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Sensors, Volume 15, Issue 5 (May 2015), Pages 9610-12102

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Open AccessArticle LED-Absorption-QEPAS Sensor for Biogas Plants
Sensors 2015, 15(5), 12092-12102; https://doi.org/10.3390/s150512092
Received: 20 March 2015 / Accepted: 13 May 2015 / Published: 22 May 2015
Cited by 20 | Viewed by 2911 | PDF Full-text (3785 KB) | HTML Full-text | XML Full-text
Abstract
A new sensor for methane and carbon dioxide concentration measurements in biogas plants is presented. LEDs in the mid infrared spectral region are implemented as low cost light source. The combination of quartz-enhanced photoacoustic spectroscopy with an absorption path leads to a sensor
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A new sensor for methane and carbon dioxide concentration measurements in biogas plants is presented. LEDs in the mid infrared spectral region are implemented as low cost light source. The combination of quartz-enhanced photoacoustic spectroscopy with an absorption path leads to a sensor setup suitable for the harsh application environment. The sensor system contains an electronics unit and the two gas sensors; it was designed to work as standalone device and was tested in a biogas plant for several weeks. Gas concentration dependent measurements show a precision better than 1% in a range between 40% and 60% target gas concentration for both sensors. Concentration dependent measurements with different background gases show a considerable decrease in cross sensitivity against the major components of biogas in direct comparison to common absorption based sensors. Full article
(This article belongs to the Section Physical Sensors)
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Open AccessArticle Iterative Precise Conductivity Measurement with IDEs
Sensors 2015, 15(5), 12080-12091; https://doi.org/10.3390/s150512080
Received: 14 November 2014 / Accepted: 18 May 2015 / Published: 22 May 2015
Viewed by 1976 | PDF Full-text (1344 KB) | HTML Full-text | XML Full-text
Abstract
The paper presents a new approach in the field of precise electrolytic conductivity measurements with planar thin- and thick-film electrodes. This novel measuring method was developed for measurement with comb-like electrodes called interdigitated electrodes (IDEs). Correction characteristics over a wide range of specific
[...] Read more.
The paper presents a new approach in the field of precise electrolytic conductivity measurements with planar thin- and thick-film electrodes. This novel measuring method was developed for measurement with comb-like electrodes called interdigitated electrodes (IDEs). Correction characteristics over a wide range of specific conductivities were determined from an interface impedance characterization of the thick-film IDEs. The local maximum of the capacitive part of the interface impedance is used for corrections to get linear responses. The measuring frequency was determined at a wide range of measured conductivity. An iteration mode of measurements was suggested to precisely measure the conductivity at the right frequency in order to achieve a highly accurate response. The method takes precise conductivity measurements in concentration ranges from 10−6 to 1 M without electrode cell replacement. Full article
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Open AccessArticle Multisensor Super Resolution Using Directionally-Adaptive Regularization for UAV Images
Sensors 2015, 15(5), 12053-12079; https://doi.org/10.3390/s150512053
Received: 27 March 2015 / Accepted: 20 May 2015 / Published: 22 May 2015
Cited by 3 | Viewed by 2248 | PDF Full-text (2019 KB) | HTML Full-text | XML Full-text
Abstract
In various unmanned aerial vehicle (UAV) imaging applications, the multisensor super-resolution (SR) technique has become a chronic problem and attracted increasing attention. Multisensor SR algorithms utilize multispectral low-resolution (LR) images to make a higher resolution (HR) image to improve the performance of the
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In various unmanned aerial vehicle (UAV) imaging applications, the multisensor super-resolution (SR) technique has become a chronic problem and attracted increasing attention. Multisensor SR algorithms utilize multispectral low-resolution (LR) images to make a higher resolution (HR) image to improve the performance of the UAV imaging system. The primary objective of the paper is to develop a multisensor SR method based on the existing multispectral imaging framework instead of using additional sensors. In order to restore image details without noise amplification or unnatural post-processing artifacts, this paper presents an improved regularized SR algorithm by combining the directionally-adaptive constraints and multiscale non-local means (NLM) filter. As a result, the proposed method can overcome the physical limitation of multispectral sensors by estimating the color HR image from a set of multispectral LR images using intensity-hue-saturation (IHS) image fusion. Experimental results show that the proposed method provides better SR results than existing state-of-the-art SR methods in the sense of objective measures. Full article
(This article belongs to the Special Issue UAV Sensors for Environmental Monitoring) Printed Edition available
Open AccessArticle Highly Sensitive Bacteria Quantification Using Immunomagnetic Separation and Electrochemical Detection of Guanine-Labeled Secondary Beads
Sensors 2015, 15(5), 12034-12052; https://doi.org/10.3390/s150512034
Received: 23 March 2015 / Accepted: 7 May 2015 / Published: 22 May 2015
Cited by 18 | Viewed by 3102 | PDF Full-text (9047 KB) | HTML Full-text | XML Full-text
Abstract
In this paper, we report the ultra-sensitive indirect electrochemical detection of E. coli O157:H7 using antibody functionalized primary (magnetic) beads for capture and polyguanine (polyG) oligonucleotide functionalized secondary (polystyrene) beads as an electrochemical tag. Vacuum filtration in combination with E. coli O157:H7 specific
[...] Read more.
