-based k-nearest neighbor (LMKNN), pseudo nearest neighbor (PNN), local mean pseudo nearest neighbor (LMPNN) classification. We compared classification performances, and achieved the best results with LMPNN, with sensitivity, specificity and accuracy all 100%. Moreover, a subset of GRFs was significantly different between the two groups via Wilcoxon rank sum test, which is compatible with the classification results. This method could potentially be used by non-experts to monitor balance and the risk of falling down in the elderly population. Full article
(This article belongs to the collection Sensors for Globalized Healthy Living and Wellbeing)
Open AccessArticle Liver Cancer Detection by a Simple, Inexpensive and Effective Immunosensor with Zinc Oxide Nanoparticles
Sensors 2015, 15(11), 29408-29418; doi:10.3390/s151129408
Received: 23 September 2015 / Revised: 9 November 2015 / Accepted: 13 November 2015 / Published: 20 November 2015
Cited by 1 | PDF Full-text (1020 KB) | HTML Full-text | XML Full-text
Abstract
Regular monitoring of blood α-fetoprotein (AFP) and/or carcino-embryonic antigen (CEA) levels is important for the routine screening of liver cancer. However, AFP and CEA have a much lower specificity than des-γ-carboxyprothrombin (DCP) to detect liver cancer. Therefore, the study reported here was designed,
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Regular monitoring of blood α-fetoprotein (AFP) and/or carcino-embryonic antigen (CEA) levels is important for the routine screening of liver cancer. However, AFP and CEA have a much lower specificity than des-γ-carboxyprothrombin (DCP) to detect liver cancer. Therefore, the study reported here was designed, to develop a screen-printed DCP immunosensor incorporating zinc oxide nanoparticles, for accurate determination of DCP. The designed immunosensor shows low detection limits for the detection of DCP: 0.440 ng/mL (based on impedance measurement), 0.081 ng/mL (based on real part of impedance measurement) and 0.078 ng/mL (based on imaginary part of impedance measurement), within the range of 3.125 ng/mL to 2000 ng/mL. In addition, there was little interference to DCP determination by molecules such as Na+, K+, Ca2+, Cl, glucose, urea, and uric acid. It is therefore concluded that the DCP immunosensor developed and reported here is simple, inexpensive and effective, and shows promise in the rapid screening of early-stage liver cancer at home with a point-of-care approach. Full article
(This article belongs to the Section Biosensors)
Open AccessArticle NiCu Alloy Nanoparticle-Loaded Carbon Nanofibers for Phenolic Biosensor Applications
Sensors 2015, 15(11), 29419-29433; doi:10.3390/s151129419
Received: 19 August 2015 / Revised: 21 October 2015 / Accepted: 13 November 2015 / Published: 20 November 2015
Cited by 4 | PDF Full-text (3140 KB) | HTML Full-text | XML Full-text
Abstract
NiCu alloy nanoparticle-loaded carbon nanofibers (NiCuCNFs) were fabricated by a combination of electrospinning and carbonization methods. A series of characterizations, including SEM, TEM and XRD, were employed to study the NiCuCNFs. The as-prepared NiCuCNFs were then mixed with laccase (Lac) and Nafion to
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NiCu alloy nanoparticle-loaded carbon nanofibers (NiCuCNFs) were fabricated by a combination of electrospinning and carbonization methods. A series of characterizations, including SEM, TEM and XRD, were employed to study the NiCuCNFs. The as-prepared NiCuCNFs were then mixed with laccase (Lac) and Nafion to form a novel biosensor. NiCuCNFs successfully achieved the direct electron transfer of Lac. Cyclic voltammetry and linear sweep voltammetry were used to study the electrochemical properties of the biosensor. The finally prepared biosensor showed favorable electrocatalytic effects toward hydroquinone. The detection limit was 90 nM (S/N = 3), the sensitivity was 1.5 µA µM−1, the detection linear range was 4 × 10−7–2.37 × 10−6 M. In addition, this biosensor exhibited satisfactory repeatability, reproducibility, anti-interference properties and stability. Besides, the sensor achieved the detection of hydroquinone in lake water. Full article
(This article belongs to the Special Issue Microbial and Enzymatic Biosensors)
Open AccessArticle Study on Miniaturized UHF Antennas for Partial Discharge Detection in High-Voltage Electrical Equipment
Sensors 2015, 15(11), 29434-29451; doi:10.3390/s151129434
Received: 18 August 2015 / Revised: 3 November 2015 / Accepted: 10 November 2015 / Published: 20 November 2015
Cited by 5 | PDF Full-text (2559 KB) | HTML Full-text | XML Full-text
Abstract
Detecting partial discharge (PD) is an effective way to evaluate the condition of high-voltage electrical equipment insulation. The UHF detection method has attracted attention due to its high sensitivity, strong interference resistance, and ability to locate PDs. In this paper, a miniaturized equiangular
[...] Read more.
