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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

Jump to: Research, Review, Other

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 Comparative Study of Different Methods for Soot Sensing and Filter Monitoring in Diesel Exhausts
Sensors 2017, 17(2), 400; doi:10.3390/s17020400
Received: 20 November 2016 / Revised: 29 January 2017 / Accepted: 11 February 2017 / Published: 18 February 2017
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Abstract
Due to increasingly tighter emission limits for diesel and gasoline engines, especially concerning particulate matter emissions, particulate filters are becoming indispensable devices for exhaust gas after treatment. Thereby, for an efficient engine and filter control strategy and a cost-efficient filter design, reliable technologies
[...] Read more.
Due to increasingly tighter emission limits for diesel and gasoline engines, especially concerning particulate matter emissions, particulate filters are becoming indispensable devices for exhaust gas after treatment. Thereby, for an efficient engine and filter control strategy and a cost-efficient filter design, reliable technologies to determine the soot load of the filters and to measure particulate matter concentrations in the exhaust gas during vehicle operation are highly needed. In this study, different approaches for soot sensing are compared. Measurements were conducted on a dynamometer diesel engine test bench with a diesel particulate filter (DPF). The DPF was monitored by a relatively new microwave-based approach. Simultaneously, a resistive type soot sensor and a Pegasor soot sensing device as a reference system measured the soot concentration exhaust upstream of the DPF. By changing engine parameters, different engine out soot emission rates were set. It was found that the microwave-based signal may not only indicate directly the filter loading, but by a time derivative, the engine out soot emission rate can be deduced. Furthermore, by integrating the measured particulate mass in the exhaust, the soot load of the filter can be determined. In summary, all systems coincide well within certain boundaries and the filter itself can act as a soot sensor. Full article
(This article belongs to the collection Gas Sensors)
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Open AccessArticle RiPPAS: A Ring-Based Privacy-Preserving Aggregation Scheme in Wireless Sensor Networks
Sensors 2017, 17(2), 300; doi:10.3390/s17020300
Received: 28 October 2016 / Revised: 16 January 2017 / Accepted: 26 January 2017 / Published: 7 February 2017
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Abstract
Recently, data privacy in wireless sensor networks (WSNs) has been paid increased attention. The characteristics of WSNs determine that users’ queries are mainly aggregation queries. In this paper, the problem of processing aggregation queries in WSNs with data privacy preservation is investigated. A
[...] Read more.
Recently, data privacy in wireless sensor networks (WSNs) has been paid increased attention. The characteristics of WSNs determine that users’ queries are mainly aggregation queries. In this paper, the problem of processing aggregation queries in WSNs with data privacy preservation is investigated. A Ring-based Privacy-Preserving Aggregation Scheme (RiPPAS) is proposed. RiPPAS adopts ring structure to perform aggregation. It uses pseudonym mechanism for anonymous communication and uses homomorphic encryption technique to add noise to the data easily to be disclosed. RiPPAS can handle both s u m ( ) queries and m i n ( ) / m a x ( ) queries, while the existing privacy-preserving aggregation methods can only deal with s u m ( ) queries. For processing s u m ( ) queries, compared with the existing methods, RiPPAS has advantages in the aspects of privacy preservation and communication efficiency, which can be proved by theoretical analysis and simulation results. For processing m i n ( ) / m a x ( ) queries, RiPPAS provides effective privacy preservation and has low communication overhead. Full article
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Open AccessArticle Gimbal Influence on the Stability of Exterior Orientation Parameters of UAV Acquired Images
Sensors 2017, 17(2), 401; doi:10.3390/s17020401
Received: 21 December 2016 / Revised: 27 January 2017 / Accepted: 16 February 2017 / Published: 18 February 2017
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Abstract
In this paper, results from the analysis of the gimbal impact on the determination of the camera exterior orientation parameters of an Unmanned Aerial Vehicle (UAV) are presented and interpreted. Additionally, a new approach and methodology for testing the influence of gimbals on
[...] Read more.
In this paper, results from the analysis of the gimbal impact on the determination of the camera exterior orientation parameters of an Unmanned Aerial Vehicle (UAV) are presented and interpreted. Additionally, a new approach and methodology for testing the influence of gimbals on the exterior orientation parameters of UAV acquired images is presented. The main motive of this study is to examine the possibility of obtaining better geometry and favorable spatial bundles of rays of images in UAV photogrammetric surveying. The subject is a 3-axis brushless gimbal based on a controller board (Storm32). Only two gimbal axes are taken into consideration: roll and pitch axes. Testing was done in a flight simulation, and in indoor and outdoor flight mode, to analyze the Inertial Measurement Unit (IMU) and photogrammetric data. Within these tests the change of the exterior orientation parameters without the use of a gimbal is determined, as well as the potential accuracy of the stabilization with the use of a gimbal. The results show that using a gimbal has huge potential. Significantly, smaller discrepancies between data are noticed when a gimbal is used in flight simulation mode, even four times smaller than in other test modes. In this test the potential accuracy of a low budget gimbal for application in real conditions is determined. Full article
(This article belongs to the Special Issue UAV-Based Remote Sensing)
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Open AccessArticle Enabling Secure XMPP Communications in Federated IoT Clouds Through XEP 0027 and SAML/SASL SSO
Sensors 2017, 17(2), 301; doi:10.3390/s17020301
Received: 28 September 2016 / Revised: 15 January 2017 / Accepted: 24 January 2017 / Published: 7 February 2017
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Abstract
Nowadays, in the panorama of Internet of Things (IoT), finding a right compromise between interactivity and security is not trivial at all. Currently, most of pervasive communication technologies are designed to work locally. As a consequence, the development of large-scale Internet services and
[...] Read more.
Nowadays, in the panorama of Internet of Things (IoT), finding a right compromise between interactivity and security is not trivial at all. Currently, most of pervasive communication technologies are designed to work locally. As a consequence, the development of large-scale Internet services and applications is not so easy for IoT Cloud providers. The main issue is that both IoT architectures and services have started as simple but they are becoming more and more complex. Consequently, the web service technology is often inappropriate. Recently, many operators in both academia and industry fields are considering the possibility to adopt the eXtensible Messaging and Presence Protocol (XMPP) for the implementation of IoT Cloud communication systems. In fact, XMPP offers many advantages in term of real-time capabilities, efficient data distribution, service discovery and inter-domain communication compared to other technologies. Nevertheless, the protocol lacks of native security, data confidentiality and trustworthy federation features. In this paper, considering an XMPP-based IoT Cloud architectural model, we discuss how can be possible to enforce message signing/encryption and Single-Sign On (SSO) authentication respectively for secure inter-module and inter-domain communications in a federated environment. Experiments prove that security mechanisms introduce an acceptable overhead, considering the obvious advantages achieved in terms of data trustiness and privacy. Full article
(This article belongs to the Section Sensor Networks)
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Open AccessArticle A Signal Processing Approach with a Smooth Empirical Mode Decomposition to Reveal Hidden Trace of Corrosion in Highly Contaminated Guided Wave Signals for Concrete-Covered Pipes
Sensors 2017, 17(2), 302; doi:10.3390/s17020302
Received: 18 December 2016 / Revised: 23 January 2017 / Accepted: 1 February 2017 / Published: 7 February 2017
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Abstract
Ultrasonic guided waves have been extensively applied for non-destructive testing of plate-like structures particularly pipes in past two decades. In this regard, if a structure has a simple geometry, obtained guided waves’ signals are easy to explain. However, any small degree of complexity
[...] Read more.
Ultrasonic guided waves have been extensively applied for non-destructive testing of plate-like structures particularly pipes in past two decades. In this regard, if a structure has a simple geometry, obtained guided waves’ signals are easy to explain. However, any small degree of complexity in the geometry such as contacting with other materials may cause an extra amount of complication in the interpretation of guided wave signals. The problem deepens if defects have irregular shapes such as natural corrosion. Signal processing techniques that have been proposed for guided wave signals’ analysis are generally good for simple signals obtained in a highly controlled experimental environment. In fact, guided wave signals in a real situation such as the existence of natural corrosion in wall-covered pipes are much more complicated. Considering pipes in residential buildings that pass through concrete walls, in this paper we introduced Smooth Empirical Mode Decomposition (SEMD) to efficiently separate overlapped guided waves. As empirical mode decomposition (EMD) which is a good candidate for analyzing non-stationary signals, suffers from some shortcomings, wavelet transform was adopted in the sifting stage of EMD to improve its outcome in SEMD. However, selection of mother wavelet that suits best for our purpose plays an important role. Since in guided wave inspection, the incident waves are well known and are usually tone-burst signals, we tailored a complex tone-burst signal to be used as our mother wavelet. In the sifting stage of EMD, wavelet de-noising was applied to eliminate unwanted frequency components from each IMF. SEMD greatly enhances the performance of EMD in guided wave analysis for highly contaminated signals. In our experiment on concrete covered pipes with natural corrosion, this method not only separates the concrete wall indication clearly in time domain signal, a natural corrosion with complex geometry that was hidden and located inside the concrete section was successfully exposed. Full article
(This article belongs to the Special Issue Ultrasonic Sensors)
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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 Towards a Semantic Web of Things: A Hybrid Semantic Annotation, Extraction, and Reasoning Framework for Cyber-Physical System
Sensors 2017, 17(2), 403; doi:10.3390/s17020403
Received: 18 December 2016 / Revised: 13 February 2017 / Accepted: 14 February 2017 / Published: 20 February 2017
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Abstract
Web of Things (WoT) facilitates the discovery and interoperability of Internet of Things (IoT) devices in a cyber-physical system (CPS). Moreover, a uniform knowledge representation of physical resources is quite necessary for further composition, collaboration, and decision-making process in CPS. Though several efforts
[...] Read more.
Web of Things (WoT) facilitates the discovery and interoperability of Internet of Things (IoT) devices in a cyber-physical system (CPS). Moreover, a uniform knowledge representation of physical resources is quite necessary for further composition, collaboration, and decision-making process in CPS. Though several efforts have integrated semantics with WoT, such as knowledge engineering methods based on semantic sensor networks (SSN), it still could not represent the complex relationships between devices when dynamic composition and collaboration occur, and it totally depends on manual construction of a knowledge base with low scalability. In this paper, to addresses these limitations, we propose the semantic Web of Things (SWoT) framework for CPS (SWoT4CPS). SWoT4CPS provides a hybrid solution with both ontological engineering methods by extending SSN and machine learning methods based on an entity linking (EL) model. To testify to the feasibility and performance, we demonstrate the framework by implementing a temperature anomaly diagnosis and automatic control use case in a building automation system. Evaluation results on the EL method show that linking domain knowledge to DBpedia has a relative high accuracy and the time complexity is at a tolerant level. Advantages and disadvantages of SWoT4CPS with future work are also discussed. Full article
(This article belongs to the Special Issue System-Integrated Intelligence and Intelligent Systems)
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Open AccessArticle Highly Sensitive Sensors Based on Metal-Oxide Nanocolumns for Fire Detection
Sensors 2017, 17(2), 303; doi:10.3390/s17020303
Received: 21 November 2016 / Revised: 18 January 2017 / Accepted: 3 February 2017 / Published: 7 February 2017
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Abstract
A fire detector is the most important component in a fire alarm system. Herein, we present the feasibility of a highly sensitive and rapid response gas sensor based on metal oxides as a high performance fire detector. The glancing angle deposition (GLAD) technique
[...] Read more.
