Journal of Electrical and Computer Engineering The latest articles from Hindawi © 2017 , Hindawi Limited . All rights reserved. Algebraic Cryptanalysis Scheme of AES-256 Using Gröbner Basis Thu, 23 Feb 2017 11:14:14 +0000 The zero-dimensional Gröbner basis construction is a crucial step in Gröbner basis cryptanalysis on AES-256. In this paper, after performing an in-depth study on the linear transformation and the system of multivariate polynomial equations of AES-256, the zero-dimensional Gröbner basis construction method is proposed by choosing suitable term order and variable order. After giving a detailed construction process of the zero-dimensional Gröbner basis, the necessary theoretical proof is presented. Based on this, an algebraic cryptanalysis scheme of AES-256 using Gröbner basis is proposed. Analysis shows that the complexity of our scheme is lower than that of the exhaustive attack. Kaixin Zhao, Jie Cui, and Zhiqiang Xie Copyright © 2017 Kaixin Zhao et al. All rights reserved. Autofocus on Depth of Interest for 3D Image Coding Wed, 22 Feb 2017 00:00:00 +0000 For some 3D applications, one may want to focus on a specific depth zone representing a region of interest in the scene. In this context, we introduce a new functionality called “autofocus” for 3D image coding, exploiting the depth map as an additional semantic information provided by the 3D sequence. The method is based on a joint “Depth of Interest” (DoI) extraction and coding scheme. First, the DoI extraction scheme consists of a precise extraction of objects located within a DoI zone, given by the viewer or deduced from an analysis process. Then, the DoI coding scheme provides a higher quality for the objects in the DoI at the expense of other depth zones. The local quality enhancement supports both higher SNR and finer resolution. The proposed scheme embeds the Locally Adaptive Resolution (LAR) codec, initially designed for 2D images. The proposed DoI scheme is developed without modifying the global coder framework, and the DoI mask is not transmitted, but it is deduced at the decoder. Results showed that our proposed joint DoI extraction and coding scheme provide a high correlation between texture objects and depth. This consistency avoids the distortion along objects contours in depth maps and those of texture images and synthesized views. Khouloud Samrouth, Olivier Deforges, Yi Liu, Mohamad Khalil, and Wassim EL Falou Copyright © 2017 Khouloud Samrouth et al. All rights reserved. Acoustic Log Prediction on the Basis of Kernel Extreme Learning Machine for Wells in GJH Survey, Erdos Basin Wed, 22 Feb 2017 00:00:00 +0000 In petroleum exploration, the acoustic log (DT) is popularly used as an estimator to calculate formation porosity, to carry out petrophysical studies, or to participate in geological analysis and research (e.g., to map abnormal pore-fluid pressure). But sometime it does not exist in those old wells drilled 20 years ago, either because of data loss or because of just being not recorded at that time. Thus synthesizing the DT log becomes the necessary task for the researchers. In this paper we propose using kernel extreme learning machine (KELM) to predict missing sonic (DT) logs when only common logs (e.g., natural gamma ray: GR, deep resistivity: REID, and bulk density: DEN) are available. The common logs are set as predictors and the DT log is the target. By using KELM, a prediction model is firstly created based on the experimental data and then confirmed and validated by blind-testing the results in wells containing both the predictors and the target (DT) values used in the supervised training. Finally the optimal model is set up as a predictor. A case study for wells in GJH survey from the Erdos Basin, about velocity inversion using the KELM-estimated DT values, is presented. The results are promising and encouraging. Jianhua Cao, Yancui Shi, Dan Wang, and Xiankun Zhang Copyright © 2017 Jianhua Cao et al. All rights reserved. Chattering-Free Sliding-Mode Control for Electromechanical Actuator with Backlash Nonlinearity Mon, 13 Feb 2017 13:08:57 +0000 Considering the backlash nonlinearity and parameter time-varying characteristics in electromechanical actuators, a chattering-free sliding-mode control strategy is proposed in this paper to regulate the rudder angle and suppress unknown external disturbances. Different from most existing backlash compensation methods, a special continuous function is addressed to approximate the backlash nonlinear dead-zone model. Regarding the approximation error, unmodeled dynamics, and unknown external disturbances as a disturbance-like term, a strict feedback nonlinear model is established. Based on this nonlinear model, a chattering-free nonsingular terminal sliding-mode controller is proposed to achieve the rudder angle tracking with a chattering elimination and tracking dynamic performance improvement. A Lyapunov-based proof ensures the asymptotic stability and finite-time convergence of the closed-loop system. Experimental results have verified the effectiveness of the proposed method. Dongqi Ma, Hui Lin, and Bingqiang Li Copyright © 2017 Dongqi Ma et al. All rights reserved. 