Journal of Sensors The latest articles from Hindawi Publishing Corporation © 2016 , Hindawi Publishing Corporation . All rights reserved. Light-Weight and Versatile Monitor for a Self-Adaptive Software Framework for IoT Systems Thu, 01 Dec 2016 09:27:15 +0000 Today, various Internet of Things (IoT) devices and applications are being developed. Such IoT devices have different hardware (HW) and software (SW) capabilities; therefore, most applications require customization when IoT devices are changed or new applications are created. However, the applications executed on these devices are not optimized for power and performance because IoT device systems do not provide suitable static and dynamic information about fast-changing system resources and applications. Therefore, this paper proposes a light-weight and versatile monitor for a self-adaptive software framework to automatically control system resources according to the system status. The monitor helps running applications guarantee low power consumption and high performance for an optimal environment. The proposed monitor has two components: a monitoring component, which provides real-time static and dynamic information about system resources and applications, and a controlling component, which supports real-time control of system resources. For the experimental verification, we created a video transport system based on IoT devices and measured the CPU utilization by dynamic voltage and frequency scaling (DVFS) for the monitor. The results demonstrate that, for up to 50 monitored processes, the monitor shows an average CPU utilization of approximately 4% in the three DVFS modes and demonstrates maximum optimization in the Performance mode of DVFS. Young-Joo Kim, Jong-Soo Seok, YungJoon Jung, and Ok-Kyoon Ha Copyright © 2016 Young-Joo Kim et al. All rights reserved. Decision-Making Algorithm for Multisensor Fusion Based on Grey Relation and DS Evidence Theory Tue, 29 Nov 2016 13:08:59 +0000 Decision-making algorithm, as the key technology for uncertain data fusion, is the core to obtain reasonable multisensor information fusion results. DS evidence theory is a typical and widely applicable decision-making method. However, DS evidence theory makes decisions without considering the sensors’ difference, which may lead to illogical results. In this paper, we present a novel decision-making algorithm for uncertain fusion based on grey relation and DS evidence theory. The proposed algorithm comprehensively takes consideration of sensor’s credibility and evidence’s overall discriminability, which can solve the uncertainty problems caused by inconsistence of sensors themselves and complexity of monitoring environment and simultaneously ensure the validity and accuracy of fusion results. The innovative decision-making algorithm firstly obtains the sensor’s credibility through the introduction of grey relation theory and then defines two impact factors as sensor’s credibility and evidence’s overall discriminability according to the focal element analyses and evidence’s distance analysis, respectively; after that, it uses the impact factors to modify the evidences and finally gets more reasonable and effective results through DS combination rule. Simulation results and analyses demonstrate that the proposed algorithm can overcome the trouble caused by large evidence conflict and one-vote veto, which indicates that it can improve the ability of target judgment and enhance precision of uncertain data fusion. Thus the novel decision-making method has a certain application value. Fang Ye, Jie Chen, Yibing Li, and Jian Kang Copyright © 2016 Fang Ye et al. All rights reserved. A Gas Cell Based on Hollow-Core Photonic Crystal Fiber (PCF) and Its Application for the Detection of Greenhouse Gas (GHG): Nitrous Oxide (N2O) Tue, 29 Nov 2016 11:12:30 +0000 The authors report the detection of nitrous oxide gas using intracavity fiber laser absorption spectroscopy. A gas cell based on a hollow-core photonic crystal fiber was constructed and used inside a fiber ring laser cavity as an intracavity gas cell. The fiber laser in the 1.55 μm band was developed using a polarization-maintaining erbium-doped fiber as the gain medium. The wavelength of the laser was selected by a fiber Bragg grating (FBG), and it matches one of the absorption lines of the gas under investigation. The laser wavelength contained multilongitudinal modes, which increases the sensitivity of the detection system. N2O gas has overtones of the fundamental absorption bands and rovibrational transitions in the 1.55 μm band. The system was operated at room temperature and was capable of detecting nitrous oxide gas at sub-ppmv concentration level. Jonas K. Valiunas, Mario