A fire detector is the most important component in a fire alarm system. Herein, we present the feasibility of a highly sensitive and rapid response gas sensor based on metal oxides as a high performance fire detector. The glancing angle deposition (GLAD) technique is used to make the highly porous structure such as nanocolumns (NCs) of various metal oxides for enhancing the gas-sensing performance. To measure the fire detection, the interface circuitry for our sensors (NiO, SnO2, WO3 and In2O3 NCs) is designed. When all the sensors with various metal-oxide NCs are exposed to fire environment, they entirely react with the target gases emitted from Poly(vinyl chlorides) (PVC) decomposed at high temperature. Before the emission of smoke from the PVC (a hot-plate temperature of 200 °C), the resistances of the metal-oxide NCs are abruptly changed and SnO2 NCs show the highest response of 2.1. However, a commercial smoke detector did not inform any warning. Interestingly, although the NiO NCs are a p-type semiconductor, they show the highest response of 577.1 after the emission of smoke from the PVC (a hot-plate temperature of 350 °C). The response time of SnO2 NCs is much faster than that of a commercial smoke detector at the hot-plate temperature of 350 °C. In addition, we investigated the selectivity of our sensors by analyzing the responses of all sensors. Our results show the high potential of a gas sensor based on metal-oxide NCs for early fire detection. Full article
(This article belongs to the collection Gas Sensors)
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Open AccessArticle Remote Sensing of Urban Microclimate Change in L’Aquila City (Italy) after Post-Earthquake Depopulation in an Open Source GIS Environment
Sensors 2017, 17(2), 404; doi:10.3390/s17020404
Received: 11 October 2016 / Revised: 10 February 2017 / Accepted: 13 February 2017 / Published: 19 February 2017
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Abstract
This work reports a first attempt to use Landsat satellite imagery to identify possible urban microclimate changes in a city center after a seismic event that affected L’Aquila City (Abruzzo Region, Italy), on 6 April 2009. After the main seismic event, the collapse
[...] Read more.
This work reports a first attempt to use Landsat satellite imagery to identify possible urban microclimate changes in a city center after a seismic event that affected L’Aquila City (Abruzzo Region, Italy), on 6 April 2009. After the main seismic event, the collapse of part of the buildings, and the damaging of most of them, with the consequence of an almost total depopulation of the historic city center, may have caused alterations to the microclimate. This work develops an inexpensive work flow—using Landsat Enhanced Thematic Mapper Plus (ETM+) scenes—to construct the evolution of urban land use after the catastrophic main seismic event that hit L’Aquila. We hypothesized, that, possibly, before the event, the temperature was higher in the city center due to the presence of inhabitants (and thus home heating); while the opposite case occurred in the surrounding areas, where new settlements of inhabitants grew over a period of a few months. We decided not to look to independent meteorological data in order to avoid being biased in their investigations; thus, only the smallest dataset of Landsat ETM+ scenes were considered as input data in order to describe the thermal evolution of the land surface after the earthquake. We managed to use the Landsat archive images to provide thermal change indications, useful for understanding the urban changes induced by catastrophic events, setting up an easy to implement, robust, reproducible, and fast procedure. Full article
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Open AccessArticle Preliminary Study for Designing a Novel Vein-Visualizing Device
Sensors 2017, 17(2), 304; doi:10.3390/s17020304
Received: 31 October 2016 / Revised: 18 January 2017 / Accepted: 3 February 2017 / Published: 7 February 2017
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Abstract
Venipuncture is an important health diagnosis process. Although venipuncture is one of the most commonly performed procedures in medical environments, locating the veins of infants, obese, anemic, or colored patients is still an arduous task even for skilled practitioners. To solve this problem,
[...] Read more.
Venipuncture is an important health diagnosis process. Although venipuncture is one of the most commonly performed procedures in medical environments, locating the veins of infants, obese, anemic, or colored patients is still an arduous task even for skilled practitioners. To solve this problem, several devices using infrared light have recently become commercially available. However, such devices for venipuncture share a common drawback, especially when visualizing deep veins or veins of a thick part of the body like the cubital fossa. This paper proposes a new vein-visualizing device applying a new penetration method using near-infrared (NIR) light. The light module is attached directly on to the declared area of the skin. Then, NIR beam is rayed from two sides of the light module to the vein with a specific angle. This gives a penetration effect. In addition, through an image processing procedure, the vein structure is enhanced to show it more accurately. Through a phantom study, the most effective penetration angle of the NIR module is decided. Additionally, the feasibility of the device is verified through experiments in vivo. The prototype allows us to visualize the vein patterns of thicker body parts, such as arms. Full article
(This article belongs to the Special Issue Sensing Technology for Healthcare System)
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Open AccessArticle A Biocompatible Colorimetric Triphenylamine- Dicyanovinyl Conjugated Fluorescent Probe for Selective and Sensitive Detection of Cyanide Ion in Aqueous Media and Living Cells
Sensors 2017, 17(2), 405; doi:10.3390/s17020405
Received: 12 December 2016 / Revised: 16 January 2017 / Accepted: 4 February 2017 / Published: 19 February 2017
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Abstract
A colorimetric and turn-on fluorescent probe 1 bearing triphenylamine-thiophene and dicyanovinyl groups has been synthesized and used to detect cyanide anion via a nucleophilic addition reaction. Probe 1 exhibited prominent selectivity and sensitivity towards CN in aqueous media, even in the presence
[...] Read more.
A colorimetric and turn-on fluorescent probe 1 bearing triphenylamine-thiophene and dicyanovinyl groups has been synthesized and used to detect cyanide anion via a nucleophilic addition reaction. Probe 1 exhibited prominent selectivity and sensitivity towards CN in aqueous media, even in the presence of other anions such as S2−, HS, SO32−, S2O32−, S2O82−, I, Br, Cl, F, NO2, N3, SO42−, SCN, HCO3, CO32− and AcO. Moreover, a low detection limit (LOD, 51 nM) was observed. In addition, good cell membrane permeability and low cytotoxicity to HeLa cells were also observed, suggesting its promising potential in bio-imaging. Full article
(This article belongs to the Special Issue Colorimetric and Fluorescent Sensor)
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Open AccessArticle A Study on the Influence of Speed on Road Roughness Sensing: The SmartRoadSense Case
Sensors 2017, 17(2), 305; doi:10.3390/s17020305
Received: 27 December 2016 / Revised: 31 January 2017 / Accepted: 2 February 2017 / Published: 7 February 2017
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Abstract
SmartRoadSense is a crowdsensing project aimed at monitoring the conditions of the road surface. Using the sensors of a smartphone, SmartRoadSense monitors the vertical accelerations inside a vehicle traveling the road and extracts a roughness index conveying information about the road conditions. The
[...] Read more.
SmartRoadSense is a crowdsensing project aimed at monitoring the conditions of the road surface. Using the sensors of a smartphone, SmartRoadSense monitors the vertical accelerations inside a vehicle traveling the road and extracts a roughness index conveying information about the road conditions. The roughness index and the smartphone GPS data are periodically sent to a central server where they are processed, associated with the specific road, and aggregated with data measured by other smartphones. This paper studies how the smartphone vertical accelerations and the roughness index are related to the vehicle speed. It is shown that the dependence can be locally approximated with a gamma (power) law. Extensive experimental results using data extracted from SmartRoadSense database confirm the gamma law relationship between the roughness index and the vehicle speed. The gamma law is then used for improving the SmartRoadSense data aggregation accounting for the effect of vehicle speed. Full article
(This article belongs to the Special Issue Sensors for Transportation)
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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
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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 An Optical Fibre Depth (Pressure) Sensor for Remote Operated Vehicles in Underwater Applications
Sensors 2017, 17(2), 406; doi:10.3390/s17020406
Received: 14 November 2016 / Revised: 15 February 2017 / Accepted: 15 February 2017 / Published: 19 February 2017
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Abstract
A miniature sensor for accurate measurement of pressure (depth) with temperature compensation in the ocean environment is described. The sensor is based on an optical fibre Extrinsic Fabry-Perot interferometer (EFPI) combined with a Fibre Bragg Grating (FBG). The EFPI provides pressure measurements while
[...] Read more.
A miniature sensor for accurate measurement of pressure (depth) with temperature compensation in the ocean environment is described. The sensor is based on an optical fibre Extrinsic Fabry-Perot interferometer (EFPI) combined with a Fibre Bragg Grating (FBG). The EFPI provides pressure measurements while the Fibre Bragg Grating (FBG) provides temperature measurements. The sensor is mechanically robust, corrosion-resistant and suitable for use in underwater applications. The combined pressure and temperature sensor system was mounted on-board a mini remotely operated underwater vehicle (ROV) in order to monitor the pressure changes at various depths. The reflected optical spectrum from the sensor was monitored online and a pressure or temperature change caused a corresponding observable shift in the received optical spectrum. The sensor exhibited excellent stability when measured over a 2 h period underwater and its performance is compared with a commercially available reference sensor also mounted on the ROV. The measurements illustrates that the EFPI/FBG sensor is more accurate for depth measurements (depth of ~0.020 m). Full article
(This article belongs to the Section Physical Sensors)
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Open AccessArticle Water Plume Temperature Measurements by an Unmanned Aerial System (UAS)
Sensors 2017, 17(2), 306; doi:10.3390/s17020306
Received: 20 December 2016 / Revised: 24 January 2017 / Accepted: 1 February 2017 / Published: 7 February 2017
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Abstract
We report on the development and testing of a proof of principle water temperature measurement system deployed on an unmanned aerial system (UAS), for field measurements of thermal discharges into water. The primary elements of the system include a quad-copter UAS to which
[...] Read more.
We report on the development and testing of a proof of principle water temperature measurement system deployed on an unmanned aerial system (UAS), for field measurements of thermal discharges into water. The primary elements of the system include a quad-copter UAS to which has been integrated, for the first time, both a thermal imaging infrared (IR) camera and an immersible probe that can be dipped below the water surface to obtain vertical water temperature profiles. The IR camera is used to take images of the overall water surface to geo-locate the plume, while the immersible probe provides quantitative temperature depth profiles at specific locations. The full system has been tested including the navigation of the UAS, its ability to safely carry the sensor payload, and the performance of both the IR camera and the temperature probe. Finally, the UAS sensor system was successfully deployed in a pilot field study at a coal burning power plant, and obtained images and temperature profiles of the thermal effluent. Full article
(This article belongs to the Special Issue UAV-Based Remote Sensing)
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Open AccessArticle Novel Hierarchical Fall Detection Algorithm Using a Multiphase Fall Model
Sensors 2017, 17(2), 307; doi:10.3390/s17020307
Received: 24 November 2016 / Revised: 26 January 2017 / Accepted: 3 February 2017 / Published: 8 February 2017
Cited by 1 | PDF Full-text (2021 KB) | HTML Full-text | XML Full-text
Abstract
Falls are the primary cause of accidents for the elderly in the living environment. Reducing hazards in the living environment and performing exercises for training balance and muscles are the common strategies for fall prevention. However, falls cannot be avoided completely; fall detection
[...] Read more.