3D Curvelet-Based Segmentation and Quantification of Drusen in Optical Coherence Tomography Images Tue, 31 Jan 2017 14:44:23 +0000 Spectral-Domain Optical Coherence Tomography (SD-OCT) is a widely used interferometric diagnostic technique in ophthalmology that provides novel in vivo information of depth-resolved inner and outer retinal structures. This imaging modality can assist clinicians in monitoring the progression of Age-related Macular Degeneration (AMD) by providing high-resolution visualization of drusen. Quantitative tools for assessing drusen volume that are indicative of AMD progression may lead to appropriate metrics for selecting treatment protocols. To address this need, a fully automated algorithm was developed to segment drusen area and volume from SD-OCT images. The proposed algorithm consists of three parts: (1) preprocessing, which includes creating binary mask and removing possible highly reflective posterior hyaloid that is used in accurate detection of inner segment/outer segment (IS/OS) junction layer and Bruch’s membrane (BM) retinal layers; (2) coarse segmentation, in which 3D curvelet transform and graph theory are employed to get the possible candidate drusenoid regions; (3) fine segmentation, in which morphological operators are used to remove falsely extracted elongated structures and get the refined segmentation results. The proposed method was evaluated in 20 publically available volumetric scans acquired by using Bioptigen spectral-domain ophthalmic imaging system. The average true positive and false positive volume fractions (TPVF and FPVF) for the segmentation of drusenoid regions were found to be 89.15% ± 3.76 and 0.17% ± .18%, respectively. M. Esmaeili, A. M. Dehnavi, and H. Rabbani Copyright © 2017 M. Esmaeili et al. All rights reserved. Internet of Things: Architectures, Protocols, and Applications Thu, 26 Jan 2017 06:11:48 +0000 The Internet of Things (IoT) is defined as a paradigm in which objects equipped with sensors, actuators, and processors communicate with each other to serve a meaningful purpose. In this paper, we survey state-of-the-art methods, protocols, and applications in this new emerging area. This survey paper proposes a novel taxonomy for IoT technologies, highlights some of the most important technologies, and profiles some applications that have the potential to make a striking difference in human life, especially for the differently abled and the elderly. As compared to similar survey papers in the area, this paper is far more comprehensive in its coverage and exhaustively covers most major technologies spanning from sensors to applications. Pallavi Sethi and Smruti R. Sarangi Copyright © 2017 Pallavi Sethi and Smruti R. Sarangi. All rights reserved. Medical Image Fusion Algorithm Based on Nonlinear Approximation of Contourlet Transform and Regional Features Tue, 24 Jan 2017 00:00:00 +0000 According to the pros and cons of contourlet transform and multimodality medical imaging, here we propose a novel image fusion algorithm that combines nonlinear approximation of contourlet transform with image regional features. The most important coefficient bands of the contourlet sparse matrix are retained by nonlinear approximation. Low-frequency and high-frequency regional features are also elaborated to fuse medical images. The results strongly suggested that the proposed algorithm could improve the visual effects of medical image fusion and image quality, image denoising, and enhancement. Hui Huang, Xi’an Feng, and Jionghui Jiang Copyright © 2017 Hui Huang et al. All rights reserved. A Comparative Study of Symmetrical Cockcroft-Walton Voltage Multipliers Mon, 16 Jan 2017 00:00:00 +0000 Decades after invention of the Cockcroft-Walton voltage multiplier, it is still being used in broad range of high voltage and ac to dc applications. High voltage ratio, low voltage stress on components, compactness, and high efficiency are its main features. Due to the problems of original circuit, reduction of output ripple and increase of accessible voltage level were the motivations for scientist to propose new topologies. In this article a comparative study on these voltage multipliers was presented. By simulations