Journal of Electrical and Computer Engineering The latest articles from Hindawi Publishing Corporation © 2015 , Hindawi Publishing Corporation . All rights reserved. An Approach to Generate Spatial Voronoi Treemaps for Points, Lines, and Polygons Wed, 29 Jul 2015 06:39:19 +0000 As a space-filling method, Voronoi Treemaps are used for showcasing hierarchies. Previously presented algorithms are limited to visualize nonspatial data. The approach of spatial Voronoi Treemaps is proposed in this paper to eliminate these problems by enabling the subdivisions for points, lines, and polygons with spatial coordinates and references. The digital distance transformation is recursively used to generate nested raster Voronoi polygons while the raster to vector conversion is used to create a vector-based Treemap visualization in a GIS (geographic information system) environment. The objective is to establish a spatial data model to better visualize and understand the hierarchies in the geographic field. Song Tian, Ximin Cui, and Yu Gong Copyright © 2015 Song Tian et al. All rights reserved. Design of Wireless Automatic Synchronization for the Low-Frequency Coded Ground Penetrating Radar Mon, 27 Jul 2015 05:55:11 +0000 Low-frequency coded ground penetrating radar (GPR) with a pair of wire dipole antennas has some advantages for deep detection. Due to the large distance between the two antennas, the synchronization design is a major challenge of implementing the GPR system. This paper proposes a simple and stable wireless automatic synchronization method based on our developed GPR system, which does not need any synchronization chips or modules and reduces the cost of the hardware system. The transmitter omits the synchronization preamble and pseudorandom binary sequence (PRBS) at an appropriate time interval, while receiver automatically estimates the synchronization time and receives the returned signal from the underground targets. All the processes are performed in a single FPGA. The performance of the proposed synchronization method is validated with experiment. Zhenghuan Xia, Qunying Zhang, Shengbo Ye, Zhiwu Xu, Jie Chen, Guangyou Fang, and Hejun Yin Copyright © 2015 Zhenghuan Xia et al. All rights reserved. Novel Chaos Secure Communication System Based on Walsh Code Thu, 09 Jul 2015 09:51:12 +0000 A multiuser communication scheme which is a hybrid of Walsh code with DCSK and CDSK is proposed to improve low data transmission rate of Differential Chaos Shift Keying (DCSK), poor bit error ratio (BER) performance of Correlation Delay Shift Keying (CDSK), and disadvantage of orthogonality in traditional multiuser DCSK. It not only overcomes the disadvantages of DCSK and CDSK, but also has better performance than CDSK and higher transmission data rate than DCSK. It has been proved that the novel multiuser CDSK-DCSK has better properties than traditional Multiple Input Multiple Output-Differential Chaos Shift Keying (MIMO-DCSK) and Modified-Differential Chaos Shift Keying (M-DCSK). Also the multiuser interference is greatly suppressed due to the orthogonality of Walsh code. Gang Zhang, Niting Cui, and Tianqi Zhang Copyright © 2015 Gang Zhang et al. All rights reserved. Human Activity Recognition Based on the Hierarchical Feature Selection and Classification Framework Tue, 07 Jul 2015 11:56:22 +0000 Human activity recognition via triaxial accelerometers can provide valuable information for evaluating functional abilities. In this paper, we present an accelerometer sensor-based approach for human activity recognition. Our proposed recognition method used a hierarchical scheme, where the recognition of ten activity classes was divided into five distinct classification problems. Every classifier used the Least Squares Support Vector Machine (LS-SVM) and Naive Bayes (NB) algorithm to distinguish different activity classes. The activity class was recognized based on the mean, variance, entropy of magnitude, and angle of triaxial accelerometer signal features. Our proposed activity recognition method recognized ten activities with an average accuracy of 95.6% using only a single triaxial accelerometer. Yuhuang Zheng Copyright © 2015 Yuhuang Zheng. All rights reserved. Forest Fire Smoke Video Detection Using Spatiotemporal and Dynamic Texture Features Thu, 02 Jul 2015 11:32:12 +0000 Smoke detection is a very key part of fire recognition in a forest fire surveillance video since the smoke produced by forest fires is visible much before the flames. The performance of smoke video detection algorithm is often influenced by some smoke-like objects