Falls are the primary cause of accidents for the elderly in the living environment. Reducing hazards in the living environment and performing exercises for training balance and muscles are the common strategies for fall prevention. However, falls cannot be avoided completely; fall detection provides an alarm that can decrease injuries or death caused by the lack of rescue. The automatic fall detection system has opportunities to provide real-time emergency alarms for improving the safety and quality of home healthcare services. Two common technical challenges are also tackled in order to provide a reliable fall detection algorithm, including variability and ambiguity. We propose a novel hierarchical fall detection algorithm involving threshold-based and knowledge-based approaches to detect a fall event. The threshold-based approach efficiently supports the detection and identification of fall events from continuous sensor data. A multiphase fall model is utilized, including free fall, impact, and rest phases for the knowledge-based approach, which identifies fall events and has the potential to deal with the aforementioned technical challenges of a fall detection system. Seven kinds of falls and seven types of daily activities arranged in an experiment are used to explore the performance of the proposed fall detection algorithm. The overall performances of the sensitivity, specificity, precision, and accuracy using a knowledge-based algorithm are 99.79%, 98.74%, 99.05% and 99.33%, respectively. The results show that the proposed novel hierarchical fall detection algorithm can cope with the variability and ambiguity of the technical challenges and fulfill the reliability, adaptability, and flexibility requirements of an automatic fall detection system with respect to the individual differences. Full article
(This article belongs to the Special Issue Sensors for Home Automation and Security)
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Open AccessArticle Compliment Graphene Oxide Coating on Silk Fiber Surface via Electrostatic Force for Capacitive Humidity Sensor Applications
Sensors 2017, 17(2), 407; doi:10.3390/s17020407
Received: 21 December 2016 / Revised: 14 February 2017 / Accepted: 15 February 2017 / Published: 19 February 2017
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Abstract
Cylindrical silk fiber (SF) was coated with Graphene oxide (GO) for capacitive humidity sensor applications. Negatively charged GO in the solution was attracted to the positively charged SF surface via electrostatic force without any help from adhesive intermediates. The magnitude of the positively
[...] Read more.
Cylindrical silk fiber (SF) was coated with Graphene oxide (GO) for capacitive humidity sensor applications. Negatively charged GO in the solution was attracted to the positively charged SF surface via electrostatic force without any help from adhesive intermediates. The magnitude of the positively charged SF surface was controlled through the static electricity charges created on the SF surface. The GO coating ability on the SF improved as the SF’s positive charge increased. The GO-coated SFs at various conditions were characterized using an optical microscope, scanning electron microscopy (SEM), energy-dispersive X-ray spectroscopy (EDS), Raman spectroscopy, and LCR meter. Unlike the intact SF, the GO-coated SF showed clear response-recovery behavior and well-behaved repeatability when it was exposed to 20% relative humidity (RH) and 90% RH alternatively in a capacitive mode. This approach allows humidity sensors to take advantage of GO’s excellent sensing properties and SF’s flexibility, expediting the production of flexible, low power consumption devices at relatively low costs. Full article
(This article belongs to the Special Issue Humidity Sensors)
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Open AccessArticle A Miniature Magnetic-Force-Based Three-Axis AC Magnetic Sensor with Piezoelectric/Vibrational Energy-Harvesting Functions
Sensors 2017, 17(2), 308; doi:10.3390/s17020308
Received: 29 August 2016 / Revised: 18 January 2017 / Accepted: 4 February 2017 / Published: 8 February 2017
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Abstract
In this paper, we demonstrate a miniature magnetic-force-based, three-axis, AC magnetic sensor with piezoelectric/vibrational energy-harvesting functions. For magnetic sensing, the sensor employs a magnetic–mechanical–piezoelectric configuration (which uses magnetic force and torque, a compact, single, mechanical mechanism, and the piezoelectric effect) to convert x
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In this paper, we demonstrate a miniature magnetic-force-based, three-axis, AC magnetic sensor with piezoelectric/vibrational energy-harvesting functions. For magnetic sensing, the sensor employs a magnetic–mechanical–piezoelectric configuration (which uses magnetic force and torque, a compact, single, mechanical mechanism, and the piezoelectric effect) to convert x-axis and y-axis in-plane and z-axis magnetic fields into piezoelectric voltage outputs. Under the x-axis magnetic field (sine-wave, 100 Hz, 0.2–3.2 gauss) and the z-axis magnetic field (sine-wave, 142 Hz, 0.2–3.2 gauss), the voltage output with the sensitivity of the sensor are 1.13–26.15 mV with 8.79 mV/gauss and 1.31–8.92 mV with 2.63 mV/gauss, respectively. In addition, through this configuration, the sensor can harness ambient vibrational energy, i.e., possessing piezoelectric/vibrational energy-harvesting functions. Under x-axis vibration (sine-wave, 100 Hz, 3.5 g) and z-axis vibration (sine-wave, 142 Hz, 3.8 g), the root-mean-square voltage output with power output of the sensor is 439 mV with 0.333 μW and 138 mV with 0.051 μW, respectively. These results show that the sensor, using this configuration, successfully achieves three-axis magnetic field sensing and three-axis vibration energy-harvesting. Due to these features, the three-axis AC magnetic sensor could be an important design reference in order to develop future three-axis AC magnetic sensors, which possess energy-harvesting functions, for practical industrial applications, such as intelligent vehicle/traffic monitoring, processes monitoring, security systems, and so on. Full article
(This article belongs to the Special Issue Autonomous Sensors)
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Open AccessArticle Formal Uncertainty and Dispersion of Single and Double Difference Models for GNSS-Based Attitude Determination
Sensors 2017, 17(2), 408; doi:10.3390/s17020408
Received: 21 November 2016 / Revised: 4 February 2017 / Accepted: 16 February 2017 / Published: 20 February 2017
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Abstract
With multi-antenna synchronized global navigation satellite system (GNSS) receivers, the single difference (SD) between two antennas is able to eliminate both satellite and receiver clock error, thus it becomes necessary to reconsider the equivalency problem between the SD and double difference (DD) models.
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With multi-antenna synchronized global navigation satellite system (GNSS) receivers, the single difference (SD) between two antennas is able to eliminate both satellite and receiver clock error, thus it becomes necessary to reconsider the equivalency problem between the SD and double difference (DD) models. In this paper, we quantitatively compared the formal uncertainties and dispersions between multiple SD models and the DD model, and also carried out static and kinematic short baseline experiments. The theoretical and experimental results show that under a non-common clock scheme the SD and DD model are equivalent. Under a common clock scheme, if we estimate stochastic uncalibrated phase delay (UPD) parameters every epoch, this SD model is still equivalent to the DD model, but if we estimate only one UPD parameter for all epochs or take it as a known constant, the SD (here called SD2) and DD models are no longer equivalent. For the vertical component of baseline solutions, the formal uncertainties of the SD2 model are two times smaller than those of the DD model, and the dispersions of the SD2 model are even more than twice smaller than those of the DD model. In addition, to obtain baseline solutions, the SD2 model requires a minimum of three satellites, while the DD model requires a minimum of four satellites, which makes the SD2 more advantageous in attitude determination under sheltered environments. Full article
(This article belongs to the Section Remote Sensors)
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Open AccessArticle GaitKeeper: A System for Measuring Canine Gait
Sensors 2017, 17(2), 309; doi:10.3390/s17020309
Received: 9 December 2016 / Revised: 25 January 2017 / Accepted: 31 January 2017 / Published: 8 February 2017
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Abstract
It is understood gait has the potential to be used as a window into neurodegenerative disorders, identify markers of subclinical pathology, inform diagnostic algorithms of disease progression and measure the efficacy of interventions. Dogs’ gaits are frequently assessed in a veterinary setting to
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It is understood gait has the potential to be used as a window into neurodegenerative disorders, identify markers of subclinical pathology, inform diagnostic algorithms of disease progression and measure the efficacy of interventions. Dogs’ gaits are frequently assessed in a veterinary setting to detect signs of lameness. Despite this, a reliable, affordable and objective method to assess lameness in dogs is lacking. Most described canine lameness assessments are subjective, unvalidated and at high risk of bias. This means reliable, early detection of canine gait abnormalities is challenging, which may have detrimental implications for dogs’ welfare. In this paper, we draw from approaches and technologies used in human movement science and describe a system for objectively measuring temporal gait characteristics in dogs (step-time, swing-time, stance-time). Asymmetries and variabilities in these characteristics are of known clinical significance when assessing lameness but presently may only be assessed on coarse scales or under highly instrumented environments. The system consists an inertial measurement unit, containing a 3-axis accelerometer and gyroscope coupled with a standardized walking course. The measurement unit is attached to each leg of the dog under assessment before it is walked around the course. The data by the measurement unit is then processed to identify steps and subsequently, micro-gait characteristics. This method has been tested on a cohort of 19 healthy dogs of various breeds ranging in height from 34.2 cm to 84.9 cm. We report the system as capable of making precise step delineations with detections of initial and final contact times of foot-to-floor to a mean precision of 0.011 s and 0.048 s, respectively. Results are based on analysis of 12,678 foot falls and we report a sensitivity, positive predictive value and F-score of 0.81, 0.83 and 0.82 respectively. To investigate the effect of gait on system performance, the approach was tested in both walking and trotting with no significant performance deviation with 7249 steps reported for a walking gait and 4977 for a trotting gait. The number of steps reported for each leg were approximately equal and this consistency was true in both walking and trotting gaits. In the walking gait 1965, 1790, 1726 and 1768 steps were reported for the front left, front right, hind left and hind right legs respectively. 1361, 1250, 1176 and 1190 steps were reported for each of the four legs in the trotting gait. The proposed system is a pragmatic and precise solution for obtaining objective measurements of canine gait. With further development, it promises potential for a wide range of applications in both research and clinical practice. Full article
(This article belongs to the Section Physical Sensors)
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Open AccessArticle Quasi-Static Calibration Method of a High-g Accelerometer
Sensors 2017, 17(2), 409; doi:10.3390/s17020409
Received: 2 January 2017 / Revised: 9 February 2017 / Accepted: 14 February 2017 / Published: 20 February 2017
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Abstract
To solve the problem of resonance during quasi-static calibration of high-g accelerometers, we deduce the relationship between the minimum excitation pulse width and the resonant frequency of the calibrated accelerometer according to the second-order mathematical model of the accelerometer, and improve the quasi-static
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To solve the problem of resonance during quasi-static calibration of high-g accelerometers, we deduce the relationship between the minimum excitation pulse width and the resonant frequency of the calibrated accelerometer according to the second-order mathematical model of the accelerometer, and improve the quasi-static calibration theory. We establish a quasi-static calibration testing system, which uses a gas gun to generate high-g acceleration signals, and apply a laser interferometer to reproduce the impact acceleration. These signals are used to drive the calibrated accelerometer. By comparing the excitation acceleration signal and the output responses of the calibrated accelerometer to the excitation signals, the impact sensitivity of the calibrated accelerometer is obtained. As indicated by the calibration test results, this calibration system produces excitation acceleration signals with a pulse width of less than 1000 μs, and realize the quasi-static calibration of high-g accelerometers with a resonant frequency above 20 kHz when the calibration error was 3%. Full article
(This article belongs to the Section Physical Sensors)
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Open AccessArticle Dynamic Voltage-Frequency and Workload Joint Scaling Power Management for Energy Harvesting Multi-Core WSN Node SoC
Sensors 2017, 17(2), 310; doi:10.3390/s17020310
Received: 9 January 2017 / Revised: 2 February 2017 / Accepted: 2 February 2017 / Published: 8 February 2017
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Abstract
This paper proposes a scheduling and power management solution for energy harvesting heterogeneous multi-core WSN node SoC such that the system continues to operate perennially and uses the harvested energy efficiently. The solution consists of a heterogeneous multi-core system oriented task scheduling algorithm
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This paper proposes a scheduling and power management solution for energy harvesting heterogeneous multi-core WSN node SoC such that the system continues to operate perennially and uses the harvested energy efficiently. The solution consists of a heterogeneous multi-core system oriented task scheduling algorithm and a low-complexity dynamic workload scaling and configuration optimization algorithm suitable for light-weight platforms. Moreover, considering the power consumption of most WSN applications have the characteristic of data dependent behavior, we introduce branches handling mechanism into the solution as well. The experimental result shows that the proposed algorithm can operate in real-time on a lightweight embedded processor (MSP430), and that it can make a system do more valuable works and make more than 99.9% use of the power budget. Full article
