Journal of Electrical and Computer Engineering The latest articles from Hindawi Publishing Corporation © 2016 , Hindawi Publishing Corporation . All rights reserved. User Adaptive and Context-Aware Smart Home Using Pervasive and Semantic Technologies Tue, 30 Aug 2016 16:33:30 +0000 Ubiquitous Computing is moving the interaction away from the human-computer paradigm and towards the creation of smart environments that users and things, from the IoT perspective, interact with. User modeling and adaptation is consistently present having the human user as a constant but pervasive interaction introduces the need for context incorporation towards context-aware smart environments. The current article discusses both aspects of the user modeling and adaptation as well as context awareness and incorporation into the smart home domain. Users are modeled as fuzzy personas and these models are semantically related. Context information is collected via sensors and corresponds to various aspects of the pervasive interaction such as temperature and humidity, but also smart city sensors and services. This context information enhances the smart home environment via the incorporation of user defined home rules. Semantic Web technologies support the knowledge representation of this ecosystem while the overall architecture has been experimentally verified using input from the SmartSantander smart city and applying it to the SandS smart home within FIRE and FIWARE frameworks. Aggeliki Vlachostergiou, Georgios Stratogiannis, George Caridakis, George Siolas, and Phivos Mylonas Copyright © 2016 Aggeliki Vlachostergiou et al. All rights reserved. Two Improved Cancellation Techniques for Direct-Conversion Receivers Tue, 30 Aug 2016 09:29:45 +0000 To solve the problems of carrier leakage and DC offset in direct-conversion receiver (DCR) system, the paper proposed two kinds of improved technology to overcome the problems in DCR system. One is the RF carrier cancellation technology; the traditional cancellation technology based on lumped parameter filter can be easily influenced by distribution parameters, the improved circuits use a 3 db bridge to realize a 180-degree phase shifter, and the method can adapt to a wider range of RF frequency. Another is DC offset cancellation technique; a novel DC servo loop circuit is proposed to replace the traditional AC-coupled amplifier circuit. It can improve the integrity of the baseband signal and reduces the complexity of the subsequent software algorithm. Experimental results show that two kinds of improved technology can improve the performance of DCR and expand its scope of application. Xueyuan Hao and Xiaohong Yan Copyright © 2016 Xueyuan Hao and Xiaohong Yan. All rights reserved. Image Blocking Encryption Algorithm Based on Laser Chaos Synchronization Wed, 24 Aug 2016 06:25:53 +0000 In view of the digital image transmission security, based on laser chaos synchronization and Arnold cat map, a novel image encryption scheme is proposed. Based on pixel values of plain image a parameter is generated to influence the secret key. Sequences of the drive system and response system are pretreated by the same method and make image blocking encryption scheme for plain image. Finally, pixels position are scrambled by general Arnold transformation. In decryption process, the chaotic synchronization accuracy is fully considered and the relationship between the effect of synchronization and decryption is analyzed, which has characteristics of high precision, higher efficiency, simplicity, flexibility, and better controllability. The experimental results show that the encryption algorithm image has high security and good antijamming performance. Shu-Ying Wang, Jian-Feng Zhao, Xian-Feng Li, and Li-Tao Zhang Copyright © 2016 Shu-Ying Wang et al. All rights reserved. Hand Depth Image Denoising and Superresolution via Noise-Aware Dictionaries Thu, 18 Aug 2016 13:55:39 +0000 This paper proposes a two-stage method for hand depth image denoising and superresolution, using bilateral filters and learned dictionaries via noise-aware orthogonal matching pursuit (NAOMP) based K-SVD. The bilateral filtering phase recovers singular points and removes artifacts on silhouettes by averaging depth data using neighborhood pixels on which both depth difference and RGB similarity restrictions are imposed. The dictionary learning phase uses NAOMP for training dictionaries which separates faithful depth from noisy data. Compared with traditional OMP, NAOMP adds a residual reduction step which effectively weakens the noise term within the residual during the residual decomposition in terms of atoms. Experimental results demonstrate that the bilateral phase and the NAOMP-based learning dictionaries phase