such as heavy fog. This paper presents a novel forest fire smoke video detection based on spatiotemporal features and dynamic texture features. At first, Kalman filtering is used to segment candidate smoke regions. Then, candidate smoke region is divided into small blocks. Spatiotemporal energy feature of each block is extracted by computing the energy features of its 8-neighboring blocks in the current frame and its two adjacent frames. Flutter direction angle is computed by analyzing the centroid motion of the segmented regions in one candidate smoke video clip. Local Binary Motion Pattern (LBMP) is used to define dynamic texture features of smoke videos. Finally, smoke video is recognized by Adaboost algorithm. The experimental results show that the proposed method can effectively detect smoke image recorded from different scenes. Yaqin Zhao, Zhong Zhou, and Mingming Xu Copyright © 2015 Yaqin Zhao et al. All rights reserved. Time-Frequency Feature Extraction of HRRP Using AGR and NMF for SAR ATR Mon, 29 Jun 2015 10:36:04 +0000 A new approach to classify synthetic aperture radar (SAR) targets based on high range resolution profiles (HRRPs) is presented. Features from each of the target HRRPs are extracted via the nonnegative matrix factorization (NMF) algorithm in time-frequency domain represented by adaptive Gaussian representation (AGR). Firstly, SAR target images have been converted into HRRPs. And the time-frequency matrix for each of HRRPs is obtained by using AGR. Secondly, the time-frequency feature vectors are extracted from the time-frequency matrix utilizing NMF. Finally, hidden Markov models (HMMs) are employed to characterize the time-frequency feature vectors corresponding to one target and are used to being the recognizer. To demonstrate the performance of the proposed approach, experiments are performed in the 10-target MSTAR public dataset. The results support the effectiveness of the proposed technique for SAR automatic target recognition (ATR). Xinzheng Zhang, Zhouyong Liu, Shujun Liu, and Guojun Li Copyright © 2015 Xinzheng Zhang et al. All rights reserved. A Zero-Watermarking Scheme for Vector Map Based on Feature Vertex Distance Ratio Wed, 17 Jun 2015 12:46:49 +0000 With the rapid development of GIS and computer techniques, vector map data has been widely used in many fields. Since the production of map data is very costly, illegal copying will result in huge loss for data owners. In order to protect the copyright of vector data, digital watermarking has been employed in recent years. In this paper, a zero-watermarking scheme for vector map data is proposed. In the proposed scheme, FVDR (feature vertex distance ratio) is constructed based on the feature vertices of objects. The feature data, FVDR, is combined with watermark to generate the zero-watermark. Due to the specially designed cover data, the proposed scheme is robust to geometrical attacks, vertex attacks, and object attacks. The results of extensive experiments also demonstrate the robustness of the proposed scheme. Yuwei Peng and Mingliang Yue Copyright © 2015 Yuwei Peng and Mingliang Yue. All rights reserved. Wavelet Domain Multidictionary Learning for Single Image Super-Resolution Mon, 15 Jun 2015 06:53:59 +0000 Image super-resolution (SR) aims at recovering the high-frequency (HF) details of a high-resolution (HR) image according to the given low-resolution (LR) image and some priors about natural images. Learning the relationship of the LR image and its corresponding HF details to guide the reconstruction of the HR image is needed. In order to alleviate the uncertainty in HF detail prediction, the HR and LR images are usually decomposed into 4 subbands after 1-level discrete wavelet transformation (DWT), including an approximation subband and three detail subbands. From our observation, we found the approximation subbands of the HR image and the corresponding bicubic interpolated image are very similar but the respective detail subbands are different. Therefore, an algorithm to learn 4 coupled principal component analysis (PCA) dictionaries to describe the relationship between the approximation subband and the detail subbands is proposed in this paper. Comparisons with various state-of-the-art methods by experiments showed that our proposed algorithm is superior to some related works. Xiaomin Wu, Jiulun Fan, Jian Xu, and Yanzi Wang Copyright © 2015 Xiaomin Wu et al. All rights reserved. Unsupervised Classification Method for Polarimetric Synthetic Aperture Radar Imagery Based on Yamaguchi Four-Component Decomposition Model Wed, 03 