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Sensors, Volume 18, Issue 2 (February 2018)

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Editorial

Jump to: Research, Review, Other

Open AccessEditorial Molecular Imprinting and Functional Polymers for All Transducers and Applications
Sensors 2018, 18(2), 327; doi:10.3390/s18020327
Received: 18 January 2018 / Revised: 22 January 2018 / Accepted: 22 January 2018 / Published: 24 January 2018
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Abstract
The main challenge in developing a chemical sensor is the synthesis of recognition coatings, which are very sensitive and selective to analytes of interest. Molecular imprinting has proven to be the most innovative strategy for this purpose in functional polymer design in the
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The main challenge in developing a chemical sensor is the synthesis of recognition coatings, which are very sensitive and selective to analytes of interest. Molecular imprinting has proven to be the most innovative strategy for this purpose in functional polymer design in the last few decades. Moreover, the introduction of functional groups brings about new applications for all available transducers. Sensitivity and selectivity features of sensor coatings can be tuned by this approach. The strategy produces molecular cavities and interaction sites in sensor coatings. The synthesis of these tailored recognition materials is performed in an outstanding manner, saving time and the high costs of chemicals. Furthermore, intermolecular interactions between the analyte and chemical layers will generate sites that are complementary to the analyte. This procedure can easily be done, directly on a transducer surface, which entails engulfing the analyte by a prepolymer and crosslinking the polymeric material. These imprinted polymers form a robust recognition layer on the transducer surface, which cannot be peeled off and can withstand very harsh conditions, both in gaseous and liquid media. These recognition materials are very suitable, for small molecules and even large bioparticles. Full article

Research

Jump to: Editorial, Review, Other

Open AccessArticle Impact Analysis of Temperature and Humidity Conditions on Electrochemical Sensor Response in Ambient Air Quality Monitoring
Sensors 2018, 18(2), 59; doi:10.3390/s18020059
Received: 23 November 2017 / Revised: 25 December 2017 / Accepted: 28 December 2017 / Published: 23 January 2018
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Abstract
The increasing applications of low-cost air sensors promises more convenient and cost-effective systems for air monitoring in many places and under many conditions. However, the data quality from such systems has not been fully characterized and may not meet user expectations in research
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The increasing applications of low-cost air sensors promises more convenient and cost-effective systems for air monitoring in many places and under many conditions. However, the data quality from such systems has not been fully characterized and may not meet user expectations in research and regulatory uses, or for use in citizen science. In our study, electrochemical sensors (Alphasense B4 series) for carbon monoxide (CO), nitric oxide (NO), nitrogen dioxide (NO2), and oxidants (Ox) were evaluated under controlled laboratory conditions to identify the influencing factors and quantify their relation with sensor outputs. Based on the laboratory tests, we developed different correction methods to compensate for the impact of ambient conditions. Further, the sensors were assembled into a monitoring system and tested in ambient conditions in Hong Kong side-by-side with regulatory reference monitors, and data from these tests were used to evaluate the performance of the models, to refine them, and validate their applicability in variable ambient conditions in the field. The more comprehensive correction models demonstrated enhanced performance when compared with uncorrected data. One over-arching observation of this study is that the low-cost sensors may promise excellent sensitivity and performance, but it is essential for users to understand and account for several key factors that may strongly affect the nature of sensor data. In this paper, we also evaluated factors of multi-month stability, temperature, and humidity, and considered the interaction of oxidant gases NO2 and ozone on a newly introduced oxidant sensor. Full article
(This article belongs to the Special Issue Signal and Information Processing in Chemical Sensing)
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Open AccessArticle Spatial Vertical Directionality and Correlation of Low-Frequency Ambient Noise in Deep Ocean Direct-Arrival Zones
Sensors 2018, 18(2), 319; doi:10.3390/s18020319
Received: 4 November 2017 / Revised: 11 January 2018 / Accepted: 19 January 2018 / Published: 23 January 2018
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Abstract
Wind-driven and distant shipping noise sources contribute to the total noise field in the deep ocean direct-arrival zones. Wind-driven and distant shipping noise sources may significantly and simultaneously affect the spatial characteristics of the total noise field to some extent. In this work,
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Wind-driven and distant shipping noise sources contribute to the total noise field in the deep ocean direct-arrival zones. Wind-driven and distant shipping noise sources may significantly and simultaneously affect the spatial characteristics of the total noise field to some extent. In this work, a ray approach and parabolic equation solution method were jointly utilized to model the low-frequency ambient noise field in a range-dependent deep ocean environment by considering their calculation accuracy and efficiency in near-field wind-driven and far-field distant shipping noise fields. The reanalysis databases of National Center of Environment Prediction (NCEP) and Volunteer Observation System (VOS) were used to model the ambient noise source intensity and distribution. Spatial vertical directionality and correlation were analyzed in three scenarios that correspond to three wind speed conditions. The noise field was dominated by distant shipping noise sources when the wind speed was less than 3 m/s, and then the spatial vertical directionality and vertical correlation of the total noise field were nearly consistent with those of distant shipping noise field. The total noise field was completely dominated by near field wind generated noise sources when the wind speed was greater than 12 m/s at 150 Hz, and then the spatial vertical correlation coefficient and directionality pattern of the total noise field was approximately consistent with that of the wind-driven noise field. The spatial characteristics of the total noise field for wind speeds between 3 m/s and 12 m/s were the weighted results of wind-driven and distant shipping noise fields. Furthermore, the spatial characteristics of low-frequency ambient noise field were compared with the classical Cron/Sherman deep water noise field coherence function. Simulation results with the described modeling method showed good agreement with the experimental measurement results based on the vertical line array deployed near the bottom in deep ocean direct-arrival zones. Full article
(This article belongs to the Special Issue Advances and Challenges in Underwater Sensor Networks)
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Open AccessArticle Data-Driven Packet Loss Estimation for Node Healthy Sensing in Decentralized Cluster
Sensors 2018, 18(2), 320; doi:10.3390/s18020320
Received: 14 November 2017 / Revised: 10 January 2018 / Accepted: 12 January 2018 / Published: 23 January 2018
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Abstract
Decentralized clustering of modern information technology is widely adopted in various fields these years. One of the main reason is the features of high availability and the failure-tolerance which can prevent the entire system form broking down by a failure of a single
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Decentralized clustering of modern information technology is widely adopted in various fields these years. One of the main reason is the features of high availability and the failure-tolerance which can prevent the entire system form broking down by a failure of a single point. Recently, toolkits such as Akka are used by the public commonly to easily build such kind of cluster. However, clusters of such kind that use Gossip as their membership managing protocol and use link failure detecting mechanism to detect link failures cannot deal with the scenario that a node stochastically drops packets and corrupts the member status of the cluster. In this paper, we formulate the problem to be evaluating the link quality and finding a max clique (NP-Complete) in the connectivity graph. We then proposed an algorithm that consists of two models driven by data from application layer to respectively solving these two problems. Through simulations with statistical data and a real-world product, we demonstrate that our algorithm has a good performance. Full article
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Open AccessArticle Simultaneous Event-Triggered Fault Detection and Estimation for Stochastic Systems Subject to Deception Attacks
Sensors 2018, 18(2), 321; doi:10.3390/s18020321
Received: 24 December 2017 / Revised: 19 January 2018 / Accepted: 21 January 2018 / Published: 23 January 2018
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Abstract
In this paper, a synthesized design of fault-detection filter and fault estimator is considered for a class of discrete-time stochastic systems in the framework of event-triggered transmission scheme subject to unknown disturbances and deception attacks. A random variable obeying the Bernoulli distribution is
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In this paper, a synthesized design of fault-detection filter and fault estimator is considered for a class of discrete-time stochastic systems in the framework of event-triggered transmission scheme subject to unknown disturbances and deception attacks. A random variable obeying the Bernoulli distribution is employed to characterize the phenomena of the randomly occurring deception attacks. To achieve a fault-detection residual is only sensitive to faults while robust to disturbances, a coordinate transformation approach is exploited. This approach can transform the considered system into two subsystems and the unknown disturbances are removed from one of the subsystems. The gain of fault-detection filter is derived by minimizing an upper bound of filter error covariance. Meanwhile, system faults can be reconstructed by the remote fault estimator. An recursive approach is developed to obtain fault estimator gains as well as guarantee the fault estimator performance. Furthermore, the corresponding event-triggered sensor data transmission scheme is also presented for improving working-life of the wireless sensor node when measurement information are aperiodically transmitted. Finally, a scaled version of an industrial system consisting of local PC, remote estimator and wireless sensor node is used to experimentally evaluate the proposed theoretical results. In particular, a novel fault-alarming strategy is proposed so that the real-time capacity of fault-detection is guaranteed when the event condition is triggered. Full article
(This article belongs to the Special Issue Sensors for Fault Detection)
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Open AccessArticle A Compact and Low Power RO PUF with High Resilience to the EM Side-Channel Attack and the SVM Modelling Attack of Wireless Sensor Networks
Sensors 2018, 18(2), 322; doi:10.3390/s18020322
Received: 9 December 2017 / Revised: 14 January 2018 / Accepted: 20 January 2018 / Published: 23 January 2018
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Abstract
Authentication is a crucial security service for the wireless sensor networks (WSNs) in versatile domains. The deployment of WSN devices in the untrusted open environment and the resource-constrained nature make the on-chip authentication an open challenge. The strong physical unclonable function (PUF) came
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Authentication is a crucial security service for the wireless sensor networks (WSNs) in versatile domains. The deployment of WSN devices in the untrusted open environment and the resource-constrained nature make the on-chip authentication an open challenge. The strong physical unclonable function (PUF) came in handy as light-weight authentication security primitive. In this paper, we present the first ring oscillator (RO) based strong physical unclonable function (PUF) with high resilience to both the electromagnetic (EM) side-channel attack and the support vector machine (SVM) modelling attack. By employing an RO based PUF architecture with the current starved inverter as the delay cell, the oscillation power is significantly reduced to minimize the emitted EM signal, leading to greatly enhanced immunity to the EM side-channel analysis attack. In addition, featuring superior reconfigurability due to the conspicuously simplified circuitries, the proposed implementation is capable of withstanding the SVM modelling attack by generating and comparing a large number of RO frequency pairs. The reported experimental results validate the prototype of a 9-stage RO PUF fabricated using standard 65 nm complementary-metal-oxide-semiconductor (CMOS) process. Operating at the supply voltage of 1.2 V and the frequency of 100 KHz, the fabricated RO PUF occupies a compact silicon area of 250 μ m 2 and consumes a power as low as 5.16 μ W per challenge-response pair (CRP). Furthermore, the uniqueness and the worst-case reliability are measured to be 50.17% and 98.30% for the working temperature range of −40∼120 C and the supply voltage variation of ±2%, respectively. Thus, the proposed PUF is applicable for the low power, low cost and secure WSN communications. Full article
(This article belongs to the Special Issue Security, Trust and Privacy for Sensor Networks)
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Open AccessArticle Single-Photon Tracking for High-Speed Vision
Sensors 2018, 18(2), 323; doi:10.3390/s18020323
Received: 1 November 2017 / Revised: 8 January 2018 / Accepted: 19 January 2018 / Published: 23 January 2018
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Abstract
Quanta Imager Sensors provide photon detections at high frame rates, with negligible read-out noise, making them ideal for high-speed optical tracking. At the basic level of bit-planes or binary maps of photon detections, objects may present limited detail. However, through motion estimation and
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Quanta Imager Sensors provide photon detections at high frame rates, with negligible read-out noise, making them ideal for high-speed optical tracking. At the basic level of bit-planes or binary maps of photon detections, objects may present limited detail. However, through motion estimation and spatial reassignment of photon detections, the objects can be reconstructed with minimal motion artefacts. We here present the first demonstration of high-speed two-dimensional (2D) tracking and reconstruction of rigid, planar objects with a Quanta Image Sensor, including a demonstration of depth-resolved tracking. Full article
(This article belongs to the Special Issue Special Issue on the 2017 International Image Sensor Workshop (IISW))
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Open AccessArticle An Efficient Direct Position Determination Method for Multiple Strictly Noncircular Sources
Sensors 2018, 18(2), 324; doi:10.3390/s18020324
Received: 5 November 2017 / Revised: 6 December 2017 / Accepted: 19 December 2017 / Published: 23 January 2018
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Abstract
This paper focuses on the localization methods for multiple sources received by widely separated arrays. The conventional two-step methods extract measurement parameters and then estimate the positions from them. In the contrast to the conventional two-step methods, direct position determination (DPD) localizes transmitters
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This paper focuses on the localization methods for multiple sources received by widely separated arrays. The conventional two-step methods extract measurement parameters and then estimate the positions from them. In the contrast to the conventional two-step methods, direct position determination (DPD) localizes transmitters directly from original sensor outputs without estimating intermediate parameters, resulting in higher location accuracy and avoiding the data association. Existing subspace data fusion (SDF)-based DPD developed in the frequency domain is computationally attractive in the presence of multiple transmitters, whereas it does not use special properties of signals. This paper proposes an improved SDF-based DPD algorithm for strictly noncircular sources. We first derive the property of strictly noncircular signals in the frequency domain. On this basis, the observed frequency-domain vectors at all arrays are concatenated and extended by exploiting the noncircular property, producing extended noise subspaces. Fusing the extended noise subspaces of all frequency components and then performing a unitary transformation, we obtain a cost function for each source location, which is formulated as the smallest eigenvalue of a real-valued matrix. To avoid the exhaustive grid search and solve this nonlinear function efficiently, we devise a Newton-type iterative method using matrix Eigen-perturbation theory. Simulation results demonstrate that the proposed DPD using Newton-type iteration substantially reduces the running time, and its performance is superior to other localization methods for both near-field and far-field noncircular sources. Full article
(This article belongs to the Section Physical Sensors)
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Open AccessArticle Performance Evaluation of IEEE 802.11ah Networks With High-Throughput Bidirectional Traffic
Sensors 2018, 18(2), 325; doi:10.3390/s18020325
Received: 3 January 2018 / Revised: 18 January 2018 / Accepted: 19 January 2018 / Published: 23 January 2018
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Abstract
So far, existing sub-GHz wireless communication technologies focused on low-bandwidth, long-range communication with large numbers of constrained devices. Although these characteristics are fine for many Internet of Things (IoT) applications, more demanding application requirements could not be met and legacy Internet technologies such