Tenuta, and Gautam Das Copyright © 2016 Jonas K. Valiunas et al. All rights reserved. Multithread Face Recognition in Cloud Tue, 29 Nov 2016 11:04:43 +0000 Faces are highly challenging and dynamic objects that are employed as biometrics evidence in identity verification. Recently, biometrics systems have proven to be an essential security tools, in which bulk matching of enrolled people and watch lists is performed every day. To facilitate this process, organizations with large computing facilities need to maintain these facilities. To minimize the burden of maintaining these costly facilities for enrollment and recognition, multinational companies can transfer this responsibility to third-party vendors who can maintain cloud computing infrastructures for recognition. In this paper, we showcase cloud computing-enabled face recognition, which utilizes PCA-characterized face instances and reduces the number of invariant SIFT points that are extracted from each face. To achieve high interclass and low intraclass variances, a set of six PCA-characterized face instances is computed on columns of each face image by varying the number of principal components. Extracted SIFT keypoints are fused using sum and max fusion rules. A novel cohort selection technique is applied to increase the total performance. The proposed protomodel is tested on BioID and FEI face databases, and the efficacy of the system is proven based on the obtained results. We also compare the proposed method with other well-known methods. Dakshina Ranjan Kisku and Srinibas Rana Copyright © 2016 Dakshina Ranjan Kisku and Srinibas Rana. All rights reserved. Use of a Secondary Current Sensor in Plasma during Electron-Beam Welding with Focus Scanning for Process Control Thu, 24 Nov 2016 14:47:28 +0000 We consider questions of building a closed-loop focus control system for electron-beam welding. As a feedback signal, we use the secondary current in the plasma that forms above the welding zone. This article presents a model of a secondary current sensor in plasma during electron-beam welding with focus scanning. A comparison of modeled results with experimental data confirms the adequacy of the model. We show that the best results for focus control are obtained when using phase relationships rather than amplitude relationships. We outline the principles for building an EBW focus control system based on parameters of the secondary current in plasma. We simulate the work of a control system’s circuits and demonstrate the stability of the synthesized system. We have conducted pilot tests on an experimental prototype. Dmitriy Trushnikov, Elena Krotova, and Elena Koleva Copyright © 2016 Dmitriy Trushnikov et al. All rights reserved. Raspberry Pi Based Intelligent Wireless Sensor Node for Localized Torrential Rain Monitoring Wed, 23 Nov 2016 13:43:24 +0000 Wireless sensor networks are proved to be effective in long-time localized torrential rain monitoring. However, the existing widely used architecture of wireless sensor networks for rain monitoring relies on network transportation and back-end calculation, which causes delay in response to heavy rain in localized areas. Our work improves the architecture by applying logistic regression and support vector machine classification to an intelligent wireless sensor node which is created by Raspberry Pi. The sensor nodes in front-end not only obtain data from sensors, but also can analyze the probabilities of upcoming heavy rain independently and give early warnings to local clients in time. When the sensor nodes send the probability to back-end server, the burdens of network transport are released. We demonstrate by simulation results that our sensor system architecture has potentiality to increase the local response to heavy rain. The monitoring capacity is also raised. Zhaozhuo Xu, Fangling Pu, Xin Fang, and Jing Fu Copyright © 2016 Zhaozhuo Xu et al. All rights reserved. Plasmon-Waveguide Resonances with Enhanced Figure of Merit and Their Potential for Anisotropic Biosensing in the Near Infrared Region Wed, 23 Nov 2016 12:37:41 +0000 The TM and TE guided modes in the coupled plasmon-waveguide resonance configuration are investigated in the spectral domain. Here we use the modes dispersion to study their capability for sensing in the near infrared region. It is shown that the spectral widths of the guided modes are, at least, one order of magnitude smaller than the conventional surface plasmon resonance counterpart. The enhanced sensitivity and figure of merit of the guided modes reveal their potential for sensing in the spectral interrogation method where the traditional configurations are inherently limited. Moreover, the high resolution