and experimental prototypes, characteristics of the topologies have been compared. In addition to the performances, components count, voltage stress on the components, and the difficulty and cost of construction are other factors which have been considered in this comparison. An easy to use table which summarized the characteristics of VMs was developed, which can be used as a decision mean for selecting of a topology based on the requirements. It is shown that, due to the application, sometimes a simple and not very famous topology is more effective than a famous one. Mohsen Ruzbehani Copyright © 2017 Mohsen Ruzbehani. All rights reserved. Modified Tang and Pun’s Current Comparator and Its Application to Full Flash and Two-Step Flash Current Mode ADCs Wed, 11 Jan 2017 06:16:55 +0000 A modification to an existing current comparator proposed by Tang and Pun has been presented. The circuit introduces a flipped voltage follower (FVF) which replaces the source follower input stage of the existing current comparator of Tang and Pun. This modification culminates into higher speed especially at lower currents and lower power dissipation. The application of the proposed current comparator has also been put forth by implementing a 3-bit current mode (CM) ADC and a two-step 3-bit CM ADC. The theoretical propositions are verified through spice simulation using 0.18 μm TSMC CMOS technology at a power supply of 1.8 V. Propagation delay, power dissipation, and power delay product (PDP) have been calculated for the proposed current comparator and process parameter variation has been studied. For both the implementations of ADCs, performance parameters, namely, DNL, INL, missing codes, monotonicity, offset, and gain errors, have been evaluated. Veepsa Bhatia and Neeta Pandey Copyright © 2017 Veepsa Bhatia and Neeta Pandey. All rights reserved. A New Digital to Analog Converter Based on Low-Offset Bandgap Reference Mon, 02 Jan 2017 14:08:02 +0000 This paper presents a new 12-bit digital to analog converter (DAC) circuit based on a low-offset bandgap reference (BGR) circuit with two cascade transistor structure and two self-contained feedback low-offset operational amplifiers to reduce the effects of offset operational amplifier voltage effect on the reference voltage, PMOS current-mirror mismatch, and its channel modulation. A Start-Up circuit with self-bias current architecture and multipoint voltage monitoring is employed to keep the BGR circuit working properly. Finally, a dual-resistor ladder DAC-Core circuit is used to generate an accuracy DAC output signal to the buffer operational amplifier. The proposed circuit was fabricated in CSMC 0.5 μm 5 V 1P4M process. The measured differential nonlinearity (DNL) of the output voltages is less than 0.45 LSB and integral nonlinearity (INL) less than 1.5 LSB at room temperature, consuming only 3.5 mW from a 5 V supply voltage. The DNL and INL at −55°C and 125°C are presented as well together with the discussion of possibility of improving the DNL and INL accuracy in future design. Jinpeng Qiu, Tong Liu, Xubin Chen, Yongheng Shang, Jiongjiong Mo, Zhiyu Wang, Hua Chen, Jiarui Liu, Jingjing Lv, and Faxin Yu Copyright © 2017 Jinpeng Qiu et al. All rights reserved. A Novel DBN Feature Fusion Model for Cross-Corpus Speech Emotion Recognition Wed, 28 Dec 2016 07:10:58 +0000 The feature fusion from separate source is the current technical difficulties of cross-corpus speech emotion recognition. The purpose of this paper is to, based on Deep Belief Nets (DBN) in Deep Learning, use the emotional information hiding in speech spectrum diagram (spectrogram) as image features and then implement feature fusion with the traditional emotion features. First, based on the spectrogram analysis by STB/Itti model, the new spectrogram features are extracted from the color, the brightness, and the orientation, respectively; then using two alternative DBN models they fuse the traditional and the spectrogram features, which increase the scale of the feature subset and the characterization ability of emotion. Through the experiment on ABC database and Chinese corpora, the new feature subset compared with traditional speech emotion features, the recognition result on cross-corpus, distinctly advances by 8.8%. The method proposed provides a new idea for feature fusion of emotion recognition. Zou Cairong, Zhang Xinran, Zha Cheng, and Zhao Li Copyright © 2016 Zou Cairong et al. All rights reserved. Hardware Efficient Architecture with Variable Block Size for Motion Estimation Mon, 26 Dec 2016 08:05:52 +0000 Video coding standards such as MPEG-x and H.26x incorporate variable block size motion estimation (VBSME) which is highly