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So far, existing sub-GHz wireless communication technologies focused on low-bandwidth, long-range communication with large numbers of constrained devices. Although these characteristics are fine for many Internet of Things (IoT) applications, more demanding application requirements could not be met and legacy Internet technologies such as Transmission Control Protocol/Internet Protocol (TCP/IP) could not be used. This has changed with the advent of the new IEEE 802.11ah Wi-Fi standard, which is much more suitable for reliable bidirectional communication and high-throughput applications over a wide area (up to 1 km). The standard offers great possibilities for network performance optimization through a number of physical- and link-layer configurable features. However, given that the optimal configuration parameters depend on traffic patterns, the standard does not dictate how to determine them. Such a large number of configuration options can lead to sub-optimal or even incorrect configurations. Therefore, we investigated how two key mechanisms, Restricted Access Window (RAW) grouping and Traffic Indication Map (TIM) segmentation, influence scalability, throughput, latency and energy efficiency in the presence of bidirectional TCP/IP traffic. We considered both high-throughput video streaming traffic and large-scale reliable sensing traffic and investigated TCP behavior in both scenarios when the link layer introduces long delays. This article presents the relations between attainable throughput per station and attainable number of stations, as well as the influence of RAW, TIM and TCP parameters on both. We found that up to 20 continuously streaming IP-cameras can be reliably connected via IEEE 802.11ah with a maximum average data rate of 160 kbps, whereas 10 IP-cameras can achieve average data rates of up to 255 kbps over 200 m. Up to 6960 stations transmitting every 60 s can be connected over 1 km with no lost packets. The presented results enable the fine tuning of RAW and TIM parameters for throughput-demanding reliable applications (i.e., video streaming, firmware updates) on one hand, and very dense low-throughput reliable networks with bidirectional traffic on the other hand. Full article
(This article belongs to the Section Sensor Networks)
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Open AccessArticle Grasping Force Control for a Robotic Hand by Slip Detection Using Developed Micro Laser Doppler Velocimeter
Sensors 2018, 18(2), 326; doi:10.3390/s18020326
Received: 30 September 2017 / Revised: 16 January 2018 / Accepted: 18 January 2018 / Published: 23 January 2018
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Abstract
The purpose of this paper is to show the feasibility of grasping force control by feeding back signals of the developed micro-laser Doppler velocimeter (μ-LDV) and by discriminating whether a grasped object is slipping or not. LDV is well known as a high
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The purpose of this paper is to show the feasibility of grasping force control by feeding back signals of the developed micro-laser Doppler velocimeter (μ-LDV) and by discriminating whether a grasped object is slipping or not. LDV is well known as a high response surface velocity sensor which can measure various surfaces—such as metal, paper, film, and so on—thus suggesting the potential application of LDV as a slip sensor for grasping various objects. However, the use of LDV as a slip sensor has not yet been reported because the size of LDVs is too large to be installed on a robotic fingertip. We have solved the size problem and enabled the performance of a feasibility test with a few-millimeter-scale LDV referred to as micro-LDV (μ-LDV) by modifying the design which was adopted from MEMS (microelectromechanical systems) fabrication process. In this paper, by applying our developed μ-LDV as a slip sensor, we have successfully demonstrated grasping force control with three target objects—aluminum block, wood block, and white acrylic block—considering that various objects made of these materials can be found in homes and factories, without grasping force feedback. We provide proofs that LDV is a new promising candidate slip sensor for grasping force control to execute target grasping. Full article
(This article belongs to the Special Issue Tactile Sensors and Sensing)
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Open AccessArticle Paper-Based Electrochemical Detection of Chlorate
Sensors 2018, 18(2), 328; doi:10.3390/s18020328
Received: 21 November 2017 / Revised: 12 January 2018 / Accepted: 19 January 2018 / Published: 24 January 2018
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Abstract
We describe the use of a paper-based probe impregnated with a vanadium-containing polyoxometalate anion, [PMo11VO40]5−, on screen-printed carbon electrodes for the electrochemical determination of chlorate. Cyclic voltammetry (CV) and chronocoulometry were used to characterize the ClO3
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We describe the use of a paper-based probe impregnated with a vanadium-containing polyoxometalate anion, [PMo11VO40]5−, on screen-printed carbon electrodes for the electrochemical determination of chlorate. Cyclic voltammetry (CV) and chronocoulometry were used to characterize the ClO3 response in a pH = 2.5 solution of 100 mM sodium acetate. A linear CV current response was observed between 0.156 and 1.25 mg/mL with a detection limit of 0.083 mg/mL (S/N > 3). This performance was reproducible using [PMo11VO40]5−-impregnated filter paper stored under ambient conditions for as long as 8 months prior to use. At high concentration of chlorate, an additional catalytic cathodic peak was seen in the reverse scan of the CVs, which was digitally simulated using a simple model. For chronocoulometry, the charge measured after 5 min gave a linear response from 0.625 to 2.5 mg/mL with a detection limit of 0.31 mg/mL (S/N > 3). In addition, the slope of charge vs. time also gave a linear response. In this case the linear range was from 0.312 to 2.5 mg/mL with a detection limit of 0.15 mg/mL (S/N > 3). Simple assays were conducted using three types of soil, and recovery measurements reported. Full article
(This article belongs to the Special Issue Paper-Based Sensors)
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Open AccessArticle Service Migration from Cloud to Multi-tier Fog Nodes for Multimedia Dissemination with QoE Support
Sensors 2018, 18(2), 329; doi:10.3390/s18020329
Received: 28 November 2017 / Revised: 15 January 2018 / Accepted: 19 January 2018 / Published: 24 January 2018
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Abstract
A wide range of multimedia services is expected to be offered for mobile users via various wireless access networks. Even the integration of Cloud Computing in such networks does not support an adequate Quality of Experience (QoE) in areas with high demands for
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A wide range of multimedia services is expected to be offered for mobile users via various wireless access networks. Even the integration of Cloud Computing in such networks does not support an adequate Quality of Experience (QoE) in areas with high demands for multimedia contents. Fog computing has been conceptualized to facilitate the deployment of new services that cloud computing cannot provide, particularly those demanding QoE guarantees. These services are provided using fog nodes located at the network edge, which is capable of virtualizing their functions/applications. Service migration from the cloud to fog nodes can be actuated by request patterns and the timing issues. To the best of our knowledge, existing works on fog computing focus on architecture and fog node deployment issues. In this article, we describe the operational impacts and benefits associated with service migration from the cloud to multi-tier fog computing for video distribution with QoE support. Besides that, we perform the evaluation of such service migration of video services. Finally, we present potential research challenges and trends. Full article
(This article belongs to the Special Issue New Paradigms in Data Sensing and Processing for Edge Computing)
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Open AccessArticle Secure Transmission of Cooperative Zero-Forcing Jamming for Two-User SWIPT Sensor Networks
Sensors 2018, 18(2), 331; doi:10.3390/s18020331
Received: 3 January 2018 / Revised: 21 January 2018 / Accepted: 22 January 2018 / Published: 24 January 2018
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Abstract
In this paper, the secrecy performance of the two-user simultaneous wireless information and power transfer (SWIPT) sensor networks is studied and a novel secure transmission scheme of cooperative zero-forcing (ZF) jamming is proposed. The two sensors opportunistically conduct the SWIPT and cooperative ZF
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In this paper, the secrecy performance of the two-user simultaneous wireless information and power transfer (SWIPT) sensor networks is studied and a novel secure transmission scheme of cooperative zero-forcing (ZF) jamming is proposed. The two sensors opportunistically conduct the SWIPT and cooperative ZF jamming, respectively, where the energy required for jamming the eavesdropper is provided by the SWIPT operation so as to keep the energy balance at the sensors in the long run. By deriving the exact closed-form expressions of the secrecy outage probability and the secrecy throughout, we provide an effective approach to precisely assess the impacts of key parameters on the secrecy performance of the system. It has been shown that the secrecy outage probability is a monotonically increasing function of the growth of secrecy rate ( R s ), and a monotonically decreasing function of the increase of the transmit signal-to-noise ratio ( γ S ), and energy conversion efficiency ( η ). Furthermore, the secrecy throughput could be enhanced when η increases, which becomes especially obvious when a large γ S is provided. Moreover, the existence of an optimum R s maximizing the secrecy throughput is depicted, which also grows with the increase of γ S . Simulations are provided for the validation of the analysis. Full article
(This article belongs to the Special Issue Sensor Networks for Collaborative and Secure Internet of Things)
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Open AccessArticle Passive Infrared (PIR)-Based Indoor Position Tracking for Smart Homes Using Accessibility Maps and A-Star Algorithm
Sensors 2018, 18(2), 332; doi:10.3390/s18020332
Received: 13 December 2017 / Revised: 16 January 2018 / Accepted: 22 January 2018 / Published: 24 January 2018
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Abstract
Indoor occupants’ positions are significant for smart home service systems, which usually consist of robot service(s), appliance control and other intelligent applications. In this paper, an innovative localization method is proposed for tracking humans’ position in indoor environments based on passive infrared (PIR)
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Indoor occupants’ positions are significant for smart home service systems, which usually consist of robot service(s), appliance control and other intelligent applications. In this paper, an innovative localization method is proposed for tracking humans’ position in indoor environments based on passive infrared (PIR) sensors using an accessibility map and an A-star algorithm, aiming at providing intelligent services. First the accessibility map reflecting the visiting habits of the occupants is established through the integral training with indoor environments and other prior knowledge. Then the PIR sensors, which placement depends on the training results in the accessibility map, get the rough location information. For more precise positioning, the A-start algorithm is used to refine the localization, fused with the accessibility map and the PIR sensor data. Experiments were conducted in a mock apartment testbed. The ground truth data was obtained from an Opti-track system. The results demonstrate that the proposed method is able to track persons in a smart home environment and provide a solution for home robot localization. Full article
(This article belongs to the Special Issue Smart Homes)
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Open AccessArticle A Novel Event-Based Incipient Slip Detection Using Dynamic Active-Pixel Vision Sensor (DAVIS)
Sensors 2018, 18(2), 333; doi:10.3390/s18020333
Received: 28 November 2017 / Revised: 19 January 2018 / Accepted: 22 January 2018 / Published: 24 January 2018
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Abstract
In this paper, a novel approach to detect incipient slip based on the contact area between a transparent silicone medium and different objects using a neuromorphic event-based vision sensor (DAVIS) is proposed. Event-based algorithms are developed to detect incipient slip, slip, stress distribution
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In this paper, a novel approach to detect incipient slip based on the contact area between a transparent silicone medium and different objects using a neuromorphic event-based vision sensor (DAVIS) is proposed. Event-based algorithms are developed to detect incipient slip, slip, stress distribution and object vibration. Thirty-seven experiments were performed on five objects with different sizes, shapes, materials and weights to compare precision and response time of the proposed approach. The proposed approach is validated by using a high speed constitutional camera (1000 FPS). The results indicate that the sensor can detect incipient slippage with an average of 44.1 ms latency in unstructured environment for various objects. It is worth mentioning that the experiments were conducted in an uncontrolled experimental environment, therefore adding high noise levels that affected results significantly. However, eleven of the experiments had a detection latency below 10 ms which shows the capability of this method. The results are very promising and show a high potential of the sensor being used for manipulation applications especially in dynamic environments. Full article
(This article belongs to the Special Issue Smart Sensors for Mechatronic and Robotic Systems)
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Open AccessArticle Ship Detection in Gaofen-3 SAR Images Based on Sea Clutter Distribution Analysis and Deep Convolutional Neural Network
Sensors 2018, 18(2), 334; doi:10.3390/s18020334
Received: 11 December 2017 / Revised: 22 January 2018 / Accepted: 22 January 2018 / Published: 24 January 2018
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Abstract
Target detection is one of the important applications in the field of remote sensing. The Gaofen-3 (GF-3) Synthetic Aperture Radar (SAR) satellite launched by China is a powerful tool for maritime monitoring. This work aims at detecting ships in GF-3 SAR images using
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Target detection is one of the important applications in the field of remote sensing. The Gaofen-3 (GF-3) Synthetic Aperture Radar (SAR) satellite launched by China is a powerful tool for maritime monitoring. This work aims at detecting ships in GF-3 SAR images using a new land masking strategy, the appropriate model for sea clutter and a neural network as the discrimination scheme. Firstly, the fully convolutional network (FCN) is applied to separate the sea from the land. Then, by analyzing the sea clutter distribution in GF-3 SAR images, we choose the probability distribution model of Constant False Alarm Rate (CFAR) detector from K-distribution, Gamma distribution and Rayleigh distribution based on a tradeoff between the sea clutter modeling accuracy and the computational complexity. Furthermore, in order to better implement CFAR detection, we also use truncated statistic (TS) as a preprocessing scheme and iterative censoring scheme (ICS) for boosting the performance of detector. Finally, we employ a neural network to re-examine the results as the discrimination stage. Experiment results on three GF-3 SAR images verify the effectiveness and efficiency of this approach. Full article
(This article belongs to the Special Issue First Experiences with Chinese Gaofen-3 SAR Sensor)
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Open AccessArticle An EEG-Based Person Authentication System with Open-Set Capability Combining Eye Blinking Signals
Sensors 2018, 18(2), 335; doi:10.3390/s18020335
Received: 30 November 2017 / Revised: 20 January 2018 / Accepted: 21 January 2018 / Published: 24 January 2018
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Abstract
The electroencephalogram (EEG) signal represents a subject’s specific brain activity patterns and is considered as an ideal biometric given its superior forgery prevention. However, the accuracy and stability of the current EEG-based person authentication systems are still unsatisfactory in practical application. In this
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The electroencephalogram (EEG) signal represents a subject’s specific brain activity patterns and is considered as an ideal biometric given its superior forgery prevention. However, the accuracy and stability of the current EEG-based person authentication systems are still unsatisfactory in practical application. In this paper, a multi-task EEG-based person authentication system combining eye blinking is proposed, which can achieve high precision and robustness. Firstly, we design a novel EEG-based biometric evoked paradigm using self- or non-self-face rapid serial visual presentation (RSVP). The designed paradigm could obtain a distinct and stable biometric trait from EEG with a lower time cost. Secondly, the event-related potential (ERP) features and morphological features are extracted from EEG signals and eye blinking signals, respectively. Thirdly, convolutional neural network and back propagation neural network are severally designed to gain the score estimation of EEG features and eye blinking features. Finally, a score fusion technology based on least square method is proposed to get the final estimation score. The performance of multi-task authentication system is improved significantly compared to the system using EEG only, with an increasing average accuracy from 92.4% to 97.6%. Moreover, open-set authentication tests for additional imposters and permanence tests for users are conducted to simulate the practical scenarios, which have never been employed in previous EEG-based person authentication systems. A mean false accepted rate (FAR) of 3.90% and a mean false rejected rate (FRR) of 3.87% are accomplished in open-set authentication tests and permanence tests, respectively, which illustrate the open-set authentication and permanence capability of our systems. Full article
(This article belongs to the Special Issue Sensor Signal and Information Processing)
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Open AccessArticle Sensing Performance Analysis on Quartz Tuning Fork-Probe at the High Order Vibration Mode for Multi-Frequency Scanning Probe Microscopy
Sensors 2018, 18(2), 336; doi:10.3390/s18020336
Received: 1 December 2017 / Revised: 12 January 2018 / Accepted: 19 January 2018 / Published: 24 January 2018
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Abstract
Multi-frequency scanning near-field optical microscopy, based on a quartz tuning fork-probe (QTF-p) sensor using the first two orders of in-plane bending symmetrical vibration modes, has recently been developed. This method can simultaneously achieve positional feedback (based on the 1st in-plane mode called the