corporately denoise both virtual and real depth images effectively. Huayang Li, Dehui Kong, Shaofan Wang, and Baocai Yin Copyright © 2016 Huayang Li et al. All rights reserved. A Chaos-Based Encryption Scheme for DCT Precoded OFDM-Based Visible Light Communication Systems Wed, 17 Aug 2016 08:37:30 +0000 This paper proposes a physical encryption scheme for discrete cosine transform (DCT) precoded OFDM-based visible light communication systems by employing chaos scrambling. In the proposed encryption scheme, the Logistic map is adopted for the chaos mapping. The chaos scrambling strategy can allocate the two scrambling sequences to the real () and imaginary () parts of OFDM frames according to the initial condition, which enhance the confidentiality of the physical layer. The simulation experimental results prove the efficiency of the proposed encryption method for DCT precoded OFDM-based VLC systems. The experimental results show that the proposed security scheme can protect the DCT precoded OFDM-based VLC from eavesdropper, while keeping the advantage of the DCT precoding technique, which can reduce the PAPR and improve the BER performance of OFDM-based VLC. Zhongpeng Wang and Shoufa Chen Copyright © 2016 Zhongpeng Wang and Shoufa Chen. All rights reserved. Multiband Circular Polarizer Based on Fission Transmission of Linearly Polarized Wave for X-Band Applications Tue, 16 Aug 2016 08:25:12 +0000 A multiband circular polarizer based on fission transmission of linearly polarized wave for x-band application is proposed, which is constructed of 2 × 2 metallic strips array. The linear-to-circular polarization conversion is obtained by decomposing the linearly incident x-polarized wave into two orthogonal vector components of equal amplitude and 90° phase difference between them. The innovative approach of “fission transmission of linear-to-circular polarized wave” is firstly introduced to obtain giant circular dichroism based on decomposition of orthogonal vector components through the structure. It means that the incident linearly polarized wave is converted into two orthogonal components through lower printed metallic strips layer and two transmitted waves impinge on the upper printed strips layer to convert into four orthogonal vector components at the end of structure. This projection and transmission sequence of orthogonal components sustain the chain transmission of electromagnetic wave and can achieve giant circular dichroism. Theoretical analysis and microwave experiments are presented to validate the performance of the structure. The measured results are in good agreement with simulation results. In addition, the proposed circular polarizer exhibits the optimal performance with respect to the normal incidence. The right handed circularly polarized wave is emitted ranging from 10.08 GHz to 10.53 GHz and 10.78 GHz to 11.12 GHz, while the left handed circular polarized wave is excited at 10.54 GHz–10.70 GHz and 11.13 GHz–11.14 GHz, respectively. Farman Ali Mangi, Shaoqiu Xiao, Ghulam Ali Mallah, Deedar Ali Jamro, Imran Memon, and Ghulam Fatima Kakepoto Copyright © 2016 Farman Ali Mangi et al. All rights reserved. Investigation of Improved Methods in Power Transfer Efficiency for Radiating Near-Field Wireless Power Transfer Sun, 14 Aug 2016 11:52:57 +0000 A metamaterial-inspired efficient electrically small antenna is proposed, firstly. And then several improving power transfer efficiency (PTE) methods for wireless power transfer (WPT) systems composed of the proposed antenna in the radiating near-field region are investigated. Method one is using a proposed antenna as a power retriever. This WPT system consisted of three proposed antennas: a transmitter, a receiver, and a retriever. The system is fed by only one power source. At a fixed distance from receiver to transmitter, the distance between the transmitter and the retriever is turned to maximize power transfer from the transmitter to the receiver. Method two is using two proposed antennas as transmitters and one antenna as receiver. The receiver is placed between the two transmitters. In this system, two power sources are used to feed the two transmitters, respectively. By adjusting the phase difference between the two feeding sources, the maximum PTE can be obtained at the optimal phase difference. Using the same configuration as method two, method three, where the maximum PTE can be increased by regulating the voltage (or power) ratio of the two feeding sources, is proposed. In addition, we combine the proposed methods to construct another two schemes, which improve the PTE at different extent than classical WPT system. Hesheng Cheng and Huakun Zhang Copyright © 2016 Hesheng Cheng and Huakun Zhang. All rights reserved. Development