time consuming and extremely complex from hardware implementation perspective due to huge computation. In this paper, we have discussed basic aspects of video coding and studied and compared existing architectures for VBSME. Various architectures with different pixel scanning pattern give a variety of performance results for motion vector (MV) generation, showing tradeoff between macroblock processed per second and resource requirement for computation. Aim of this paper is to design VBSME architecture which utilizes optimal resources to minimize chip area and offer adequate frame processing rate for real time implementation. Speed of computation can be improved by accessing 16 pixels of base macroblock of size 4 × 4 in single clock cycle using z scanning pattern. Widely adopted cost function for hardware implementation known as sum of absolute differences (SAD) is used for VBSME architecture with multiplexer based absolute difference calculator and partial summation term reduction (PSTR) based multioperand adders. Device utilization of proposed implementation is only 22k gates and it can process 179 HD (1920 × 1080) resolution frames in best case and 47 HD resolution frames in worst case per second. Due to such higher throughput design is well suitable for real time implementation. Nehal N. Shah, Harikrishna Singapuri, and Upena D. Dalal Copyright © 2016 Nehal N. Shah et al. All rights reserved. Fetal Heart Rate Monitoring from Phonocardiograph Signal Using Repetition Frequency of Heart Sounds Sun, 25 Dec 2016 14:33:57 +0000 As a passive, harmless, and low-cost diagnosis tool, fetal heart rate (FHR) monitoring based on fetal phonocardiography (fPCG) signal is alternative to ultrasonographic cardiotocography. Previous fPCG-based methods commonly relied on the time difference of detected heart sound bursts. However, the performance is unavoidable to degrade due to missed heart sounds in very low signal-to-noise ratio environments. This paper proposes a FHR monitoring method using repetition frequency of heart sounds. The proposed method can track time-varying heart rate without both heart sound burst identification and denoising. The average accuracy rate comparison to benchmark is 88.3% as the SNR ranges from −4.4 dB to −26.7 dB. Hong Tang, Ting Li, Tianshuang Qiu, and Yongwan Park Copyright © 2016 Hong Tang et al. All rights reserved. Design of CPW-Fed Antenna with Defected Substrate for Wideband Applications Tue, 20 Dec 2016 09:28:04 +0000 A CPW-fed defected substrate microstrip antenna is proposed. The proposed antenna shows wideband applications by choosing suitable defected crown shaped substrate. Defected substrate also reduces the size of an antenna. The radiating patch of proposed antenna is taken in the form of extended U-shape. The space around the radiator is utilized by extending the ground plane on both sides of radiator. Simulation of proposed antenna is done on Ansoft’s High Frequency Structure Simulator (HFSS v. 14). Measured results are in good agreement with simulated results. The prototype is taken with dimensions 36 mm × 42 mm × 1.6 mm that achieves good return loss, constant group delay, and good radiation characteristics within the entire operating band from 4.5 to 13.5 GHz (9.0 GHz) with 100% impedance bandwidth at 9.0 GHz centre frequency. Thus, the proposed antenna is applicable for C and X band applications. Amar Sharma, Puneet Khanna, Kshitij Shinghal, and Arun Kumar Copyright © 2016 Amar Sharma et al. All rights reserved. Experiments on Detection of Voiced Hesitations in Russian Spontaneous Speech Sun, 18 Dec 2016 14:34:43 +0000 The development and popularity of voice-user interfaces made spontaneous speech processing an important research field. One of the main focus areas in this field is automatic speech recognition (ASR) that enables the recognition and translation of spoken language into text by computers. However, ASR systems often work less efficiently for spontaneous than for read speech, since the former differs from any other type of speech in many ways. And the presence of speech disfluencies is its prominent characteristic. These phenomena are an important feature in human-human communication and at the same time they are a challenging obstacle for the speech processing tasks. In this paper we address an issue of voiced hesitations (filled pauses and sound lengthenings) detection in Russian spontaneous speech by utilizing different machine learning techniques, from grid search and gradient descent in rule-based approaches to such data-driven ones as ELM and SVM based on the automatically extracted acoustic features. Experimental results on the mixed and quality diverse corpus of spontaneous