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Sensors, Volume 17, Issue 6 (June 2017)

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Cover Story (view full-size image) In Italy, organic egg production farms use free-range housing systems with a big outdoor area and a [...] Read more.
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Open AccessArticle
Cell Selection Technique for Millimeter-Wave Cellular Systems with Hybrid Beamforming
Sensors 2017, 17(6), 1461; https://doi.org/10.3390/s17061461 - 21 Jun 2017
Cited by 2 | Viewed by 2140
Abstract
In this paper, a cell selection technique for millimeter-wave (mm-wave) cellular systems with hybrid beamforming is proposed. To select a serving cell, taking into account hybrid beamforming structures in a mm-wave cellular system, the angles of arrival and departure for all candidate cells [...] Read more.
In this paper, a cell selection technique for millimeter-wave (mm-wave) cellular systems with hybrid beamforming is proposed. To select a serving cell, taking into account hybrid beamforming structures in a mm-wave cellular system, the angles of arrival and departure for all candidate cells need to be estimated in the initialization stage, requiring a long processing time. To enable simultaneous multi-beam transmissions in a multi-cell environment, a cell and beam synchronization signal (CBSS) is proposed to carry beam IDs in conjunction with cell IDs. A serving cell maximizing the channel capacity of the hybrid beamformer is selected with the estimated channel information and the optimum precoder. The performance of the proposed technique is evaluated by a computer simulation with a spatial channel model in a simple model of a mm-wave cellular system. It is shown by simulation that the proposed technique with the CBSS can significantly reduce the processing time for channel estimation and cell selection, and can achieve additional gains in channel capacity, or in bit error rate, compared to that obtained by conventional techniques. Full article
(This article belongs to the Section Sensor Networks)
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Open AccessArticle
Analysis of Maneuvering Targets with Complex Motions by Two-Dimensional Product Modified Lv’s Distribution for Quadratic Frequency Modulation Signals
Sensors 2017, 17(6), 1460; https://doi.org/10.3390/s17061460 - 21 Jun 2017
Cited by 3 | Viewed by 1403
Abstract
For targets with complex motion, such as ships fluctuating with oceanic waves and high maneuvering airplanes, azimuth echo signals can be modeled as multicomponent quadratic frequency modulation (QFM) signals after migration compensation and phase adjustment. For the QFM signal model, the chirp rate [...] Read more.
For targets with complex motion, such as ships fluctuating with oceanic waves and high maneuvering airplanes, azimuth echo signals can be modeled as multicomponent quadratic frequency modulation (QFM) signals after migration compensation and phase adjustment. For the QFM signal model, the chirp rate (CR) and the quadratic chirp rate (QCR) are two important physical quantities, which need to be estimated. For multicomponent QFM signals, the cross terms create a challenge for detection, which needs to be addressed. In this paper, by employing a novel multi-scale parametric symmetric self-correlation function (PSSF) and modified scaled Fourier transform (mSFT), an effective parameter estimation algorithm is proposed—referred to as the Two-Dimensional product modified Lv’s distribution (2D-PMLVD)—for QFM signals. The 2D-PMLVD is simple and can be easily implemented by using fast Fourier transform (FFT) and complex multiplication. These measures are analyzed in the paper, including the principle, the cross term, anti-noise performance, and computational complexity. Compared to the other three representative methods, the 2D-PMLVD can achieve better anti-noise performance. The 2D-PMLVD, which is free of searching and has no identifiability problems, is more suitable for multicomponent situations. Through several simulations and analyses, the effectiveness of the proposed estimation algorithm is verified. Full article
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Open AccessArticle
Light Emitting Marker for Robust Vision-Based On-The-Spot Bacterial Growth Detection
Sensors 2017, 17(6), 1459; https://doi.org/10.3390/s17061459 - 21 Jun 2017
Cited by 3 | Viewed by 2593
Abstract
Simple methods using the striped pattern paper marker and FFT (fast Fourier transformation) have been proposed as alternatives to measuring the optical density for determining the level of bacterial growth. The marker-based method can be easily automated, but due to image-processing-base of the [...] Read more.
Simple methods using the striped pattern paper marker and FFT (fast Fourier transformation) have been proposed as alternatives to measuring the optical density for determining the level of bacterial growth. The marker-based method can be easily automated, but due to image-processing-base of the method, the presence of light or the color of the culture broth can disturb the detection process. This paper proposes a modified version of marker-FFT-based growth detection that uses a light emitting diode (LED) array as a marker. Since the marker itself can emit the light, the measurements can be performed even when there is no light source or the bacteria are cultured in a large volume of darkly colored broth. In addition, an LED marker can function as a region of interest (ROI) indicator in the image. We expect that the proposed LED-based marker system will allow more robust growth detection compared to conventional methods. Full article
(This article belongs to the Special Issue Sensors for Toxic and Pathogen Detection)
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Open AccessArticle
Ag Nanoparticles Drop-Casting Modification of Screen-Printed Electrodes for the Simultaneous Voltammetric Determination of Cu(II) and Pb(II)
Sensors 2017, 17(6), 1458; https://doi.org/10.3390/s17061458 - 21 Jun 2017
Cited by 13 | Viewed by 2091
Abstract
A new silver nanoparticle modified screen-printed electrode was developed and applied to the simultaneous determination of Pb(II) and Cu(II). Two different types of silver nanoparticles with different shapes and sizes, Ag nanoseeds and Ag nanoprisms, were microscopically characterized and three different carbon substrates, [...] Read more.