In this paper, we report the ultra-sensitive indirect electrochemical detection of E. coli O157:H7 using antibody functionalized primary (magnetic) beads for capture and polyguanine (polyG) oligonucleotide functionalized secondary (polystyrene) beads as an electrochemical tag. Vacuum filtration in combination with E. coli O157:H7 specific antibody modified magnetic beads were used for extraction of E. coli O157:H7 from 100 mL samples. The magnetic bead conjugated E. coli O157:H7 cells were then attached to polyG functionalized secondary beads to form a sandwich complex (magnetic bead/E. coli secondary bead). While the use of magnetic beads for immuno-based capture is well characterized, the use of oligonucleotide functionalized secondary beads helps combine amplification and potential multiplexing into the system. The antibody functionalized secondary beads can be easily modified with a different antibody to detect other pathogens from the same sample and enable potential multiplexing. The polyGs on the secondary beads enable signal amplification up to 10\(^{8}\) guanine tags per secondary bead (\(7.5\times10^{6}\) biotin-FITC per secondary bead, 20 guanines per oligonucleotide) bound to the target (E. coli). A single-stranded DNA probe functionalized reduced graphene oxide modified glassy carbon electrode was used to bind the polyGs on the secondary beads. Fluorescent imaging was performed to confirm the hybridization of the complex to the electrode surface. Differential pulse voltammetry (DPV) was used to quantify the amount of polyG involved in the hybridization event with tris(2,2'-bipyridine)ruthenium(II) (Ru(bpy)\(_{3}^{2+}\)) as the mediator. The amount of polyG signal can be correlated to the amount of E. coli O157:H7 in the sample. The method was able to detect concentrations of E. coli O157:H7 down to 3 CFU/100 mL, which is 67 times lower than the most sensitive technique reported in literature. The signal to noise ratio for this work was 3. We also demonstrate the use of the protocol for detection of E. coli O157:H7 seeded in waste water effluent samples. Full article
(This article belongs to the Special Issue Biosensors for Pathogen Detection)
Open AccessArticle Gated Silicon Drift Detector Fabricated from a Low-Cost Silicon Wafer
Sensors 2015, 15(5), 12022-12033; https://doi.org/10.3390/s150512022
Received: 7 April 2015 / Revised: 11 May 2015 / Accepted: 16 May 2015 / Published: 22 May 2015
Cited by 4 | Viewed by 2058 | PDF Full-text (1898 KB) | HTML Full-text | XML Full-text
Abstract
Inexpensive high-resolution silicon (Si) X-ray detectors are required for on-site surveys of traces of hazardous elements in food and soil by measuring the energies and counts of X-ray fluorescence photons radially emitted from these elements. Gated silicon drift detectors (GSDDs) are much cheaper
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Inexpensive high-resolution silicon (Si) X-ray detectors are required for on-site surveys of traces of hazardous elements in food and soil by measuring the energies and counts of X-ray fluorescence photons radially emitted from these elements. Gated silicon drift detectors (GSDDs) are much cheaper to fabricate than commercial silicon drift detectors (SDDs). However, previous GSDDs were fabricated from \(10\)-k\(\Omega \cdot\)cm Si wafers, which are more expensive than \(2\)-k\(\Omega \cdot\)cm Si wafers used in commercial SDDs. To fabricate cheaper portable X-ray fluorescence instruments, we investigate GSDDs formed from \(2\)-k\(\Omega \cdot\)cm Si wafers. The thicknesses of commercial SDDs are up to \(0.5\) mm, which can detect photons with energies up to \(27\) keV, whereas we describe GSDDs that can detect photons with energies of up to \(35\) keV. We simulate the electric potential distributions in GSDDs with Si thicknesses of \(0.5\) and \(1\) mm at a single high reverse bias. GSDDs with one gate pattern using any resistivity Si wafer can work well for changing the reverse bias that is inversely proportional to the resistivity of the Si wafer. Full article
(This article belongs to the Special Issue State-of-the-Art Sensors Technology in Japan 2015)
Open AccessReview Survey of WBSNs for Pre-Hospital Assistance: Trends to Maximize the Network Lifetime and Video Transmission Techniques
Sensors 2015, 15(5), 11993-12021; https://doi.org/10.3390/s150511993
Received: 14 October 2014 / Accepted: 18 May 2015 / Published: 22 May 2015
Cited by 11 | Viewed by 3167 | PDF Full-text (634 KB) | HTML Full-text | XML Full-text
Abstract
This survey aims to encourage the multidisciplinary communities to join forces for innovation in the mobile health monitoring area. Specifically, multidisciplinary innovations in medical emergency scenarios can have a significant impact on the effectiveness and quality of the procedures and practices in the
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This survey aims to encourage the multidisciplinary communities to join forces for innovation in the mobile health monitoring area. Specifically, multidisciplinary innovations in medical emergency scenarios can have a significant impact on the effectiveness and quality of the procedures and practices in the delivery of medical care. Wireless body sensor networks (WBSNs) are a promising technology capable of improving the existing practices in condition assessment and care delivery for a patient in a medical emergency. This technology can also facilitate the early interventions of a specialist physician during the pre-hospital period. WBSNs make possible these early interventions by establishing remote communication links with video/audio support and by providing medical information such as vital signs, electrocardiograms, etc. in real time. This survey focuses on relevant issues needed to understand how to setup a WBSN for medical emergencies. These issues are: monitoring vital signs and video transmission, energy efficient protocols, scheduling, optimization and energy consumption on a WBSN. Full article
(This article belongs to the Special Issue Wireless Sensor Network for Pervasive Medical Care)
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Open AccessReply Revision of J3Gen and Validity of the Attacks by Peinado et al.
Sensors 2015, 15(5), 11988-11992; https://doi.org/10.3390/s150511988
Received: 7 May 2015 / Accepted: 18 May 2015 / Published: 22 May 2015
Viewed by 1477 | PDF Full-text (198 KB) | HTML Full-text | XML Full-text
Abstract
This letter is the reply to: Remarks on Peinado et al.’s Analysis of J3Gen by J. Garcia-Alfaro, J. Herrera-Joancomartí and J. Melià-Seguí published in Sensors 2015, 15, 6217–6220. Peinado et al. cryptanalyzed the pseudorandom number generator proposed by Melià-Seguí et al., describing two
[...] Read more.
This letter is the reply to: Remarks on Peinado et al.’s Analysis of J3Gen by J. Garcia-Alfaro, J. Herrera-Joancomartí and J. Melià-Seguí published in Sensors 2015, 15, 6217–6220. Peinado et al. cryptanalyzed the pseudorandom number generator proposed by Melià-Seguí et al., describing two possible attacks. Later, Garcia-Alfaro claimed that one of this attack did not hold in practice because the assumptions made by Peinado et al. were not correct. This letter reviews those remarks, showing that J3Gen is anyway flawed and that, without further information, the interpretation made by Peinado et al. seems to be correct. Full article
(This article belongs to the Section Sensor Networks)
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Open AccessArticle A Highly Sensitive Porous Silicon (P-Si)-Based Human Kallikrein 2 (hK2) Immunoassay Platform toward Accurate Diagnosis of Prostate Cancer
Sensors 2015, 15(5), 11972-11987; https://doi.org/10.3390/s150511972
Received: 19 February 2015 / Accepted: 14 May 2015 / Published: 22 May 2015
Cited by 5 | Viewed by 2102 | PDF Full-text (2462 KB) | HTML Full-text | XML Full-text
Abstract
Levels of total human kallikrein 2 (hK2), a protein involved the pathology of prostate cancer (PCa), could be used as a biomarker to aid in the diagnosis of this disease. In this study, we report on a porous silicon antibody immunoassay platform for
[...] Read more.
