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Sensors, Volume 17, Issue 2 (February 2017)

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Cover Story Plasmon assisted microscopy of nano-objects is a highly sensitive label-free method, which helps to [...] Read more.
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Editorial

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Open AccessEditorial Why Using Molecularly Imprinted Polymers in Connection to Biosensors?
Sensors 2017, 17(2), 246; doi:10.3390/s17020246
Received: 14 December 2016 / Accepted: 19 January 2017 / Published: 27 January 2017
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Abstract
The area of biosensor-oriented research has grown rapidly during recent years. Full article
(This article belongs to the Special Issue Biosensors and Molecular Imprinting)
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Research

Jump to: Editorial, Review, Other

Open AccessArticle Quantification of Finger-Tapping Angle Based on Wearable Sensors
Sensors 2017, 17(2), 203; doi:10.3390/s17020203
Received: 23 October 2016 / Revised: 15 January 2017 / Accepted: 16 January 2017 / Published: 25 January 2017
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Abstract
We propose a novel simple method for quantitative and qualitative finger-tapping assessment based on miniature inertial sensors (3D gyroscopes) placed on the thumb and index-finger. We propose a simplified description of the finger tapping by using a single angle, describing rotation around a
[...] Read more.
We propose a novel simple method for quantitative and qualitative finger-tapping assessment based on miniature inertial sensors (3D gyroscopes) placed on the thumb and index-finger. We propose a simplified description of the finger tapping by using a single angle, describing rotation around a dominant axis. The method was verified on twelve subjects, who performed various tapping tasks, mimicking impaired patterns. The obtained tapping angles were compared with results of a motion capture camera system, demonstrating excellent accuracy. The root-mean-square (RMS) error between the two sets of data is, on average, below 4°, and the intraclass correlation coefficient is, on average, greater than 0.972. Data obtained by the proposed method may be used together with scores from clinical tests to enable a better diagnostic. Along with hardware simplicity, this makes the proposed method a promising candidate for use in clinical practice. Furthermore, our definition of the tapping angle can be applied to all tapping assessment systems. Full article
(This article belongs to the Special Issue Wearable Biomedical Sensors)
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Open AccessArticle Volatile Organic Compounds Sensing Using Optical Fibre Long Period Grating with Mesoporous Nano-Scale Coating
Sensors 2017, 17(2), 205; doi:10.3390/s17020205
Received: 24 November 2016 / Revised: 11 January 2017 / Accepted: 17 January 2017 / Published: 8 February 2017
Cited by 1 | PDF Full-text (4069 KB) | HTML Full-text | XML Full-text | Supplementary Files
Abstract
A long period grating (LPG) modified with a mesoporous film infused with a calixarene as a functional compound was employed for the detection of individual volatile organic compounds (VOCs) and their mixtures. The mesoporous film consisted of an inorganic part, SiO2 nanoparticles
[...] Read more.
A long period grating (LPG) modified with a mesoporous film infused with a calixarene as a functional compound was employed for the detection of individual volatile organic compounds (VOCs) and their mixtures. The mesoporous film consisted of an inorganic part, SiO2 nanoparticles (NPs), along with an organic moiety of poly(allylamine hydrochloride) polycation PAH, which was finally infused with the functional compound, p-sulphanato calix[4]arene (CA[4]) or p-sulphanato calix[8]arene (CA[8]). The LPG sensor was designed to operate at the phase matching turning point to provide the highest sensitivity. The sensing mechanism is based on the measurement of the refractive index (RI) change induced by a complex of the VOCs with calixarene. The LPG, modified with a coating of 5 cycles of (SiO2 NPs/PAH) and infused with CA[4] or CA[8], was exposed to chloroform, benzene, toluene and acetone vapours. The British Standards test of the VOCs emissions from material (BS EN ISO 16000-9:2006) was used to test the LPG sensor performance. Full article
(This article belongs to the Special Issue Gas Nanosensors)
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Open AccessArticle Intelligent RF-Based Gesture Input Devices Implemented Using e-Textiles
Sensors 2017, 17(2), 219; doi:10.3390/s17020219
Received: 1 December 2016 / Revised: 17 January 2017 / Accepted: 17 January 2017 / Published: 24 January 2017
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Abstract
We present an radio-frequency (RF)-based approach to gesture detection and recognition, using e-textile versions of common transmission lines used in microwave circuits. This approach allows for easy fabrication of input swatches that can detect a continuum of finger positions and similarly basic gestures,
[...] Read more.
We present an radio-frequency (RF)-based approach to gesture detection and recognition, using e-textile versions of common transmission lines used in microwave circuits. This approach allows for easy fabrication of input swatches that can detect a continuum of finger positions and similarly basic gestures, using a single measurement line. We demonstrate that the swatches can perform gesture detection when under thin layers of cloth or when weatherproofed, providing a high level of versatility not present with other types of approaches. Additionally, using small convolutional neural networks, low-level gestures can be identified with a high level of accuracy using a small, inexpensive microcontroller, allowing for an intelligent fabric that reports only gestures of interest, rather than a simple sensor requiring constant surveillance from an external computing device. The resulting e-textile smart composite has applications in controlling wearable devices by providing a simple, eyes-free mechanism to input simple gestures. Full article
(This article belongs to the Special Issue System-Integrated Intelligence and Intelligent Systems)
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Open AccessArticle A Modified Azimuth Weighting Method in a Two-Step Process Approach for Sliding Spotlight Data Processing
Sensors 2017, 17(2), 220; doi:10.3390/s17020220
Received: 7 November 2016 / Revised: 19 January 2017 / Accepted: 20 January 2017 / Published: 24 January 2017
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Abstract
Low sidelobes are important and essential in all SAR (Synthetic Aperture Radar) images, regardless of the imaging mode, for fewer artificial targets. For strip-map mode all targets overlap in frequency, which is convenient to suppress sidelobes. However, weighting requires total overlap in the
[...] Read more.
Low sidelobes are important and essential in all SAR (Synthetic Aperture Radar) images, regardless of the imaging mode, for fewer artificial targets. For strip-map mode all targets overlap in frequency, which is convenient to suppress sidelobes. However, weighting requires total overlap in the time or frequency domain, which a sliding spotlight signal could not satisfy. Furthermore, the wavelength cannot be regarded as a constant value under the condition of a wideband chirp signal, which leads to the variation of the Doppler bandwidth along with the range frequency. In this article, an azimuth weighting method is proposed that considers the influence of a wideband based on a two-step algorithm. The computer simulation is given to verify the presented method. Full article
(This article belongs to the Section Remote Sensors)
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Open AccessArticle Microshell Arrays Enhanced Sensitivity in Detection of Specific Antibody for Reduced Graphene Oxide Optical Sensor
Sensors 2017, 17(2), 221; doi:10.3390/s17020221
Received: 19 November 2016 / Revised: 14 January 2017 / Accepted: 18 January 2017 / Published: 24 January 2017
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Abstract
Protein-protein interactions play an important role in the investigation of biomolecules. In this paper, we reported on the use of a reduced graphene oxide microshell (RGOM)-based optical biosensor for the determination of goat anti-rabbit IgG. The biosensor was prepared through a self-assembly of
[...] Read more.
Protein-protein interactions play an important role in the investigation of biomolecules. In this paper, we reported on the use of a reduced graphene oxide microshell (RGOM)-based optical biosensor for the determination of goat anti-rabbit IgG. The biosensor was prepared through a self-assembly of monolayers of monodisperse polystyrene microspheres, combined with a high-temperature reduction, in order to decorate the RGOM with rabbit IgG. The periodic microshells allowed a simpler functionalization and modification of RGOM with bioreceptor units, than reduced graphene oxide (RGO). With additional antibody-antigen binding, the RGOM-based biosensor achieved better real-time and label-free detection. The RGOM-based biosensor presented a more satisfactory response to goat anti-rabbit IgG than the RGO-based biosensor. This method is promising for immobilizing biomolecules on graphene surfaces and for the fabrication of biosensors with enhanced sensitivity. Full article
(This article belongs to the Special Issue Biosensors for Antibody Detection)
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Open AccessArticle A Hierarchical Building Segmentation in Digital Surface Models for 3D Reconstruction
Sensors 2017, 17(2), 222; doi:10.3390/s17020222
Received: 17 October 2016 / Revised: 30 December 2016 / Accepted: 13 January 2017 / Published: 24 January 2017
Cited by 1 | PDF Full-text (6767 KB) | HTML Full-text | XML Full-text
Abstract
In this study, a hierarchical method for segmenting buildings in a digital surface model (DSM), which is used in a novel framework for 3D reconstruction, is proposed. Most 3D reconstructions of buildings are model-based. However, the limitations of these methods are overreliance on
[...] Read more.
In this study, a hierarchical method for segmenting buildings in a digital surface model (DSM), which is used in a novel framework for 3D reconstruction, is proposed. Most 3D reconstructions of buildings are model-based. However, the limitations of these methods are overreliance on completeness of the offline-constructed models of buildings, and the completeness is not easily guaranteed since in modern cities buildings can be of a variety of types. Therefore, a model-free framework using high precision DSM and texture-images buildings was introduced. There are two key problems with this framework. The first one is how to accurately extract the buildings from the DSM. Most segmentation methods are limited by either the terrain factors or the difficult choice of parameter-settings. A level-set method are employed to roughly find the building regions in the DSM, and then a recently proposed ‘occlusions of random textures model’ are used to enhance the local segmentation of the buildings. The second problem is how to generate the facades of buildings. Synergizing with the corresponding texture-images, we propose a roof-contour guided interpolation of building facades. The 3D reconstruction results achieved by airborne-like images and satellites are compared. Experiments show that the segmentation method has good performance, and 3D reconstruction is easily performed by our framework, and better visualization results can be obtained by airborne-like images, which can be further replaced by UAV images. Full article
(This article belongs to the Special Issue UAV-Based Remote Sensing)
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Open AccessArticle A 11 mW 2.4 GHz 0.18 µm CMOS Transceivers for Wireless Sensor Networks
Sensors 2017, 17(2), 223; doi:10.3390/s17020223
Received: 11 September 2016 / Revised: 23 November 2016 / Accepted: 22 December 2016 / Published: 24 January 2017
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Abstract
In this paper, a low power transceiver for wireless sensor networks (WSN) is proposed. The system is designed with fully functional blocks including a receiver, a fractional-N frequency synthesizer, and a class-E transmitter, and it is optimized with a good balance among output
[...] Read more.
In this paper, a low power transceiver for wireless sensor networks (WSN) is proposed. The system is designed with fully functional blocks including a receiver, a fractional-N frequency synthesizer, and a class-E transmitter, and it is optimized with a good balance among output power, sensitivity, power consumption, and silicon area. A transmitter and receiver (TX-RX) shared input-output matching network is used so that only one off-chip inductor is needed in the system. The power and area efficiency-oriented, fully-integrated frequency synthesizer is able to provide programmable output frequencies in the 2.4 GHz range while occupying a small silicon area. Implemented in a standard 0.18 μm RF Complementary Metal Oxide Semiconductor (CMOS) technology, the whole transceiver occupies a chip area of 0.5 mm2 (1.2 mm2 including bonding pads for a QFN package). Measurement results suggest that the design is able to work at amplitude shift keying (ASK)/on-off-keying (OOK) and FSK modes with up to 500 kbps data rate. With an input sensitivity of −60 dBm and an output power of 3 dBm, the receiver, transmitter and frequency synthesizer consumes 2.3 mW, 4.8 mW, and 3.9 mW from a 1.8 V supply voltage, respectively. Full article
(This article belongs to the Special Issue Smart Sensor Interface Circuits and Systems)
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Open AccessArticle Outage Probability Minimization for Energy Harvesting Cognitive Radio Sensor Networks
Sensors 2017, 17(2), 224; doi:10.3390/s17020224
Received: 29 November 2016 / Revised: 3 January 2017 / Accepted: 17 January 2017 / Published: 24 January 2017
Cited by 1 | PDF Full-text (941 KB) | HTML Full-text | XML Full-text
Abstract
The incorporation of cognitive radio (CR) capability in wireless sensor networks yields a promising network paradigm known as CR sensor networks (CRSNs), which is able to provide spectrum efficient data communication. However, due to the high energy consumption results from spectrum sensing, as
[...] Read more.
The incorporation of cognitive radio (CR) capability in wireless sensor networks yields a promising network paradigm known as CR sensor networks (CRSNs), which is able to provide spectrum efficient data communication. However, due to the high energy consumption results from spectrum sensing, as well as subsequent data transmission, the energy supply for the conventional sensor nodes powered by batteries is regarded as a severe bottleneck for sustainable operation. The energy harvesting technique, which gathers energy from the ambient environment, is regarded as a promising solution to perpetually power-up energy-limited devices with a continual source of energy. Therefore, applying the energy harvesting (EH) technique in CRSNs is able to facilitate the self-sustainability of the energy-limited sensors. The primary concern of this study is to design sensing-transmission policies to minimize the long-term outage probability of EH-powered CR sensor nodes. We formulate this problem as an infinite-horizon discounted Markov decision process and propose an ϵ-optimal sensing-transmission (ST) policy through using the value iteration algorithm. ϵ is the error bound between the ST policy and the optimal policy, which can be pre-defined according to the actual need. Moreover, for a special case that the signal-to-noise (SNR) power ratio is sufficiently high, we present an efficient transmission (ET) policy and prove that the ET policy achieves the same performance with the ST policy. Finally, extensive simulations are conducted to evaluate the performance of the proposed policies and the impaction of various network parameters. Full article
(This article belongs to the Section Sensor Networks)
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Open AccessArticle An Efficient Location Verification Scheme for Static Wireless Sensor Networks
Sensors 2017, 17(2), 225; doi:10.3390/s17020225
Received: 18 July 2016 / Revised: 17 January 2017 / Accepted: 19 January 2017 / Published: 24 January 2017
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Abstract
In wireless sensor networks (WSNs), the accuracy of location information is vital to support many interesting applications. Unfortunately, sensors have difficulty in estimating their location when malicious sensors attack the location estimation process. Even though secure localization schemes have been proposed to protect
[...] Read more.