A new silver nanoparticle modified screen-printed electrode was developed and applied to the simultaneous determination of Pb(II) and Cu(II). Two different types of silver nanoparticles with different shapes and sizes, Ag nanoseeds and Ag nanoprisms, were microscopically characterized and three different carbon substrates, graphite, graphene and carbon nanofibers, were tested. The best analytical performance was achieved for the combination of Ag nanoseeds with a carbon nanofiber modified screen-printed electrode. The resulting sensor allowed the simultaneous determination of Pb(II) and Cu(II) at trace levels and its applicability to natural samples was successfully tested with a groundwater certified reference material, presenting high reproducibility and trueness. Full article
(This article belongs to the Special Issue Screen-Printed Electrodes)
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Open AccessArticle
Towards the Internet of Smart Trains: A Review on Industrial IoT-Connected Railways
Sensors 2017, 17(6), 1457; https://doi.org/10.3390/s17061457 - 21 Jun 2017
Cited by 37 | Viewed by 4572
Abstract
Nowadays, the railway industry is in a position where it is able to exploit the opportunities created by the IIoT (Industrial Internet of Things) and enabling communication technologies under the paradigm of Internet of Trains. This review details the evolution of communication technologies [...] Read more.
Nowadays, the railway industry is in a position where it is able to exploit the opportunities created by the IIoT (Industrial Internet of Things) and enabling communication technologies under the paradigm of Internet of Trains. This review details the evolution of communication technologies since the deployment of GSM-R, describing the main alternatives and how railway requirements, specifications and recommendations have evolved over time. The advantages of the latest generation of broadband communication systems (e.g., LTE, 5G, IEEE 802.11ad) and the emergence of Wireless Sensor Networks (WSNs) for the railway environment are also explained together with the strategic roadmap to ensure a smooth migration from GSM-R. Furthermore, this survey focuses on providing a holistic approach, identifying scenarios and architectures where railways could leverage better commercial IIoT capabilities. After reviewing the main industrial developments, short and medium-term IIoT-enabled services for smart railways are evaluated. Then, it is analyzed the latest research on predictive maintenance, smart infrastructure, advanced monitoring of assets, video surveillance systems, railway operations, Passenger and Freight Information Systems (PIS/FIS), train control systems, safety assurance, signaling systems, cyber security and energy efficiency. Overall, it can be stated that the aim of this article is to provide a detailed examination of the state-of-the-art of different technologies and services that will revolutionize the railway industry and will allow for confronting today challenges. Full article
(This article belongs to the Special Issue Sensors for Transportation)
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Open AccessArticle
Single-Lead Fetal ECG Extraction Based on a Parallel Marginalized Particle Filter
Sensors 2017, 17(6), 1456; https://doi.org/10.3390/s17061456 - 21 Jun 2017
Cited by 2 | Viewed by 1624
Abstract
This paper presents a novel method for extracting the fetal ECG (FECG) from a single-lead abdominal signal. A dynamical model for a modified abdominal signal is proposed, in which both the maternal ECG (MECG) and the FECG are modeled, and then a parallel [...] Read more.
This paper presents a novel method for extracting the fetal ECG (FECG) from a single-lead abdominal signal. A dynamical model for a modified abdominal signal is proposed, in which both the maternal ECG (MECG) and the FECG are modeled, and then a parallel marginalized particle filter (par-MPF) is used for tracking the abdominal signal. Finally, the FECG and MECG are simultaneously separated. Several experiments are conducted using both simulated and clinical signals. The results indicate that the method proposed in this paper effectively extracts the FECG and outperforms other Bayesian filtering algorithms. Full article
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Open AccessArticle
Soil Moisture Content Estimation Based on Sentinel-1 and Auxiliary Earth Observation Products. A Hydrological Approach
Sensors 2017, 17(6), 1455; https://doi.org/10.3390/s17061455 - 21 Jun 2017
Cited by 26 | Viewed by 2177
Abstract
A methodology for elaborating multi-temporal Sentinel-1 and Landsat 8 satellite images for estimating topsoil Soil Moisture Content (SMC) to support hydrological simulation studies is proposed. After pre-processing the remote sensing data, backscattering coefficient, Normalized Difference Vegetation Index (NDVI), thermal infrared temperature and incidence [...] Read more.
A methodology for elaborating multi-temporal Sentinel-1 and Landsat 8 satellite images for estimating topsoil Soil Moisture Content (SMC) to support hydrological simulation studies is proposed. After pre-processing the remote sensing data, backscattering coefficient, Normalized Difference Vegetation Index (NDVI), thermal infrared temperature and incidence angle parameters are assessed for their potential to infer ground measurements of SMC, collected at the top 5 cm. A non-linear approach using Artificial Neural Networks (ANNs) is tested. The methodology is applied in Western Crete, Greece, where a SMC gauge network was deployed during 2015. The performance of the proposed algorithm is evaluated using leave-one-out cross validation and sensitivity analysis. ANNs prove to be the most efficient in SMC estimation yielding R2 values between 0.7 and 0.9. The proposed methodology is used to support a hydrological simulation with the HEC-HMS model, applied at the Keramianos basin which is ungauged for SMC. Results and model sensitivity highlight the contribution of combining Sentinel-1 SAR and Landsat 8 images for improving SMC estimates and supporting hydrological studies. Full article
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Open AccessArticle
Compressed-Sensing Reconstruction Based on Block Sparse Bayesian Learning in Bearing-Condition Monitoring
Sensors 2017, 17(6), 1454; https://doi.org/10.3390/s17061454 - 21 Jun 2017
Cited by 2 | Viewed by 2153
Abstract
Remote monitoring of bearing conditions, using wireless sensor network (WSN), is a developing trend in the industrial field. In complicated industrial environments, WSN face three main constraints: low energy, less memory, and low operational capability. Conventional data-compression methods, which concentrate on data compression [...] Read more.