Detecting partial discharge (PD) is an effective way to evaluate the condition of high-voltage electrical equipment insulation. The UHF detection method has attracted attention due to its high sensitivity, strong interference resistance, and ability to locate PDs. In this paper, a miniaturized equiangular spiral antenna (ESA) for UHF detection that uses a printed circuit board is proposed. I-shaped, L-shaped, and C-shaped microstrip baluns were designed to match the impedance between the ESA and coaxial cable and were verified by a vector network analyzer. For comparison, three other types of UHF antenna were also designed: A microstrip patch antenna, a microstrip slot antenna, and a printed dipole antenna. Their antenna factors were calibrated in a uniform electric field of different frequencies modulated in a gigahertz transverse electromagnetic cell. We performed comparison experiments on PD signal detection using an artificial defect model based on the international IEC 60270 standard. We also conducted time-delay test experiments on the ESA sensor to locate a PD source. It was found that the proposed ESA sensor meets PD signal detection requirements. The sensor’s compact size makes it suitable for internal installation in high-voltage electrical equipment. Full article
(This article belongs to the Section Physical Sensors)
Open AccessArticle Robust Diagnosis Method Based on Parameter Estimation for an Interturn Short-Circuit Fault in Multipole PMSM under High-Speed Operation
Sensors 2015, 15(11), 29452-29466; doi:10.3390/s151129452
Received: 19 October 2015 / Revised: 16 November 2015 / Accepted: 17 November 2015 / Published: 20 November 2015
Cited by 2 | PDF Full-text (863 KB) | HTML Full-text | XML Full-text
Abstract
This paper proposes a diagnosis method for a multipole permanent magnet synchronous motor (PMSM) under an interturn short circuit fault. Previous works in this area have suffered from the uncertainties of the PMSM parameters, which can lead to misdiagnosis. The proposed method estimates
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This paper proposes a diagnosis method for a multipole permanent magnet synchronous motor (PMSM) under an interturn short circuit fault. Previous works in this area have suffered from the uncertainties of the PMSM parameters, which can lead to misdiagnosis. The proposed method estimates the q-axis inductance (Lq) of the faulty PMSM to solve this problem. The proposed method also estimates the faulty phase and the value of G, which serves as an index of the severity of the fault. The q-axis current is used to estimate the faulty phase, the values of G and Lq. For this reason, two open-loop observers and an optimization method based on a particle-swarm are implemented. The q-axis current of a healthy PMSM is estimated by the open-loop observer with the parameters of a healthy PMSM. The Lq estimation significantly compensates for the estimation errors in high-speed operation. The experimental results demonstrate that the proposed method can estimate the faulty phase, G, and Lq besides exhibiting robustness against parameter uncertainties. Full article
(This article belongs to the Section Physical Sensors)
Open AccessArticle Wireless Low-Power Integrated Basal-Body-Temperature Detection Systems Using Teeth Antennas in the MedRadio Band
Sensors 2015, 15(11), 29467-29477; doi:10.3390/s151129467
Received: 15 July 2015 / Revised: 10 November 2015 / Accepted: 17 November 2015 / Published: 20 November 2015
PDF Full-text (1983 KB) | HTML Full-text | XML Full-text
Abstract
This study proposes using wireless low power thermal sensors for basal-body-temperature detection using frequency modulated telemetry devices. A long-term monitoring sensor requires low-power circuits including a sampling circuit and oscillator. Moreover, temperature compensated technologies are necessary because the modulated frequency might have additional
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This study proposes using wireless low power thermal sensors for basal-body-temperature detection using frequency modulated telemetry devices. A long-term monitoring sensor requires low-power circuits including a sampling circuit and oscillator. Moreover, temperature compensated technologies are necessary because the modulated frequency might have additional frequency deviations caused by the varying temperature. The temperature compensated oscillator is composed of a ring oscillator and a controlled-steering current source with temperature compensation, so the output frequency of the oscillator does not drift with temperature variations. The chip is fabricated in a standard Taiwan Semiconductor Manufacturing Company (TSMC) 0.18-μm complementary metal oxide semiconductor (CMOS) process, and the chip area is 0.9 mm2. The power consumption of the sampling amplifier is 128 µW. The power consumption of the voltage controlled oscillator (VCO) core is less than 40 µW, and the output is −3.04 dBm with a buffer stage. The output voltage of the bandgap reference circuit is 1 V. For temperature measurements, the maximum error is 0.18 °C with a standard deviation of ±0.061 °C, which is superior to the required specification of 0.1 °C. Full article
(This article belongs to the Special Issue Power Schemes for Biosensors and Biomedical Devices)
Open AccessArticle TF4SM: A Framework for Developing Traceability Solutions in Small Manufacturing Companies
Sensors 2015, 15(11), 29478-29510; doi:10.3390/s151129478
Received: 20 July 2015 / Revised: 26 October 2015 / Accepted: 18 November 2015 / Published: 20 November 2015
Cited by 7 | PDF Full-text (1324 KB) | HTML Full-text | XML Full-text
Abstract
Nowadays, manufacturing processes have become highly complex. Besides, more and more, governmental institutions require companies to implement systems to trace a product’s life (especially for foods, clinical materials or similar items). In this paper, we propose a new framework, based on cyber-physical systems,
[...] Read more.
Nowadays, manufacturing processes have become highly complex. Besides, more and more, governmental institutions require companies to implement systems to trace a product’s life (especially for foods, clinical materials or similar items). In this paper, we propose a new framework, based on cyber-physical systems, for developing traceability systems in small manufacturing companies (which because of their size cannot implement other commercial products). We propose a general theoretical framework, study the requirements of these companies in relation to traceability systems, propose a reference architecture based on both previous elements and build the first minimum functional prototype, to compare our solution to a traditional tag-based traceability system. Results show that our system reduces the number of inefficiencies and reaction time. Full article
(This article belongs to the Special Issue Cyber-Physical Systems)
Open AccessArticle Detection of Lettuce Discoloration Using Hyperspectral Reflectance Imaging
Sensors 2015, 15(11), 29511-29534; doi:10.3390/s151129511
Received: 10 July 2015 / Revised: 11 November 2015 / Accepted: 17 November 2015 / Published: 20 November 2015
PDF Full-text (2931 KB) | HTML Full-text | XML Full-text
Abstract
Rapid visible/near-infrared (VNIR) hyperspectral imaging methods, employing both a single waveband algorithm and multi-spectral algorithms, were developed in order to discrimination between sound and discolored lettuce. Reflectance spectra for sound and discolored lettuce surfaces were extracted from hyperspectral reflectance images obtained in the
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Rapid visible/near-infrared (VNIR) hyperspectral imaging methods, employing both a single waveband algorithm and multi-spectral algorithms, were developed in order to discrimination between sound and discolored lettuce. Reflectance spectra for sound and discolored lettuce surfaces were extracted from hyperspectral reflectance images obtained in the 400–1000 nm wavelength range. The optimal wavebands for discriminating between discolored and sound lettuce surfaces were determined using one-way analysis of variance. Multi-spectral imaging algorithms developed using ratio and subtraction functions resulted in enhanced classification accuracy of above 99.9% for discolored and sound areas on both adaxial and abaxial lettuce surfaces. Ratio imaging (RI) and subtraction imaging (SI) algorithms at wavelengths of 552/701 nm and 557–701 nm, respectively, exhibited better classification performances compared to results obtained for all possible two-waveband combinations. These results suggest that hyperspectral reflectance imaging techniques can potentially be used to discriminate between discolored and sound fresh-cut lettuce. Full article
Open AccessArticle A Real-Time Monitoring System of Industry Carbon Monoxide Based on Wireless Sensor Networks
Sensors 2015, 15(11), 29535-29546; doi:10.3390/s151129535
Received: 30 July 2015 / Accepted: 17 November 2015 / Published: 20 November 2015
Cited by 57 | PDF Full-text (3042 KB) | HTML Full-text | XML Full-text
Abstract
Carbon monoxide (CO) burns or explodes at over-standard concentration. Hence, in this paper, a Wifi-based, real-time monitoring of a CO system is proposed for application in the construction industry, in which a sensor measuring node is designed by low-frequency modulation method to acquire
[...] Read more.