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Multi-frequency scanning near-field optical microscopy, based on a quartz tuning fork-probe (QTF-p) sensor using the first two orders of in-plane bending symmetrical vibration modes, has recently been developed. This method can simultaneously achieve positional feedback (based on the 1st in-plane mode called the low mode) and detect near-field optically induced forces (based on the 2nd in-plane mode called the high mode). Particularly, the high mode sensing performance of the QTF-p is an important issue for characterizing the tip-sample interactions and achieving higher resolution microscopic imaging but the related researches are insufficient. Here, we investigate the vibration performance of QTF-p at high mode based on the experiment and finite element method. The frequency spectrum characteristics are obtained by our homemade laser Doppler vibrometer system. The effects of the properties of the connecting glue layer and the probe features on the dynamic response of the QTF-p sensor at the high mode are investigated for optimization design. Finally, compared with the low mode, an obvious improvement of quality factor, of almost 50%, is obtained at the high mode. Meanwhile, the QTF-p sensor has a high force sensing sensitivity and a large sensing range at the high mode, indicating a broad application prospect for force sensing. Full article
(This article belongs to the Special Issue Piezoelectric Micro- and Nano-Devices)
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Open AccessArticle New Fault Recognition Method for Rotary Machinery Based on Information Entropy and a Probabilistic Neural Network
Sensors 2018, 18(2), 337; doi:10.3390/s18020337
Received: 30 November 2017 / Revised: 12 January 2018 / Accepted: 22 January 2018 / Published: 24 January 2018
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Abstract
Feature recognition and fault diagnosis plays an important role in equipment safety and stable operation of rotating machinery. In order to cope with the complexity problem of the vibration signal of rotating machinery, a feature fusion model based on information entropy and probabilistic
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Feature recognition and fault diagnosis plays an important role in equipment safety and stable operation of rotating machinery. In order to cope with the complexity problem of the vibration signal of rotating machinery, a feature fusion model based on information entropy and probabilistic neural network is proposed in this paper. The new method first uses information entropy theory to extract three kinds of characteristics entropy in vibration signals, namely, singular spectrum entropy, power spectrum entropy, and approximate entropy. Then the feature fusion model is constructed to classify and diagnose the fault signals. The proposed approach can combine comprehensive information from different aspects and is more sensitive to the fault features. The experimental results on simulated fault signals verified better performances of our proposed approach. In real two-span rotor data, the fault detection accuracy of the new method is more than 10% higher compared with the methods using three kinds of information entropy separately. The new approach is proved to be an effective fault recognition method for rotating machinery. Full article
(This article belongs to the Special Issue Sensors for Fault Detection)
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Open AccessArticle Monitoring of Bridges by a Laser Pointer: Dynamic Measurement of Support Rotations and Elastic Line Displacements: Methodology and First Test
Sensors 2018, 18(2), 338; doi:10.3390/s18020338
Received: 8 December 2017 / Revised: 21 January 2018 / Accepted: 23 January 2018 / Published: 25 January 2018
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Abstract
Deck inclination and vertical displacements are among the most important technical parameters to evaluate the health status of a bridge and to verify its bearing capacity. Several methods, both conventional and innovative, are used for structural rotations and displacement monitoring; however, none of
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Deck inclination and vertical displacements are among the most important technical parameters to evaluate the health status of a bridge and to verify its bearing capacity. Several methods, both conventional and innovative, are used for structural rotations and displacement monitoring; however, none of these allow, at the same time, precision, automation, static and dynamic monitoring without using high cost instrumentation. The proposed system uses a common laser pointer and image processing. The elastic line inclination is measured by analyzing the single frames of an HD video of the laser beam imprint projected on a flat target. For the image processing, a code was developed in Matlab® that provides instantaneous rotation and displacement of a bridge, charged by a mobile load. An important feature is the synchronization of the load positioning, obtained by a GNSS receiver or by a video. After the calibration procedures, a test was carried out during the movements of a heavy truck maneuvering on a bridge. Data acquisition synchronization allowed us to relate the position of the truck on the deck to inclination and displacements. The inclination of the elastic line at the support was obtained with a precision of 0.01 mrad. The results demonstrate the suitability of the method for dynamic load tests, and the control and monitoring of bridges. Full article
(This article belongs to the Section Remote Sensors)
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Open AccessArticle Low Power Operation of Temperature-Modulated Metal Oxide Semiconductor Gas Sensors
Sensors 2018, 18(2), 339; doi:10.3390/s18020339
Received: 27 December 2017 / Revised: 17 January 2018 / Accepted: 23 January 2018 / Published: 25 January 2018
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Abstract
Mobile applications based on gas sensing present new opportunities for low-cost air quality monitoring, safety, and healthcare. Metal oxide semiconductor (MOX) gas sensors represent the most prominent technology for integration into portable devices, such as smartphones and wearables. Traditionally, MOX sensors have been
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Mobile applications based on gas sensing present new opportunities for low-cost air quality monitoring, safety, and healthcare. Metal oxide semiconductor (MOX) gas sensors represent the most prominent technology for integration into portable devices, such as smartphones and wearables. Traditionally, MOX sensors have been continuously powered to increase the stability of the sensing layer. However, continuous power is not feasible in many battery-operated applications due to power consumption limitations or the intended intermittent device operation. This work benchmarks two low-power, duty-cycling, and on-demand modes against the continuous power one. The duty-cycling mode periodically turns the sensors on and off and represents a trade-off between power consumption and stability. On-demand operation achieves the lowest power consumption by powering the sensors only while taking a measurement. Twelve thermally modulated SB-500-12 (FIS Inc. Jacksonville, FL, USA) sensors were exposed to low concentrations of carbon monoxide (0–9 ppm) with environmental conditions, such as ambient humidity (15–75% relative humidity) and temperature (21–27 °C), varying within the indicated ranges. Partial Least Squares (PLS) models were built using calibration data, and the prediction error in external validation samples was evaluated during the two weeks following calibration. We found that on-demand operation produced a deformation of the sensor conductance patterns, which led to an increase in the prediction error by almost a factor of 5 as compared to continuous operation (2.2 versus 0.45 ppm). Applying a 10% duty-cycling operation of 10-min periods reduced this prediction error to a factor of 2 (0.9 versus 0.45 ppm). The proposed duty-cycling powering scheme saved up to 90% energy as compared to the continuous operating mode. This low-power mode may be advantageous for applications that do not require continuous and periodic measurements, and which can tolerate slightly higher prediction errors. Full article
(This article belongs to the Special Issue Signal and Information Processing in Chemical Sensing)
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Open AccessArticle Fabrications and Performance of Wireless LC Pressure Sensors through LTCC Technology
Sensors 2018, 18(2), 340; doi:10.3390/s18020340
Received: 17 December 2017 / Revised: 12 January 2018 / Accepted: 15 January 2018 / Published: 25 January 2018
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Abstract
This paper presents a kind of passive wireless pressure sensor comprised of a planar spiral inductor and a cavity parallel plate capacitor fabricated through low-temperature co-fired ceramic (LTCC) technology. The LTCC material with a low Young’s modulus of ~65 GPa prepared by our
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This paper presents a kind of passive wireless pressure sensor comprised of a planar spiral inductor and a cavity parallel plate capacitor fabricated through low-temperature co-fired ceramic (LTCC) technology. The LTCC material with a low Young’s modulus of ~65 GPa prepared by our laboratory was used to obtain high sensitivity. A three-step lamination process was applied to construct a high quality cavity structure without using any sacrificial materials. The effects of the thickness of the sensing membranes on the sensitivity and detection range of the pressure sensors were investigated. The sensor with a 148 μm sensing membrane showed the highest sensitivity of 3.76 kHz/kPa, and the sensor with a 432 μm sensing membrane presented a high detection limit of 2660 kPa. The tunable sensitivity and detection limit of the wireless pressure sensors can meet the requirements of different scenes. Full article
(This article belongs to the Section Physical Sensors)
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Open AccessArticle A Novel Loss Recovery and Tracking Scheme for Maneuvering Target in Hybrid WSNs
Sensors 2018, 18(2), 341; doi:10.3390/s18020341
Received: 26 December 2017 / Revised: 18 January 2018 / Accepted: 23 January 2018 / Published: 25 January 2018
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Abstract
Tracking a mobile target, which aims to timely monitor the invasion of specific target, is one of the most prominent applications in wireless sensor networks (WSNs). Traditional tracking methods in WSNs only based on static sensor nodes (SNs) have several critical problems. For
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Tracking a mobile target, which aims to timely monitor the invasion of specific target, is one of the most prominent applications in wireless sensor networks (WSNs). Traditional tracking methods in WSNs only based on static sensor nodes (SNs) have several critical problems. For example, to void the loss of mobile target, many SNs must be active to track the target in all possible directions, resulting in excessive energy consumption. Additionally, when entering coverage holes in the monitoring area, the mobile target may be missing and then its state is unknown during this period. To tackle these problems, in this paper, a few mobile sensor nodes (MNs) are introduced to cooperate with SNs to form a hybrid WSN due to their stronger abilities and less constrained energy. Then, we propose a valid target tracking scheme for hybrid WSNs to dynamically schedule the MNs and SNs. Moreover, a novel loss recovery mechanism is proposed to find the lost target and recover the tracking with fewer SNs awakened. Furthermore, to improve the robustness and accuracy of the recovery mechanism, an adaptive unscented Kalman filter (AUKF) algorithm is raised to dynamically adjust the process noise covariance. Simulation results demonstrate that our tracking scheme for maneuvering target in hybrid WSNs can not only track the target effectively even if the target is lost but also maintain an excellent accuracy and robustness with fewer activated nodes. Full article
(This article belongs to the Section Sensor Networks)
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Open AccessArticle Preliminary Results of a New Auxiliary Mechatronic Near-Field Radar System to 3D Mammography for Early Detection of Breast Cancer
Sensors 2018, 18(2), 342; doi:10.3390/s18020342
Received: 3 November 2017 / Revised: 20 December 2017 / Accepted: 30 December 2017 / Published: 25 January 2018
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Abstract
Accurate and early detection of breast cancer is of high importance, as it is directly associated with the patients’ overall well-being during treatment and their chances of survival. Uncertainties in current breast imaging methods can potentially cause two main problems: (1) missing newly
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Accurate and early detection of breast cancer is of high importance, as it is directly associated with the patients’ overall well-being during treatment and their chances of survival. Uncertainties in current breast imaging methods can potentially cause two main problems: (1) missing newly formed or small tumors; and (2) false alarms, which could be a source of stress for patients. A recent study at the Massachusetts General Hospital (MGH) indicates that using Digital Breast Tomosynthesis (DBT) can reduce the number of false alarms, when compared to conventional mammography. Despite the image quality enhancement DBT provides, the accurate detection of cancerous masses is still limited by low radiological contrast (about 1%) between the fibro-glandular tissue and affected tissue at X-ray frequencies. In a lower frequency region, at microwave frequencies, the contrast is comparatively higher (about 10%) between the aforementioned tissues; yet, microwave imaging suffers from low spatial resolution. This work reviews conventional X-ray breast imaging and describes the preliminary results of a novel near-field radar imaging mechatronic system (NRIMS) that can be fused with the DBT, in a co-registered fashion, to combine the advantages of both modalities. The NRIMS consists of two antipodal Vivaldi antennas, an XY positioner, and an ethanol container, all of which are particularly designed based on the DBT physical specifications. In this paper, the independent performance of the NRIMS is assessed by (1) imaging a bearing ball immersed in sunflower oil and (2) computing the heat Specific Absorption Rate (SAR) due to the electromagnetic power transmitted into the breast. The preliminary results demonstrate that the system is capable of generating images of the ball. Furthermore, the SAR results show that the system complies with the standards set for human trials. As a result, a configuration based on this design might be suitable for use in realistic clinical applications. Full article
(This article belongs to the Section State-of-the-Art Sensors Technologies)
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Open AccessArticle Dual-Mode Gas Sensor Composed of a Silicon Nanoribbon Field Effect Transistor and a Bulk Acoustic Wave Resonator: A Case Study in Freons
Sensors 2018, 18(2), 343; doi:10.3390/s18020343
Received: 27 December 2017 / Revised: 14 January 2018 / Accepted: 14 January 2018 / Published: 25 January 2018
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Abstract
In this paper, we develop a novel dual-mode gas sensor system which comprises a silicon nanoribbon field effect transistor (Si-NR FET) and a film bulk acoustic resonator (FBAR). We investigate their sensing characteristics using polar and nonpolar organic compounds, and demonstrate that polarity
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In this paper, we develop a novel dual-mode gas sensor system which comprises a silicon nanoribbon field effect transistor (Si-NR FET) and a film bulk acoustic resonator (FBAR). We investigate their sensing characteristics using polar and nonpolar organic compounds, and demonstrate that polarity has a significant effect on the response of the Si-NR FET sensor, and only a minor effect on the FBAR sensor. In this dual-mode system, qualitative discrimination can be achieved by analyzing polarity with the Si-NR FET and quantitative concentration information can be obtained using a polymer-coated FBAR with a detection limit at the ppm level. The complementary performance of the sensing elements provides higher analytical efficiency. Additionally, a dual mixture of two types of freons (CFC-113 and HCFC-141b) is further analyzed with the dual-mode gas sensor. Owing to the small size and complementary metal-oxide semiconductor (CMOS)-compatibility of the system, the dual-mode gas sensor shows potential as a portable integrated sensing system for the analysis of gas mixtures in the future. Full article
(This article belongs to the Section Chemical Sensors)
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Open AccessArticle A Novel Noncircular MUSIC Algorithm Based on the Concept of the Difference and Sum Coarray
Sensors 2018, 18(2), 344; doi:10.3390/s18020344
Received: 15 December 2017 / Revised: 17 January 2018 / Accepted: 22 January 2018 / Published: 25 January 2018
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Abstract
In this paper, we propose a vectorized noncircular MUSIC (VNCM) algorithm based on the concept of the coarray, which can construct the difference and sum (diff–sum) coarray, for direction finding of the noncircular (NC) quasi-stationary sources. Utilizing both the NC property and the
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In this paper, we propose a vectorized noncircular MUSIC (VNCM) algorithm based on the concept of the coarray, which can construct the difference and sum (diff–sum) coarray, for direction finding of the noncircular (NC) quasi-stationary sources. Utilizing both the NC property and the concept of the Khatri–Rao product, the proposed method can be applied to not only the ULA but also sparse arrays. In addition, we utilize the quasi-stationary characteristic instead of the spatial smoothing method to solve the coherent issue generated by the Khatri–Rao product operation so that the available degree of freedom (DOF) of the constructed virtual array will not be reduced by half. Compared with the traditional NC virtual array obtained in the NC MUSIC method, the diff–sum coarray achieves a higher number of DOFs as it comprises both the difference set and the sum set. Due to the complementarity between the difference set and the sum set for the coprime array, we choose the coprime array with multiperiod subarrays (CAMpS) as the array model and summarize the properties of the corresponding diff–sum coarray. Furthermore, we develop a diff–sum coprime array with multiperiod subarrays (DsCAMpS) whose diff–sum coarray has a higher DOF. Simulation results validate the effectiveness of the proposed method and the high DOF of the diff–sum coarray. Full article
(This article belongs to the Section Physical Sensors)
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Open AccessArticle Three-Dimensional Blood Vessel Model with Temperature-Indicating Function for Evaluation of Thermal Damage during Surgery
Sensors 2018, 18(2), 345; doi:10.3390/s18020345
Received: 21 December 2017 / Revised: 20 January 2018 / Accepted: 23 January 2018 / Published: 25 January 2018
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Abstract