Levels of total human kallikrein 2 (hK2), a protein involved the pathology of prostate cancer (PCa), could be used as a biomarker to aid in the diagnosis of this disease. In this study, we report on a porous silicon antibody immunoassay platform for the detection of serum levels of total hK2. The surface of porous silicon has a 3-dimensional macro- and nanoporous structure, which offers a large binding capacity for capturing probe molecules. The tailored pore size of the porous silicon also allows efficient immobilization of antibodies by surface adsorption, and does not require chemical immobilization. Monoclonal hK2 capture antibody (6B7) was dispensed onto P-Si chip using a piezoelectric dispenser. In total 13 × 13 arrays (169 spots) were spotted on the chip with its single spot volume of 300 pL. For an optimization of capture antibody condition, we firstly performed an immunoassay of the P-Si microarray under a titration series of hK2 in pure buffer (PBS) at three different antibody densities (75, 100 and 145 µg/mL). The best performance of the microarray platform was seen at 100 µg/mL of the capture antibody concentration (LOD was 100 fg/mL). The platform then was subsequently evaluated for a titration series of serum-spiked hK2 samples. The developed platform utilizes only 15 µL of serum per test and the total assay time is about 3 h, including immobilization of the capture antibody. The detection limit of the hK2 assay was 100 fg/mL in PBS buffer and 1 pg/mL in serum with a dynamic range of 106 (10−4 to 102 ng/mL). Full article
(This article belongs to the Special Issue Immunosensors 2014)
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Open AccessArticle User Activity Recognition in Smart Homes Using Pattern Clustering Applied to Temporal ANN Algorithm
Sensors 2015, 15(5), 11953-11971; https://doi.org/10.3390/s150511953
Received: 11 February 2015 / Accepted: 14 May 2015 / Published: 21 May 2015
Cited by 35 | Viewed by 3204 | PDF Full-text (1212 KB) | HTML Full-text | XML Full-text
Abstract
This paper discusses the possibility of recognizing and predicting user activities in the IoT (Internet of Things) based smart environment. The activity recognition is usually done through two steps: activity pattern clustering and activity type decision. Although many related works have been suggested,
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This paper discusses the possibility of recognizing and predicting user activities in the IoT (Internet of Things) based smart environment. The activity recognition is usually done through two steps: activity pattern clustering and activity type decision. Although many related works have been suggested, they had some limited performance because they focused only on one part between the two steps. This paper tries to find the best combination of a pattern clustering method and an activity decision algorithm among various existing works. For the first step, in order to classify so varied and complex user activities, we use a relevant and efficient unsupervised learning method called the K-pattern clustering algorithm. In the second step, the training of smart environment for recognizing and predicting user activities inside his/her personal space is done by utilizing the artificial neural network based on the Allen’s temporal relations. The experimental results show that our combined method provides the higher recognition accuracy for various activities, as compared with other data mining classification algorithms. Furthermore, it is more appropriate for a dynamic environment like an IoT based smart home. Full article
(This article belongs to the Special Issue Sensors and Smart Cities)
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Open AccessArticle A Lightweight White-Box Symmetric Encryption Algorithm against Node Capture for WSNs
Sensors 2015, 15(5), 11928-11952; https://doi.org/10.3390/s150511928
Received: 26 February 2015 / Accepted: 8 May 2015 / Published: 21 May 2015
Cited by 6 | Viewed by 1798 | PDF Full-text (1510 KB) | HTML Full-text | XML Full-text
Abstract
Wireless Sensor Networks (WSNs) are often deployed in hostile environments and, thus, nodes can be potentially captured by an adversary. This is a typical white-box attack context, i.e., the adversary may have total visibility of the implementation of the build-in cryptosystem and
[...] Read more.
Wireless Sensor Networks (WSNs) are often deployed in hostile environments and, thus, nodes can be potentially captured by an adversary. This is a typical white-box attack context, i.e., the adversary may have total visibility of the implementation of the build-in cryptosystem and full control over its execution platform. Handling white-box attacks in a WSN scenario is a challenging task. Existing encryption algorithms for white-box attack contexts require large memory footprint and, hence, are not applicable for wireless sensor networks scenarios. As a countermeasure against the threat in this context, in this paper, we propose a class of lightweight secure implementations of the symmetric encryption algorithm SMS4. The basic idea of our approach is to merge several steps of the round function of SMS4 into table lookups, blended by randomly generated mixing bijections. Therefore, the size of the implementations are significantly reduced while keeping the same security efficiency. The security and efficiency of the proposed solutions are theoretically analyzed. Evaluation shows our solutions satisfy the requirement of sensor nodes in terms of limited memory size and low computational costs. Full article
(This article belongs to the Section Sensor Networks)
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Open AccessReview Fruit Quality Evaluation Using Spectroscopy Technology: A Review
Sensors 2015, 15(5), 11889-11927; https://doi.org/10.3390/s150511889
Received: 17 March 2015 / Revised: 14 May 2015 / Accepted: 18 May 2015 / Published: 21 May 2015
Cited by 50 | Viewed by 3071 | PDF Full-text (812 KB) | HTML Full-text | XML Full-text
Abstract
An overview is presented with regard to applications of visible and near infrared (Vis/NIR) spectroscopy, multispectral imaging and hyperspectral imaging techniques for quality attributes measurement and variety discrimination of various fruit species, i.e., apple, orange, kiwifruit, peach, grape, strawberry, grape, jujube, banana,
[...] Read more.
An overview is presented with regard to applications of visible and near infrared (Vis/NIR) spectroscopy, multispectral imaging and hyperspectral imaging techniques for quality attributes measurement and variety discrimination of various fruit species, i.e., apple, orange, kiwifruit, peach, grape, strawberry, grape, jujube, banana, mango and others. Some commonly utilized chemometrics including pretreatment methods, variable selection methods, discriminant methods and calibration methods are briefly introduced. The comprehensive review of applications, which concentrates primarily on Vis/NIR spectroscopy, are arranged according to fruit species. Most of the applications are focused on variety discrimination or the measurement of soluble solids content (SSC), acidity and firmness, but also some measurements involving dry matter, vitamin C, polyphenols and pigments have been reported. The feasibility of different spectral modes, i.e., reflectance, interactance and transmittance, are discussed. Optimal variable selection methods and calibration methods for measuring different attributes of different fruit species are addressed. Special attention is paid to sample preparation and the influence of the environment. Areas where further investigation is needed and problems concerning model robustness and model transfer are identified. Full article
(This article belongs to the Special Issue Sensors for Food Safety and Quality) Printed Edition available
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Open AccessArticle Surface Acoustic Wave (SAW) Resonators for Monitoring Conditioning Film Formation
Sensors 2015, 15(5), 11873-11888; https://doi.org/10.3390/s150511873
Received: 2 April 2015 / Accepted: 17 May 2015 / Published: 21 May 2015
Cited by 10 | Viewed by 2598 | PDF Full-text (1740 KB) | HTML Full-text | XML Full-text
Abstract
We propose surface acoustic wave (SAW) resonators as a complementary tool for conditioning film monitoring. Conditioning films are formed by adsorption of inorganic and organic substances on a substrate the moment this substrate comes into contact with a liquid phase. In the case
[...] Read more.