In wireless sensor networks (WSNs), the accuracy of location information is vital to support many interesting applications. Unfortunately, sensors have difficulty in estimating their location when malicious sensors attack the location estimation process. Even though secure localization schemes have been proposed to protect location estimation process from attacks, they are not enough to eliminate the wrong location estimations in some situations. The location verification can be the solution to the situations or be the second-line defense. The problem of most of the location verifications is the explicit involvement of many sensors in the verification process and requirements, such as special hardware, a dedicated verifier and the trusted third party, which causes more communication and computation overhead. In this paper, we propose an efficient location verification scheme for static WSN called mutually-shared region-based location verification (MSRLV), which reduces those overheads by utilizing the implicit involvement of sensors and eliminating several requirements. In order to achieve this, we use the mutually-shared region between location claimant and verifier for the location verification. The analysis shows that MSRLV reduces communication overhead by 77% and computation overhead by 92% on average, when compared with the other location verification schemes, in a single sensor verification. In addition, simulation results for the verification of the whole network show that MSRLV can detect the malicious sensors by over 90% when sensors in the network have five or more neighbors. Full article
(This article belongs to the Section Sensor Networks)
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Open AccessArticle Single-Step Purification of Monomeric l-Selectin via Aptamer Affinity Chromatography
Sensors 2017, 17(2), 226; doi:10.3390/s17020226
Received: 22 December 2016 / Revised: 19 January 2017 / Accepted: 20 January 2017 / Published: 24 January 2017
Cited by 3 | PDF Full-text (2240 KB) | HTML Full-text | XML Full-text
Abstract
l-selectin is a transmembrane receptor expressed on the surface of white blood cells and responsible for the tethering of leukocytes to vascular endothelial cells. This initial intercellular contact is the first step of the complex leukocyte adhesion cascade that ultimately permits extravasation
[...] Read more.
l-selectin is a transmembrane receptor expressed on the surface of white blood cells and responsible for the tethering of leukocytes to vascular endothelial cells. This initial intercellular contact is the first step of the complex leukocyte adhesion cascade that ultimately permits extravasation of leukocytes into the surrounding tissue in case of inflammation. Here we show the binding of a soluble histidine tagged l-selectin to a recently described shortened variant of an l-selectin specific DNA aptamer with surface plasmon resonance. The high specificity of this aptamer in combination with its high binding affinity of ~12 nM, allows for a single-step protein purification from cell culture supernatants. In comparison to the well-established Ni-NTA based technology, aptamer affinity chromatography (AAC) was easier to establish, resulted in a 3.6-fold higher protein yield, and increased protein purity. Moreover, due to target specificity, the DNA aptamer facilitated binding studies directly from cell culture supernatant, a helpful characteristic to quickly monitor successful expression of biological active l-selectin. Full article
(This article belongs to the Special Issue Aptasensors 2016)
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Open AccessArticle Customization of UWB 3D-RTLS Based on the New Uncertainty Model of the AoA Ranging Technique
Sensors 2017, 17(2), 227; doi:10.3390/s17020227
Received: 14 September 2016 / Revised: 23 December 2016 / Accepted: 18 January 2017 / Published: 25 January 2017
Cited by 1 | PDF Full-text (17233 KB) | HTML Full-text | XML Full-text
Abstract
The increased potential and effectiveness of Real-time Locating Systems (RTLSs) substantially influence their application spectrum. They are widely used, inter alia, in the industrial sector, healthcare, home care, and in logistic and security applications. The research aims to develop an analytical method to
[...] Read more.
The increased potential and effectiveness of Real-time Locating Systems (RTLSs) substantially influence their application spectrum. They are widely used, inter alia, in the industrial sector, healthcare, home care, and in logistic and security applications. The research aims to develop an analytical method to customize UWB-based RTLS, in order to improve their localization performance in terms of accuracy and precision. The analytical uncertainty model of Angle of Arrival (AoA) localization in a 3D indoor space, which is the foundation of the customization concept, is established in a working environment. Additionally, a suitable angular-based 3D localization algorithm is introduced. The paper investigates the following issues: the influence of the proposed correction vector on the localization accuracy; the impact of the system’s configuration and LS’s relative deployment on the localization precision distribution map. The advantages of the method are verified by comparing them with a reference commercial RTLS localization engine. The results of simulations and physical experiments prove the value of the proposed customization method. The research confirms that the analytical uncertainty model is the valid representation of RTLS’ localization uncertainty in terms of accuracy and precision and can be useful for its performance improvement. The research shows, that the Angle of Arrival localization in a 3D indoor space applying the simple angular-based localization algorithm and correction vector improves of localization accuracy and precision in a way that the system challenges the reference hardware advanced localization engine. Moreover, the research guides the deployment of location sensors to enhance the localization precision. Full article
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Open AccessArticle Fusion of High Resolution Multispectral Imagery in Vulnerable Coastal and Land Ecosystems
Sensors 2017, 17(2), 228; doi:10.3390/s17020228
Received: 4 October 2016 / Revised: 14 December 2016 / Accepted: 17 January 2017 / Published: 25 January 2017
Cited by 1 | PDF Full-text (12094 KB) | HTML Full-text | XML Full-text
Abstract
Ecosystems provide a wide variety of useful resources that enhance human welfare, but these resources are declining due to climate change and anthropogenic pressure. In this work, three vulnerable ecosystems, including shrublands, coastal areas with dunes systems and areas of shallow water, are
[...] Read more.
Ecosystems provide a wide variety of useful resources that enhance human welfare, but these resources are declining due to climate change and anthropogenic pressure. In this work, three vulnerable ecosystems, including shrublands, coastal areas with dunes systems and areas of shallow water, are studied. As far as these resources’ reduction is concerned, remote sensing and image processing techniques could contribute to the management of these natural resources in a practical and cost-effective way, although some improvements are needed for obtaining a higher quality of the information available. An important quality improvement is the fusion at the pixel level. Hence, the objective of this work is to assess which pansharpening technique provides the best fused image for the different types of ecosystems. After a preliminary evaluation of twelve classic and novel fusion algorithms, a total of four pansharpening algorithms was analyzed using six quality indices. The quality assessment was implemented not only for the whole set of multispectral bands, but also for the subset of spectral bands covered by the wavelength range of the panchromatic image and outside of it. A better quality result is observed in the fused image using only the bands covered by the panchromatic band range. It is important to highlight the use of these techniques not only in land and urban areas, but a novel analysis in areas of shallow water ecosystems. Although the algorithms do not show a high difference in land and coastal areas, coastal ecosystems require simpler algorithms, such as fast intensity hue saturation, whereas more heterogeneous ecosystems need advanced algorithms, as weighted wavelet ‘à trous’ through fractal dimension maps for shrublands and mixed ecosystems. Moreover, quality map analysis was carried out in order to study the fusion result in each band at the local level. Finally, to demonstrate the performance of these pansharpening techniques, advanced Object-Based (OBIA) support vector machine classification was applied, and a thematic map for the shrubland ecosystem was obtained, which corroborates wavelet ‘à trous’ through fractal dimension maps as the best fusion algorithm for this ecosystem. Full article
(This article belongs to the Section Remote Sensors)
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Open AccessArticle Hysteresis Compensation of Piezoresistive Carbon Nanotube/Polydimethylsiloxane Composite-Based Force Sensors
Sensors 2017, 17(2), 229; doi:10.3390/s17020229
Received: 9 November 2016 / Revised: 27 December 2016 / Accepted: 20 January 2017 / Published: 24 January 2017
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Abstract
This paper provides a preliminary study on the hysteresis compensation of a piezoresistive silicon-based polymer composite, poly(dimethylsiloxane) dispersed with carbon nanotubes (CNTs), to demonstrate its feasibility as a conductive composite (i.e., a force-sensitive resistor) for force sensors. In this study, the potential use
[...] Read more.
This paper provides a preliminary study on the hysteresis compensation of a piezoresistive silicon-based polymer composite, poly(dimethylsiloxane) dispersed with carbon nanotubes (CNTs), to demonstrate its feasibility as a conductive composite (i.e., a force-sensitive resistor) for force sensors. In this study, the potential use of the nanotube/polydimethylsiloxane (CNT/PDMS) as a force sensor is evaluated for the first time. The experimental results show that the electrical resistance of the CNT/PDMS composite changes in response to sinusoidal loading and static compressive load. The compensated output based on the Duhem hysteresis model shows a linear relationship. This simple hysteresis model can compensate for the nonlinear frequency-dependent hysteresis phenomenon when a dynamic sinusoidal force input is applied. Full article
(This article belongs to the Section Physical Sensors)
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Open AccessArticle Wideband Direction of Arrival Estimation in the Presence of Unknown Mutual Coupling
Sensors 2017, 17(2), 230; doi:10.3390/s17020230
Received: 23 August 2016 / Revised: 12 January 2017 / Accepted: 13 January 2017 / Published: 6 February 2017
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Abstract
This paper investigates a subarray based algorithm for direction of arrival (DOA) estimation of wideband uniform linear array (ULA), under the presence of frequency-dependent mutual coupling effects. Based on the Toeplitz structure of mutual coupling matrices, the whole array is divided into the
[...] Read more.
This paper investigates a subarray based algorithm for direction of arrival (DOA) estimation of wideband uniform linear array (ULA), under the presence of frequency-dependent mutual coupling effects. Based on the Toeplitz structure of mutual coupling matrices, the whole array is divided into the middle subarray and the auxiliary subarray. Then two-sided correlation transformation is applied to the correlation matrix of the middle subarray instead of the whole array. In this way, the mutual coupling effects can be eliminated. Finally, the multiple signal classification (MUSIC) method is utilized to derive the DOAs. For the condition when the blind angles exist, we refine DOA estimation by using a simple approach based on the frequency-dependent mutual coupling matrixes (MCMs). The proposed method can achieve high estimation accuracy without any calibration sources. It has a low computational complexity because iterative processing is not required. Simulation results validate the effectiveness and feasibility of the proposed algorithm. Full article
(This article belongs to the Section Physical Sensors)
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Open AccessArticle Emission Flux Measurement Error with a Mobile DOAS System and Application to NOx Flux Observations
Sensors 2017, 17(2), 231; doi:10.3390/s17020231
Received: 15 December 2016 / Revised: 18 January 2017 / Accepted: 19 January 2017 / Published: 25 January 2017
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Abstract
Mobile differential optical absorption spectroscopy (mobile DOAS) is an optical remote sensing method that can rapidly measure trace gas emission flux from air pollution sources (such as power plants, industrial areas, and cities) in real time. Generally, mobile DOAS is influenced by wind,
[...] Read more.
Mobile differential optical absorption spectroscopy (mobile DOAS) is an optical remote sensing method that can rapidly measure trace gas emission flux from air pollution sources (such as power plants, industrial areas, and cities) in real time. Generally, mobile DOAS is influenced by wind, drive velocity, and other factors, especially in the usage of wind field when the emission flux in a mobile DOAS system is observed. This paper presents a detailed error analysis and NOx emission with mobile DOAS system from a power plant in Shijiazhuang city, China. Comparison of the SO2 emission flux from mobile DOAS observations with continuous emission monitoring system (CEMS) under different drive speeds and wind fields revealed that the optimal drive velocity is 30–40 km/h, and the wind field at plume height is selected when mobile DOAS observations are performed. In addition, the total errors of SO2 and NO2 emissions with mobile DOAS measurements are 32% and 30%, respectively, combined with the analysis of the uncertainties of column density, wind field, and drive velocity. Furthermore, the NOx emission of 0.15 ± 0.06 kg/s from the power plant is estimated, which is in good agreement with that from CEMS observations of 0.17 ± 0.07 kg/s. This study has significantly contributed to the measurement of the mobile DOAS system on emission from air pollution sources, thus improving estimation accuracy. Full article
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Open AccessArticle Capacity-Delay Trade-Off in Collaborative Hybrid Ad-Hoc Networks with Coverage Sensing
Sensors 2017, 17(2), 232; doi:10.3390/s17020232
Received: 19 November 2016 / Revised: 12 January 2017 / Accepted: 18 January 2017 / Published: 26 January 2017
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Abstract
The integration of ad hoc device-to-device (D2D) communications and open-access small cells can result in a networking paradigm called hybrid the ad hoc network, which is particularly promising in delivering delay-tolerant data. The capacity-delay performance of hybrid ad hoc networks has been studied
[...] Read more.
The integration of ad hoc device-to-device (D2D) communications and open-access small cells can result in a networking paradigm called hybrid the ad hoc network, which is particularly promising in delivering delay-tolerant data. The capacity-delay performance of hybrid ad hoc networks has been studied extensively under a popular framework called scaling law analysis. These studies, however, do not take into account aspects of interference accumulation and queueing delay and, therefore, may lead to over-optimistic results. Moreover, focusing on the average measures, existing works fail to give finer-grained insights into the distribution of delays. This paper proposes an alternative analytical framework based on queueing theoretic models and physical interference models. We apply this framework to study the capacity-delay performance of a collaborative cellular D2D network with coverage sensing and two-hop relay. The new framework allows us to fully characterize the delay distribution in the transform domain and pinpoint the impacts of coverage sensing, user and base station densities, transmit power, user mobility and packet size on the capacity-delay trade-off. We show that under the condition of queueing equilibrium, the maximum throughput capacity per device saturates to an upper bound of 0.7239 λ b / λ u bits/s/Hz, where λ b and λ u are the densities of base stations and mobile users, respectively. Full article
(This article belongs to the Special Issue New Paradigms in Cyber-Physical Social Sensing)
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Open AccessArticle A Denoising Scheme for Randomly Clustered Noise Removal in ICCD Sensing Image
Sensors 2017, 17(2), 233; doi:10.3390/s17020233
Received: 17 November 2016 / Revised: 22 December 2016 / Accepted: 9 January 2017 / Published: 26 January 2017
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Abstract
An Intensified Charge-Coupled Device (ICCD) image is captured by the ICCD image sensor in extremely low-light conditions. Its noise has two distinctive characteristics. (a) Different from the independent identically distributed (i.i.d.) noise in natural image, the noise in the ICCD sensing
[...] Read more.