(This article belongs to the Special Issue Energy Harvesting Sensors for Long Term Applications in the IoT Era)
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Open AccessArticle Toward Improving Electrocardiogram (ECG) Biometric Verification using Mobile Sensors: A Two-Stage Classifier Approach
Sensors 2017, 17(2), 410; doi:10.3390/s17020410
Received: 4 December 2016 / Revised: 17 January 2017 / Accepted: 9 February 2017 / Published: 20 February 2017
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Abstract
Electrocardiogram (ECG) signals sensed from mobile devices pertain the potential for biometric identity recognition applicable in remote access control systems where enhanced data security is demanding. In this study, we propose a new algorithm that consists of a two-stage classifier combining random forest
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Electrocardiogram (ECG) signals sensed from mobile devices pertain the potential for biometric identity recognition applicable in remote access control systems where enhanced data security is demanding. In this study, we propose a new algorithm that consists of a two-stage classifier combining random forest and wavelet distance measure through a probabilistic threshold schema, to improve the effectiveness and robustness of a biometric recognition system using ECG data acquired from a biosensor integrated into mobile devices. The proposed algorithm is evaluated using a mixed dataset from 184 subjects under different health conditions. The proposed two-stage classifier achieves a total of 99.52% subject verification accuracy, better than the 98.33% accuracy from random forest alone and 96.31% accuracy from wavelet distance measure algorithm alone. These results demonstrate the superiority of the proposed algorithm for biometric identification, hence supporting its practicality in areas such as cloud data security, cyber-security or remote healthcare systems. Full article
(This article belongs to the Section Biosensors)
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Open AccessArticle Dynamic Method of Neutral Axis Position Determination and Damage Identification with Distributed Long-Gauge FBG Sensors
Sensors 2017, 17(2), 411; doi:10.3390/s17020411
Received: 25 November 2016 / Revised: 6 February 2017 / Accepted: 10 February 2017 / Published: 20 February 2017
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Abstract
The neutral axis position (NAP) is a key parameter of a flexural member for structure design and safety evaluation. The accuracy of NAP measurement based on traditional methods does not satisfy the demands of structural performance assessment especially under live traffic loads. In
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The neutral axis position (NAP) is a key parameter of a flexural member for structure design and safety evaluation. The accuracy of NAP measurement based on traditional methods does not satisfy the demands of structural performance assessment especially under live traffic loads. In this paper, a new method to determine NAP is developed by using modal macro-strain (MMS). In the proposed method, macro-strain is first measured with long-gauge Fiber Bragg Grating (FBG) sensors; then the MMS is generated from the measured macro-strain with Fourier transform; and finally the neutral axis position coefficient (NAPC) is determined from the MMS and the neutral axis depth is calculated with NAPC. To verify the effectiveness of the proposed method, some experiments on FE models, steel beam and reinforced concrete (RC) beam were conducted. From the results, the plane section was first verified with MMS of the first bending mode. Then the results confirmed the high accuracy and stability for assessing NAP. The results also proved that the NAPC was a good indicator of local damage. In summary, with the proposed method, accurate assessment of flexural structures can be facilitated. Full article
(This article belongs to the Special Issue Recent Advances in Fiber Bragg Grating Sensing)
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Open AccessArticle Hybrid Analytical and Data-Driven Modeling for Feed-Forward Robot Control †
Sensors 2017, 17(2), 311; doi:10.3390/s17020311
Received: 23 December 2016 / Revised: 30 January 2017 / Accepted: 1 February 2017 / Published: 8 February 2017
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Abstract
Feed-forward model-based control relies on models of the controlled plant, e.g., in robotics on accurate knowledge of manipulator kinematics or dynamics. However, mechanical and analytical models do not capture all aspects of a plant’s intrinsic properties and there remain unmodeled dynamics due to
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Feed-forward model-based control relies on models of the controlled plant, e.g., in robotics on accurate knowledge of manipulator kinematics or dynamics. However, mechanical and analytical models do not capture all aspects of a plant’s intrinsic properties and there remain unmodeled dynamics due to varying parameters, unmodeled friction or soft materials. In this context, machine learning is an alternative suitable technique to extract non-linear plant models from data. However, fully data-based models suffer from inaccuracies as well and are inefficient if they include learning of well known analytical models. This paper thus argues that feed-forward control based on hybrid models comprising an analytical model and a learned error model can significantly improve modeling accuracy. Hybrid modeling here serves the purpose to combine the best of the two modeling worlds. The hybrid modeling methodology is described and the approach is demonstrated for two typical problems in robotics, i.e., inverse kinematics control and computed torque control. The former is performed for a redundant soft robot and the latter for a rigid industrial robot with redundant degrees of freedom, where a complete analytical model is not available for any of the platforms. Full article
(This article belongs to the Special Issue System-Integrated Intelligence and Intelligent Systems)
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Open AccessArticle Basic Send-on-Delta Sampling for Signal Tracking-Error Reduction
Sensors 2017, 17(2), 312; doi:10.3390/s17020312
Received: 12 December 2016 / Revised: 21 January 2017 / Accepted: 3 February 2017 / Published: 8 February 2017
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Abstract
This paper investigates the dynamic selection of an appropriate threshold for basic Send-on-Delta (SoD) sampling strategies, given an available transmission rate to reduce the signal tracking-error. The paper formulates the error-reduction principle and proposes an algorithm that calculates, in real time, the amplitude
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This paper investigates the dynamic selection of an appropriate threshold for basic Send-on-Delta (SoD) sampling strategies, given an available transmission rate to reduce the signal tracking-error. The paper formulates the error-reduction principle and proposes an algorithm that calculates, in real time, the amplitude threshold value (also called delta value) for a desired mean transmission rate. The algorithm is implemented to be computed in a Send-on-Delta driver and is tested with three signals that match the step response of a second order control system. Comparison results with a conformant periodic transmission strategy reveals that it improves deeply the tracking-error while maintaining the desired average throughput. Full article
(This article belongs to the Section Sensor Networks)
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Open AccessArticle An Improved Azimuth Angle Estimation Method with a Single Acoustic Vector Sensor Based on an Active Sonar Detection System
Sensors 2017, 17(2), 412; doi:10.3390/s17020412
Received: 7 November 2016 / Revised: 15 February 2017 / Accepted: 16 February 2017 / Published: 20 February 2017
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Abstract
In this paper, an improved azimuth angle estimation method with a single acoustic vector sensor (AVS) is proposed based on matched filtering theory. The proposed method is mainly applied in an active sonar detection system. According to the conventional passive method based on
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In this paper, an improved azimuth angle estimation method with a single acoustic vector sensor (AVS) is proposed based on matched filtering theory. The proposed method is mainly applied in an active sonar detection system. According to the conventional passive method based on complex acoustic intensity measurement, the mathematical and physical model of this proposed method is described in detail. The computer simulation and lake experiments results indicate that this method can realize the azimuth angle estimation with high precision by using only a single AVS. Compared with the conventional method, the proposed method achieves better estimation performance. Moreover, the proposed method does not require complex operations in frequencydomain and achieves computational complexity reduction. Full article
(This article belongs to the Section Physical Sensors)
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Open AccessArticle Analyzing the Effects of UAV Mobility Patterns on Data Collection in Wireless Sensor Networks
Sensors 2017, 17(2), 413; doi:10.3390/s17020413
Received: 28 December 2016 / Revised: 8 February 2017 / Accepted: 15 February 2017 / Published: 20 February 2017
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Abstract
Sensor nodes in a Wireless Sensor Network (WSN) can be dispersed over a remote sensing area (e.g., the regions that are hardly accessed by human beings). In such kinds of networks, datacollectionbecomesoneofthemajorissues. Getting connected to each sensor node and retrieving the information in
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Sensor nodes in a Wireless Sensor Network (WSN) can be dispersed over a remote sensing area (e.g., the regions that are hardly accessed by human beings). In such kinds of networks, datacollectionbecomesoneofthemajorissues. Getting connected to each sensor node and retrieving the information in time introduces new challenges. Mobile sink usage—especially Unmanned Aerial Vehicles (UAVs)—is the most convenient approach to covering the area and accessing each sensor node in such a large-scale WSN. However, the operation of the UAV depends on some parameters, such as endurance time, altitude, speed, radio type in use, and the path. In this paper, we explore various UAV mobility patterns that follow different paths to sweep the operation area in order to seek the best area coverage with the maximum number of covered nodes in the least amount of time needed by the mobile sink. We also introduce a new metric to formulate the tradeoff between maximizing the covered nodes and minimizing the operation time when choosing the appropriate mobility pattern. A realistic simulation environment is used in order to compare and evaluate the performance of the system. We present the performance results for the explored UAV mobility patterns. The results are very useful to present the tradeoff between maximizing the covered nodes and minimizing the operation time to choose the appropriate mobility pattern. Full article
(This article belongs to the Section Remote Sensors)
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Open AccessArticle An Adaptive Multi-Sensor Data Fusion Method Based on Deep Convolutional Neural Networks for Fault Diagnosis of Planetary Gearbox
Sensors 2017, 17(2), 414; doi:10.3390/s17020414
Received: 30 December 2016 / Revised: 11 February 2017 / Accepted: 16 February 2017 / Published: 21 February 2017
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Abstract
A fault diagnosis approach based on multi-sensor data fusion is a promising tool to deal with complicated damage detection problems of mechanical systems. Nevertheless, this approach suffers from two challenges, which are (1) the feature extraction from various types of sensory data and
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A fault diagnosis approach based on multi-sensor data fusion is a promising tool to deal with complicated damage detection problems of mechanical systems. Nevertheless, this approach suffers from two challenges, which are (1) the feature extraction from various types of sensory data and (2) the selection of a suitable fusion level. It is usually difficult to choose an optimal feature or fusion level for a specific fault diagnosis task, and extensive domain expertise and human labor are also highly required during these selections. To address these two challenges, we propose an adaptive multi-sensor data fusion method based on deep convolutional neural networks (DCNN) for fault diagnosis. The proposed method can learn features from raw data and optimize a combination of different fusion levels adaptively to satisfy the requirements of any fault diagnosis task. The proposed method is tested through a planetary gearbox test rig. Handcraft features, manual-selected fusion levels, single sensory data, and two traditional intelligent models, back-propagation neural networks (BPNN) and a support vector machine (SVM), are used as comparisons in the experiment. The results demonstrate that the proposed method is able to detect the conditions of the planetary gearbox effectively with the best diagnosis accuracy among all comparative methods in the experiment. Full article
(This article belongs to the Section Physical Sensors)
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Open AccessArticle Hyperspectral Image Classification with Spatial Filtering and \(l_{(2,1)}\) Norm
Sensors 2017, 17(2), 314; doi:10.3390/s17020314
Received: 8 December 2016 / Revised: 24 January 2017 / Accepted: 4 February 2017 / Published: 8 February 2017
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Abstract
Recently, the sparse representation based classification methods have received particular attention in the classification of hyperspectral imagery. However, current sparse representation based classification models have not considered all the test pixels simultaneously. In this paper, we propose a hyperspectral classification method with spatial
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Recently, the sparse representation based classification methods have received particular attention in the classification of hyperspectral imagery. However, current sparse representation based classification models have not considered all the test pixels simultaneously. In this paper, we propose a hyperspectral classification method with spatial filtering and \(l_{(2,1)}\) norm (SFL) that can deal with all the test pixels simultaneously. The \(l_{(2,1)}\) norm regularization is used to extract relevant training samples among the whole training data set with joint sparsity. In addition, the \(l_{(2,1)}\) norm loss function is adopted to make it robust for samples that deviate significantly from the rest of the samples. Moreover, to take the spatial information into consideration, a spatial filtering step is implemented where all the training and testing samples are spatially averaged with its nearest neighbors. Furthermore, the non-negative constraint is added to the sparse representation matrix motivated by hyperspectral unmixing. Finally, the alternating direction method of multipliers is used to solve SFL. Experiments on real hyperspectral images demonstrate that the proposed SFL method can obtain better classification performance than some other popular classifiers. Full article
