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Sensors, Volume 18, Issue 12 (December 2018)

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Cover Story (view full-size image) Pupils’ health, performance, and well-being crucially depend on indoor environmental quality (IEQ), [...] Read more.
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Open AccessArticle Detection of RINEX-2 Files With Mixed GPS L2P(Y)/L2C Carrier Phase Observations
Sensors 2018, 18(12), 4507; https://doi.org/10.3390/s18124507
Received: 16 November 2018 / Revised: 27 November 2018 / Accepted: 16 December 2018 / Published: 19 December 2018
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Abstract
Presently, the global positioning system (GPS) satellite constellation consists of 40% older Block IIA and IIR space vehicles and 60% newer IIR-M and IIF satellites. Only newer GPS satellites are capable of transmitting the L2C signal which is in quadrature to the legacy [...] Read more.
Presently, the global positioning system (GPS) satellite constellation consists of 40% older Block IIA and IIR space vehicles and 60% newer IIR-M and IIF satellites. Only newer GPS satellites are capable of transmitting the L2C signal which is in quadrature to the legacy L2P(Y) signal being broadcast by all satellites. The data format RINEX-2 is not prepared to contain carrier phase observations of both L2 signals, but should contain either one or the other. If a mix of unaligned L2P(Y) and L2C carrier phase observations are stored in a RINEX-2 file, the quarter cycle bias causes the file to be defective and not usable for precise positioning purposes. Algorithms that detect such files are presented in this study. They are mainly based on the analysis of widelane fractional ambiguities and were applied to RINEX-2 files of 2624 reference stations. Seventy-two station files (2.7%) were found to be defective since they contained mixed and unaligned L2P(Y) and L2C carrier phase observations. If such files are used for precise positioning with ambiguities being fixed to integer values, resulting coordinate errors in long baselines can reach centimeter levels. Unaligned L2 observations often prevent ambiguity fixing, especially in short baselines. Full article
(This article belongs to the Section Remote Sensors)
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Open AccessArticle A Novel Beamforming Algorithm for GNSS Receivers with Dual-Polarized Sensitive Arrays in the Joint Space–Time-Polarization Domain
Sensors 2018, 18(12), 4506; https://doi.org/10.3390/s18124506
Received: 7 November 2018 / Revised: 13 December 2018 / Accepted: 18 December 2018 / Published: 19 December 2018
Cited by 1 | Viewed by 464 | PDF Full-text (6500 KB) | HTML Full-text | XML Full-text
Abstract
Dual-polarized sensitive arrays (DPSAs) with the space–time-polarization adaptive processing (STPAP) technique, which employs the polarization domain as well as the space domain and time domain to filter out interferences, can cancel a larger number of wideband interferences for GNSS receivers. However, the traditional [...] Read more.
Dual-polarized sensitive arrays (DPSAs) with the space–time-polarization adaptive processing (STPAP) technique, which employs the polarization domain as well as the space domain and time domain to filter out interferences, can cancel a larger number of wideband interferences for GNSS receivers. However, the traditional STPAP beamforming algorithm, which requires a separate adaptive filter for each GNSS satellite, will make the process computationally intensive as there are multiple GNSS satellites in the field of view (FOV). In order to overcome the shortcoming, a novel STPAP beamforming algorithm based on the minimum variance distortionless response (MVDR) criterion is proposed. Compared with the traditional STPAP beamforming algorithm, the proposed STPAP beamforming algorithm can process multiple GNSS satellites at once using only one adaptive filter, which will greatly reduce the computational complexity. Moreover, the proposed algorithm will not lead to a sharp deterioration in the output carrier-to-noise density ratio (C/N0) performance if the number of GNSS satellites processed in the same adaptive filter is proper. Furthermore, to calculate weight vector iteratively, an adaptive algorithm based on the constrained least mean square (CLMS) method is derived for the proposed STPAP beamforming algorithm. Simulation results validate that the proposed algorithm is effective in mitigating interferences for GNSS receivers in the joint space–time-polarization domain and meanwhile has lower computational complexity when maintaining the output C/N0 performance close to that of the traditional STPAP algorithm. Full article
(This article belongs to the Section Remote Sensors)
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Open AccessArticle A Long Time-Series Radiometric Normalization Method for Landsat Images
Sensors 2018, 18(12), 4505; https://doi.org/10.3390/s18124505
Received: 4 October 2018 / Revised: 7 December 2018 / Accepted: 12 December 2018 / Published: 19 December 2018
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Abstract
Radiometric normalization attempts to normalize the radiomimetic distortion caused by non-land surface-related factors, for example, different atmospheric conditions at image acquisition time and sensor factors, and to improve the radiometric consistency between remote sensing images. Using a remote sensing image and a reference [...] Read more.
Radiometric normalization attempts to normalize the radiomimetic distortion caused by non-land surface-related factors, for example, different atmospheric conditions at image acquisition time and sensor factors, and to improve the radiometric consistency between remote sensing images. Using a remote sensing image and a reference image as a pair is a traditional method of performing radiometric normalization. However, when applied to the radiometric normalization of long time-series of images, this method has two deficiencies: first, different pseudo-invariant features (PIFs)—radiometric characteristics of which do not change with time—are extracted in different pairs of images; and second, when processing an image based on a reference, we can minimize the residual between them, but the residual between temporally adjacent images may induce steep increases and decreases, which may conceal the information contained in the time-series indicators, such as vegetative index. To overcome these two problems, we propose an optimization strategy for radiometric normalization of long time-series of remote sensing images. First, the time-series gray-scale values for a pixel in the near-infrared band are sorted in ascending order and segmented into different parts. Second, the outliers and inliers of the time-series observation are determined using a modified Inflexion Based Cloud Detection (IBCD) method. Third, the variation amplitudes of the PIFs are smaller than for vegetation but larger than for water, and accordingly the PIFs are identified. Last, a novel optimization strategy aimed at minimizing the correction residual between the image to be processed and the images processed previously is adopted to determine the radiometric normalization sequence. Time-series images from the Thematic Mapper onboard Landsat 5 for Hangzhou City are selected for the experiments, and the results suggest that our method can effectively eliminate the radiometric distortion and preserve the variation of vegetation in the time-series of images. Smoother time-series profiles of gray-scale values and uniform root mean square error distributions can be obtained compared with those of the traditional method, which indicates that our method can obtain better radiometric consistency and normalization performance. Full article
(This article belongs to the Section Remote Sensors)
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Open AccessArticle A Wind Estimation Method with an Unmanned Rotorcraft for Environmental Monitoring Tasks
Sensors 2018, 18(12), 4504; https://doi.org/10.3390/s18124504
Received: 7 November 2018 / Revised: 16 December 2018 / Accepted: 18 December 2018 / Published: 19 December 2018
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Abstract
Wind velocity (strength and direction) is an important parameter for unmanned aerial vehicle (UAV)-based environmental monitoring tasks. A novel wind velocity estimation method is proposed for rotorcrafts. Based on an extended state observer, this method derives the wind disturbance from rotors’ speeds and [...] Read more.