An Intensified Charge-Coupled Device (ICCD) image is captured by the ICCD image sensor in extremely low-light conditions. Its noise has two distinctive characteristics. (a) Different from the independent identically distributed (i.i.d.) noise in natural image, the noise in the ICCD sensing image is spatially clustered, which induces unexpected structure information; (b) The pattern of the clustered noise is formed randomly. In this paper, we propose a denoising scheme to remove the randomly clustered noise in the ICCD sensing image. First, we decompose the image into non-overlapped patches and classify them into flat patches and structure patches according to if real structure information is included. Then, two denoising algorithms are designed for them, respectively. For each flat patch, we simulate multiple similar patches for it in pseudo-time domain and remove its noise by averaging all the simulated patches, considering that the structure information induced by the noise varies randomly over time. For each structure patch, we design a structure-preserved sparse coding algorithm to reconstruct the real structure information. It reconstructs each patch by describing it as a weighted summation of its neighboring patches and incorporating the weights into the sparse representation of the current patch. Based on all the reconstructed patches, we generate a reconstructed image. After that, we repeat the whole process by changing relevant parameters, considering that blocking artifacts exist in a single reconstructed image. Finally, we obtain the reconstructed image by merging all the generated images into one. Experiments are conducted on an ICCD sensing image dataset, which verifies its subjective performance in removing the randomly clustered noise and preserving the real structure information in the ICCD sensing image. Full article
(This article belongs to the Section Physical Sensors)
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Open AccessArticle Set-Based Discriminative Measure for Electrocardiogram Beat Classification
Sensors 2017, 17(2), 234; doi:10.3390/s17020234
Received: 2 December 2016 / Revised: 10 January 2017 / Accepted: 16 January 2017 / Published: 25 January 2017
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Abstract
Computer aided diagnosis systems can help to reduce the high mortality rate among cardiac patients. Automatical classification of electrocardiogram (ECG) beats plays an important role in such systems, but this issue is challenging because of the complexities of ECG signals. In literature, feature
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Computer aided diagnosis systems can help to reduce the high mortality rate among cardiac patients. Automatical classification of electrocardiogram (ECG) beats plays an important role in such systems, but this issue is challenging because of the complexities of ECG signals. In literature, feature designing has been broadly-studied. However, such methodology is inevitably limited by the heuristics of hand-crafting process and the challenge of signals themselves. To address it, we treat the problem of ECG beat classification from the metric and measurement perspective. We propose a novel approach, named “Set-Based Discriminative Measure”, which first learns a discriminative metric space to ensure that intra-class distances are smaller than inter-class distances for ECG features in a global way, and then measures a new set-based dissimilarity in such learned space to cope with the local variation of samples. Experimental results have demonstrated the advantage of this approach in terms of effectiveness, robustness, and flexibility based on ECG beats from the MIT-BIH Arrhythmia Database. Full article
(This article belongs to the Section State-of-the-Art Sensors Technologies)
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Open AccessArticle Earthquake Damage Visualization (EDV) Technique for the Rapid Detection of Earthquake-Induced Damages Using SAR Data
Sensors 2017, 17(2), 235; doi:10.3390/s17020235
Received: 27 September 2016 / Accepted: 18 January 2017 / Published: 27 January 2017
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Abstract
The damage of buildings and manmade structures, where most of human activities occur, is the major cause of casualties of from earthquakes. In this paper, an improved technique, Earthquake Damage Visualization (EDV) is presented for the rapid detection of earthquake damage using the
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The damage of buildings and manmade structures, where most of human activities occur, is the major cause of casualties of from earthquakes. In this paper, an improved technique, Earthquake Damage Visualization (EDV) is presented for the rapid detection of earthquake damage using the Synthetic Aperture Radar (SAR) data. The EDV is based on the pre-seismic and co-seismic coherence change method. The normalized difference between the pre-seismic and co-seismic coherences, and vice versa, are used to calculate the forward (from pre-seismic to co-seismic) and backward (from co-seismic to pre-seismic) change parameters, respectively. The backward change parameter is added to visualize the retrospective changes caused by factors other than the earthquake. The third change-free parameter uses the average values of the pre-seismic and co-seismic coherence maps. These three change parameters were ultimately merged into the EDV as an RGB (Red, Green, and Blue) composite imagery. The EDV could visualize the earthquake damage efficiently using Horizontal transmit and Horizontal receive (HH), and Horizontal transmit and Vertical receive (HV) polarizations data from the Advanced Land Observing Satellite-2 (ALOS-2). Its performance was evaluated in the Kathmandu Valley, which was hit severely by the 2015 Nepal Earthquake. The cross-validation results showed that the EDV is more sensitive to the damaged buildings than the existing method. The EDV could be used for building damage detection in other earthquakes as well. Full article
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Open AccessArticle Fabrication of Annealed Gold Nanostructures on Pre-Treated Glow-Discharge Cleaned Glasses and Their Used for Localized Surface Plasmon Resonance (LSPR) and Surface Enhanced Raman Spectroscopy (SERS) Detection of Adsorbed (Bio)molecules
Sensors 2017, 17(2), 236; doi:10.3390/s17020236
Received: 21 November 2016 / Revised: 4 January 2017 / Accepted: 18 January 2017 / Published: 26 January 2017
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Abstract
Metallic nanoparticles are considered as active supports in the development of specific chemical or biological biosensors. Well-organized nanoparticles can be prepared either through expensive (e.g., electron beam lithography) or inexpensive (e.g., thermal synthesis) approaches where different shapes of nanoparticles are easily obtained over
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Metallic nanoparticles are considered as active supports in the development of specific chemical or biological biosensors. Well-organized nanoparticles can be prepared either through expensive (e.g., electron beam lithography) or inexpensive (e.g., thermal synthesis) approaches where different shapes of nanoparticles are easily obtained over large solid surfaces. Herein, the authors propose a low-cost thermal synthesis of active plasmonic nanostructures on thin gold layers modified glass supports after 1 h holding on a hot plate (~350 °C). The resulted annealed nanoparticles proved a good reproducibility of localized surface plasmon resonance (LSPR) and surface enhanced Raman spectroscopy (SERS) optical responses and where used for the detection of low concentrations of two model (bio)chemical molecules, namely the human cytochrome b5 (Cyt-b5) and trans-1,2-bis(4-pyridyl)ethylene (BPE). Full article
(This article belongs to the Special Issue Last Advances in Nanoplasmonics Biosensors)
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Open AccessArticle Practical Considerations in the Implementation of Collaborative Beamforming on Wireless Sensor Networks
Sensors 2017, 17(2), 237; doi:10.3390/s17020237
Received: 28 November 2016 / Revised: 18 January 2017 / Accepted: 19 January 2017 / Published: 26 January 2017
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Abstract
Wireless Sensor Networks (WSNs) are composed of spatially distributed autonomous sensor devices, named motes. These motes have their own power supply, processing unit, sensors and wireless communications However with many constraints, such as limited energy, bandwidth and computational capabilities. In these networks, at
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Wireless Sensor Networks (WSNs) are composed of spatially distributed autonomous sensor devices, named motes. These motes have their own power supply, processing unit, sensors and wireless communications However with many constraints, such as limited energy, bandwidth and computational capabilities. In these networks, at least one mote called a sink, acts as a gateway to connect with other networks. These sensor networks run monitoring applications and then the data gathered by these motes needs to be retrieved by the sink. When this sink is located in the far field, there have been many proposals in the literature based on Collaborative Beamforming (CB), also known as Distributed or Cooperative Beamforming, for these long range communications to reach the sink. In this paper, we conduct a thorough study of the related work and analyze the requirements to do CB. In order to implement these communications in real scenarios, we will consider if these requirements and the assumptions made are feasible from the point of view of commercial motes and their constraints. In addition, we will go a step further and will consider different alternatives, by relaxing these requirements, trying to find feasible assumptions to carry out these types of communications with commercial motes. This research considers the nonavailability of a central clock that synchronizes all motes in the WSN, and all motes have identical hardware. This is a feasibility study to do CB on WSN, using a simulated scenario with randomized delays obtained from experimental data from commercial motes. Full article
(This article belongs to the Special Issue State-of-the-Art Sensors Technology in Spain 2016)
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Open AccessArticle Combining CHAMP and Swarm Satellite Data to Invert the Lithospheric Magnetic Field in the Tibetan Plateau
Sensors 2017, 17(2), 238; doi:10.3390/s17020238
Received: 2 November 2016 / Revised: 18 January 2017 / Accepted: 19 January 2017 / Published: 26 January 2017
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Abstract
CHAMP and Swarm satellite magnetic data are combined to establish the lithospheric magnetic field over the Tibetan Plateau at satellite altitude by using zonal revised spherical cap harmonic analysis (R-SCHA). These data are integrated with geological structures data to analyze the relationship between
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CHAMP and Swarm satellite magnetic data are combined to establish the lithospheric magnetic field over the Tibetan Plateau at satellite altitude by using zonal revised spherical cap harmonic analysis (R-SCHA). These data are integrated with geological structures data to analyze the relationship between magnetic anomaly signals and large-scale geological tectonic over the Tibetan Plateau and to explore the active tectonic region based on the angle of the magnetic anomaly. Results show that the model fitting error is small for a layer 250–500 km high, and the RMSE of the horizontal and radial geomagnetic components is better than 0.3 nT. The proposed model can accurately describe medium- to long-scale lithospheric magnetic anomalies. Analysis indicates that a negative magnetic anomaly in the Tibetan Plateau significantly differs with a positive magnetic anomaly in the surrounding area, and the boundary of the positive and negative regions is generally consistent with the geological tectonic boundary in the plateau region. Significant differences exist between the basement structures of the hinterland of the plateau and the surrounding area. The magnetic anomaly in the Central and Western Tibetan Plateau shows an east–west trend, which is identical to the direction of the geological structures. The magnetic anomaly in the eastern part is arc-shaped and extends along the northeast direction. Its direction is significantly different from the trend of the geological structures. The strongest negative anomaly is located in the Himalaya block, with a central strength of up to −9 nT at a height of 300 km. The presence of a strong negative anomaly implies that the Curie isotherm in this area is relatively shallow and deep geological tectonic activity may exist. Full article
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Open AccessArticle Performance Enhancement of a USV INS/CNS/DVL Integration Navigation System Based on an Adaptive Information Sharing Factor Federated Filter
Sensors 2017, 17(2), 239; doi:10.3390/s17020239
Received: 30 November 2016 / Revised: 14 January 2017 / Accepted: 19 January 2017 / Published: 3 February 2017
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Abstract
To improve the ability of autonomous navigation for Unmanned Surface Vehicles (USVs), multi-sensor integrated navigation based on Inertial Navigation System (INS), Celestial Navigation System (CNS) and Doppler Velocity Log (DVL) is proposed. The CNS position and the DVL velocity are introduced as the
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To improve the ability of autonomous navigation for Unmanned Surface Vehicles (USVs), multi-sensor integrated navigation based on Inertial Navigation System (INS), Celestial Navigation System (CNS) and Doppler Velocity Log (DVL) is proposed. The CNS position and the DVL velocity are introduced as the reference information to correct the INS divergence error. The autonomy of the integrated system based on INS/CNS/DVL is much better compared with the integration based on INS/GNSS alone. However, the accuracy of DVL velocity and CNS position are decreased by the measurement noise of DVL and bad weather, respectively. Hence, the INS divergence error cannot be estimated and corrected by the reference information. To resolve the problem, the Adaptive Information Sharing Factor Federated Filter (AISFF) is introduced to fuse data. The information sharing factor of the Federated Filter is adaptively adjusted to maintaining multiple component solutions usable as back-ups, which can improve the reliability of overall system. The effectiveness of this approach is demonstrated by simulation and experiment, the results show that for the INS/CNS/DVL integrated system, when the DVL velocity accuracy is decreased and the CNS cannot work under bad weather conditions, the INS/CNS/DVL integrated system can operate stably based on the AISFF method. Full article
(This article belongs to the Special Issue Multi-Sensor Integration and Fusion)
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Open AccessArticle Geometric Positioning for Satellite Imagery without Ground Control Points by Exploiting Repeated Observation
Sensors 2017, 17(2), 240; doi:10.3390/s17020240
Received: 21 November 2016 / Revised: 2 January 2017 / Accepted: 5 January 2017 / Published: 26 January 2017
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Abstract
With the development of space technology and the performance of remote sensors, high-resolution satellites are continuously launched by countries around the world. Due to high efficiency, large coverage and not being limited by the spatial regulation, satellite imagery becomes one of the important
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With the development of space technology and the performance of remote sensors, high-resolution satellites are continuously launched by countries around the world. Due to high efficiency, large coverage and not being limited by the spatial regulation, satellite imagery becomes one of the important means to acquire geospatial information. This paper explores geometric processing using satellite imagery without ground control points (GCPs). The outcome of spatial triangulation is introduced for geo-positioning as repeated observation. Results from combining block adjustment with non-oriented new images indicate the feasibility of geometric positioning with the repeated observation. GCPs are a must when high accuracy is demanded in conventional block adjustment; the accuracy of direct georeferencing with repeated observation without GCPs is superior to conventional forward intersection and even approximate to conventional block adjustment with GCPs. The conclusion is drawn that taking the existing oriented imagery as repeated observation enhances the effective utilization of previous spatial triangulation achievement, which makes the breakthrough for repeated observation to improve accuracy by increasing the base-height ratio and redundant observation. Georeferencing tests using data from multiple sensors and platforms with the repeated observation will be carried out in the follow-up research. Full article
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Open AccessArticle IEEE 802.15.4 Frame Aggregation Enhancement to Provide High Performance in Life-Critical Patient Monitoring Systems
Sensors 2017, 17(2), 241; doi:10.3390/s17020241
Received: 3 November 2016 / Revised: 18 January 2017 / Accepted: 23 January 2017 / Published: 28 January 2017
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Abstract
In wireless body area sensor networks (WBASNs), Quality of Service (QoS) provision for patient monitoring systems in terms of time-critical deadlines, high throughput and energy efficiency is a challenging task. The periodic data from these systems generates a large number of small packets