Remote monitoring of bearing conditions, using wireless sensor network (WSN), is a developing trend in the industrial field. In complicated industrial environments, WSN face three main constraints: low energy, less memory, and low operational capability. Conventional data-compression methods, which concentrate on data compression only, cannot overcome these limitations. Aiming at these problems, this paper proposed a compressed data acquisition and reconstruction scheme based on Compressed Sensing (CS) which is a novel signal-processing technique and applied it for bearing conditions monitoring via WSN. The compressed data acquisition is realized by projection transformation and can greatly reduce the data volume, which needs the nodes to process and transmit. The reconstruction of original signals is achieved in the host computer by complicated algorithms. The bearing vibration signals not only exhibit the sparsity property, but also have specific structures. This paper introduced the block sparse Bayesian learning (BSBL) algorithm which works by utilizing the block property and inherent structures of signals to reconstruct CS sparsity coefficients of transform domains and further recover the original signals. By using the BSBL, CS reconstruction can be improved remarkably. Experiments and analyses showed that BSBL method has good performance and is suitable for practical bearing-condition monitoring. Full article
(This article belongs to the Special Issue Smart Industrial Wireless Sensor Networks)
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Open AccessReview
Smartphone-Based Food Diagnostic Technologies: A Review
Sensors 2017, 17(6), 1453; https://doi.org/10.3390/s17061453 - 20 Jun 2017
Cited by 44 | Viewed by 5654
Abstract
A new generation of mobile sensing approaches offers significant advantages over traditional platforms in terms of test speed, control, low cost, ease-of-operation, and data management, and requires minimal equipment and user involvement. The marriage of novel sensing technologies with cellphones enables the development [...] Read more.
A new generation of mobile sensing approaches offers significant advantages over traditional platforms in terms of test speed, control, low cost, ease-of-operation, and data management, and requires minimal equipment and user involvement. The marriage of novel sensing technologies with cellphones enables the development of powerful lab-on-smartphone platforms for many important applications including medical diagnosis, environmental monitoring, and food safety analysis. This paper reviews the recent advancements and developments in the field of smartphone-based food diagnostic technologies, with an emphasis on custom modules to enhance smartphone sensing capabilities. These devices typically comprise multiple components such as detectors, sample processors, disposable chips, batteries and software, which are integrated with a commercial smartphone. One of the most important aspects of developing these systems is the integration of these components onto a compact and lightweight platform that requires minimal power. To date, researchers have demonstrated several promising approaches employing various sensing techniques and device configurations. We aim to provide a systematic classification according to the detection strategy, providing a critical discussion of strengths and weaknesses. We have also extended the analysis to the food scanning devices that are increasingly populating the Internet of Things (IoT) market, demonstrating how this field is indeed promising, as the research outputs are quickly capitalized on new start-up companies. Full article
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Open AccessArticle
MinT: Middleware for Cooperative Interaction of Things
Sensors 2017, 17(6), 1452; https://doi.org/10.3390/s17061452 - 20 Jun 2017
Cited by 5 | Viewed by 2094
Abstract
This paper proposes an Internet of Things (IoT) middleware called Middleware for Cooperative Interaction of Things (MinT). MinT supports a fully distributed IoT environment in which IoT devices directly connect to peripheral devices easily construct a local or global network, and share their [...] Read more.
This paper proposes an Internet of Things (IoT) middleware called Middleware for Cooperative Interaction of Things (MinT). MinT supports a fully distributed IoT environment in which IoT devices directly connect to peripheral devices easily construct a local or global network, and share their data in an energy efficient manner. MinT provides a sensor abstract layer, a system layer and an interaction layer. These enable integrated sensing device operations, efficient resource management, and active interconnection between peripheral IoT devices. In addition, MinT provides a high-level API to develop IoT devices easily for IoT device developers. We aim to enhance the energy efficiency and performance of IoT devices through the performance improvements offered by MinT resource management and request processing. The experimental results show that the average request rate increased by 25% compared to Californium, which is a middleware for efficient interaction in IoT environments with powerful performance, an average response time decrease of 90% when resource management was used, and power consumption decreased by up to 68%. Finally, the proposed platform can reduce the latency and power consumption of IoT devices. 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
Fiber Optic Thermo-Hygrometers for Soil Moisture Monitoring
Sensors 2017, 17(6), 1451; https://doi.org/10.3390/s17061451 - 20 Jun 2017
Cited by 9 | Viewed by 3004
Abstract
This work deals with the fabrication, prototyping, and experimental validation of a fiber optic thermo-hygrometer-based soil moisture sensor, useful for rainfall-induced landslide prevention applications. In particular, we recently proposed a new generation of fiber Bragg grating (FBGs)-based soil moisture sensors for irrigation purposes. [...] Read more.
This work deals with the fabrication, prototyping, and experimental validation of a fiber optic thermo-hygrometer-based soil moisture sensor, useful for rainfall-induced landslide prevention applications. In particular, we recently proposed a new generation of fiber Bragg grating (FBGs)-based soil moisture sensors for irrigation purposes. This device was realized by integrating, inside a customized aluminum protection package, a FBG thermo-hygrometer with a polymer micro-porous membrane. Here, we first verify the limitations, in terms of the volumetric water content (VWC) measuring range, of this first version of the soil moisture sensor for its exploitation in landslide prevention applications. Successively, we present the development, prototyping, and experimental validation of a novel, optimized version of a soil VWC sensor, still based on a FBG thermo-hygrometer, but able to reliably monitor, continuously and in real-time, VWC values up to 37% when buried in the soil. Full article
(This article belongs to the Special Issue Humidity Sensors)
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Open AccessReview
Current Research in Lidar Technology Used for the Remote Sensing of Atmospheric Aerosols
Sensors 2017, 17(6), 1450; https://doi.org/10.3390/s17061450 - 20 Jun 2017
Cited by 7 | Viewed by 3099
Abstract
Lidars are active optical remote sensing instruments with unique capabilities for atmospheric sounding. A manifold of atmospheric variables can be profiled using different types of lidar: concentration of species, wind speed, temperature, etc. Among them, measurement of the properties of aerosol particles, whose [...] Read more.