associated with the narrow resonances and the polarization dependence make these modes very promising for anisotropic biosensing in the spectral interrogation approach. The extremely high figure of merit, large penetration depth, and propagation distance in the near infrared region open the possibility of combining the plasmon-waveguide configuration with absorption spectroscopy techniques for molecular recognition. Said Mahajna, Michal Neumann, Ofer Eyal, and Atef Shalabney Copyright © 2016 Said Mahajna et al. All rights reserved. Human Motion Capture Algorithm Based on Inertial Sensors Wed, 23 Nov 2016 09:45:33 +0000 On the basis of inertial navigation, we conducted a comprehensive analysis of the human body kinematics principle. From the direction of two characteristic parameters, namely, displacement and movement angle, we calculated the attitude of a node during the human motion capture process by combining complementary and Kalman filters. Then, we evaluated the performance of the proposed attitude strategy by selecting different platforms as the validation object. Results show that the proposed strategy for the real-time tracking of the human motion process has higher accuracy than the traditional strategy. Pengzhan Chen, Ye Kuang, and Jie Li Copyright © 2016 Pengzhan Chen et al. All rights reserved. Relative Pose Estimation Algorithm with Gyroscope Sensor Sun, 20 Nov 2016 12:04:25 +0000 This paper proposes a novel vision and inertial fusion algorithm S2fM (Simplified Structure from Motion) for camera relative pose estimation. Different from current existing algorithms, our algorithm estimates rotation parameter and translation parameter separately. S2fM employs gyroscopes to estimate camera rotation parameter, which is later fused with the image data to estimate camera translation parameter. Our contributions are in two aspects. (1) Under the circumstance that no inertial sensor can estimate accurately enough translation parameter, we propose a translation estimation algorithm by fusing gyroscope sensor and image data. (2) Our S2fM algorithm is efficient and suitable for smart devices. Experimental results validate efficiency of the proposed S2fM algorithm. Shanshan Wei, Zhiqiang He, and Wei Xie Copyright © 2016 Shanshan Wei et al. All rights reserved. Night-Time Vehicle Detection Algorithm Based on Visual Saliency and Deep Learning Sun, 20 Nov 2016 11:30:06 +0000 Night vision systems get more and more attention in the field of automotive active safety field. In this area, a number of researchers have proposed far-infrared sensor based night-time vehicle detection algorithm. However, existing algorithms have low performance in some indicators such as the detection rate and processing time. To solve this problem, we propose a far-infrared image vehicle detection algorithm based on visual saliency and deep learning. Firstly, most of the nonvehicle pixels will be removed with visual saliency computation. Then, vehicle candidate will be generated by using prior information such as camera parameters and vehicle size. Finally, classifier trained with deep belief networks will be applied to verify the candidates generated in last step. The proposed algorithm is tested in around 6000 images and achieves detection rate of 92.3% and processing time of 25 Hz which is better than existing methods. Yingfeng Cai, Xiaoqiang Sun, Hai Wang, Long Chen, and Haobin Jiang Copyright © 2016 Yingfeng Cai et al. All rights reserved. Sensor-Based Model Driven Control Strategy for Precision Irrigation Thu, 17 Nov 2016 10:43:09 +0000 Improving the efficiency of the agricultural irrigation systems substantially contributes to sustainable water management. This improvement can be achieved through an automated irrigation system that includes a real-time control strategy based on the water, soil, and crop relationship. This paper presents a model driven control strategy applied to an irrigation system, in order to make an efficient use of water for large crop fields, that is, applying the correct amount of water in the correct place at the right moment. The proposed model uses a predictive algorithm that senses soil moisture and weather variables, to determine optimal amount of water required by the crop. This proposed approach is evaluated against a traditional irrigation system based on the empirical definition of time periods and against a basic soil moisture control system. Results indicate that the use of a model predictive control in an irrigation system achieves a higher efficiency and significantly reduce the water consumption. Camilo Lozoya, Carlos Mendoza, Alberto Aguilar, Armando Román, and Rodolfo Castelló Copyright © 2016 Camilo Lozoya et al. All rights reserved. Feature