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In wireless body area sensor networks (WBASNs), Quality of Service (QoS) provision for patient monitoring systems in terms of time-critical deadlines, high throughput and energy efficiency is a challenging task. The periodic data from these systems generates a large number of small packets in a short time period which needs an efficient channel access mechanism. The IEEE 802.15.4 standard is recommended for low power devices and widely used for many wireless sensor networks applications. It provides a hybrid channel access mechanism at the Media Access Control (MAC) layer which plays a key role in overall successful transmission in WBASNs. There are many WBASN’s MAC protocols that use this hybrid channel access mechanism in variety of sensor applications. However, these protocols are less efficient for patient monitoring systems where life critical data requires limited delay, high throughput and energy efficient communication simultaneously. To address these issues, this paper proposes a frame aggregation scheme by using the aggregated-MAC protocol data unit (A-MPDU) which works with the IEEE 802.15.4 MAC layer. To implement the scheme accurately, we develop a traffic patterns analysis mechanism to understand the requirements of the sensor nodes in patient monitoring systems, then model the channel access to find the performance gap on the basis of obtained requirements, finally propose the design based on the needs of patient monitoring systems. The mechanism is initially verified using numerical modelling and then simulation is conducted using NS2.29, Castalia 3.2 and OMNeT++. The proposed scheme provides the optimal performance considering the required QoS. Full article
(This article belongs to the Special Issue Advances in Body Sensor Networks: Sensors, Systems, and Applications)
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Open AccessArticle Structure-From-Motion in 3D Space Using 2D Lidars
Sensors 2017, 17(2), 242; doi:10.3390/s17020242
Received: 27 September 2016 / Revised: 11 January 2017 / Accepted: 17 January 2017 / Published: 3 February 2017
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Abstract
This paper presents a novel structure-from-motion methodology using 2D lidars (Light Detection And Ranging). In 3D space, 2D lidars do not provide sufficient information for pose estimation. For this reason, additional sensors have been used along with the lidar measurement. In this paper,
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This paper presents a novel structure-from-motion methodology using 2D lidars (Light Detection And Ranging). In 3D space, 2D lidars do not provide sufficient information for pose estimation. For this reason, additional sensors have been used along with the lidar measurement. In this paper, we use a sensor system that consists of only 2D lidars, without any additional sensors. We propose a new method of estimating both the 6D pose of the system and the surrounding 3D structures. We compute the pose of the system using line segments of scan data and their corresponding planes. After discarding the outliers, both the pose and the 3D structures are refined via nonlinear optimization. Experiments with both synthetic and real data show the accuracy and robustness of the proposed method. Full article
(This article belongs to the Section Physical Sensors)
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Open AccessArticle A Quantitative Comparison of Calibration Methods for RGB-D Sensors Using Different Technologies
Sensors 2017, 17(2), 243; doi:10.3390/s17020243
Received: 21 October 2016 / Accepted: 11 January 2017 / Published: 27 January 2017
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Abstract
RGB-D (Red Green Blue and Depth) sensors are devices that can provide color and depth information from a scene at the same time. Recently, they have been widely used in many solutions due to their commercial growth from the entertainment market
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RGB-D (Red Green Blue and Depth) sensors are devices that can provide color and depth information from a scene at the same time. Recently, they have been widely used in many solutions due to their commercial growth from the entertainment market to many diverse areas (e.g., robotics, CAD, etc.). In the research community, these devices have had good uptake due to their acceptable levelofaccuracyformanyapplicationsandtheirlowcost,butinsomecases,theyworkatthelimitof their sensitivity, near to the minimum feature size that can be perceived. For this reason, calibration processes are critical in order to increase their accuracy and enable them to meet the requirements of such kinds of applications. To the best of our knowledge, there is not a comparative study of calibration algorithms evaluating its results in multiple RGB-D sensors. Specifically, in this paper, a comparison of the three most used calibration methods have been applied to three different RGB-D sensors based on structured light and time-of-flight. The comparison of methods has been carried out by a set of experiments to evaluate the accuracy of depth measurements. Additionally, an object reconstruction application has been used as example of an application for which the sensor works at the limit of its sensitivity. The obtained results of reconstruction have been evaluated through visual inspection and quantitative measurements. Full article
(This article belongs to the Special Issue State-of-the-Art Sensors Technology in Spain 2016)
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Open AccessArticle Application of the PAMONO-Sensor for Quantification of Microvesicles and Determination of Nano-Particle Size Distribution
Sensors 2017, 17(2), 244; doi:10.3390/s17020244
Received: 31 October 2016 / Accepted: 16 January 2017 / Published: 27 January 2017
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Abstract
The PAMONO-sensor (plasmon assisted microscopy of nano-objects) demonstrated an ability to detect and quantify individual viruses and virus-like particles. However, another group of biological vesicles—microvesicles (100–1000 nm)—also attracts growing interest as biomarkers of different pathologies and needs development of novel techniques for characterization.
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The PAMONO-sensor (plasmon assisted microscopy of nano-objects) demonstrated an ability to detect and quantify individual viruses and virus-like particles. However, another group of biological vesicles—microvesicles (100–1000 nm)—also attracts growing interest as biomarkers of different pathologies and needs development of novel techniques for characterization. This work shows the applicability of a PAMONO-sensor for selective detection of microvesicles in aquatic samples. The sensor permits comparison of relative concentrations of microvesicles between samples. We also study a possibility of repeated use of a sensor chip after elution of the microvesicle capturing layer. Moreover, we improve the detection features of the PAMONO-sensor. The detection process utilizes novel machine learning techniques on the sensor image data to estimate particle size distributions of nano-particles in polydisperse samples. Altogether, our findings expand analytical features and the application field of the PAMONO-sensor. They can also serve for a maturation of diagnostic tools based on the PAMONO-sensor platform. Full article
(This article belongs to the Special Issue Last Advances in Nanoplasmonics Biosensors)
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Open AccessArticle Trust-Based Cooperative Social System Applied to a Carpooling Platform for Smartphones
Sensors 2017, 17(2), 245; doi:10.3390/s17020245
Received: 9 December 2016 / Accepted: 24 January 2017 / Published: 27 January 2017
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Abstract
One of the worst traffic problems today is the existence of huge traffic jams in almost any big city, produced by the large number of commuters using private cars. This problem has led to an increase in research on the optimization of vehicle
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One of the worst traffic problems today is the existence of huge traffic jams in almost any big city, produced by the large number of commuters using private cars. This problem has led to an increase in research on the optimization of vehicle occupancy in urban areas as this would help to solve the problem that most cars are occupied by single passengers. The solution of sharing the available seats in cars, known as carpooling, is already available in major cities around the world. However, carpooling is still not considered a safe and reliable solution for many users. With the widespread use of mobile technology and social networks, it is possible to create a trust-based platform to promote carpooling through a convenient, fast and secure system. The main objective of this work is the design and implementation of a carpool system that improves some important aspects of previous systems, focusing on trust between users, and on the security of the system. The proposed system guarantees user privacy and measures trust levels through a new reputation algorithm. In addition to this, the proposal has been developed as a mobile application for devices using the Android Open Source Project. Full article
(This article belongs to the Special Issue Sensors for Transportation)
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Open AccessArticle A Novel Method for Separating and Locating Multiple Partial Discharge Sources in a Substation
Sensors 2017, 17(2), 247; doi:10.3390/s17020247
Received: 15 December 2016 / Accepted: 23 January 2017 / Published: 27 January 2017
Cited by 1 | PDF Full-text (4808 KB) | HTML Full-text | XML Full-text | Supplementary Files
Abstract
To separate and locate multi-partial discharge (PD) sources in a substation, the use of spectrum differences of ultra-high frequency signals radiated from various sources as characteristic parameters has been previously reported. However, the separation success rate was poor when signal-to-noise ratio was low,
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To separate and locate multi-partial discharge (PD) sources in a substation, the use of spectrum differences of ultra-high frequency signals radiated from various sources as characteristic parameters has been previously reported. However, the separation success rate was poor when signal-to-noise ratio was low, and the localization result was a coordinate on two-dimensional plane. In this paper, a novel method is proposed to improve the separation rate and the localization accuracy. A directional measuring platform is built using two directional antennas. The time delay (TD) of the signals captured by the antennas is calculated, and TD sequences are obtained by rotating the platform at different angles. The sequences are separated with the TD distribution feature, and the directions of the multi-PD sources are calculated. The PD sources are located by directions using the error probability method. To verify the method, a simulated model with three PD sources was established by XFdtd. Simulation results show that the separation rate is increased from 71% to 95% compared with the previous method, and an accurate three-dimensional localization result was obtained. A field test with two PD sources was carried out, and the sources were separated and located accurately by the proposed method. Full article
(This article belongs to the Section Physical Sensors)
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Open AccessArticle Ultrafast Fiber Bragg Grating Interrogation for Sensing in Detonation and Shock Wave Experiments
Sensors 2017, 17(2), 248; doi:10.3390/s17020248
Received: 13 December 2016 / Accepted: 21 January 2017 / Published: 27 January 2017
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Abstract
Chirped fiber Bragg grating (CFBG) sensors coupled to high speed interrogation systems are described as robust diagnostic approaches to monitoring shock wave and detonation front propagation tracking events for use in high energy density shock physics applications. Taking advantage of the linear distributed
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Chirped fiber Bragg grating (CFBG) sensors coupled to high speed interrogation systems are described as robust diagnostic approaches to monitoring shock wave and detonation front propagation tracking events for use in high energy density shock physics applications. Taking advantage of the linear distributed spatial encoding of the spectral band in single-mode CFBGs, embedded fiber systems and associated photonic interrogation methodologies are shown as an effective approach to sensing shock and detonation-driven loading processes along the CFBG length. Two approaches, one that detects spectral changes in the integrated spectrum of the CFBG and another coherent pulse interrogation approach that fully resolves its spectral response, shows that 100-MHz–1-GHz interrogation rates are possible with spatial resolution along the CFBG in the 50 µm to sub-millimeter range depending on the combination of CFBG parameters (i.e., length, chirp rate, spectrum) and interrogator design specifics. Results from several dynamic tests are used to demonstrate the performance of these high speed systems for shock and detonation propagation tracking under strong and weak shock pressure loading: (1) linear detonation front tracking in the plastic bonded explosive (PBX) PBX-9501; (2) tracking of radial decaying shock with crossover to non-destructive CFBG response; (3) shock wave tracking along an aluminum cylinder wall under weak loading accompanied by dynamic strain effects in the CFBG sensor. Full article
(This article belongs to the Special Issue Recent Advances in Fiber Bragg Grating Sensing)
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Open AccessArticle Superframe Duration Allocation Schemes to Improve the Throughput of Cluster-Tree Wireless Sensor Networks
Sensors 2017, 17(2), 249; doi:10.3390/s17020249
Received: 16 September 2016 / Revised: 23 November 2016 / Accepted: 6 December 2016 / Published: 27 January 2017
Cited by 4 | PDF Full-text (7130 KB) | HTML Full-text | XML Full-text
Abstract
The use of Wireless Sensor Network (WSN) technologies is an attractive option to support wide-scale monitoring applications, such as the ones that can be found in precision agriculture, environmental monitoring and industrial automation. The IEEE 802.15.4/ZigBee cluster-tree topology is a suitable topology to
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The use of Wireless Sensor Network (WSN) technologies is an attractive option to support wide-scale monitoring applications, such as the ones that can be found in precision agriculture, environmental monitoring and industrial automation. The IEEE 802.15.4/ZigBee cluster-tree topology is a suitable topology to build wide-scale WSNs. Despite some of its known advantages, including timing synchronisation and duty-cycle operation, cluster-tree networks may suffer from severe network congestion problems due to the convergecast pattern of its communication traffic. Therefore, the careful adjustment of transmission opportunities (superframe durations) allocated to the cluster-heads is an important research issue. This paper proposes a set of proportional Superframe Duration Allocation (SDA) schemes, based on well-defined protocol and timing models, and on the message load imposed by child nodes (Load-SDA scheme), or by number of descendant nodes (Nodes-SDA scheme) of each cluster-head. The underlying reasoning is to adequately allocate transmission opportunities (superframe durations) and parametrize buffer sizes, in order to improve the network throughput and avoid typical problems, such as: network congestion, high end-to-end communication delays and discarded messages due to buffer overflows. Simulation assessments show how proposed allocation schemes may clearly improve the operation of wide-scale cluster-tree networks. Full article
(This article belongs to the Section Sensor Networks)
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Open AccessArticle Impedance-Based Pre-Stress Monitoring of Rock Bolts Using a Piezoceramic-Based Smart Washer—A Feasibility Study
Sensors 2017, 17(2), 250; doi:10.3390/s17020250
Received: 6 January 2017 / Accepted: 24 January 2017 / Published: 27 January 2017
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Abstract
Pre-stress degradation or looseness of rock bolts in mining or tunnel engineering threatens the stability and reliability of the structures. In this paper, an innovative piezoelectric device named a “smart washer” with the impedance method is proposed with the aim of developing a
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Pre-stress degradation or looseness of rock bolts in mining or tunnel engineering threatens the stability and reliability of the structures. In this paper, an innovative piezoelectric device named a “smart washer” with the impedance method is proposed with the aim of developing a real-time device to monitor the pre-stress level of rock bolts. The proposed method was verified through tests on a rock bolt specimen. By applying high-frequency sweep excitations (typically >30 kHz) to the smart washer that was installed on the rock bolt specimen, we observed that the variation in impedance signatures indicated the rock bolt pre-stress status. With the degradation of rock bolt pre-stress, the frequency in the dominating peak of the real part of the electrical impedance signature increased. To quantify the effectiveness of the proposed technique, a normalized root mean square deviation (RMSD) index was developed to evaluate the degradation level of the rock bolt pre-stress. The experimental results demonstrated that the normalized RMSD-based looseness index, which was computed from the impedance value detected by the “smart washer”, increased with loss of the pre-stress of the rock bolt. Therefore, the proposed method can effectively detect the degradation of rock bolt pre-stress, as demonstrated by experiments. Full article