Carbon monoxide (CO) burns or explodes at over-standard concentration. Hence, in this paper, a Wifi-based, real-time monitoring of a CO system is proposed for application in the construction industry, in which a sensor measuring node is designed by low-frequency modulation method to acquire CO concentration reliably, and a digital filtering method is adopted for noise filtering. According to the triangulation, the Wifi network is constructed to transmit information and determine the position of nodes. The measured data are displayed on a computer or smart phone by a graphical interface. The experiment shows that the monitoring system obtains excellent accuracy and stability in long-term continuous monitoring. Full article
(This article belongs to the Special Issue Sensors for Fire Detection)
Open AccessArticle Automated Negotiation for Resource Assignment in Wireless Surveillance Sensor Networks
Sensors 2015, 15(11), 29547-29568; doi:10.3390/s151129547
Received: 23 September 2015 / Revised: 6 November 2015 / Accepted: 18 November 2015 / Published: 24 November 2015
Cited by 2 | PDF Full-text (412 KB) | HTML Full-text | XML Full-text
Abstract
Due to the low cost of CMOS IP-based cameras, wireless surveillance sensor networks have emerged as a new application of sensor networks able to monitor public or private areas or even country borders. Since these networks are bandwidth intensive and the radioelectric spectrum
[...] Read more.
Due to the low cost of CMOS IP-based cameras, wireless surveillance sensor networks have emerged as a new application of sensor networks able to monitor public or private areas or even country borders. Since these networks are bandwidth intensive and the radioelectric spectrum is limited, especially in unlicensed bands, it is mandatory to assign frequency channels in a smart manner. In this work, we propose the application of automated negotiation techniques for frequency assignment. Results show that these techniques are very suitable for the problem, being able to obtain the best solutions among the techniques with which we have compared them. Full article
(This article belongs to the Section Sensor Networks)
Open AccessArticle Automated Low-Cost Smartphone-Based Lateral Flow Saliva Test Reader for Drugs-of-Abuse Detection
Sensors 2015, 15(11), 29569-29593; doi:10.3390/s151129569
Received: 31 August 2015 / Revised: 10 November 2015 / Accepted: 16 November 2015 / Published: 24 November 2015
Cited by 10 | PDF Full-text (5228 KB) | HTML Full-text | XML Full-text
Abstract
Lateral flow assay tests are nowadays becoming powerful, low-cost diagnostic tools. Obtaining a result is usually subject to visual interpretation of colored areas on the test by a human operator, introducing subjectivity and the possibility of errors in the extraction of the results.
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Lateral flow assay tests are nowadays becoming powerful, low-cost diagnostic tools. Obtaining a result is usually subject to visual interpretation of colored areas on the test by a human operator, introducing subjectivity and the possibility of errors in the extraction of the results. While automated test readers providing a result-consistent solution are widely available, they usually lack portability. In this paper, we present a smartphone-based automated reader for drug-of-abuse lateral flow assay tests, consisting of an inexpensive light box and a smartphone device. Test images captured with the smartphone camera are processed in the device using computer vision and machine learning techniques to perform automatic extraction of the results. A deep validation of the system has been carried out showing the high accuracy of the system. The proposed approach, applicable to any line-based or color-based lateral flow test in the market, effectively reduces the manufacturing costs of the reader and makes it portable and massively available while providing accurate, reliable results. Full article
Open AccessArticle Vision Sensor-Based Road Detection for Field Robot Navigation
Sensors 2015, 15(11), 29594-29617; doi:10.3390/s151129594
Received: 21 September 2015 / Revised: 13 November 2015 / Accepted: 17 November 2015 / Published: 24 November 2015
Cited by 5 | PDF Full-text (38257 KB) | HTML Full-text | XML Full-text
Abstract
Road detection is an essential component of field robot navigation systems. Vision sensors play an important role in road detection for their great potential in environmental perception. In this paper, we propose a hierarchical vision sensor-based method for robust road detection in challenging
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Road detection is an essential component of field robot navigation systems. Vision sensors play an important role in road detection for their great potential in environmental perception. In this paper, we propose a hierarchical vision sensor-based method for robust road detection in challenging road scenes. More specifically, for a given road image captured by an on-board vision sensor, we introduce a multiple population genetic algorithm (MPGA)-based approach for efficient road vanishing point detection. Superpixel-level seeds are then selected in an unsupervised way using a clustering strategy. Then, according to the GrowCut framework, the seeds proliferate and iteratively try to occupy their neighbors. After convergence, the initial road segment is obtained. Finally, in order to achieve a globally-consistent road segment, the initial road segment is refined using the conditional random field (CRF) framework, which integrates high-level information into road detection. We perform several experiments to evaluate the common performance, scale sensitivity and noise sensitivity of the proposed method. The experimental results demonstrate that the proposed method exhibits high robustness compared to the state of the art. Full article
(This article belongs to the Special Issue Sensors for Robots)
Figures

Open AccessArticle Particle Fabrication Using Inkjet Printing onto Hydrophobic Surfaces for Optimization and Calibration of Trace Contraband Detection Sensors
Sensors 2015, 15(11), 29618-29634; doi:10.3390/s151129618
Received: 4 September 2015 / Revised: 16 November 2015 / Accepted: 18 November 2015 / Published: 24 November 2015
Cited by 2 | PDF Full-text (2793 KB) | HTML Full-text | XML Full-text
Abstract
A method has been developed to fabricate patterned arrays of micrometer-sized monodisperse solid particles of ammonium nitrate on hydrophobic silicon surfaces using inkjet printing. The method relies on dispensing one or more microdrops of a concentrated aqueous ammonium nitrate solution from a drop-on-demand