Extraction of Underwater Target Signal Using Mel Frequency Cepstrum Coefficients Based on Acoustic Vector Sensor Thu, 17 Nov 2016 09:08:39 +0000 Feature extraction method using Mel frequency cepstrum coefficients (MFCC) based on acoustic vector sensor is researched in the paper. Signals of pressure are simulated as well as particle velocity of underwater target, and the features of underwater target using MFCC are extracted to verify the feasibility of the method. The experiment of feature extraction of two kinds of underwater targets is carried out, and these underwater targets are classified and recognized by Backpropagation (BP) neural network using fusion of multi-information. Results of the research show that MFCC, first-order differential MFCC, and second-order differential MFCC features could be used as effective features to recognize those underwater targets and the recognition rate, which using the particle velocity signal is higher than that using the pressure signal, could be improved by using fusion features. Lanyue Zhang, Di Wu, Xue Han, and Zhongrui Zhu Copyright © 2016 Lanyue Zhang et al. All rights reserved. Low-Cost Monitoring System of Sensors for Evaluating Dynamic Solicitations of Semitrailer Structure Thu, 17 Nov 2016 05:53:04 +0000 Analysis of the fatigue life of a semitrailer structure necessitates identification of the loads and dynamic solicitations in the structure. These forces can be introduced in computer simulation software (multibody + finite element) for analysing the response of different design solutions to them. These numerical models must be validated and some parameters need to be measured directly in a field test with real vehicles under various driving conditions. In this study, a low-cost monitoring system is developed for application to a real fleet of semitrailers. According to the definition of the numerical model, the guidance of a virtual vehicle is defined by the three-dimensional kinematics of the kingpin. For characterisation of these movements, a monitoring system having a low-cost inertial measurement unit (IMU) and global positioning system (GPS) antennas is developed with different configurations to enable analysis of the best cost-benefit (result accuracy) solution, and an extended Kalman filter (EKF) that characterises the kinematic guidance of the kingpin is proposed. A semitrailer was equipped with the experimental low-cost monitoring system and high-precision sensors (IMU, GPS) in order to validate the results obtained by the experimental low-cost monitoring system and the inertial-extended Kalman filter developed. The validated system has applicability in the low-cost monitoring of a fleet of real vehicles. Pablo Luque, Daniel A. Mántaras, Aida Rodríguez, Hugo Malón, Luis Castejón, Javier G. Jalón, José L. López, and Ángel Martín Copyright © 2016 Pablo Luque et al. All rights reserved. Oxadiazole Based Polyether as Sensitive Films for Ratiometric Optical Temperature Detection Tue, 15 Nov 2016 13:29:37 +0000 A new type of polymer, based on the oxadiazole group, has been tested as indicator material for a ratiometric photoluminescence and optical reflection based temperature sensor in the temperature range between 30°C and 60°C. Thin films of the new polymer have been deposited by spin-coating on a glass substrate, excited by means of a low-cost near UV-LED. The optical spectrum, as detected by a fiber-based PC-card optical spectrometer, consisted of the reflection peak at the excitation wavelength and two distinct photoluminescence peaks at 430 nm and 480 nm, both in the blue spectral region. The peak amplitudes of all three spectral peaks depend linearly on the exciting light intensity. Changing the sample temperature, all peak amplitude values decrease monotonously with increasing temperature. By using a ratiometric approach, it has been found that the ratio between the two photoluminescence peaks was almost constant with temperature, while the ratio between the main photoluminescence peak at 430 nm and the reflection peak around 380 nm scaled nicely with the ambient temperature. Therefore, it has been proposed to use the latter criterion and a simple polynomial fit to the temperature versus peak amplitude relation. H. C. Neitzert, S. Cuccurullo, S. Concilio, and P. Iannelli Copyright © 2016 H. C. Neitzert et al. All rights reserved. Statistical Delay QoS Provisioning for Energy-Efficient Spectrum-Sharing Based Wireless Ad Hoc Sensor Networks Mon, 14 Nov 2016 11:38:42 +0000 In this paper, we develop the statistical delay quality-of-service (QoS) provisioning framework for the energy-efficient spectrum-sharing based wireless ad hoc sensor network (WAHSN), which is characterized by the