(This article belongs to the Section Physical Sensors)
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Open AccessArticle Localized Temperature Variations in Laser-Irradiated Composites with Embedded Fiber Bragg Grating Sensors
Sensors 2017, 17(2), 251; doi:10.3390/s17020251
Received: 15 December 2016 / Accepted: 25 January 2017 / Published: 27 January 2017
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Abstract
Fiber Bragg grating (FBG) temperature sensors are embedded in composites to detect localized temperature gradients resulting from high energy infrared laser radiation. The goal is to detect the presence of radiation on a composite structure as rapidly as possible and to identify its
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Fiber Bragg grating (FBG) temperature sensors are embedded in composites to detect localized temperature gradients resulting from high energy infrared laser radiation. The goal is to detect the presence of radiation on a composite structure as rapidly as possible and to identify its location, much the same way human skin senses heat. A secondary goal is to determine how a network of sensors can be optimized to detect thermal damage in laser-irradiated composite materials or structures. Initial tests are conducted on polymer matrix composites reinforced with either carbon or glass fiber with a single optical fiber embedded into each specimen. As many as three sensors in each optical fiber measure the temporal and spatial thermal response of the composite to high energy radiation incident on the surface. Additional tests use a 2 × 2 × 3 array of 12 sensors embedded in a carbon fiber/epoxy composite to simultaneously measure temperature variations at locations on the composite surface and through the thickness. Results indicate that FBGs can be used to rapidly detect temperature gradients in a composite and their location, even for a direct strike of laser radiation on a sensor, when high temperatures can cause a non-uniform thermal response and FBG decay. Full article
(This article belongs to the Special Issue Recent Advances in Fiber Bragg Grating Sensing)
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Open AccessArticle A Novel Earphone Type Sensor for Measuring Mealtime: Consideration of the Method to Distinguish between Running and Meals
Sensors 2017, 17(2), 252; doi:10.3390/s17020252
Received: 25 October 2016 / Accepted: 24 January 2017 / Published: 27 January 2017
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Abstract
In this study, we describe a technique for estimating meal times using an earphone-type wearable sensor. A small optical sensor composed of a light-emitting diode and phototransistor is inserted into the ear hole of a user and estimates the meal times of the
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In this study, we describe a technique for estimating meal times using an earphone-type wearable sensor. A small optical sensor composed of a light-emitting diode and phototransistor is inserted into the ear hole of a user and estimates the meal times of the user from the time variations in the amount of light received. This is achieved by emitting light toward the inside of the ear canal and receiving light reflected back from the ear canal. This proposed technique allowed “meals” to be differentiated from having conversations, sneezing, walking, ascending and descending stairs, operating a computer, and using a smartphone. Conventional devices worn on the head of users and that measure food intake can vibrate during running as the body is jolted more violently than during walking; this can result in the misidentification of running as eating by these devices. To solve this problem, we used two of our sensors simultaneously: one in the left ear and one in the right ear. This was based on our finding that measurements from the left and right ear canals have a strong correlation during running but no correlation during eating. This allows running and eating to be distinguished based on correlation coefficients, which can reduce misidentification. Moreover, by using an optical sensor composed of a semiconductor, a small and lightweight device can be created. This measurement technique can also measure body motion associated with running, and the data obtained from the optical sensor inserted into the ear can be used to support a healthy lifestyle regarding both eating and exercise. Full article
(This article belongs to the Special Issue Wearable Biomedical Sensors)
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Open AccessArticle An Interactive Image Segmentation Method in Hand Gesture Recognition
Sensors 2017, 17(2), 253; doi:10.3390/s17020253
Received: 28 October 2016 / Accepted: 17 January 2017 / Published: 27 January 2017
Cited by 4 | PDF Full-text (6741 KB) | HTML Full-text | XML Full-text
Abstract
In order to improve the recognition rate of hand gestures a new interactive image segmentation method for hand gesture recognition is presented, and popular methods, e.g., Graph cut, Random walker, Interactive image segmentation using geodesic star convexity, are studied in this article. The
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In order to improve the recognition rate of hand gestures a new interactive image segmentation method for hand gesture recognition is presented, and popular methods, e.g., Graph cut, Random walker, Interactive image segmentation using geodesic star convexity, are studied in this article. The Gaussian Mixture Model was employed for image modelling and the iteration of Expectation Maximum algorithm learns the parameters of Gaussian Mixture Model. We apply a Gibbs random field to the image segmentation and minimize the Gibbs Energy using Min-cut theorem to find the optimal segmentation. The segmentation result of our method is tested on an image dataset and compared with other methods by estimating the region accuracy and boundary accuracy. Finally five kinds of hand gestures in different backgrounds are tested on our experimental platform, and the sparse representation algorithm is used, proving that the segmentation of hand gesture images helps to improve the recognition accuracy. Full article
(This article belongs to the Section Physical Sensors)
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Open AccessArticle A New, Adaptable, Optical High-Resolution 3-Axis Sensor
Sensors 2017, 17(2), 254; doi:10.3390/s17020254
Received: 13 December 2016 / Accepted: 23 January 2017 / Published: 27 January 2017
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Abstract
This article presents a new optical, multi-functional, high-resolution 3-axis sensor which serves to navigate and can, for example, replace standard joysticks in medical devices such as electric wheelchairs, surgical robots or medical diagnosis devices. A light source, e.g., a laser diode, is affixed
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This article presents a new optical, multi-functional, high-resolution 3-axis sensor which serves to navigate and can, for example, replace standard joysticks in medical devices such as electric wheelchairs, surgical robots or medical diagnosis devices. A light source, e.g., a laser diode, is affixed to a movable axis and projects a random geometric shape on an image sensor (CMOS or CCD). The downstream microcontroller’s software identifies the geometric shape’s center, distortion and size, and then calculates x, y, and z coordinates, which can be processed in attached devices. Depending on the image sensor in use (e.g., 6.41 megapixels), the 3-axis sensor features a resolution of 1544 digits from right to left and 1038 digits up and down. Through interpolation, these values rise by a factor of 100. A unique feature is the exact reproducibility (deflection to coordinates) and its precise ability to return to its neutral position. Moreover, optical signal processing provides a high level of protection against electromagnetic and radio frequency interference. The sensor is adaptive and adjustable to fit a user’s range of motion (stroke and force). This recommendation aims to optimize sensor systems such as joysticks in medical devices in terms of safety, ease of use, and adaptability. Full article
(This article belongs to the Section Physical Sensors)
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Open AccessArticle Loose and Tight GNSS/INS Integrations: Comparison of Performance Assessed in Real Urban Scenarios
Sensors 2017, 17(2), 255; doi:10.3390/s17020255
Received: 30 November 2016 / Revised: 13 January 2017 / Accepted: 19 January 2017 / Published: 29 January 2017
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Abstract
Global Navigation Satellite Systems (GNSSs) remain the principal mean of positioning in many applications and systems, but in several types of environment, the performance of standalone receivers is degraded. Although many works show the benefits of the integration between GNSS and Inertial Navigation
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Global Navigation Satellite Systems (GNSSs) remain the principal mean of positioning in many applications and systems, but in several types of environment, the performance of standalone receivers is degraded. Although many works show the benefits of the integration between GNSS and Inertial Navigation Systems (INSs), tightly-coupled architectures are mainly implemented in professional devices and are based on high-grade Inertial Measurement Units (IMUs). This paper investigates the performance improvements enabled by the tight integration, using low-cost sensors and a mass-market GNSS receiver. Performance is assessed through a series of tests carried out in real urban scenarios and is compared against commercial modules, operating in standalone mode or featuring loosely-coupled integrations. The paper describes the developed tight-integration algorithms with a terse mathematical model and assesses their efficacy from a practical perspective. Full article
(This article belongs to the Special Issue Inertial Sensors and Systems 2016)
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Open AccessArticle Topologically Optimized Nano-Positioning Stage Integrating with a Capacitive Comb Sensor
Sensors 2017, 17(2), 257; doi:10.3390/s17020257
Received: 25 November 2016 / Revised: 24 January 2017 / Accepted: 24 January 2017 / Published: 28 January 2017
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Abstract
Nano-positioning technology has been widely used in many fields, such as microelectronics, optical engineering, and micro manufacturing. This paper presents a one-dimensional (1D) nano-positioning system, adopting a piezoelectric ceramic (PZT) actuator and a multi-objective topological optimal structure. The combination of a nano-positioning stage
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Nano-positioning technology has been widely used in many fields, such as microelectronics, optical engineering, and micro manufacturing. This paper presents a one-dimensional (1D) nano-positioning system, adopting a piezoelectric ceramic (PZT) actuator and a multi-objective topological optimal structure. The combination of a nano-positioning stage and a feedback capacitive comb sensor has been achieved. In order to obtain better performance, a wedge-shaped structure is used to apply the precise pre-tension for the piezoelectric ceramics. Through finite element analysis and experimental verification, better static performance and smaller kinetic coupling are achieved. The output displacement of the system achieves a long-stroke of up to 14.7 μm and high-resolution of less than 3 nm. It provides a flexible and efficient way in the design and optimization of the nano-positioning system. Full article
(This article belongs to the collection Modeling, Testing and Reliability Issues in MEMS Engineering)
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Open AccessArticle THz Pyro-Optical Detector Based on LiNbO3 Whispering Gallery Mode Microdisc Resonator
Sensors 2017, 17(2), 258; doi:10.3390/s17020258
Received: 7 December 2016 / Revised: 16 January 2017 / Accepted: 24 January 2017 / Published: 28 January 2017
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Abstract
This study analyzes the capabilities of a LiNbO3 whispering gallery mode microdisc resonator as a potential bolometer detector in the THz range. The resonator is theoretically characterized in the stationary regime by its thermo-optic and thermal coefficients. Considering a Q-factor of 10
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This study analyzes the capabilities of a LiNbO3 whispering gallery mode microdisc resonator as a potential bolometer detector in the THz range. The resonator is theoretically characterized in the stationary regime by its thermo-optic and thermal coefficients. Considering a Q-factor of 107, a minimum detectable power of 20 μW was evaluated, three orders of magnitude above its noise equivalent power. This value opens up the feasibility of exploiting LiNbO3 disc resonators as sensitive room-temperature detectors in the THz range. Full article
(This article belongs to the Special Issue Infrared Detectors)
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Open AccessArticle Evaluation of the Vegetation Coverage Resilience in Areas Damaged by the Wenchuan Earthquake Based on MODIS-EVI Data
Sensors 2017, 17(2), 259; doi:10.3390/s17020259
Received: 3 December 2016 / Revised: 20 January 2017 / Accepted: 24 January 2017 / Published: 28 January 2017
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Abstract
The concept of resilience was integrated into post-earthquake ecological restoration assessments in 10 counties heavily impacted by the 2008 Wenchuan earthquake. Ecological resilience was defined as the time interval required for the vegetation coverage to recover to pre-earthquake levels in damaged areas. MODIS-EVI
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The concept of resilience was integrated into post-earthquake ecological restoration assessments in 10 counties heavily impacted by the 2008 Wenchuan earthquake. Ecological resilience was defined as the time interval required for the vegetation coverage to recover to pre-earthquake levels in damaged areas. MODIS-EVI data from May to August in 2000 to 2016 were used to calculate the ecological resilience by fitting the curve of recovery rate (RR) versus time. The following conclusions were reached: (1) An area of 424.1 km2 sustained vegetation damage. (2) The vegetation recovery was found to be linear based on the statistical analysis of the most common components of the damaged areas; consequently, linear fitting was used to estimate the resilience. (3) In terms of vegetation coverage, 44.2% of the damaged areas have already recovered. The vast majority of damaged areas are predicted to achieve vegetation recovery by 2022, but 5.3% of the damaged areas will not recover within this time period and have no resilience. (4) The management of damaged areas near roads, rivers and mining operations, especially at elevations of 2000–2500 m, slopes greater than 30°, and precipitation levels greater than 1200 mm, should be prioritized in the future. (5) The innovations of this study include the method used to extract earthquake-related vegetation damage and the prediction of vegetation succession based on resilience. Full article
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Open AccessArticle A Semantic Labeling of the Environment Based on What People Do
Sensors 2017, 17(2), 260; doi:10.3390/s17020260
Received: 27 October 2016 / Revised: 19 January 2017 / Accepted: 20 January 2017 / Published: 29 January 2017
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Abstract
In this work, a system is developed for semantic labeling of locations based on what people do. This system is useful for semantic navigation of mobile robots. The system differentiates environments according to what people do in them. Background sound, number of people
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In this work, a system is developed for semantic labeling of locations based on what people do. This system is useful for semantic navigation of mobile robots. The system differentiates environments according to what people do in them. Background sound, number of people in a room and amount of movement of those people are items to be considered when trying to tell if people are doing different actions. These data are sampled, and it is assumed that people behave differently and perform different actions. A support vector machine is trained with the obtained samples, and therefore, it allows one to identify the room. Finally, the results are discussed and support the hypothesis that the proposed system can help to semantically label a room. Full article
(This article belongs to the Special Issue System-Integrated Intelligence and Intelligent Systems)
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Open AccessArticle Low-Coherence Interferometric Fiber-Optic Sensors with Potential Applications as Biosensors
Sensors 2017, 17(2), 261; doi:10.3390/s17020261
Received: 22 December 2016 / Revised: 23 January 2017 / Accepted: 24 January 2017 / Published: 28 January 2017
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Abstract