Surgical simulators have recently attracted attention because they enable the evaluation of the surgical skills of medical doctors and the performance of medical devices. However, thermal damage to the human body during surgery is difficult to evaluate using conventional surgical simulators. In this
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Surgical simulators have recently attracted attention because they enable the evaluation of the surgical skills of medical doctors and the performance of medical devices. However, thermal damage to the human body during surgery is difficult to evaluate using conventional surgical simulators. In this study, we propose a functional surgical model with a temperature-indicating function for the evaluation of thermal damage during surgery. The simulator is made of a composite material of polydimethylsiloxane and a thermochromic dye, which produces an irreversible color change as the temperature increases. Using this material, we fabricated a three-dimensional blood vessel model using the lost-wax process. We succeeded in fabricating a renal vessel model for simulation of catheter ablation. Increases in the temperature of the materials can be measured by image analysis of their color change. The maximum measurement error of the temperature was approximately −1.6 °C/+2.4 °C within the range of 60 °C to 100 °C. Full article
(This article belongs to the Special Issue Non-Invasive Biomedical Sensors)
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Open AccessArticle A Novel Single-Axis MEMS Tilt Sensor with a High Sensitivity in the Measurement Range from 0 to 360
Sensors 2018, 18(2), 346; doi:10.3390/s18020346
Received: 16 November 2017 / Revised: 18 January 2018 / Accepted: 19 January 2018 / Published: 25 January 2018
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Abstract
In this paper, a novel single-axis MEMS tilt sensor is presented. It contains a hexagonal proof mass, six micro-lever force amplifiers and three double-ended-tuning fork (DETF) resonant strain gauges. The proof mass is placed in the center with the micro-levers and the DETFs
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In this paper, a novel single-axis MEMS tilt sensor is presented. It contains a hexagonal proof mass, six micro-lever force amplifiers and three double-ended-tuning fork (DETF) resonant strain gauges. The proof mass is placed in the center with the micro-levers and the DETFs radially arrayed around. The variation of gravity acceleration applied on the proof mass will result in frequency shifts of the DETFs. Angular tilt can be got by analyzing the frequency outputs. The structural design of the tilt sensor is optimized by finite element simulation and the device is microfabricated using a silicon-on-insulator process, followed by open-loop and closed-loop characterizations. Results show that the scale factor of such sensor is at least 11.53 Hz/degree. Minimum Allan deviation of the DETF oscillator is 220 ppb (parts per billion) of the resonant frequency for an 5 s integration time. Resolution of the tilt sensor is 0.002 in the whole measurement range from 0 to 360 . Full article
(This article belongs to the Special Issue Smart Sensors for Mechatronic and Robotic Systems)
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Open AccessArticle VLSI Design of Trusted Virtual Sensors
Sensors 2018, 18(2), 347; doi:10.3390/s18020347
Received: 30 December 2017 / Revised: 20 January 2018 / Accepted: 22 January 2018 / Published: 25 January 2018
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Abstract
This work presents a Very Large Scale Integration (VLSI) design of trusted virtual sensors providing a minimum unitary cost and very good figures of size, speed and power consumption. The sensed variable is estimated by a virtual sensor based on a configurable and
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This work presents a Very Large Scale Integration (VLSI) design of trusted virtual sensors providing a minimum unitary cost and very good figures of size, speed and power consumption. The sensed variable is estimated by a virtual sensor based on a configurable and programmable PieceWise-Affine hyper-Rectangular (PWAR) model. An algorithm is presented to find the best values of the programmable parameters given a set of (empirical or simulated) input-output data. The VLSI design of the trusted virtual sensor uses the fast authenticated encryption algorithm, AEGIS, to ensure the integrity of the provided virtual measurement and to encrypt it, and a Physical Unclonable Function (PUF) based on a Static Random Access Memory (SRAM) to ensure the integrity of the sensor itself. Implementation results of a prototype designed in a 90-nm Complementary Metal Oxide Semiconductor (CMOS) technology show that the active silicon area of the trusted virtual sensor is 0.86 mm 2 and its power consumption when trusted sensing at 50 MHz is 7.12 mW. The maximum operation frequency is 85 MHz, which allows response times lower than 0.25 μ s. As application example, the designed prototype was programmed to estimate the yaw rate in a vehicle, obtaining root mean square errors lower than 1.1%. Experimental results of the employed PUF show the robustness of the trusted sensing against aging and variations of the operation conditions, namely, temperature and power supply voltage (final value as well as ramp-up time). Full article
(This article belongs to the Special Issue State-of-the-Art Sensors Technology in Spain 2017)
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Open AccessArticle High Frequency Data Acquisition System for Modelling the Impact of Visitors on the Thermo-Hygrometric Conditions of Archaeological Sites: A Casa di Diana (Ostia Antica, Italy) Case Study
Sensors 2018, 18(2), 348; doi:10.3390/s18020348
Received: 2 January 2018 / Revised: 20 January 2018 / Accepted: 21 January 2018 / Published: 25 January 2018
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Abstract
The characterization of the microclimatic conditions is fundamental for the preventive conservation of archaeological sites. In this context, the identification of the factors that influence the thermo-hygrometric equilibrium is key to determine the causes of cultural heritage deterioration. In this work, a characterization
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The characterization of the microclimatic conditions is fundamental for the preventive conservation of archaeological sites. In this context, the identification of the factors that influence the thermo-hygrometric equilibrium is key to determine the causes of cultural heritage deterioration. In this work, a characterization of the thermo-hygrometric conditions of Casa di Diana (Ostia Antica, Italy) is carried out analyzing the data of temperature and relative humidity recorded by a system of sensors with high monitoring frequency. Sensors are installed in parallel, calibrated and synchronized with a microcontroller. A data set of 793,620 data, arranged in a matrix with 66,135 rows and 12 columns, was used. Furthermore, the influence of human impact (visitors) is evaluated through a multiple linear regression model and a logistic regression model. The visitors do not affect the environmental humidity as it is very high and constant all the year. The results show a significant influence of the visitors in the upset of the thermal balance. When a tourist guide takes place, the probability that the hourly temperature variation reaches values higher than its monthly average is 10.64 times higher than it remains equal or less to its monthly average. The analysis of the regression residuals shows the influence of outdoor climatic variables in the thermal balance, such as solar radiation or ventilation. Full article
(This article belongs to the Special Issue State-of-the-Art Sensors Technology in Spain 2017)
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Open AccessArticle Development of Low Parasitic Light Sensitivity and Low Dark Current 2.8 μm Global Shutter Pixel
Sensors 2018, 18(2), 349; doi:10.3390/s18020349
Received: 31 October 2017 / Revised: 22 January 2018 / Accepted: 23 January 2018 / Published: 25 January 2018
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Abstract
We developed a low parasitic light sensitivity (PLS) and low dark current 2.8 μm global shutter pixel. We propose a new inner lens design concept to realize both low PLS and high quantum efficiency (QE). 1/PLS is 7700 and QE is 62% at
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We developed a low parasitic light sensitivity (PLS) and low dark current 2.8 μm global shutter pixel. We propose a new inner lens design concept to realize both low PLS and high quantum efficiency (QE). 1/PLS is 7700 and QE is 62% at a wavelength of 530 nm. We also propose a new storage-gate based memory node for low dark current. P-type implants and negative gate biasing are introduced to suppress dark current at the surface of the memory node. This memory node structure shows the world smallest dark current of 9.5 e/s at 60 °C. Full article
(This article belongs to the Special Issue Special Issue on the 2017 International Image Sensor Workshop (IISW))
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Open AccessArticle Control of the Singular Points Location for Miniature Switches with Magnetically Driven Contacts
Sensors 2018, 18(2), 350; doi:10.3390/s18020350
Received: 26 December 2017 / Revised: 19 January 2018 / Accepted: 21 January 2018 / Published: 26 January 2018
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Abstract
This paper presents and discusses usefulness and possibility of control of the singular points location of a driving magnetic field under as structure considerations as well as selection of energizing magnet systems for miniature electromagnetic switches. The sample results of theoretical analysis and
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This paper presents and discusses usefulness and possibility of control of the singular points location of a driving magnetic field under as structure considerations as well as selection of energizing magnet systems for miniature electromagnetic switches. The sample results of theoretical analysis and experimental testing concern selected reed switches with normally open contacts as well as a developed miniature switch with a metallic ball contact. It must be noted that the switch with the contact performed by means of the metallic tiny ball can be effectively used both as a change-over switch as well as a detector of the energizing magnetic field distribution under designing and assembling of any electromagnetic contact device preferably with an increased degree of integration and miniaturization. Full article
(This article belongs to the Special Issue Small Devices and the High-Tech Society)
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Open AccessArticle A Novel Inverse Solution of Contact Force Based on a Sparse Tactile Sensor Array
Sensors 2018, 18(2), 351; doi:10.3390/s18020351
Received: 27 December 2017 / Revised: 23 January 2018 / Accepted: 23 January 2018 / Published: 26 January 2018
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Abstract
High-density tactile sensing has been pursued for humanoid robotic hands to obtain contact force information while the elastomer skin cover is traditionally considered to impair the force discrimination. In this work, we try to utilize the diffusion effect of the elastomer cover to
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High-density tactile sensing has been pursued for humanoid robotic hands to obtain contact force information while the elastomer skin cover is traditionally considered to impair the force discrimination. In this work, we try to utilize the diffusion effect of the elastomer cover to identify an arbitrary contact force load just based on a sparse tactile sensor array. By numerical analysis, we proved the monotonous relation between the Pearson’s correlation coefficient and the relative distance of two single-force loads. Then, we meshed the elastomer surface and conducted the calibration load process to establish the calibration database of the sensing outputs. Afterwards, we applied the correlation method to the database and the sensing output of the unknown load to determine its location and intensity. For validation tests of the proposed method, we designed and fabricated a 3 × 3 sparse tactile sensor array with flat elastomer cover and established an automatic three-axis loading system. The validation tests were implemented including 100 random points with force intensity ranging from 0.1 to 1 N. The test results show that the method has good accuracy of detecting force load with the mean location error of 0.46 mm and the mean intensity error of 0.043 N, which meets the basic requirements of tactile sensing. Therefore, it is feasible for the sparse tactile sensor array to realize high-density load detection. Full article
(This article belongs to the Section Physical Sensors)
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Open AccessArticle Microservices in Web Objects Enabled IoT Environment for Enhancing Reusability
Sensors 2018, 18(2), 352; doi:10.3390/s18020352
Received: 15 December 2017 / Revised: 18 January 2018 / Accepted: 24 January 2018 / Published: 26 January 2018
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Abstract
In the ubiquitous Internet of Things (IoT) environment, reusing objects instead of creating new one has become important in academics and industries. The situation becomes complex due to the availability of a huge number of connected IoT objects, and each individual service creates
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In the ubiquitous Internet of Things (IoT) environment, reusing objects instead of creating new one has become important in academics and industries. The situation becomes complex due to the availability of a huge number of connected IoT objects, and each individual service creates a new object instead of reusing the existing one to fulfill a requirement. A well-standard mechanism not only improves the reusability of objects but also improves service modularity and extensibility, and reduces cost. Web Objects enabled IoT environment applies the principle of reusability of objects in multiple IoT application domains through central objects repository and microservices. To reuse objects with microservices and to maintain a relationship with them, this study presents an architecture of Web of Objects platform. In the case of a similar request for an object, the already instantiated object that exists in the same or from other domain can be reused. Reuse of objects through microservices avoids duplications, and reduces time to search and instantiate them from their registries. Further, this article presents an algorithm for microservices and related objects discovery that considers the reusability of objects through the central objects repository. To support the reusability of objects, the necessary algorithm for objects matching is also presented. To realize the reusability of objects in Web Objects enabled IoT environment, a prototype has been designed and implemented based on a use case scenario. Finally, the results of the prototype have been analyzed and discussed to validate the proposed approach. Full article
(This article belongs to the Section Sensor Networks)
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Open AccessCommunication A Proposal for IoT Dynamic Routes Selection Based on Contextual Information
Sensors 2018, 18(2), 353; doi:10.3390/s18020353
Received: 5 December 2017 / Revised: 19 January 2018 / Accepted: 23 January 2018 / Published: 26 January 2018
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Abstract
The Internet of Things (IoT) is based on interconnection of intelligent and addressable devices, allowing their autonomy and proactive behavior with Internet connectivity. Data dissemination in IoT usually depends on the application and requires context-aware routing protocols that must include auto-configuration features (which
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The Internet of Things (IoT) is based on interconnection of intelligent and addressable devices, allowing their autonomy and proactive behavior with Internet connectivity. Data dissemination in IoT usually depends on the application and requires context-aware routing protocols that must include auto-configuration features (which adapt the behavior of the network at runtime, based on context information). This paper proposes an approach for IoT route selection using fuzzy logic in order to attain the requirements of specific applications. In this case, fuzzy logic is used to translate in math terms the imprecise information expressed by a set of linguistic rules. For this purpose, four Objective Functions (OFs) are proposed for the Routing Protocol for Low Power and Loss Networks (RPL); such OFs are dynamically selected based on context information. The aforementioned OFs are generated from the fusion of the following metrics: Expected Transmission Count (ETX), Number of Hops (NH) and Energy Consumed (EC). The experiments performed through simulation, associated with the statistical data analysis, conclude that this proposal provides high reliability by successfully delivering nearly 100% of data packets, low delay for data delivery and increase in QoS. In addition, an 30% improvement is attained in the network life time when using one of proposed objective function, keeping the devices alive for longer duration. Full article
(This article belongs to the Special Issue Sensor Networks for Collaborative and Secure Internet of Things)
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Open AccessArticle Label-Free Aptasensor for Lysozyme Detection Using Electrochemical Impedance Spectroscopy
Sensors 2018, 18(2), 354; doi:10.3390/s18020354
Received: 20 December 2017 / Revised: 16 January 2018 / Accepted: 23 January 2018 / Published: 26 January 2018
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Abstract
This research develops a label-free aptamer biosensor (aptasensor) based on graphite-epoxy composite electrodes (GECs) for the detection of lysozyme protein using Electrochemical Impedance Spectroscopy (EIS) technique. The chosen immobilization technique was based on covalent bonding using carbodiimide chemistry; for this purpose, carboxylic moieties
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This research develops a label-free aptamer biosensor (aptasensor) based on graphite-epoxy composite electrodes (GECs) for the detection of lysozyme protein using Electrochemical Impedance Spectroscopy (EIS) technique. The chosen immobilization technique was based on covalent bonding using carbodiimide chemistry; for this purpose, carboxylic moieties were first generated on the graphite by electrochemical grafting. The detection was performed using [Fe(CN)6]3−/[Fe(CN)6]4− as redox probe. After recording the frequency response, values were fitted to its electric model using the principle of equivalent circuits. The aptasensor showed a linear response up to 5 µM for lysozyme and a limit of detection of 1.67 µM. The sensitivity of the established method was 0.090 µM−1 in relative charge transfer resistance values. The interference response by main proteins, such as bovine serum albumin and cytochrome c, has been also characterized. To finally verify the performance of the developed aptasensor, it was applied to wine analysis. Full article