Jun 2015 06:16:51 +0000 For improving the accuracy of unsupervised classification based on scattering models, the four-component Yamaguchi model is introduced, which is an improved version of the best-known three-component Freeman model. Therewith, the four-component model is combined with the Wishart distance model. The new proposed algorithm of clustering is rolled out thereafter and the procedure of this new method is listed. In experiments, seven areas of various homogeneities are singled out from the Flevoland sample image in AIRSAR dataset. Qualitative and quantitative experiments are performed for a comparative study. It can be easily seen that the resolution and details are remarkably upgraded by the new proposed method. The accuracy of classification in homogeneous areas has also increased significantly by adopting the new iterative algorithm. Sheng Sun, Renfeng Liu, and Wen Wen Copyright © 2015 Sheng Sun et al. All rights reserved. Drive Current Enhancement in TFET by Dual Source Region Sun, 24 May 2015 13:38:06 +0000 This paper presents tunneling field-effect transistor (TFET) with dual source regions. It explores the physics of drive current enhancement. The novel approach of dual source provides an effective technique for enhancing the drive current. It is found that this structure can offer four tunneling junctions by increasing a source region. Meanwhile, the dual source structure does not influence the excellent features of threshold slope (SS) of TFET. The number of the electrons and holes would be doubled by going through the tunneling junctions on the original basis. The overlap length of gate-source is also studied. The dependence of gate-drain capacitance and gate-source capacitance on gate-to-source voltage and drain-to-source voltage was further investigated. There are simulation setups and methodology used for the dual source TFET (DS-TFET) assessment, including delay time, total energy per operation, and energy-delay product. It is confirmed that the proposed TFET has strong potentials for VLSI. Zhi Jiang, Yiqi Zhuang, Cong Li, Ping Wang, and Yuqi Liu Copyright © 2015 Zhi Jiang et al. All rights reserved. Doppler Ambiguity Resolution Based on Random Sparse Probing Pulses Mon, 11 May 2015 12:30:26 +0000 A novel method for solving Doppler ambiguous problem based on compressed sensing (CS) theory is proposed in this paper. A pulse train with the random and sparse transmitting time is transmitted. The received signals after matched filtering can be viewed as randomly sparse sampling from the traditional fixed-pulse repetition frequency (PRF) echo signals. The whole target echo could be reconstructed via CS recovery algorithms. Through refining the sensing matrix, which is equivalent to increase the sampling frequency of target characteristic, the Doppler unambiguous range is enlarged. In particular, Complex Approximate Message Passing (CAMP) algorithm is developed to estimate the unambiguity Doppler frequency. Cramer-Rao lower bound expressions are derived for the frequency. Numerical simulations validate the effectiveness of the proposed method. Finally, compared with traditional methods, the proposed method only requires transmitting a few sparse probing pulses to achieve a larger Doppler frequency unambiguous range and can also reduce the consumption of the radar time resources. Yunjian Zhang, Zhenmiao Deng, Jianghong Shi, Linmei Ye, Maozhong Fu, and Chen Zhao Copyright © 2015 Yunjian Zhang et al. All rights reserved. An Extraction Method of Weak Low-Frequency Magnetic Communication Signals Based on Multisensor Sun, 10 May 2015 06:11:53 +0000 It is a technical challenge to effectively remove the influence of magnetic noise from the vicinity of the receiving sensors on low-frequency magnetic communication. The traditional denoising methods are difficult to extract high-quality original signals under the condition of low SNR (the signal-to-noise ratio). In this paper, we analyze the numerical characteristics of the low-frequency magnetic field and propose the algorithms of the fast optimization of blind source separation (FOBSS) and the frequency-domain correlation extraction (FDCE). FOBSS is based on blind source separation (BSS). Signal extraction of low SNR can be implemented through FOBSS and FDCE. This signal extraction method is verified in multiple field experiments which can remove the magnetic noise by about 25 dB or more. Chao Huang, Xin Xu, Dunge Liu, Wanhua Zhu, Xiaojuan Zhang, and Guangyou Fang Copyright © 2015 Chao Huang et al. All rights reserved. Robust Recursive Algorithm under