Journal of Electrical and Computer Engineering The latest articles from Hindawi Publishing Corporation © 2015 , Hindawi Publishing Corporation . 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. A Study of Transmission Control Method for Distributed Parameters Measurement in Large Factories and Storehouses Sun, 08 Mar 2015 12:41:22 +0000 For the characteristics of parameters dispersion in large factories, storehouses, and other applications, a distributed parameter measurement system is designed that is based on the ring network. The structure of the system and the circuit design of the master-slave node are described briefly. The basic protocol architecture about transmission communication is introduced, and then this paper comes up with two kinds of distributed transmission control methods. Finally, the reliability, extendibility, and control characteristic of these two methods are tested through a series of experiments. Moreover, the measurement results are compared and discussed. Shujing Su, Min Yi, Wei Ji, Qing He, and Xiufeng Xie Copyright © 2015 Shujing Su et al. All rights reserved. Improvement of High-Power Three-Level Explosion-Proof Inverters Using Soft Switching Control Based on Optimized Power-Loss Algorithm Mon, 02 Mar 2015 10:25:37 +0000 The high-power three-level explosion-proof inverters demand high thermal stability of power devices, and a set of theories and methods is needed to achieve an accurate power-loss calculation of power devices, to establish heat dissipation model, and ultimately to reduce the power loss to improve thermal stability of system. In this paper, the principle of neutral point clamped three-level (NPC3L) inverter is elaborated firstly, and a fourth-order RC equivalent circuit of IGBT is derived, on which basis the power-loss model of IGBT and the optimized maternal power-loss thermal model, using an optimized power-loss algorithm, are established. Secondly, in accordance with the optimized maternal power-loss thermal model, the generic formulas of power-loss calculation are deduced to calculate the power-loss modification values of NPC3L and soft switching three-level (S3L) inverters, which will be the thermal sources during thermal analysis for maternal power-loss thermal models. Finally, the experiment conducted on the 2.1 MW experimental platform shows that S3L inverter has the same excellent output characteristics with NPC3L inverter, reduces the power loss significantly by 213 W in each half-bridge, and decreases the temperature by 10°C, coinciding with the theoretical calculation, which verifies the accuracy of optimized power-loss algorithm and the effectiveness of the improvement. Shi-Zhou Xu and Feng-You He Copyright © 2015 Shi-Zhou Xu and Feng-You He. All rights reserved. Design of IIR Digital Filters with Arbitrary Flatness Using Iterative Quadratic Programming Wed, 25 Feb 2015 14:11:53 +0000 This paper presents a design method of Chebyshev-type and inverse-Chebyshev-type infinite impulse response (IIR) filters with an approximately linear phase response. In the design of Chebyshev-type filters, the flatness condition in the stopband is preincorporated into a transfer function, and an equiripple characteristic in the passband is achieved by iteratively solving the QP problem using the transfer function. In the design of inverse-Chebyshev-type filters, the flatness condition in the passband is added to the constraint of the QP problem as the linear matrix equality, and an equiripple characteristic in the stopband is realized by iteratively solving the QP problem. To guarantee the stability of the obtained filters, we apply the extended positive realness to the QP problem. As a result, the proposed method can design the filters with more high precision than the conventional methods. The effectiveness of the proposed design method is illustrated with some examples. Yasunori Sugita Copyright © 2015 Yasunori Sugita. All rights reserved. Improved RSSI Positioning Algorithm for Coal Mine Underground Locomotive Tue, 17 Feb 2015 14:22:25 +0000 Aiming at the large positioning errors of traditional coal mine underground locomotive, an improved received signal strength indication (RSSI) positioning algorithm for coal mine underground locomotive was proposed. The RSSI value fluctuates heavily due to the poor environment of coal mine underground. The nodes with larger RSSI value corrected by Gaussian-weighted model were selected as beacon nodes. In order to reduce the positioning error further, the estimated positions of the locomotives were corrected by the weighted distance correction method. The difference between actual position and estimated position of beacon node was regarded as the positioning error and was given a corresponding weight. The results of simulation show that the positioning accuracy of Gaussian-weighted model is better than statistical