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Nonparametric Statistical Feature Scaling Based Quadratic Regressive Convolution Deep Neural Network for Software Fault Prediction

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Computers, Materials & Continua 2024年第3期78卷 3469-3487页

作者： Sureka Sivavelu Venkatesh Palanisamy school of Computer Science engineering and information Systems Vellore Institute of TechnologyVellore632014India

The development of defect prediction plays a significant role in improving software quality. Such predictions are used to identify defective modules before the testing and to minimize the time and cost. The software with defects negatively impacts operational costs and finally affects customer satisfaction. Numerous approaches exist to predict software defects. However, the timely and accurate software bugs are the major challenging issues. To improve the timely and accurate software defect prediction, a novel technique called Nonparametric Statistical feature scaled QuAdratic regressive convolution Deep nEural Network (SQADEN) is introduced. The proposed SQADEN technique mainly includes two major processes namely metric or feature selection and classification. First, the SQADEN uses the nonparametric statistical Torgerson–Gower scaling technique for identifying the relevant software metrics by measuring the similarity using the dice coefficient. The feature selection process is used to minimize the time complexity of software fault prediction. With the selected metrics, software fault perdition with the help of the Quadratic Censored regressive convolution deep neural network-based classification. The deep learning classifier analyzes the training and testing samples using the contingency correlation coefficient. The softstep activation function is used to provide the final fault prediction results. To minimize the error, the Nelder–Mead method is applied to solve non-linear least-squares problems. Finally, accurate classification results with a minimum error are obtained at the output layer. Experimental evaluation is carried out with different quantitative metrics such as accuracy, precision, recall, F-measure, and time complexity. The analyzed results demonstrate the superior performance of our proposed SQADEN technique with maximum accuracy, sensitivity and specificity by 3%, 3%, 2% and 3% and minimum time and space by 13% and 15% when compared with the two sta

关键词： Software defect prediction feature selection nonparametric statistical Torgerson-Gower scaling technique quadratic censored regressive convolution deep neural network softstep activation function nelder-mead method

Performance Analysis and Optimization of Energy Harvesting Modulation for Multi-User Integrated Data and Energy Transfer

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China Communications 2024年第1期21卷 148-162页

作者： Yizhe Zhao Yanliang Wu Jie Hu Kun Yang school of information and Communication engineering University of Electronic Science and Technology of ChinaChengdu 611731China

Integrated data and energy transfer(IDET)enables the electromagnetic waves to transmit wireless energy at the same time of data delivery for lowpower *** this paper,an energy harvesting modulation(EHM)assisted multi-user IDET system is studied,where all the received signals at the users are exploited for energy harvesting without the degradation of wireless data transfer(WDT)*** joint IDET performance is then analysed theoretically by conceiving a practical time-dependent wireless *** the aid of the AO based algorithm,the average effective data rate among users are maximized by ensuring the BER and the wireless energy transfer(WET)*** results validate and evaluate the IDET performance of the EHM assisted system,which also demonstrates that the optimal number of user clusters and IDET time slots should be allocated,in order to improve the WET and WDT performance.

关键词： energy harvesting modulation(EHM) integrated data and energy transfer(IDET) performance analysis wireless data transfer(WDT) wireless energy transfer(WET)

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Representation learning: serial-autoencoder for personalized recommendation

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Frontiers of Computer Science 2024年第4期18卷 61-72页

作者： Yi ZHU Yishuai GENG Yun LI Jipeng QIANG Xindong WU school of information engineering Yangzhou UniversityYangzhou 225127China Key Laboratory of Knowledge engineering with Big Data(Ministry of Education of the People’s Republic of China) Hefei University of TechnologyHefei 230009China school of Computer Science and information engineering Hefei University of TechnologyHefei 230009China

Nowadays,the personalized recommendation has become a research hotspot for addressing information *** this,generating effective recommendations from sparse data remains a ***,auxiliary information has been widely used to address data sparsity,but most models using auxiliary information are linear and have limited *** to the advantages of feature extraction and no-label requirements,autoencoder-based methods have become quite ***,most existing autoencoder-based methods discard the reconstruction of auxiliary information,which poses huge challenges for better representation learning and model *** address these problems,we propose Serial-Autoencoder for Personalized Recommendation(SAPR),which aims to reduce the loss of critical information and enhance the learning of feature ***,we first combine the original rating matrix and item attribute features and feed them into the first autoencoder for generating a higher-level representation of the ***,we use a second autoencoder to enhance the reconstruction of the data representation of the prediciton rating *** output rating information is used for recommendation *** experiments on the MovieTweetings and MovieLens datasets have verified the effectiveness of SAPR compared to state-of-the-art models.

