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Franklin Open 2024年 6卷

作者： Duarte, Aldo Nghiem, Truong X. Wei, Shuangqing Division of Electrical and Computer Engineering School of Electrical Engineering and Commputer Science Louisiana State University Baton Rouge 70803 LA United States School of Informatics Computing and Cyber Systems Northern Arizona University Flagstaff 86011 AZ United States

In distributed optimization schemes consisting of a group of agents connected to a central coordinator, the optimization algorithm often involves the agents solving private local sub-problems and exchanging data frequently with the coordinator to solve the global distributed problem. In those cases, the query-response mechanism usually causes excessive communication costs to the system, necessitating communication reduction in scenarios where communication is costly. Integrating Gaussian processes (GP) as a learning component to the Alternating Direction Method of Multipliers (ADMM) has proven effective in learning each agent's local proximal operator to reduce the required communication exchange. A key element for integrating GP into the ADMM algorithm is the querying mechanism upon which the coordinator decides when communication with an agent is required. In this paper, we formulate a general querying decision framework as an optimization problem that balances reducing the communication cost and decreasing the prediction error. Under this framework, we propose a joint query strategy that takes into account the joint statistics of the query and ADMM variables and the total communication cost of all agents in the presence of uncertainty caused by the GP regression. In addition, we derive three different decision mechanisms that simplify the general framework by making the communication decision for each agent individually. We integrate multiple measures to quantify the trade-off between the communication cost reduction and the optimization solution's accuracy/optimality. The proposed methods can achieve significant communication reduction and good optimization solution accuracy for distributed optimization, as demonstrated by extensive simulations of a distributed sharing problem. © 2024 The Authors

关键词： ADMM Communication reduction Distributed optimization Gaussian process Proximal operator

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Visualization System Using Virtual Reality for Work Improvement in Small and Medium Manufacturing Industries

Visualization System Using Virtual Reality for Work Improvem...

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IEEE International Conference on Embedded and Real-Time Computing systems and Applications (RTCSA)

作者： Shogo Ogihara Tetsuro Kato Takafumi Kawasaki Yuki Okura Takeshi Iwamoto Electrical and Computer Engineering Graduate School of Engineering Toyama Prefectural University Toyama Japan IoTry Inc. Toyama Japan Department of Information Systems Engineering Toyama Prefectural University Toyama Japan

The advancement of digitalization in the manufacturing industry has visualization that enables managers to comprehend the status and operation time of machines, thereby allowing them to identify and address bottlenecks in production lines. Although Gantt charts are commonly used for visualization in the manufacturing industry, there is an increasing need to adopt methods that more effectively visualize past events to facilitate understanding. Consequently, we have developed a Virtual Reality (VR) system aimed at improving the operations of small and medium-sized manufacturing enterprises through visualization. By utilizing sensors installed within the factory, we demonstrated that the VR space facilitates comprehensible work analysis instruction and simulation of optimal work processes.

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QAOA-Assisted Benders' Decomposition for Mixed-integer Linear Programming

QAOA-Assisted Benders' Decomposition for Mixed-integer Linea...

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IEEE International Conference on Communications (ICC)

作者： Zhongqi Zhao Lei Fan Yuanxiong Guo Yu Wang Zhu Han Lajos Hanzo Department of Electrical and Computer Engineering University of Houston Houston TX USA Department of Engineering Technology University of Houston Houston TX USA Department of Information Systems and Cyber Security University of Texas at San Antonio San Antonio TX USA Department of Computer and Information Sciences Temple University Philadelphia PA USA School of Electronics and Computer Science University of Southampton Southampton UK

ISBN: (数字)9781728190549

ISBN: (纸本)9781728190556

Benders' decomposition (BD) algorithm constitutes a powerful mathematical programming method of solving mixed-integer linear programming (MILP) problems with a specific block structure. Nevertheless, BD still needs to solve an NP-hard quasi-integer programming master problem (MAP), which motivates us to harness the popular variational quantum algorithm (VQA) to assist BD. More specifically, we choose the popular quantum approximate optimization algorithm (QAOA) of the VQA family. We transfer the BD's MAP into a digital quantum circuit associated with a physically tangible problem-specific ansatz; and then solve it with the aid of a state-of-the-art digital quantum computer. Next, we evaluate the computational results and discuss the feasibility of the proposed algorithm. The hybrid approach advocated, which utilizes both classical and digital quantum computers, is capable of tackling many practical MILP problems in communication and networking, as demonstrated by a pair of case studies.