Russian speech indicate the efficiency of the techniques for the task in question, with SVM outperforming other methods. Vasilisa Verkhodanova and Vladimir Shapranov Copyright © 2016 Vasilisa Verkhodanova and Vladimir Shapranov. All rights reserved. Parameter Extraction of Solar Photovoltaic Modules Using Gravitational Search Algorithm Thu, 15 Dec 2016 14:22:48 +0000 Parameter extraction of a solar photovoltaic system is a nonlinear problem. Many optimization algorithms are implemented for this purpose, which failed in giving better results at low irradiance levels. This article presents a novel method for parameter extraction using gravitational search algorithm. The proposed method evaluates the parameters of different PV panels at various irradiance levels. A critical evaluation and comparison of gravitational search algorithm with other optimization techniques such as genetic algorithm are given. Extensive simulation analyses are carried out on the proposed method and show that GSA is much suitable for parameter extraction problem. R. Sarjila, K. Ravi, J. Belwin Edward, K. Sathish Kumar, and Avagaddi Prasad Copyright © 2016 R. Sarjila et al. All rights reserved. The Comprehensive Study of Electrical Faults in PV Arrays Tue, 06 Dec 2016 13:34:13 +0000 The rapid growth of the solar industry over the past several years has expanded the significance of photovoltaic (PV) systems. Fault analysis in solar photovoltaic (PV) arrays is a fundamental task to increase reliability, efficiency, and safety in PV systems and, if not detected, may not only reduce power generation and accelerated system aging but also threaten the availability of the whole system. Due to the current-limiting nature and nonlinear output characteristics of PV arrays, faults in PV arrays may not be detected. In this paper, all possible faults that happen in the PV system have been classified and six common faults (shading condition, open-circuit fault, degradation fault, line-to-line fault, bypass diode fault, and bridging fault) have been implemented in 7.5 KW PV farm. Based on the simulation results, both normal operational curves and fault curves have been compared. M. Sabbaghpur Arani and M. A. Hejazi Copyright © 2016 M. Sabbaghpur Arani and M. A. Hejazi. All rights reserved. Score-Informed Source Separation for Multichannel Orchestral Recordings Mon, 05 Dec 2016 09:34:13 +0000 This paper proposes a system for score-informed audio source separation for multichannel orchestral recordings. The orchestral music repertoire relies on the existence of scores. Thus, a reliable separation requires a good alignment of the score with the audio of the performance. To that extent, automatic score alignment methods are reliable when allowing a tolerance window around the actual onset and offset. Moreover, several factors increase the difficulty of our task: a high reverberant image, large ensembles having rich polyphony, and a large variety of instruments recorded within a distant-microphone setup. To solve these problems, we design context-specific methods such as the refinement of score-following output in order to obtain a more precise alignment. Moreover, we extend a close-microphone separation framework to deal with the distant-microphone orchestral recordings. Then, we propose the first open evaluation dataset in this musical context, including annotations of the notes played by multiple instruments from an orchestral ensemble. The evaluation aims at analyzing the interactions of important parts of the separation framework on the quality of separation. Results show that we are able to align the original score with the audio of the performance and separate the sources corresponding to the instrument sections. Marius Miron, Julio J. Carabias-Orti, Juan J. Bosch, Emilia Gómez, and Jordi Janer Copyright © 2016 Marius Miron et al. All rights reserved. On the Capacity of MIMO Weibull-Gamma Fading Channels in Low SNR Regime Wed, 30 Nov 2016 13:08:38 +0000 We present capacity analysis for multiple-input multiple-output (MIMO) system under a low signal-to-noise ratio (SNR) regime. We have selected a composite fading channel that considers Weibull fading for multipath and gamma fading for shadowing. We have presented the analysis in a detailed form for three different techniques, namely, spatial multiplexing (SM) with optimal detection, SM with minimum mean square error (MMSE) detection, and orthogonal space-time block codes (OSTBC). Because capacity analysis at arbitrary signal-to-noise (SNR) is stringent, a low SNR regime is considered to achieve a positive rate and wideband slope. The improvement is the result of minimizing energy per information bit . For the first