average model and Gaussian model and it has a high positioning accuracy after correcting positioning error correction. In the 10 m of communication range, positioning error can be maintained at 0.5 m. Bin Ge, Kai Wang, Jianghong Han, and Bao Zhao Copyright © 2015 Bin Ge et al. All rights reserved. Robust Abnormal Event Recognition via Motion and Shape Analysis at ATM Installations Mon, 16 Feb 2015 13:44:05 +0000 Automated teller machines (ATM) are widely being used to carry out banking transactions and are becoming one of the necessities of everyday life. ATMs facilitate withdrawal, deposit, and transfer of money from one account to another round the clock. However, this convenience is marred by criminal activities like money snatching and attack on customers, which are increasingly affecting the security of bank customers. In this paper, we propose a video based framework that efficiently identifies abnormal activities happening at the ATM installations and generates an alarm during any untoward incidence. The proposed approach makes use of motion history image (MHI) and Hu moments to extract relevant features from video. Principle component analysis has been used to reduce the dimensionality of features and classification has been carried out by using support vector machine. Analysis has been carried out on different video sequences by varying the window size of MHI. The proposed framework is able to distinguish the normal and abnormal activities like money snatching, harm to the customer by virtue of fight, or attack on the customer with an average accuracy of 95.73%. Vikas Tripathi, Durgaprasad Gangodkar, Vivek Latta, and Ankush Mittal Copyright © 2015 Vikas Tripathi et al. All rights reserved. Maximum Likelihood Sequence Detection Receivers for Nonlinear Optical Channels Mon, 16 Feb 2015 06:28:34 +0000 The space-time whitened matched filter (ST-WMF) maximum likelihood sequence detection (MLSD) architecture has been recently proposed (Maggio et al., 2014). Its objective is reducing implementation complexity in transmissions over nonlinear dispersive channels. The ST-WMF-MLSD receiver (i) drastically reduces the number of states of the Viterbi decoder (VD) and (ii) offers a smooth trade-off between performance and complexity. In this work the ST-WMF-MLSD receiver is investigated in detail. We show that the space compression of the nonlinear channel is an instrumental property of the ST-WMF-MLSD which results in a major reduction of the implementation complexity in intensity modulation and direct detection (IM/DD) fiber optic systems. Moreover, we assess the performance of ST-WMF-MLSD in IM/DD optical systems with chromatic dispersion (CD) and polarization mode dispersion (PMD). Numerical results for a 10 Gb/s, 700 km, and IM/DD fiber-optic link with 50 ps differential group delay (DGD) show that the number of states of the VD in ST-WMF-MLSD can be reduced ~4 times compared to an oversampled MLSD. Finally, we analyze the impact of the imperfect channel estimation on the performance of the ST-WMF-MLSD. Our results show that the performance degradation caused by channel estimation inaccuracies is low and similar to that achieved by existing MLSD schemes (~0.2 dB). Gabriel N. Maggio, Mario R. Hueda, and Oscar E. Agazzi Copyright © 2015 Gabriel N. Maggio et al. All rights reserved. A 3.9 μs Settling-Time Fractional Spread-Spectrum Clock Generator Using a Dual-Charge-Pump Control Technique for Serial-ATA Applications Thu, 12 Feb 2015 06:47:18 +0000 A low-jitter fractional spread-spectrum clock generator (SSCG) utilizing a fast-settling dual-charge-pump (CP) technique is developed for serial-advanced technology attachment (SATA) applications. The dual-CP architecture reduces a design area to 60% by shrinking an effective capacitance of a loop filter. Moreover, the settling-time is reduced by 4 μs to charge a current to the capacitor by only main-CP in initial period in settling-time. The SSCG is fabricated in a 0.13 μm CMOS and achieves settling time of 3.91 μs faster than 8.11 μs of a conventional SSCG. The random jitter and total jitter at 250 cycles at 1.5 GHz are less than 3.2 and 10.7 psrms, respectively. The triangular modulation signal frequency is 31.5 kHz and the modulation deviation is from −5000 ppm to 0 ppm at 1.5 GHz. The EMI reduction is 10.0 dB. The design area and power consumption are 300 × 700 μm and 18 mW, respectively. Takashi Kawamoto, Masato Suzuki, and Takayuki Noto Copyright © 2015 Takashi Kawamoto et al. All rights reserved. Analysis of Generalization Ability for Different AdaBoost Variants Based on Classification and Regression Trees Tue, 10 Feb 2015 12:22:19 +0000 As a machine learning method, AdaBoost is widely applied to data classification and object detection because of its robustness and efficiency. AdaBoost constructs a global and optimal combination of weak