of Testing Platform and Comparison Studies for Wood Nondestructive Testing Thu, 11 Aug 2016 16:16:00 +0000 Stress wave based techniques have been developed for evaluating the quality of the wooden materials nondestructively. However the existing techniques have some shortcomings due to the significant variation of the wood properties and are now in need of updating. There are also stress wave based instruments which have been widely used for nondestructive testing of wood. But most of them are inflexible and unsuitable for the tentative studies. This paper proposed and implemented a wood nondestructive testing platform based on NI virtual instrument. Three wood nondestructive testing methods, including peak time interval measurement, cross-correlation, and spectrum analysis, were also tested on this platform with serious decay sample, early decay sample, and defect-free sample. The results show that new methods can be verified easily and the researches of wood nondestructive testing will be accelerated with the designed platform. Jian Li, Yiming Fang, Jiyong Tang, Hailin Feng, and Xiongwei Lou Copyright © 2016 Jian Li et al. All rights reserved. A Novel Hybrid Method for Short-Term Power Load Forecasting Thu, 11 Aug 2016 13:41:27 +0000 Influenced by many uncertain and random factors, nonstationary, nonlinearity, and time-variety appear in power load series, which is difficult to forecast accurately. Aiming at locating these issues of power load forecasting, an innovative hybrid method is proposed to forecast power load in this paper. Firstly, ensemble empirical mode decomposition (EEMD) is used to decompose the power load series into a series of independent intrinsic mode functions (IMFs) and a residual term. Secondly, genetic algorithm (GA) is then applied to determine the best weights of each IMF and the residual term named ensemble empirical mode decomposition based on weight (WEEMD). Thirdly, least square support vector machine (LSSVM) and nonparametric generalized autoregressive conditional heteroscedasticity (NPGARCH) are employed to forecast the subseries, respectively, based on the characteristics of power load series. Finally, the forecasted power load of each component is summed as the final forecasted result of power load. Compared with other methods, the forecasting results of this proposed model applied to the electricity market of Pennsylvania-New Jersey-Maryland (PJM) indicate that the proposed model outperforms other models. Huang Yuansheng, Huang Shenhai, and Song Jiayin Copyright © 2016 Huang Yuansheng et al. All rights reserved. Object Tracking via 2DPCA and -Regularization Wed, 10 Aug 2016 14:23:26 +0000 We present a fast and robust object tracking algorithm by using 2DPCA and -regularization in a Bayesian inference framework. Firstly, we model the challenging appearance of the tracked object using 2DPCA bases, which exploit the strength of subspace representation. Secondly, we adopt the -regularization to solve the proposed presentation model and remove the trivial templates from the sparse tracking method which can provide a more fast tracking performance. Finally, we present a novel likelihood function that considers the reconstruction error, which is concluded from the orthogonal left-projection matrix and the orthogonal right-projection matrix. Experimental results on several challenging image sequences demonstrate that the proposed method can achieve more favorable performance against state-of-the-art tracking algorithms. Haijun Wang, Hongjuan Ge, and Shengyan Zhang Copyright © 2016 Haijun Wang et al. All rights reserved. Performance Estimation Based Multicriteria Partitioning Approach for Dynamic Dataflow Programs Sun, 07 Aug 2016 08:41:57 +0000 The problem of partitioning a dataflow program onto a target architecture is a difficult challenge for any application design. In general, since the problem is NP-complete, it consists of looking for high quality solutions in terms of maximizing the achievable data throughput. The difficulty is given by the exploration of the design space which results in being extremely large for parallel platforms. The paper describes a heuristic partitioning methodology applicable to dynamic dataflow programs. The methodology is based on two elements: an execution model of the dynamic dataflow program which is used as estimation of the performance for the exploration of the large design space and several partitioning algorithms competing to lead to specific high quality solutions. Experimental results are validated with executions on a virtual platform. Małgorzata Michalska, Nicolas Zufferey, and Marco Mattavelli Copyright © 2016 Małgorzata Michalska et al. All rights reserved. Multialgorithmic Frameworks for Human Face Recognition