Fiber-optic Fabry-Pérot interferometers (FPI) can be applied as optical sensors, and excellent measurement sensitivity can be obtained by fine-tuning the interferometer design. In this work, we evaluate the ability of selected dielectric thin films to optimize the reflectivity of the Fabry-Pérot cavity. The
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Fiber-optic Fabry-Pérot interferometers (FPI) can be applied as optical sensors, and excellent measurement sensitivity can be obtained by fine-tuning the interferometer design. In this work, we evaluate the ability of selected dielectric thin films to optimize the reflectivity of the Fabry-Pérot cavity. The spectral reflectance and transmittance of dielectric films made of titanium dioxide (TiO2) and aluminum oxide (Al2O3) with thicknesses from 30 to 220 nm have been evaluated numerically and compared. TiO2 films were found to be the most promising candidates for the tuning of FPI reflectivity. In order to verify and illustrate the results of modelling, TiO2 films with the thickness of 80 nm have been deposited on the tip of a single-mode optical fiber by atomic layer deposition (ALD). The thickness, the structure, and the chemical properties of the films have been determined. The ability of the selected TiO2 films to modify the reflectivity of the Fabry-Pérot cavity, to provide protection of the fibers from aggressive environments, and to create multi-cavity interferometric sensors in FPI has then been studied. The presented sensor exhibits an ability to measure refractive index in the range close to that of silica glass fiber, where sensors without reflective films do not work, as was demonstrated by the measurement of the refractive index of benzene. This opens up the prospects of applying the investigated sensor in biosensing, which we confirmed by measuring the refractive index of hemoglobin and glucose. Full article
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Open AccessArticle An Information Retrieval Approach for Robust Prediction of Road Surface States
Sensors 2017, 17(2), 262; doi:10.3390/s17020262
Received: 29 November 2016 / Revised: 19 January 2017 / Accepted: 23 January 2017 / Published: 28 January 2017
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Abstract
Recently, due to the increasing importance of reducing severe vehicle accidents on roads (especially on highways), the automatic identification of road surface conditions, and the provisioning of such information to drivers in advance, have recently been gaining significant momentum as a proactive solution
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Recently, due to the increasing importance of reducing severe vehicle accidents on roads (especially on highways), the automatic identification of road surface conditions, and the provisioning of such information to drivers in advance, have recently been gaining significant momentum as a proactive solution to decrease the number of vehicle accidents. In this paper, we firstly propose an information retrieval approach that aims to identify road surface states by combining conventional machine-learning techniques and moving average methods. Specifically, when signal information is received from a radar system, our approach attempts to estimate the current state of the road surface based on the similar instances observed previously based on utilizing a given similarity function. Next, the estimated state is then calibrated by using the recently estimated states to yield both effective and robust prediction results. To validate the performances of the proposed approach, we established a real-world experimental setting on a section of actual highway in South Korea and conducted a comparison with the conventional approaches in terms of accuracy. The experimental results show that the proposed approach successfully outperforms the previously developed methods. Full article
(This article belongs to the Special Issue Sensors for Transportation)
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Open AccessArticle Replacement Condition Detection of Railway Point Machines Using an Electric Current Sensor
Sensors 2017, 17(2), 263; doi:10.3390/s17020263
Received: 16 November 2016 / Revised: 18 January 2017 / Accepted: 23 January 2017 / Published: 29 January 2017
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Abstract
Detecting replacement conditions of railway point machines is important to simultaneously satisfy the budget-limit and train-safety requirements. In this study, we consider classification of the subtle differences in the aging effect—using electric current shape analysis—for the purpose of replacement condition detection of railway
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Detecting replacement conditions of railway point machines is important to simultaneously satisfy the budget-limit and train-safety requirements. In this study, we consider classification of the subtle differences in the aging effect—using electric current shape analysis—for the purpose of replacement condition detection of railway point machines. After analyzing the shapes of after-replacement data and then labeling the shapes of each before-replacement data, we can derive the criteria that can handle the subtle differences between “does-not-need-to-be-replaced” and “needs-to-be-replaced” shapes. On the basis of the experimental results with in-field replacement data, we confirmed that the proposed method could detect the replacement conditions with acceptable accuracy, as well as provide visual interpretability of the criteria used for the time-series classification. Full article
(This article belongs to the Special Issue Sensors for Transportation)
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Open AccessArticle A Kalman Filter for SINS Self-Alignment Based on Vector Observation
Sensors 2017, 17(2), 264; doi:10.3390/s17020264
Received: 27 November 2016 / Revised: 24 January 2017 / Accepted: 25 January 2017 / Published: 29 January 2017
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Abstract
In this paper, a self-alignment method for strapdown inertial navigation systems based on the q-method is studied. In addition, an improved method based on integrating gravitational apparent motion to form apparent velocity is designed, which can reduce the random noises of the
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In this paper, a self-alignment method for strapdown inertial navigation systems based on the q-method is studied. In addition, an improved method based on integrating gravitational apparent motion to form apparent velocity is designed, which can reduce the random noises of the observation vectors. For further analysis, a novel self-alignment method using a Kalman filter based on adaptive filter technology is proposed, which transforms the self-alignment procedure into an attitude estimation using the observation vectors. In the proposed method, a linear psuedo-measurement equation is adopted by employing the transfer method between the quaternion and the observation vectors. Analysis and simulation indicate that the accuracy of the self-alignment is improved. Meanwhile, to improve the convergence rate of the proposed method, a new method based on parameter recognition and a reconstruction algorithm for apparent gravitation is devised, which can reduce the influence of the random noises of the observation vectors. Simulations and turntable tests are carried out, and the results indicate that the proposed method can acquire sound alignment results with lower standard variances, and can obtain higher alignment accuracy and a faster convergence rate. Full article
(This article belongs to the Section Physical Sensors)
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Open AccessArticle Liquid Temperature Measurements Using Two Different Tunable Hollow Prisms
Sensors 2017, 17(2), 266; doi:10.3390/s17020266
Received: 25 August 2016 / Revised: 27 October 2016 / Accepted: 27 October 2016 / Published: 29 January 2017
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Abstract
This paper describes the design, fabrication, and testing of two hollow prisms. One is a prism with a grating glued to its hypotenuse. This ensemble, prism + grating, is called a grism. It can be applied as an on-axis tunable spectrometer. The other
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This paper describes the design, fabrication, and testing of two hollow prisms. One is a prism with a grating glued to its hypotenuse. This ensemble, prism + grating, is called a grism. It can be applied as an on-axis tunable spectrometer. The other hollow prism is a constant deviation one called a Pellin-Broca. It can be used as a tunable dispersive element in a spectrometer with no moving parts. The application of prisms as temperature sensors is shown. Full article
(This article belongs to the Special Issue Innovative Sensing Control Scheme for Advanced Materials)
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Open AccessArticle Enhanced Living by Assessing Voice Pathology Using a Co-Occurrence Matrix
Sensors 2017, 17(2), 267; doi:10.3390/s17020267
Received: 22 November 2016 / Revised: 14 January 2017 / Accepted: 25 January 2017 / Published: 29 January 2017
Cited by 3 | PDF Full-text (3597 KB) | HTML Full-text | XML Full-text
Abstract
A large number of the population around the world suffers from various disabilities. Disabilities affect not only children but also adults of different professions. Smart technology can assist the disabled population and lead to a comfortable life in an enhanced living environment (ELE).
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A large number of the population around the world suffers from various disabilities. Disabilities affect not only children but also adults of different professions. Smart technology can assist the disabled population and lead to a comfortable life in an enhanced living environment (ELE). In this paper, we propose an effective voice pathology assessment system that works in a smart home framework. The proposed system takes input from various sensors, and processes the acquired voice signals and electroglottography (EGG) signals. Co-occurrence matrices in different directions and neighborhoods from the spectrograms of these signals were obtained. Several features such as energy, entropy, contrast, and homogeneity from these matrices were calculated and fed into a Gaussian mixture model-based classifier. Experiments were performed with a publicly available database, namely, the Saarbrucken voice database. The results demonstrate the feasibility of the proposed system in light of its high accuracy and speed. The proposed system can be extended to assess other disabilities in an ELE. Full article
(This article belongs to the Special Issue Multisensory Big Data Analytics for Enhanced Living Environments)
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Open AccessArticle A Ring Artifact Correction Method: Validation by Micro-CT Imaging with Flat-Panel Detectors and a 2D Photon-Counting Detector
Sensors 2017, 17(2), 269; doi:10.3390/s17020269
Received: 3 October 2016 / Revised: 15 December 2016 / Accepted: 26 January 2017 / Published: 30 January 2017
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Abstract
We introduce an efficient ring artifact correction method for a cone-beam computed tomography (CT). In the first step, we correct the defective pixels whose values are close to zero or saturated in the projection domain. In the second step, we compute the mean
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We introduce an efficient ring artifact correction method for a cone-beam computed tomography (CT). In the first step, we correct the defective pixels whose values are close to zero or saturated in the projection domain. In the second step, we compute the mean value at each detector element along the view angle in the sinogram to obtain the one-dimensional (1D) mean vector, and we then compute the 1D correction vector by taking inverse of the mean vector. We multiply the correction vector with the sinogram row by row over all view angles. In the third step, we apply a Gaussian filter on the difference image between the original CT image and the corrected CT image obtained in the previous step. The filtered difference image is added to the corrected CT image to compensate the possible contrast anomaly that may appear due to the contrast change in the sinogram after removing stripe artifacts. We applied the proposed method to the projection data acquired by two flat-panel detectors (FPDs) and a silicon-based photon-counting X-ray detector (PCXD). Micro-CT imaging experiments of phantoms and a small animal have shown that the proposed method can greatly reduce ring artifacts regardless of detector types. Despite the great reduction of ring artifacts, the proposed method does not compromise the original spatial resolution and contrast. Full article
(This article belongs to the Section Physical Sensors)
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Open AccessArticle Real-Time Straight-Line Detection for XGA-Size Videos by Hough Transform with Parallelized Voting Procedures
Sensors 2017, 17(2), 270; doi:10.3390/s17020270
Received: 31 October 2016 / Accepted: 20 January 2017 / Published: 30 January 2017
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Abstract
The Hough Transform (HT) is a method for extracting straight lines from an edge image. The main limitations of the HT for usage in actual applications are computation time and storage requirements. This paper reports a hardware architecture for HT implementation on a
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The Hough Transform (HT) is a method for extracting straight lines from an edge image. The main limitations of the HT for usage in actual applications are computation time and storage requirements. This paper reports a hardware architecture for HT implementation on a Field Programmable Gate Array (FPGA) with parallelized voting procedure. The 2-dimensional accumulator array, namely the Hough space in parametric form (ρ, θ), for computing the strength of each line by a voting mechanism is mapped on a 1-dimensional array with regular increments of θ. Then, this Hough space is divided into a number of parallel parts. The computation of (ρ, θ) for the edge pixels and the voting procedure for straight-line determination are therefore executable in parallel. In addition, a synchronized initialization for the Hough space further increases the speed of straight-line detection, so that XGA video processing becomes possible. The designed prototype system has been synthesized on a DE4 platform with a Stratix-IV FPGA device. In the application of road-lane detection, the average processing speed of this HT implementation is 5.4ms per XGA-frame at 200 MHz working frequency. Full article
(This article belongs to the Special Issue Video Analysis and Tracking Using State-of-the-Art Sensors)
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Open AccessArticle Classification of Multiple Chinese Liquors by Means of a QCM-based E-Nose and MDS-SVM Classifier
Sensors 2017, 17(2), 272; doi:10.3390/s17020272
Received: 8 November 2016 / Accepted: 25 January 2017 / Published: 30 January 2017
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Abstract
Chinese liquors are internationally well-known fermentative alcoholic beverages. They have unique flavors attributable to the use of various bacteria and fungi, raw materials, and production processes. Developing a novel, rapid, and reliable method to identify multiple Chinese liquors is of positive significance. This
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Chinese liquors are internationally well-known fermentative alcoholic beverages. They have unique flavors attributable to the use of various bacteria and fungi, raw materials, and production processes. Developing a novel, rapid, and reliable method to identify multiple Chinese liquors is of positive significance. This paper presents a pattern recognition system for classifying ten brands of Chinese liquors based on multidimensional scaling (MDS) and support vector machine (SVM) algorithms in a quartz crystal microbalance (QCM)-based electronic nose (e-nose) we designed. We evaluated the comprehensive performance of the MDS-SVM classifier that predicted all ten brands of Chinese liquors individually. The prediction accuracy (98.3%) showed superior performance of the MDS-SVM classifier over the back-propagation artificial neural network (BP-ANN) classifier (93.3%) and moving average-linear discriminant analysis (MA-LDA) classifier (87.6%). The MDS-SVM classifier has reasonable reliability, good fitting and prediction (generalization) performance in classification of the Chinese liquors. Taking both application of the e-nose and validation of the MDS-SVM classifier into account, we have thus created a useful method for the classification of multiple Chinese liquors. Full article
(This article belongs to the Section Physical Sensors)
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Open AccessArticle Learning to Monitor Machine Health with Convolutional Bi-Directional LSTM Networks
Sensors 2017, 17(2), 273; doi:10.3390/s17020273
Received: 24 November 2016 / Revised: 12 January 2017 / Accepted: 24 January 2017 / Published: 30 January 2017
Cited by 2 | PDF Full-text (856 KB) | HTML Full-text | XML Full-text
Abstract
In modern manufacturing systems and industries, more and more research efforts have been made in developing effective machine health monitoring systems. Among various machine health monitoring approaches, data-driven methods are gaining in popularity due to the development of advanced sensing and data analytic
