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A State-Migration Particle Swarm Optimizer for Adaptive Latent Factor Analysis of High-Dimensional and Incomplete Data

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IEEE/CAA Journal of Automatica Sinica 2024年第11期11卷 2220-2235页

作者： Jiufang Chen Kechen Liu Xin Luo Ye Yuan Khaled Sedraoui Yusuf Al-Turki MengChu Zhou IEEE the College of Computer Science and Technology Chongqing University of Posts and Telecommunications the Department of Computer Science Columbia University the College of Computer and Information Science Southwest University the Department of Electrical and Computer Engineering Faculty of Engineeringand also with K.A.CARE Energy Research and Innovation CenterKing Abdulaziz University the Center of Research Excellence in Renewable Energy and Power Systems the Department of Electrical and Computer EngineeringFaculty of Engineeringand also with K.A.CARE Energy Research and Innovation CenterKing Abdulaziz University the Department of Electrical and Computer Engineering New Jersey Institute of Technology

High-dimensional and incomplete(HDI) matrices are primarily generated in all kinds of big-data-related practical applications. A latent factor analysis(LFA) model is capable of conducting efficient representation learning to an HDI matrix,whose hyper-parameter adaptation can be implemented through a particle swarm optimizer(PSO) to meet scalable ***, conventional PSO is limited by its premature issues,which leads to the accuracy loss of a resultant LFA model. To address this thorny issue, this study merges the information of each particle's state migration into its evolution process following the principle of a generalized momentum method for improving its search ability, thereby building a state-migration particle swarm optimizer(SPSO), whose theoretical convergence is rigorously proved in this study. It is then incorporated into an LFA model for implementing efficient hyper-parameter adaptation without accuracy loss. Experiments on six HDI matrices indicate that an SPSO-incorporated LFA model outperforms state-of-the-art LFA models in terms of prediction accuracy for missing data of an HDI matrix with competitive computational ***, SPSO's use ensures efficient and reliable hyper-parameter adaptation in an LFA model, thus ensuring practicality and accurate representation learning for HDI matrices.

关键词： Data science generalized momentum high-dimensional and incomplete(HDI)data hyper-parameter adaptation latent factor analysis(LFA) particle swarm optimization(PSO)

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Opportunities and challenges of diffusion models for generative AI

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National Science Review 2024年第12期11卷 254-276页

作者： Minshuo Chen Song Mei Jianqing Fan Mengdi Wang Department of Electrical and Computer Engineering Princeton University Department of Statistics University of CaliforniaBerkeley Department of Operations Research and Financial Engineering Princeton University

Diffusion models, a powerful and universal generative artificial intelligence technology, have achieved tremendous success and opened up new possibilities in diverse applications. In these applications, diffusion models provide flexible high-dimensional data modeling, and act as a sampler for generating new samples under active control towards task-desired properties. Despite the significant empirical success, theoretical underpinnings of diffusion models are very limited, potentially slowing down principled methodological innovations for further harnessing and improving diffusion models. In this paper, we review emerging applications of diffusion models to highlight their sample generation capabilities under various control goals. At the same time, we dive into the unique working flow of diffusion models through the lens of stochastic processes. We identify theoretical challenges in analyzing diffusion models, owing to their complicated training procedure and interaction with the underlying data distribution. To address these challenges, we overview several promising advances, demonstrating diffusion models as an efficient distribution learner and a sampler. Furthermore, we introduce a new avenue in high-dimensional structured optimization through diffusion models, where searching for solutions is reformulated as a conditional sampling problem and solved by diffusion models. Lastly, we discuss future directions about diffusion models. The purpose of this paper is to provide a well-rounded exposure for stimulating forward-looking theories and methods of diffusion models.

关键词： generative AI diffusion model sample generation under controls optimization

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Secure beamforming and deployment design for rate-splitting multiple access-based UAV communications

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Science China(Information Sciences) 2025年第1期68卷 342-356页

作者： Bing WANG Xiaofeng TAO Shujun HAN Huici WU Kai YANG Zhu HAN National Engineering Research Center of Mobile Network Technologies Beijing University of Posts and Telecommunications Peng Cheng Laboratory Department of Electrical and Computer Engineering University of Houston