Lidars are active optical remote sensing instruments with unique capabilities for atmospheric sounding. A manifold of atmospheric variables can be profiled using different types of lidar: concentration of species, wind speed, temperature, etc. Among them, measurement of the properties of aerosol particles, whose influence in many atmospheric processes is important but is still poorly stated, stands as one of the main fields of application of current lidar systems. This paper presents a review on fundamentals, technology, methodologies and state-of-the art of the lidar systems used to obtain aerosol information. Retrieval of structural (aerosol layers profiling), optical (backscatter and extinction coefficients) and microphysical (size, shape and type) properties requires however different levels of instrumental complexity; this general outlook is structured following a classification that attends these criteria. Thus, elastic systems (detection only of emitted frequencies), Raman systems (detection also of Raman frequency-shifted spectral lines), high spectral resolution lidars, systems with depolarization measurement capabilities and multi-wavelength instruments are described, and the fundamentals in which the retrieval of aerosol parameters is based is in each case detailed. Full article
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Open AccessArticle
Measurement of Rayleigh Wave Beams Using Angle Beam Wedge Transducers as the Transmitter and Receiver with Consideration of Beam Spreading
Sensors 2017, 17(6), 1449; https://doi.org/10.3390/s17061449 - 20 Jun 2017
Cited by 5 | Viewed by 2154
Abstract
A theoretical model, along with experimental verification, is developed to describe the generation, propagation and reception of a Rayleigh wave using angle beam wedge transducers. The Rayleigh wave generation process using an angle beam wedge transducer is analyzed, and the actual Rayleigh wave [...] Read more.
A theoretical model, along with experimental verification, is developed to describe the generation, propagation and reception of a Rayleigh wave using angle beam wedge transducers. The Rayleigh wave generation process using an angle beam wedge transducer is analyzed, and the actual Rayleigh wave sound source distributions are evaluated numerically. Based on the reciprocity theorem and considering the actual sound source, the Rayleigh wave beams are modeled using an area integral method. The leaky Rayleigh wave theory is introduced to investigate the reception of the Rayleigh wave using the angle beam wedge transducers, and the effects of the wave spreading in the wedge and transducer size are considered in the reception process. The effects of attenuations of the Rayleigh wave and leaky Rayleigh wave are discussed, and the received wave results with different sizes of receivers are compared. The experiments are conducted using two angle beam wedge transducers to measure the Rayleigh wave, and the measurement results are compared with the predictions using different theoretical models. It is shown that the proposed model which considers the wave spreading in both the sample and wedges can be used to interpret the measurements reasonably. Full article
(This article belongs to the Special Issue Surface Acoustic Wave and Bulk Acoustic Wave Sensors)
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Open AccessArticle
On the Application of Image Processing Methods for Bubble Recognition to the Study of Subcooled Flow Boiling of Water in Rectangular Channels
Sensors 2017, 17(6), 1448; https://doi.org/10.3390/s17061448 - 20 Jun 2017
Cited by 1 | Viewed by 1535
Abstract
This work introduces the use of machine vision in the massive bubble recognition process, which supports the validation of boiling models involving bubble dynamics, as well as nucleation frequency, active site density and size of the bubbles. The two algorithms presented are meant [...] Read more.
This work introduces the use of machine vision in the massive bubble recognition process, which supports the validation of boiling models involving bubble dynamics, as well as nucleation frequency, active site density and size of the bubbles. The two algorithms presented are meant to be run employing quite standard images of the bubbling process, recorded in general-purpose boiling facilities. The recognition routines are easily adaptable to other facilities if a minimum number of precautions are taken in the setup and in the treatment of the information. Both the side and front projections of subcooled flow-boiling phenomenon over a plain plate are covered. Once all of the intended bubbles have been located in space and time, the proper post-process of the recorded data become capable of tracking each of the recognized bubbles, sketching their trajectories and size evolution, locating the nucleation sites, computing their diameters, and so on. After validating the algorithm’s output against the human eye and data from other researchers, machine vision systems have been demonstrated to be a very valuable option to successfully perform the recognition process, even though the optical analysis of bubbles has not been set as the main goal of the experimental facility. Full article
(This article belongs to the Section Physical Sensors)
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Open AccessArticle
Dual-Channel Cosine Function Based ITD Estimation for Robust Speech Separation
Sensors 2017, 17(6), 1447; https://doi.org/10.3390/s17061447 - 20 Jun 2017
Cited by 1 | Viewed by 1498
Abstract
In speech separation tasks, many separation methods have the limitation that the microphones are closely spaced, which means that these methods are unprevailing for phase wrap-around. In this paper, we present a novel speech separation scheme by using two microphones that does not [...] Read more.
In speech separation tasks, many separation methods have the limitation that the microphones are closely spaced, which means that these methods are unprevailing for phase wrap-around. In this paper, we present a novel speech separation scheme by using two microphones that does not have this restriction. The technique utilizes the estimation of interaural time difference (ITD) statistics and binary time-frequency mask for the separation of mixed speech sources. The novelties of the paper consist in: (1) the extended application of delay-and-sum beamforming (DSB) and cosine function for ITD calculation; and (2) the clarification of the connection between ideal binary mask and DSB amplitude ratio. Our objective quality evaluation experiments demonstrate the effectiveness of the proposed method. Full article
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Open AccessArticle
A New Privacy-Preserving Handover Authentication Scheme for Wireless Networks
Sensors 2017, 17(6), 1446; https://doi.org/10.3390/s17061446 - 20 Jun 2017
Viewed by 1601
Abstract
Handover authentication is a critical issue in wireless networks, which is being used to ensure mobile nodes wander over multiple access points securely and seamlessly. A variety of handover authentication schemes for wireless networks have been proposed in the literature. Unfortunately, existing handover [...] Read more.