(This article belongs to the Section Remote Sensors)
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Open AccessArticle Depicting Binding-Mediated Translocation of HIV-1 Tat Peptides in Living Cells with Nanoscale Pens of Tat-Conjugated Quantum Dots
Sensors 2017, 17(2), 315; doi:10.3390/s17020315
Received: 28 December 2016 / Revised: 24 January 2017 / Accepted: 30 January 2017 / Published: 10 February 2017
PDF Full-text (4518 KB) | HTML Full-text | XML Full-text | Supplementary Files
Abstract
Cell-penetrating peptides (CPPs) can translocate across cell membranes, and thus have great potential for the cellular delivery of macromolecular cargoes. However, the mechanism of this cellular uptake process is not yet fully understood. In this study, a time-lapse single-particle light-sheet microscopy technique was
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Cell-penetrating peptides (CPPs) can translocate across cell membranes, and thus have great potential for the cellular delivery of macromolecular cargoes. However, the mechanism of this cellular uptake process is not yet fully understood. In this study, a time-lapse single-particle light-sheet microscopy technique was implemented to obtain a parallel visualization of the translocating process of individual human immunodeficiency virus 1 (HIV-1) transactivator of transcription (Tat) peptide conjugated quantum dots (TatP-QDs) in complex cellular terrains. Here, TatP-QDs served as nanoscale dynamic pens, which depict remarkable trajectory aggregates of TatP-QDs on the cell surface. Spectral-embedding analysis of the trajectory aggregates revealed a manifold formed by isotropic diffusion and a fraction of directed movement, possibly caused by interaction between the Tat peptides and heparan sulfate groups on the plasma membrane. Further analysis indicated that the membrane deformation induced by Tat-peptide attachment increased with the disruption of the actin framework in cytochalasin D (cyto D)-treated cells, yielding higher interactions on the TatP-QDs. In native cells, the Tat peptides can remodel the actin framework to reduce their interaction with the local membrane environment. Characteristic hot spots for interaction were detected on the membrane, suggesting that a funnel passage may have formed for the Tat-coated particles. This finding offers valuable insight into the cellular delivery of nanoscale cargo, suggesting an avenue for direct therapeutic delivery. Full article
(This article belongs to the Special Issue Single-Molecule Sensing)
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Open AccessArticle Probabilistic Neighborhood-Based Data Collection Algorithms for 3D Underwater Acoustic Sensor Networks
Sensors 2017, 17(2), 316; doi:10.3390/s17020316
Received: 9 January 2017 / Revised: 6 February 2017 / Accepted: 6 February 2017 / Published: 8 February 2017
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Abstract
Marine environmental monitoring provides crucial information and support for the exploitation, utilization, and protection of marine resources. With the rapid development of information technology, the development of three-dimensional underwater acoustic sensor networks (3D UASNs) provides a novel strategy to acquire marine environment information
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Marine environmental monitoring provides crucial information and support for the exploitation, utilization, and protection of marine resources. With the rapid development of information technology, the development of three-dimensional underwater acoustic sensor networks (3D UASNs) provides a novel strategy to acquire marine environment information conveniently, efficiently and accurately. However, the specific propagation effects of acoustic communication channel lead to decreased successful information delivery probability with increased distance. Therefore, we investigate two probabilistic neighborhood-based data collection algorithms for 3D UASNs which are based on a probabilistic acoustic communication model instead of the traditional deterministic acoustic communication model. An autonomous underwater vehicle (AUV) is employed to traverse along the designed path to collect data from neighborhoods. For 3D UASNs without prior deployment knowledge, partitioning the network into grids can allow the AUV to visit the central location of each grid for data collection. For 3D UASNs in which the deployment knowledge is known in advance, the AUV only needs to visit several selected locations by constructing a minimum probabilistic neighborhood covering set to reduce data latency. Otherwise, by increasing the transmission rounds, our proposed algorithms can provide a tradeoff between data collection latency and information gain. These algorithms are compared with basic Nearest-neighbor Heuristic algorithm via simulations. Simulation analyses show that our proposed algorithms can efficiently reduce the average data collection completion time, corresponding to a decrease of data latency. Full article
(This article belongs to the Special Issue Advances and Challenges in Underwater Sensor Networks)
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Open AccessArticle Dynamic Fluid in a Porous Transducer-Based Angular Accelerometer
Sensors 2017, 17(2), 416; doi:10.3390/s17020416
Received: 5 December 2016 / Revised: 8 February 2017 / Accepted: 15 February 2017 / Published: 21 February 2017
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Abstract
This paper presents a theoretical model of the dynamics of liquid flow in an angular accelerometer comprising a porous transducer in a circular tube of liquid. Wave speed and dynamic permeability of the transducer are considered to describe the relation between angular acceleration
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This paper presents a theoretical model of the dynamics of liquid flow in an angular accelerometer comprising a porous transducer in a circular tube of liquid. Wave speed and dynamic permeability of the transducer are considered to describe the relation between angular acceleration and the differential pressure on the transducer. The permeability and streaming potential coupling coefficient of the transducer are determined in the experiments, and special prototypes are utilized to validate the theoretical model in both the frequency and time domains. The model is applied to analyze the influence of structural parameters on the frequency response and the transient response of the fluidic system. It is shown that the radius of the circular tube and the wave speed affect the low frequency gain, as well as the bandwidth of the sensor. The hydrodynamic resistance of the transducer and the cross-section radius of the circular tube can be used to control the transient performance. The proposed model provides the basic techniques to achieve the optimization of the angular accelerometer together with the methodology to control the wave speed and the hydrodynamic resistance of the transducer. Full article
(This article belongs to the Section Physical Sensors)
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Open AccessArticle Towards Building a Computer Aided Education System for Special Students Using Wearable Sensor Technologies
Sensors 2017, 17(2), 317; doi:10.3390/s17020317
Received: 21 November 2016 / Revised: 27 January 2017 / Accepted: 4 February 2017 / Published: 8 February 2017
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Abstract
Human computer interaction is a growing field in terms of helping people in their daily life to improve their living. Especially, people with some disability may need an interface which is more appropriate and compatible with their needs. Our research is focused on
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Human computer interaction is a growing field in terms of helping people in their daily life to improve their living. Especially, people with some disability may need an interface which is more appropriate and compatible with their needs. Our research is focused on similar kinds of problems, such as students with some mental disorder or mood disruption problems. To improve their learning process, an intelligent emotion recognition system is essential which has an ability to recognize the current emotional state of the brain. Nowadays, in special schools, instructors are commonly use some conventional methods for managing special students for educational purposes. In this paper, we proposed a novel computer aided method for instructors at special schools where they can teach special students with the support of our system using wearable technologies. Full article
(This article belongs to the Special Issue Multisensory Big Data Analytics for Enhanced Living Environments)
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Open AccessArticle A Sensor Data Fusion System Based on k-Nearest Neighbor Pattern Classification for Structural Health Monitoring Applications
Sensors 2017, 17(2), 417; doi:10.3390/s17020417
Received: 30 December 2016 / Revised: 9 February 2017 / Accepted: 17 February 2017 / Published: 21 February 2017
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Abstract
Civil and military structures are susceptible and vulnerable to damage due to the environmental and operational conditions. Therefore, the implementation of technology to provide robust solutions in damage identification (by using signals acquired directly from the structure) is a requirement to reduce operational
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Civil and military structures are susceptible and vulnerable to damage due to the environmental and operational conditions. Therefore, the implementation of technology to provide robust solutions in damage identification (by using signals acquired directly from the structure) is a requirement to reduce operational and maintenance costs. In this sense, the use of sensors permanently attached to the structures has demonstrated a great versatility and benefit since the inspection system can be automated. This automation is carried out with signal processing tasks with the aim of a pattern recognition analysis. This work presents the detailed description of a structural health monitoring (SHM) system based on the use of a piezoelectric (PZT) active system. The SHM system includes: (i) the use of a piezoelectric sensor network to excite the structure and collect the measured dynamic response, in several actuation phases; (ii) data organization; (iii) advanced signal processing techniques to define the feature vectors; and finally; (iv) the nearest neighbor algorithm as a machine learning approach to classify different kinds of damage. A description of the experimental setup, the experimental validation and a discussion of the results from two different structures are included and analyzed. Full article
(This article belongs to the Special Issue System-Integrated Intelligence and Intelligent Systems)
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Open AccessArticle Online Condition Monitoring of a Rail Fastening System on High-Speed Railways Based on Wavelet Packet Analysis
Sensors 2017, 17(2), 318; doi:10.3390/s17020318
Received: 26 November 2016 / Revised: 21 January 2017 / Accepted: 26 January 2017 / Published: 8 February 2017
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Abstract
The rail fastening system is an important part of a high-speed railway track. It is always critical to the operational safety and comfort of railway vehicles. Therefore, the condition detection of the rail fastening system, looseness or absence, is an important task in
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The rail fastening system is an important part of a high-speed railway track. It is always critical to the operational safety and comfort of railway vehicles. Therefore, the condition detection of the rail fastening system, looseness or absence, is an important task in railway maintenance. However, the vision-based method cannot identify the severity of rail fastener looseness. In this paper, the condition of rail fastening system is monitored based on an automatic and remote-sensing measurement system. Meanwhile, wavelet packet analysis is used to analyze the acceleration signals, based on which two damage indices are developed to locate the damage position and evaluate the severity of rail fasteners looseness, respectively. To verify the effectiveness of the proposed method, an experiment is performed on a high-speed railway experimental platform. The experimental results show that the proposed method is effective to assess the condition of the rail fastening system. The monitoring system significantly reduces the inspection time and increases the efficiency of maintenance management. Full article
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Open AccessArticle Data Collection and Analysis Using Wearable Sensors for Monitoring Knee Range of Motion after Total Knee Arthroplasty
Sensors 2017, 17(2), 418; doi:10.3390/s17020418
Received: 15 October 2016 / Revised: 17 January 2017 / Accepted: 13 February 2017 / Published: 22 February 2017
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Abstract
Total knee arthroplasty (TKA) is the most common treatment for degenerative osteoarthritis of that articulation. However, either in rehabilitation clinics or in hospital wards, the knee range of motion (ROM) can currently only be assessed using a goniometer. In order to provide continuous
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Total knee arthroplasty (TKA) is the most common treatment for degenerative osteoarthritis of that articulation. However, either in rehabilitation clinics or in hospital wards, the knee range of motion (ROM) can currently only be assessed using a goniometer. In order to provide continuous and objective measurements of knee ROM, we propose the use of wearable inertial sensors to record the knee ROM during the recovery progress. Digitalized and objective data can assist the surgeons to control the recovery status and flexibly adjust rehabilitation programs during the early acute inpatient stage. The more knee flexion ROM regained during the early inpatient period, the better the long-term knee recovery will be and the sooner early discharge can be achieved. The results of this work show that the proposed wearable sensor approach can provide an alternative for continuous monitoring and objective assessment of knee ROM recovery progress for TKA patients compared to the traditional goniometer measurements. Full article
(This article belongs to the Special Issue Wearable and Ambient Sensors for Healthcare and Wellness Applications)
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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,
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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 Time-Elastic Generative Model for Acceleration Time Series in Human Activity Recognition
Sensors 2017, 17(2), 319; doi:10.3390/s17020319