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A method has been developed to fabricate patterned arrays of micrometer-sized monodisperse solid particles of ammonium nitrate on hydrophobic silicon surfaces using inkjet printing. The method relies on dispensing one or more microdrops of a concentrated aqueous ammonium nitrate solution from a drop-on-demand (DOD) inkjet printer at specific locations on a silicon substrate rendered hydrophobic by a perfluorodecytrichlorosilane monolayer coating. The deposited liquid droplets form into the shape of a spherical shaped cap; during the evaporation process, a deposited liquid droplet maintains this geometry until it forms a solid micrometer sized particle. Arrays of solid particles are obtained by sequential translation of the printer stage. The use of DOD inkjet printing for fabrication of discrete particle arrays allows for precise control of particle characteristics (mass, diameter and height), as well as the particle number and spatial distribution on the substrate. The final mass of an individual particle is precisely determined by using gravimetric measurement of the average mass of solution ejected per microdrop. The primary application of this method is fabrication of test materials for the evaluation of spatially-resolved optical and mass spectrometry based sensors used for detecting particle residues of contraband materials, such as explosives or narcotics. Full article
(This article belongs to the Section Physical Sensors)
Open AccessArticle Study and Test of a New Bundle-Structure Riser Stress Monitoring Sensor Based on FBG
Sensors 2015, 15(11), 29648-29660; doi:10.3390/s151129648
Received: 27 August 2015 / Revised: 5 November 2015 / Accepted: 9 November 2015 / Published: 24 November 2015
Cited by 1 | PDF Full-text (1515 KB) | HTML Full-text | XML Full-text
Abstract
To meet the requirements of riser safety monitoring in offshore oil fields, a new Fiber Bragg Grating (FBG)-based bundle-structure riser stress monitoring sensor has been developed. In cooperation with many departments, a 49-day marine test in water depths of 1365 m and 1252
[...] Read more.
To meet the requirements of riser safety monitoring in offshore oil fields, a new Fiber Bragg Grating (FBG)-based bundle-structure riser stress monitoring sensor has been developed. In cooperation with many departments, a 49-day marine test in water depths of 1365 m and 1252 m was completed on the “HYSY-981” ocean oil drilling platform. No welding and pasting were used when the sensor was installed on risers. Therefore, the installation is convenient, reliable and harmless to risers. The continuous, reasonable, time-consistent data obtained indicates that the sensor worked normally under water. In all detailed working conditions, the test results show that the sensor can do well in reflecting stresses and bending moments both in and in magnitude. The measured maximum stress is 132.7 MPa, which is below the allowable stress. In drilling and testing conditions, the average riser stress was 86.6 MPa, which is within the range of the China National Offshore Oil Corporation (CNOOC) mechanical simulation results. Full article
(This article belongs to the Special Issue Sensors for Harsh Environments)
Open AccessArticle The Indoor Localization and Tracking Estimation Method of Mobile Targets in Three-Dimensional Wireless Sensor Networks
Sensors 2015, 15(11), 29661-29684; doi:10.3390/s151129661
Received: 1 September 2015 / Revised: 17 November 2015 / Accepted: 18 November 2015 / Published: 24 November 2015
Cited by 2 | PDF Full-text (515 KB) | HTML Full-text | XML Full-text
Abstract
Indoor localization is a significant research area in wireless sensor networks (WSNs). Generally, the nodes of WSNs are deployed in the same plane, i.e., the floor, as the target to be positioned, which causes the sensing signal to be influenced or even blocked
[...] Read more.
Indoor localization is a significant research area in wireless sensor networks (WSNs). Generally, the nodes of WSNs are deployed in the same plane, i.e., the floor, as the target to be positioned, which causes the sensing signal to be influenced or even blocked by unpredictable obstacles, like furniture. However, a 3D system, like Cricket, can reduce the negative impact of obstacles to the maximum extent and guarantee the sensing signal transmission by using the line of sight (LOS). However, most of the traditional localization methods are not available for the new deployment mode. In this paper, we propose the self-localization of beacons method based on the Cayley–Menger determinant, which can determine the positions of beacons stuck in the ceiling; and differential sensitivity analysis (DSA) is also applied to eliminate measurement errors in measurement data fusion. Then, the calibration of beacons scheme is proposed to further refine the locations of beacons by the mobile robot. According to the robot’s motion model based on dead reckoning, which is the process of determining one’s current position, we employ the H ∞ filter and the strong tracking filter (STF) to calibrate the rough locations, respectively. Lastly, the optimal node selection scheme based on geometric dilution precision (GDOP) is presented here, which is able to pick the group of beacons with the minimum GDOP from all of the beacons. Then, we propose the GDOP-based weighting estimation method (GWEM) to associate redundant information with the position of the target. To verify the proposed methods in the paper, we design and conduct a simulation and an experiment in an indoor setting. Compared to EKF and the H ∞ filter, the adopted STF method can more effectively calibrate the locations of beacons; GWEM can provide centimeter-level precision in 3D environments by using the combination of beacons that minimizes GDOP. Full article
(This article belongs to the Section Sensor Networks)
Open AccessArticle SSL: Signal Similarity-Based Localization for Ocean Sensor Networks
Sensors 2015, 15(11), 29702-29720; doi:10.3390/s151129702
Received: 1 October 2015 / Revised: 8 November 2015 / Accepted: 19 November 2015 / Published: 24 November 2015
Cited by 4 | PDF Full-text (5855 KB) | HTML Full-text | XML Full-text
Abstract
Nowadays, wireless sensor networks are often deployed on the sea surface for ocean scientific monitoring. One of the important challenges is to localize the nodes’ positions. Existing localization schemes can be roughly divided into two types: range-based and range-free. The range-based localization approaches
[...] Read more.