关键词： Performance evaluation Quantum computing Quantum algorithm Programming Approximation algorithms Mixed integer linear programming Quantum circuit

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Integrated electro-optic isolator on thin-film lithium niobate (Jun, 10.1038/s41566-023-01227-8, 2023)

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NATURE PHOTONICS 2023年第8期17卷 732-732页

作者： Yu, Mengjie Cheng, Rebecca Reimer, Christian He, Lingyan Luke, Kevin Puma, Eric Shao, Linbo Shams-Ansari, Amirhassan Ren, Xinyi Grant, Hannah R. R. Johansson, Leif Zhang, Mian Loncar, Marko John A. Paulson School of Engineering and Applied Sciences Harvard University Cambridge MA USA Ming Hsieh Department of Electrical and Computer Engineering University of Southern California Los Angeles CA USA HyperLight Cambridge MA USA Draper Scholar The Charles Stark Draper Laboratory Cambridge MA USA Bradley Department of Electrical and Computer Engineering Virginia Tech Blacksburg VA USA Freedom Photonics Goleta CA USA

Optical isolators are indispensable components of almost any optical system and are used to protect a laser from unwanted reflections for phase-stable coherent operation. The emergence of chip-scale optical systems, powered by semiconductor lasers that are integrated on the same chip, has generated a demand for a fully integrated optical isolator. Conventional approaches, which rely on the use of magneto-optic materials to break Lorentz reciprocity, present substantial challenges in terms of material integration. Although alternative magnetic-free approaches have been explored, an integrated isolator with a low insertion loss, high isolation ratio, broad bandwidth and low power consumption on a monolithic material platform is yet to be achieved. Here we realize a non-reciprocal travelling-wave-based electro-optic isolator on thin-film lithium niobate. The isolator enables a maximum optical isolation of 48.0 dB with an on-chip insertion loss of 0.5 dB and uses a single-frequency microwave drive power of 21 dBm. The isolation ratio remains larger than 37 dB across a tunable optical wavelength range from 1,510 to 1,630 nm. We realize a hybrid distributed feedback laser–lithium niobate isolator module that successfully protects the single-mode operation and linewidth of the laser from reflection. Our result represents an important step towards a practical high-performance optical isolator on chip.

关键词： Integrated optics Nanophotonics and plasmonics Nonlinear optics

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Resilient control under denial-of-service and uncertainty: An adaptive dynamic programming approach

arXiv

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arXiv 2024年

作者： Gao, Weinan Jiang, Zhong-Ping Chai, Tianyou State Key Laboratory of Synthetical Automation for Process Industries Northeastern University Shenyang110819 China Department of Electrical and Computer Engineering Tandon School of Engineering New York University BrooklynNY11201 United States

In this paper, a new framework for the resilient control of continuous-time linear systems under denial-of-service (DoS) attacks and system uncertainty is presented. Integrating techniques from reinforcement learning and output regulation theory, it is shown that resilient optimal controllers can be learned directly from real-time state and input data collected from the systems subjected to attacks. Sufficient conditions are given under which the closed-loop system remains stable given any upper bound of DoS attack duration. Simulation results are used to demonstrate the efficacy of the proposed learning-based framework for resilient control under DoS attacks and model uncertainty. © 2024, CC BY.

关键词： Denial-of-service attack

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Multi-Band Hybrid DRA for O-RAN Compliant 5G Small Cell Radio Unit

Multi-Band Hybrid DRA for O-RAN Compliant 5G Small Cell Radi...

