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Regression analysis of squeezing-induced hybrid nanofluid flow in Darcy-Forchheimer porous medium

Applied Mathematics and Mechanics(English Edition) 2025年第1期46卷 193-208页

作者： K.MUHAMMAD M.SARFRAZ department of Humanities and sciences School of Electrical Engineering and Computer Science National University of Sciences and Technology department of Mathematics Quaid-i-Azam University

This article presents a mathematical model addressing a scenario involving a hybrid nanofluid flow between two infinite parallel plates. One plate remains stationary, while the other moves downward at a squeezing velocity. The space between these plates contains a Darcy-Forchheimer porous medium. A mixture of water-based fluid with gold(Au) and silicon dioxide(Si O2) nanoparticles is formulated. In contrast to the conventional Fourier's heat flux equation, this study employs the Cattaneo-Christov heat flux equation. A uniform magnetic field is applied perpendicular to the flow direction, invoking magnetohydrodynamic(MHD) effects. Further, the model accounts for Joule heating, which is the heat generated when an electric current passes through the fluid. The problem is solved via NDSolve in MATHEMATICA. Numerical and statistical analyses are conducted to provide insights into the behavior of the nanomaterials between the parallel plates with respect to the flow, energy transport, and skin *** findings of this study have potential applications in enhancing cooling systems and optimizing thermal management strategies. It is observed that the squeezing motion generates additional pressure gradients within the fluid, which enhances the flow rate but reduces the frictional drag. Consequently, the fluid is pushed more vigorously between the plates, increasing the flow velocity. As the fluid experiences higher flow rates due to the increased squeezing effect, it spends less time in the region between the plates. The thermal relaxation, however, abruptly changes the temperature, leading to a decrease in the temperature fluctuations.

关键词： convective boundary condition Darcy-Forchheimer medium hybrid nanofluid Joule heating magnetohydrodynamic (MHD) numerical solution O175.2 O361 regression analysis squeezing flow

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Intelligent integrated sensing and communication:a survey

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Science China(Information sciences) 2025年第03期68卷 5-46页

作者： Jifa ZHANG Weidang LU Chengwen XING Nan ZHAO Naofal AL-DHAHIR George K.KARAGIANNIDIS Xiaoniu YANG School of Information and Communication engineering Dalian University of Technology College of Information engineering Zhejiang University of Technology School of Information and Electronics Beijing Institute of Technology department of electrical and computer engineering The University of Texas at Dallas department of electrical and computer engineering Aristotle University of Thessaloniki

Integrated sensing and communication (ISAC) is a promising technique to increase spectral efficiency and support various emerging applications by sharing the spectrum and hardware between these functionalities. However, the traditional ISAC schemes are highly dependent on the accurate mathematical model and suffer from the challenges of high complexity and poor performance in practical scenarios. Recently, artificial intelligence (AI) has emerged as a viable technique to address these issues due to its powerful learning capabilities, satisfactory generalization capability, fast inference speed, and high adaptability for dynamic environments, facilitating a system design shift from model-driven to data-driven. Intelligent ISAC, which integrates AI into ISAC, has been a hot topic that has attracted many researchers to investigate. In this paper, we provide a comprehensive overview of intelligent ISAC, including its motivation, typical applications, recent trends, and challenges. In particular, we first introduce the basic principle of ISAC, followed by its key techniques. Then, an overview of AI and a comparison between model-based and AI-based methods for ISAC are provided. Furthermore, the typical applications of AI in ISAC and the recent trends for AI-enabled ISAC are reviewed. Finally, the future research issues and challenges of intelligent ISAC are discussed.