Wind velocity (strength and direction) is an important parameter for unmanned aerial vehicle (UAV)-based environmental monitoring tasks. A novel wind velocity estimation method is proposed for rotorcrafts. Based on an extended state observer, this method derives the wind disturbance from rotors’ speeds and rotorcraft’s acceleration and position. Then the wind disturbance is scaled to calculate the airspeed vector, which is substituted into a wind triangle to obtain the wind velocity. Easy-to-implement methods for calculating the rotorcraft’s thrust and drag coefficient are also proposed, which are important parameters to obtain the wind drag and the airspeed, respectively. Simulations and experiments using a quadrotor in both hovering and flight conditions have validated the proposed method. Full article
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Open AccessArticle Early Detection of Freeze Damage in Navelate Oranges with Electrochemical Impedance Spectroscopy
Sensors 2018, 18(12), 4503; https://doi.org/10.3390/s18124503
Received: 16 October 2018 / Revised: 12 December 2018 / Accepted: 13 December 2018 / Published: 19 December 2018
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Abstract
The early detection of freeze damage in Navelate oranges (Citrus sinensis L. Osbeck) was studied using electrochemical impedance spectroscopy (EIS), which is associated with a specific double-needle sensor. The objective was to identify this problem early in order to help to determine when [...] Read more.
The early detection of freeze damage in Navelate oranges (Citrus sinensis L. Osbeck) was studied using electrochemical impedance spectroscopy (EIS), which is associated with a specific double-needle sensor. The objective was to identify this problem early in order to help to determine when a freeze phenomenon occurs. Thus, we selected a set of Navelate oranges without external defects, belonging to the same batch. Next, an intense cold process was simulated to analyze the oranges before and after freezing. The results of the spectroscopy analysis revealed different signals for oranges depending on whether they had experienced freezing or not. Principal Component Analysis (PCA) and Partial Least Squares-Discriminant Analysis (PLS-DA) of the obtained data demonstrated that it is possible to discriminate the samples, explaining 88.5% of the total variability (PCA) and being able to design a mathematical model with a prediction sensitivity of 80% (PLS-DA). Additionally, a designed artificial neural network (ANN) prediction model managed to correctly classify 100% of the studied samples. Therefore, EIS together with ANN-based data treatment is proposed as a viable alternative to the traditional techniques for the early detection of freeze damage in oranges. Full article
(This article belongs to the Section Chemical Sensors)
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Open AccessArticle Efficient Fiducial Point Detection of ECG QRS Complex Based on Polygonal Approximation
Sensors 2018, 18(12), 4502; https://doi.org/10.3390/s18124502
Received: 20 November 2018 / Revised: 10 December 2018 / Accepted: 13 December 2018 / Published: 19 December 2018
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Abstract
Electrocardiogram signal analysis is based on detecting a fiducial point consisting of the onset, offset, and peak of each waveform. The accurate diagnosis of arrhythmias depends on the accuracy of fiducial point detection. Detecting the onset and offset fiducial points is ambiguous because [...] Read more.
Electrocardiogram signal analysis is based on detecting a fiducial point consisting of the onset, offset, and peak of each waveform. The accurate diagnosis of arrhythmias depends on the accuracy of fiducial point detection. Detecting the onset and offset fiducial points is ambiguous because the feature values are similar to those of the surrounding sample. To improve the accuracy of this paper’s fiducial point detection, the signal is represented by a small number of vertices through a curvature-based vertex selection technique using polygonal approximation. The proposed method minimizes the number of candidate samples for fiducial point detection and emphasizes these sample’s feature values to enable reliable detection. It is also sensitive to the morphological changes of various QRS complexes by generating an accumulated signal of the amplitude change rate between vertices as an auxiliary signal. To verify the superiority of the proposed algorithm, error distribution is measured through comparison with the QT-DB annotation provided by Physionet. The mean and standard deviation of the onset and the offset were stable as 4.02 ± 7.99 ms and 5.45 ± 8.04 ms, respectively. The results show that proposed method using small number of vertices is acceptable in practical applications. We also confirmed that the proposed method is effective through the clustering of the QRS complex. Experiments on the arrhythmia data of MIT-BIH ADB confirmed reliable fiducial point detection results for various types of QRS complexes. Full article
(This article belongs to the Special Issue Sensor Signal and Information Processing II)
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Open AccessArticle Validation of an Inertial Sensor Algorithm to Quantify Head and Trunk Movement in Healthy Young Adults and Individuals with Mild Traumatic Brain Injury
Sensors 2018, 18(12), 4501; https://doi.org/10.3390/s18124501
Received: 20 October 2018 / Revised: 10 December 2018 / Accepted: 16 December 2018 / Published: 19 December 2018
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Abstract
Wearable inertial measurement units (IMUs) may provide useful, objective information to clinicians interested in quantifying head movements as patients’ progress through vestibular rehabilitation. The purpose of this study was to validate an IMU-based algorithm against criterion data (motion capture) to estimate average head [...] Read more.