delay-bound violation probability. Based on the established delay QoS provisioning framework, we formulate the nonconvex optimization problem which aims at maximizing the average energy efficiency of the sensor node in the WAHSN while meeting PU’s statistical delay QoS requirement as well as satisfying sensor node’s average transmission rate, average transmitting power, and peak transmitting power constraints. By employing the theories of fractional programming, convex hull, and probabilistic transmission, we convert the original fractional-structured nonconvex problem to the additively structured parametric convex problem and obtain the optimal power allocation strategy under the given parameter via Lagrangian method. Finally, we derive the optimal average energy efficiency and corresponding optimal power allocation scheme by employing the Dinkelbach method. Simulation results show that our derived optimal power allocation strategy can be dynamically adjusted based on PU’s delay QoS requirement as well as the channel conditions. The impact of PU’s delay QoS requirement on sensor node’s energy efficiency is also illustrated. Yichen Wang and Wenwen Xu Copyright © 2016 Yichen Wang and Wenwen Xu. All rights reserved. A High Performance Target Tracing Transmission Model Oriented to Lifecycle Maximization Thu, 10 Nov 2016 13:23:46 +0000 For the high speed sensor networks applications such as Internet of Things, multimedia transmission, the realization of high-rate transmission under limited resources has become a problem to be solved. A high speed transmission and energy optimization model oriented to lifecycle maximization is proposed in this paper. Based on information-directed mechanism, the energy threshold set and the relay node distance selection will be done in the process of target tracing, as a result, retaining a balance between transmission rate and energy consumption. Meanwhile, multiagent coevolution is adopted to achieve the maximum of network lifecycle. Comparing with the relevant methods, indexes for network such as hops, throughput, and number of active nodes, standard deviation of remaining energy, and the network lifecycle are considered, and the simulated experiments show that the proposed method will promote the transmission rate effectively, prolong the network lifecycle, and improve network performance as a whole. Zhong-Nan Zhao, Pei-Li Qiao, and Jian Wang Copyright © 2016 Zhong-Nan Zhao et al. All rights reserved. An IFPI Temperature Sensor Fabricated in an Unstriped Optical Fiber with Self-Strain-Compensation Function Thu, 10 Nov 2016 13:05:42 +0000 This paper describes an intrinsic Fabry-Perot interferometer (IFPI) temperature sensor with self-strain-compensation function. The sensor was fabricated on a buffer-intact optical fiber using a femtosecond (fs) laser system. The use of fs laser allows the sensor to be fabricated in an optical fiber without the necessity of removing the polymer buffer coating, thus not compromising its mechanical property. The sensor is composed of two cascaded IFPIs in different cavity length of 100 μm and 500 μm, respectively. The shorter IFPI serves as the temperature sensor, while the second IFPI serves as a compensation sensor, which is used to decouple the strain from the raw signal collected by the shorter FPI. The reflection spectrum of sensor, containing both sensory information and compensation information, is collected in wavelength domain and demultiplexed in the Fourier domain of reflection spectrum. An algorithm was developed and successfully implemented to compensate the strain influence on the proposed temperature sensor. The results showed that the proposed sensor structure holds a constant temperature sensitivity of 11.33 pm/°C when strained differently. Yang Song, Liwei Hua, Jincheng Lei, Qi Zhang, Jie Liu, Lingyun Ye, and Hai Xiao Copyright © 2016 Yang Song et al. All rights reserved. Object Detection and Tracking-Based Camera Calibration for Normalized Human Height Estimation Wed, 09 Nov 2016 11:52:28 +0000 This paper presents a normalized human height estimation algorithm using an uncalibrated camera. To estimate the normalized human height, the proposed algorithm detects a moving object and performs tracking-based automatic camera calibration. The proposed method consists of three steps: (i) moving human detection and tracking, (ii) automatic camera calibration, and (iii) human height estimation and error correction. The proposed method automatically calibrates camera by detecting moving humans and estimates the human height using error correction. The proposed method can be applied to object-based video surveillance systems and digital forensic. Jaehoon Jung, Inhye Yoon, Sangkeun Lee, and