Uncertainties via Worst-Case SINR Maximization Wed, 06 May 2015 09:56:47 +0000 The performance of traditional constrained-LMS (CLMS) algorithm is known to degrade seriously in the presence of small training data size and mismatches between the assumed array response and the true array response. In this paper, we develop a robust constrained-LMS (RCLMS) algorithm based on worst-case SINR maximization. Our algorithm belongs to the class of diagonal loading techniques, in which the diagonal loading factor is obtained in a simple form and it decreases the computation cost. The updated weight vector is derived by the descent gradient method and Lagrange multiplier method. It demonstrates that our proposed recursive algorithm provides excellent robustness against signal steering vector mismatches and the small training data size and, has fast convergence rate, and makes the mean output array signal-to-interference-plus-noise ratio (SINR) consistently close to the optimal one. Some simulation results are presented to compare the performance of our robust algorithm with the traditional CLMS algorithm. Xin Song, Feng Wang, Jinkuan Wang, and Jingguo Ren Copyright © 2015 Xin Song et al. All rights reserved. Climate Characteristics of High-Temperature and Muggy Days in the Beijing-Tianjin-Hebei Region in the Recent 30 Years Wed, 29 Apr 2015 06:23:14 +0000 The climate characteristics of high-temperature (37°C and above) and muggy days in the Beijing-Tianjin-Hebei region over the past 30 years from 1981 to 2010 are analyzed. The results are summarized as follows. During this period, the years with the most number of high-temperature days are 1997–2005 and 2009 in the Beijing-Tianjin-Hebei region, while high-temperature extremes appear in 1999, 2000, 2002, 2009, and 2010. This disparity between the years with high-temperature extremes and the years with the most number of high-temperature days is located primarily in the central and southern cities of the Beijing-Tianjin-Hebei region. High-temperature extremes in the southern cities appear in June and July, while high-temperature extremes in the other cities appear in July. The years with the most number of muggy days are 1994, 1997, 1998, 2000, and 2010 in the Beijing-Tianjin-Hebei region, but the years with the extreme muggy conditions appear in 1981, 2002, 2005, and 2010. The most number of muggy days are in July, and the muggy days in July and August account for about 90% of the entire summer. Over the 30-year period, no apparent changes are observed in the number of days with precipitation and the annual precipitation amount. Guohua Zhang, Jian Guan, Jingyi Ai, Jiangtao Zhang, and Xiaoqing Jin Copyright © 2015 Guohua Zhang et al. All rights reserved. Performance Analysis of Multiscale Entropy for the Assessment of ECG Signal Quality Mon, 27 Apr 2015 09:09:45 +0000 This study explored the performance of multiscale entropy (MSE) for the assessment of mobile ECG signal quality, aiming to provide a reasonable application guideline. Firstly, the MSE for the typical noises, that is, high frequency (HF) noise, low frequency (LF) noise, and power-line (PL) noise, was analyzed. The sensitivity of MSE to the signal to noise ratio (SNR) of the synthetic artificial ECG plus different noises was further investigated. The results showed that the MSE values could reflect content level of various noises contained in the ECG signals. For the synthetic ECG plus LF noise, the MSE was sensitive to SNR within higher range of scale factor. However, for the synthetic ECG plus HF noise, the MSE was sensitive to SNR within lower range of scale factor. Thus, a recommended scale factor range within 5 to 10 was given. Finally, the results were verified on the real ECG signals, which were derived from MIT-BIH Arrhythmia Database and Noise Stress Test Database. In all, MSE could effectively assess the noise level on the real ECG signals, and this study provided a valuable reference for applying MSE method to the practical signal quality assessment of mobile ECG. Yatao Zhang, Shoushui Wei, Yutao Long, and Chengyu Liu Copyright © 2015 Yatao Zhang et al. All rights reserved. Time-Frequency Analysis of Clinical Percussion Signals Using Matrix Pencil Method Thu, 16 Apr 2015 15:47:07 +0000 This paper discusses time-frequency analysis of clinical percussion signals produced by tapping over human chest or abdomen with a neurological hammer and recorded with an air microphone. The analysis of short, highly damped percussion signals using conventional time-frequency distributions (TFDs) meets certain difficulties, such