Wearable inertial measurement units (IMUs) may provide useful, objective information to clinicians interested in quantifying head movements as patients’ progress through vestibular rehabilitation. The purpose of this study was to validate an IMU-based algorithm against criterion data (motion capture) to estimate average head and trunk range of motion (ROM) and average peak velocity. Ten participants completed two trials of standing and walking tasks while moving the head with and without moving the trunk. Validity was assessed using a combination of Intra-class Correlation Coefficients (ICC), root mean square error (RMSE), and percent error. Bland-Altman plots were used to assess bias. Excellent agreement was found between the IMU and criterion data for head ROM and peak rotational velocity (average ICC > 0.9). The trunk showed good agreement for most conditions (average ICC > 0.8). Average RMSE for both ROM (head = 2.64°; trunk = 2.48°) and peak rotational velocity (head = 11.76 °/s; trunk = 7.37 °/s) was low. The average percent error was below 5% for head and trunk ROM and peak rotational velocity. No clear pattern of bias was found for any measure across conditions. Findings suggest IMUs may provide a promising solution for estimating head and trunk movement, and a practical solution for tracking progression throughout rehabilitation or home exercise monitoring. Full article
(This article belongs to the Special Issue Sensors for Gait, Posture, and Health Monitoring)
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Open AccessArticle Vehicle-Type Detection Based on Compressed Sensing and Deep Learning in Vehicular Networks
Sensors 2018, 18(12), 4500; https://doi.org/10.3390/s18124500
Received: 10 November 2018 / Revised: 14 December 2018 / Accepted: 17 December 2018 / Published: 19 December 2018
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Abstract
Throughout the past decade, vehicular networks have attracted a great deal of interest in various fields. The increasing number of vehicles has led to challenges in traffic regulation. Vehicle-type detection is an important research topic that has found various applications in numerous fields. [...] Read more.
Throughout the past decade, vehicular networks have attracted a great deal of interest in various fields. The increasing number of vehicles has led to challenges in traffic regulation. Vehicle-type detection is an important research topic that has found various applications in numerous fields. Its main purpose is to extract the different features of vehicles from videos or pictures captured by traffic surveillance so as to identify the types of vehicles, and then provide reference information for traffic monitoring and control. In this paper, we propose a step-forward vehicle-detection and -classification method using a saliency map and the convolutional neural-network (CNN) technique. Specifically, compressed-sensing (CS) theory is applied to generate the saliency map to label the vehicles in an image, and the CNN scheme is then used to classify them. We applied the concept of the saliency map to search the image for target vehicles: this step is based on the use of the saliency map to minimize redundant areas. CS was used to measure the image of interest and obtain its saliency in the measurement domain. Because the data in the measurement domain are much smaller than those in the pixel domain, saliency maps can be generated at a low computation cost and faster speed. Then, based on the saliency map, we identified the target vehicles and classified them into different types using the CNN. The experimental results show that our method is able to speed up the window-calibrating stages of CNN-based image classification. Moreover, our proposed method has better overall performance in vehicle-type detection compared with other methods. It has very broad prospects for practical applications in vehicular networks. Full article
(This article belongs to the Special Issue Advances on Vehicular Networks: From Sensing to Autonomous Driving)
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Open AccessArticle Components of Artificial Neural Networks Realized in CMOS Technology to be Used in Intelligent Sensors in Wireless Sensor Networks
Sensors 2018, 18(12), 4499; https://doi.org/10.3390/s18124499
Received: 6 November 2018 / Revised: 10 December 2018 / Accepted: 17 December 2018 / Published: 19 December 2018
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Abstract
The article presents novel hardware solutions for new intelligent sensors that can be used in wireless sensor networks (WSN). A substantial reduction of the amount of data sent by the sensor to the base station in the WSN may extend the possible sensor [...] Read more.
The article presents novel hardware solutions for new intelligent sensors that can be used in wireless sensor networks (WSN). A substantial reduction of the amount of data sent by the sensor to the base station in the WSN may extend the possible sensor working time. Miniature integrated artificial neural networks (ANN) applied directly in the sensor can take over the analysis of data collected from the environment, thus reducing amount of data sent over the RF communication block. A prototype specialized chip with components of the ANN was designed in the CMOS 130 nm technology. An adaptation mechanism and a programmable multi-phase clock generator—components of the ANN—are described in more detail. Both simulation and measurement results of selected blocks are presented to demonstrate the correctness of the design. Full article
(This article belongs to the Section Sensor Networks)
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Open AccessArticle Chirp-Based FHSS Receiver with Recursive Symbol Synchronization for Underwater Acoustic Communication
Sensors 2018, 18(12), 4498; https://doi.org/10.3390/s18124498
Received: 18 October 2018 / Revised: 10 December 2018 / Accepted: 11 December 2018 / Published: 19 December 2018
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Abstract
In this paper, we propose a covert underwater acoustic communication method that is robust to fading using a chirp signal combined with a frequency-hopping spread spectrum scheme. A fractional Fourier transform, which estimates the slope of the signal frequency variation, is applied to [...] Read more.
In this paper, we propose a covert underwater acoustic communication method that is robust to fading using a chirp signal combined with a frequency-hopping spread spectrum scheme. A fractional Fourier transform, which estimates the slope of the signal frequency variation, is applied to the receiver to enable a robust and reliable symbol estimation with respect to the frequency and irregular phase variations. In addition, since the recursive symbol synchronization can be implemented using a chirp signal, compression and expansion effects due to the Doppler shift can be mitigated. Simulation and lake trials were performed to verify the performance of the proposed method. The simulation was performed by two different methods. Full article
(This article belongs to the Section Physical Sensors)
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Open AccessArticle A Robust Approach to TDMA Synchronization in Aerial Networks
Sensors 2018, 18(12), 4497; https://doi.org/10.3390/s18124497
Received: 10 November 2018 / Revised: 13 December 2018 / Accepted: 15 December 2018 / Published: 19 December 2018
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Abstract
Unmanned Aerial Vehicles (UAVs) can be a powerful tool for live (interactive) remote inspection of large-scale structures or areas of interest. Instead of manual, local, and labor-intensive inspections, we envision human operators working together with networks of semi-autonomous UAVs. The current state-of-the-art for [...] Read more.