Wed, 03 Aug 2016 11:59:41 +0000 This paper presents a critical evaluation of multialgorithmic face recognition systems for human authentication in unconstrained environment. We propose different frameworks of multialgorithmic face recognition system combining holistic and texture methods. Our aim is to combine the uncorrelated methods of the face recognition that supplement each other and to produce a comprehensive representation of the biometric cue to achieve optimum recognition performance. The multialgorithmic frameworks are designed to combine different face recognition methods such as (i) Eigenfaces and local binary pattern (LBP), (ii) Fisherfaces and LBP, (iii) Eigenfaces and augmented local binary pattern (A-LBP), and (iv) Fisherfaces and A-LBP. The matching scores of these multialgorithmic frameworks are processed using different normalization techniques whereas their performance is evaluated using different fusion strategies. The robustness of proposed multialgorithmic frameworks of face recognition system is tested on publicly available databases, for example, AT & T (ORL) and Labeled Faces in the Wild (LFW). The experimental results show a significant improvement in recognition accuracies of the proposed frameworks of face recognition system in comparison to their individual methods. In particular, the performance of the multialgorithmic frameworks combining face recognition methods with the devised face recognition method such as A-LBP improves significantly. Radhey Shyam and Yogendra Narain Singh Copyright © 2016 Radhey Shyam and Yogendra Narain Singh. All rights reserved. Image Edge Detection Based on Gaussian Mixture Model in Nonsubsampled Contourlet Domain Thu, 28 Jul 2016 14:27:24 +0000 In order to get accurate location and continuous edges, Gaussian mixture model and local direction modulus nonmaxima suppression are used in high frequency subbands of nonsubsampled Contourlet transform. The distribution of NSCT high frequency subbands coefficients has the “high spikes, long tail” non-Gaussian statistical characteristic. Gaussian mixture model (GMM) is used to distinguish the linear singular signal and the nonlinear singular signal on the high frequency subbands. Local direction modulus nonmaxima suppression is used to refine the linear singular signal. An appropriate threshold is used to distinguish edge pixels and nonedge pixels to get binary image. The experimental results demonstrate that the proposed method can capture more continuous edges in multiple directions and has accurate edge location. And the edges are with great convenience for the image recognition. Li Yang, Chang Xia, and Chang Juan Copyright © 2016 Li Yang et al. All rights reserved. An Analysis of QoS in ZigBee Network Based on Deviated Node Priority Thu, 28 Jul 2016 07:40:49 +0000 ZigBee is an IEEE 802.15.4 standardized communication protocol. It forms a flawless Wireless Sensor Network (WSN) standard for interoperability at all levels of the network, particularly the application level which most closely touches the user. A large number of devices from different vendors can work seamlessly. These devices act as a network and send huge data traffic to the Coordinator. End devices at different zones have different roles in communication with each other. There has been a lack in executing their requests in a synchronized way based on task priority. This lack leads to massive data traffic loss and degrades the Quality of Service (QoS). One of the challenges is to analyze the QoS parameters in ZigBee network that help to detect the overall network performance. The contribution of this paper is twofold; first, a ZigBee Network is implemented based on node priority. It demonstrates a method to generate a new priority of devices with respect to their existing priority and zones’ priority as well. Second, the QoS is analyzed based on the new priority status for tasks preference purposes. The outcome of this paper shows that the QoS of the network is more conspicuous than non-priority based network. Md. Jaminul Haque Biddut, Nazrul Islam, Md. Maksudul Karim, and Mohammad Badrul Alam Miah Copyright © 2016 Md. Jaminul Haque Biddut et al. All rights reserved. Communication Behaviour-Based Big Data Application to Classify and Detect HTTP Automated Software Wed, 27 Jul 2016 13:45:38 +0000 HTTP is recognized as the most widely used protocol on the Internet when applications are being transferred more and more by developers onto the web. Due to increasingly complex computer systems, diversity HTTP automated software (autoware) thrives. Unfortunately, besides normal autoware, HTTP malware and greyware are also spreading rapidly in web environment. Consequently, network communication is not just rigorously