Handover authentication is a critical issue in wireless networks, which is being used to ensure mobile nodes wander over multiple access points securely and seamlessly. A variety of handover authentication schemes for wireless networks have been proposed in the literature. Unfortunately, existing handover authentication schemes are vulnerable to a few security attacks, or incur high communication and computation costs. Recently, He et al. proposed a handover authentication scheme PairHand and claimed it can resist various attacks without rigorous security proofs. In this paper, we show that PairHand does not meet forward secrecy and strong anonymity. More seriously, it is vulnerable to key compromise attack, where an adversary can recover the private key of any mobile node. Then, we propose a new efficient and provably secure handover authentication scheme for wireless networks based on elliptic curve cryptography. Compared with existing schemes, our proposed scheme can resist key compromise attack, and achieves forward secrecy and strong anonymity. Moreover, it is more efficient in terms of computation and communication. Full article
(This article belongs to the Special Issue Mobile Sensing Applications)
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Open AccessReview
Fano Effect and Quantum Entanglement in Hybrid Semiconductor Quantum Dot-Metal Nanoparticle System
Sensors 2017, 17(6), 1445; https://doi.org/10.3390/s17061445 - 20 Jun 2017
Viewed by 2059
Abstract
In this paper, we review the investigation for the light-matter interaction between surface plasmon field in metal nanoparticle (MNP) and the excitons in semiconductor quantum dots (SQDs) in hybrid SQD-MNP system under the full quantum description. The exciton-plasmon interaction gives rise to the [...] Read more.
In this paper, we review the investigation for the light-matter interaction between surface plasmon field in metal nanoparticle (MNP) and the excitons in semiconductor quantum dots (SQDs) in hybrid SQD-MNP system under the full quantum description. The exciton-plasmon interaction gives rise to the modified decay rate and the exciton energy shift which are related to the exciton energy by using a quantum transformation method. We illustrate the responses of the hybrid SQD-MNP system to external field, and reveal Fano effect shown in the absorption spectrum. We demonstrate quantum entanglement between two SQD mediated by surface plasmon field. In the absence of a laser field, concurrence of quantum entanglement will disappear after a few ns. If the laser field is present, the steady states appear, so that quantum entanglement produced will reach a steady-state entanglement. Because one of all optical pathways to induce Fano effect refers to the generation of quantum entangled states, It is shown that the concurrence of quantum entanglement can be obtained by observation for Fano effect. In a hybrid system including two MNP and a SQD, because the two Fano quantum interference processes share a segment of all optical pathways, there is correlation between the Fano effects of the two MNP. The investigations for the light-matter interaction in hybrid SQD-MNP system can pave the way for the development of the optical processing devices and quantum information based on the exciton-plasmon interaction. Full article
(This article belongs to the Special Issue Surface Plasmon Resonance Sensing)
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Open AccessFeature PaperArticle
Fabrication and Characterization of Plasmonic Nanopores with Cavities in the Solid Support
Sensors 2017, 17(6), 1444; https://doi.org/10.3390/s17061444 - 20 Jun 2017
Cited by 6 | Viewed by 2217
Abstract
Plasmonic nanostructures are widely used for various sensing applications by monitoring changes in refractive index through optical spectroscopy or as substrates for surface enhanced Raman spectroscopy. However, in most practical situations conventional surface plasmon resonance is preferred for biomolecular interaction analysis because of [...] Read more.
Plasmonic nanostructures are widely used for various sensing applications by monitoring changes in refractive index through optical spectroscopy or as substrates for surface enhanced Raman spectroscopy. However, in most practical situations conventional surface plasmon resonance is preferred for biomolecular interaction analysis because of its high resolution in surface coverage and the simple single-material planar interface. Still, plasmonic nanostructures may find unique sensing applications, for instance when the nanoscale geometry itself is of interest. This calls for new methods to prepare nanoscale particles and cavities with controllable dimensions and curvature. In this work, we present two types of plasmonic nanopores where the solid support underneath a nanohole array has been etched, thereby creating cavities denoted as ‘nanowells’ or ‘nanocaves’ depending on the degree of anisotropy (dry or wet etch). The refractometric sensitivity is shown to be enhanced upon removing the solid support because of an increased probing volume and a shift of the asymmetric plasmonic field towards the liquid side of the finite gold film. Furthermore, the structures exhibit different spectral changes upon binding inside the cavities compared to the gold surface, which means that the structures can be used for location-specific detection. Other sensing applications are also suggested. Full article
(This article belongs to the Special Issue Micro and Nanofabrication Technologies for Biosensors)
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Open AccessArticle
Development of a Novel Transparent Flexible Capacitive Micromachined Ultrasonic Transducer
Sensors 2017, 17(6), 1443; https://doi.org/10.3390/s17061443 - 20 Jun 2017
Cited by 7 | Viewed by 1923
Abstract
This paper presents the world’s first transparent flexible capacitive micromachined ultrasonic transducer (CMUT) that was fabricated through a roll-lamination technique. This polymer-based CMUT has advantages of transparency, flexibility, and non-contacting detection which provide unique functions in display panel applications. Comprising an indium tin [...] Read more.