Joonki Paik Copyright © 2016 Jaehoon Jung et al. All rights reserved. Using the Dual-Tree Complex Wavelet Transform for Improved Fabric Defect Detection Mon, 07 Nov 2016 13:48:53 +0000 The dual-tree complex wavelet transform (DTCWT) solves the problems of shift variance and low directional selectivity in two and higher dimensions found with the commonly used discrete wavelet transform (DWT). It has been proposed for applications such as texture classification and content-based image retrieval. In this paper, the performance of the dual-tree complex wavelet transform for fabric defect detection is evaluated. As experimental samples, the fabric images from TILDA, a textile texture database from the Workgroup on Texture Analysis of the German Research Council (DFG), are used. The mean energies of real and imaginary parts of complex wavelet coefficients taken separately are identified as effective features for the purpose of fabric defect detection. Then it is shown that the use of the dual-tree complex wavelet transform yields greater performance as compared to the undecimated wavelet transform (UDWT) with a detection rate of 4.5% to 15.8% higher depending on the fabric type. Hermanus Vermaak, Philibert Nsengiyumva, and Nicolaas Luwes Copyright © 2016 Hermanus Vermaak et al. All rights reserved. A Review of Machine Vision-Based Structural Health Monitoring: Methodologies and Applications Sun, 06 Nov 2016 13:53:44 +0000 In the past two decades, a significant number of innovative sensing and monitoring systems based on the machine vision-based technology have been exploited in the field of structural health monitoring (SHM). This technology has some inherent distinctive advantages such as noncontact, nondestructive, long distance, high precision, immunity to electromagnetic interference, and large-range and multiple-target monitoring. A lot of machine vision-based structural dynamic measurement and structural state inspection methods have been proposed. Real-world applications are also carried out to measure the structural physical parameters such as the displacement, strain/stress, rotation, vibration, crack, and spalling. The purpose of this review article is devoted to presenting a summary of the basic theories and practical applications of the machine vision-based technology employed in structural monitoring as well as its systematic error sources and integration with other modern sensing techniques. X. W. Ye, C. Z. Dong, and T. Liu Copyright © 2016 X. W. Ye et al. All rights reserved. Yonjung High-Speed Railway Bridge Assessment Using Output-Only Structural Health Monitoring Measurements under Train Speed Changing Sun, 06 Nov 2016 10:46:14 +0000 Yonjung Bridge is a hybrid multispan bridge that is designed to transport high-speed trains (HEMU-430X) with maximum operating speed of 430 km/h. The bridge consists of simply supported prestressed concrete (PSC) and composite steel girders to carry double railway tracks. The structural health monitoring system (SHM) is designed and installed to investigate and assess the performance of the bridge in terms of acceleration and deformation measurements under different speeds of the passing train. The SHM measurements are investigated in both time and frequency domains; in addition, several identification models are examined to assess the performance of the bridge. The drawn conclusions show that the maximum deflection and acceleration of the bridge are within the design limits that are specified by the Korean and European codes. The parameters evaluation of the model identification depicts the quasistatic and dynamic deformations of PSC and steel girders to be different and less correlated when higher speeds of the passing trains are considered. Finally, the variation of the frequency content of the dynamic deformations of the girders is negligible when high speeds are considered. Mosbeh R. Kaloop, Jong Wan Hu, and Mohamed A. Sayed Copyright © 2016 Mosbeh R. Kaloop et al. All rights reserved. Sensorimotor Piano System for People with Disabilities Tue, 01 Nov 2016 08:09:47 +0000 A sensorimotor training system that facilitates learning to play piano was developed and tested. The system consists of three communicating units. The first unit comprises two pianos: an E-piano with a MIDI output for the teacher and an acoustic or an E-piano for the pupil. The pupil’s piano is supplied with an LED bar that illuminates the key to be struck. The second unit is a controller providing the interface between the teacher’s piano and the LED bar. The third unit consists of two pairs of gloves: one for the teacher and one for the pupil. The teacher gloves have integrated pressure sensors at every fingertip. The pupil’s gloves