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In modern manufacturing systems and industries, more and more research efforts have been made in developing effective machine health monitoring systems. Among various machine health monitoring approaches, data-driven methods are gaining in popularity due to the development of advanced sensing and data analytic techniques. However, considering the noise, varying length and irregular sampling behind sensory data, this kind of sequential data cannot be fed into classification and regression models directly. Therefore, previous work focuses on feature extraction/fusion methods requiring expensive human labor and high quality expert knowledge. With the development of deep learning methods in the last few years, which redefine representation learning from raw data, a deep neural network structure named Convolutional Bi-directional Long Short-Term Memory networks (CBLSTM) has been designed here to address raw sensory data. CBLSTM firstly uses CNN to extract local features that are robust and informative from the sequential input. Then, bi-directional LSTM is introduced to encode temporal information. Long Short-Term Memory networks(LSTMs) are able to capture long-term dependencies and model sequential data, and the bi-directional structure enables the capture of past and future contexts. Stacked, fully-connected layers and the linear regression layer are built on top of bi-directional LSTMs to predict the target value. Here, a real-life tool wear test is introduced, and our proposed CBLSTM is able to predict the actual tool wear based on raw sensory data. The experimental results have shown that our model is able to outperform several state-of-the-art baseline methods. Full article
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Open AccessArticle IRNSS/NavIC L5 Attitude Determination
Sensors 2017, 17(2), 274; doi:10.3390/s17020274
Received: 10 December 2016 / Revised: 17 January 2017 / Accepted: 25 January 2017 / Published: 30 January 2017
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Abstract
The Indian Regional Navigation Satellite System (IRNSS) has recently (May 2016) become fully-operational and has been provided with the operational name of NavIC (Navigation with Indian Constellation). It has been developed by the Indian Space Research Organization (ISRO) with the objective of offering
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The Indian Regional Navigation Satellite System (IRNSS) has recently (May 2016) become fully-operational and has been provided with the operational name of NavIC (Navigation with Indian Constellation). It has been developed by the Indian Space Research Organization (ISRO) with the objective of offering positioning, navigation and timing (PNT) to the users in its service area. This contribution provides for the first time an assessment of the IRNSS L5-signal capability to achieve instantaneous attitude determination on the basis of data collected in Perth, Australia. Our evaluations are conducted for both a linear array of two antennas and a planar array of three antennas. A pre-requisite for precise and fast IRNSS attitude determination is the successful resolution of the double-differenced (DD) integer carrier-phase ambiguities. In this contribution, we will compare the performances of different such methods, amongst which the unconstrained and the multivariate-constrained LAMBDA method for both linear and planar arrays. It is demonstrated that the instantaneous ambiguity success rates increase from 15% to 90% for the linear array and from 5% to close to 100% for the planar array, thus showing that standalone IRNSS can realize 24-h almost instantaneous precise attitude determination with heading and elevation standard deviations of 0.05 and 0.10 degrees, respectively. Full article
(This article belongs to the Section Remote Sensors)
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Open AccessArticle Active AU Based Patch Weighting for Facial Expression Recognition
Sensors 2017, 17(2), 275; doi:10.3390/s17020275
Received: 30 December 2016 / Accepted: 24 January 2017 / Published: 30 January 2017
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Abstract
Facial expression has many applications in human-computer interaction. Although feature extraction and selection have been well studied, the specificity of each expression variation is not fully explored in state-of-the-art works. In this work, the problem of multiclass expression recognition is converted into triplet-wise
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Facial expression has many applications in human-computer interaction. Although feature extraction and selection have been well studied, the specificity of each expression variation is not fully explored in state-of-the-art works. In this work, the problem of multiclass expression recognition is converted into triplet-wise expression recognition. For each expression triplet, a new feature optimization model based on action unit (AU) weighting and patch weight optimization is proposed to represent the specificity of the expression triplet. The sparse representation-based approach is then proposed to detect the active AUs of the testing sample for better generalization. The algorithm achieved competitive accuracies of 89.67% and 94.09% for the Jaffe and Cohn–Kanade (CK+) databases, respectively. Better cross-database performance has also been observed. Full article
(This article belongs to the Section Sensor Networks)
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Open AccessArticle A Paper-Based Electrochromic Array for Visualized Electrochemical Sensing
Sensors 2017, 17(2), 276; doi:10.3390/s17020276
Received: 30 November 2016 / Accepted: 5 January 2017 / Published: 31 January 2017
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Abstract
We report a battery-powered, paper-based electrochromic array for visualized electrochemical sensing. The paper-based sensing system consists of six parallel electrochemical cells, which are powered by an aluminum-air battery. Each single electrochemical cell uses a Prussian Blue spot electrodeposited on an indium-doped tin oxide
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We report a battery-powered, paper-based electrochromic array for visualized electrochemical sensing. The paper-based sensing system consists of six parallel electrochemical cells, which are powered by an aluminum-air battery. Each single electrochemical cell uses a Prussian Blue spot electrodeposited on an indium-doped tin oxide thin film as the electrochromic indicator. Each electrochemical cell is preloaded with increasing amounts of analyte. The sample activates the battery for the sensing. Both the preloaded analyte and the analyte in the sample initiate the color change of Prussian Blue to Prussian White. With a reaction time of 60 s, the number of electrochemical cells with complete color changes is correlated to the concentration of analyte in the sample. As a proof-of-concept analyte, lactic acid was detected semi-quantitatively using the naked eye. Full article
(This article belongs to the Special Issue Point-of-Care Biosensors)
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Open AccessArticle Non-Destructive Sensor-Based Prediction of Maturity and Optimum Harvest Date of Sweet Cherry Fruit
Sensors 2017, 17(2), 277; doi:10.3390/s17020277
Received: 18 November 2016 / Revised: 20 January 2017 / Accepted: 23 January 2017 / Published: 31 January 2017
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Abstract
(1) Background: The aim of the study was to use innovative sensor technology for non-destructive determination and prediction of optimum harvest date (OHD), using sweet cherry as a model fruit, based on different ripening parameters. (2) Methods: Two cherry varieties in two growing
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(1) Background: The aim of the study was to use innovative sensor technology for non-destructive determination and prediction of optimum harvest date (OHD), using sweet cherry as a model fruit, based on different ripening parameters. (2) Methods: Two cherry varieties in two growing systems viz. field and polytunnel in two years were employed. The fruit quality parameters such as fruit weight and size proved unsuitable to detect OHD alone due to their dependence on crop load, climatic conditions, cultural practices, and season. Coloration during cherry ripening was characterized by a complete decline of green chlorophyll and saturation of the red anthocyanins, and was measured with a portable sensor viz. spectrometer 3–4 weeks before expected harvest until 2 weeks after harvest. (3) Results: Expressed as green NDVI (normalized differential vegetation index) and red NAI (normalized anthocyanin index) values, NAI increased from −0.5 (unripe) to +0.7 to +0.8 in mature fruit and remained at this saturation level with overripe fruits, irrespective of variety, treatment, and year. A model was developed to predict the OHD, which coincided with when NDVI reached and exceeded zero and the first derivative of NAI asymptotically approached zero. (4) Conclusion: The use of this sensor technology appears suitable for several cherry varieties and growing systems to predict the optimum harvest date. Full article
(This article belongs to the Section Physical Sensors)
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Open AccessArticle Performance Characterization of an xy-Stage Applied to Micrometric Laser Direct Writing Lithography
Sensors 2017, 17(2), 278; doi:10.3390/s17020278
Received: 29 November 2016 / Accepted: 3 January 2017 / Published: 31 January 2017
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Abstract
This article concerns the characterization of the stability and performance of a motorized stage used in laser direct writing lithography. The system was built from commercial components and commanded by G-code. Measurements use a pseudo-periodic-pattern (PPP) observed by a camera and image processing
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This article concerns the characterization of the stability and performance of a motorized stage used in laser direct writing lithography. The system was built from commercial components and commanded by G-code. Measurements use a pseudo-periodic-pattern (PPP) observed by a camera and image processing is based on Fourier transform and phase measurement methods. The results report that the built system has a stability against vibrations determined by peak-valley deviations of 65 nm and 26 nm in the x and y directions, respectively, with a standard deviation of 10 nm in both directions. When the xy-stage is in movement, it works with a resolution of 0.36 μm, which is an acceptable value for most of research and development (R and D) microtechnology developments in which the typical feature size used is in the micrometer range. Full article
(This article belongs to the Section Physical Sensors)
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Open AccessArticle Analysis of Temperature and Humidity Field in a New Bulk Tobacco Curing Barn Based on CFD
Sensors 2017, 17(2), 279; doi:10.3390/s17020279
Received: 12 November 2016 / Accepted: 24 January 2017 / Published: 31 January 2017
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Abstract
A new structure bulk tobacco curing barn was presented. To study the temperature and humidity field in the new structure tobacco curing barn, a 3D transient computational fluid dynamics (CFD) model was developed using porous medium, species transport, κ-ε turbulence and discrete phase
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A new structure bulk tobacco curing barn was presented. To study the temperature and humidity field in the new structure tobacco curing barn, a 3D transient computational fluid dynamics (CFD) model was developed using porous medium, species transport, κ-ε turbulence and discrete phase models. The CFD results demonstrated that (1) the temperature and relative humidity predictions were validated by the experimental results, and comparison of simulation results with experimental data showed a fairly close agreement; (2) the temperature of the bottom and inlet area was higher than the top and outlet area, and water vapor concentrated on the top and outlet area in the barn; (3) tobacco loading density and thickness of tobacco leaves had an explicit effect on the temperature distributions in the barn. Full article
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Open AccessArticle A Versatile and Reproducible Multi-Frequency Electrical Impedance Tomography System
Sensors 2017, 17(2), 280; doi:10.3390/s17020280
Received: 5 December 2016 / Revised: 18 January 2017 / Accepted: 25 January 2017 / Published: 31 January 2017
Cited by 4 | PDF Full-text (1804 KB) | HTML Full-text | XML Full-text
Abstract
A highly versatile Electrical Impedance Tomography (EIT) system, nicknamed the ScouseTom, has been developed. The system allows control over current amplitude, frequency, number of electrodes, injection protocol and data processing. Current is injected using a Keithley 6221 current source, and voltages are recorded
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A highly versatile Electrical Impedance Tomography (EIT) system, nicknamed the ScouseTom, has been developed. The system allows control over current amplitude, frequency, number of electrodes, injection protocol and data processing. Current is injected using a Keithley 6221 current source, and voltages are recorded with a 24-bit EEG system with minimum bandwidth of 3.2 kHz. Custom PCBs interface with a PC to control the measurement process, electrode addressing and triggering of external stimuli. The performance of the system was characterised using resistor phantoms to represent human scalp recordings, with an SNR of 77.5 dB, stable across a four hour recording and 20 Hz to 20 kHz. In studies of both haeomorrhage using scalp electrodes, and evoked activity using epicortical electrode mats in rats, it was possible to reconstruct images matching established literature at known areas of onset. Data collected using scalp electrode in humans matched known tissue impedance spectra and was stable over frequency. The experimental procedure is software controlled and is readily adaptable to new paradigms. Where possible, commercial or open-source components were used, to minimise the complexity in reproduction. The hardware designs and software for the system have been released under an open source licence, encouraging contributions and allowing for rapid replication. Full article
(This article belongs to the Section Biosensors)
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Open AccessCommunication An Electrochemical Gas Biosensor Based on Enzymes Immobilized on Chromatography Paper for Ethanol Vapor Detection
Sensors 2017, 17(2), 281; doi:10.3390/s17020281
Received: 30 November 2016 / Accepted: 25 January 2017 / Published: 1 February 2017
Cited by 1 | PDF Full-text (823 KB) | HTML Full-text | XML Full-text | Supplementary Files
Abstract
This paper presents a novel method of fabricating an enzymatic biosensor for breath analysis using chromatography paper as enzyme supporting layer and a liquid phase layer on top of screen printed carbon electrodes. We evaluated the performance with ethanol vapor being one of
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This paper presents a novel method of fabricating an enzymatic biosensor for breath analysis using chromatography paper as enzyme supporting layer and a liquid phase layer on top of screen printed carbon electrodes. We evaluated the performance with ethanol vapor being one of the breathing ingredients. The experimental results show that our sensor is able to measure the concentration of ethanol vapor within the range of 50 to 500 ppm. These results suggest the ability of detecting breath ethanol, and it can possibly be applied as a generic vapor biosensor to a wide range of diseases. Full article
(This article belongs to the Special Issue Gas Sensors for Health Care and Medical Applications)
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Open AccessArticle Real-Time Performance of a Self-Powered Environmental IoT Sensor Network System
Sensors 2017, 17(2), 282; doi:10.3390/s17020282
Received: 25 October 2016 / Accepted: 28 January 2017 / Published: 1 February 2017
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Abstract
Wireless sensor networks (WSNs) play an increasingly important role in monitoring applications in many areas. With the emergence of the Internet-of-Things (IoT), many more lowpower sensors will need to be deployed in various environments to collect and monitor data about environmental factors in
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Wireless sensor networks (WSNs) play an increasingly important role in monitoring applications in many areas. With the emergence of the Internet-of-Things (IoT), many more lowpower sensors will need to be deployed in various environments to collect and monitor data about environmental factors in real time. Providing power supply to these sensor nodes becomes a critical challenge for realizations of IoT applications as sensor nodes are normally battery-powered and have a limited lifetime. This paper proposes a wireless sensor network that is powered by solar energy harvesting. The sensor network monitors the environmental data with low-power sensor electronics and forms a network using multiple XBee wireless modules. A detailed performance analysis of the network system under solar energy harvesting has been presented. The sensor network system and the proposed energy-harvesting techniques are configured to achieve a continuous energy source for the sensor network. The proposed energy-harvesting system has been successfully designed to enable an energy solution in order to keep sensor nodes active and reliable for a whole day. The paper also outlines some of our experiences in real-time implementation of a sensor network system with energy harvesting. Full article