Rate-splitting multiple access(RSMA) has recently gained attention as a potential robust multiple access(MA)scheme for upcoming wireless networks. Given its ability to efficiently utilize wireless resources and design interference management strategies, it can be applied to unmanned aerial vehicle(UAV) networks to provide convenient services for large-scale access ground users. However, due to the line-of-sight(LoS) broadcast nature of UAV transmission, information is susceptible to eavesdropping in RSMA-based UAV networks. Moreover, the superposition of signals at the receiver in such networks becomes complicated. To cope with the challenge, we propose a two-user multi-input single-output(MISO) RSMA-based UAV secure transmission framework in downlink communication networks. In a passive eavesdropping scenario, our goal is to maximize the sum secrecy rate by optimizing the transmit beamforming and deployment location of the UAV-base station(UAV-BS),while considering quality-of-service(QoS) constraints, maximum transmit power, and flight space limitations. To address the non-convexity of the proposed problem, the optimization problem is first decoupled into two subproblems. Then, the successive convex approximation(SCA) method is employed to solve each subproblem using different propositions. In addition, an alternating optimization(AO)-based location RSMA(L-RSMA) beamforming algorithm is developed to implement joint optimization to obtain the suboptimal solution. Numerical results demonstrate that(1) the proposed L-RSMA scheme yields a28.97% higher sum secrecy rate than the baseline L-space division multiple access(SDMA) scheme;(2) the proposed L-RSMA scheme improves the security performance by 42.61% compared to the L-non-orthogonal multiple access(NOMA) scheme.

关键词： rate-splitting multiple access UAV communication precoding optimization deployment location physical layer security

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Cavity-agnostic acoustofluidic manipulations enabled by guided flexural waves on a membrane acoustic waveguide actuator

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Microsystems & Nanoengineering 2024年第2期10卷 153-171页

作者： Philippe Vachon Srinivas Merugu Jaibir Sharma Amit Lal Eldwin J.Ng Yul Koh Joshua E.-Y.Lee Chengkuo Lee Department of Electrical and Computer Engineering National University of SingaporeSingaporeSingapore Institute of Microelectronics Agency for ScienceTechnology and Research(A*STAR)SingaporeSingapore SonicMEMS Laboratory School of Electrical and Computer EngineeringCornell UniversityIthacaNYUSA School of Electrical and Data Engineering University of Technology SydneyUltimoNSWAustralia

This article presents an in-depth exploration of the acoustofluidic capabilities of guided flexural waves(GFWs)generated by a membrane acoustic waveguide actuator(MAWA).By harnessing the potential of GFWs,cavity-agnostic advanced particle manipulation functions are achieved,unlocking new avenues for microfluidic systems and lab-on-a-chip *** localized acoustofluidic effects of GFWs arising from the evanescent nature of the acoustic fields they induce inside a liquid medium are numerically investigated to highlight their unique and promising *** traditional acoustofluidic technologies,the GFWs propagating on the MAWA’s membrane waveguide allow for cavity-agnostic particle manipulation,irrespective of the resonant properties of the fluidic ***,the acoustofluidic functions enabled by the device depend on the flexural mode populating the active region of the membrane *** demonstrations using two types of particles include in-sessile-droplet particle transport,mixing,and spatial separation based on particle diameter,along with streaming-induced counter-flow virtual channel generation in microfluidic PDMS *** experiments emphasize the versatility and potential applications of the MAWA as a microfluidic platform targeted at lab-on-a-chip development and showcase the MAWA’s compatibility with existing microfluidic systems.

关键词： waveguide fluid cavity

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Cross-subcarrier precoder design for massive MIMO-OFDM downlink with symplectic optimization

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Science China(Information Sciences) 2025年第2期68卷 216-229页

作者： Yuxuan ZHANG An-An LU Xiang-Gen XIA Xiqi GAO National Mobile Communications Research Laboratory Southeast University Purple Mountain Laboratories Department of Electrical and Computer Engineering University of Delaware

We propose a cross-subcarrier precoder design(CSPD) for massive multiple-input multiple-output(MIMO) orthogonal frequency division multiplexing(OFDM) downlink. This work aims to significantly improve the channel estimation and signal detection performance by enhancing the smoothness of the frequency domain effective channel. This is accomplished by designing a few vectors known as the transform domain precoding vectors(TDPVs), which are then transformed into the frequency domain to generate the precoders for a set of subcarriers. To combat the effect of channel aging, the TDPVs are optimized under imperfect channel state information(CSI). The optimal precoder structure is derived by maximizing an upper bound of the ergodic weighted sum-rate(WSR) and utilizing the a posteriori beam-based statistical channel model(BSCM). To avoid the large-dimensional matrix inversion, we propose an algorithm with symplectic optimization. Simulation results indicate that the proposed cross-subcarrier precoder design significantly outperforms conventional methods.