Unmanned Aerial Vehicles (UAVs) can be a powerful tool for live (interactive) remote inspection of large-scale structures or areas of interest. Instead of manual, local, and labor-intensive inspections, we envision human operators working together with networks of semi-autonomous UAVs. The current state-of-the-art for low-delay high-throughput inter-vehicle networking relies on Time-Division Multiple Access (TDMA) techniques that require accurate synchronization among all network nodes. In this paper, we propose a delay-tolerant synchronization approach that converges to the correct order of the TDMA slots implemented over COTS WiFi in a fully-distributed way and without resorting to a global clock. This highly flexible solution allows building an ad-hoc aerial network based on a backbone of relaying UAVs. We show several alternatives to achieve this synchronization in a concrete aerial network and compare them in terms of slots’ overlap, throughput, and packet delivery. The results show that these alternatives lead to trade-offs in the referenced metrics. The results also provide insight into the delays caused by buffering in the protocol stack and especially in the WiFi interface. Full article
(This article belongs to the Special Issue Design and Implementation of Future CPS)
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Open AccessArticle Feasibility Analysis on the Use of Ultrasonic Communications for Body Sensor Networks
Sensors 2018, 18(12), 4496; https://doi.org/10.3390/s18124496
Received: 31 October 2018 / Revised: 12 December 2018 / Accepted: 17 December 2018 / Published: 19 December 2018
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Abstract
Ultrasonic waves have good propagation in the human body and have been widely applied in biomedical device design without any reported side effects. Therefore, ultrasonic waves can provide an alternative method as an information carrier for body sensor networks (BSNs). This paper presents [...] Read more.
Ultrasonic waves have good propagation in the human body and have been widely applied in biomedical device design without any reported side effects. Therefore, ultrasonic waves can provide an alternative method as an information carrier for body sensor networks (BSNs). This paper presents a novel wireless communication method that uses ultrasonic sound waves as a medium for healthcare systems. We investigated the feasibility of our proposal by testing it in a real digital communication experimental setup. To find an acceptable modulation method, the functionality of the proposed ultrasound-based digital communication approach was tested involving three principal modulation methods: amplitude shift keying (ASK), frequency shift keying (FSK), and phase shift keying (PSK). The modulated digital signals obtained from the experiments were compared with the simulated signals. Analysis of the results shows that ultrasonic waves are feasible and can be used for digital communication. Full article
(This article belongs to the Special Issue Wireless Body Area Networks and Connected Health)
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Open AccessArticle Fast Measurement of Magnetostriction Coefficients for Silicon Steel Strips Using Magnetostriction-Based EMAT
Sensors 2018, 18(12), 4495; https://doi.org/10.3390/s18124495
Received: 16 November 2018 / Revised: 11 December 2018 / Accepted: 12 December 2018 / Published: 19 December 2018
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Abstract
Strain gauges and optical methods are commonly used to measure the magnetostriction coefficient of a sample. All these methods require a specific size sample and can only realize offline measurement, which is time-consuming. Therefore, we propose a new method using a magnetostriction-based electromagnetic [...] Read more.
Strain gauges and optical methods are commonly used to measure the magnetostriction coefficient of a sample. All these methods require a specific size sample and can only realize offline measurement, which is time-consuming. Therefore, we propose a new method using a magnetostriction-based electromagnetic acoustic transducer (EMAT) to measure the magnetostriction coefficient. The amplitude of the ultrasonic waves generated by the EMAT is applied to characterize the magnetostriction coefficient of a sample. A nonlinear magnetostriction finite element model is established, and the simulation results show that the amplitude of the ultrasonic wave generated by the magnetostriction-based EMAT is proportional to the magnetostriction coefficient of the material. Experiments are carried out on silicon steel strips with different silicon contents. The results show that the method can effectively measure their relative magnetostriction coefficients. Furthermore, the structure of the magnetostriction-based EMAT is optimized to maximize efficiency. The excitation and receiving transducers reach their maximum efficiency when the static magnetic flux densities are 3.5 mT and 6.8 mT, respectively. Moreover, the relative error caused by the vibration reaches the minimal size when the lift-off of the receiving coil is set to 3 mm around. This method is fast and can be applied to online measurement. Full article
(This article belongs to the Special Issue Ultrasound Transducers)
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Open AccessArticle A Software Defined Radio Evaluation Platform for WBAN Systems
Sensors 2018, 18(12), 4494; https://doi.org/10.3390/s18124494
Received: 31 October 2018 / Revised: 29 November 2018 / Accepted: 15 December 2018 / Published: 19 December 2018
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Abstract
In recent years, the Wireless Body Area Network (WBAN) concept has attracted significant academic and industrial attention. WBAN specifies a network dedicated to collecting personal biomedical data from advanced sensors that are then used for health and lifestyle purposes. In 2012, the 802.15.6 [...] Read more.
In recent years, the Wireless Body Area Network (WBAN) concept has attracted significant academic and industrial attention. WBAN specifies a network dedicated to collecting personal biomedical data from advanced sensors that are then used for health and lifestyle purposes. In 2012, the 802.15.6 WBAN standard was released by the Institute of Electrical and Electronics Engineers (IEEE), which regulates and specifies the configurations of WBAN. Compared to the prevailing wireless communication technologies such as Bluetooth and ZigBee, the WBAN standard has the advantages of ultra-low power consumption, high reliability, and high-security protection while transmitting sensitive personal data. Based on the standard specification, several implementations have been published. However, in terms of evaluation, different designs were implemented in proprietary evaluation environments, which may lead to unfair comparison. In this paper, a Software-Defined Radio (SDR) evaluation platform for WBAN systems is proposed to evaluate the RF channel specified in the IEEE 802.15.6 standard. A narrowband communication protocol demonstration with a security scheme in WBAN has been performed to successfully validate the design in the proposed evaluation platform. Full article
(This article belongs to the Special Issue Wireless Body Area Networks and Connected Health)
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Open AccessArticle Versatile Protein-A Coated Photoelectric Immunosensors with a Purple-Membrane Monolayer Transducer Fabricated by Affinity-Immobilization on a Graphene-Oxide Complexed Linker and by Shear Flow
Sensors 2018, 18(12), 4493; https://doi.org/10.3390/s18124493
Received: 11 November 2018 / Revised: 6 December 2018 / Accepted: 17 December 2018 / Published: 18 December 2018
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Abstract
Bacteriorhodopsin-embedded purple membranes (PM) have been demonstrated to be a sensitive photoelectric transducer for microbial detection. To efficiently prepare versatile BR-based immunosensors with protein A as antibody captures, a large, high-coverage, and uniformly oriented PM monolayer was fabricated on an electrode as an [...] Read more.