(This article belongs to the Special Issue I3S 2017 Selected Papers)
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Open AccessArticle The Response of HeLa Cells to Fluorescent NanoDiamond Uptake
Sensors 2018, 18(2), 355; doi:10.3390/s18020355
Received: 11 December 2017 / Revised: 11 January 2018 / Accepted: 15 January 2018 / Published: 26 January 2018
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Abstract
Fluorescent nanodiamonds are promising probes for nanoscale magnetic resonance measurements. Their physical properties predict them to have particularly useful applications in intracellular analysis. Before using them in intracellular experiments however, it should be clear whether diamond particles influence cell biology. While cytotoxicity has
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Fluorescent nanodiamonds are promising probes for nanoscale magnetic resonance measurements. Their physical properties predict them to have particularly useful applications in intracellular analysis. Before using them in intracellular experiments however, it should be clear whether diamond particles influence cell biology. While cytotoxicity has already been ruled out in previous studies, we consider the non-fatal influence of fluorescent nanodiamonds on the formation of reactive oxygen species (an important stress indicator and potential target for intracellular sensing) for the first time. We investigated the influence of different sizes, shapes and concentrations of nanodiamonds on the genetic and protein level involved in oxidative stress-related pathways of the HeLa cell, an important model cell line in research. The changes in viability of the cells and the difference in intracellular levels of free radicals, after diamond uptake, are surprisingly small. At lower diamond concentrations, the cellular metabolism cannot be distinguished from that of untreated cells. This research supports the claims of non-toxicity and includes less obvious non-fatal responses. Finally, we give a handhold concerning the diamond concentration and size to use for non-toxic, intracellular measurements in favour of (cancer) research in HeLa cells. Full article
(This article belongs to the Special Issue Sensors Based on Quantum Phenomena)
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Open AccessArticle Impact of MAC Delay on AUV Localization: Underwater Localization Based on Hyperbolic Frequency Modulation Signal
Sensors 2018, 18(2), 356; doi:10.3390/s18020356
Received: 5 January 2018 / Revised: 20 January 2018 / Accepted: 21 January 2018 / Published: 26 January 2018
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Abstract
Medium Access Control (MAC) delay which occurs between the anchor node’s transmissions is one of the error sources in underwater localization. In particular, in AUV localization, the MAC delay significantly degrades the ranging accuracy. The Cramer-Rao Low Bound (CRLB) definition theoretically proves that
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Medium Access Control (MAC) delay which occurs between the anchor node’s transmissions is one of the error sources in underwater localization. In particular, in AUV localization, the MAC delay significantly degrades the ranging accuracy. The Cramer-Rao Low Bound (CRLB) definition theoretically proves that the MAC delay significantly degrades the localization performance. This paper proposes underwater localization combined with multiple access technology to decouple the localization performance from the MAC delay. Towards this goal, we adopt hyperbolic frequency modulation (HFM) signal that provides multiplexing based on its good property, high-temporal correlation. Owing to the multiplexing ability of the HFM signal, the anchor nodes can transmit packets without MAC delay, i.e., simultaneous transmission is possible. In addition, the simulation results show that the simultaneous transmission is not an optional communication scheme, but essential for the localization of mobile object in underwater. Full article
(This article belongs to the Special Issue Advances and Challenges in Underwater Sensor Networks)
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Open AccessArticle Detection of Abrin by Electrochemiluminescence Biosensor Based on Screen Printed Electrode
Sensors 2018, 18(2), 357; doi:10.3390/s18020357
Received: 3 November 2017 / Revised: 26 December 2017 / Accepted: 22 January 2018 / Published: 26 January 2018
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Abstract
For the convenience of fast measurement in the outdoor environment, a portable electrochemiluminescence biosensor with the screen-printed electrode as the reaction center was developed, which possesses the characteristics of high sensitivity, small scale, simplified operation and so on, and has been used for
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For the convenience of fast measurement in the outdoor environment, a portable electrochemiluminescence biosensor with the screen-printed electrode as the reaction center was developed, which possesses the characteristics of high sensitivity, small scale, simplified operation and so on, and has been used for in situ detection of abrin. First, combining with magnetic separation technique, the “biotin-avidin” method was used to immobilize the polyclonal antibody (pcAb) on the magnetic microspheres surface as the capture probe. Secondly, the Ru(bpy)32+-labeled monoclonal antibody (mcAb) was used as the specific electrochemiluminescence signal probe. Then, the “mcAb-toxin-pcAb” sandwich model was built to actualize the quantitative detection of abrin on the surface of the screen-printed electrode. The linear detection range was 0.5–1000 ng/mL; the regression equation was Y = 89.251lgX + 104.978 (R = 0.9989, n = 7, p < 0.0001); and the limit of detection (LOD) was 0.1 ng/mL. The sensing system showed high sensitivity, excellent specificity and good anti-interference ability, and could be used for the analysis of trace abrin in various environmental samples with good recovery and reproducibility. Compared with the traditional electrochemiluminescence sensing device, its miniaturization and portability gives it potential to satisfy the requirement of in situ detection. Full article
(This article belongs to the Special Issue Environmental Monitoring Biosensors)
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Open AccessArticle Photo-Induced Room-Temperature Gas Sensing with a-IGZO Based Thin-Film Transistors Fabricated on Flexible Plastic Foil
Sensors 2018, 18(2), 358; doi:10.3390/s18020358
Received: 19 December 2017 / Revised: 19 January 2018 / Accepted: 23 January 2018 / Published: 26 January 2018
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Abstract
We present a gas sensitive thin-film transistor (TFT) based on an amorphous Indium–Gallium–Zinc–Oxide (a-IGZO) semiconductor as the sensing layer, which is fabricated on a free-standing flexible polyimide foil. The photo-induced sensor response to NO2 gas at room temperature and the cross-sensitivity to
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We present a gas sensitive thin-film transistor (TFT) based on an amorphous Indium–Gallium–Zinc–Oxide (a-IGZO) semiconductor as the sensing layer, which is fabricated on a free-standing flexible polyimide foil. The photo-induced sensor response to NO2 gas at room temperature and the cross-sensitivity to humidity are investigated. We combine the advantages of a transistor based sensor with flexible electronics technology to demonstrate the first flexible a-IGZO based gas sensitive TFT. Since flexible plastic substrates prohibit the use of high operating temperatures, the charge generation is promoted with the help of UV-light absorption, which ultimately triggers the reversible chemical reaction with the trace gas. Furthermore, the device fabrication process flow can be directly implemented in standard TFT technology, allowing for the parallel integration of the sensor and analog or logical circuits. Full article
(This article belongs to the Special Issue Thin-Film Transistors for Biomedical and Chemical Sensing)
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Open AccessArticle A IR-Femtosecond Laser Hybrid Sensor to Measure the Thermal Expansion and Thermo-Optical Coefficient of Silica-Based FBG at High Temperatures
Sensors 2018, 18(2), 359; doi:10.3390/s18020359
Received: 21 November 2017 / Revised: 17 January 2018 / Accepted: 17 January 2018 / Published: 26 January 2018
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Abstract
In this paper, a hybrid sensor was fabricated using a IR-femtosecond laser to measure the thermal expansion and thermo-optical coefficient of silica-based fiber Bragg gratings (FBGs). The hybrid sensor was composed of an inline fiber Fabry-Perot interferometer (FFPI) cavity and a type-II FBG.
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In this paper, a hybrid sensor was fabricated using a IR-femtosecond laser to measure the thermal expansion and thermo-optical coefficient of silica-based fiber Bragg gratings (FBGs). The hybrid sensor was composed of an inline fiber Fabry-Perot interferometer (FFPI) cavity and a type-II FBG. Experiment results showed that the type-II FBG had three high reflectivity resonances in the wavelength ranging from 1100 to 1600 nm, showing the peaks in 1.1, 1.3 and 1.5 μm, respectively. The thermal expansion and thermo-optical coefficient (1.3 μm, 1.5 μm) of silica-based FBG, under temperatures ranging from 30 to 1100 °C, had been simultaneously calculated by measuring the wavelength of the type-II FBG and FFPI cavity length. Full article
(This article belongs to the Section Physical Sensors)
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Open AccessArticle Strapdown Airborne Gravimetry Quality Assessment Method Based on Single Survey Line Data: A Study by SGA-WZ02 Gravimeter
Sensors 2018, 18(2), 360; doi:10.3390/s18020360
Received: 8 January 2018 / Revised: 21 January 2018 / Accepted: 23 January 2018 / Published: 26 January 2018
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Abstract
Quality assessment is an important part in the strapdown airborne gravimetry. Root mean square error (RMSE) evaluation method is a classical way to evaluate the gravimetry quality, but classical evaluation methods are preconditioned by extra flight or reference data. Thus, a method, which
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Quality assessment is an important part in the strapdown airborne gravimetry. Root mean square error (RMSE) evaluation method is a classical way to evaluate the gravimetry quality, but classical evaluation methods are preconditioned by extra flight or reference data. Thus, a method, which is able to largely conquer the premises of classical quality assessment methods and can be used in single survey line, has been developed in this paper. According to theoretical analysis, the method chooses the stability of two horizontal attitude angles, horizontal specific force and vertical specific force as the determinants of quality assessment method. The actual data, collected by SGA-WZ02 from 13 flights 21 lines in certain survey, was used to build the model and elaborate the method. To substantiate the performance of the quality assessment model, the model is applied in extra repeat line flights from two surveys. Compared with internal RMSE, standard deviation of assessment residuals are 0.23 mGal and 0.16 mGal in two surveys, which shows that the quality assessment method is reliable and stricter. The extra flights are not necessary by specially arranging the route of flights. The method, summarized from SGA-WZ02, is a feasible approach to assess gravimetry quality using single line data and is also suitable for other strapdown gravimeters. Full article
(This article belongs to the Section Physical Sensors)
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Open AccessArticle Artificial Vector Calibration Method for Differencing Magnetic Gradient Tensor Systems
Sensors 2018, 18(2), 361; doi:10.3390/s18020361
Received: 21 October 2017 / Revised: 19 December 2017 / Accepted: 17 January 2018 / Published: 26 January 2018
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Abstract
The measurement error of the differencing (i.e., using two homogenous field sensors at a known baseline distance) magnetic gradient tensor system includes the biases, scale factors, nonorthogonality of the single magnetic sensor, and the misalignment error between the sensor arrays, all of which
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The measurement error of the differencing (i.e., using two homogenous field sensors at a known baseline distance) magnetic gradient tensor system includes the biases, scale factors, nonorthogonality of the single magnetic sensor, and the misalignment error between the sensor arrays, all of which can severely affect the measurement accuracy. In this paper, we propose a low-cost artificial vector calibration method for the tensor system. Firstly, the error parameter linear equations are constructed based on the single-sensor’s system error model to obtain the artificial ideal vector output of the platform, with the total magnetic intensity (TMI) scalar as a reference by two nonlinear conversions, without any mathematical simplification. Secondly, the Levenberg–Marquardt algorithm is used to compute the integrated model of the 12 error parameters by nonlinear least-squares fitting method with the artificial vector output as a reference, and a total of 48 parameters of the system is estimated simultaneously. The calibrated system outputs along the reference platform-orthogonal coordinate system. The analysis results show that the artificial vector calibrated output can track the orientation fluctuations of TMI accurately, effectively avoiding the “overcalibration” problem. The accuracy of the error parameters’ estimation in the simulation is close to 100%. The experimental root-mean-square error (RMSE) of the TMI and tensor components is less than 3 nT and 20 nT/m, respectively, and the estimation of the parameters is highly robust. Full article
(This article belongs to the Special Issue Magnetic Sensors and Their Applications)
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Open AccessArticle A Micro-Resonant Gas Sensor with Nanometer Clearance between the Pole Plates
Sensors 2018, 18(2), 362; doi:10.3390/s18020362
Received: 26 December 2017 / Revised: 20 January 2018 / Accepted: 25 January 2018 / Published: 26 January 2018
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Abstract
In micro-resonant gas sensors, the capacitive detection is widely used because of its simple structure. However, its shortcoming is a weak signal output caused by a small capacitance change. Here, we reduced the initial clearance between the pole plates to the nanometer level,
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In micro-resonant gas sensors, the capacitive detection is widely used because of its simple structure. However, its shortcoming is a weak signal output caused by a small capacitance change. Here, we reduced the initial clearance between the pole plates to the nanometer level, and increased the capacitance between the pole plates and its change during resonator vibration. We propose a fabricating process of the micro-resonant gas sensor by which the initial clearance between the pole plates is reduced to the nanometer level and a micro-resonant gas sensor with 200 nm initial clearance is fabricated. With this sensor, the resonant frequency shifts were measured when they were exposed to several different vapors, and high detection accuracies were obtained. The detection accuracy with respect to ethanol vapor was 0.4 ppm per Hz shift, and the detection accuracy with respect to hydrogen and ammonias vapors was 3 ppm and 0.5 ppm per Hz shift, respectively. Full article
(This article belongs to the collection Gas Sensors)
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Open AccessArticle Hyperspectral Image Classification for Land Cover Based on an Improved Interval Type-II Fuzzy C-Means Approach
Sensors 2018, 18(2), 363; doi:10.3390/s18020363
Received: 9 November 2017 / Revised: 15 January 2018 / Accepted: 24 January 2018 / Published: 26 January 2018
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Abstract
Few studies have examined hyperspectral remote-sensing image classification with type-II fuzzy sets. This paper addresses image classification based on a hyperspectral remote-sensing technique using an improved interval type-II fuzzy c-means (IT2FCM*) approach. In this study, in contrast to other traditional fuzzy c-means-based approaches,
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Few studies have examined hyperspectral remote-sensing image classification with type-II fuzzy sets. This paper addresses image classification based on a hyperspectral remote-sensing technique using an improved interval type-II fuzzy c-means (IT2FCM*) approach. In this study, in contrast to other traditional fuzzy c-means-based approaches, the IT2FCM* algorithm considers the ranking of interval numbers and the spectral uncertainty. The classification results based on a hyperspectral dataset using the FCM, IT2FCM, and the proposed improved IT2FCM* algorithms show that the IT2FCM* method plays the best performance according to the clustering accuracy. In this paper, in order to validate and demonstrate the separability of the IT2FCM*, four type-I fuzzy validity indexes are employed, and a comparative analysis of these fuzzy validity indexes also applied in FCM and IT2FCM methods are made. These four indexes are also applied into different spatial and spectral resolution datasets to analyze the effects of spectral and spatial scaling factors on the separability of FCM, IT2FCM, and IT2FCM* methods. The results of these validity indexes from the hyperspectral datasets show that the improved IT2FCM* algorithm have the best values among these three algorithms in general. The results demonstrate that the IT2FCM* exhibits good performance in hyperspectral remote-sensing image classification because of its ability to handle hyperspectral uncertainty. Full article
(This article belongs to the Special Issue Analysis of Multispectral and Hyperspectral Data)
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Open AccessArticle A Novel Grid SINS/DVL Integrated Navigation Algorithm for Marine Application
Sensors 2018, 18(2), 364; doi:10.3390/s18020364
Received: 7 December 2017 / Revised: 21 January 2018 / Accepted: 23 January 2018 / Published: 26 January 2018
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Abstract
Integrated navigation algorithms under the grid frame have been proposed based on the Kalman filter (KF) to solve the problem of navigation in some special regions. However, in the existing study of grid strapdown inertial navigation system (SINS)/Doppler velocity log (DVL) integrated navigation