Nowadays, wireless sensor networks are often deployed on the sea surface for ocean scientific monitoring. One of the important challenges is to localize the nodes’ positions. Existing localization schemes can be roughly divided into two types: range-based and range-free. The range-based localization approaches heavily depend on extra hardware capabilities, while range-free ones often suffer from poor accuracy and low scalability, far from the practical ocean monitoring applications. In response to the above limitations, this paper proposes a novel signal similarity-based localization (SSL) technology, which localizes the nodes’ positions by fully utilizing the similarity of received signal strength and the open-air characteristics of the sea surface. In the localization process, we first estimate the relative distance between neighboring nodes through comparing the similarity of received signal strength and then calculate the relative distance for non-neighboring nodes with the shortest path algorithm. After that, the nodes’ relative relation map of the whole network can be obtained. Given at least three anchors, the physical locations of nodes can be finally determined based on the multi-dimensional scaling (MDS) technology. The design is evaluated by two types of ocean experiments: a zonal network and a non-regular network using 28 nodes. Results show that the proposed design improves the localization accuracy compared to typical connectivity-based approaches and also confirm its effectiveness for large-scale ocean sensor networks. Full article
(This article belongs to the Special Issue Underwater Sensor Nodes and Underwater Sensor Networks 2016)
Open AccessArticle A Modified Rife Algorithm for Off-Grid DOA Estimation Based on Sparse Representations
Sensors 2015, 15(11), 29721-29733; doi:10.3390/s151129721
Received: 17 July 2015 / Revised: 12 November 2015 / Accepted: 17 November 2015 / Published: 24 November 2015
Cited by 3 | PDF Full-text (712 KB) | HTML Full-text | XML Full-text
Abstract
In this paper we address the problem of off-grid direction of arrival (DOA) estimation based on sparse representations in the situation of multiple measurement vectors (MMV). A novel sparse DOA estimation method which changes MMV problem to SMV is proposed. This method uses
[...] Read more.
In this paper we address the problem of off-grid direction of arrival (DOA) estimation based on sparse representations in the situation of multiple measurement vectors (MMV). A novel sparse DOA estimation method which changes MMV problem to SMV is proposed. This method uses sparse representations based on weighted eigenvectors (SRBWEV) to deal with the MMV problem. MMV problem can be changed to single measurement vector (SMV) problem by using the linear combination of eigenvectors of array covariance matrix in signal subspace as a new SMV for sparse solution calculation. So the complexity of this proposed algorithm is smaller than other DOA estimation algorithms of MMV. Meanwhile, it can overcome the limitation of the conventional sparsity-based DOA estimation approaches that the unknown directions belong to a predefined discrete angular grid, so it can further improve the DOA estimation accuracy. The modified Rife algorithm for DOA estimation (MRife-DOA) is simulated based on SRBWEV algorithm. In this proposed algorithm, the largest and sub-largest inner products between the measurement vector or its residual and the atoms in the dictionary are utilized to further modify DOA estimation according to the principle of Rife algorithm and the basic idea of coarse-to-fine estimation. Finally, simulation experiments show that the proposed algorithm is effective and can reduce the DOA estimation error caused by grid effect with lower complexity. Full article
(This article belongs to the Section Physical Sensors)
Open AccessArticle UAVs Task and Motion Planning in the Presence of Obstacles and Prioritized Targets
Sensors 2015, 15(11), 29734-29764; doi:10.3390/s151129734
Received: 25 June 2015 / Revised: 5 November 2015 / Accepted: 12 November 2015 / Published: 24 November 2015
Cited by 2 | PDF Full-text (902 KB) | HTML Full-text | XML Full-text
Abstract
The intertwined task assignment and motion planning problem of assigning a team of fixed-winged unmanned aerial vehicles to a set of prioritized targets in an environment with obstacles is addressed. It is assumed that the targets’ locations and initial priorities are determined using
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The intertwined task assignment and motion planning problem of assigning a team of fixed-winged unmanned aerial vehicles to a set of prioritized targets in an environment with obstacles is addressed. It is assumed that the targets’ locations and initial priorities are determined using a network of unattended ground sensors used to detect potential threats at restricted zones. The targets are characterized by a time-varying level of importance, and timing constraints must be fulfilled before a vehicle is allowed to visit a specific target. It is assumed that the vehicles are carrying body-fixed sensors and, thus, are required to approach a designated target while flying straight and level. The fixed-winged aerial vehicles are modeled as Dubins vehicles, i.e., having a constant speed and a minimum turning radius constraint. The investigated integrated problem of task assignment and motion planning is posed in the form of a decision tree, and two search algorithms are proposed: an exhaustive algorithm that improves over run time and provides the minimum cost solution, encoded in the tree, and a greedy algorithm that provides a quick feasible solution. To satisfy the target’s visitation timing constraint, a path elongation motion planning algorithm amidst obstacles is provided. Using simulations, the performance of the algorithms is compared, evaluated and exemplified. Full article
(This article belongs to the Special Issue UAV Sensors for Environmental Monitoring)

Review

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Open AccessReview Membrane Potential and Calcium Dynamics in Beta Cells from Mouse Pancreas Tissue Slices: Theory, Experimentation, and Analysis
Sensors 2015, 15(11), 27393-27419; doi:10.3390/s151127393
Received: 28 August 2015 / Revised: 11 October 2015 / Accepted: 14 October 2015 / Published: 28 October 2015
Cited by 2 | PDF Full-text (4271 KB) | HTML Full-text | XML Full-text
Abstract
Beta cells in the pancreatic islets of Langerhans are precise biological sensors for glucose and play a central role in balancing the organism between catabolic and anabolic needs. A hallmark of the beta cell response to glucose are oscillatory changes of membrane potential
[...] Read more.