This paper presents the world’s first transparent flexible capacitive micromachined ultrasonic transducer (CMUT) that was fabricated through a roll-lamination technique. This polymer-based CMUT has advantages of transparency, flexibility, and non-contacting detection which provide unique functions in display panel applications. Comprising an indium tin oxide-polyethylene terephthalate (ITO-PET) substrate, SU-8 sidewall and vibrating membranes, and silver nanowire transparent electrode, the transducer has visible-light transmittance exceeding 80% and can operate on curved surfaces with a 40 mm radius of curvature. Unlike the traditional silicon-based high temperature process, the CMUT can be fabricated on a flexible substrate at a temperature below 100 °C to reduce residual stress introduced at high temperature. The CMUT on the curved surfaces can detect a flat target and finger at distances up to 50 mm and 40 mm, respectively. The transparent flexible CMUT provides a better human-machine interface than existing touch panels because it can be integrated with a display panel for non-contacting control in a health conscious environment and the flexible feature is critical for curved display and wearable electronics. Full article
(This article belongs to the Section Physical Sensors)
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Open AccessArticle
Micro-Viscometer for Measuring Shear-Varying Blood Viscosity over a Wide-Ranging Shear Rate
Sensors 2017, 17(6), 1442; https://doi.org/10.3390/s17061442 - 20 Jun 2017
Cited by 14 | Viewed by 2399
Abstract
In this study, a micro-viscometer is developed for measuring shear-varying blood viscosity over a wide-ranging shear rate. The micro-viscometer consists of 10 microfluidic channel arrays, each of which has a different micro-channel width. The proposed design enables the retrieval of 10 different shear [...] Read more.
In this study, a micro-viscometer is developed for measuring shear-varying blood viscosity over a wide-ranging shear rate. The micro-viscometer consists of 10 microfluidic channel arrays, each of which has a different micro-channel width. The proposed design enables the retrieval of 10 different shear rates from a single flow rate, thereby enabling the measurement of shear-varying blood viscosity with a fixed flow rate condition. For this purpose, an optimal design that guarantees accurate viscosity measurement is selected from a parametric study. The functionality of the micro-viscometer is verified by both numerical and experimental studies. The proposed micro-viscometer shows 6.8% (numerical) and 5.3% (experimental) in relative error when compared to the result from a standard rotational viscometer. Moreover, a reliability test is performed by repeated measurement (N = 7), and the result shows 2.69 ± 2.19% for the mean relative error. Accurate viscosity measurements are performed on blood samples with variations in the hematocrit (35%, 45%, and 55%), which significantly influences blood viscosity. Since the blood viscosity correlated with various physical parameters of the blood, the micro-viscometer is anticipated to be a significant advancement for realization of blood on a chip. Full article
(This article belongs to the Special Issue Microfluidic Sensors and Control Devices)
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Open AccessArticle
Image Mosaicking Approach for a Double-Camera System in the GaoFen2 Optical Remote Sensing Satellite Based on the Big Virtual Camera
Sensors 2017, 17(6), 1441; https://doi.org/10.3390/s17061441 - 20 Jun 2017
Cited by 5 | Viewed by 1907
Abstract
The linear array push broom imaging mode is widely used for high resolution optical satellites (HROS). Using double-cameras attached by a high-rigidity support along with push broom imaging is one method to enlarge the field of view while ensuring high resolution. High accuracy [...] Read more.
The linear array push broom imaging mode is widely used for high resolution optical satellites (HROS). Using double-cameras attached by a high-rigidity support along with push broom imaging is one method to enlarge the field of view while ensuring high resolution. High accuracy image mosaicking is the key factor of the geometrical quality of complete stitched satellite imagery. This paper proposes a high accuracy image mosaicking approach based on the big virtual camera (BVC) in the double-camera system on the GaoFen2 optical remote sensing satellite (GF2). A big virtual camera can be built according to the rigorous imaging model of a single camera; then, each single image strip obtained by each TDI-CCD detector can be re-projected to the virtual detector of the big virtual camera coordinate system using forward-projection and backward-projection to obtain the corresponding single virtual image. After an on-orbit calibration and relative orientation, the complete final virtual image can be obtained by stitching the single virtual images together based on their coordinate information on the big virtual detector image plane. The paper subtly uses the concept of the big virtual camera to obtain a stitched image and the corresponding high accuracy rational function model (RFM) for concurrent post processing. Experiments verified that the proposed method can achieve seamless mosaicking while maintaining the geometric accuracy. Full article
(This article belongs to the Special Issue Multi-Sensor Integration and Fusion)
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Open AccessArticle
The Ship Movement Trajectory Prediction Algorithm Using Navigational Data Fusion
Sensors 2017, 17(6), 1432; https://doi.org/10.3390/s17061432 - 20 Jun 2017
Cited by 13 | Viewed by 2548
Abstract
It is essential for the marine navigator conducting maneuvers of his ship at sea to know future positions of himself and target ships in a specific time span to effectively solve collision situations. This article presents an algorithm of ship movement trajectory prediction, [...] Read more.
It is essential for the marine navigator conducting maneuvers of his ship at sea to know future positions of himself and target ships in a specific time span to effectively solve collision situations. This article presents an algorithm of ship movement trajectory prediction, which, through data fusion, takes into account measurements of the ship’s current position from a number of doubled autonomous devices. This increases the reliability and accuracy of prediction. The algorithm has been implemented in NAVDEC, a navigation decision support system and practically used on board ships. Full article
(This article belongs to the Special Issue Soft Sensors and Intelligent Algorithms for Data Fusion)
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Open AccessArticle
Rapid Global Calibration Technology for Hybrid Visual Inspection System
Sensors 2017, 17(6), 1440; https://doi.org/10.3390/s17061440 - 19 Jun 2017
Cited by 5 | Viewed by 1866
Abstract
Vision-based methods for product quality inspection are playing an increasingly important role in modern industries for their good performance and high efficiency. A hybrid visual inspection system, which consists of an industrial robot with a flexible sensor and several stationary sensors, has been [...] Read more.