as poor time-frequency localization, cross terms, and masking of the lower energy features by the higher energy ones. The above shortcomings lead to inaccurate and ambiguous representation of the signal behavior in the time-frequency plane. This work describes an attempt to construct a TF representation specifically tailored to clinical percussion signals to achieve better resolution of individual components corresponding to physical oscillation modes. Matrix Pencil Method (MPM) is used to decompose the signal into a set of exponentially damped sinusoids, which are then plotted in the time-frequency plane. Such representation provides better visualization of the signal structure than the commonly used frequency-amplitude plots and facilitates tracking subtle changes in the signal for diagnostic purposes. The performance of our approach has been verified on both ideal and real percussion signals. The MPM-based time-frequency analysis appears to be a better choice for clinical percussion signals than conventional TFDs, while its ability to visualize damping has immediate practical applications. Moinuddin Bhuiyan, Eugene V. Malyarenko, Mircea A. Pantea, Dante Capaldi, Alfred E. Baylor, and Roman Gr. Maev Copyright © 2015 Moinuddin Bhuiyan et al. All rights reserved. New Current-Mode Integrated Ternary Min/Max Circuits without Constant Independent Current Sources Tue, 07 Apr 2015 08:30:25 +0000 Novel designs of current-mode Ternary minimum (AND) and maximum (OR) are proposed in this paper based on Carbon NanoTube Field Effect Transistors (CNTFET). First, these Ternary operators are designed separately. Then, they are combined together in order to generate both outputs concurrently in an integrated design. This integration results in the elimination of common parts when both functions are required at the same time. The third proposed current-mode integrated circuit generates both ternary operators with the usage of only 30 transistors. The new designs are composed of three main parts: (1) the part which converts current to voltage; (2) threshold detectors; and (3) the parallel paths through which the output current flows. Unlike the previously presented structure, there is no need for any constant current source within the new designs. This elimination leads to less static power dissipation. The second proposed current-mode segregated Ternary minimum operates 43% faster and consumes 40% less power in comparison with a previously presented structure. Mona Moradi, Reza Faghih Mirzaee, and Keivan Navi Copyright © 2015 Mona Moradi et al. All rights reserved. A Curvelet-SC Recognition Method for Maize Disease Sun, 05 Apr 2015 14:35:07 +0000 Because the corn vein and noise influence the contour extraction of the maize leaf disease, we put forward a new recognition algorithm based on Curvelet and Shape Context (SC). This method can improve the speed and accuracy of maize leaf disease recognition. Firstly, we use Seeded Regional Growing (SRG) algorithm to segment the maize leaf disease image. Secondly, Curvelet Modulus Correlation (CMC) method is put forward to extract the effective contour of maize leaf disease. Thirdly, we combine CMC with the SC algorithm to obtain the histogram features and then use these features we obtain to calculate the similarities between the template image and the target image. Finally, we adopt n-fold cross-validation algorithm to recognize diseases on maize leaf disease database. Experimental results show that the proposed algorithm can recognize 6 kinds of maize leaf diseases accurately and achieve the accuracy of 94.446%. Meanwhile this algorithm has guiding significance for other diseases recognition to an extent. Jing Luo, Shuze Geng, Chunbo Xiu, Dan Song, and Tingting Dong Copyright © 2015 Jing Luo et al. All rights reserved. Fast Two-Step Energy Detection for Spectrum Sensing Mon, 30 Mar 2015 14:16:03 +0000 Spectrum sensing is one of the key tasks in cognitive radio. This paper proposes a fast two-step energy detection (FED) algorithm for spectrum sensing via improving the sampling process of conventional energy detection (CED). The algorithm adaptively selects -point or 2-point sampling by comparing its observed energy with prefixed double thresholds, and thereby is superior in sampling time and detection speed. Moreover, under the constraint of constant false alarm, this paper optimizes the thresholds from maximizing detection probability point of view. Theoretical analyses and simulation results show that, compared with CED, the proposed FED can achieve significant gain in detection speed