We propose surface acoustic wave (SAW) resonators as a complementary tool for conditioning film monitoring. Conditioning films are formed by adsorption of inorganic and organic substances on a substrate the moment this substrate comes into contact with a liquid phase. In the case of implant insertion, for instance, initial protein adsorption is required to start wound healing, but it will also trigger immune reactions leading to inflammatory responses. The control of the initial protein adsorption would allow to promote the healing process and to suppress adverse immune reactions. Methods to investigate these adsorption processes are available, but it remains difficult to translate measurement results into actual protein binding events. Biosensor transducers allow user-friendly investigation of protein adsorption on different surfaces. The combination of several transduction principles leads to complementary results, allowing a more comprehensive characterization of the adsorbing layer. We introduce SAW resonators as a novel complementary tool for time-resolved conditioning film monitoring. SAW resonators were coated with polymers. The adsorption of the plasma proteins human serum albumin (HSA) and fibrinogen onto the polymer-coated surfaces were monitored. Frequency results were compared with quartz crystal microbalance (QCM) sensor measurements, which confirmed the suitability of the SAW resonators for this application. Full article
(This article belongs to the Special Issue Acoustic Waveguide Sensors)
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Open AccessArticle Branch-Based Centralized Data Collection for Smart Grids Using Wireless Sensor Networks
Sensors 2015, 15(5), 11854-11872; https://doi.org/10.3390/s150511854
Received: 24 February 2015 / Revised: 14 May 2015 / Accepted: 18 May 2015 / Published: 21 May 2015
Cited by 6 | Viewed by 2080 | PDF Full-text (1168 KB) | HTML Full-text | XML Full-text
Abstract
A smart grid is one of the most important applications in smart cities. In a smart grid, a smart meter acts as a sensor node in a sensor network, and a central device collects power usage from every smart meter. This paper focuses
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A smart grid is one of the most important applications in smart cities. In a smart grid, a smart meter acts as a sensor node in a sensor network, and a central device collects power usage from every smart meter. This paper focuses on a centralized data collection problem of how to collect every power usage from every meter without collisions in an environment in which the time synchronization among smart meters is not guaranteed. To solve the problem, we divide a tree that a sensor network constructs into several branches. A conflict-free query schedule is generated based on the branches. Each power usage is collected according to the schedule. The proposed method has important features: shortening query processing time and avoiding collisions between a query and query responses. We evaluate this method using the ns-2 simulator. The experimental results show that this method can achieve both collision avoidance and fast query processing at the same time. The success rate of data collection at a sink node executing this method is 100%. Its running time is about 35 percent faster than that of the round-robin method, and its memory size is reduced to about 10% of that of the depth-first search method. Full article
(This article belongs to the Special Issue Sensors and Smart Cities)
Open AccessArticle Electronic Properties of DNA-Based Schottky Barrier Diodes in Response to Alpha Particles
Sensors 2015, 15(5), 11836-11853; https://doi.org/10.3390/s150511836
Received: 26 March 2015 / Accepted: 11 May 2015 / Published: 21 May 2015
Cited by 5 | Viewed by 1998 | PDF Full-text (4998 KB) | HTML Full-text | XML Full-text
Abstract
Detection of nuclear radiation such as alpha particles has become an important field of research in recent history due to nuclear threats and accidents. In this context; deoxyribonucleic acid (DNA) acting as an organic semiconducting material could be utilized in a metal/semiconductor Schottky
[...] Read more.
Detection of nuclear radiation such as alpha particles has become an important field of research in recent history due to nuclear threats and accidents. In this context; deoxyribonucleic acid (DNA) acting as an organic semiconducting material could be utilized in a metal/semiconductor Schottky junction for detecting alpha particles. In this work we demonstrate for the first time the effect of alpha irradiation on an Al/DNA/p-Si/Al Schottky diode by investigating its current-voltage characteristics. The diodes were exposed for different periods (0–20 min) of irradiation. Various diode parameters such as ideality factor, barrier height, series resistance, Richardson constant and saturation current were then determined using conventional, Cheung and Cheung’s and Norde methods. Generally, ideality factor or n values were observed to be greater than unity, which indicates the influence of some other current transport mechanism besides thermionic processes. Results indicated ideality factor variation between 9.97 and 9.57 for irradiation times between the ranges 0 to 20 min. Increase in the series resistance with increase in irradiation time was also observed when calculated using conventional and Cheung and Cheung’s methods. These responses demonstrate that changes in the electrical characteristics of the metal-semiconductor-metal diode could be further utilized as sensing elements to detect alpha particles. Full article
(This article belongs to the Special Issue Next-Generation Nucleic Acid Sensors)
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Open AccessArticle Highly Stable Liquid Metal-Based Pressure Sensor Integrated with a Microfluidic Channel
Sensors 2015, 15(5), 11823-11835; https://doi.org/10.3390/s150511823
Received: 29 April 2015 / Revised: 19 May 2015 / Accepted: 19 May 2015 / Published: 21 May 2015
Cited by 28 | Viewed by 3056 | PDF Full-text (2164 KB) | HTML Full-text | XML Full-text
Abstract
Pressure measurement is considered one of the key parameters in microfluidic systems. It has been widely used in various fields, such as in biology and biomedical fields. The electrical measurement method is the most widely investigated; however, it is unsuitable for microfluidic systems
[...] Read more.