Bacteriorhodopsin-embedded purple membranes (PM) have been demonstrated to be a sensitive photoelectric transducer for microbial detection. To efficiently prepare versatile BR-based immunosensors with protein A as antibody captures, a large, high-coverage, and uniformly oriented PM monolayer was fabricated on an electrode as an effective foundation for protein A conjugation through bis-NHS esters, by first affinity-coating biotinylated PM on an aminated surface using a complex of oxidized avidin and graphene oxide as the planar linker and then washing the coating with a shear flow. Three different polyclonal antibodies, each against Escherichia coli, Lactobacillus acidophilus, and Streptococcus mutans, respectively, were individually, effectively and readily adsorbed on the protein A coated electrodes, leading to selective and sensitive quantitative detection of their respective target cells in a single step without any labeling. A single-cell detection limit was achieved for the former two cells. AFM, photocurrent, and Raman analyses all displayed each fabricated layer as well as the captured bacteria, with AFM particularly revealing the formation of a massive continuous PM monolayer on aminated mica. The facile cell-membrane monolayer fabrication and membrane surface conjugation techniques disclosed in this study may be widely applied to the preparation of different biomembrane-based biosensors. Full article
(This article belongs to the Section Biosensors)
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Open AccessArticle Coil Inductance Model Based Solenoid on–off Valve Spool Displacement Sensing via Laser Calibration
Sensors 2018, 18(12), 4492; https://doi.org/10.3390/s18124492
Received: 20 October 2018 / Revised: 13 December 2018 / Accepted: 17 December 2018 / Published: 18 December 2018
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Abstract
Direct acting solenoid on–off valves are key fluid power components whose efficiency is dependent upon the state of the spool’s axial motion. By sensing the trajectory of the valve spool, more efficient control schemes can be implemented. Therefore, the goal of this study [...] Read more.
Direct acting solenoid on–off valves are key fluid power components whose efficiency is dependent upon the state of the spool’s axial motion. By sensing the trajectory of the valve spool, more efficient control schemes can be implemented. Therefore, the goal of this study is to derive an analytical model for spool displacement sensing based on coil inductance. First, a mathematical model of the coil inductance as a function of air gap width and lumped magnetic reluctance is derived. Second, to solve the inductance from coil current, an optimization to obtain an initial value based on physical constraints is proposed. Furthermore, an experiment using a laser triangulation sensor is designed to correlate the magnetic reluctance to the air gap. Lastly, using the obtained empirical reluctance model to eliminate unknowns from the proposed air gap-inductance model, the model in atmosphere or hydraulic oil environments was tested. Initial results showed that the proposed model is capable of calculating the spool displacement based on the coil current, and the estimation errors compared to the laser measurement are within ±7% in air environment. Full article
(This article belongs to the Special Issue Laser Sensors for Displacement, Distance and Position)
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Open AccessArticle Design of a Piezoelectric Multilayered Structure for Ultrasound Sensors Using the Equivalent Circuit Method
Sensors 2018, 18(12), 4491; https://doi.org/10.3390/s18124491
Received: 29 October 2018 / Revised: 15 December 2018 / Accepted: 17 December 2018 / Published: 18 December 2018
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Abstract
This study investigates the electroacoustic behavior of a piezoelectric multilayered structure for ultrasonic sensors using the equivalent circuit method (ECM). We first derived the vertical deflection of the multilayered structure as a function of pressure and voltage using equilibrium equations of the structure. [...] Read more.
This study investigates the electroacoustic behavior of a piezoelectric multilayered structure for ultrasonic sensors using the equivalent circuit method (ECM). We first derived the vertical deflection of the multilayered structure as a function of pressure and voltage using equilibrium equations of the structure. The deflection derived in this work is novel in that it includes the effect of piezoelectricity as well as the external pressure on the radiating surface. Subsequently, the circuit parameters were derived from the vertical deflection. The acoustic characteristics of the structure were then analyzed using the electro-acoustical model of an ultrasonic sensor for in-air application. Using the equivalent circuit, we analyzed the effects of various structural parameters on the acoustic properties of the structure such as resonance frequency, radiated sound pressure, and beam pattern. The validity of the ECM was verified initially by comparing the results with those from the finite element analysis (FEA) of the same structure. Furthermore, experimental testing of an actual ultrasonic sensor was carried out to verify the efficacy of the ECM. The ECM presented in this study can estimate the performance characteristics of a piezoelectric multilayered structure with high rapidity and efficiency. Full article
(This article belongs to the Special Issue Ultrasound Transducers)
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Open AccessArticle Electrochemical Instrumentation of an Embedded Potentiostat System (EPS) for a Programmable-System-On-a-Chip
Sensors 2018, 18(12), 4490; https://doi.org/10.3390/s18124490
Received: 2 October 2018 / Revised: 20 November 2018 / Accepted: 20 November 2018 / Published: 18 December 2018
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Abstract
Under the main features required on portable devices in electrochemical instrumentation is to have a small size, low power consumption, economically affordable and precision in the measurements. This paper describes the development of a programmable Embedded Potentiostat System (EPS) capable of performing electrochemical [...] Read more.
Under the main features required on portable devices in electrochemical instrumentation is to have a small size, low power consumption, economically affordable and precision in the measurements. This paper describes the development of a programmable Embedded Potentiostat System (EPS) capable of performing electrochemical sensing over system-on-a-chip platforms. Furthermore, the study explains a circuit design and develops some validation of the entire system. The hardware validation is performed by electrochemical experiments such as Double Step Chronoamperometry (DSC), Linear Sweep Voltammetry (LSV) and Cyclic Voltammetry (CV); moreover, a comparison of the experimental signals between a commercial potentiostat and the EPS was done by analysis of errors on the response signal. Results illustrate that the EPS is capable of handling currents in the range of absolute values of 86.44 to 3000 nA and having control voltages in the range of ±2 V. The device can support from 50 to 2000 samples per second. The EPS capabilities were compared with other compact potentiostats. The programmable EPS is an original approach which hugely reduces the hardware complexity and leads the way to create new applications for Point-of-Care or industrial developments with a reusable full electronics module. Full article
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Open AccessArticle A Tunable Plasmonic Refractive Index Sensor with Nanoring-Strip Graphene Arrays
Sensors 2018, 18(12), 4489; https://doi.org/10.3390/s18124489
Received: 25 October 2018 / Revised: 1 December 2018 / Accepted: 12 December 2018 / Published: 18 December 2018
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Abstract
In the present study, we design a tunable plasmonic refractive index sensor with nanoring-strip graphene arrays. The calculations prove that the nanoring-strip have two transmission dips. By changing the strip length L of the present structure, we find that the nanoring-strip graphene arrays [...] Read more.