Vision-based methods for product quality inspection are playing an increasingly important role in modern industries for their good performance and high efficiency. A hybrid visual inspection system, which consists of an industrial robot with a flexible sensor and several stationary sensors, has been widely applied in mass production, especially in automobile manufacturing. In this paper, a rapid global calibration method for the hybrid visual inspection system is proposed. Global calibration of a flexible sensor is performed first based on the robot kinematic. Then, with the aid of the calibrated flexible sensor, stationary sensors are calibrated globally one by one based on homography. Only a standard sphere and an auxiliary target with a 2D planar pattern are applied during the system global calibration, and the calibration process can be easily re-performed during the system’s periodical maintenance. An error compensation method is proposed for the hybrid inspection system, and the final accuracy of the hybrid system is evaluated with the deviation and correlation coefficient between the measured results of the hybrid system and Coordinate Measuring Machine (CMM). An accuracy verification experiment shows that deviation of over 95% of featured points are less than ±0.3 mm, and the correlation coefficients of over 85% of points are larger than 0.7. Full article
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Open AccessArticle
Adhesive Defect Monitoring of Glass Fiber Epoxy Plate Using an Impedance-Based Non-Destructive Testing Method for Multiple Structures
Sensors 2017, 17(6), 1439; https://doi.org/10.3390/s17061439 - 19 Jun 2017
Cited by 4 | Viewed by 2258
Abstract
The emergence of composite materials has revolutionized the approach to building engineering structures. With the number of applications for composites increasing every day, maintaining structural integrity is of utmost importance. For composites, adhesive bonding is usually the preferred choice over the mechanical fastening [...] Read more.
The emergence of composite materials has revolutionized the approach to building engineering structures. With the number of applications for composites increasing every day, maintaining structural integrity is of utmost importance. For composites, adhesive bonding is usually the preferred choice over the mechanical fastening method, and monitoring for delamination is an essential factor in the field of composite materials. In this study, a non-destructive method known as the electromechanical impedance method is used with an approach of monitoring multiple areas by specifying certain frequency ranges to correspond to a certain test specimen. Experiments are conducted using various numbers of stacks created by attaching glass fiber epoxy composite plates onto one another, and two different debonding damage types are introduced to evaluate the performance of the multiple monitoring electromechanical impedance method. Full article
(This article belongs to the Special Issue Sensor Technologies for Health Monitoring of Composite Structures)
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Open AccessArticle
A New Filtering and Smoothing Algorithm for Railway Track Surveying Based on Landmark and IMU/Odometer
Sensors 2017, 17(6), 1438; https://doi.org/10.3390/s17061438 - 19 Jun 2017
Cited by 6 | Viewed by 2243
Abstract
High-accuracy railway track surveying is essential for railway construction and maintenance. The traditional approaches based on total station equipment are not efficient enough since high precision surveying frequently needs static measurements. This paper proposes a new filtering and smoothing algorithm based on the [...] Read more.
High-accuracy railway track surveying is essential for railway construction and maintenance. The traditional approaches based on total station equipment are not efficient enough since high precision surveying frequently needs static measurements. This paper proposes a new filtering and smoothing algorithm based on the IMU/odometer and landmarks integration for the railway track surveying. In order to overcome the difficulty of estimating too many error parameters with too few landmark observations, a new model with completely observable error states is established by combining error terms of the system. Based on covariance analysis, the analytical relationship between the railway track surveying accuracy requirements and equivalent gyro drifts including bias instability and random walk noise are established. Experiment results show that the accuracy of the new filtering and smoothing algorithm for railway track surveying can reach 1 mm (1σ) when using a Ring Laser Gyroscope (RLG)-based Inertial Measurement Unit (IMU) with gyro bias instability of 0.03°/h and random walk noise of 0.005 °h while control points of the track control network (CPIII) position observations are provided by the optical total station in about every 60 m interval. The proposed approach can satisfy at the same time the demands of high accuracy and work efficiency for railway track surveying. Full article
(This article belongs to the Special Issue Sensors for Transportation)
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Open AccessArticle
Localization Framework for Real-Time UAV Autonomous Landing: An On-Ground Deployed Visual Approach
Sensors 2017, 17(6), 1437; https://doi.org/10.3390/s17061437 - 19 Jun 2017
Cited by 11 | Viewed by 2162
Abstract
[-5]One of the greatest challenges for fixed-wing unmanned aircraft vehicles (UAVs) is safe landing. Hereafter, an on-ground deployed visual approach is developed in this paper. This approach is definitely suitable for landing within the global navigation satellite system (GNSS)-denied environments. As for applications, [...] Read more.
[-5]One of the greatest challenges for fixed-wing unmanned aircraft vehicles (UAVs) is safe landing. Hereafter, an on-ground deployed visual approach is developed in this paper. This approach is definitely suitable for landing within the global navigation satellite system (GNSS)-denied environments. As for applications, the deployed guidance system makes full use of the ground computing resource and feedbacks the aircraft’s real-time localization to its on-board autopilot. Under such circumstances, a separate long baseline stereo architecture is proposed to possess an extendable baseline and wide-angle field of view (FOV) against the traditional fixed baseline schemes. Furthermore, accuracy evaluation of the new type of architecture is conducted by theoretical modeling and computational analysis. Dataset-driven experimental results demonstrate the feasibility and effectiveness of the developed approach. Full article
(This article belongs to the Special Issue UAV or Drones for Remote Sensing Applications) Printed Edition available
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Open AccessArticle
Active2Gether: A Personalized m-Health Intervention to Encourage Physical Activity
Sensors 2017, 17(6), 1436; https://doi.org/10.3390/s17061436 - 19 Jun 2017
Cited by 8 | Viewed by 2311
Abstract
Lack of physical activity is an increasingly important health risk. Modern mobile technology, such as smartphones and digital measurement devices, provides new opportunities to tackle physical inactivity. This paper describes the design of a system that aims to encourage young adults to be [...] Read more.