关键词： personalized recommendation autoencoder representation learning collaborative filtering

Deep Global Multiple-Scale and Local Patches Attention Dual-Branch Network for Pose-Invariant Facial Expression Recognition

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Computer Modeling in engineering & Sciences 2024年第4期139卷 405-440页

作者： Chaoji Liu Xingqiao Liu Chong Chen Kang Zhou school of Electrical and information engineering Jiangsu UniversityZhenjiang212013China school of Electrical engineering Yancheng Institute of TechnologyYancheng224051China

Pose-invariant facial expression recognition(FER)is an active but challenging research topic in computer *** with the involvement of diverse observation angles,FER makes the training parameter models inconsistent from one view to *** study develops a deep global multiple-scale and local patches attention(GMS-LPA)dual-branch network for pose-invariant FER to weaken the influence of pose variation and selfocclusion on recognition *** this research,the designed GMS-LPA network contains four main parts,i.e.,the feature extraction module,the global multiple-scale(GMS)module,the local patches attention(LPA)module,and the model-level fusion *** feature extraction module is designed to extract and normalize texture information to the same *** GMS model can extract deep global features with different receptive fields,releasing the sensitivity of deeper convolution layers to pose-variant and *** LPA module is built to force the network to focus on local salient features,which can lower the effect of pose variation and self-occlusion on recognition ***,the extracted features are fused with a model-level strategy to improve recognition *** experimentswere conducted on four public databases,and the recognition results demonstrated the feasibility and validity of the proposed methods.

关键词： Pose-invariant FER global multiple-scale(GMS) local patches attention(LPA) model-level fusion

An Effective Power Optimization Approach Based on Whale Optimization Algorithm with Two-Populations and Mutation Strategies

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Chinese Journal of Electronics 2024年第2期33卷 423-435页

作者： Juncai HE Zhenxue HE Jia LIU Yan ZHANG Fan ZHANG Fangfang LIANG Tao WANG Limin XIAO Xiang WANG Hebei Agricultural University Beijing information Science and technology University school of Computer Science and engineering Beihang University school of Electronic and information engineering Beihang University

Power is an issue that must be considered in the design of logic circuits. Power optimization is a combinatorial optimization problem, since it is necessary to search for a logical expression that consumes the least amount of power from a large number of Reed-Muller(RM) logical expressions. The existing approach for optimizing the power of multi-output mixed polarity RM(MPRM) logic circuits suffer from poor optimization results. To solve this problem, a whale optimization algorithm with two-populations strategy and mutation strategy(TMWOA) is proposed in this paper. The two-populations strategy speeds up the convergence of the algorithm by exchanging information about the two-populations. The mutation strategy enhances the ability of the algorithm to jump out of the local optimal solutions by using the information of the current optimal solution. Based on the TMWOA, we propose a multi-output MPRM logic circuits power optimization approach(TMMPOA). Experiments based on the benchmark circuits of the Microelectronics Center of North Carolina(MCNC) validate the effectiveness and superiority of the proposed TMMPOA.

关键词： Logic circuits Benchmark testing Search problems Whale optimization algorithms Microelectronics Optimization Convergence

Identification of the Hammerstein nonlinear system with noisy output measurements

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Control Theory and technology 2024年第2期22卷 203-212页

作者： Qiming Zha Feng Li Ranran Liu school of Electrical and information engineering Jiangsu University of TechnologyChangzhou213001JiangsuChina school of Automobile and Traffic engineering Jiangsu University of TechnologyChangzhou213001JiangsuChina

In this research, we present a methodology to identify the Hammerstein nonlinear system with noisy output measurements. The Hammerstein system presented is comprised of neural fuzzy model (NFM) as its static nonlinear block and auto-regressive with extra input (ARX) model as its dynamic linear block, and a two-step procedure is accomplished using signal combination. In the first step, in the case of input–output of Gaussian signals, the correlation function-based least squares (CF-LS) technique is utilized to identify the linear block, solving the problem that the intermediate variable connecting nonlinear and linear blocks cannot be measured. In the second step, to improve the identification accuracy of the nonlinear block parameters, an improved particle swarm optimization technique is developed under input–output of random signals. The validity and accuracy of the presented scheme are verified by a numerical simulation and a practical nonlinear process, and the results illustrate that the proposed methodology can identify well the Hammerstein nonlinear system with noisy output measurements.