at the expense of slight accuracy loss. Specifically, within high signal-to-noise ratio regions, as much as 25% of samples can be reduced. Meiling Lai, Shengliang Peng, Xi Yang, and Lin Zhou Copyright © 2015 Meiling Lai et al. All rights reserved. Improved Mainlobe Interference Suppression Based on Blocking Matrix Preprocess Mon, 30 Mar 2015 12:29:44 +0000 For the problem of mainlobe direction shifting that is caused by the mainlobe interference suppression based on blocking matrix preprocess, an effective method is proposed which is based on the combination of diagonal loading and linear constraints. Therein, the reason for mainlobe direction shifting is analyzed and found to be that the covariance matrix mismatch exists in the realization of the adaptive beamforming. Therefore, the diagonal loading processing is used to overcome the mismatch and correct the mainlobe direction shifting, and the linear constraints are used to make sure of the beam pattern nulling in the interference directions; then the desired performance of adaptive beamforming is obtained. Simulation results attest the correctness and effectiveness of the proposed method, and they also show that the proposed method is insensitive to the selection of diagonal loading level, which means the loading factor is easy to choose. Jie Yang and Congfeng Liu Copyright © 2015 Jie Yang and Congfeng Liu. All rights reserved. Dynamic Antenna Alignment Control in Microwave Air-Bridging for Sky-Net Mobile Communication Using Unmanned Flying Platform Sun, 29 Mar 2015 06:18:45 +0000 This paper presents a preliminary study on establishing a mobile point-to-point (P2P) microwave air-bridging (MAB) between Unmanned Low Altitude Flying Platform (ULAFP) and backhaul telecommunication network. The proposed Sky-Net system relays telecom signal for general mobile cellphone users via ULAFP when natural disaster sweeps off Base Transceiver Stations (BTSs). Unlike the conventional fix point microwave bridging application, the ULAFP is cruising on a predefined mission flight path to cover a wider range of service. The difficulty and challenge fall on how to maintain antenna alignment accurately in order to provide the signal strength for MAB. A dual-axis rotation mechanism with embedded controller is designed and implemented on airborne and ground units for stabilizing airborne antenna and tracking the moving ULAFP. The MAB link is established in flight tests using the proposed antenna stabilizing/tracking mechanism with correlated control method. The result supports backbone technique of the Sky-Net mobile communication and verifies the feasibility of airborne e-Cell BTS. Chin E. Lin and Ying-Chi Huang Copyright © 2015 Chin E. Lin and Ying-Chi Huang. All rights reserved. Hysteresis Control for Shunt Active Power Filter under Unbalanced Three-Phase Load Conditions Thu, 26 Mar 2015 08:59:43 +0000 This paper focuses on a four-wire shunt active power filter (APF) control scheme proposed to improve the performance of the APF. This filter is used to compensate harmonic distortion in three-phase four-wire systems. Several harmonic suppression techniques have been widely proposed and applied to minimize harmonic effects. The proposed control scheme can compensate harmonics and reactive power of the nonlinear loads simultaneously. This approach is compared to the conventional shunt APF reference compensation strategy. The developed algorithm is validated by simulation tests using MATLAB Simulink. The obtained results have demonstrated the effectiveness of the proposed scheme and confirmed the theoretical developments for balanced and unbalanced nonlinear loads. Z. Chelli, R. Toufouti, A. Omeiri, and S. Saad Copyright © 2015 Z. Chelli et al. All rights reserved. Candidate Smoke Region Segmentation of Fire Video Based on Rough Set Theory Thu, 26 Mar 2015 08:03:01 +0000 Candidate smoke region segmentation is the key link of smoke video detection; an effective and prompt method of candidate smoke region segmentation plays a significant role in a smoke recognition system. However, the interference of heavy fog and smoke-color moving objects greatly degrades the recognition accuracy. In this paper, a novel method of candidate smoke region segmentation based on rough set theory is presented. First, Kalman filtering is used to update video background in order to exclude the interference of static smoke-color objects, such as blue sky. Second, in RGB color space smoke regions are segmented by defining the upper approximation, lower approximation, and roughness of smoke-color distribution. Finally, in