Received: 21 December 2016 / Revised: 1 February 2017 / Accepted: 6 February 2017 / Published: 8 February 2017
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Abstract
Body-worn sensors in general and accelerometers in particular have been widely used in order to detect human movements and activities. The execution of each type of movement by each particular individual generates sequences of time series of sensed data from which specific movement
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Body-worn sensors in general and accelerometers in particular have been widely used in order to detect human movements and activities. The execution of each type of movement by each particular individual generates sequences of time series of sensed data from which specific movement related patterns can be assessed. Several machine learning algorithms have been used over windowed segments of sensed data in order to detect such patterns in activity recognition based on intermediate features (either hand-crafted or automatically learned from data). The underlying assumption is that the computed features will capture statistical differences that can properly classify different movements and activities after a training phase based on sensed data. In order to achieve high accuracy and recall rates (and guarantee the generalization of the system to new users), the training data have to contain enough information to characterize all possible ways of executing the activity or movement to be detected. This could imply large amounts of data and a complex and time-consuming training phase, which has been shown to be even more relevant when automatically learning the optimal features to be used. In this paper, we present a novel generative model that is able to generate sequences of time series for characterizing a particular movement based on the time elasticity properties of the sensed data. The model is used to train a stack of auto-encoders in order to learn the particular features able to detect human movements. The results of movement detection using a newly generated database with information on five users performing six different movements are presented. The generalization of results using an existing database is also presented in the paper. The results show that the proposed mechanism is able to obtain acceptable recognition rates (F = 0.77) even in the case of using different people executing a different sequence of movements and using different hardware. Full article
(This article belongs to the Special Issue Body Worn Behavior Sensing)
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Open AccessArticle Long Term Amperometric Recordings in the Brain Extracellular Fluid of Freely Moving Immunocompromised NOD SCID Mice
Sensors 2017, 17(2), 419; doi:10.3390/s17020419
Received: 3 January 2017 / Revised: 10 February 2017 / Accepted: 18 February 2017 / Published: 22 February 2017
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Abstract
We describe the in vivo characterization of microamperometric sensors for the real-time monitoring of nitric oxide (NO) and oxygen (O2) in the striatum of immunocompromised NOD SCID mice. The latter strain has been utilized routinely in the establishment of humanized models
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We describe the in vivo characterization of microamperometric sensors for the real-time monitoring of nitric oxide (NO) and oxygen (O2) in the striatum of immunocompromised NOD SCID mice. The latter strain has been utilized routinely in the establishment of humanized models of disease e.g., Parkinson’s disease. NOD SCID mice were implanted with highly sensitive and selective NO and O2 sensors that have been previously characterized both in vitro and in freely moving rats. Animals were systemically administered compounds that perturbed the amperometric current and confirmed sensor performance. Furthermore, the stability of the amperometric current was investigated and 24 h recordings examined. Saline injections caused transient changes in both currents that were not significant from baseline. l-NAME caused significant decreases in NO (p < 0.05) and O2 (p < 0.001) currents compared to saline. l-Arginine produced a significant increase (p < 0.001) in NO current, and chloral hydrate and Diamox (acetazolamide) caused significant increases in O2 signal (p < 0.01) compared against saline. The stability of both currents were confirmed over an eight-day period and analysis of 24-h recordings identified diurnal variations in both signals. These findings confirm the efficacy of the amperometric sensors to perform continuous and reliable recordings in immunocompromised mice. Full article
(This article belongs to the Section Biosensors)
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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
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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 Investigation of Pristine Graphite Oxide as Room-Temperature Chemiresistive Ammonia Gas Sensing Material
Sensors 2017, 17(2), 320; doi:10.3390/s17020320
Received: 26 December 2016 / Revised: 2 February 2017 / Accepted: 6 February 2017 / Published: 9 February 2017
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Abstract
Graphite oxide has been investigated as a possible room-temperature chemiresistive sensor of ammonia in a gas phase. Graphite oxide was synthesized from high purity graphite using the modified Hummers method. The graphite oxide sample was investigated using scanning electron microscopy, energy dispersive X-ray
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Graphite oxide has been investigated as a possible room-temperature chemiresistive sensor of ammonia in a gas phase. Graphite oxide was synthesized from high purity graphite using the modified Hummers method. The graphite oxide sample was investigated using scanning electron microscopy, energy dispersive X-ray spectroscopy, X-ray diffraction, thermogravimetry and differential scanning calorimetry. Sensing properties were tested in a wide range of ammonia concentrations in air (10–1000 ppm) and under different relative humidity levels (3%–65%). It was concluded that the graphite oxide–based sensor possessed a good response to NH3 in dry synthetic air (ΔR/R0 ranged from 2.5% to 7.4% for concentrations of 100–500 ppm and 3% relative humidity) with negligible cross-sensitivity towards H2 and CH4. It was determined that the sensor recovery rate was improved with ammonia concentration growth. Increasing the ambient relative humidity led to an increase of the sensor response. The highest response of 22.2% for 100 ppm of ammonia was achieved at a 65% relative humidity level. Full article
(This article belongs to the Special Issue Gas Nanosensors)
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Open AccessArticle A Soft Sensor-Based Three-Dimensional (3-D) Finger Motion Measurement System
Sensors 2017, 17(2), 420; doi:10.3390/s17020420
Received: 20 December 2016 / Revised: 30 January 2017 / Accepted: 10 February 2017 / Published: 22 February 2017
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Abstract
In this study, a soft sensor-based three-dimensional (3-D) finger motion measurement system is proposed. The sensors, made of the soft material Ecoflex, comprise embedded microchannels filled with a conductive liquid metal (EGaln). The superior elasticity, light weight, and sensitivity of soft sensors allows
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In this study, a soft sensor-based three-dimensional (3-D) finger motion measurement system is proposed. The sensors, made of the soft material Ecoflex, comprise embedded microchannels filled with a conductive liquid metal (EGaln). The superior elasticity, light weight, and sensitivity of soft sensors allows them to be embedded in environments in which conventional sensors cannot. Complicated finger joints, such as the carpometacarpal (CMC) joint of the thumb are modeled to specify the location of the sensors. Algorithms to decouple the signals from soft sensors are proposed to extract the pure flexion, extension, abduction, and adduction joint angles. The performance of the proposed system and algorithms are verified by comparison with a camera-based motion capture system. Full article
(This article belongs to the Special Issue Flexible Electronics and 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
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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 Efficient Data Collection in Widely Distributed Wireless Sensor Networks with Time Window and Precedence Constraints
Sensors 2017, 17(2), 421; doi:10.3390/s17020421
Received: 15 December 2016 / Revised: 6 February 2017 / Accepted: 7 February 2017 / Published: 22 February 2017
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Abstract
In addition to the traditional densely deployed cases, widely distributed wireless sensor networks (WDWSNs) have begun to emerge. In these networks, sensors are far away from each other and have no network connections. In this paper, a special application of data collection for
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In addition to the traditional densely deployed cases, widely distributed wireless sensor networks (WDWSNs) have begun to emerge. In these networks, sensors are far away from each other and have no network connections. In this paper, a special application of data collection for WDWSNs is considered where each sensor (Unmanned Ground Vehicle, UGV) moves in a hazardous and complex terrain with many obstacles. They have their own work cycles and can be accessed only at a few locations. A mobile sink cruises on the ground to collect data gathered from these UGVs. Considerable delay is inevitable if the UGV and the mobile sink miss the meeting window or wait idly at the meeting spot. The unique challenge here is that, for each cycle of an UGV, there is only a limited time window for it to appear in front of the mobile sink. Therefore, we propose scheduling the path of a single mobile sink, targeted at visiting a maximum number of UGVs in a timely manner with the shortest path, according to the timing constraints bound by the cycles of UGVs. We then propose a bipartite matching based algorithm to reduce the number of mobile sinks. Simulation results show that the proposed algorithm can achieve performance close to the theoretical maximum determined by the duty cycle instance. Full article
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Open AccessArticle Intelligent Luminance Control of Lighting Systems Based on Imaging Sensor Feedback
Sensors 2017, 17(2), 321; doi:10.3390/s17020321
Received: 7 January 2017 / Revised: 1 February 2017 / Accepted: 3 February 2017 / Published: 9 February 2017
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Abstract
An imaging sensor-based intelligent Light Emitting Diode (LED) lighting system for desk use is proposed. In contrast to the traditional intelligent lighting system, such as the photosensitive resistance sensor-based or the infrared sensor-based system, the imaging sensor can realize a finer perception of
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An imaging sensor-based intelligent Light Emitting Diode (LED) lighting system for desk use is proposed. In contrast to the traditional intelligent lighting system, such as the photosensitive resistance sensor-based or the infrared sensor-based system, the imaging sensor can realize a finer perception of the environmental light; thus it can guide a more precise lighting control. Before this system works, first lots of typical imaging lighting data of the desk application are accumulated. Second, a series of subjective and objective Lighting Effect Evaluation Metrics (LEEMs) are defined and assessed for these datasets above. Then the cluster benchmarks of these objective LEEMs can be obtained. Third, both a single LEEM-based control and a multiple LEEMs-based control are developed to realize a kind of optimal luminance tuning. When this system works, first it captures the lighting image using a wearable camera. Then it computes the objective LEEMs of the captured image and compares them with the cluster benchmarks of the objective LEEMs. Finally, the single LEEM-based or the multiple LEEMs-based control can be implemented to get a kind of optimal lighting effect. Many experiment results have shown the proposed system can tune the LED lamp automatically according to environment luminance changes. Full article
(This article belongs to the Section Physical Sensors)
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Open AccessArticle A Temperature-Dependent Battery Model for Wireless Sensor Networks
Sensors 2017, 17(2), 422; doi:10.3390/s17020422
Received: 15 December 2016 / Revised: 24 January 2017 / Accepted: 3 February 2017 / Published: 22 February 2017
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Abstract
Energy consumption is a major issue in Wireless Sensor Networks (WSNs), as nodes are powered by chemical batteries with an upper bounded lifetime. Estimating the lifetime of batteries is a difficult task, as it depends on several factors, such as operating temperatures and
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Energy consumption is a major issue in Wireless Sensor Networks (WSNs), as nodes are powered by chemical batteries with an upper bounded lifetime. Estimating the lifetime of batteries is a difficult task, as it depends on several factors, such as operating temperatures and discharge rates. Analytical battery models can be used for estimating both the battery lifetime and the voltage behavior over time. Still, available models usually do not consider the impact of operating temperatures on the battery behavior. The target of this work is to extend the widely-used Kinetic Battery Model (KiBaM) to include the effect of temperature on the battery behavior. The proposed Temperature-Dependent KiBaM (T-KiBaM) is able to handle operating temperatures, providing better estimates for the battery lifetime and voltage behavior. The performed experimental validation shows that T-KiBaM achieves an average accuracy error smaller than 0.33%, when estimating the lifetime of Ni-MH batteries for different temperature conditions. In addition, T-KiBaM significantly improves the original KiBaM voltage model. The proposed model can be easily adapted to handle other battery technologies, enabling the consideration of different WSN deployments. Full article
(This article belongs to the Special Issue Wireless Rechargeable Sensor Networks)
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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
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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
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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 Study on the Thermomechanical Reliability Risks of Through-Silicon-Vias in Sensor Applications
Sensors 2017, 17(2), 322; doi:10.3390/s17020322
Received: 1 November 2016 / Revised: 9 January 2017 / Accepted: 16 January 2017 / Published: 9 February 2017
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Abstract
Reliability risks for two different types of through-silicon-vias (TSVs) are discussed in this paper. The first is a partially-filled copper TSV, if which the copper layer covers the side walls and bottom. A polymer is used to fill the rest of the cavity.