time, closed-form expressions are evaluated for the capacity of MIMO systems at low SNR under WG fading channels which facilitate the performance comparison for proposed techniques. Keerti Tiwari, Davinder S. Saini, and Sunil V. Bhooshan Copyright © 2016 Keerti Tiwari et al. All rights reserved. Contact-Free Cognitive Load Recognition Based on Eye Movement Wed, 30 Nov 2016 11:50:27 +0000 The cognitive overload not only affects the physical and mental diseases, but also affects the work efficiency and safety. Hence, the research of measuring cognitive load has been an important part of cognitive load theory. In this paper, we proposed a method to identify the state of cognitive load by using eye movement data in a noncontact manner. We designed a visual experiment to elicit human’s cognitive load as high and low state in two light intense environments and recorded the eye movement data in this whole process. Twelve salient features of the eye movement were selected by using statistic test. Algorithms for processing some features are proposed for increasing the recognition rate. Finally we used the support vector machine (SVM) to classify high and low cognitive load. The experimental results show that the method can achieve 90.25% accuracy in light controlled condition. Xin Liu, Tong Chen, Guoqiang Xie, and Guangyuan Liu Copyright © 2016 Xin Liu et al. All rights reserved. Audio Watermarking Scheme Based on Singular Spectrum Analysis and Psychoacoustic Model with Self-Synchronization Wed, 30 Nov 2016 06:35:12 +0000 This paper proposes a blind, inaudible, and robust audio watermarking scheme based on singular spectrum analysis (SSA) and the psychoacoustic model 1 (ISO/IEC 11172-3). In this work, SSA is used to analyze the host signals and to extract the singular spectra. A watermark is embedded into the host signals by modifying the singular spectra which are in the convex part of the singular spectrum curve so that this part becomes concave. This modification certainly affects the inaudibility and robustness properties of the watermarking scheme. To satisfy both properties, the modified part of the singular spectrum is determined by a novel parameter selection method based on the psychoacoustic model. The test results showed that the proposed scheme achieves not only inaudibility and robustness but also blindness. In addition, this work showed that the extraction process of a variant of the proposed scheme can extract the watermark without assuming to know the frame positions in advance and without embedding additional synchronization code into the audio content. Jessada Karnjana, Masashi Unoki, Pakinee Aimmanee, and Chai Wutiwiwatchai Copyright © 2016 Jessada Karnjana et al. All rights reserved. A Complete Subspace Analysis of Linear Discriminant Analysis and Its Robust Implementation Wed, 30 Nov 2016 06:32:14 +0000 Linear discriminant analysis has been widely studied in data mining and pattern recognition. However, when performing the eigen-decomposition on the matrix pair (within-class scatter matrix and between-class scatter matrix) in some cases, one can find that there exist some degenerated eigenvalues, thereby resulting in indistinguishability of information from the eigen-subspace corresponding to some degenerated eigenvalue. In order to address this problem, we revisit linear discriminant analysis in this paper and propose a stable and effective algorithm for linear discriminant analysis in terms of an optimization criterion. By discussing the properties of the optimization criterion, we find that the eigenvectors in some eigen-subspaces may be indistinguishable if the degenerated eigenvalue occurs. Inspired from the idea of the maximum margin criterion (MMC), we embed MMC into the eigen-subspace corresponding to the degenerated eigenvalue to exploit discriminability of the eigenvectors in the eigen-subspace. Since the proposed algorithm can deal with the degenerated case of eigenvalues, it not only handles the small-sample-size problem but also enables us to select projection vectors from the null space of the between-class scatter matrix. Extensive experiments on several face images and microarray data sets are conducted to evaluate the proposed algorithm in terms of the classification performance, and experimental results show that our method has smaller standard deviations than other methods in most cases. Zhicheng Lu and Zhizheng Liang Copyright © 2016 Zhicheng Lu and Zhizheng Liang. All rights reserved. A Russian Keyword Spotting System Based on Large Vocabulary Continuous Speech Recognition and Linguistic Knowledge Tue, 29 Nov 2016 13:26:42 +0000 The paper describes the key concepts of a word spotting system