In the present study, we design a tunable plasmonic refractive index sensor with nanoring-strip graphene arrays. The calculations prove that the nanoring-strip have two transmission dips. By changing the strip length L of the present structure, we find that the nanoring-strip graphene arrays have a wide range of resonances (resonance wavelength increases from 17.73 μm to 28.15 μm). When changing the sensing medium refractive index nmed, the sensitivity of mode A and B can reach 2.97 μm/RIU and 5.20 μm/RIU. By changing the doping level ng, we notice that the transmission characteristics can be tuned flexibly. Finally, the proposed sensor also shows good angle tolerance for both transverse magnetic (TM) and transverse electric (TE) polarizations. The proposed nanoring-strip graphene arrays along with the numerical results could open a new avenue to realize various tunable plasmon devices and have a great application prospect in biosensing, detection, and imaging. Full article
(This article belongs to the Section Sensor Materials)
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Open AccessArticle CMOS Current Feedback Operational Amplifier-Based Relaxation Generator for Capacity to Voltage Sensor Interface
Sensors 2018, 18(12), 4488; https://doi.org/10.3390/s18124488
Received: 2 November 2018 / Revised: 14 December 2018 / Accepted: 16 December 2018 / Published: 18 December 2018
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Abstract
This paper presents a simple relaxation generator, suitable for a sensor interface, operating as a transducer of capacitance to frequency/period. The proposed circuit employs a current feedback operational amplifier, fabricated in I3T25 0.35 μm ON Semiconductor CMOS process, and four passive elements [...] Read more.
This paper presents a simple relaxation generator, suitable for a sensor interface, operating as a transducer of capacitance to frequency/period. The proposed circuit employs a current feedback operational amplifier, fabricated in I3T25 0.35 μ m ON Semiconductor CMOS process, and four passive elements including a grounded capacitor (the sensed parameter). It offers a low-impedance voltage output of the generated square wave. Additional frequency to DC voltage converter offers output information in the form of voltage. The experimental capacitance variation from 6.8 nF to 100 nF yields voltage change in the range from 21 mV to 106 mV with error below 5% and sensitivity 0.912 mV/nF evaluated over the full range of change. These values are in good agreement with simulation results obtained from the Mathcad model of frequency to DC voltage transducer passive circuit. Full article
(This article belongs to the Section Physical Sensors)
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Open AccessArticle SVM Optimization for Brain Tumor Identification Using Infrared Spectroscopic Samples
Sensors 2018, 18(12), 4487; https://doi.org/10.3390/s18124487
Received: 24 November 2018 / Revised: 14 December 2018 / Accepted: 15 December 2018 / Published: 18 December 2018
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Abstract
The work presented in this paper is focused on the use of spectroscopy to identify the type of tissue of human brain samples employing support vector machine classifiers. Two different spectrometers were used to acquire infrared spectroscopic signatures in the wavenumber range between [...] Read more.
The work presented in this paper is focused on the use of spectroscopy to identify the type of tissue of human brain samples employing support vector machine classifiers. Two different spectrometers were used to acquire infrared spectroscopic signatures in the wavenumber range between 1200–3500 cm−1. An extensive analysis was performed to find the optimal configuration for a support vector machine classifier and determine the most relevant regions of the spectra for this particular application. The results demonstrate that the developed algorithm is robust enough to classify the infrared spectroscopic data of human brain tissue at three different discrimination levels. Full article
(This article belongs to the Special Issue Biomedical Infrared Imaging: From Sensors to Applications)
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Open AccessArticle Answering the Min-Cost Quality-Aware Query on Multi-Sources in Sensor-Cloud Systems
Sensors 2018, 18(12), 4486; https://doi.org/10.3390/s18124486
Received: 4 November 2018 / Revised: 10 December 2018 / Accepted: 11 December 2018 / Published: 18 December 2018
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Abstract
In sensor-based systems, the data of an object is often provided by multiple sources. Since the data quality of these sources might be different, when querying the observations, it is necessary to carefully select the sources to make sure that high quality data [...] Read more.
In sensor-based systems, the data of an object is often provided by multiple sources. Since the data quality of these sources might be different, when querying the observations, it is necessary to carefully select the sources to make sure that high quality data is accessed. A solution is to perform a quality evaluation in the cloud and select a set of high-quality, low-cost data sources (i.e., sensors or small sensor networks) that can answer queries. This paper studies the problem of min-cost quality-aware query which aims to find high quality results from multi-sources with the minimized cost. The measurement of the query results is provided, and two methods for answering min-cost quality-aware query are proposed. How to get a reasonable parameter setting is also discussed. Experiments on real-life data verify that the proposed techniques are efficient and effective. Full article
(This article belongs to the Special Issue Fog/Edge Computing-Based Smart Sensing System)
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Open AccessArticle An RFID-Based Sensor for Masonry Crack Monitoring
Sensors 2018, 18(12), 4485; https://doi.org/10.3390/s18124485
Received: 11 November 2018 / Revised: 14 December 2018 / Accepted: 17 December 2018 / Published: 18 December 2018
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Abstract
A radio frequency identifier (RFID) tag sensor for the real time monitoring of cracks in civil engineering building is presented in this work. The RFID tag is equipped with a piezoelectric sensor able to detect small movements of crack in order to prevent [...] Read more.