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Microwave, Antennas & Circuits (ICMAC), International Conference on

作者： Asadullah Muhammad U. Khan Nosherwan Shoaib Ali Ahmed Atef A. Aburas Abdulkarim AlDabbagh Anas M. A. Saleh School of Electrical Engineering and Computer Science (SEECS) National University of Sciences and Technology (NUST) Islamabad Pakistan Telecom R&D Department Advanced Communications & Electronics Systems (ACES) Riyadh Kingdom of Saudi Arabia

ISBN: (数字)9798331518424

ISBN: (纸本)9798331518431

A 4-element hybrid MIMO antenna is presented for O-RAN compliant 5G small cell radio unit. The antenna design consists of U-shaped microstrip radiator elements which are designed to operate in FR1 band having impedance bandwidth of 2.16-4.5 GHz. A partial cylindrical DRA is integrated with the U-shaped microstrip for the FR2 band resonance having impedance bandwidth of 20.8 - 29.55 GHz. MIMO antenna elements are rotated 90° and placed in square arrangement resulting in the overall size of 72.12mm x 72.12mm making this antenna easily coalescent with the RFFE module of the Open RU. The antenna has a peak gain of 1.42 dB on the FR1 band and 3 dB in the FR2 band. The antenna offers omni-directional radiation characteristics making it suitable for small cell applications for both indoor as well as outdoor implementation.

关键词： Wireless LAN 5G mobile communication Resonant frequency Open RAN Microstrip antennas Bandwidth Microstrip components Resonance Impedance Gain

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Dual Distillation Fusion for Weakly Supervised Anomaly Detection in Surveillance Videos

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IEEE Transactions on Circuits and systems for Video Technology 2025年

作者： Zhang, Sijia Gong, Maoguo Lin, Yiming Li, Hao Gao, Yuan Zhang, Yihong Shaanxi Normal University School of Computer Science Xi'an China Xidian University School of Electronic Engineering Key Laboratory of Collaborative Intelligence Systems Ministry of Education Xi'an China Inner Mongolia Normal University Academy of Artificial Intelligence College of Mathematics Science Hohhot China

Anomaly detection in surveillance videos aims to differentiate anomalies from regular events by discriminative representations, which has gathered considerable attention due to its significant effect to public security. However, most existing works are limited in the lack of annotated samples, and lots of approaches find it challenging to avoid the well-reconstruction of anomalous data. To alleviate these issues, we propose a dual distillation fusion framework for weakly supervised anomaly detection. We reformulate the anomaly detection problem into two steps, namely filtering anomalies and inpainting normal patterns. Each step corresponds to one branch of the dual distillation. Specifically, the dual distillation comprises the contrastive distillation module and the inpainting distillation module. The contrastive distillation optimizes the encoder to filter out abnormal features and capture key normal features, while the inpainting distillation refines the decoder to inpaint normal patterns on the encoded features. The contrastive distillation module and the inpainting distillation module are optimized iteratively in a self-training manner with video-level labeled data. Moreover, a joint optimization module is devised to effectively fuse the distilled encoder and decoder, thereby collectively improving the anomaly detection performance. During the training phase, we take into account the diversity of normal samples by selecting pseudo normal and abnormal samples with high confidence from abnormal videos. These selected samples, along with original normal frames, are then fed into the subsequent training iterations to enhance the distinguishing ability of the model. Experimental results show that our proposed method performs competitively on five benchmark datasets. © 1991-2012 IEEE.

关键词： Iterative decoding

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Generative Artificial Intelligence Assisted Wireless Sensing: Human Flow Detection in Practical Communication Environments

arXiv

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arXiv 2024年

作者： Wang, Jiacheng Du, Hongyang Niyato, Dusit Xiong, Zehui Kang, Jiawen Ai, Bo Han, Zhu Kim, Dong In School of Computer Science and Engineering Nanyang Technological University Singapore639798 Singapore Pillar of Information Systems Technology and Design Singapore University of Technology and Design Singapore China Ministry of Education Guangzhou510006 China State Key Laboratory of Rail Traffic Control and Safety Beijing Engineering Research Center of High-Speed Railway Broadband Mobile Communications Beijing Jiaotong University Beijing100044 China Department of Electrical and Computer Engineering University of Houston HoustonTX77004 United States Department of Electrical and Computer Engineering Sungkyunkwan University Suwon16419 Korea Republic of