classifiers based on a sample reweighting. It is known that this kind of combination improves the classification performance tremendously. As the popularity of AdaBoost increases, many variants have been proposed to improve the performance of AdaBoost. Then, a lot of comparison and review studies for AdaBoost variants have also been published. Some researchers compared different AdaBoost variants by experiments in their own fields, and others reviewed various AdaBoost variants by basically introducing these algorithms. However, there is a lack of mathematical analysis of the generalization abilities for different AdaBoost variants. In this paper, we analyze the generalization abilities of six AdaBoost variants in terms of classification margins. The six compared variants are Real AdaBoost, Gentle AdaBoost, Modest AdaBoost, Parameterized AdaBoost, Margin-pruning Boost, and Penalized AdaBoost. Finally, we use experiments to verify our analyses. Shuqiong Wu and Hiroshi Nagahashi Copyright © 2015 Shuqiong Wu and Hiroshi Nagahashi. All rights reserved. An Improved Harmony Search Algorithm for Power Distribution Network Planning Mon, 02 Feb 2015 10:00:12 +0000 Distribution network planning because of involving many variables and constraints is a multiobjective, discrete, nonlinear, and large-scale optimization problem. Harmony search (HS) algorithm is a metaheuristic algorithm inspired by the improvisation process of music players. HS algorithm has several impressive advantages, such as easy implementation, less adjustable parameters, and quick convergence. But HS algorithm still has some defects such as premature convergence and slow convergence speed. According to the defects of the standard algorithm and characteristics of distribution network planning, an improved harmony search (IHS) algorithm is proposed in this paper. We set up a mathematical model of distribution network structure planning, whose optimal objective function is to get the minimum annual cost and constraint conditions are overload and radial network. IHS algorithm is applied to solve the complex optimization mathematical model. The empirical results strongly indicate that IHS algorithm can effectively provide better results for solving the distribution network planning problem compared to other optimization algorithms. Wei Sun and Xingyan Chang Copyright © 2015 Wei Sun and Xingyan Chang. All rights reserved. Analysis of an Underground Vertical Electrically Small Wire Antenna Thu, 29 Jan 2015 14:04:43 +0000 The problem considered is a vertical electrically small wire antenna located underground, which transmits electromagnetic signals to the ground. Getting Green’s function of the vertical dipole underground was the first step to calculate this issue. A quasistatic situation was considered to make an approximation on Sommerfeld integral for easy solution. The method of moments was used to solve the current distribution on the antenna surface at different frequencies, which laid a good foundation for obtaining the electric field of the antenna. Then the axial and radial components of the electric field with the radial distance on the ground were investigated, as well as the voltage received on the ground. Furthermore, the influence of the frequency and stratum parameters on current and electric field was studied to understand the variation clearly. Shuwei Dong, Aiguo Yao, and Fanhe Meng Copyright © 2015 Shuwei Dong et al. All rights reserved. Probabilistic Routing Based on Two-Hop Information in Delay/Disruption Tolerant Networks Mon, 26 Jan 2015 13:44:34 +0000 We investigate an opportunistic routing protocol in delay/disruption tolerant networks (DTNs) where the end-to-end path between source and destination nodes may not exist for most of the time. Probabilistic routing protocol using history of encounters and transitivity (PRoPHET) is an efficient history-based routing protocol specifically proposed for DTNs, which only utilizes the delivery predictability of one-hop neighbors to make a decision for message forwarding. In order to further improve the message delivery rate and to reduce the average overhead of PRoPHET, in this paper we propose an improved probabilistic routing algorithm (IPRA), where the history information of contacts for the immediate encounter and two-hop neighbors has been jointly used to make an informed decision for message forwarding. Based on the Opportunistic Networking Environment (ONE) simulator, the performance of IPRA has been evaluated via extensive simulations. The results show that IPRA can significantly improve the average delivery rate while achieving a better or comparable performance with respect to average overhead, average delay, and total energy consumption compared with the existing algorithms. Xu Wang, Rongxi He, Bin Lin, and Ying Wang Copyright © 2015 Xu Wang et al. All rights reserved. Low-Complexity