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Reliability risks for two different types of through-silicon-vias (TSVs) are discussed in this paper. The first is a partially-filled copper TSV, if which the copper layer covers the side walls and bottom. A polymer is used to fill the rest of the cavity. Stresses in risk sites are studied and ranked for this TSV structure by FEA modeling. Parametric studies for material properties (modulus and thermal expansion) of TSV polymer are performed. The second type is a high aspect ratio TSV filled by polycrystalline silicon (poly Si). Potential risks of the voids in the poly Si due to filling defects are studied. Fracture mechanics methods are utilized to evaluate the risk for two different assembly conditions: package assembled to printed circuit board (PCB) and package assembled to flexible substrate. The effect of board/substrate/die thickness and the size and location of the void are discussed. Full article
(This article belongs to the collection Modeling, Testing and Reliability Issues in MEMS Engineering)
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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
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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 BeiDou Signal Acquisition with Neumann–Hoffman Code Modulation in a Degraded Channel
Sensors 2017, 17(2), 323; doi:10.3390/s17020323
Received: 7 December 2016 / Revised: 19 January 2017 / Accepted: 19 January 2017 / Published: 9 February 2017
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Abstract
With the modernization of global navigation satellite systems (GNSS), secondary codes, also known as the Neumann–Hoffman (NH) codes, are modulated on the satellite signal to obtain a better positioning performance. However, this leads to an attenuation of the acquisition sensitivity of classic integration
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With the modernization of global navigation satellite systems (GNSS), secondary codes, also known as the Neumann–Hoffman (NH) codes, are modulated on the satellite signal to obtain a better positioning performance. However, this leads to an attenuation of the acquisition sensitivity of classic integration algorithms because of the frequent bit transitions that refer to the NH codes. Taking weak BeiDou navigation satellite system (BDS) signals as objects, the present study analyzes the side effect of NH codes on acquisition in detail and derives a straightforward formula, which indicates that bit transitions decrease the frequency accuracy. To meet the requirement of carrier-tracking loop initialization, a frequency recalculation algorithm is proposed based on verified fast Fourier transform (FFT) to mitigate the effect, meanwhile, the starting point of NH codes is found. Then, a differential correction is utilized to improve the acquisition accuracy of code phase. Monte Carlo simulations and real BDS data tests demonstrate that the new structure is superior to the conventional algorithms both in detection probability and frequency accuracy in a degraded channel. Full article
(This article belongs to the Section Remote Sensors)
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Open AccessArticle Experimental Validation of Depth Cameras for the Parameterization of Functional Balance of Patients in Clinical Tests
Sensors 2017, 17(2), 424; doi:10.3390/s17020424
Received: 24 November 2016 / Revised: 25 January 2017 / Accepted: 19 February 2017 / Published: 22 February 2017
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Abstract
In clinical practice, patients’ balance can be assessed using standard scales. Two of the most validated clinical tests for measuring balance are the Timed Up and Go (TUG) test and the MultiDirectional Reach Test (MDRT). Nowadays, inertial sensors (IS) are employed for kinematic
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In clinical practice, patients’ balance can be assessed using standard scales. Two of the most validated clinical tests for measuring balance are the Timed Up and Go (TUG) test and the MultiDirectional Reach Test (MDRT). Nowadays, inertial sensors (IS) are employed for kinematic analysis of functional tests in the clinical setting, and have become an alternative to expensive, 3D optical motion capture systems. In daily clinical practice, however, IS-based setups are yet cumbersome and inconvenient to apply. Current depth cameras have the potential for such application, presenting many advantages as, for instance, being portable, low-cost and minimally-invasive. This paper aims at experimentally validating to what extent this technology can substitute IS for the parameterization and kinematic analysis of the TUG and the MDRT tests. Twenty healthy young adults were recruited as participants to perform five different balance tests while kinematic data from their movements were measured by both a depth camera and an inertial sensor placed on their trunk. The reliability of the camera’s measurements is examined through the Interclass Correlation Coefficient (ICC), whilst the Pearson Correlation Coefficient (r) is computed to evaluate the correlation between both sensor’s measurements, revealing excellent reliability and strong correlations in most cases. Full article
(This article belongs to the collection Sensors for Globalized Healthy Living and Wellbeing)
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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
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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
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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 mDARAL: A Multi-Radio Version for the DARAL Routing Algorithm
Sensors 2017, 17(2), 324; doi:10.3390/s17020324
Received: 7 December 2016 / Revised: 31 January 2017 / Accepted: 3 February 2017 / Published: 9 February 2017
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Abstract
Smart Cities are called to change the daily life of human beings. This concept permits improving the efficiency of our cities in several areas such as the use of water, energy consumption, waste treatment, and mobility both for people as well as vehicles
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Smart Cities are called to change the daily life of human beings. This concept permits improving the efficiency of our cities in several areas such as the use of water, energy consumption, waste treatment, and mobility both for people as well as vehicles throughout the city. This represents an interconnected scenario in which thousands of embedded devices need to work in a collaborative way both for sensing and modifying the environment properly. Under this scenario, the majority of devices will use wireless protocols for communicating among them, representing a challenge for optimizing the use of the electromagnetic spectrum. When the density of deployed nodes increases, the competition for using the physical medium becomes harder and, in consequence, traffic collisions will be higher, affecting data-rates in the communication process. This work presents mDARAL, a multi-radio routing algorithm based on the Dynamic and Adaptive Radio Algorithm (DARAL), which has the capability of isolating groups of nodes into sub-networks. The nodes of each sub-network will communicate among them using a dedicated radio frequency, thus isolating the use of the radio channel to a reduced number of nodes. Each sub-network will have a master node with two physical radios, one for communicating with its neighbours and the other for being the contact point among its group and other sub-networks. The communication among sub-networks is done through master nodes in a dedicated radio frequency. The algorithm works to maximize the overall performance of the network through the distribution of the traffic messages into unoccupied frequencies. The obtained results show that mDARAL achieves great improvement in terms of the number of control messages necessary to connect a node to the network, convergence time and energy consumption during the connection phase compared to DARAL. Full article
(This article belongs to the Special Issue Smart City: Vision and Reality)
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Open AccessArticle A New Deep Learning Model for Fault Diagnosis with Good Anti-Noise and Domain Adaptation Ability on Raw Vibration Signals
Sensors 2017, 17(2), 425; doi:10.3390/s17020425
Received: 18 January 2017 / Revised: 16 February 2017 / Accepted: 20 February 2017 / Published: 22 February 2017
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Abstract
Intelligent fault diagnosis techniques have replaced time-consuming and unreliable human analysis, increasing the efficiency of fault diagnosis. Deep learning models can improve the accuracy of intelligent fault diagnosis with the help of their multilayer nonlinear mapping ability. This paper proposes a novel method
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Intelligent fault diagnosis techniques have replaced time-consuming and unreliable human analysis, increasing the efficiency of fault diagnosis. Deep learning models can improve the accuracy of intelligent fault diagnosis with the help of their multilayer nonlinear mapping ability. This paper proposes a novel method named Deep Convolutional Neural Networks with Wide First-layer Kernels (WDCNN). The proposed method uses raw vibration signals as input (data augmentation is used to generate more inputs), and uses the wide kernels in the first convolutional layer for extracting features and suppressing high frequency noise. Small convolutional kernels in the preceding layers are used for multilayer nonlinear mapping. AdaBN is implemented to improve the domain adaptation ability of the model. The proposed model addresses the problem that currently, the accuracy of CNN applied to fault diagnosis is not very high. WDCNN can not only achieve 100% classification accuracy on normal signals, but also outperform the state-of-the-art DNN model which is based on frequency features under different working load and noisy environment conditions. Full article
(This article belongs to the Section Physical Sensors)
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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
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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 Improved Omnidirectional Odometry for a View-Based Mapping Approach
Sensors 2017, 17(2), 325; doi:10.3390/s17020325
Received: 9 December 2016 / Revised: 3 February 2017 / Accepted: 6 February 2017 / Published: 9 February 2017
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Abstract
This work presents an improved visual odometry using omnidirectional images. The main purpose is to generate a reliable prior input which enhances the SLAM (Simultaneous Localization and Mapping) estimation tasks within the framework of navigation in mobile robotics, in detriment of the internal
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This work presents an improved visual odometry using omnidirectional images. The main purpose is to generate a reliable prior input which enhances the SLAM (Simultaneous Localization and Mapping) estimation tasks within the framework of navigation in mobile robotics, in detriment of the internal odometry data. Generally, standard SLAM approaches extensively use data such as the main prior input to localize the robot. They also tend to consider sensory data acquired with GPSs, lasers or digital cameras, as the more commonly acknowledged to re-estimate the solution. Nonetheless, the modeling of the main prior is crucial, and sometimes especially challenging when it comes to non-systematic terms, such as those associated with the internal odometer, which ultimately turn to be considerably injurious and compromise the convergence of the system. This omnidirectional odometry relies on an adaptive feature point matching through the propagation of the current uncertainty of the system. Ultimately, it is fused as the main prior input in an EKF (Extended Kalman Filter) view-based SLAM system, together with the adaption of the epipolar constraint to the omnidirectional geometry. Several improvements have been added to the initial visual odometry proposal so as to produce better performance. We present real data experiments to test the validity of the proposal and to demonstrate its benefits, in contrast to the internal odometry. Furthermore, SLAM results are included to assess its robustness and accuracy when using the proposed prior omnidirectional odometry. Full article
(This article belongs to the Section Physical Sensors)
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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
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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
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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 Development and Experimental Validation of a Dry Non-Invasive Multi-Channel Mouse Scalp EEG Sensor through Visual Evoked Potential Recordings
Sensors 2017, 17(2), 326; doi:10.3390/s17020326
Received: 20 September 2016 / Revised: 30 December 2016 / Accepted: 4 February 2017 / Published: 9 February 2017
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Abstract
In this paper, we introduce a dry non-invasive multi-channel sensor for measuring brainwaves on the scalps of mice. The research on laboratory animals provide insights to various practical applications involving human beings and other animals such as working animals, pets, and livestock. An