Lack of physical activity is an increasingly important health risk. Modern mobile technology, such as smartphones and digital measurement devices, provides new opportunities to tackle physical inactivity. This paper describes the design of a system that aims to encourage young adults to be more physically active. The system monitors the user’s behavior, uses social comparison and provides tailored and personalized feedback based on intelligent reasoning mechanisms. As the name suggests, social processes play an important role in the Active2Gether system. The design choices and functioning of the system are described in detail. Based on the experiences with the development and deployment of the system, a number of lessons learnt are provided and suggestions are proposed for improvements in future developments. Full article
(This article belongs to the Special Issue Smart Sensing Technologies for Personalised Coaching)
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Open AccessArticle
Design and Performance of a Portable and Multichannel SPR Device
Sensors 2017, 17(6), 1435; https://doi.org/10.3390/s17061435 - 19 Jun 2017
Cited by 6 | Viewed by 2164
Abstract
A portable multichannel surface plasmon resonance (SPR) biosensor device is presented in this study. As an optical biosensor device, the core component of its light path is a semi-cylindrical prism, which is used as the coupling unit for the excitation of the SPR [...] Read more.
A portable multichannel surface plasmon resonance (SPR) biosensor device is presented in this study. As an optical biosensor device, the core component of its light path is a semi-cylindrical prism, which is used as the coupling unit for the excitation of the SPR phenomena. Based on this prism, a wedge-shaped incident light beam including a continuous angle range (10°) is chosen to replace the commonly-used parallel light beam in traditional SPR devices, in which the incident angle is adjusted by a sophisticated mechanical system. Thus, complicated, cumbersome, and costly mechanical structures can be avoided in this design. Furthermore, the selection of a small and high-stability semiconductor laser and matrix CCD detector as well as a microfluidic system aids in the realization of a miniaturized and multichannel device. Several different samples were used to test the performance of this new device. For ethanol with different concentrations, the sensing response was of good linear relativity with the concentration (Y = 3.17143X + 2.81518, R2 = 0.97661). Mouse IgG and goat anti-mouse IgG were used as biological samples for immunological analysis, and BSA as the control group. Good specific recognition between mouse IgG and goat anti-mouse IgG has been achieved. The detection limit of antibody to antigen coated on the sensing surface was about 25 mg/L without surface modification. Full article
(This article belongs to the Special Issue Surface Plasmon Resonance Sensing)
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Open AccessArticle
A Novel Extreme Learning Machine Classification Model for e-Nose Application Based on the Multiple Kernel Approach
Sensors 2017, 17(6), 1434; https://doi.org/10.3390/s17061434 - 19 Jun 2017
Cited by 11 | Viewed by 2166
Abstract
A novel classification model, named the quantum-behaved particle swarm optimization (QPSO)-based weighted multiple kernel extreme learning machine (QWMK-ELM), is proposed in this paper. Experimental validation is carried out with two different electronic nose (e-nose) datasets. Being different from the existing multiple kernel extreme [...] Read more.
A novel classification model, named the quantum-behaved particle swarm optimization (QPSO)-based weighted multiple kernel extreme learning machine (QWMK-ELM), is proposed in this paper. Experimental validation is carried out with two different electronic nose (e-nose) datasets. Being different from the existing multiple kernel extreme learning machine (MK-ELM) algorithms, the combination coefficients of base kernels are regarded as external parameters of single-hidden layer feedforward neural networks (SLFNs). The combination coefficients of base kernels, the model parameters of each base kernel, and the regularization parameter are optimized by QPSO simultaneously before implementing the kernel extreme learning machine (KELM) with the composite kernel function. Four types of common single kernel functions (Gaussian kernel, polynomial kernel, sigmoid kernel, and wavelet kernel) are utilized to constitute different composite kernel functions. Moreover, the method is also compared with other existing classification methods: extreme learning machine (ELM), kernel extreme learning machine (KELM), k-nearest neighbors (KNN), support vector machine (SVM), multi-layer perceptron (MLP), radical basis function neural network (RBFNN), and probabilistic neural network (PNN). The results have demonstrated that the proposed QWMK-ELM outperforms the aforementioned methods, not only in precision, but also in efficiency for gas classification. Full article
(This article belongs to the Special Issue Electronic Tongues and Electronic Noses)
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Open AccessArticle
Two Novel Two-Stage Direction of Arrival Estimation Algorithms for Two-Dimensional Mixed Noncircular and Circular Sources
Sensors 2017, 17(6), 1433; https://doi.org/10.3390/s17061433 - 18 Jun 2017
Cited by 3 | Viewed by 1297
Abstract
This paper addresses the two-dimensional (2D) direction-of-arrival (DOA) estimation problem with two novel methods for mixed noncircular and circular signals. The first proposed method is named the two-stage direction-of-arrival matrix (TSDOAM) method, and the other is called the two-stage rank reduction (TSRARE) method. [...] Read more.
This paper addresses the two-dimensional (2D) direction-of-arrival (DOA) estimation problem with two novel methods for mixed noncircular and circular signals. The first proposed method is named the two-stage direction-of-arrival matrix (TSDOAM) method, and the other is called the two-stage rank reduction (TSRARE) method. The proposed methods utilize both the circularity and the direction-of-arrival differences between the noncircular and circular sources to estimate the 2D directions-of-arrival (DOAs). The maximum detectable 2D angle parameters of the TSDOAM and TSRARE methods are twice those of the existing methods. Moreover, the TSRARE method can detect more incident signals than the TSDOAM method due to the array aperture of two parallel uniform linear arrays (ULAs) being fully utilized. Simulation results show that compared to the existing methods for the small angle separation of 2D directions-of-arrival, the two proposed methods perform well in terms of the signal-to-noise ratio (SNR) and snapshots. Full article
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