HSV color space small smoke regions are merged by the definition of equivalence relation so as to distinguish smoke images from heavy fog images in terms of component value variety from center to edge of smoke region. The experimental results on smoke region segmentation demonstrated the effectiveness and usefulness of the proposed scheme. Yaqin Zhao Copyright © 2015 Yaqin Zhao. All rights reserved. Quasi-ADS-B Based UAV Conflict Detection and Resolution to Manned Aircraft Wed, 25 Mar 2015 09:59:56 +0000 A Conflict Detection and Resolution (CD&R) system for manned/unmanned aerial vehicle (UAV) based on Automatic Dependent Surveillance-Broadcast (ADS-B) concept is designed and verified in this paper. The 900 MHz XBee-Pro is selected as data transponder to broadcast flight information among participating aircraft in omnirange. Standard Compact Position Report (CPR) format packet data are automatically broadcasted by ID sequencing under Quasi-ADS-B mechanism. Time Division Multiple Access (TDMA) monitoring checks the designated time slot and reallocates the conflict ID. This mechanism allows the transponder to effectively share data with multiple aircraft in near airspace. The STM32f103 microprocessor is designed to handle RF, GPS, and flight data with Windows application on manned aircraft and ground control station simultaneously. Different conflict detection and collision avoidance algorithms can be implemented into the system to ensure flight safety. The proposed UAV/CD&R using Quasi-ADS-B transceiver is tested using ultralight aircraft flying at 100–120 km/hr speed in small airspace for mission simulation. The proposed hardware is also useful to additional applications to mountain hikers for emergency search and rescue. The fundamental function by the proposed UAV/CD&R using Quasi-ADS-B is verified with effective signal broadcasting for surveillance and efficient collision alert and avoidance performance to low altitude flights. Chin E. Lin and Ya-Hsien Lai Copyright © 2015 Chin E. Lin and Ya-Hsien Lai. All rights reserved. Performance Analysis of Homogeneous On-Chip Large-Scale Parallel Computing Architectures for Data-Parallel Applications Tue, 24 Mar 2015 09:23:31 +0000 On-chip computing platforms are evolving from single-core bus-based systems to many-core network-based systems, which are referred to as On-chip Large-scale Parallel Computing Architectures (OLPCs) in the paper. Homogenous OLPCs feature strong regularity and scalability due to its identical cores and routers. Data-parallel applications have their parallel data subsets that are handled individually by the same program running in different cores. Therefore, data-parallel applications are able to obtain good speedup in homogenous OLPCs. The paper addresses modeling the speedup performance of homogeneous OLPCs for data-parallel applications. When establishing the speedup performance model, the network communication latency and the ways of storing data of data-parallel applications are modeled and analyzed in detail. Two abstract concepts (equivalent serial packet and equivalent serial communication) are proposed to construct the network communication latency model. The uniform and hotspot traffic models are adopted to reflect the ways of storing data. Some useful suggestions are presented during the performance model’s analysis. Finally, three data-parallel applications are performed on our cycle-accurate homogenous OLPC experimental platform to validate the analytic results and demonstrate that our study provides a feasible way to estimate and evaluate the performance of data-parallel applications onto homogenous OLPCs. Xiaowen Chen, Zhonghai Lu, Axel Jantsch, Shuming Chen, Yang Guo, Shenggang Chen, and Hu Chen Copyright © 2015 Xiaowen Chen et al. All rights reserved. Hybrid Model: An Efficient Symmetric Multiprocessor Reference Model Tue, 24 Mar 2015 07:18:41 +0000 Functional verification has become one of the main bottlenecks in the cost-effective design of embedded systems, particularly for symmetric multiprocessors. It is estimated that verification in its entirety accounts for up to 60% of design resources, including duration, computer resources, and total personnel. Simulation-based verification is a long-standing approach used to locate design errors in the symmetric multiprocessor verification. The greatest challenge of simulation-based verification is the creation of the reference model of the symmetric multiprocessor. In this paper, we propose an efficient symmetric multiprocessor reference model, Hybrid Model, written with SystemC. SystemC