controlled by users intention. This raises the demand for analyzing HTTP autoware communication behaviour to detect and classify malicious and normal activities via HTTP traffic. Hence, in this paper, based on many studies and analysis of the autoware communication behaviour through access graph, a new method to detect and classify HTTP autoware communication at network level is presented. The proposal system includes combination of MapReduce of Hadoop and MarkLogic NoSQL database along with xQuery to deal with huge HTTP traffic generated each day in a large network. The method is examined with real outbound HTTP traffic data collected through a proxy server of a private network. Experimental results obtained for proposed method showed that promised outcomes are achieved since 95.1% of suspicious autoware are classified and detected. This finding may assist network and system administrator in inspecting early the internal threats caused by HTTP autoware. Manh Cong Tran and Yasuhiro Nakamura Copyright © 2016 Manh Cong Tran and Yasuhiro Nakamura. All rights reserved. A Comprehensive Taxonomy and Analysis of IEEE 802.15.4 Attacks Tue, 26 Jul 2016 11:42:21 +0000 The IEEE 802.15.4 standard has been established as the dominant enabling technology for Wireless Sensor Networks (WSNs). With the proliferation of security-sensitive applications involving WSNs, WSN security has become a topic of great significance. In comparison with traditional wired and wireless networks, WSNs possess additional vulnerabilities which present opportunities for attackers to launch novel and more complicated attacks against such networks. For this reason, a thorough investigation of attacks against WSNs is required. This paper provides a single unified survey that dissects all IEEE 802.15.4 PHY and MAC layer attacks known to date. While the majority of existing references investigate the motive and behavior of each attack separately, this survey classifies the attacks according to clear metrics within the paper and addresses the interrelationships and differences between the attacks following their classification. The authors’ opinions and comments regarding the placement of the attacks within the defined classifications are also provided. A comparative analysis between the classified attacks is then performed with respect to a set of defined evaluation criteria. The first half of this paper addresses attacks on the IEEE 802.15.4 PHY layer, whereas the second half of the paper addresses IEEE 802.15.4 MAC layer attacks. Yasmin M. Amin and Amr T. Abdel-Hamid Copyright © 2016 Yasmin M. Amin and Amr T. Abdel-Hamid. All rights reserved. Compressive Imaging of Moving Object Based on Linear Array Sensor Thu, 14 Jul 2016 16:06:41 +0000 Using the characteristics of a moving object, this paper presents a compressive imaging method for moving objects based on a linear array sensor. The method uses a higher sampling frequency and a traditional algorithm to recover the image through a column-by-column process. During the compressive sampling stage, the output values of the linear array sensor are multiplied by a coefficient that is a measurement matrix element, and then the measurement value can be acquired by adding all the multiplication values together. During the reconstruction stage, the orthogonal matching pursuit algorithm is used to recover the original image when all the measurement values are obtained. Numerical simulations and experimental results show that the proposed compressive imaging method not only effectively captures the information required from the moving object for image reconstruction but also achieves direct separation of the moving object from a static scene. Changjun Zha, Yao Li, Jinyao Gui, Huimin Duan, and Tailong Xu Copyright © 2016 Changjun Zha et al. All rights reserved. The Comparison of Distributed P2P Trust Models Based on Quantitative Parameters in the File Downloading Scenarios Wed, 13 Jul 2016 08:35:15 +0000 Varied P2P trust models have been proposed recently; it is necessary to develop an effective method to evaluate these trust models to resolve the commonalities (guiding the newly generated trust models in theory) and individuality (assisting a decision maker in choosing an optimal trust model to implement in specific context) issues. A new method for analyzing and comparing P2P trust models based on hierarchical parameters quantization in the file downloading scenarios is proposed in this paper. Several parameters are extracted from the functional attributes and quality feature of trust relationship, as well as requirements from the specific network context and the evaluators. Several distributed P2P trust models are analyzed quantitatively with extracted parameters modeled into a hierarchical