Robust Capon Beamforming Based on Reduced-Rank Technique Wed, 21 Jan 2015 12:59:27 +0000 Existing robust Capon beamformers achieve robustness against steering vector errors at a high cost in terms of computational complexity. Computationally efficient robust Capon beamforming approach based on the reduced-rank technique is proposed in this paper. The proposed method projects the received data snapshots onto a lower dimensional subspace consisting of the matched filters of the multistage Wiener filter (MSWF). The subsequent adaptive beamforming will then be performed within this subspace. The combination of the benefit of the robust adaptive beamforming and the reduced-rank technique improves the performance on combating steering vector errors and lowering the computational complexity. Zaifang Xi, Xiao-feng Wu, Shuyue Wu, Zhijun Tang, and Shigang Hu Copyright © 2015 Zaifang Xi et al. All rights reserved. Adaptive Reference Image Set Selection in Automated X-Ray Inspection Mon, 29 Dec 2014 13:58:55 +0000 The automatic radioscopic inspection of industrial parts usually uses reference based methods. These methods select, as benchmark for comparison, image data from good parts to detect the anomalies of parts under inspection. However, parts can vary within the specification during the production process, which makes comparison of older reference image sets with current images of parts difficult and increases the probability of false rejections. To counter this variability, the reference image sets have to be updated. This paper proposes an adaptive reference image set selection procedure to be used in the assisted defect recognition (ADR) system in turbine blade inspection. The procedure first selects an initial reference image set using an approach called ADR Model Optimizer and then uses positive rate in a sliding-time window to determine the need to update the reference image set. Whenever there is a need, the ADR Model Optimizer is retrained with new data consisting of the old reference image sets augmented with false rejected images to generate a new reference image set. The experimental result demonstrates that the proposed procedure can adaptively select a reference image set, leading to an inspection process with a high true positive rate and a low false positive rate. Xinhua Xiao, Andrew Ferro, Tao Ma, Chia Y. Han, Xuefu Zhou, and William Wee Copyright © 2014 Xinhua Xiao et al. All rights reserved. Joint DOA and DOD Estimation in Bistatic MIMO Radar without Estimating the Number of Targets Tue, 09 Dec 2014 11:31:52 +0000 Existing subspace-based direction finding methods for multiple-input multiple-output (MIMO) radar assume perfect knowledge about the dimension of the signal or noise subspace, which is hard to be established without prior knowledge of the signal environment. In this paper, an efficient method for joint DOA and DOD estimation in bistatic MIMO radar without estimating the number of targets is presented. The proposed method computes an estimate of the noise subspace using the power of R (POR) technique. Then the two-dimensional (2D) direction finding problem is decoupled into two successive one-dimensional (1D) angle estimation problems by employing the rank reduction (RARE) estimator. Zaifang Xi, Xiao-feng Wu, Shuyue Wu, Zhijun Tang, and Shigang Hu Copyright © 2014 Zaifang Xi et al. All rights reserved. A Low Leakage Autonomous Data Retention Flip-Flop with Power Gating Technique Sun, 30 Nov 2014 12:34:13 +0000 With the scaling of technology process, leakage power becomes an increasing portion of total power. Power gating technology is an effective method to suppress the leakage power in VLSI design. When the power gating technique is applied in sequential circuits, such as flip-flops and latches, the data retention is necessary to store the circuit states. A low leakage autonomous data retention flip-flop (ADR-FF) is proposed in this paper. Two high- transistors are utilized to reduce the leakage power consumption in the sleep mode. The data retention cell is composed of a pair of always powered cross-coupled inverters in the slave latch. No extra control signals and complex operations are needed for controlling the data retention and restoration. The data retention flip-flops are simulated with NCSU 45 nm technology. The postlayout simulation results show that the leakage power of the ADR-FF reduces 51.39% compared with the Mutoh-FF. The active power of the ADR-FF is almost equal to other data retention flip-flops. The average state mode transition time of ADR-FF decreases 55.98%, 51.35%, and 21.07% as compared with Mutoh-FF, Balloon-FF, and Memory-TG-FF, respectively. Furthermore, the area overhead of ADR-FF is smaller than other data retention flip-flops. Xiaohui Fan, Yangbo Wu, Hengfeng Dong, and Jianping Hu Copyright © 2014 Xiaohui Fan et al. All rights reserved.