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In this paper, we introduce a dry non-invasive multi-channel sensor for measuring brainwaves on the scalps of mice. The research on laboratory animals provide insights to various practical applications involving human beings and other animals such as working animals, pets, and livestock. An experimental framework targeting the laboratory animals has the potential to lead to successful translational research when it closely resembles the environment of real applications. To serve scalp electroencephalography (EEG) research environments for the laboratory mice, the dry non-invasive scalp EEG sensor with sixteen electrodes is proposed to measure brainwaves over the entire brain area without any surgical procedures. We validated the proposed sensor system with visual evoked potential (VEP) experiments elicited by flash stimulations. The VEP responses obtained from experiments are compared with the existing literature, and analyzed in temporal and spatial perspectives. We further interpret the experimental results using time-frequency distribution (TFD) and distance measurements. The developed sensor guarantees stable operations for in vivo experiments in a non-invasive manner without surgical procedures, therefore exhibiting a high potential to strengthen longitudinal experimental studies and reliable translational research exploiting non-invasive paradigms. Full article
(This article belongs to the Section Biosensors)
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Open AccessArticle The Impact of 3D Stacking and Technology Scaling on the Power and Area of Stereo Matching Processors
Sensors 2017, 17(2), 426; doi:10.3390/s17020426
Received: 30 November 2016 / Revised: 12 February 2017 / Accepted: 17 February 2017 / Published: 22 February 2017
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Abstract
Recently, stereo matching processors have been adopted in real-time embedded systems such as intelligent robots and autonomous vehicles, which require minimal hardware resources and low power consumption. Meanwhile, thanks to the through-silicon via (TSV), three-dimensional (3D) stacking technology has emerged as a practical
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Recently, stereo matching processors have been adopted in real-time embedded systems such as intelligent robots and autonomous vehicles, which require minimal hardware resources and low power consumption. Meanwhile, thanks to the through-silicon via (TSV), three-dimensional (3D) stacking technology has emerged as a practical solution to achieving the desired requirements of a high-performance circuit. In this paper, we present the benefits of 3D stacking and process technology scaling on stereo matching processors. We implemented 2-tier 3D-stacked stereo matching processors with GlobalFoundries 130-nm and Nangate 45-nm process design kits and compare them with their two-dimensional (2D) counterparts to identify comprehensive design benefits. In addition, we examine the findings from various analyses to identify the power benefits of 3D-stacked integrated circuit (IC) and device technology advancements. From experiments, we observe that the proposed 3D-stacked ICs, compared to their 2D IC counterparts, obtain 43% area, 13% power, and 14% wire length reductions. In addition, we present a logic partitioning method suitable for a pipeline-based hardware architecture that minimizes the use of TSVs. Full article
(This article belongs to the Special Issue Advances on Resources Management for Multi-Platform Infrastructures)
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Open AccessArticle Dual MIMU Pedestrian Navigation by Inequality Constraint Kalman Filtering
Sensors 2017, 17(2), 427; doi:10.3390/s17020427
Received: 30 November 2016 / Revised: 9 February 2017 / Accepted: 19 February 2017 / Published: 22 February 2017
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Abstract
The foot-mounted inertial navigation system is an important method of pedestrian navigation as it, in principle, does not rely any external assistance. A real-time range decomposition constraint method is proposed in this paper to combine the information of dual foot-mounted inertial navigation systems.
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The foot-mounted inertial navigation system is an important method of pedestrian navigation as it, in principle, does not rely any external assistance. A real-time range decomposition constraint method is proposed in this paper to combine the information of dual foot-mounted inertial navigation systems. It is well known that low-cost inertial pedestrian navigation aided with both ZUPT (zero velocity update) and the range decomposition constraint performs better than those in their own respective methods. This paper recommends that the separation distance between the position estimates of the two foot-mounted inertial navigation systems be restricted by an ellipsoidal constraint that relates to the maximum step length and the leg height. The performance of the proposed method is studied by utilizing experimental data, and the results indicate that the method can effectively correct the dual navigation systems’ position over the traditional spherical constraint. Full article
(This article belongs to the Special Issue System-Integrated Intelligence and Intelligent Systems)
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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
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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
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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 Alternative cDEP Design to Facilitate Cell Isolation for Identification by Raman Spectroscopy
Sensors 2017, 17(2), 327; doi:10.3390/s17020327
Received: 1 December 2016 / Revised: 24 January 2017 / Accepted: 3 February 2017 / Published: 9 February 2017
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Abstract
Dielectrophoresis (DEP) uses non-uniform electric fields to cause motion in particles due to the particles’ intrinsic properties. As such, DEP is a well-suited label-free means for cell sorting. Of the various methods of implementing DEP, contactless dielectrophoresis (cDEP) is advantageous as it avoids
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Dielectrophoresis (DEP) uses non-uniform electric fields to cause motion in particles due to the particles’ intrinsic properties. As such, DEP is a well-suited label-free means for cell sorting. Of the various methods of implementing DEP, contactless dielectrophoresis (cDEP) is advantageous as it avoids common problems associated with DEP, such as electrode fouling and electrolysis. Unfortunately, cDEP devices can be difficult to fabricate, replicate, and reuse. In addition, the operating parameters are limited by the dielectric breakdown of polydimethylsiloxane (PDMS). This study presents an alternative way to fabricate a cDEP device allowing for higher operating voltages, improved replication, and the opportunity for analysis using Raman spectroscopy. In this device, channels were formed in fused silica rather than PDMS. The device successfully trapped 3.3 μm polystyrene spheres for analysis by Raman spectroscopy. The successful implementation indicates the potential to use cDEP to isolate and identify biological samples on a single device. Full article
(This article belongs to the Special Issue Applications of Raman Spectroscopy in Biosensors)
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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
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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
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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 Proof of Concept of Integrated Load Measurement in 3D Printed Structures
Sensors 2017, 17(2), 328; doi:10.3390/s17020328
Received: 24 November 2016 / Revised: 25 January 2017 / Accepted: 5 February 2017 / Published: 9 February 2017
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Abstract
Currently, research on structural health monitoring systems is focused on direct integration of the system into a component or structure. The latter results in a so-called smart structure. One example of a smart structure is a component with integrated strain sensing for continuous
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Currently, research on structural health monitoring systems is focused on direct integration of the system into a component or structure. The latter results in a so-called smart structure. One example of a smart structure is a component with integrated strain sensing for continuous load monitoring. Additive manufacturing, or 3D printing, now also enables such integration of functions inside components. As a proof-of-concept, the Fused Deposition Modeling (FDM) technique was used to integrate a strain sensing element inside polymer (ABS) tensile test samples. The strain sensing element consisted of a closed capillary filled with a fluid and connected to an externally mounted pressure sensor. The volumetric deformation of the integrated capillary resulted in pressure changes in the fluid. The obtained pressure measurements during tensile testing are reported in this paper and compared to state-of-the-art extensometer measurements. The sensitivity of the 3D printed pressure-based strain sensor is primarily a function of the compressibility of the capillary fluid. Air- and watertightness are of critical importance for the proper functioning of the 3D printed pressure-based strain sensor. Therefore, the best after-treatment procedure was selected on basis of a comparative analysis. The obtained pressure measurements are linear with respect to the extensometer readings, and the uncertainty on the strain measurement of a capillary filled with water (incompressible fluid) is ±3.1 µstrain, which is approximately three times less sensitive than conventional strain gauges (±1 µstrain), but 32 times more sensitive than the same sensor based on air (compressible fluid) (±101 µstrain). Full article
(This article belongs to the Special Issue 3D Printed Sensors)
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Open AccessArticle Effect of the Matching Circuit on the Electromechanical Characteristics of Sandwiched Piezoelectric Transducers
Sensors 2017, 17(2), 329; doi:10.3390/s17020329
Received: 30 November 2016 / Revised: 17 January 2017 / Accepted: 25 January 2017 / Published: 10 February 2017
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Abstract
The input electrical impedance behaves as a capacitive when a piezoelectric transducer is excited near its resonance frequency. In order to increase the energy transmission efficiency, a series or parallel inductor should be used to compensate the capacitive impedance of the piezoelectric transducer.
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The input electrical impedance behaves as a capacitive when a piezoelectric transducer is excited near its resonance frequency. In order to increase the energy transmission efficiency, a series or parallel inductor should be used to compensate the capacitive impedance of the piezoelectric transducer. In this paper, the effect of the series matching inductor on the electromechanical characteristics of the piezoelectric transducer is analyzed. The dependency of the resonance/anti-resonance frequency, the effective electromechanical coupling coefficient, the electrical quality factor and the electro-acoustical efficiency on the matching inductor is obtained. It is shown that apart from compensating the capacitive impedance of the piezoelectric transducer, the series matching inductor can also change the electromechanical characteristics of the piezoelectric transducer. When series matching inductor is increased, the resonance frequency is decreased and the anti-resonance unchanged; the effective electromechanical coupling coefficient is increased. For the electrical quality factor and the electroacoustic efficiency, the dependency on the matching inductor is different when the transducer is operated at the resonance and the anti-resonance frequency. The electromechanical characteristics of the piezoelectric transducer with series matching inductor are measured. It is shown that the theoretically predicted relationship between the electromechanical characteristics and the series matching inductor is in good agreement with the experimental results. Full article
(This article belongs to the Special Issue Self-Powered 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
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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 Hybrid Visible Light and Ultrasound-Based Sensor for Distance Estimation
Sensors 2017, 17(2), 330; doi:10.3390/s17020330
Received: 7 December 2016 / Revised: 18 January 2017 / Accepted: 7 February 2017 / Published: 10 February 2017
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Abstract
Distance estimation plays an important role in location-based services, which has become very popular in recent years. In this paper, a new short range cricket sensor-based approach is proposed for indoor location applications. This solution uses Time Difference of Arrival (TDoA) between an
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Distance estimation plays an important role in location-based services, which has become very popular in recent years. In this paper, a new short range cricket sensor-based approach is proposed for indoor location applications. This solution uses Time Difference of Arrival (TDoA) between an optical and an ultrasound signal which are transmitted simultaneously, to estimate the distance from the base station to the mobile receiver. The measurement of the TDoA at the mobile receiver endpoint is proportional to the distance. The use of optical and ultrasound signals instead of the conventional radio wave signal makes the proposed approach suitable for environments with high levels of electromagnetic interference or where the propagation of radio frequencies is entirely restricted. Furthermore, unlike classical cricket systems, a double-way measurement procedure is introduced, allowing both the base station and mobile node to perform distance estimation simultaneously. Full article
(This article belongs to the Special Issue Ultrasonic Sensors)
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