model. The fuzzy inferring method is applied to the hierarchical modeling of parameters to fuse the evaluated values of the candidate trust models, and then the relative optimal one is selected based on the sorted overall quantitative values. Finally, analyses and simulation are performed. The results show that the proposed method is reasonable and effective compared with the previous algorithms. Jingpei Wang and Jie Liu Copyright © 2016 Jingpei Wang and Jie Liu. All rights reserved. Augmented Reality for Assistance of Total Knee Replacement Mon, 04 Jul 2016 09:17:49 +0000 The aim of this work was the development of a surgical assistance system based on augmented reality to support joint replacement procedures and implantation of prosthetic knee. Images of the scene were captured in order to detect the visual markers located on the lateral surface of the patient’s leg for overlapping the 3D models of the prosthesis and the joint, as well as the tool used by the medical specialist. With the marker identification, it was possible to compute its position and orientation for locating the virtual models, obtaining a monitoring system for giving accurate information about the procedure. Also it can be used as training platform for surgeons, without having volunteers or patients for performing real surgeries; instead they can train in a virtual environment. The results have shown an efficient system in terms of cost-benefit relation, taking into account the materials used for developing the system; nevertheless, the accuracy of the algorithm decreases according to the distance between the markers. Castillo Daniel and Olga Ramos Copyright © 2016 Castillo Daniel and Olga Ramos. All rights reserved. Advanced Information Technology Convergence Wed, 29 Jun 2016 12:11:33 +0000 Jucheng Yang, Hui Cheng, Sook Yoon, Anthony T. S. Ho, and Weiming Zeng Copyright © 2016 Jucheng Yang et al. All rights reserved. Design of Fixed Wideband Beamformer through Improved Maximum Energy Approach Wed, 15 Jun 2016 09:40:08 +0000 A maximum energy approach is investigated in this paper to design fixed wideband beamformer. This approach has been improved by integrating response variation (RV) into the target function to maintain the frequency invariant property of wideband beamformer over the whole passband. Two methods for designing null to suppress interference signal also have been proposed to make the wideband beamformer robust in complicated environment. Comparisons among other methods are provided to illustrate the effectiveness and enhancement of performance of the new approaches. Rui Du, Yangyu Fan, and Jianshu Wang Copyright © 2016 Rui Du et al. All rights reserved. A Novel Edge-Map Creation Approach for Highly Accurate Pupil Localization in Unconstrained Infrared Iris Images Sun, 05 Jun 2016 13:35:53 +0000 Iris segmentation in the iris recognition systems is a challenging task under noncooperative environments. The iris segmentation is a process of detecting the pupil, iris’s outer boundary, and eyelids in the iris image. In this paper, we propose a pupil localization method for locating the pupils in the non-close-up and frontal-view iris images that are captured under near-infrared (NIR) illuminations and contain the noise, such as specular and lighting reflection spots, eyeglasses, nonuniform illumination, low contrast, and occlusions by the eyelids, eyelashes, and eyebrow hair. In the proposed method, first, a novel edge-map is created from the iris image, which is based on combining the conventional thresholding and edge detection based segmentation techniques, and then, the general circular Hough transform (CHT) is used to find the pupil circle parameters in the edge-map. Our main contribution in this research is a novel edge-map creation technique, which reduces the false edges drastically in the edge-map of the iris image and makes the pupil localization in the noisy NIR images more accurate, fast, robust, and simple. The proposed method was tested with three iris databases: CASIA-Iris-Thousand (version 4.0), CASIA-Iris-Lamp (version 3.0), and MMU (version 2.0). The average accuracy of the proposed method is 99.72% and average time cost per image is 0.727 sec. Vineet Kumar, Abhijit Asati, and Anu Gupta Copyright © 2016 Vineet Kumar et al. All rights reserved. Anticollusion Attack Noninteractive Security Hierarchical Key Agreement Scheme in WHMS Thu, 02 Jun 2016 14:54:57 +0000 Wireless Health Monitoring Systems (WHMS) have potential to change the way of health care and bring numbers of benefits to patients, physicians, hospitals, and society. However, there are crucial barriers not only to transmit the biometric information but also to protect the privacy and security of the patients’ information. The