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Integrated navigation algorithms under the grid frame have been proposed based on the Kalman filter (KF) to solve the problem of navigation in some special regions. However, in the existing study of grid strapdown inertial navigation system (SINS)/Doppler velocity log (DVL) integrated navigation algorithms, the Earth models of the filter dynamic model and the SINS mechanization are not unified. Besides, traditional integrated systems with the KF based correction scheme are susceptible to measurement errors, which would decrease the accuracy and robustness of the system. In this paper, an adaptive robust Kalman filter (ARKF) based hybrid-correction grid SINS/DVL integrated navigation algorithm is designed with the unified reference ellipsoid Earth model to improve the navigation accuracy in middle-high latitude regions for marine application. Firstly, to unify the Earth models, the mechanization of grid SINS is introduced and the error equations are derived based on the same reference ellipsoid Earth model. Then, a more accurate grid SINS/DVL filter model is designed according to the new error equations. Finally, a hybrid-correction scheme based on the ARKF is proposed to resist the effect of measurement errors. Simulation and experiment results show that, compared with the traditional algorithms, the proposed navigation algorithm can effectively improve the navigation performance in middle-high latitude regions by the unified Earth models and the ARKF based hybrid-correction scheme. Full article
(This article belongs to the Special Issue Inertial Sensors for Positioning and Navigation)
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Open AccessArticle A Fiber Bragg Grating-Based Dynamic Tension Detection System for Overhead Transmission Line Galloping
Sensors 2018, 18(2), 365; doi:10.3390/s18020365
Received: 12 December 2017 / Revised: 20 January 2018 / Accepted: 25 January 2018 / Published: 26 January 2018
PDF Full-text (5953 KB) | HTML Full-text | XML Full-text | Supplementary Files
Abstract
Galloping of overhead transmission lines (OHTLs) may induce conductor breakage and tower collapse, and there is no effective method for long distance distribution on-line galloping monitoring. To overcome the drawbacks of the conventional galloping monitoring systems, such as sensitivity to electromagnetic interference, the
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Galloping of overhead transmission lines (OHTLs) may induce conductor breakage and tower collapse, and there is no effective method for long distance distribution on-line galloping monitoring. To overcome the drawbacks of the conventional galloping monitoring systems, such as sensitivity to electromagnetic interference, the need for onsite power, and short lifetimes, a novel optical remote passive measuring system is proposed in the paper. Firstly, to solve the hysteresis and eccentric load problem in tension sensing, and to extent the dynamic response range, an ‘S’ type elastic element structure with flanges was proposed. Then, a tension experiment was carried out to demonstrate the dynamic response characteristics. Moreover, the designed tension sensor was stretched continuously for 30 min to observe its long time stability. Last but not the least, the sensor was mounted on a 70 m conductor model, and the conductor was oscillated at different frequencies to investigate the dynamic performance of the sensor. The experimental results demonstrate the sensor is suitable for the OHTL galloping detection. Compared with the conventional sensors for OHTL monitoring, the system has many advantages, such as easy installation, no flashover risk, distribution monitoring, better bandwidth, improved accuracy and higher reliability. Full article
(This article belongs to the Special Issue Sensors for Deformation Monitoring of Large Civil Infrastructures)
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Open AccessArticle A Low-Cost Data Acquisition System for Automobile Dynamics Applications
Sensors 2018, 18(2), 366; doi:10.3390/s18020366
Received: 19 December 2017 / Revised: 24 January 2018 / Accepted: 25 January 2018 / Published: 27 January 2018
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Abstract
This project addresses the need for the implementation of low-cost acquisition technology in the field of vehicle engineering: the design, development, manufacture, and verification of a low-cost Arduino-based data acquisition platform to be used in <80 Hz data acquisition in vehicle dynamics, using
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This project addresses the need for the implementation of low-cost acquisition technology in the field of vehicle engineering: the design, development, manufacture, and verification of a low-cost Arduino-based data acquisition platform to be used in <80 Hz data acquisition in vehicle dynamics, using low-cost accelerometers. In addition to this, a comparative study is carried out of professional vibration acquisition technologies and low-cost systems, obtaining optimum results for low- and medium-frequency operations with an error of 2.19% on road tests. It is therefore concluded that these technologies are applicable to the automobile industry, thereby allowing the project costs to be reduced and thus facilitating access to this kind of research that requires limited resources. Full article
(This article belongs to the Section Physical Sensors)
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Open AccessArticle Fuzzy Traffic Control with Vehicle-to-Everything Communication
Sensors 2018, 18(2), 368; doi:10.3390/s18020368
Received: 30 November 2017 / Revised: 4 January 2018 / Accepted: 19 January 2018 / Published: 27 January 2018
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Abstract
Traffic signal control (TSC) with vehicle-to everything (V2X) communication can be a very efficient solution to traffic congestion problem. Ratio of vehicles equipped with V2X communication capability in the traffic to the total number of vehicles (called penetration rate PR) is still low,
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Traffic signal control (TSC) with vehicle-to everything (V2X) communication can be a very efficient solution to traffic congestion problem. Ratio of vehicles equipped with V2X communication capability in the traffic to the total number of vehicles (called penetration rate PR) is still low, thus V2X based TSC systems need to be supported by some other mechanisms. PR is the major factor that affects the quality of TSC process along with the evaluation interval. Quality of the TSC in each direction is a function of overall TSC quality of an intersection. Hence, quality evaluation of each direction should follow the evaluation of the overall intersection. Computational intelligence, more specifically swarm algorithm, has been recently used in this field in a European Framework Program FP7 supported project called COLOMBO. In this paper, using COLOMBO framework, further investigations have been done and two new methodologies using simple and fuzzy logic have been proposed. To evaluate the performance of our proposed methods, a comparison with COLOMBOs approach has been realized. The results reveal that TSC problem can be solved as a logical problem rather than an optimization problem. Performance of the proposed approaches is good enough to be suggested for future work under realistic scenarios even under low PR. Full article
(This article belongs to the Special Issue Sensor Networks for Smart Roads)
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Open AccessArticle Comparing Two Independent Satellite-Based Algorithms for Detecting and Tracking Ash Clouds by Using SEVIRI Sensor
Sensors 2018, 18(2), 369; doi:10.3390/s18020369
Received: 10 January 2018 / Revised: 23 January 2018 / Accepted: 25 January 2018 / Published: 27 January 2018
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Abstract
The Eyjafjallajökull (Iceland) volcanic eruption of April–May 2010 caused unprecedented air-traffic disruption in Northern Europe, revealing some important weaknesses of current operational ash-monitoring and forecasting systems and encouraging the improvement of methods and procedures for supporting the activities of Volcanic Ash Advisory Centers
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The Eyjafjallajökull (Iceland) volcanic eruption of April–May 2010 caused unprecedented air-traffic disruption in Northern Europe, revealing some important weaknesses of current operational ash-monitoring and forecasting systems and encouraging the improvement of methods and procedures for supporting the activities of Volcanic Ash Advisory Centers (VAACs) better. In this work, we compare two established satellite-based algorithms for ash detection, namely RSTASH and the operational London VAAC method, both exploiting sensor data of the spinning enhanced visible and infrared imager (SEVIRI). We analyze similarities and differences in the identification of ash clouds during the different phases of the Eyjafjallajökull eruption. The work reveals, in some cases, a certain complementary behavior of the two techniques, whose combination might improve the identification of ash-affected areas in specific conditions. This is indicated by the quantitative comparison of the merged SEVIRI ash product, achieved integrating outputs of the RSTASH and London VAAC methods, with independent atmospheric infrared sounder (AIRS) DDA (dust-detection algorithm) observations. Full article
(This article belongs to the Section Remote Sensors)
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Open AccessArticle Securing Cooperative Spectrum Sensing Against Collusive SSDF Attack using XOR Distance Analysis in Cognitive Radio Networks
Sensors 2018, 18(2), 370; doi:10.3390/s18020370
Received: 12 November 2017 / Revised: 13 January 2018 / Accepted: 24 January 2018 / Published: 27 January 2018
PDF Full-text (357 KB) | HTML Full-text | XML Full-text
Abstract
Cooperative spectrum sensing (CSS) is considered as a powerful approach to improve the utilization of scarce spectrum resources. However, if CSS assumes that all secondary users (SU) are honest, it may offer opportunities for attackers to conduct a spectrum sensing data falsification (SSDF)
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Cooperative spectrum sensing (CSS) is considered as a powerful approach to improve the utilization of scarce spectrum resources. However, if CSS assumes that all secondary users (SU) are honest, it may offer opportunities for attackers to conduct a spectrum sensing data falsification (SSDF) attack. To suppress such a threat, recent efforts have been made to develop trust mechanisms. Currently, some attackers can collude with each other to form a collusive clique, and thus not only increase the power of SSDF attack but also avoid the detection of a trust mechanism. Noting the duality of sensing data, we propose a defense scheme called XDA from the perspective of XOR distance analysis to suppress a collusive SSDF attack. In the XDA scheme, the XOR distance calculation in line with the type of “0” and “1” historical sensing data is used to measure the similarity between any two SUs. Noting that collusive SSDF attackers hold high trust value and the minimum XOR distance, the algorithm to detect collusive SSDF attackers is designed. Meanwhile, the XDA scheme can perfect the trust mechanism to correct collusive SSDF attackers’ trust value. Simulation results show that the XDA scheme can enhance the accuracy of trust evaluation, and thus successfully reduce the power of collusive SSDF attack against CSS. Full article
(This article belongs to the Special Issue Cognitive Radio Sensing and Sensor Networks)
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Open AccessArticle An Interdigital Electrode Probe for Detection, Localization and Evaluation of Surface Notch-Type Damage in Metals
Sensors 2018, 18(2), 371; doi:10.3390/s18020371
Received: 6 November 2017 / Revised: 29 December 2017 / Accepted: 21 January 2018 / Published: 27 January 2018
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Abstract
Available microwave notch-type damage detection sensors are typically based on monitoring frequency shift or magnitude changes. However, frequency shift testing needs sweep-frequency data that make scanning detection becomes difficult and time-consuming. This work presents a microwave near-field nondestructive testing sensor for detecting sub-millimeter
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Available microwave notch-type damage detection sensors are typically based on monitoring frequency shift or magnitude changes. However, frequency shift testing needs sweep-frequency data that make scanning detection becomes difficult and time-consuming. This work presents a microwave near-field nondestructive testing sensor for detecting sub-millimeter notch-type damage detection in metallic surfaces. The sensor is loaded with an interdigital electrode element in an open-ended coaxial. It is simple to fabricate and inexpensive, as it is etched on the RC4003 patch by using printed circuit board technology. The detection is achieved by monitoring changes in reflection amplitude, which is caused by perturbing the electromagnetic field around the interdigital structure. The proposed sensor was tested on a metallic plate with different defects, and the experimental results indicated that the interdigital electrode probe can determine the orientation, localization and dimension of surface notch-type damage. Full article
(This article belongs to the Special Issue Intelligent Sensing Technologies for Nondestructive Evaluation)
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Open AccessArticle Human Identification by Cross-Correlation and Pattern Matching of Personalized Heartbeat: Influence of ECG Leads and Reference Database Size
Sensors 2018, 18(2), 372; doi:10.3390/s18020372
Received: 17 January 2018 / Revised: 23 January 2018 / Accepted: 24 January 2018 / Published: 27 January 2018
PDF Full-text (3494 KB) | HTML Full-text | XML Full-text | Supplementary Files
Abstract
Human identification (ID) is a biometric task, comparing single input sample to many stored templates to identify an individual in a reference database. This paper aims to present the perspectives of personalized heartbeat pattern for reliable ECG-based identification. The investigations are using a
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Human identification (ID) is a biometric task, comparing single input sample to many stored templates to identify an individual in a reference database. This paper aims to present the perspectives of personalized heartbeat pattern for reliable ECG-based identification. The investigations are using a database with 460 pairs of 12-lead resting electrocardiograms (ECG) with 10-s durations recorded at time-instants T1 and T2 > T1 + 1 year. Intra-subject long-term ECG stability and inter-subject variability of personalized PQRST (500 ms) and QRS (100 ms) patterns is quantified via cross-correlation, amplitude ratio and pattern matching between T1 and T2 using 7 features × 12-leads. Single and multi-lead ID models are trained on the first 230 ECG pairs. Their validation on 10, 20, ... 230 reference subjects (RS) from the remaining 230 ECG pairs shows: (i) two best single-lead ID models using lead II for a small population RS = (10–140) with identification accuracy AccID = (89.4–67.2)% and aVF for a large population RS = (140–230) with AccID = (67.2–63.9)%; (ii) better performance of the 6-lead limb vs. the 6-lead chest ID model—(91.4–76.1)% vs. (90.9–70)% for RS = (10–230); (iii) best performance of the 12-lead ID model—(98.4–87.4)% for RS = (10–230). The tolerable reference database size, keeping AccID > 80%, is RS = 30 in the single-lead ID scenario (II); RS = 50 (6 chest leads); RS = 100 (6 limb leads), RS > 230—maximal population in this study (12-lead ECG). Full article
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Open AccessArticle Multi-Feature Classification of Multi-Sensor Satellite Imagery Based on Dual-Polarimetric Sentinel-1A, Landsat-8 OLI, and Hyperion Images for Urban Land-Cover Classification
Sensors 2018, 18(2), 373; doi:10.3390/s18020373
Received: 9 January 2018 / Revised: 24 January 2018 / Accepted: 25 January 2018 / Published: 27 January 2018
PDF Full-text (3315 KB) | HTML Full-text | XML Full-text
Abstract
This paper focuses on evaluating the ability and contribution of using backscatter intensity, texture, coherence, and color features extracted from Sentinel-1A data for urban land cover classification and comparing different multi-sensor land cover mapping methods to improve classification accuracy. Both Landsat-8 OLI and
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This paper focuses on evaluating the ability and contribution of using backscatter intensity, texture, coherence, and color features extracted from Sentinel-1A data for urban land cover classification and comparing different multi-sensor land cover mapping methods to improve classification accuracy. Both Landsat-8 OLI and Hyperion images were also acquired, in combination with Sentinel-1A data, to explore the potential of different multi-sensor urban land cover mapping methods to improve classification accuracy. The classification was performed using a random forest (RF) method. The results showed that the optimal window size of the combination of all texture features was 9 × 9, and the optimal window size was different for each individual texture feature. For the four different feature types, the texture features contributed the most to the classification, followed by the coherence and backscatter intensity features; and the color features had the least impact on the urban land cover classification. Satisfactory classification results can be obtained using only the combination of texture and coherence features, with an overall accuracy up to 91.55% and a kappa coefficient up to 0.8935, respectively. Among all combinations of Sentinel-1A-derived features, the combination of the four features had the best classification result. Multi-sensor urban land cover mapping obtained higher classification accuracy. The combination of Sentinel-1A and Hyperion data achieved higher classification accuracy compared to the combination of Sentinel-1A and Landsat-8 OLI images, with an overall accuracy of up to 99.12% and a kappa coefficient up to 0.9889. When Sentinel-1A data was added to Hyperion images, the overall accuracy and kappa coefficient were increased by 4.01% and 0.0519, respectively. Full article
(This article belongs to the Special Issue Spatial Analysis and Remote Sensing)
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Open AccessArticle Vehicle Detection with Occlusion Handling, Tracking, and OC-SVM Classification: A High Performance Vision-Based System
Sensors 2018, 18(2), 374; doi:10.3390/s18020374
Received: 30 November 2017 / Revised: 7 January 2018 / Accepted: 18 January 2018 / Published: 27 January 2018
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Abstract
This paper presents a high performance vision-based system with a single static camera for traffic surveillance, for moving vehicle detection with occlusion handling, tracking, counting, and One Class Support Vector Machine (OC-SVM) classification. In this approach, moving objects are first segmented from the
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This paper presents a high performance vision-based system with a single static camera for traffic surveillance, for moving vehicle detection with occlusion handling, tracking, counting, and One Class Support Vector Machine (OC-SVM) classification. In this approach, moving objects are first segmented from the background using the adaptive Gaussian Mixture Model (GMM). After that, several geometric features are extracted, such as vehicle area, height, width, centroid, and bounding box. As occlusion is present, an algorithm was implemented to reduce it. The tracking is performed with adaptive Kalman filter. Finally, the selected geometric features: estimated area, height, and width are used by different classifiers in order to sort vehicles into three classes: small, midsize, and large. Extensive experimental results in eight real traffic videos with more than 4000 ground truth vehicles have shown that the improved system can run in real time under an occlusion index of 0.312 and classify vehicles with a global detection rate or recall, precision, and F-measure of up to 98.190%, and an F-measure of up to 99.051% for midsize vehicles. Full article