关键词： Hammerstein nonlinear system Signal combination Auto-regressive with extra input Improved particle swarm optimization

Novel method for extraction of ship target with overlaps in SAR image via EM algorithm

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Journal of Systems engineering and Electronics 2024年第4期35卷 874-887页

作者： CAO Rui WANG Yong school of Electronics and information engineering Harbin Institute of TechnologyHarbin 150001China

The quality of synthetic aperture radar(SAR)image degrades in the case of multiple imaging projection planes(IPPs)and multiple overlapping ship targets,and then the performance of target classification and recognition can be *** addressing this issue,a method for extracting ship targets with overlaps via the expectation maximization(EM)algorithm is ***,the scatterers of ship targets are obtained via the target detection ***,the EM algorithm is applied to extract the scatterers of a single ship target with a single ***,a novel image amplitude estimation approach is pro-posed,with which the radar image of a single target with a sin-gle IPP can be *** proposed method can accom-plish IPP selection and targets separation in the image domain,which can improve the image quality and reserve the target information most *** of simulated and real mea-sured data demonstrate the effectiveness of the proposed method.

关键词： expectation maximization(EM)algorithm image processing imaging projection plane(IPP) overlapping ship tar-get synthetic aperture radar(SAR)

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Weighted sum power maximization for STAR-RIS-aided SWIPT systems with nonlinear energy harvesting

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Science China(information Sciences) 2024年第10期67卷 343-358页

作者： Weiping SHI Cunhua PAN Feng SHU Yongpeng WU Jiangzhou WANG Yongqiang BAO Jin TIAN school of Network and Communication Nanjing Vocational College of Information Technology National Mobile Communications Research Laboratory Southeast University school of information and Communication engineering Hainan University school of Electronic and Optical engineering Nanjing University of Science and Technology Shanghai Key Laboratory of Navigation and Location Based Services Shanghai Jiao Tong University school of engineering University of Kent school of information and Communication engineering Nanjing Institute of Technology engineering school of Networks and Telecommunications Jinling Institute of Technology

The conventional reconfigurable intelligent surface(RIS) is limited to reflecting incident signals,thereby imposing constraints on the placement of the transmitter and receiver, which hinders achieving comprehensive signal coverage across an entire area. This paper investigates a simultaneously transmitting and reflecting(STAR)-RIS-aided simultaneous wireless information and power transfer(SWIPT) system with a nonlinear energy harvesting model under three different RIS transmission protocols: energy splitting(ES),time switching(TS), and mode switching(MS). The objective of this paper is to maximize the weighted sum power(WSP) of all energy harvesting receivers(EHRs) while ensuring fairness in the collected power among them. This is achieved by jointly optimizing the transmit beamforming at the base station(BS)and the transmission and reflection coefficients at the STAR-RIS, subject to rate constraints for information decoding receivers(IDRs), transmit power constraint at the BS, and coefficient constraints of each element at the STAR-RIS corresponding to the three protocols. Solving this optimization problem poses challenges because of the complicated objective function and numerous coupled optimization variables of the ES STAR-RIS. To address this complexity, an efficient alternating optimization(AO) approach is proposed as an iterative solution method that achieves suboptimal results. The AO algorithm is then extended to MS STAR-RIS and TS STAR-RIS. Specifically, for MS STRA-RIS, binary constraints in the STAR-RIS coefficient optimization subproblem are handled using the first-order approximation technique along with the penalty function method. For TS STAR-RIS, apart from optimizing BS transmit beamforming and STAR-RIS coefficients subproblems, the transmission and reflection time allocation of STAR-RIS also needs *** findings demonstrate that compared to conventional RIS-aided systems, utilizing three different protocols in a STAR-RIS-aided sy

关键词： STAR-RIS beamforming SWIPT alternating optimization nonlinear energy harvesting

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Numerical Simulation of Droplet Generation in Coaxial Microchannels

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Fluid Dynamics & Materials Processing 2024年第3期20卷 487-504页

作者： Zongjun Yin Rong Su Hui Xu school of Mechanical engineering Anhui Institute of Information TechnologyWuhu241100China

In this study,numerical simulations of the pinching-off phenomena displayed by the dispersed phase in a continuous phase have been conducted using COMSOL Multiphysics(level-set method).Four flow patterns,namely“drop flow”,“jet flow”,“squeeze flow”,and“co-flow”,have been obtained for different flow velocity ratios,channel diameter ratios,density ratios,viscosity ratios,and surface *** flow pattern map of two-phase flow in coaxial microchannels has been obtained accordingly,and the associated droplet generation process has been critically discussed considering the related frequency,diameter,and pinch-off *** particular,it is shown that the larger the flow velocity ratio,the smaller the diameter of generated droplets and the shorter the pinch-off *** pinch-off length of a droplet is influenced by the channel diameter ratio and density *** changes in viscosity ratio have a negligible influence on the droplet generation pinching *** an increase in surface tension,the frequency of generation and pinch-off length of droplets decrease,but for small surface tension the generation diameter of droplet increases.

关键词： Droplet generation characteristics coaxial microchannels flow patterns pinch-off length