key agreement between two entities is an essential cryptography operation to clear the barriers. In particular, the noninteractive hierarchical key agreement scheme becomes an attractive direction in WHMS because each sensor node or gateway has limited resources and power. Recently, a noninteractive hierarchical key agreement scheme has been proposed by Kim for WHMS. However, we show that Kim’s cryptographic scheme is vulnerable to the collusion attack if the physicians can be corrupted. Obviously, it is a more practical security condition. Therefore, we proposed an improved key agreement scheme against the attack. Security proof, security analysis, and experimental results demonstrate that our proposed scheme gains enhanced security and more efficiency than Kim’s previous scheme while inheriting its qualities of one-round communication and security properties. Kefei Mao, Jianwei Liu, and Jie Chen Copyright © 2016 Kefei Mao et al. All rights reserved. Disordered and Multiple Destinations Path Planning Methods for Mobile Robot in Dynamic Environment Wed, 01 Jun 2016 08:56:31 +0000 In the smart home environment, aiming at the disordered and multiple destinations path planning, the sequencing rule is proposed to determine the order of destinations. Within each branching process, the initial feasible path set is generated according to the law of attractive destination. A sinusoidal adaptive genetic algorithm is adopted. It can calculate the crossover probability and mutation probability adaptively changing with environment at any time. According to the cultural-genetic algorithm, it introduces the concept of reducing turns by parallelogram and reducing length by triangle in the belief space, which can improve the quality of population. And the fallback strategy can help to jump out of the “U” trap effectively. The algorithm analyses the virtual collision in dynamic environment with obstacles. According to the different collision types, different strategies are executed to avoid obstacles. The experimental results show that cultural-genetic algorithm can overcome the problems of premature and convergence of original algorithm effectively. It can avoid getting into the local optimum. And it is more effective for mobile robot path planning. Even in complex environment with static and dynamic obstacles, it can avoid collision safely and plan an optimal path rapidly at the same time. Yong-feng Dong, Hong-mei Xia, and Yan-cong Zhou Copyright © 2016 Yong-feng Dong et al. All rights reserved. Fast Direct Solution of Electromagnetic Scattering from Left-Handed Materials Coated Target over Wide Angle Mon, 30 May 2016 15:44:44 +0000 When solving the electromagnetic scattering problems over wide angle, the traditional method of moments (MoM) needs to repeat the solving process of dense systems of linear equations using the iteration method at each incident angle, which proved to be quite inefficient. To circumvent this problem, a fast numerical method based on block LDLT factorization accelerated by adaptive cross approximation (ACA) algorithm is presented to analyze the electromagnetic scattering of left-handed materials (LHM) coated target. The ACA algorithm is applied to impedance matrix filling and all steps of block LDLT factorization process, which can accelerate the computation process and reduce the memory consumption. The numerical results proved that the proposed method is efficient in calculating monostatic RCS of LHM coated target with many required sampling angles. Compared with the traditional MoM, computation time and memory consumption are reduced effectively. Guo-hua Wang and Ying-bao Geng Copyright © 2016 Guo-hua Wang and Ying-bao Geng. All rights reserved. New Application’s Approach to Unified Power Quality Conditioners for Mitigation of Surge Voltages Mon, 30 May 2016 15:35:32 +0000 This paper outlines a new approach for the compensation of power systems presented through the use of a unified power quality conditioner (UPQC) which compensates impulsive and oscillatory electromagnetic transients. The newly proposed control technique involves a dual analysis of the UPQC where the parallel compensator is modelled as a sinusoidal controlled voltage source, while the series compensator is modelled as a sinusoidal controlled current source, opposed to the traditional approach where the parallel and series compensators are modelled as current and voltage nonsinusoidal sources, respectively. Also a new compensation algorithm is proposed through the application of the theory of generalized reactive power; this is then compared with the theory of active and reactive instantaneous power, or theory. The results are presented by means of simulations in MATLAB-Simulink┬«. Yeison Alberto