Pressure measurement is considered one of the key parameters in microfluidic systems. It has been widely used in various fields, such as in biology and biomedical fields. The electrical measurement method is the most widely investigated; however, it is unsuitable for microfluidic systems because of a complicated fabrication process and difficult integration. Moreover, it is generally damaged by large deflection. This paper proposes a thin-film-based pressure sensor that is free from these limitations, using a liquid metal called galinstan. The proposed pressure sensor is easily integrated into a microfluidic system using soft lithography because galinstan exists in a liquid phase at room temperature. We investigated the characteristics of the proposed pressure sensor by calibrating for a pressure range from 0 to 230 kPa (R2 > 0.98) using deionized water. Furthermore, the viscosity of various fluid samples was measured for a shear-rate range of 30–1000 s1. The results of Newtonian and non-Newtonian fluids were evaluated using a commercial viscometer and normalized difference was found to be less than 5.1% and 7.0%, respectively. The galinstan-based pressure sensor can be used in various microfluidic systems for long-term monitoring with high linearity, repeatability, and long-term stability. Full article
(This article belongs to the Section Physical Sensors)
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Open AccessArticle Modeling of Acoustic Emission Signal Propagation in Waveguides
Sensors 2015, 15(5), 11805-11822; https://doi.org/10.3390/s150511805
Received: 31 March 2015 / Revised: 11 May 2015 / Accepted: 15 May 2015 / Published: 21 May 2015
Cited by 15 | Viewed by 2437 | PDF Full-text (3933 KB) | HTML Full-text | XML Full-text
Abstract
Acoustic emission (AE) testing is a widely used nondestructive testing (NDT) method to investigate material failure. When environmental conditions are harmful for the operation of the sensors, waveguides are typically mounted in between the inspected structure and the sensor. Such waveguides can be
[...] Read more.
Acoustic emission (AE) testing is a widely used nondestructive testing (NDT) method to investigate material failure. When environmental conditions are harmful for the operation of the sensors, waveguides are typically mounted in between the inspected structure and the sensor. Such waveguides can be built from different materials or have different designs in accordance with the experimental needs. All these variations can cause changes in the acoustic emission signals in terms of modal conversion, additional attenuation or shift in frequency content. A finite element method (FEM) was used to model acoustic emission signal propagation in an aluminum plate with an attached waveguide and was validated against experimental data. The geometry of the waveguide is systematically changed by varying the radius and height to investigate the influence on the detected signals. Different waveguide materials were implemented and change of material properties as function of temperature were taken into account. Development of the option of modeling different waveguide options replaces the time consuming and expensive trial and error alternative of experiments. Thus, the aim of this research has important implications for those who use waveguides for AE testing. Full article
(This article belongs to the Special Issue Acoustic Waveguide Sensors)
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Open AccessReview ZnO Nanostructure-Based Intracellular Sensor
Sensors 2015, 15(5), 11787-11804; https://doi.org/10.3390/s150511787
Received: 15 March 2015 / Revised: 23 April 2015 / Accepted: 13 May 2015 / Published: 21 May 2015
Cited by 9 | Viewed by 2198 | PDF Full-text (2290 KB) | HTML Full-text | XML Full-text
Abstract
Recently ZnO has attracted much interest because of its usefulness for intracellular measurements of biochemical species by using its semiconducting, electrochemical, catalytic properties and for being biosafe and biocompatible. ZnO thus has a wide range of applications in optoelectronics, intracellular nanosensors, transducers, energy
[...] Read more.
Recently ZnO has attracted much interest because of its usefulness for intracellular measurements of biochemical species by using its semiconducting, electrochemical, catalytic properties and for being biosafe and biocompatible. ZnO thus has a wide range of applications in optoelectronics, intracellular nanosensors, transducers, energy conversion and medical sciences. This review relates specifically to intracellular electrochemical (glucose and free metal ion) biosensors based on functionalized zinc oxide nanowires/nanorods. For intracellular measurements, the ZnO nanowires/nanorods were grown on the tip of a borosilicate glass capillary (0.7 µm in diameter) and functionalized with membranes or enzymes to produce intracellular selective metal ion or glucose sensors. Successful intracellular measurements were carried out using ZnO nanowires/nanorods grown on small tips for glucose and free metal ions using two types of cells, human fat cells and frog oocytes. The sensors in this study were used to detect real-time changes of metal ions and glucose across human fat cells and frog cells using changes in the electrochemical potential at the interface of the intracellular micro-environment. Such devices are helpful in explaining various intracellular processes involving ions and glucose. Full article
(This article belongs to the Special Issue Intracellular Sensing)
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Open AccessArticle Building Keypoint Mappings on Multispectral Images by a Cascade of Classifiers with a Resurrection Mechanism
Sensors 2015, 15(5), 11769-11786; https://doi.org/10.3390/s150511769
Received: 13 March 2015 / Revised: 27 April 2015 / Accepted: 5 May 2015 / Published: 21 May 2015
Cited by 1 | Viewed by 1627 | PDF Full-text (2054 KB) | HTML Full-text | XML Full-text
Abstract
Inspired by the boosting technique for detecting objects, this paper proposes a cascade structure with a resurrection mechanism to establish keypoint mappings on multispectral images. The cascade structure is composed of four steps by utilizing best bin first (BBF), color and intensity distribution
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Inspired by the boosting technique for detecting objects, this paper proposes a cascade structure with a resurrection mechanism to establish keypoint mappings on multispectral images. The cascade structure is composed of four steps by utilizing best bin first (BBF), color and intensity distribution of segment (CIDS), global information and the RANSAC process to remove outlier keypoint matchings. Initial keypoint mappings are built with the descriptors associated with keypoints; then, at each step, only a small number of keypoint mappings of a high confidence are classified to be incorrect. The unclassified keypoint mappings will be passed on to subsequent steps for determining whether they are correct. Due to the drawback of a classification rule, some correct keypoint mappings may be misclassified as incorrect at a step. Observing this, we design a resurrection mechanism, so that they will be reconsidered and evaluated by the rules utilized in subsequent steps. Experimental results show that the proposed cascade structure combined with the resurrection mechanism can effectively build more reliable keypoint mappings on multispectral images than existing methods. Full article
(This article belongs to the Section Remote Sensors)
Open AccessArticle An Ultra-Low Power Wireless Sensor Network for Bicycle Torque Performance Measurements
Sensors 2015, 15(5), 11741-11768; https://doi.org/10.3390/s150511741
Received: 5 February 2015 / Revised: 23 April 2015 / Accepted: 27 April 2015 / Published: 21 May 2015
Cited by 12 | Viewed by 2856 | PDF Full-text (4424 KB) | HTML Full-text | XML Full-text
Abstract
In this paper, we propose an energy-efficient transmission technique known as the sleep/wake algorithm for a bicycle torque sensor node. This paper aims to highlight the trade-off between energy efficiency and the communication range between the cyclist and coach. Two experiments were conducted.