(This article belongs to the Special Issue Sensors for Transportation)
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Open AccessArticle Self-Learning Power Control in Wireless Sensor Networks
Sensors 2018, 18(2), 375; doi:10.3390/s18020375
Received: 14 December 2017 / Revised: 19 January 2018 / Accepted: 21 January 2018 / Published: 27 January 2018
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Abstract
Current trends in interconnecting myriad smart objects to monetize on Internet of Things applications have led to high-density communications in wireless sensor networks. This aggravates the already over-congested unlicensed radio bands, calling for new mechanisms to improve spectrum management and energy efficiency, such
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Current trends in interconnecting myriad smart objects to monetize on Internet of Things applications have led to high-density communications in wireless sensor networks. This aggravates the already over-congested unlicensed radio bands, calling for new mechanisms to improve spectrum management and energy efficiency, such as transmission power control. Existing protocols are based on simplistic heuristics that often approach interference problems (i.e., packet loss, delay and energy waste) by increasing power, leading to detrimental results. The scope of this work is to investigate how machine learning may be used to bring wireless nodes to the lowest possible transmission power level and, in turn, to respect the quality requirements of the overall network. Lowering transmission power has benefits in terms of both energy consumption and interference. We propose a protocol of transmission power control through a reinforcement learning process that we have set in a multi-agent system. The agents are independent learners using the same exploration strategy and reward structure, leading to an overall cooperative network. The simulation results show that the system converges to an equilibrium where each node transmits at the minimum power while respecting high packet reception ratio constraints. Consequently, the system benefits from low energy consumption and packet delay. Full article
(This article belongs to the Special Issue Smart Communication Protocols and Algorithms for Sensor Networks)
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Open AccessArticle Estimation of the Land Surface Temperature over the Tibetan Plateau by Using Chinese FY-2C Geostationary Satellite Data
Sensors 2018, 18(2), 376; doi:10.3390/s18020376
Received: 6 December 2017 / Revised: 20 January 2018 / Accepted: 24 January 2018 / Published: 28 January 2018
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Abstract
During the process of land–atmosphere interaction, one of the essential parameters is the land surface temperature (LST). The LST has high temporal variability, especially in its diurnal cycle, which cannot be acquired by polar-orbiting satellites. Therefore, it is of great practical significance to
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During the process of land–atmosphere interaction, one of the essential parameters is the land surface temperature (LST). The LST has high temporal variability, especially in its diurnal cycle, which cannot be acquired by polar-orbiting satellites. Therefore, it is of great practical significance to retrieve LST data using geostationary satellites. According to the data of FengYun 2C (FY-2C) satellite and the measurements from the Enhanced Observing Period (CEOP) of the Asia–Australia Monsoon Project (CAMP) on the Tibetan Plateau (CAMP/Tibet), a regression approach was utilized in this research to optimize the split window algorithm (SWA). The thermal infrared data obtained by the Chinese geostationary satellite FY-2C over the Tibetan Plateau (TP) was used to estimate the hourly LST time series. To decrease the effects of cloud, the 10-day composite hourly LST data were obtained through the approach of maximal value composite (MVC). The derived LST was used to compare with the product of MODIS LST and was also validated by the field observation. The results show that the LST retrieved through the optimized SWA and in situ data has a better consistency (with correlation coefficient (R), mean absolute error (MAE), mean bias (MB), and root mean square error (RMSE) values of 0.987, 1.91 K, 0.83 K and 2.26 K, respectively) than that derived from Becker and Li’s SWA and MODIS LST product, which means that the modified SWA can be applied to achieve plateau-scale LST. The diurnal variation of the LST and the hourly time series of the LST over the Tibetan Plateau were also obtained. The diurnal range of LST was found to be clearly affected by the influence of the thawing and freezing process of soil and the summer monsoon evolution. The comparison between the seasonal and diurnal variations of LST at four typical underlying surfaces over the TP indicate that the variation of LST is closely connected with the underlying surface types as well. The diurnal variation of LST is the smallest at the water (5.12 K), second at the snow and ice (5.45 K), third at the grasslands (19.82 K) and largest at the barren or sparsely vegetated (22.83 K). Full article
(This article belongs to the Section Remote Sensors)
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Open AccessArticle On the Design of an Efficient Cardiac Health Monitoring System Through Combined Analysis of ECG and SCG Signals
Sensors 2018, 18(2), 379; doi:10.3390/s18020379
Received: 30 November 2017 / Revised: 21 January 2018 / Accepted: 24 January 2018 / Published: 28 January 2018
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Abstract
Cardiovascular disease (CVD) is a major public concern and socioeconomic problem across the globe. The popular high-end cardiac health monitoring systems such as magnetic resonance imaging (MRI), computerized tomography scan (CT scan), and echocardiography (Echo) are highly expensive and do not support long-term
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Cardiovascular disease (CVD) is a major public concern and socioeconomic problem across the globe. The popular high-end cardiac health monitoring systems such as magnetic resonance imaging (MRI), computerized tomography scan (CT scan), and echocardiography (Echo) are highly expensive and do not support long-term continuous monitoring of patients without disrupting their activities of daily living (ADL). In this paper, the continuous and non-invasive cardiac health monitoring using unobtrusive sensors is explored aiming to provide a feasible and low-cost alternative to foresee possible cardiac anomalies in an early stage. It is learned that cardiac health monitoring based on sole usage of electrocardiogram (ECG) signals may not provide powerful insights as ECG provides shallow information on various cardiac activities in the form of electrical impulses only. Hence, a novel low-cost, non-invasive seismocardiogram (SCG) signal along with ECG signals are jointly investigated for the robust cardiac health monitoring. For this purpose, the in-laboratory data collection model is designed for simultaneous acquisition of ECG and SCG signals followed by mechanisms for the automatic delineation of relevant feature points in acquired ECG and SCG signals. In addition, separate feature points based novel approach is adopted to distinguish between normal and abnormal morphology in each ECG and SCG cardiac cycle. Finally, a combined analysis of ECG and SCG is carried out by designing a Naïve Bayes conditional probability model. Experiments on Institutional Review Board (IRB) approved licensed ECG/SCG signals acquired from real subjects containing 12,000 cardiac cycles show that the proposed feature point delineation mechanisms and abnormal morphology detection methods consistently perform well and give promising results. In addition, experimental results show that the combined analysis of ECG and SCG signals provide more reliable cardiac health monitoring compared to the standalone use of ECG and SCG. Full article
(This article belongs to the Special Issue Sensors for Health Monitoring and Disease Diagnosis)
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Open AccessArticle Joint Interference Alignment and Power Allocation for K-User Multicell MIMO Channel through Staggered Antenna Switching
Sensors 2018, 18(2), 380; doi:10.3390/s18020380
Received: 10 December 2017 / Revised: 24 January 2018 / Accepted: 24 January 2018 / Published: 28 January 2018
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Abstract
In this paper, we characterise the joint interference alignment (IA) and power allocation strategies for a K-user multicell multiple-input multiple-output (MIMO) Gaussian interference channel. We consider a MIMO interference channel with blind-IA through staggered antenna switching on the receiver. We explore the
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In this paper, we characterise the joint interference alignment (IA) and power allocation strategies for a K-user multicell multiple-input multiple-output (MIMO) Gaussian interference channel. We consider a MIMO interference channel with blind-IA through staggered antenna switching on the receiver. We explore the power allocation and feasibility condition for cooperative cell-edge (CE) mobile users (MUs) by assuming that the channel state information is unknown. The new insight behind the transmission strategy of the proposed scheme is premeditated (randomly generated transmission strategy) and partial cooperative CE MUs, where the transmitter is equipped with a conventional antenna, the receiver is equipped with a reconfigurable multimode antenna (staggered antenna switching pattern), and the receiver switches between preset T modes. Our proposed scheme assists and aligns the desired signals and interference signals to cancel the common interference signals because the received signal must have a corresponding independent signal subspace. The capacity for a K-user multicell MIMO Gaussian interference channel with reconfigurable multimode antennas is completely characterised. Furthermore, we show that the proposed K-user multicell MIMO scheduling and K-user L-cell CEUs partial cooperation algorithms elaborate the generalisation of K-user IA and power allocation strategies. The numerical results demonstrate that the proposed intercell interference scheme with partial-cooperative CE MUs achieves better capacity and signal-to-interference plus noise ratio (SINR) performance compared to noncooperative CE MUs and without intercell interference schemes. Full article
(This article belongs to the Section Sensor Networks)
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Open AccessArticle An Improved Method for Magnetic Nanocarrier Drug Delivery across the Cell Membrane
Sensors 2018, 18(2), 381; doi:10.3390/s18020381
Received: 31 October 2017 / Revised: 2 December 2017 / Accepted: 7 December 2017 / Published: 29 January 2018
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Abstract
One of the crucial issues in the pharmacological field is developing new drug delivery systems. The main concern is to develop new methods for improving the drug delivery efficiencies such as low disruptions, precise control of the target of delivery and drug sustainability.
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One of the crucial issues in the pharmacological field is developing new drug delivery systems. The main concern is to develop new methods for improving the drug delivery efficiencies such as low disruptions, precise control of the target of delivery and drug sustainability. Nowadays, there are many various methods for drug delivery systems. Carbon-based nanocarriers are a new efficient tool for translocating drug into the defined area or cells inside the body. These nanocarriers can be functionalized with proteins, peptides and used to transport their freight to cells or defined areas. Since functionalized carbon-based nanocarriers show low toxicity and high biocompatibility, they are used in many nanobiotechnology fields. In this study, different shapes of nanocarrier are investigated, and the suitable magnetic field, which is applied using MRI for the delivery of the nanocarrier, is proposed. In this research, based on the force required to cross the membrane and MD simulations, the optimal magnetic field profile is designed. This optimal magnetic force field is derived from the mathematical model of the system and magnetic particle dynamics inside the nanocarrier. The results of this paper illustrate the effects of the nanocarrier’s shapes on the percentage of success in crossing the membrane and the optimal required magnetic field. Full article
(This article belongs to the Special Issue Bio-MEMS for Precision Medicine)
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Open AccessArticle Cutting Pattern Identification for Coal Mining Shearer through a Swarm Intelligence–Based Variable Translation Wavelet Neural Network
Sensors 2018, 18(2), 382; doi:10.3390/s18020382
Received: 26 October 2017 / Revised: 25 January 2018 / Accepted: 26 January 2018 / Published: 29 January 2018
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Abstract
As a sound signal has the advantages of non-contacted measurement, compact structure, and low power consumption, it has resulted in much attention in many fields. In this paper, the sound signal of the coal mining shearer is analyzed to realize the accurate online
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As a sound signal has the advantages of non-contacted measurement, compact structure, and low power consumption, it has resulted in much attention in many fields. In this paper, the sound signal of the coal mining shearer is analyzed to realize the accurate online cutting pattern identification and guarantee the safety quality of the working face. The original acoustic signal is first collected through an industrial microphone and decomposed by adaptive ensemble empirical mode decomposition (EEMD). A 13-dimensional set composed by the normalized energy of each level is extracted as the feature vector in the next step. Then, a swarm intelligence optimization algorithm inspired by bat foraging behavior is applied to determine key parameters of the traditional variable translation wavelet neural network (VTWNN). Moreover, a disturbance coefficient is introduced into the basic bat algorithm (BA) to overcome the disadvantage of easily falling into local extremum and limited exploration ability. The VTWNN optimized by the modified BA (VTWNN-MBA) is used as the cutting pattern recognizer. Finally, a simulation example, with an accuracy of 95.25%, and a series of comparisons are conducted to prove the effectiveness and superiority of the proposed method. Full article
(This article belongs to the Special Issue Sensor Signal and Information Processing)
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Open AccessArticle A Triaxial Applicator for the Measurement of the Electromagnetic Properties of Materials
Sensors 2018, 18(2), 383; doi:10.3390/s18020383
Received: 31 October 2017 / Revised: 17 January 2018 / Accepted: 23 January 2018 / Published: 29 January 2018
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Abstract
The design, analysis, and fabrication of a prototype triaxial applicator is described. The applicator provides both reflected and transmitted signals that can be used to characterize the electromagnetic properties of materials in situ. A method for calibrating the probe is outlined and validated
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The design, analysis, and fabrication of a prototype triaxial applicator is described. The applicator provides both reflected and transmitted signals that can be used to characterize the electromagnetic properties of materials in situ. A method for calibrating the probe is outlined and validated using simulated data. Fabrication of the probe is discussed, and measured data for typical absorbing materials and for the probe situated in air are presented. The simulations and measurements suggest that the probe should be useful for measuring the properties of common radar absorbing materials under usual in situ conditions. Full article
(This article belongs to the Section Physical Sensors)
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Open AccessArticle A New Strategy Involving the Use of Peptides and Graphene Oxide for Fluorescence Turn-on Detection of Proteins
Sensors 2018, 18(2), 385; doi:10.3390/s18020385
Received: 29 December 2017 / Revised: 23 January 2018 / Accepted: 25 January 2018 / Published: 29 January 2018
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Abstract
The detection of proteins is of great biological significance as disease biomarkers in early diagnosis, prognosis tracking and therapeutic evaluation. Thus, we developed a simple, sensitive and universal protein-sensing platform based on peptide and graphene oxide (GO). The design consists of a fluorophore
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The detection of proteins is of great biological significance as disease biomarkers in early diagnosis, prognosis tracking and therapeutic evaluation. Thus, we developed a simple, sensitive and universal protein-sensing platform based on peptide and graphene oxide (GO). The design consists of a fluorophore (TAMRA, TAM), a peptide containing eight arginines and peptide ligand that could recognize the target protein, and GO used as a quencher. To demonstrate the feasible use of the sensor for target detection, Bcl-xL was evaluated as the model target. The sensor was proved to be sensitive and applied for the detection of the target proteins in buffer, 2% serum and living cells. Full article
(This article belongs to the Special Issue Carbon Materials Based Sensors and the Application)
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Open AccessArticle Use of Acoustic Emission and Pattern Recognition for Crack Detection of a Large Carbide Anvil
Sensors 2018, 18(2), 386; doi:10.3390/s18020386
Received: 25 December 2017 / Revised: 24 January 2018 / Accepted: 26 January 2018 / Published: 29 January 2018
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Abstract
Large-volume cubic high-pressure apparatus is commonly used to produce synthetic diamond. Due to the high pressure, high temperature and alternative stresses in practical production, cracks often occur in the carbide anvil, thereby resulting in significant economic losses or even casualties. Conventional methods are