Beta cells in the pancreatic islets of Langerhans are precise biological sensors for glucose and play a central role in balancing the organism between catabolic and anabolic needs. A hallmark of the beta cell response to glucose are oscillatory changes of membrane potential that are tightly coupled with oscillatory changes in intracellular calcium concentration which, in turn, elicit oscillations of insulin secretion. Both membrane potential and calcium changes spread from one beta cell to the other in a wave-like manner. In order to assess the properties of the abovementioned responses to physiological and pathological stimuli, the main challenge remains how to effectively measure membrane potential and calcium changes at the same time with high spatial and temporal resolution, and also in as many cells as possible. To date, the most wide-spread approach has employed the electrophysiological patch-clamp method to monitor membrane potential changes. Inherently, this technique has many advantages, such as a direct contact with the cell and a high temporal resolution. However, it allows one to assess information from a single cell only. In some instances, this technique has been used in conjunction with CCD camera-based imaging, offering the opportunity to simultaneously monitor membrane potential and calcium changes, but not in the same cells and not with a reliable cellular or subcellular spatial resolution. Recently, a novel family of highly-sensitive membrane potential reporter dyes in combination with high temporal and spatial confocal calcium imaging allows for simultaneously detecting membrane potential and calcium changes in many cells at a time. Since the signals yielded from both types of reporter dyes are inherently noisy, we have developed complex methods of data denoising that permit for visualization and pixel-wise analysis of signals. Combining the experimental approach of high-resolution imaging with the advanced analysis of noisy data enables novel physiological insights and reassessment of current concepts in unprecedented detail. Full article
Open AccessReview Electronic Nose Feature Extraction Methods: A Review
Sensors 2015, 15(11), 27804-27831; doi:10.3390/s151127804
Received: 30 August 2015 / Revised: 10 October 2015 / Accepted: 27 October 2015 / Published: 2 November 2015
Cited by 7 | PDF Full-text (1157 KB) | HTML Full-text | XML Full-text
Abstract
Many research groups in academia and industry are focusing on the performance improvement of electronic nose (E-nose) systems mainly involving three optimizations, which are sensitive material selection and sensor array optimization, enhanced feature extraction methods and pattern recognition method selection. For a specific
[...] Read more.
Many research groups in academia and industry are focusing on the performance improvement of electronic nose (E-nose) systems mainly involving three optimizations, which are sensitive material selection and sensor array optimization, enhanced feature extraction methods and pattern recognition method selection. For a specific application, the feature extraction method is a basic part of these three optimizations and a key point in E-nose system performance improvement. The aim of a feature extraction method is to extract robust information from the sensor response with less redundancy to ensure the effectiveness of the subsequent pattern recognition algorithm. Many kinds of feature extraction methods have been used in E-nose applications, such as extraction from the original response curves, curve fitting parameters, transform domains, phase space (PS) and dynamic moments (DM), parallel factor analysis (PARAFAC), energy vector (EV), power density spectrum (PSD), window time slicing (WTS) and moving window time slicing (MWTS), moving window function capture (MWFC), etc. The object of this review is to provide a summary of the various feature extraction methods used in E-noses in recent years, as well as to give some suggestions and new inspiration to propose more effective feature extraction methods for the development of E-nose technology. Full article
(This article belongs to the Special Issue Gas Sensors—Designs and Applications)
Open AccessReview A Review of LIDAR Radiometric Processing: From Ad Hoc Intensity Correction to Rigorous Radiometric Calibration
Sensors 2015, 15(11), 28099-28128; doi:10.3390/s151128099
Received: 6 August 2015 / Revised: 23 October 2015 / Accepted: 2 November 2015 / Published: 6 November 2015
Cited by 18 | PDF Full-text (1433 KB) | HTML Full-text | XML Full-text
Abstract
In addition to precise 3D coordinates, most light detection and ranging (LIDAR) systems also record “intensity”, loosely defined as the strength of the backscattered echo for each measured point. To date, LIDAR intensity data have proven beneficial in a wide range of applications
[...] Read more.