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In this paper, we propose an energy-efficient transmission technique known as the sleep/wake algorithm for a bicycle torque sensor node. This paper aims to highlight the trade-off between energy efficiency and the communication range between the cyclist and coach. Two experiments were conducted. The first experiment utilised the Zigbee protocol (XBee S2), and the second experiment used the Advanced and Adaptive Network Technology (ANT) protocol based on the Nordic nRF24L01 radio transceiver chip. The current consumption of ANT was measured, simulated and compared with a torque sensor node that uses the XBee S2 protocol. In addition, an analytical model was derived to correlate the sensor node average current consumption with a crank arm cadence. The sensor node achieved 98% power savings for ANT relative to ZigBee when they were compared alone, and the power savings amounted to 30% when all components of the sensor node are considered. The achievable communication range was 65 and 50 m for ZigBee and ANT, respectively, during measurement on an outdoor cycling track (i.e., velodrome). The conclusions indicate that the ANT protocol is more suitable for use in a torque sensor node when power consumption is a crucial demand, whereas the ZigBee protocol is more convenient in ensuring data communication between cyclist and coach. Full article
(This article belongs to the Section Sensor Networks)
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Open AccessArticle Evaluation of Three State-of-the-Art Classifiers for Recognition of Activities of Daily Living from Smart Home Ambient Data
Sensors 2015, 15(5), 11725-11740; https://doi.org/10.3390/s150511725
Received: 10 March 2015 / Revised: 13 May 2015 / Accepted: 14 May 2015 / Published: 21 May 2015
Cited by 21 | Viewed by 2590 | PDF Full-text (1286 KB) | HTML Full-text | XML Full-text
Abstract
Smart homes for the aging population have recently started attracting the attention of the research community. The “health state” of smart homes is comprised of many different levels; starting with the physical health of citizens, it also includes longer-term health norms and outcomes,
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Smart homes for the aging population have recently started attracting the attention of the research community. The “health state” of smart homes is comprised of many different levels; starting with the physical health of citizens, it also includes longer-term health norms and outcomes, as well as the arena of positive behavior changes. One of the problems of interest is to monitor the activities of daily living (ADL) of the elderly, aiming at their protection and well-being. For this purpose, we installed passive infrared (PIR) sensors to detect motion in a specific area inside a smart apartment and used them to collect a set of ADL. In a novel approach, we describe a technology that allows the ground truth collected in one smart home to train activity recognition systems for other smart homes. We asked the users to label all instances of all ADL only once and subsequently applied data mining techniques to cluster in-home sensor firings. Each cluster would therefore represent the instances of the same activity. Once the clusters were associated to their corresponding activities, our system was able to recognize future activities. To improve the activity recognition accuracy, our system preprocessed raw sensor data by identifying overlapping activities. To evaluate the recognition performance from a 200-day dataset, we implemented three different active learning classification algorithms and compared their performance: naive Bayesian (NB), support vector machine (SVM) and random forest (RF). Based on our results, the RF classifier recognized activities with an average specificity of 96.53%, a sensitivity of 68.49%, a precision of 74.41% and an F-measure of 71.33%, outperforming both the NB and SVM classifiers. Further clustering markedly improved the results of the RF classifier. An activity recognition system based on PIR sensors in conjunction with a clustering classification approach was able to detect ADL from datasets collected from different homes. Thus, our PIR-based smart home technology could improve care and provide valuable information to better understand the functioning of our societies, as well as to inform both individual and collective action in a smart city scenario. Full article
(This article belongs to the Special Issue Sensors and Smart Cities)
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Open AccessArticle Entropy-Based TOA Estimation and SVM-Based Ranging Error Mitigation in UWB Ranging Systems
Sensors 2015, 15(5), 11701-11724; https://doi.org/10.3390/s150511701
Received: 26 March 2015 / Revised: 10 May 2015 / Accepted: 14 May 2015 / Published: 21 May 2015
Cited by 8 | Viewed by 2077 | PDF Full-text (1482 KB) | HTML Full-text | XML Full-text
Abstract
The major challenges for Ultra-wide Band (UWB) indoor ranging systems are the dense multipath and non-line-of-sight (NLOS) problems of the indoor environment. To precisely estimate the time of arrival (TOA) of the first path (FP) in such a poor environment, a novel approach
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The major challenges for Ultra-wide Band (UWB) indoor ranging systems are the dense multipath and non-line-of-sight (NLOS) problems of the indoor environment. To precisely estimate the time of arrival (TOA) of the first path (FP) in such a poor environment, a novel approach of entropy-based TOA estimation and support vector machine (SVM) regression-based ranging error mitigation is proposed in this paper. The proposed method can estimate the TOA precisely by measuring the randomness of the received signals and mitigate the ranging error without the recognition of the channel conditions. The entropy is used to measure the randomness of the received signals and the FP can be determined by the decision of the sample which is followed by a great entropy decrease. The SVM regression is employed to perform the ranging-error mitigation by the modeling of the regressor between the characteristics of received signals and the ranging error. The presented numerical simulation results show that the proposed approach achieves significant performance improvements in the CM1 to CM4 channels of the IEEE 802.15.4a standard, as compared to conventional approaches. Full article
(This article belongs to the Special Issue Sensors for Indoor Mapping and Navigation)
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Open AccessArticle Optimal Self-Tuning PID Controller Based on Low Power Consumption for a Server Fan Cooling System
Sensors 2015, 15(5), 11685-11700; https://doi.org/10.3390/s150511685
Received: 24 March 2015 / Accepted: 15 May 2015 / Published: 20 May 2015
Cited by 10 | Viewed by 2571 | PDF Full-text (1900 KB) | HTML Full-text | XML Full-text
Abstract
Recently, saving the cooling power in servers by controlling the fan speed has attracted considerable attention because of the increasing demand for high-density servers. This paper presents an optimal self-tuning proportional-integral-derivative (PID) controller, combining a PID neural network (PIDNN) with fan-power-based optimization in
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Recently, saving the cooling power in servers by controlling the fan speed has attracted considerable attention because of the increasing demand for high-density servers. This paper presents an optimal self-tuning proportional-integral-derivative (PID) controller, combining a PID neural network (PIDNN) with fan-power-based optimization in the transient-state temperature response in the time domain, for a server fan cooling system. Because the thermal model of the cooling system is nonlinear and complex, a server mockup system simulating a 1U rack server was constructed and a fan power model was created using a third-order nonlinear curve fit to determine the cooling power consumption by the fan speed control. PIDNN with a time domain criterion is used to tune all online and optimized PID gains. The proposed controller was validated through experiments of step response when the server operated from the low to high power state. The results show that up to 14% of a server’s fan cooling power can be saved if the fan control permits a slight temperature response overshoot in the electronic components, which may provide a time-saving strategy for tuning the PID controller to control the server fan speed during low fan power consumption. Full article