(This article belongs to the Special Issue Autonomous Sensors)
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Open AccessArticle SOUNET: Self-Organized Underwater Wireless Sensor Network
Sensors 2017, 17(2), 0283; doi:10.3390/s17020283
Received: 21 November 2016 / Accepted: 24 January 2017 / Published: 2 February 2017
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Abstract
In this paper, we propose an underwater wireless sensor network (UWSN) named SOUNET where sensor nodes form and maintain a tree-topological network for data gathering in a self-organized manner. After network topology discovery via packet flooding, the sensor nodes consistently update their parent
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In this paper, we propose an underwater wireless sensor network (UWSN) named SOUNET where sensor nodes form and maintain a tree-topological network for data gathering in a self-organized manner. After network topology discovery via packet flooding, the sensor nodes consistently update their parent node to ensure the best connectivity by referring to the timevarying neighbor tables. Such a persistent and self-adaptive method leads to high network connectivity without any centralized control, even when sensor nodes are added or unexpectedly lost. Furthermore, malfunctions that frequently happen in self-organized networks such as node isolation and closed loop are resolved in a simple way. Simulation results show that SOUNET outperforms other conventional schemes in terms of network connectivity, packet delivery ratio (PDR), and energy consumption throughout the network. In addition, we performed an experiment at the Gyeongcheon Lake in Korea using commercial underwater modems to verify that SOUNET works well in a real environment. Full article
(This article belongs to the Section Sensor Networks)
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Open AccessArticle High-Sensitivity and Low-Hysteresis Porous MIMType Capacitive Humidity Sensor Using Functional Polymer Mixed with TiO2 Microparticles
Sensors 2017, 17(2), 0284; doi:10.3390/s17020284
Received: 28 November 2016 / Accepted: 30 January 2017 / Published: 2 February 2017
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Abstract
In this study, a high-sensitivity and low-hysteresis porous metal–insulator–metal-type capacitive humidity sensor is investigated using a functional polymer mixed with TiO2 microparticles. The humidity sensor consists of an optimally designed porous top electrode, a functional polymer humidity sensitive layer, a bottom electrode, and
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In this study, a high-sensitivity and low-hysteresis porous metal–insulator–metal-type capacitive humidity sensor is investigated using a functional polymer mixed with TiO2 microparticles. The humidity sensor consists of an optimally designed porous top electrode, a functional polymer humidity sensitive layer, a bottom electrode, and a glass substrate. The porous top electrode is designed to increase the contact area between the sensing layer and water vapor, leading to high sensitivity and quick response time. The functional polymer mixed with TiO2 microparticles shows excellent hysteresis under a wide humidity-sensing range with good longterm stability. The results show that as the relative humidity ranges from 10% RH to 90% RH, the proposed humidity sensor achieves a high sensitivity of 0.85 pF/% RH and a fast response time of less than 35 s. Furthermore, the sensor shows an ultra-low hysteresis of 0.95% RH at 60% RH, a good temperature dependence, and a stable capacitance value with a maximum of 0.17% RH drift during 120 h of continuous test. Full article
(This article belongs to the Special Issue Humidity Sensors)
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Open AccessArticle Camber Angle Inspection for Vehicle Wheel Alignments
Sensors 2017, 17(2), 285; doi:10.3390/s17020285
Received: 10 November 2016 / Revised: 5 January 2017 / Accepted: 24 January 2017 / Published: 3 February 2017
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Abstract
This paper introduces an alternative approach to the camber angle measurement for vehicle wheel alignment. Instead of current commercial approaches that apply computation vision techniques, this study aims at realizing a micro-control-unit (MCU)-based camber inspection system with a 3-axis accelerometer. We analyze the
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This paper introduces an alternative approach to the camber angle measurement for vehicle wheel alignment. Instead of current commercial approaches that apply computation vision techniques, this study aims at realizing a micro-control-unit (MCU)-based camber inspection system with a 3-axis accelerometer. We analyze the precision of the inspection system for the axis misalignments of the accelerometer. The results show that the axes of the accelerometer can be aligned to the axes of the camber inspection system imperfectly. The calibrations that can amend these axis misalignments between the camber inspection system and the accelerometer are also originally proposed since misalignments will usually happen in fabrications of the inspection systems. During camber angle measurements, the x-axis or z-axis of the camber inspection system and the wheel need not be perfectly aligned in the proposed approach. We accomplished two typical authentic camber angle measurements. The results show that the proposed approach is applicable with a precision of ± 0.015 and therefore facilitates the camber measurement process without downgrading the precision by employing an appropriate 3-axis accelerometer. In addition, the measured results of camber angles can be transmitted via the medium such as RS232, Bluetooth, and Wi-Fi. Full article
(This article belongs to the Special Issue Sensors for Transportation)
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Open AccessArticle Real Time Apnoea Monitoring of Children Using the Microsoft Kinect Sensor: A Pilot Study
Sensors 2017, 17(2), 286; doi:10.3390/s17020286
Received: 18 November 2016 / Revised: 27 January 2017 / Accepted: 30 January 2017 / Published: 3 February 2017
Cited by 7 | PDF Full-text (6335 KB) | HTML Full-text | XML Full-text
Abstract
The objective of this study was to design a non-invasive system for the observation of respiratory rates and detection of apnoea using analysis of real time image sequences captured in any given sleep position and under any light conditions (even in dark environments).
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The objective of this study was to design a non-invasive system for the observation of respiratory rates and detection of apnoea using analysis of real time image sequences captured in any given sleep position and under any light conditions (even in dark environments). A Microsoft Kinect sensor was used to visualize the variations in the thorax and abdomen from the respiratory rhythm. These variations were magnified, analyzed and detected at a distance of 2.5 m from the subject. A modified motion magnification system and frame subtraction technique were used to identify breathing movements by detecting rapid motion areas in the magnified frame sequences. The experimental results on a set of video data from five subjects (3 h for each subject) showed that our monitoring system can accurately measure respiratory rate and therefore detect apnoea in infants and young children. The proposed system is feasible, accurate, safe and low computational complexity, making it an efficient alternative for non-contact home sleep monitoring systems and advancing health care applications. Full article
(This article belongs to the Special Issue Non-Contact Sensing)
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Open AccessArticle Diagnosis by Volatile Organic Compounds in Exhaled Breath from Lung Cancer Patients Using Support Vector Machine Algorithm
Sensors 2017, 17(2), 287; doi:10.3390/s17020287
Received: 15 November 2016 / Revised: 20 January 2017 / Accepted: 29 January 2017 / Published: 4 February 2017
Cited by 1 | PDF Full-text (2528 KB) | HTML Full-text | XML Full-text | Supplementary Files
Abstract
Monitoring exhaled breath is a very attractive, noninvasive screening technique for early diagnosis of diseases, especially lung cancer. However, the technique provides insufficient accuracy because the exhaled air has many crucial volatile organic compounds (VOCs) at very low concentrations (ppb level). We analyzed
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Monitoring exhaled breath is a very attractive, noninvasive screening technique for early diagnosis of diseases, especially lung cancer. However, the technique provides insufficient accuracy because the exhaled air has many crucial volatile organic compounds (VOCs) at very low concentrations (ppb level). We analyzed the breath exhaled by lung cancer patients and healthy subjects (controls) using gas chromatography/mass spectrometry (GC/MS), and performed a subsequent statistical analysis to diagnose lung cancer based on the combination of multiple lung cancer-related VOCs. We detected 68 VOCs as marker species using GC/MS analysis. We reduced the number of VOCs and used support vector machine (SVM) algorithm to classify the samples. We observed that a combination of five VOCs (CHN, methanol, CH3CN, isoprene, 1-propanol) is sufficient for 89.0% screening accuracy, and hence, it can be used for the design and development of a desktop GC-sensor analysis system for lung cancer. Full article
(This article belongs to the Special Issue Gas Sensors for Health Care and Medical Applications)
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Open AccessArticle A Novel Physical Layer Assisted Authentication Scheme for Mobile Wireless Sensor Networks
Sensors 2017, 17(2), 289; doi:10.3390/s17020289
Received: 22 November 2016 / Revised: 25 January 2017 / Accepted: 26 January 2017 / Published: 4 February 2017
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Abstract
Physical-layer authentication can address physical layer vulnerabilities and security threats in wireless sensor networks, and has been considered as an effective complementary enhancement to existing upper-layer authentication mechanisms. In this paper, to advance the existing research and improve the authentication performance, we propose
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Physical-layer authentication can address physical layer vulnerabilities and security threats in wireless sensor networks, and has been considered as an effective complementary enhancement to existing upper-layer authentication mechanisms. In this paper, to advance the existing research and improve the authentication performance, we propose a novel physical layer assisted authentication scheme for mobile wireless sensor networks. In our proposed scheme, we explore the reciprocity and spatial uncorrelation of the wireless channel to verify the identities of involved transmitting users and decide whether all data frames are from the same sender. In our proposed scheme, a new method is developed for the legitimate users to compare their received signal strength (RSS) records, which avoids the information from being disclosed to the adversary. Our proposed scheme can detect the spoofing attack even in a high dynamic environment. We evaluate our scheme through experiments under indoor and outdoor environments. Experiment results show that our proposed scheme is more efficient and achieves a higher detection rate as well as keeping a lower false alarm rate. Full article
(This article belongs to the Special Issue Sensors for Home Automation and Security)
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Open AccessArticle A Detailed Algorithm for Vital Sign Monitoring of a Stationary/Non-Stationary Human through IR-UWB Radar
Sensors 2017, 17(2), 290; doi:10.3390/s17020290
Received: 6 November 2016 / Revised: 6 January 2017 / Accepted: 25 January 2017 / Published: 4 February 2017
Cited by 5 | PDF Full-text (6501 KB) | HTML Full-text | XML Full-text
Abstract
The vital sign monitoring through Impulse Radio Ultra-Wide Band (IR-UWB) radar provides continuous assessment of a patient’s respiration and heart rates in a non-invasive manner. In this paper, IR UWB radar is used for monitoring respiration and the human heart rate. The breathing
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The vital sign monitoring through Impulse Radio Ultra-Wide Band (IR-UWB) radar provides continuous assessment of a patient’s respiration and heart rates in a non-invasive manner. In this paper, IR UWB radar is used for monitoring respiration and the human heart rate. The breathing and heart rate frequencies are extracted from the signal reflected from the human body. A Kalman filter is applied to reduce the measurement noise from the vital signal. An algorithm is presented to separate the heart rate signal from the breathing harmonics. An auto-correlation based technique is applied for detecting random body movements (RBM) during the measurement process. Experiments were performed in different scenarios in order to show the validity of the algorithm. The vital signs were estimated for the signal reflected from the chest, as well as from the back side of the body in different experiments. The results from both scenarios are compared for respiration and heartbeat estimation accuracy. Full article
(This article belongs to the collection Sensors for Globalized Healthy Living and Wellbeing)
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Open AccessArticle A Spot Reminder System for the Visually Impaired Based on a Smartphone Camera
Sensors 2017, 17(2), 291; doi:10.3390/s17020291
Received: 27 October 2016 / Revised: 20 January 2017 / Accepted: 23 January 2017 / Published: 4 February 2017
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Abstract
The present paper proposes a smartphone-camera-based system to assist visually impaired users in recalling their memories related to important locations, called spots, that they visited. The memories are recorded as voice memos, which can be played back when the users return to the
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The present paper proposes a smartphone-camera-based system to assist visually impaired users in recalling their memories related to important locations, called spots, that they visited. The memories are recorded as voice memos, which can be played back when the users return to the spots. Spot-to-spot correspondence is determined by image matching based on the scale invariant feature transform. The main contribution of the proposed system is to allow visually impaired users to associate arbitrary voice memos with arbitrary spots. The users do not need any special devices or systems except smartphones and do not need to remember the spots where the voice memos were recorded. In addition, the proposed system can identify spots in environments that are inaccessible to the global positioning system. The proposed system has been evaluated by two experiments: image matching tests and a user study. The experimental results suggested the effectiveness of the system to help visually impaired individuals, including blind individuals, recall information about regularly-visited spots. Full article
(This article belongs to the Section Physical Sensors)
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Open AccessArticle A Multichannel Calorimetric Simultaneous Assay Platform Using a Microampere Constant-Current Looped Enthalpy Sensor Array
Sensors 2017, 17(2), 292; doi:10.3390/s17020292
Received: 30 October 2016 / Revised: 23 January 2017 / Accepted: 1 February 2017 / Published: 4 February 2017
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Abstract
Calorimetric biochemical measurements offer various advantages such as low waste, low cost, low sample consumption, short operating time, and labor-savings. Multichannel calorimeters can enhance the possibility of performing higher-throughput biochemical measurements. An enthalpy sensor (ES) array is a key device in multichannel calorimeters.
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Calorimetric biochemical measurements offer various advantages such as low waste, low cost, low sample consumption, short operating time, and labor-savings. Multichannel calorimeters can enhance the possibility of performing higher-throughput biochemical measurements. An enthalpy sensor (ES) array is a key device in multichannel calorimeters. Most ES arrays use Wheatstone bridge amplifiers to condition the sensor signals, but such an approach is only suitable for null detection and low resistance sensors. To overcome these limitations, we have developed a multichannel calorimetric simultaneous assay (MCSA) platform. An adjustable microampere constant-current (AMCC) source was designed for exciting the ES array using a microampere current loop measurement circuit topology. The MCSA platform comprises a measurement unit, which contains a multichannel calorimeter and an automatic simultaneous injector, and a signal processing unit, which contains multiple ES signal conditioners and a data processor. This study focused on the construction of the MCSA platform; in particular, construction of the measurement circuit and calorimeter array in a single block. The performance of the platform, including current stability, temperature sensitivity and heat sensitivity, was evaluated. The sensor response time and calorimeter constants were given. The capability of the platform to detect relative enzyme activity was also demonstrated. The experimental results show that the proposed MCSA is a flexible and powerful biochemical measurement device with higher throughput than existing alternatives. Full article
(This article belongs to the Section Physical Sensors)
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