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Large-volume cubic high-pressure apparatus is commonly used to produce synthetic diamond. Due to the high pressure, high temperature and alternative stresses in practical production, cracks often occur in the carbide anvil, thereby resulting in significant economic losses or even casualties. Conventional methods are unsuitable for crack detection of the carbide anvil. This paper is concerned with acoustic emission-based crack detection of carbide anvils, regarded as a pattern recognition problem; this is achieved using a microphone, with methods including sound pulse detection, feature extraction, feature optimization and classifier design. Through analyzing the characteristics of background noise, the cracked sound pulses are separated accurately from the originally continuous signal. Subsequently, three different kinds of features including a zero-crossing rate, sound pressure levels, and linear prediction cepstrum coefficients are presented for characterizing the cracked sound pulses. The original high-dimensional features are adaptively optimized using principal component analysis. A hybrid framework of a support vector machine with k nearest neighbors is designed to recognize the cracked sound pulses. Finally, experiments are conducted in a practical diamond workshop to validate the feasibility and efficiency of the proposed method. Full article
(This article belongs to the Section Sensor Networks)
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Open AccessArticle Compressive Multispectral Spectrum Sensing for Spectrum Cartography
Sensors 2018, 18(2), 387; doi:10.3390/s18020387
Received: 10 October 2017 / Revised: 5 January 2018 / Accepted: 11 January 2018 / Published: 29 January 2018
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Abstract
In the process of spectrum sensing applied to wireless communications, it is possible to build interference maps based on acquired power spectral values. This allows the characterization of spectral occupation, which is crucial to take management spectrum decisions. However, the amount of information
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In the process of spectrum sensing applied to wireless communications, it is possible to build interference maps based on acquired power spectral values. This allows the characterization of spectral occupation, which is crucial to take management spectrum decisions. However, the amount of information both in the space and frequency domains that needs to be processed generates an enormous amount of data with high transmission delays and high memory requirements. Meanwhile, compressive sensing is a technique that allows the reconstruction of sparse or compressible signals using fewer samples than those required by the Nyquist criterion. This paper presents a new model that uses compressed multispectral sampling for spectrum sensing. The aim is to reduce the number of data required for the storage and the subsequent construction of power spectral maps with geo-referenced information in different frequency bands. This model is based on architectures that use compressive sensing to analyze multispectral images. The operation of a centralized manager is presented in order to select the power data of different sensors by binary patterns. These sensors are located in different geographical positions. The centralized manager reconstructs a data cube with the transmitted power and frequency of operation of all the sensors based on the samples taken and applying multispectral sensing techniques. The results show that this multispectral data cube can be built with 50% of the samples generated by the devices, and the spectrum cartography information can be stored using only 6.25% of the original data. Full article
(This article belongs to the Section Physical Sensors)
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Open AccessArticle Feature Extraction of Electronic Nose Signals Using QPSO-Based Multiple KFDA Signal Processing
Sensors 2018, 18(2), 388; doi:10.3390/s18020388
Received: 21 November 2017 / Revised: 8 January 2018 / Accepted: 26 January 2018 / Published: 29 January 2018
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Abstract
The aim of this research was to enhance the classification accuracy of an electronic nose (E-nose) in different detecting applications. During the learning process of the E-nose to predict the types of different odors, the prediction accuracy was not quite satisfying because the
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The aim of this research was to enhance the classification accuracy of an electronic nose (E-nose) in different detecting applications. During the learning process of the E-nose to predict the types of different odors, the prediction accuracy was not quite satisfying because the raw features extracted from sensors’ responses were regarded as the input of a classifier without any feature extraction processing. Therefore, in order to obtain more useful information and improve the E-nose’s classification accuracy, in this paper, a Weighted Kernels Fisher Discriminant Analysis (WKFDA) combined with Quantum-behaved Particle Swarm Optimization (QPSO), i.e., QWKFDA, was presented to reprocess the original feature matrix. In addition, we have also compared the proposed method with quite a few previously existing ones including Principal Component Analysis (PCA), Locality Preserving Projections (LPP), Fisher Discriminant Analysis (FDA) and Kernels Fisher Discriminant Analysis (KFDA). Experimental results proved that QWKFDA is an effective feature extraction method for E-nose in predicting the types of wound infection and inflammable gases, which shared much higher classification accuracy than those of the contrast methods. Full article
(This article belongs to the Special Issue Artificial Olfaction and Taste)
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Open AccessArticle Implementation and Operational Analysis of an Interactive Intensive Care Unit within a Smart Health Context
Sensors 2018, 18(2), 389; doi:10.3390/s18020389
Received: 31 December 2017 / Revised: 23 January 2018 / Accepted: 26 January 2018 / Published: 29 January 2018
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Abstract
In the context of hospital management and operation, Intensive Care Units (ICU) are one of the most challenging in terms of time responsiveness and criticality, in which adequate resource management and signal processing play a key role in overall system performance. In this
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In the context of hospital management and operation, Intensive Care Units (ICU) are one of the most challenging in terms of time responsiveness and criticality, in which adequate resource management and signal processing play a key role in overall system performance. In this work, a context aware Intensive Care Unit is implemented and analyzed to provide scalable signal acquisition capabilities, as well as to provide tracking and access control. Wireless channel analysis is performed by means of hybrid optimized 3D Ray Launching deterministic simulation to assess potential interference impact as well as to provide required coverage/capacity thresholds for employed transceivers. Wireless system operation within the ICU scenario, considering conventional transceiver operation, is feasible in terms of quality of service for the complete scenario. Extensive measurements of overall interference levels have also been carried out, enabling subsequent adequate coverage/capacity estimations, for a set of Zigbee based nodes. Real system operation has been tested, with ad-hoc designed Zigbee wireless motes, employing lightweight communication protocols to minimize energy and bandwidth usage. An ICU information gathering application and software architecture for Visitor Access Control has been implemented, providing monitoring of the Boxes external doors and the identification of visitors via a RFID system. The results enable a solution to provide ICU access control and tracking capabilities previously not exploited, providing a step forward in the implementation of a Smart Health framework. Full article
(This article belongs to the Special Issue State-of-the-Art Sensors Technology in Spain 2017)
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Open AccessArticle The Effect of Zeolite Composition and Grain Size on Gas Sensing Properties of SnO2/Zeolite Sensor
Sensors 2018, 18(2), 390; doi:10.3390/s18020390
Received: 19 December 2017 / Revised: 24 January 2018 / Accepted: 24 January 2018 / Published: 29 January 2018
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Abstract
In order to improve the sensing properties of tin dioxide gas sensor, four kinds of different SiO2/Al2O3 ratio, different particle size of MFI type zeolites (ZSM-5) were coated on the SnO2 to prepared zeolite modified gas sensors,
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In order to improve the sensing properties of tin dioxide gas sensor, four kinds of different SiO2/Al2O3 ratio, different particle size of MFI type zeolites (ZSM-5) were coated on the SnO2 to prepared zeolite modified gas sensors, and the gas sensing properties were tested. The measurement results showed that the response values of ZSM-5 zeolite (SiO2/Al2O3 = 70, grain size 300 nm) coated SnO2 gas sensors to formaldehyde vapor were increased, and the response to acetone decreased compared with that of SnO2 gas sensor, indicating an improved selectivity property. The other three ZSM-5 zeolites with SiO2/Al2O3 70, 150 and 470, respectively, and grain sizes all around 1 μm coated SnO2 sensors did not show much difference with SnO2 sensor for the response properties to both formaldehyde and acetone. The sensing mechanism of ZSM-5 modified sensors was briefly analyzed. Full article
(This article belongs to the Special Issue Novel Sensors Based on Metal Oxide Films and Structures)
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Open AccessArticle Research on the Effects of Drying Temperature on Nitrogen Detection of Different Soil Types by Near Infrared Sensors
Sensors 2018, 18(2), 391; doi:10.3390/s18020391
Received: 7 December 2017 / Revised: 5 January 2018 / Accepted: 22 January 2018 / Published: 29 January 2018
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Abstract
Soil is a complicated system whose components and mechanisms are complex and difficult to be fully excavated and comprehended. Nitrogen is the key parameter supporting plant growth and development, and is the material basis of plant growth as well. An accurate grasp of
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Soil is a complicated system whose components and mechanisms are complex and difficult to be fully excavated and comprehended. Nitrogen is the key parameter supporting plant growth and development, and is the material basis of plant growth as well. An accurate grasp of soil nitrogen information is the premise of scientific fertilization in precision agriculture, where near infrared sensors are widely used for rapid detection of nutrients in soil. However, soil texture, soil moisture content and drying temperature all affect soil nitrogen detection using near infrared sensors. In order to investigate the effects of drying temperature on the nitrogen detection in black soil, loess and calcium soil, three kinds of soils were detected by near infrared sensors after 25 °C placement (ambient temperature), 50 °C drying (medium temperature), 80 °C drying (medium-high temperature) and 95 °C drying (high temperature). The successive projections algorithm based on multiple linear regression (SPA-MLR), partial least squares (PLS) and competitive adaptive reweighted squares (CARS) were used to model and analyze the spectral information of different soil types. The predictive abilities were assessed using the prediction correlation coefficients (RP), the root mean squared error of prediction (RMSEP), and the residual predictive deviation (RPD). The results showed that the loess (RP = 0.9721, RMSEP = 0.067 g/kg, RPD = 4.34) and calcium soil (RP = 0.9588, RMSEP = 0.094 g/kg, RPD = 3.89) obtained the best prediction accuracy after 95 °C drying. The detection results of black soil (RP = 0.9486, RMSEP = 0.22 g/kg, RPD = 2.82) after 80 °C drying were the optimum. In conclusion, drying temperature does have an obvious influence on the detection of soil nitrogen by near infrared sensors, and the suitable drying temperature for different soil types was of great significance in enhancing the detection accuracy. Full article
(This article belongs to the Special Issue Sensors in Agriculture)
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Open AccessArticle A Total Bounded Variation Approach to Low Visibility Estimation on Expressways
Sensors 2018, 18(2), 392; doi:10.3390/s18020392
Received: 28 December 2017 / Revised: 22 January 2018 / Accepted: 24 January 2018 / Published: 29 January 2018
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Abstract
Low visibility on expressways caused by heavy fog and haze is a main reason for traffic accidents. Real-time estimation of atmospheric visibility is an effective way to reduce traffic accident rates. With the development of computer technology, estimating atmospheric visibility via computer vision
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Low visibility on expressways caused by heavy fog and haze is a main reason for traffic accidents. Real-time estimation of atmospheric visibility is an effective way to reduce traffic accident rates. With the development of computer technology, estimating atmospheric visibility via computer vision becomes a research focus. However, the estimation accuracy should be enhanced since fog and haze are complex and time-varying. In this paper, a total bounded variation (TBV) approach to estimate low visibility (less than 300 m) is introduced. Surveillance images of fog and haze are processed as blurred images (pseudo-blurred images), while the surveillance images at selected road points on sunny days are handled as clear images, when considering fog and haze as noise superimposed on the clear images. By combining image spectrum and TBV, the features of foggy and hazy images can be extracted. The extraction results are compared with features of images on sunny days. Firstly, the low visibility surveillance images can be filtered out according to spectrum features of foggy and hazy images. For foggy and hazy images with visibility less than 300 m, the high-frequency coefficient ratio of Fourier (discrete cosine) transform is less than 20%, while the low-frequency coefficient ratio is between 100% and 120%. Secondly, the relationship between TBV and real visibility is established based on machine learning and piecewise stationary time series analysis. The established piecewise function can be used for visibility estimation. Finally, the visibility estimation approach proposed is validated based on real surveillance video data. The validation results are compared with the results of image contrast model. Besides, the big video data are collected from the Tongqi expressway, Jiangsu, China. A total of 1,782,000 frames were used and the relative errors of the approach proposed are less than 10%. Full article
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Open AccessArticle A Compact Operational Amplifier with Load-Insensitive Stability Compensation for High-Precision Transducer Interface
Sensors 2018, 18(2), 393; doi:10.3390/s18020393
Received: 20 December 2017 / Revised: 14 January 2018 / Accepted: 24 January 2018 / Published: 29 January 2018
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Abstract
High-resolution electronic interface circuits for transducers with nonlinear capacitive impedance need an operational amplifier, which is stable for a wide range of load capacitance. Such operational amplifier in a conventional design requires a large area for compensation capacitors, increasing costs and limiting applications.
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High-resolution electronic interface circuits for transducers with nonlinear capacitive impedance need an operational amplifier, which is stable for a wide range of load capacitance. Such operational amplifier in a conventional design requires a large area for compensation capacitors, increasing costs and limiting applications. In order to address this problem, we present a gain-boosted two-stage operational amplifier, whose frequency response compensation capacitor size is insensitive to the load capacitance and also orders of magnitude smaller compared to the conventional Miller-compensation capacitor that often dominates chip area. By exploiting pole-zero cancellation between a gain-boosting stage and the main amplifier stage, the compensation capacitor of the proposed operational amplifier becomes less dependent of load capacitance, so that it can also operate with a wide range of load capacitance. A prototype operational amplifier designed in 0.13- μ m complementary metal–oxide–semiconductor (CMOS) with a 400-fF compensation capacitor occupies 900- μ m 2 chip area and achieves 0.022–2.78-MHz unity gain bandwidth and over 65 phase margin with a load capacitance of 0.1–15 nF. The prototype amplifier consumes 7.6 μ W from a single 1.0-V supply. For a given compensation capacitor size and a chip area, the prototype design demonstrates the best reported performance trade-off on unity gain bandwidth, maximum stable load capacitance, and power consumption. Full article
(This article belongs to the Section Physical Sensors)
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Open AccessArticle What is the Best Configuration of Wearable Sensors to Measure Spatiotemporal Gait Parameters in Children with Cerebral Palsy?
Sensors 2018, 18(2), 394; doi:10.3390/s18020394
Received: 13 December 2017 / Revised: 23 January 2018 / Accepted: 25 January 2018 / Published: 30 January 2018
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Abstract
Wearable inertial devices have recently been used to evaluate spatiotemporal parameters of gait in daily life situations. Given the heterogeneity of gait patterns in children with cerebral palsy (CP), the sensor placement and analysis algorithm may influence the validity of the results. This
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Wearable inertial devices have recently been used to evaluate spatiotemporal parameters of gait in daily life situations. Given the heterogeneity of gait patterns in children with cerebral palsy (CP), the sensor placement and analysis algorithm may influence the validity of the results. This study aimed at comparing the spatiotemporal measurement performances of three wearable configurations defined by different sensor positioning on the lower limbs: (1) shanks and thighs, (2) shanks, and (3) feet. The three configurations were selected based on their potential to be used in daily life for children with CP and typically developing (TD) controls. For each configuration, dedicated gait analysis algorithms were used to detect gait events and compute spatiotemporal parameters. Fifteen children with CP and 11 TD controls were included. Accuracy, precision, and agreement of the three configurations were determined in comparison with an optoelectronic system as a reference. The three configurations were comparable for the evaluation of TD children and children with a low level of disability (CP-GMFCS I) whereas the shank-and-thigh-based configuration was more robust regarding children with a higher level of disability (CP-GMFCS II–III). Full article
(This article belongs to the Special Issue Sensors for Gait, Posture, and Health Monitoring)
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Open AccessArticle Analysis of 3D Scan Measurement Distribution with Application to a Multi-Beam Lidar on a Rotating Platform