关键词： massive MIMO-OFDM cross subcarrier precoder design transform domain precoding vectors effective channel symplectic optimization

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An electrical Impedance Imaging System Towards Edge Intelligence for Non-Destructive Testing of Concrete

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Tsinghua Science and Technology 2024年第3期29卷 883-896页

作者： Abolfazl Roshanpanah Mahdi Abbasi Hani Attar Ayman Amer Mohammad R.Khosravi Ahmed A.Solyman Department of Electrical Engineering Islamic Azad UniversityScience and Research BranceTehran ***Iran Department of Computer Engineering Bu-Ali Sina UniversityHamedan ***Iran Department of Energy Engineering Zarqa UniversityZarqa 13110Jordan Department of Computer Engineering Persian Gulf UniversityBushehr ***Iran Department of Electrical and Electronics Engineering Faculty of Engineering and ArchitectureNişantaşıUniversityIstanbul 34398Turkey

In the construction industry,to prevent accidents,non-destructive tests are necessary and *** impedance tomography is a new technology in non-invasive imaging in which the image of the inner part of conductive bodies is reconstructed by the arrays of external electrodes that are connected on the periphery of the *** equipment is cheap,fast,and edge *** this imaging method,the image of electrical conductivity distribution(or its opposite;electrical impedance)of the internal parts of the target object is *** image reconstruction process is performed by injecting a precise electric current to the peripheral boundaries of the object,measuring the peripheral voltages induced from it and processing the collected *** an electrical impedance tomography system,the voltages measured in the peripheral boundaries have a non-linear equation with the electrical conductivity *** paper presents a cheap electrical Impedance Tomography(EIT)instrument for detecting impurities in the concrete.A voltage-controlled current source,a micro-controller,a set of multiplexers,a set of electrodes,and a personal computer constitute the structure of the *** conducted tests on concrete with impurities show that the designed EIT system can reveal impurities with a good accuracy in a reasonable time.

关键词： non-destructive testing system concrete electrical impedance tomography

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IRS-enabled NOMA communication systems:A network architecture primer with future trends and challenges

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Digital Communications and Networks 2024年第5期10卷 1503-1528页

作者： Haleema Sadia Ahmad Kamal Hassan Ziaul Haq Abbas Ghulam Abbas Muhammad Waqas Zhu Han Faculty of Electrical Engineering and Telecommunications and Networking(TeleCoN)Research Center Ghulam Ishaq Khan Institute of Engineering and Technology(GIKI)Topi 23640Pakistan Faculty of Computer Science and Engineering GIKITopi 23640Pakistan Department of Computer Engineering College of Information TechnologyUniversity of Bahrain32028Bahrain School of Engineering Edith Cowan UniversityPerth WA6027Australia Department of Electrical and Computer Engineering University of HoustonHoustonTX 77004USA Department of Computer Science and Engineering Kyung Hee UniversitySeoul 446-701South Korea

Non-Orthogonal Multiple Access(NOMA)has already proven to be an effective multiple access scheme for5th Generation(5G)wireless *** provides improved performance in terms of system throughput,spectral efficiency,fairness,and energy efficiency(EE).However,in conventional NOMA networks,performance degradation still exists because of the stochastic behavior of wireless *** combat this challenge,the concept of Intelligent Reflecting Surface(IRS)has risen to prominence as a low-cost intelligent solution for Beyond 5G(B5G)*** this paper,a modeling primer based on the integration of these two cutting-edge technologies,i.e.,IRS and NOMA,for B5G wireless networks is *** in-depth comparative analysis of IRS-assisted Power Domain(PD)-NOMA networks is provided through 3-fold ***,a primer is presented on the system architecture of IRS-enabled multiple-configuration PD-NOMA systems,and parallels are drawn with conventional network configurations,i.e.,conventional NOMA,Orthogonal Multiple Access(OMA),and IRS-assisted OMA *** by this,a comparative analysis of these network configurations is showcased in terms of significant performance metrics,namely,individual users'achievable rate,sum rate,ergodic rate,EE,and outage ***,for multi-antenna IRS-enabled NOMA networks,we exploit the active Beamforming(BF)technique by employing a greedy algorithm using a state-of-the-art branch-reduceand-bound(BRB)*** optimality of the BRB algorithm is presented by comparing it with benchmark BF techniques,i.e.,minimum-mean-square-error,zero-forcing-BF,and ***,we present an outlook on future envisioned NOMA networks,aided by IRSs,i.e.,with a variety of potential applications for 6G wireless *** work presents a generic performance assessment toolkit for wireless networks,focusing on IRS-assisted NOMA *** comparative analysis provides a solid foundation for the dev