A radio frequency identifier (RFID) tag sensor for the real time monitoring of cracks in civil engineering building is presented in this work. The RFID tag is equipped with a piezoelectric sensor able to detect small movements of crack in order to prevent collapses of buildings or civil engineering structures. The information is delivered by using the modulated scattering technique (MST) which permits to obtain high operative ranges. The sensor is passive, the power supply is provided by means of a suitable rect-antenna and a Chockcroft-Walton multiplier circuit powered by means of the impinging interrogating electromagnetic wave. A system prototype, operating in the X band at 10 GHz, has been designed fabricated and experimentally assessed in a realistic scenario obtaining promising results. Full article
(This article belongs to the Special Issue RFID-Based Sensors for IoT Applications)
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Open AccessArticle Application of Convolutional Long Short-Term Memory Neural Networks to Signals Collected from a Sensor Network for Autonomous Gas Source Localization in Outdoor Environments
Sensors 2018, 18(12), 4484; https://doi.org/10.3390/s18124484
Received: 7 November 2018 / Revised: 3 December 2018 / Accepted: 13 December 2018 / Published: 18 December 2018
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Abstract
Convolutional Long Short-Term Memory Neural Networks (CNN-LSTM) are a variant of recurrent neural networks (RNN) that can extract spatial features in addition to classifying or making predictions from sequential data. In this paper, we analyzed the use of CNN-LSTM for gas source localization [...] Read more.
Convolutional Long Short-Term Memory Neural Networks (CNN-LSTM) are a variant of recurrent neural networks (RNN) that can extract spatial features in addition to classifying or making predictions from sequential data. In this paper, we analyzed the use of CNN-LSTM for gas source localization (GSL) in outdoor environments using time series data from a gas sensor network and anemometer. CNN-LSTM is used to estimate the location of a gas source despite the challenges created from inconsistent airflow and gas distribution in outdoor environments. To train CNN-LSTM for GSL, we used temporal data taken from a 5 × 6 metal oxide semiconductor (MOX) gas sensor array, spaced 1.5 m apart, and an anemometer placed in the center of the sensor array in an open area outdoors. The output of the CNN-LSTM is one of thirty cells approximating the location of a gas source. We show that by using CNN-LSTM, we were able to determine the location of a gas source from sequential data. In addition, we compared several artificial neural network (ANN) architectures as well as trained them without wind vector data to estimate the complexity of the task. We found that ANN is a promising prospect for GSL tasks. Full article
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Open AccessArticle Design, Implementation and Validation of a GNSS Measurement Exclusion and Weighting Function with a Dual Polarized Antenna
Sensors 2018, 18(12), 4483; https://doi.org/10.3390/s18124483
Received: 15 October 2018 / Revised: 7 December 2018 / Accepted: 14 December 2018 / Published: 18 December 2018
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Abstract
Global Navigation Satellite Systems (GNSSs) have become a ubiquitous tool for our modern society to carry out vital tasks such as transportation, civil engineering or precision agriculture. This breath has reached the realm of safety-critical applications such as time management of critical infrastructures [...] Read more.
Global Navigation Satellite Systems (GNSSs) have become a ubiquitous tool for our modern society to carry out vital tasks such as transportation, civil engineering or precision agriculture. This breath has reached the realm of safety-critical applications such as time management of critical infrastructures or autonomous vehicles, in which GNSS is an essential tool nowadays. Unfortunately, current GNSS performance is not enough to fulfill the requirements of these professional and critical applications. For this reason, the FANTASTIC project was launched to boost the adoption of these applications. The project was funded by the European GNSS agency (GSA) in order to enhance the robustness and accuracy of GNSS in harsh environments. This paper presents the part related to the development of a weighting and exclusion function with a dual circularly polarized antenna. The idea is to reduce the effects of multipath by weighting and/or excluding those measurements affected by multipath. The observables and other metrics obtained from a dual polarized antenna will be exploited to define an exclusion threshold and to provide the weights. Real-world experiments will show the improvement in the positioning solution, using all available constellations, obtained with the developed technique. Full article
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Open AccessArticle A Novel Approach for Partial Discharge Measurements on GIS Using HFCT Sensors
Sensors 2018, 18(12), 4482; https://doi.org/10.3390/s18124482
Received: 18 October 2018 / Revised: 7 December 2018 / Accepted: 12 December 2018 / Published: 18 December 2018
Cited by 2 | Viewed by 480 | PDF Full-text (6527 KB) | HTML Full-text | XML Full-text
Abstract
This paper presents a novel measuring system for partial discharge (PD) measurements in Gas Insulated Systems (GIS) using high frequency current transformers (HFCT). The system is based on the measurement of the induced PD currents in the GIS enclosure. In opposition to the [...] Read more.
This paper presents a novel measuring system for partial discharge (PD) measurements in Gas Insulated Systems (GIS) using high frequency current transformers (HFCT). The system is based on the measurement of the induced PD currents in the GIS enclosure. In opposition to the existing antenna technologies that measure the radiated energy in the very high frequency/ultra-high frequency (VHF/UHF) range, the proposed system measures the PD conducted currents in the high frequency (HF) range and below. The foundation of the measurements together with a detailed explanation of the sensor installed conveniently at the bolts of the GIS spacer are presented. An experimental study on the current distribution in the GIS enclosure is described to evaluate the impact of the sensor on the measurements. Laboratory experiments have been performed that show the suitability of this method to properly measure particle discharges caused by corona, surface and free moving particle discharges in SF6. Discharges in the range of 1 to 4 pC have been properly measured. An analysis to evaluate the performance of the method is shown, in comparison to VHF/UHF antenna measurements. The potential benefits of this novel technique rely on the small attenuation of PD signals in the GIS components in the HF range and sample rate reductions. Finally, a discussion on the potential applicability of present cluster and charge calculation techniques to the proposed PD GIS measurement using HFCT is presented. Full article
(This article belongs to the Special Issue UHF and RF Sensor Technology for Partial Discharge Detection)
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Open AccessArticle Secure and Efficient Three-Factor Protocol for Wireless Sensor Networks
Sensors 2018, 18(12), 4481; https://doi.org/10.3390/s18124481
Received: 8 November 2018 / Revised: 12 December 2018 / Accepted: 14 December 2018 / Published: 18 December 2018
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Abstract
Wireless sensor networks are widely used in many applications such as environmental monitoring, health care, smart grid and surveillance. Many security protocols have been proposed and intensively studied due to the inherent nature of wireless networks. In particular, Wu et al. proposed a [...] Read more.