have vibration motors and LEDs at every finger. The pressure sensed on the teacher’s glove is transmitted to the corresponding finger on the pupil’s glove via the vibration motors and LEDs, such that the pupil knows which finger should strike which key. Additionally, two OLED displays showing the notation of the note played by the teacher can be attached to the left and right pupil’s gloves. Initially developed for people with cerebral palsy the sensorimotor system can support the learning also to all those with sensory, cognitive, and space perception impairments. Tobias Blumenstein, Varvara Turova, Ana Alves-Pinto, and Renée Lampe Copyright © 2016 Tobias Blumenstein et al. All rights reserved. Identity Recognition Using Biological Electroencephalogram Sensors Mon, 31 Oct 2016 11:53:55 +0000 Brain wave signal is a bioelectric phenomenon reflecting activities in human brain. In this paper, we firstly introduce brain wave-based identity recognition techniques and the state-of-the-art work. We then analyze important features of brain wave and present challenges confronted by its applications. Further, we evaluate the security and practicality of using brain wave in identity recognition and anticounterfeiting authentication and describe use cases of several machine learning methods in brain wave signal processing. Afterwards, we survey the critical issues of characteristic extraction, classification, and selection involved in brain wave signal processing. Finally, we propose several brain wave-based identity recognition techniques for further studies and conclude this paper. Wei Liang, Liang Cheng, and Mingdong Tang Copyright © 2016 Wei Liang et al. All rights reserved. Route Choice of the Shortest Travel Time Based on Floating Car Data Mon, 31 Oct 2016 09:08:18 +0000 Finding a route with shortest travel time according to the traffic condition can help travelers to make better route choice decisions. In this paper, the shortest travel time based on FCD (floating car data) which is used to assess overall traffic conditions is proposed. To better fit FCD and road map, a new map matching algorithm which fully considers distance factor, direction factor, and accessibility factor is designed to map all GPS (Global Positioning System) points to roads. A mixed graph structure is constructed and a route analysis algorithm of shortest travel time which considers the dynamic edge weight is designed. By comparing with other map matching algorithms, the proposed method has a higher accuracy. The comparison results show that the shortest travel time path is longer than the shortest distance path, but it costs less traveling time. The implementation of the route choice based on the shortest travel time method can be used to guide people’s travel by selecting the space-time dependent optimal path. Jingwei Shen and Yifang Ban Copyright © 2016 Jingwei Shen and Yifang Ban. All rights reserved. Deep Learning for Hyperspectral Data Classification through Exponential Momentum Deep Convolution Neural Networks Tue, 25 Oct 2016 15:51:24 +0000 Classification is a hot topic in hyperspectral remote sensing community. In the last decades, numerous efforts have been concentrated on the classification problem. Most of the existing studies and research efforts are following the conventional pattern recognition paradigm, which is based on complex handcrafted features. However, it is rarely known which features are important for the problem. In this paper, a new classification skeleton based on deep machine learning is proposed for hyperspectral data. The proposed classification framework, which is composed of exponential momentum deep convolution neural network and support vector machine (SVM), can hierarchically construct high-level spectral-spatial features in an automated way. Experimental results and quantitative validation on widely used datasets showcase the potential of the developed approach for accurate hyperspectral data classification. Qi Yue and Caiwen Ma Copyright © 2016 Qi Yue and Caiwen Ma. All rights reserved. An Access Control Protocol for Wireless Sensor Network Using Double Trapdoor Chameleon Hash Function Tue, 25 Oct 2016 14:37:59 +0000 Wireless sensor network (WSN), a type of communication system, is normally deployed into the unattended environment where the intended user can get access to the network. The sensor nodes collect data from this environment. If the data are valuable and confidential, then security measures are needed to protect them from the unauthorized access. This situation requires an access control protocol (ACP) in the design of sensor network because of sensor nodes which are vulnerable to various malicious attacks during the authentication and