(This article belongs to the Section Physical Sensors)
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Open AccessArticle Classifying Sources Influencing Indoor Air Quality (IAQ) Using Artificial Neural Network (ANN)
Sensors 2015, 15(5), 11665-11684; https://doi.org/10.3390/s150511665
Received: 19 January 2015 / Revised: 21 April 2015 / Accepted: 22 April 2015 / Published: 20 May 2015
Cited by 12 | Viewed by 2715 | PDF Full-text (3427 KB) | HTML Full-text | XML Full-text
Abstract
Monitoring indoor air quality (IAQ) is deemed important nowadays. A sophisticated IAQ monitoring system which could classify the source influencing the IAQ is definitely going to be very helpful to the users. Therefore, in this paper, an IAQ monitoring system has been proposed
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Monitoring indoor air quality (IAQ) is deemed important nowadays. A sophisticated IAQ monitoring system which could classify the source influencing the IAQ is definitely going to be very helpful to the users. Therefore, in this paper, an IAQ monitoring system has been proposed with a newly added feature which enables the system to identify the sources influencing the level of IAQ. In order to achieve this, the data collected has been trained with artificial neural network or ANN—a proven method for pattern recognition. Basically, the proposed system consists of sensor module cloud (SMC), base station and service-oriented client. The SMC contain collections of sensor modules that measure the air quality data and transmit the captured data to base station through wireless network. The IAQ monitoring system is also equipped with IAQ Index and thermal comfort index which could tell the users about the room’s conditions. The results showed that the system is able to measure the level of air quality and successfully classify the sources influencing IAQ in various environments like ambient air, chemical presence, fragrance presence, foods and beverages and human activity. Full article
(This article belongs to the Section Sensor Networks)
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Open AccessArticle Medically Relevant Assays with a Simple Smartphone and Tablet Based Fluorescence Detection System
Sensors 2015, 15(5), 11653-11664; https://doi.org/10.3390/s150511653
Received: 31 March 2015 / Accepted: 17 May 2015 / Published: 20 May 2015
Cited by 12 | Viewed by 5926 | PDF Full-text (2004 KB) | HTML Full-text | XML Full-text
Abstract
Cell phones and smart phones can be reconfigured as biomedical sensor devices but this requires specialized add-ons. In this paper we present a simple cell phone-based portable bioassay platform, which can be used with fluorescent assays in solution. The system consists of a
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Cell phones and smart phones can be reconfigured as biomedical sensor devices but this requires specialized add-ons. In this paper we present a simple cell phone-based portable bioassay platform, which can be used with fluorescent assays in solution. The system consists of a tablet, a polarizer, a smart phone (camera) and a box that provides dark readout conditions. The assay in a well plate is placed on the tablet screen acting as an excitation source. A polarizer on top of the well plate separates excitation light from assay fluorescence emission enabling assay readout with a smartphone camera. The assay result is obtained by analysing the intensity of image pixels in an appropriate colour channel. With this device we carried out two assays, for collagenase and trypsin using fluorescein as the detected fluorophore. The results of collagenase assay with the lowest measured concentration of 3.75 µg/mL and 0.938 µg in total in the sample were comparable to those obtained by a microplate reader. The lowest measured amount of trypsin was 930 pg, which is comparable to the low detection limit of 400 pg for this assay obtained in a microplate reader. The device is sensitive enough to be used in point-of-care medical diagnostics of clinically relevant conditions, including arthritis, cystic fibrosis and acute pancreatitis. Full article
(This article belongs to the Special Issue Smartphone-Based Sensors for Non-Invasive Physiological Monitoring)
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Open AccessArticle An Energy-Efficient Transmission Scheme for Real-Time Data in Wireless Sensor Networks
Sensors 2015, 15(5), 11628-11652; https://doi.org/10.3390/s150511628
Received: 18 March 2015 / Revised: 13 May 2015 / Accepted: 14 May 2015 / Published: 20 May 2015
Cited by 8 | Viewed by 2262 | PDF Full-text (2790 KB) | HTML Full-text | XML Full-text
Abstract
The Internet of things (IoT) is a novel paradigm where all things or objects in daily life can communicate with other devices and provide services over the Internet. Things or objects need identifying, sensing, networking and processing capabilities to make the IoT paradigm
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The Internet of things (IoT) is a novel paradigm where all things or objects in daily life can communicate with other devices and provide services over the Internet. Things or objects need identifying, sensing, networking and processing capabilities to make the IoT paradigm a reality. The IEEE 802.15.4 standard is one of the main communication protocols proposed for the IoT. The IEEE 802.15.4 standard provides the guaranteed time slot (GTS) mechanism that supports the quality of service (QoS) for the real-time data transmission. In spite of some QoS features in IEEE 802.15.4 standard, the problem of end-to-end delay still remains. In order to solve this problem, we propose a cooperative medium access scheme (MAC) protocol for real-time data transmission. We also evaluate the performance of the proposed scheme through simulation. The simulation results demonstrate that the proposed scheme can improve the network performance. Full article
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Open AccessArticle A Negative Index Metamaterial-Inspired UWB Antenna with an Integration of Complementary SRR and CLS Unit Cells for Microwave Imaging Sensor Applications
Sensors 2015, 15(5), 11601-11627; https://doi.org/10.3390/s150511601
Received: 21 February 2015 / Accepted: 30 April 2015 / Published: 20 May 2015
Cited by 30 | Viewed by 2815 | PDF Full-text (5237 KB) | HTML Full-text | XML Full-text
Abstract
This paper presents a negative index metamaterial incorporated UWB antenna with an integration of complementary SRR (split-ring resonator) and CLS (capacitive loaded strip) unit cells for microwave imaging sensor applications. This metamaterial UWB antenna sensor consists of four unit cells along one axis,
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This paper presents a negative index metamaterial incorporated UWB antenna with an integration of complementary SRR (split-ring resonator) and CLS (capacitive loaded strip) unit cells for microwave imaging sensor applications. This metamaterial UWB antenna sensor consists of four unit cells along one axis, where each unit cell incorporates a complementary SRR and CLS pair. This integration enables a design layout that allows both a negative value of permittivity and a negative value of permeability simultaneous, resulting in a durable negative index to enhance the antenna sensor performance for microwave imaging sensor applications. The proposed MTM antenna sensor was designed and fabricated on an FR4 substrate having a thickness of 1.6 mm and a dielectric constant of 4.6. The electrical dimensions of this antenna sensor are 0.20 λ × 0.29 λ at a lower frequency of 3.1 GHz. This antenna sensor achieves a 131.5% bandwidth (VSWR < 2) covering the frequency bands from 3.1 GHz to more than 15 GHz with a maximum gain of 6.57 dBi. High fidelity factor and gain, smooth surface-current distribution and nearly omni-directional radiation patterns with low cross-polarization confirm that the proposed negative index UWB antenna is a promising entrant in the field of microwave imaging sensors. Full article