Wireless sensor networks are widely used in many applications such as environmental monitoring, health care, smart grid and surveillance. Many security protocols have been proposed and intensively studied due to the inherent nature of wireless networks. In particular, Wu et al. proposed a promising authentication scheme which is sufficiently robust against various attacks. However, according to our analysis, Wu et al.’s scheme has two serious security weaknesses against malicious outsiders. First, their scheme can lead to user impersonation attacks. Second, user anonymity is not preserved in their scheme. In this paper, we present these vulnerabilities of Wu et al.’s scheme in detail. We also propose a new scheme to complement their weaknesses. We improve and speed up the vulnerability of the Wu et al. scheme. Security analysis is analyzed by Proverif and informal analysis is performed for various attacks. Full article
(This article belongs to the Section Sensor Networks)
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Open AccessArticle Sudden Event Monitoring of Civil Infrastructure Using Demand-Based Wireless Smart Sensors
Sensors 2018, 18(12), 4480; https://doi.org/10.3390/s18124480
Received: 18 November 2018 / Revised: 11 December 2018 / Accepted: 14 December 2018 / Published: 18 December 2018
Cited by 1 | Viewed by 659 | PDF Full-text (6565 KB) | HTML Full-text | XML Full-text
Abstract
Wireless smart sensors (WSS) have been proposed as an effective means to reduce the high cost of wired structural health monitoring systems. However, many damage scenarios for civil infrastructure involve sudden events, such as strong earthquakes, which can result in damage or even [...] Read more.
Wireless smart sensors (WSS) have been proposed as an effective means to reduce the high cost of wired structural health monitoring systems. However, many damage scenarios for civil infrastructure involve sudden events, such as strong earthquakes, which can result in damage or even failure in a matter of seconds. Wireless monitoring systems typically employ duty cycling to reduce power consumption; hence, they will miss such events if they are in power-saving sleep mode when the events occur. This paper develops a demand-based WSS to meet the requirements of sudden event monitoring with minimal power budget and low response latency, without sacrificing high-fidelity measurements or risking a loss of critical information. In the proposed WSS, a programmable event-based switch is implemented utilizing a low-power trigger accelerometer; the switch is integrated in a high-fidelity sensor platform. Particularly, the approach can rapidly turn on the WSS upon the occurrence of a sudden event and seamlessly transition from low-power acceleration measurement to high-fidelity data acquisition. The capabilities of the proposed WSS are validated through laboratory and field experiments. The results show that the proposed approach is able to capture the occurrence of sudden events and provide high-fidelity data for structural condition assessment in an efficient manner. Full article
(This article belongs to the Special Issue Smart Sensors for Structural Health Monitoring)
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Open AccessArticle Determination of HPLC-UV Fingerprints of Spanish Paprika (Capsicum annuum L.) for Its Classification by Linear Discriminant Analysis
Sensors 2018, 18(12), 4479; https://doi.org/10.3390/s18124479
Received: 29 November 2018 / Revised: 11 December 2018 / Accepted: 16 December 2018 / Published: 18 December 2018
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Abstract
The development of a simple HPLC-UV method towards the evaluation of Spanish paprika’s phenolic profile and their discrimination based on the former is reported herein. The approach is based on C18 reversed-phase chromatography to generate characteristic fingerprints, in combination with linear discriminant [...] Read more.
The development of a simple HPLC-UV method towards the evaluation of Spanish paprika’s phenolic profile and their discrimination based on the former is reported herein. The approach is based on C18 reversed-phase chromatography to generate characteristic fingerprints, in combination with linear discriminant analysis (LDA) to achieve their classification. To this aim, chromatographic conditions were optimized so as to achieve the separation of major phenolic compounds already identified in paprika. Paprika samples were subjected to a sample extraction stage by sonication and centrifugation; extracting procedure and conditions were optimized to maximize the generation of enough discriminant fingerprints. Finally, chromatograms were baseline corrected, compressed employing fast Fourier transform (FFT), and then analyzed by means of principal component analysis (PCA) and LDA to carry out the classification of paprika samples. Under the developed procedure, a total of 96 paprika samples were analyzed, achieving a classification rate of 100% for the test subset (n = 25). Full article
(This article belongs to the Special Issue Multivariate Data Analysis for Sensors and Sensor Arrays)
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Open AccessArticle Tilted Fiber Bragg Grating Sensor Using Chemical Plating of a Palladium Membrane for the Detection of Hydrogen Leakage
Sensors 2018, 18(12), 4478; https://doi.org/10.3390/s18124478
Received: 21 November 2018 / Revised: 12 December 2018 / Accepted: 12 December 2018 / Published: 18 December 2018
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Abstract
A tilted fiber Bragg grating (TFBG) hydrogen sensor coated with a palladium (Pd) membrane by the electroless plating method is proposed in this paper. A uniform layer of Pd metal is fabricated in aqueous solutions by the chemical coating method, which is used [...] Read more.
A tilted fiber Bragg grating (TFBG) hydrogen sensor coated with a palladium (Pd) membrane by the electroless plating method is proposed in this paper. A uniform layer of Pd metal is fabricated in aqueous solutions by the chemical coating method, which is used as the sensitive element to detect the change of the surrounding refractive index (SRI) caused by hydrogen absorption. The change in SRI causes an unsynchronized change of the cladding modes and the Bragg peak in the TFBG transmission spectrum, thereby eliminating the cross-sensitivity due to membrane expansion and is able to simultaneously monitor the presence of cracks in the pipe, as well as the hydrogen leakage. By subtracting the wavelength shift caused by fiber expansion, the change of SRI, i.e., the information from the H2 level, can be separately obtained. The drifted wavelength is measured for the H2 concentration below the hydrogen explosion limit between 1% and 4%. The chemical-based coating has the advantages of a low cost, a simple operation, and being suitable for coating on long fiber structures. The proposed sensor is able to detect the H2 signal in 5 min at a 1% H2 concentration. The proposed sensor is proved to be able to monitor the hydrogen level without the cross-sensitivity of temperature variation and expansion strains, so could be a good candidate for security applications in industry. Full article
(This article belongs to the Section Physical Sensors)
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