In addition to precise 3D coordinates, most light detection and ranging (LIDAR) systems also record “intensity”, loosely defined as the strength of the backscattered echo for each measured point. To date, LIDAR intensity data have proven beneficial in a wide range of applications because they are related to surface parameters, such as reflectance. While numerous procedures have been introduced in the scientific literature, and even commercial software, to enhance the utility of intensity data through a variety of “normalization”, “correction”, or “calibration” techniques, the current situation is complicated by a lack of standardization, as well as confusing, inconsistent use of terminology. In this paper, we first provide an overview of basic principles of LIDAR intensity measurements and applications utilizing intensity information from terrestrial, airborne topographic, and airborne bathymetric LIDAR. Next, we review effective parameters on intensity measurements, basic theory, and current intensity processing methods. We define terminology adopted from the most commonly-used conventions based on a review of current literature. Finally, we identify topics in need of further research. Ultimately, the presented information helps lay the foundation for future standards and specifications for LIDAR radiometric calibration. Full article
(This article belongs to the Section Remote Sensors)
Open AccessReview Magnetic Sensors Based on Amorphous Ferromagnetic Materials: A Review
Sensors 2015, 15(11), 28340-28366; doi:10.3390/s151128340
Received: 21 September 2015 / Revised: 26 October 2015 / Accepted: 5 November 2015 / Published: 11 November 2015
Cited by 12 | PDF Full-text (842 KB) | HTML Full-text | XML Full-text
Abstract
Currently there are many types of sensors that are used in lots of applications. Among these, magnetic sensors are a good alternative for the detection and measurement of different phenomena because they are a “simple” and readily available technology. For the construction of
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Currently there are many types of sensors that are used in lots of applications. Among these, magnetic sensors are a good alternative for the detection and measurement of different phenomena because they are a “simple” and readily available technology. For the construction of such devices there are many magnetic materials available, although amorphous ferromagnetic materials are the most suitable. The existence in the market of these materials allows the production of different kinds of sensors, without requiring expensive manufacture investments for the magnetic cores. Furthermore, these are not fragile materials that require special care, favouring the construction of solid and reliable devices. Another important feature is that these sensors can be developed without electric contact between the measuring device and the sensor, making them especially fit for use in harsh environments. In this review we will look at the main types of developed magnetic sensors. This work presents the state of the art of magnetic sensors based on amorphous ferromagnetic materials used in modern technology: security devices, weapon detection, magnetic maps, car industry, credit cards, etc. Full article
(This article belongs to the Special Issue Magnetic Sensor Device-Part 1)
Open AccessReview Recent Developments of Magnetoresistive Sensors for Industrial Applications
Sensors 2015, 15(11), 28665-28689; doi:10.3390/s151128665
Received: 31 August 2015 / Revised: 4 November 2015 / Accepted: 5 November 2015 / Published: 12 November 2015
Cited by 14 | PDF Full-text (2714 KB) | HTML Full-text | XML Full-text
Abstract
The research and development in the field of magnetoresistive sensors has played an important role in the last few decades. Here, the authors give an introduction to the fundamentals of the anisotropic magnetoresistive (AMR) and the giant magnetoresistive (GMR) effect as well as
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The research and development in the field of magnetoresistive sensors has played an important role in the last few decades. Here, the authors give an introduction to the fundamentals of the anisotropic magnetoresistive (AMR) and the giant magnetoresistive (GMR) effect as well as an overview of various types of sensors in industrial applications. In addition, the authors present their recent work in this field, ranging from sensor systems fabricated on traditional substrate materials like silicon (Si), over new fabrication techniques for magnetoresistive sensors on flexible substrates for special applications, e.g., a flexible write head for component integrated data storage, micro-stamping of sensors on arbitrary surfaces or three dimensional sensing under extreme conditions (restricted mounting space in motor air gap, high temperatures during geothermal drilling). Full article
(This article belongs to the Special Issue Magnetic Sensor Device-Part 2)
Open AccessReview Manipulation of Superparamagnetic Beads on Patterned Exchange-Bias Layer Systems for Biosensing Applications
Sensors 2015, 15(11), 28854-28888; doi:10.3390/s151128854
Received: 7 October 2015 / Revised: 30 October 2015 / Accepted: 9 November 2015 / Published: 13 November 2015
Cited by 10 | PDF Full-text (1900 KB) | HTML Full-text | XML Full-text
Abstract
A technology platform based on a remotely controlled and stepwise transport of an array arrangement of superparamagnetic beads (SPB) for efficient molecular uptake, delivery and accumulation in the context of highly specific and sensitive analyte molecule detection for the application in lab-on-a-chip devices
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A technology platform based on a remotely controlled and stepwise transport of an array arrangement of superparamagnetic beads (SPB) for efficient molecular uptake, delivery and accumulation in the context of highly specific and sensitive analyte molecule detection for the application in lab-on-a-chip devices is presented. The near-surface transport of SPBs is realized via the dynamic transformation of the SPBs’ magnetic potential energy landscape above a magnetically stripe patterned Exchange-Bias (EB) thin film layer systems due to the application of sub-mT external magnetic field pulses. In this concept, the SPB velocity is dramatically influenced by the magnitude and gradient of the magnetic field landscape (MFL) above the magnetically stripe patterned EB substrate, the SPB to substrate distance, the magnetic properties of both the SPBs and the EB layer system, respectively, as well as by the properties of the external magnetic field pulses and the surrounding fluid. The focus of this review is laid on the specific MFL design in EB layer systems via light-ion bombardment induced magnetic patterning (IBMP). A numerical approach is introduced for the theoretical description of the MFL in comparison to experimental characterization via scanning Hall probe microscopy. The SPB transport mechanism will be outlined in terms of the dynamic interplay between the EB substrate’s MFL and the pulse scheme of the external magnetic field. Full article
(This article belongs to the Special Issue Magnetic Sensor Device-Part 1)
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Open AccessReview Power Approaches for Implantable Medical Devices
Sensors 2015, 15(11), 28889-28914; doi:10.3390/s151128889
Received: 30 August 2015 / Revised: 15 October 2015 / Accepted: 6 November 2015 / Published: 13 November 2015
Cited by 16 | PDF Full-text (1900 KB) | HTML Full-text | XML Full-text
Abstract
Implantable medical devices have been implemented to provide treatment and to assess in vivo physiological information in humans as well as animal models for medical diagnosis and prognosis, therapeutic applications and biological science studies. The advances of micro/nanotechnology dovetailed with novel biomaterials have