(This article belongs to the Special Issue Metamaterial-Inspired Sensors)
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Open AccessArticle Mapping the Salinity Gradient in a Microfluidic Device with Schlieren Imaging
Sensors 2015, 15(5), 11587-11600; https://doi.org/10.3390/s150511587
Received: 3 March 2015 / Revised: 12 May 2015 / Accepted: 18 May 2015 / Published: 20 May 2015
Cited by 2 | Viewed by 2096 | PDF Full-text (3266 KB) | HTML Full-text | XML Full-text
Abstract
This work presents the use of the schlieren imaging to quantify the salinity gradients in a microfluidic device. By partially blocking the back focal plane of the objective lens, the schlieren microscope produces an image with patterns that correspond to spatial derivative of
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This work presents the use of the schlieren imaging to quantify the salinity gradients in a microfluidic device. By partially blocking the back focal plane of the objective lens, the schlieren microscope produces an image with patterns that correspond to spatial derivative of refractive index in the specimen. Since salinity variation leads to change in refractive index, the fluid mixing of an aqueous salt solution of a known concentration and water in a T-microchannel is used to establish the relation between salinity gradients and grayscale readouts. This relation is then employed to map the salinity gradients in the target microfluidic device from the grayscale readouts of the corresponding micro-schlieren image. For saline solution with salinity close to that of the seawater, the grayscale readouts vary linearly with the salinity gradient, and the regression line is independent of the flow condition and the salinity of the injected solution. It is shown that the schlieren technique is well suited to quantify the salinity gradients in microfluidic devices, for it provides a spatially resolved, non-invasive, full-field measurement. Full article
(This article belongs to the Special Issue Modeling, Testing and Reliability Issues in MEMS Engineering 2013)
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Open AccessArticle A Wavelet-Based Approach to Fall Detection
Sensors 2015, 15(5), 11575-11586; https://doi.org/10.3390/s150511575
Received: 24 February 2015 / Revised: 29 April 2015 / Accepted: 13 May 2015 / Published: 20 May 2015
Cited by 18 | Viewed by 2610 | PDF Full-text (810 KB) | HTML Full-text | XML Full-text
Abstract
Falls among older people are a widely documented public health problem. Automatic fall detection has recently gained huge importance because it could allow for the immediate communication of falls to medical assistance. The aim of this work is to present a novel wavelet-based
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Falls among older people are a widely documented public health problem. Automatic fall detection has recently gained huge importance because it could allow for the immediate communication of falls to medical assistance. The aim of this work is to present a novel wavelet-based approach to fall detection, focusing on the impact phase and using a dataset of real-world falls. Since recorded falls result in a non-stationary signal, a wavelet transform was chosen to examine fall patterns. The idea is to consider the average fall pattern as the “prototype fall”.In order to detect falls, every acceleration signal can be compared to this prototype through wavelet analysis. The similarity of the recorded signal with the prototype fall is a feature that can be used in order to determine the difference between falls and daily activities. The discriminative ability of this feature is evaluated on real-world data. It outperforms other features that are commonly used in fall detection studies, with an Area Under the Curve of 0.918. This result suggests that the proposed wavelet-based feature is promising and future studies could use this feature (in combination with others considering different fall phases) in order to improve the performance of fall detection algorithms. Full article
(This article belongs to the collection Sensors for Globalized Healthy Living and Wellbeing)
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Open AccessArticle Towards the Automatic Scanning of Indoors with Robots
Sensors 2015, 15(5), 11551-11574; https://doi.org/10.3390/s150511551
Received: 13 April 2015 / Revised: 13 May 2015 / Accepted: 15 May 2015 / Published: 19 May 2015
Cited by 11 | Viewed by 2730 | PDF Full-text (9048 KB) | HTML Full-text | XML Full-text
Abstract
This paper is framed in both 3D digitization and 3D data intelligent processing research fields. Our objective is focused on developing a set of techniques for the automatic creation of simple three-dimensional indoor models with mobile robots. The document presents the principal steps
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This paper is framed in both 3D digitization and 3D data intelligent processing research fields. Our objective is focused on developing a set of techniques for the automatic creation of simple three-dimensional indoor models with mobile robots. The document presents the principal steps of the process, the experimental setup and the results achieved. We distinguish between the stages concerning intelligent data acquisition and 3D data processing. This paper is focused on the first stage. We show how the mobile robot, which carries a 3D scanner, is able to, on the one hand, make decisions about the next best scanner position and, on the other hand, navigate autonomously in the scene with the help of the data collected from earlier scans. After this stage, millions of 3D data are converted into a simplified 3D indoor model. The robot imposes a stopping criterion when the whole point cloud covers the essential parts of the scene. This system has been tested under real conditions indoors with promising results. The future is addressed to extend the method in much more complex and larger scenarios. Full article
(This article belongs to the Special Issue Sensors for Indoor Mapping and Navigation)
Open AccessArticle Semi-Supervised Bayesian Classification of Materials with Impact-Echo Signals
Sensors 2015, 15(5), 11528-11550; https://doi.org/10.3390/s150511528
Received: 23 March 2015 / Revised: 29 April 2015 / Accepted: 11 May 2015 / Published: 19 May 2015
Cited by 10 | Viewed by 1690 | PDF Full-text (478 KB) | HTML Full-text | XML Full-text
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The detection and identification of internal defects in a material require the use of some technology that translates the hidden interior damages into observable signals with different signature-defect correspondences. We apply impact-echo techniques for this purpose. The materials are classified according to their
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The detection and identification of internal defects in a material require the use of some technology that translates the hidden interior damages into observable signals with different signature-defect correspondences. We apply impact-echo techniques for this purpose. The materials are classified according to their defective status (homogeneous, one defect or multiple defects) and kind of defect (hole or crack, passing through or not). Every specimen is impacted by a hammer, and the spectrum of the propagated wave is recorded. This spectrum is the input data to a Bayesian classifier that is based on the modeling of the conditional probabilities with a mixture of Gaussians. The parameters of the Gaussian mixtures and the class probabilities are estimated using an extended expectation-maximization algorithm. The advantage of our proposal is that it is flexible, since it obtains good results for a wide range of models even under little supervision; e.g., it obtains a harmonic average of precision and recall value of 92.38% given only a 10% supervision ratio. We test the method with real specimens made of aluminum alloy. The results show that the algorithm works very well. This technique could be applied in many industrial problems, such as the optimization of the marble cutting process. Full article
(This article belongs to the Section Physical Sensors)
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