key establishment and the new node addition phase. In this paper, we propose a secured ACP for such WSN. This protocol is based on Elliptic Curve Discrete Log Problem (ECDLP) and double trapdoor chameleon hash function which secures the WSN from malicious attacks such as node masquerading attack, replay attack, man-in-the-middle attack, and forgery attacks. Proposed ACP has a special feature known as session key security. Also, the proposed ACP is more efficient as it requires only one modular multiplication during the initialization phase. Tejeshwari Thakur Copyright © 2016 Tejeshwari Thakur. All rights reserved. New Leakage Current Particulate Matter Sensor for On-Board Diagnostics Tue, 25 Oct 2016 13:31:27 +0000 Structure and principle of the new leakage current particulate matter (PM) sensor are introduced and further study is performed on the PM sensor with the combination of numerical simulation and bench test. High voltage electrode, conductive shell, and heaters are all built-in. Based on the principle of Venturi tube and maze structure design, this sensor can detect transient PM concentrations. Internal flow field of the sensor and distribution condition of PM inside the sensor are analyzed through gas-solid two-phase flow numerical simulation. The experiment was also carried out on the whole sensor system (including mechanical and electronic circuit part) and the output signals were analyzed. The results of simulation and experiment reveal the possibility of PM concentration (mass) detection by the sensor. Jiawei Wang, Dong Tang, Songhua Wang, Zehong Zhu, Nan Li, and Lie Chen Copyright © 2016 Jiawei Wang et al. All rights reserved. Research on Fused Tapered Photonic Crystal Fiber Sensor Based on the Method of Intermittent Cooling Mon, 24 Oct 2016 13:43:14 +0000 Based on the intermittent cooling method, a fused tapered Photonic Crystal Fiber (PCF) interferometer is proposed. In the process of tapering, stop heating and wait for cooling at different taper length. Repeat heating and cooling, until taper goes to the expected length. Compared with the ordinary fused tapered method, the fringe contrast of the transmission spectra of this sensor is 15.06 dB. The transmission spectra in different concentrations of glycerol solution are obtained, and the temperature cross-sensitivity of the sensor is studied. The experimental results show that as the external refractive index increases, the transmission spectra of the sensor shift to longer wavelength. In the measuring glycerol solution, the refractive index sensitivity of the sensor can achieve 797.674 nm/RIU, and the temperature sensitivity is only 0.00125 nm/°C. Guangwei Fu, Xinghu Fu, Peng Guo, Yushen Ji, and Weihong Bi Copyright © 2016 Guangwei Fu et al. All rights reserved. Improving Localization in Wireless Sensor Network Using Fixed and Mobile Guide Nodes Mon, 24 Oct 2016 08:44:51 +0000 Wireless sensor network contains very large number of tiny sensors; some nodes with known position are recognized as guide nodes. Other nodes with unknown position are localized by guide nodes. This article uses the combination of fixed and mobile guide nodes in wireless network localization. So nearly 20% of nodes are fixed guide nodes and three nodes are intended as mobile guide nodes. To evaluate the proficiency, the proposed algorithm has been successfully studied and verified through simulation. Low cost, high accuracy, and low power consumption of nodes and complete coverage are the benefits of this approach and long term in localization is the disadvantage of this method. R. Ahmadi, G. Ekbatanifard, A. Jahangiry, and M. Kordlar Copyright © 2016 R. Ahmadi et al. All rights reserved. Privacy Models in Wireless Sensor Networks: A Survey Mon, 24 Oct 2016 06:55:32 +0000 Wireless Sensor Networks (WSNs) are attracting attention from the research community. One of the key issues is to provide them with privacy protection. In recent years, a huge amount of contributions has been focused on this area. Surveys and literature reviews have also been produced to give a systematic view of the different approaches taken. However, no previous work has focused on privacy models, that is, the set of assumptions made to build the approach. In particular, this paper focuses on this matter by studying 41 papers of the last 5 years. We highlight the great differences appearing among related papers that could make them incompatible to be applied simultaneously. We propose a set of guidelines to build comprehensive privacy models so as to foster their comparability and suitability analysis for different scenarios. J. M. de Fuentes, L. González-Manzano, and O. Mirzaei Copyright © 2016 J. M. de Fuentes et al. All rights reserved.