Garcés Gomez, Nicolás Toro García, and Fredy E. Hoyos Copyright © 2016 Yeison Alberto Garcés Gomez et al. All rights reserved. System and Network Security: Anomaly Detection and Monitoring Mon, 30 May 2016 10:30:34 +0000 Michele Vadursi, Andrea Ceccarelli, Elias P. Duarte Jr., and Aniket Mahanti Copyright © 2016 Michele Vadursi et al. All rights reserved. Compensatory Analysis and Optimization for MADM for Heterogeneous Wireless Network Selection Mon, 30 May 2016 06:40:35 +0000 In the next-generation heterogeneous wireless networks, a mobile terminal with a multi-interface may have network access from different service providers using various technologies. In spite of this heterogeneity, seamless intersystem mobility is a mandatory requirement. One of the major challenges for seamless mobility is the creation of a network selection scheme, which is for users that select an optimal network with best comprehensive performance between different types of networks. However, the optimal network may be not the most reasonable one due to compensation of MADM (Multiple Attribute Decision Making), and the network is called pseudo-optimal network. This paper conducts a performance evaluation of a number of widely used MADM-based methods for network selection that aim to keep the mobile users always best connected anywhere and anytime, where subjective weight and objective weight are all considered. The performance analysis shows that the selection scheme based on MEW (weighted multiplicative method) and combination weight can better avoid accessing pseudo-optimal network for balancing network load and reducing ping-pong effect in comparison with three other MADM solutions. Jian Zhou and Can-yan Zhu Copyright © 2016 Jian Zhou and Can-yan Zhu. All rights reserved. Iterative Forward-Backward Pursuit Algorithm for Compressed Sensing Thu, 26 May 2016 12:51:05 +0000 It has been shown that iterative reweighted strategies will often improve the performance of many sparse reconstruction algorithms. Iterative Framework for Sparse Reconstruction Algorithms (IFSRA) is a recently proposed method which iteratively enhances the performance of any given arbitrary sparse reconstruction algorithm. However, IFSRA assumes that the sparsity level is known. Forward-Backward Pursuit (FBP) algorithm is an iterative approach where each iteration consists of consecutive forward and backward stages. Based on the IFSRA, this paper proposes the Iterative Forward-Backward Pursuit (IFBP) algorithm, which applies the iterative reweighted strategies to FBP without the need for the sparsity level. By using an approximate iteration strategy, IFBP gradually iterates to approach the unknown signal. Finally, this paper demonstrates that IFBP significantly improves the reconstruction capability of the FBP algorithm, via simulations including recovery of random sparse signals with different nonzero coefficient distributions in addition to the recovery of a sparse image. Feng Wang, Jianping Zhang, Guiling Sun, and Tianyu Geng Copyright © 2016 Feng Wang et al. All rights reserved. Face Spoof Attack Recognition Using Discriminative Image Patches Sun, 22 May 2016 07:40:26 +0000 Face recognition systems are now being used in many applications such as border crossings, banks, and mobile payments. The wide scale deployment of facial recognition systems has attracted intensive attention to the reliability of face biometrics against spoof attacks, where a photo, a video, or a 3D mask of a genuine user’s face can be used to gain illegitimate access to facilities or services. Though several face antispoofing or liveness detection methods (which determine at the time of capture whether a face is live or spoof) have been proposed, the issue is still unsolved due to difficulty in finding discriminative and computationally inexpensive features and methods for spoof attacks. In addition, existing techniques use whole face image or complete video for liveness detection. However, often certain face regions (video frames) are redundant or correspond to the clutter in the image (video), thus leading generally to low performances. Therefore, we propose seven novel methods to find discriminative image patches, which we define as regions that are salient, instrumental, and class-specific. Four well-known classifiers, namely, support vector machine (SVM), Naive-Bayes, Quadratic Discriminant Analysis (QDA), and Ensemble, are then used to distinguish between genuine and spoof faces using a voting based scheme. Experimental analysis on two publicly available databases (Idiap REPLAY-ATTACK and CASIA-FASD) shows promising results compared to existing works. Zahid Akhtar and Gian Luca Foresti Copyright © 2016 Zahid Akhtar and Gian Luca Foresti. All rights reserved.