can provide a high-level simulation environment and is faster than the traditional hardware description languages. Hybrid Model has been implemented in an efficient 32-bit symmetric multiprocessor verification. Experimental results show our proposed model is a fast, accurate, and efficient symmetric multiprocessor reference model and it is able to help designers to locate design errors easily and accurately. Shupeng Wang, Kai Huang, Tianyi Xie, and Xiaolang Yan Copyright © 2015 Shupeng Wang et al. All rights reserved. Performance Analysis of SNR-Based HDAF M2M Cooperative Networks Mon, 23 Mar 2015 12:10:16 +0000 The lower bound on outage probability (OP) of mobile-to-mobile (M2M) cooperative networks over N-Nakagami fading channels is derived for SNR-based hybrid decode-amplify-forward (HDAF) relaying. The OP performance under different conditions is evaluated through numerical simulation to verify the accuracy of the analysis. These results show that the fading coefficient, number of cascaded components, relative geometric gain, and power-allocation are important parameters that influence this performance. Lingwei Xu, Hao Zhang, and T. Aaron Gulliver Copyright © 2015 Lingwei Xu et al. All rights reserved. Adaptive Jamming Suppression in Coherent FFH System Using Weighted Equal Gain Combining Receiver over Fading Channels with Imperfect CSI Sun, 22 Mar 2015 12:21:18 +0000 Fast frequency hopping (FFH) is commonly used as an antijamming communication method. In this paper, we propose efficient adaptive jamming suppression schemes for binary phase shift keying (BPSK) based coherent FFH system, namely, weighted equal gain combining (W-EGC) with the optimum and suboptimum weighting coefficient. We analyze the bit error ratio (BER) of EGC and W-EGC receivers with partial band noise jamming (PBNJ), frequency selective Rayleigh fading, and channel estimation errors. Particularly, closed-form BER expressions are presented with diversity order two. Our analysis is verified by simulations. It is shown that W-EGC receivers significantly outperform EGC. As compared to the maximum likelihood (ML) receiver in conventional noncoherent frequency shift keying (FSK) based FFH, coherent FFH/BPSK W-EGC receivers also show significant advantages in terms of BER. Moreover, W-EGC receivers greatly reduce the hostile jammers’ jamming efficiency. Yishan He, Yufan Cheng, Gang Wu, Binhong Dong, and Shaoqian Li Copyright © 2015 Yishan He et al. All rights reserved. Compressive Background Modeling for Foreground Extraction Mon, 16 Mar 2015 16:29:06 +0000 Robust and efficient foreground extraction is a crucial topic in many computer vision applications. In this paper, we propose an accurate and computationally efficient background subtraction method. The key idea is to reduce the data dimensionality of image frame based on compressive sensing and in the meanwhile apply sparse representation to build the current background by a set of preceding background images. According to greedy iterative optimization, the background image and background subtracted image can be recovered by using a few compressive measurements. The proposed method is validated through multiple challenging video sequences. Experimental results demonstrate the fact that the performance of our approach is comparable to those of existing classical background subtraction techniques. Yong Wang, Qian Lu, Dianhong Wang, and Wei Liu Copyright © 2015 Yong Wang et al. All rights reserved. A Novel Directionlet-Based Image Denoising Method Using MMSE Estimator and Laplacian Mixture Distribution Wed, 11 Mar 2015 14:04:54 +0000 A novel method based on directionlet transform is proposed for image denoising under Bayesian framework. In order to achieve noise removal, the directionlet coefficients of the uncorrupted image are modeled independently and identically by a two-state Laplacian mixture model with zero mean. The expectation-maximization algorithm is used to estimate the parameters that characterize the assumed prior model. Within the framework of Bayesian theory, the directionlet coefficients of noise-free image are estimated by a nonlinear shrinkage function based on weighted average of the minimum mean square error estimator. We demonstrate through simulations with images contaminated by additive white Gaussian noise that the proposed method is very competitive when compared with other methods in terms of both peak signal-to-noise ratio and visual quality. Yixiang Lu, Qingwei Gao, Dong Sun, Dexiang Zhang, Yi Xia, and Hui Wang Copyright © 2015 Yixiang Lu et al. All rights reserved.