关键词： Intelligent reflecting surface Non-orthogonal multiple access 6G Beamforming Sum rate Energy efficiency

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Representing a Model for the Anonymization of Big Data Stream Using In-Memory Processing

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Annals of Data Science 2025年第1期12卷 223-252页

作者： Shamsinejad, Elham Banirostam, Touraj Pedram, Mir Mohsen Rahmani, Amir Masoud Department of Computer Engineering Central Tehran Branch Islamic Azad University Tehran Iran Department of Electrical and Computer Engineering Faculty of Engineering Kharazmi University Tehran Iran Department of Computer Engineering Science and Research Branch Islamic Azad University Tehran Iran

In light of the escalating privacy risks in the big data era, this paper introduces an innovative model for the anonymization of big data streams, leveraging in-memory processing within the Spark framework. The approach is founded on the principle of K-anonymity and propels the field forward by critically evaluating various anonymization methods and algorithms, benchmarking their performance with respect to time and space complexities. A distinctive formula for optimized cluster determination in the K-means algorithm is presented, along with a novel tuple expiration time strategy for the efficient purging of clusters. The integration of these components into Spark’s RDD and MLlib modules results in a significant decrease in execution time and data loss rates, even with increasing data volumes. The paper’s notable contributions are its methodological advancements that offer a robust, scalable solution for data anonymization, safeguarding user privacy without sacrificing data utility or processing efficiency. © The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2024.

关键词： Big data

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A Review of Anonymization Algorithms and Methods in Big Data

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Annals of Data Science 2025年第1期12卷 253-279页

In the era of big data, with the increase in volume and complexity of data, the main challenge is how to use big data while preserving the privacy of users. This study was conducted with the aim of finding a solution to this challenge. In this study, we examined various data anonymization methods, including differential privacy, advanced encryption, and strong access controls. In addition, the operation, advantages, disadvantages, and use of these methods, the challenges of adapting these methods to big data, and possible solutions for them were also examined. Our results show that traditional data anonymization methods lack scalability, leading to privacy breaches and data loss. When faced with large volumes of data, these methods may not be able to fully process the data. Also, these methods may be ineffective against re-identification attacks, linkage attacks, and inference attacks. We introduced emerging methods that are capable of providing improved privacy with minimal data loss. These methods have scalability for big data. Finally, we examined future research works and raised important questions that can help improve existing algorithms or develop new methods, better manage the complexity and scale of unstructured data. © The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2024.

关键词： Big data

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Empirical Wavelet Transform Based Method for Identification and Analysis of Sub-synchronous Oscillation Modes Using PMU Data

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Journal of Modern Power Systems and Clean Energy 2024年第1期12卷 34-40页

作者： Joice G.Philip Jaesung Jung Ahmet Onen the Department of Energy Systems Research Ajou UniversitySuwonSouth Korea the Department of Electrical and Electronic Engineering Abdullah Gul UniversityKayseri38080Turkey the Department of Electrical and Computer Engineering College of EngineeringSultan Qaboos UniversityAl-KhoudMuscatOman

This paper proposes an empirical wavelet transform(EWT)based method for identification and analysis of sub-synchronous oscillation(SSO)modes in the power system using phasor measurement unit(PMU)*** phasors from PMUs are preprocessed to check for the presence of *** the presence is established,the signal is decomposed using EWT and the parameters of the mono-components are estimated through Yoshida *** superiority of the proposed method is tested using test signals with known parameters and simulated using actual SSO signals from the Hami Power Grid in Northwest *** show the effectiveness of the proposed EWT-Yoshida method in detecting the SSO and estimating its parameters.

关键词： Empirical wavelet transform(EWT) sub-synchronous oscillation Prony-based method Yoshida algorithm variational mode decomposition phasor measurement unit(PMU)

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