关键词： artificial intelligence deep learning deep reinforcement learning federated learning generative artificial intelligence integrated sensing and communication machine learning transfer learning

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Optimizing BERT for Bengali Emotion Classification: Evaluating Knowledge Distillation, Pruning, and Quantization

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computer Modeling in engineering & sciences 2025年第2期142卷 1637-1666页

作者： Md Hasibur Rahman Mohammed Arif Uddin Zinnat Fowzia Ria Rashedur M.Rahman department of electrical and computer engineering North South UniversityDhaka1229Bangladesh

The rapid growth of digital data necessitates advanced natural language processing(NLP)models like BERT(Bidi-rectional Encoder Representations from Transformers),known for its superior performance in text ***,BERT’s size and computational demands limit its practicality,especially in resource-constrained *** research compresses the BERT base model for Bengali emotion classification through knowledge distillation(KD),pruning,and quantization *** Bengali being the sixth most spoken language globally,NLP research in this area is *** approach addresses this gap by creating an efficient BERT-based model for Bengali *** have explored 20 combinations for KD,quantization,and pruning,resulting in improved speedup,fewer parameters,and reduced memory *** best results demonstrate significant improvements in both speed and *** instance,in the case of mBERT,we achieved a 3.87×speedup and 4×compression ratio with a combination of Distil+Prune+Quant that reduced parameters from 178 to 46 M,while the memory size decreased from 711 to 178 *** results offer scalable solutions for NLP tasks in various languages and advance the field of model compression,making these models suitable for real-world applications in resource-limited environments.

关键词： Bengali NLP black-box distillation emotion classification model compression post-training quantization unstructured pruning

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Detectability of Discrete Event Systems Under Sensor Attacks

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Journal of Systems Science & Complexity 2025年第01期 150-177页

作者： RITSUKA K. LIN Feng LAFORTUNE Stéphane WANG Caisheng department of electrical engineering and computer Science University of Michigan department of electrical and computer engineering Wayne State University

The authors consider the property of detectability of discrete event systems in the presence of sensor attacks in the context of cyber-security. The authors model the system using an automaton and study the general notion of detectability where a given set of state pairs needs to be(eventually or periodically) distinguished in any estimate of the state of the system. The authors adopt the ALTER sensor attack model from previous work and formulate four notions of CA-detectability in the context of this attack model based on the following attributes: strong or weak; eventual or periodic. The authors present verification methods for strong CA-detectability and weak CA-detectability. The authors present definitions of strong and weak periodic CA-detectability that are based on the construction of a verifier automaton called the augmented CA-observer. The development also resulted in relaxing assumptions in prior results on D-detectability, which is a special case of CA-detectability.

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Low-profile,low sidelobe array antenna with ultrawide beam coverage for UAV communication

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Chinese Journal of Aeronautics 2025年第1期38卷 444-454页

作者： Mei LI Zhiliang SHANG Lin PU Ming-Chun TANG Lei ZHU School of Microelectronics and Communication engineering Chongqing UniversityChongqing 400044China department of electrical and computer engineering University of MacaoMacao SAR 999078China

This paper presents a design method to implement an antenna array characterized by ultra-wide beam coverage,low profile,and low Sidelobe Level(SLL)for the application of Unmanned Aerial Vehicle(UAV)air-to-ground *** array consists of ten broadside-radiating,ultrawide-beamwidth elements that are cascaded by a central-symmetry series-fed network with tapered currents following Dolph-Chebyshev distribution to provide low ***,an innovative design of end-fire Huygens source antenna that is compatible with metal ground is presented.A low-profile,half-mode Microstrip Patch Antenna(MPA)is utilized to serve as the magnetic dipole and a monopole is utilized to serves as the electric dipole,constructing the compact,end-fire,grounded Huygens source ***,two opposite-oriented end-fire Huygens source antennas are seamlessly integrated into a single antenna element in the form of monopole-loaded MPA to accomplish the ultrawide,broadside-radiating *** consideration has been applied into the design of series-fed network as well as antenna element to compensate the adverse coupling effects between elements on the radiation *** indicates an ultrawide Half-Power Beamwidth(HPBW)of 161°and a low SLL of-25 dB with a high gain of 12 d Bi under a single-layer *** concurrent ultrawide beamwidth and low SLL make it particularly attractive for applications of UAV air-to-ground communication.