Groundbreaking applications such as ChatGPT have heightened research interest in generative artificial intelligence (GAI). Essentially, GAI excels not only in content generation but also signal processing, offering support for wireless sensing. Hence, we introduce a novel GAI-assisted human flow detection system (G-HFD). Rigorously, G-HFD first uses the channel state information (CSI) to estimate the velocity and acceleration of propagation path length change of the human induced reflection (HIR). Then, given the strong inference ability of the diffusion model, we propose a unified weighted conditional diffusion model (UW-CDM) to denoise the estimation results, enabling detection of the number of targets. Next, we use the CSI obtained by a uniform linear array with wavelength spacing to estimate the HIR’s time of flight and direction of arrival (DoA). In this process, UW-CDM solves the problem of ambiguous DoA spectrum, ensuring accurate DoA estimation. Finally, through clustering, G-HFD determines the number of subflows and the number of targets in each subflow, i.e., the subflow size. The evaluation based on practical downlink communication signals shows G-HFD’s accuracy of subflow size detection can reach 91%. This validates its effectiveness and underscores the significant potential of GAI in the context of wireless sensing. © 2024, CC BY.

关键词： Artificial intelligence

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Games of social distancing during an epidemic: Local vs statistical information

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computer Methods and Programs in Biomedicine Update 2022年 2卷

作者： Lagos, A.-R. Kordonis, I. Papavassilopoulos, G.P. National Technical University of Athens School of Electrical and Computer Engineering Greece USC Viterbi Ming Hsieh Department of Electrical and Computer Engineering - Systems United States

The choices of a population to apply social distancing are modeled as a Nash game, where the agents determine their social interactions. The interconnections among the agents are modeled by a network. The main contribution of this work is the study of an agent-based epidemic model coupled with a social distancing game, which are both determined by the networked structure of human interconnections. The information available to the agents plays a crucial role. We examine the case that the agents know exactly the health states of their neighbors and the case they have only statistical information for the global prevalence of the epidemic. The agents are considered to be myopic, and thus, the Nash equilibria of static games for each day are studied. Through theoretical analysis, we characterize these Nash equilibria and we propose algorithms to compute them. Interestingly, in the case of statistical information the equilibrium strategies for an agent, at each day, are either full isolation or no social distancing at all. Through experimental studies, we observe that in the case of local information, the agents can significantly affect the prevalence of the epidemic with low social distancing, while in the other case, they can also affect the prevalence of the epidemic, but they have to pay the burden of not being well informed by applying strict social distancing. Moreover, the effects of the network structure, the virus transmissibility, the number of vulnerable agents, the health care system capacity and the information quality (fake news) are discussed and relevant simulations are provided. © 2022 The Authors

关键词： Epidemics on networks Games on networks Information patterns Nash game Social distancing

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Artificial Intelligence Assistive Non-Destructive Testing of Welding Joints: A Review

SSRN

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SSRN 2025年

作者： Mian Qaisar, Saeed Say, Dalila Krichen, Moez Zidi, Salah Hatem Bettaher Laboratory IResCoMath University of Gabes Gabes6029 Tunisia Electrical and Computer Engineering Department Effat University Jeddah21478 Saudi Arabia Faculty of Computer Science and Information Technology Al-Baha University ReDCAD Laboratory National School of Engineers of Sfax University of Sfax Al-Baha65528 Saudi Arabia

Non-Destructive Testing (NDT) is an appealing technique for confirming the welding quality and ensuring structural integrity without causing damage. It assists in regulatory compliance, risk mitigation, and process optimization for improved industrial reliability. This study reviews potential NDT approaches. Through a rigorous analysis of existing surveys, we aim to decipher the current landscape and highlight the significant advancements in the field. Because of the potential of artificial intelligence (AI) assistive X-ray imaging-based NDT, we particularly examine the integration of AI algorithms and X-ray imaging in the NDT of welds. This convergence represents a paradigm shift, redefining traditional methods and ushering in a new era of precision, automation, and efficiency. As we navigate through potential X-ray imaging datasets, delve into crucial image processing techniques, examine feature extraction methods, and explore AI algorithms, our survey reveals the intricate interplay of technologies that drive automated weld defect categorization. The review broadens its focus by including various practical applications, highlighting the adaptable utility of AI-assistive X-ray imaging for weld defect detection in potential industrial applications. Moreover, the promising opportunities and nuanced challenges associated with integrating X-ray imaging and AI in weld integrity assessment are highlighted. It provides a comprehensive perspective on this rapidly evolving field. © 2025, The Authors. All rights reserved.

关键词： Fracture mechanics

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