for Russian based on large vocabulary continuous speech recognition. Key algorithms and system settings are described, including the pronunciation variation algorithm, and the experimental results on the real-life telecom data are provided. The description of system architecture and the user interface is provided. The system is based on CMU Sphinx open-source speech recognition platform and on the linguistic models and algorithms developed by Speech Drive LLC. The effective combination of baseline statistic methods, real-world training data, and the intensive use of linguistic knowledge led to a quality result applicable to industrial use. Valentin Smirnov, Dmitry Ignatov, Michael Gusev, Mais Farkhadov, Natalia Rumyantseva, and Mukhabbat Farkhadova Copyright © 2016 Valentin Smirnov et al. All rights reserved. An Algorithm of Traffic Perception of DDoS Attacks against SOA Based on Time United Conditional Entropy Sun, 27 Nov 2016 10:28:09 +0000 DDoS attacks can prevent legitimate users from accessing the service by consuming resource of the target nodes, whose availability of network and service is exposed to a significant threat. Therefore, DDoS traffic perception is the premise and foundation of the whole system security. In this paper the method of DDoS traffic perception for SOA network based on time united conditional entropy was proposed. According to many-to-one relationship mapping between the source IP address and destination IP addresses of DDoS attacks, traffic characteristics of services are analyzed based on conditional entropy. The algorithm is provided with perception ability of DDoS attacks on SOA services by introducing time dimension. Simulation results show that the novel method can realize DDoS traffic perception with analyzing abrupt variation of conditional entropy in time dimension. Yuntao Zhao, Hengchi Liu, and Yongxin Feng Copyright © 2016 Yuntao Zhao et al. All rights reserved. First-Order Statistical Characteristics of Macrodiversity System with Three Microdiversity MRC Receivers in the Presence of - Short-Term Fading and Gamma Long-Term Fading Wed, 23 Nov 2016 06:07:39 +0000 Macrodiversity system with macrodiversity SC receiver and three microdiversity MRC (maximum ratio combining) receivers is considered. Independent k-μ short-term fading and correlated Gamma long-term fading are present at the inputs of microdiversity MRC receivers. For this model, the probability density function and the cumulative density function of microdiversity MRC receivers and macrodiversity SC receiver output signal envelopes are calculated. Influences of Gamma shadowing severity, k-μ multipath fading severity, Rician factor and correlation coefficient at probability density function, and cumulative density function of macrodiversity SC receiver output signal envelopes are graphically presented. Branimir Jaksic, Mihajlo Stefanovic, Danijela Aleksic, Dragan Radenkovic, and Sinisa Minic Copyright © 2016 Branimir Jaksic et al. All rights reserved. A Novel Dictionary Learning Model with PT-HLBP for Palmprint Recognition Tue, 22 Nov 2016 13:27:36 +0000 A novel projective dictionary pair learning (PDPL) model with statistical local features for palmprint recognition is proposed. Pooling technique is used to enhance the invariance of hierarchical local binary pattern (PT-HLBP) for palmprint feature extraction. PDPL is employed to learn an analysis dictionary and a synthesis dictionary which are utilized for image discrimination and representation. The proposed algorithm has been tested by the Hong Kong Polytechnic University (PolyU) database (v2) and ideal recognition accuracy can be achieved. Experimental results indicate that the algorithm not only greatly reduces the time complexity in training and testing phase, but also exhibits good robustness for image rotation and corrosion. Xiumei Guo and Weidong Zhou Copyright © 2016 Xiumei Guo and Weidong Zhou. All rights reserved. Speaker Recognition Using Wavelet Cepstral Coefficient, I-Vector, and Cosine Distance Scoring and Its Application for Forensics Sun, 06 Nov 2016 08:59:11 +0000 An important application of speaker recognition is forensics. However, the accuracy of speaker recognition in forensic cases often drops off rapidly because of the ill effect of ambient noise, variable channel, different duration of speech data, and so on. Therefore, finding a robust speaker recognition model is very important for forensics. This paper builds a new speaker recognition model based on wavelet cepstral coefficient (WCC), i-vector, and cosine distance scoring (CDS). This model firstly uses the WCC to transform the speech into spectral feature vecors and then uses those spectral feature vectors