关键词： Array antenna Broad beam Fan beam Low sidelobe level Chebyshev synthesis UAV communication

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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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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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PS-CoT-Adapter: adapting plan-and-solve chain-of-thought for ScienceQA

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Science China(Information sciences) 2025年第1期68卷 392-393页

作者： Qun LI Haixin SUN Fu XIAO Yiming WANG Xinping GAO Bir BHANU School of computer Science Nanjing University of Posts and Telecommunications Purple Mountain Laboratories department of electrical and computer engineering University of California at Riverside

Large language models (LLMs) have recently shown remarkable performance in a variety of natural language processing (NLP) *** further explore LLMs'reasoning abilities in solving complex problems,recent research [1-3]has investigated chain-of-thought (CoT) reasoning in complex multimodal scenarios,such as science question answering (ScienceQA) tasks [4],by fine-tuning multimodal models through human-annotated CoT ***,collected CoT rationales often miss the necessary rea-soning steps and specific expertise.

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Robust Transmission Design for Federated Learning Through Over-the-Air Computation

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China Communications 2025年第03期 65-75页

作者： Hamideh Zamanpour Abyaneh Saba Asaad Amir Masoud Rabiei School of electrical and computer engineering College of Engineering University of Tehran department of electrical engineering and computer Science York University

Over-the-air computation(AirComp) enables federated learning(FL) to rapidly aggregate local models at the central server using waveform superposition property of wireless channel. In this paper, a robust transmission scheme for an AirCompbased FL system with imperfect channel state information(CSI) is proposed. To model CSI uncertainty, an expectation-based error model is *** main objective is to maximize the number of selected devices that meet mean-squared error(MSE)requirements for model broadcast and model aggregation. The problem is formulated as a combinatorial optimization problem and is solved in two ***, the priority order of devices is determined by a sparsity-inducing procedure. Then, a feasibility detection scheme is used to select the maximum number of devices to guarantee that the MSE requirements are met. An alternating optimization(AO) scheme is used to transform the resulting nonconvex problem into two convex subproblems. Numerical results illustrate the effectiveness and robustness of the proposed scheme.

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Enhanced Acceleration for Generalized Nonconvex Low-Rank Matrix Learning

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Chinese Journal of Electronics 2025年第1期34卷 98-113页

作者： Hengmin Zhang Jian Yang Wenli Du Bob Zhang Zhiyuan Zha Bihan Wen School of electrical and Electronic engineering Nanyang Technological University School of computer Science and engineering Nanjing University of Science and Technology School of Information Science and engineering East China University of Science and Technology department of electrical and computer engineering University of Macau

Matrix minimization techniques that employ the nuclear norm have gained recognition for their applicability in tasks like image inpainting, clustering, classification, and reconstruction. However, they come with inherent biases and computational burdens, especially when used to relax the rank function, making them less effective and efficient in real-world scenarios. To address these challenges, our research focuses on generalized nonconvex rank regularization problems in robust matrix completion, low-rank representation, and robust matrix regression. We introduce innovative approaches for effective and efficient low-rank matrix learning, grounded in generalized nonconvex rank relaxations inspired by various substitutes for the ?0-norm relaxed functions. These relaxations allow us to more accurately capture low-rank structures. Our optimization strategy employs a nonconvex and multi-variable alternating direction method of multipliers, backed by rigorous theoretical analysis for complexity and *** algorithm iteratively updates blocks of variables, ensuring efficient convergence. Additionally, we incorporate the randomized singular value decomposition technique and/or other acceleration strategies to enhance the computational efficiency of our approach, particularly for large-scale constrained minimization problems. In conclusion, our experimental results across a variety of image vision-related application tasks unequivocally demonstrate the superiority of our proposed methodologies in terms of both efficacy and efficiency when compared to most other related learning methods.

关键词： Learning systems Image recognition Minimization Computational efficiency Complexity theory Matrix decomposition Optimization Image reconstruction Singular value decomposition Convergence

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