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Implantable medical devices have been implemented to provide treatment and to assess in vivo physiological information in humans as well as animal models for medical diagnosis and prognosis, therapeutic applications and biological science studies. The advances of micro/nanotechnology dovetailed with novel biomaterials have further enhanced biocompatibility, sensitivity, longevity and reliability in newly-emerged low-cost and compact devices. Close-loop systems with both sensing and treatment functions have also been developed to provide point-of-care and personalized medicine. Nevertheless, one of the remaining challenges is whether power can be supplied sufficiently and continuously for the operation of the entire system. This issue is becoming more and more critical to the increasing need of power for wireless communication in implanted devices towards the future healthcare infrastructure, namely mobile health (m-Health). In this review paper, methodologies to transfer and harvest energy in implantable medical devices are introduced and discussed to highlight the uses and significances of various potential power sources. Full article
(This article belongs to the Special Issue Power Schemes for Biosensors and Biomedical Devices)
Open AccessReview Correlating the Integral Sensing Properties of Zeolites with Molecular Processes by Combining Broadband Impedance and DRIFT Spectroscopy—A New Approach for Bridging the Scales
Sensors 2015, 15(11), 28915-28941; doi:10.3390/s151128915
Received: 6 October 2015 / Revised: 2 November 2015 / Accepted: 5 November 2015 / Published: 13 November 2015
Cited by 7 | PDF Full-text (3276 KB) | HTML Full-text | XML Full-text
Abstract
Zeolites have been found to be promising sensor materials for a variety of gas molecules such as NH3, NOx, hydrocarbons, etc. The sensing effect results from the interaction of the adsorbed gas molecules with mobile cations, which are non-covalently
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Zeolites have been found to be promising sensor materials for a variety of gas molecules such as NH3, NOx, hydrocarbons, etc. The sensing effect results from the interaction of the adsorbed gas molecules with mobile cations, which are non-covalently bound to the zeolite lattice. The mobility of the cations can be accessed by electrical low-frequency (LF; mHz to MHz) and high-frequency (HF; GHz) impedance measurements. Recent developments allow in situ monitoring of catalytic reactions on proton-conducting zeolites used as catalysts. The combination of such in situ impedance measurements with diffuse reflectance infrared Fourier transform spectroscopy (DRIFTS), which was applied to monitor the selective catalytic reduction of nitrogen oxides (DeNOx-SCR), not only improves our understanding of the sensing properties of zeolite catalysts from integral electric signal to molecular processes, but also bridges the length scales being studied, from centimeters to nanometers. In this work, recent developments of zeolite-based, impedimetric sensors for automotive exhaust gases, in particular NH3, are summarized. The electrical response to NH3 obtained from LF impedance measurements will be compared with that from HF impedance measurements, and correlated with the infrared spectroscopic characteristics obtained from the DRIFTS studies of molecules involved in the catalytic conversion. The future perspectives, which arise from the combination of these methods, will be discussed. Full article
(This article belongs to the Special Issue Gas Sensors—Designs and Applications)
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Open AccessReview Tunable Microfluidic Devices for Hydrodynamic Fractionation of Cells and Beads: A Review
Sensors 2015, 15(11), 29685-29701; doi:10.3390/s151129685
Received: 3 September 2015 / Revised: 26 October 2015 / Accepted: 5 November 2015 / Published: 24 November 2015
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Abstract
The adjustable microfluidic devices that have been developed for hydrodynamic-based fractionation of beads and cells are important for fast performance tunability through interaction of mechanical properties of particles in fluid flow and mechanically flexible microstructures. In this review, the research works reported on
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The adjustable microfluidic devices that have been developed for hydrodynamic-based fractionation of beads and cells are important for fast performance tunability through interaction of mechanical properties of particles in fluid flow and mechanically flexible microstructures. In this review, the research works reported on fabrication and testing of the tunable elastomeric microfluidic devices for applications such as separation, filtration, isolation, and trapping of single or bulk of microbeads or cells are discussed. Such microfluidic systems for rapid performance alteration are classified in two groups of bulk deformation of microdevices using external mechanical forces, and local deformation of microstructures using flexible membrane by pneumatic pressure. The main advantage of membrane-based tunable systems has been addressed to be the high capability of integration with other microdevice components. The stretchable devices based on bulk deformation of microstructures have in common advantage of simplicity in design and fabrication process. Full article
(This article belongs to the Special Issue Micro/Nano Fluidic Devices and Bio-MEMS)

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Open AccessAddendum Addendum: Hochreiter, B.; Pardo-Garcia, A.; Schmid, J.A. Fluorescent Proteins as Genetically Encoded FRET Biosensors in Life Sciences. Sensors 2015, 15, 26281–26314
Sensors 2015, 15(11), 29182; doi:10.3390/s151129182
Received: 9 November 2015 / Accepted: 10 November 2015 / Published: 18 November 2015
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Abstract The authors wish to add an Acknowledgments section to their paper published in Sensors [1], doi:10.3390/s151026281, website: http://www.mdpi.com/1424-8220/15/10/26281. [...] Full article
(This article belongs to the Special Issue FRET Biosensors)
Open AccessTechnical Note Influence of Culture Media on Microbial Fingerprints Using Raman Spectroscopy
Sensors 2015, 15(11), 29635-29647; doi:10.3390/s151129635
Received: 3 September 2015 / Revised: 9 November 2015 / Accepted: 19 November 2015 / Published: 24 November 2015
Cited by 1 | PDF Full-text (1681 KB) | HTML Full-text | XML Full-text
Abstract
Raman spectroscopy has a broad range of applications across numerous scientific fields, including microbiology. Our work here monitors the influence of culture media on the Raman spectra of clinically important microorganisms (Escherichia coli, Staphylococcus aureus, Staphylococcus epidermidis and Candida albicans
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Raman spectroscopy has a broad range of applications across numerous scientific fields, including microbiology. Our work here monitors the influence of culture media on the Raman spectra of clinically important microorganisms (Escherichia coli, Staphylococcus aureus, Staphylococcus epidermidis and Candida albicans). Choosing an adequate medium may enhance the reproducibility of the method as well as simplifying the data processing and the evaluation. We tested four different media per organism depending on the nutritional requirements and clinical usage directly on a Petri dish. Some of the media have a significant influence on the microbial fingerprint (Roosvelt-Park Institute Medium, CHROMagar) and should not be used for the acquisition of Raman spectra. It was found that the most suitable medium for microbiological experiments regarding these organisms was Mueller-Hinton agar. Full article
(This article belongs to the Section Biosensors)

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