to train the i-vectors that represent the speeches having different durations. CDS is used to compare the i-vectors to give out the evidence. Moreover, linear discriminant analysis (LDA) and the within-class covariance normalization (WCNN) are added to the CDS algorithm to deal with the channel variability problem. Finally, the likelihood ratio estimates the strength of the evidence. We use the TIMIT database to evaluate the performance of the proposed model. The experimental results show that the proposed model can effectively solve the troubles of forensic scenario, but the time cost of the method is high. Lei Lei and She Kun Copyright © 2016 Lei Lei and She Kun. All rights reserved. Modelling and Automated Implementation of Optimal Power Saving Strategies in Coarse-Grained Reconfigurable Architectures Wed, 02 Nov 2016 11:10:57 +0000 This paper focuses on how to efficiently reduce power consumption in coarse-grained reconfigurable designs, to allow their effective adoption in heterogeneous architectures supporting and accelerating complex and highly variable multifunctional applications. We propose a design flow for this kind of architectures that, besides their automatic customization, is also capable of determining their optimal power management support. Power and clock gating implementation costs are estimated in advance, before their physical implementation, on the basis of the functional, technological, and architectural parameters of the baseline design. Experimental results, on 90 and 45 nm CMOS technologies, demonstrate that the proposed approach guides the designer towards optimal implementation. Francesca Palumbo, Tiziana Fanni, Carlo Sau, Paolo Meloni, and Luigi Raffo Copyright © 2016 Francesca Palumbo et al. All rights reserved. A Model for Analyzing a Five-Phase Fractional-Slot Permanent Magnet Tubular Linear Motor with Modified Winding Function Approach Thu, 27 Oct 2016 08:32:05 +0000 This paper presents a model for analyzing a five-phase fractional-slot permanent magnet tubular linear motor (FSPMTLM) with the modified winding function approach (MWFA). MWFA is a fast modeling method and it gives deep insight into the calculations of the following parameters: air-gap magnetic field, inductances, flux linkages, and detent force, which are essential in modeling the motor. First, using a magnetic circuit model, the air-gap magnetic density is computed from stator magnetomotive force (MMF), flux barrier, and mover geometry. Second, the inductances, flux linkages, and detent force are analytically calculated using modified winding function and the air-gap magnetic density. Finally, a model has been established with the five-phase Park transformation and simulated. The calculations of detent force reveal that the end-effect force is the main component of the detent force. This is also proven by finite element analysis on the motor. The accuracy of the model is validated by comparing with the results obtained using semianalytical method (SAM) and measurements to analyze the motor’s transient characteristics. In addition, the proposed method requires less computation time. Bo Zhang, Rong Qi, Hui Lin, and Julius Mwaniki Copyright © 2016 Bo Zhang et al. All rights reserved. Improving Robustness of Biometric Identity Determination with Digital Watermarking Thu, 27 Oct 2016 08:07:41 +0000 The determination of an identity from noisy biometric measurements is a continuing challenge. In many applications, such as identity-based encryption, the identity needs to be known with virtually 100% certainty. The determination of identities with such precision from face images taken under a wide range of natural situations is still an unsolved problem. We propose a digital watermarking based method to aid face recognizers to tackle this problem in applications. In particular, we suggest embedding multiple face dependent watermarks into an image to serve as expert knowledge on the corresponding identities to identity-based schemes. This knowledge could originate, for example, from the tagging of those people on a social network. In our proposal, a single payload consists of a correction vector that can be added to the extracted biometric template to compile a nearly noiseless identity. It also supports the removal of a person from the image. If a particular face is censored, the corresponding identity is also removed. Based on our experiments, our method is robust against JPEG compression, image filtering, and occlusion and enables a reliable determination of an identity without side information. Juha Partala, Angelos Fylakis, Anu Pramila, Anja Keskinarkaus, and Tapio Seppänen Copyright © 2016 Juha Partala et al. All rights reserved.