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Efficient Image Super-Resolution With Feature Interaction Weighted Hybrid Network

IEEE Transactions on Multimedia 2025年 27卷 2256-2267页

作者： Li, Wenjie Li, Juncheng Gao, Guangwei Deng, Weihong Yang, Jian Qi, Guo-Jun Lin, Chia-Wen Beijing University of Posts and Telecommunications Pattern Recognition and Intelligent System Laboratory School of Artificial Intelligence Beijing100080 China Shanghai University School of Communication and Information Engineering Shanghai200444 China Nanjing University of Posts and Telecommunications IVIPLab Institute of Advanced Technology Nanjing210046 China Ministry of Education Key Laboratory of Artificial Intelligence Shanghai200240 China Soochow University Provincial Key Laboratory for Computer Information Processing Technology Suzhou215006 China Nanjing University of Science and Technology School of Computer Science and Technology Nanjing210094 China Westlake University Research Center for Industries of the Future School of Engineering Hangzhou310024 China OPPO Research SeattleWA98101 United States National Tsing Hua University Department of Electrical Engineering Institute of Communications Engneering Hsinchu300044 Taiwan

Lightweight image super-resolution aims to reconstruct high-resolution images from low-resolution images using low computational costs. However, existing methods result in the loss of middle-layer features due to activation functions. To minimize the impact of intermediate feature loss on reconstruction quality, we propose a Feature Interaction Weighted Hybrid Network (FIWHN), which comprises a series of Wide-residual Distillation Interaction Block (WDIB) as the backbone. Every third WDIB forms a Feature Shuffle Weighted Group (FSWG) by applying mutual information shuffle and fusion. Moreover, to mitigate the negative effects of intermediate feature loss, we introduce Wide Residual Weighting units within WDIB. These units effectively fuse features of varying levels of detail through a Wide-residual Distillation Connection (WRDC) and a Self-Calibrating Fusion (SCF). To compensate for global feature deficiencies, we incorporate a Transformer and explore a novel architecture to combine CNN and Transformer. We show that our FIWHN achieves a favorable balance between performance and efficiency through extensive experiments on low-level and high-level tasks. © 1999-2012 IEEE.

关键词： Transformers Convolutional neural networks Computational modeling Feature extraction Training Superresolution Adaptation models computer architecture Telecommunications Image reconstruction

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Satellite-UAV Networks for 6G Control: A Sensing-Communication-Computing-Control Closed Loop Perspective

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IEEE Network 2025年

作者： Lei, Chengleyang Fang, Xinran Feng, Wei Chen, Yunfei Xiao, Ming Ge, Ning Mao, Shiwen The Department of Electronic Engineering State Key Laboratory of Space Network and Communications Tsinghua University Beijing100084 China The Department of Engineering University of Durham DurhamDH1 3LE United Kingdom The Department of Information Science and Engineering School of Electrical Engineering and Computer Science Royal Institute of Technology Sweden The Department of Electrical and Computer Engineering Auburn University AuburnAL36849 United States

The future sixth-generation (6G) networks are envisioned to support machines and robots besides human beings. In order to efficiently support machines and robots working in remote and post-disaster areas, satellites and unmanned aerial vehicles (UAVs) can be utilized. In this article, we investigate how satellite-UAV networks can serve robots for their control tasks. We introduce the typical use cases of the satellite-UAV networks for control and outline the relevant challenges. The control process usually involves sensing, communication, computing, and control components, which forms a sensing-communication-computing-control (SC3) closed loop. In analogy with the reflex arc structure of humans, we reveal the indivisibility of the SC3 closed loops and propose a closed-loop-oriented system design framework. Within this framework, we take the closed-loop control performance as the design target, and highlight the holistic consideration of sensing, communication, computing, and control components in the SC3 closed loop. Furthermore, we discuss the extended SC3 closed loop with multiple sensors and robots to decompose complex control systems. A case study is provided to show the performance gain of the proposed closed-loop-oriented system design. Finally, we outline open issues in designing more efficient satellite-UAV networks for control. ©1986-2012 IEEE.

关键词： Unmanned aerial vehicles (UAV)

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Hardware Design and Security Needs Attention: From Survey to Path Forward

arXiv

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arXiv 2025年

作者： Ghimire, Sujan Chowdhury, Muhtasim Alam Latibari, Banafsheh Saber Mamun, Muntasir Carpenter, Jaeden Wolf Tan, Benjamin Pearce, Hammond Satam, Pratik Salehi, Soheil Systems and Industrial Engineering Department University of Arizona TucsonAZ United States Electrical and Computer Engineering Department University of Arizona TucsonAZ United States Department of Electrical and Software Engineering University of Calgary Alberta CalgaryAB Canada School of Computer Science and Engineering University of New South Wales Sydney Australia

Recent advances in attention-based artificial intelligence (AI) models have unlocked vast potential to automate digital hardware design while enhancing and strengthening security measures against various threats. This rapidly emerging field leverages Large Language Models (LLMs) to generate HDL code, identify vulnerabilities, and sometimes mitigate them. The state of the art in this design automation space utilizes optimized LLMs with HDL datasets, creating automated systems for register transfer level(RTL) generation, verification, and debugging and establishing LLM-driven design environments for streamlined logic designs. Additionally, attention-based models like graph attention have shown promise in chip design applications, including floorplanning. This survey investigates the integration of these models into hardware-related domains, emphasizing logic design and hardware security, with or without the use of IP libraries. This study explores the commercial and academic landscape, highlighting technical hurdles and future prospects for automating hardware design and security. Moreover, it provides new insights into the study of LLM-driven design systems, advances in hardware security mechanisms, and the impact of influential works on industry practices. Through the examination of 30 representative approaches and illustrative case studies, this paper underscores the transformative potential of attention-based models in revolutionizing hardware design while addressing the challenges that lie ahead in this interdisciplinary domain. © 2025, CC BY.

关键词： Hardware-software codesign

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Fully Decentralized Computation Offloading in Priority-Driven Edge Computing systems

arXiv

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arXiv 2025年

作者： Aggarwal, Shubham Bastopcu, Melih Zaman, Muhammad Aneeq uz Başar, Tamer Ulukus, Sennur Akar, Nail Coordinated Science Laboratory University of Illinois Urbana Champaign United States Department of Electrical and Electronics Engineering Bilkent University Turkey Department of Electrical and Computer Engineering University of Maryland United States

We develop a novel framework for fully decentralized offloading policy design in multi access edge computing (MEC) systems. The system comprises N power-constrained user equipments (UEs) assisted by an edge server (ES) to process incoming tasks. Tasks are labeled with urgency flags, and in this paper, we classify them under three urgency levels, namely, high, moderate, and low urgency. We formulate the problem of designing computation decisions for the UEs within a large population noncooperative game framework, where each UE selfishly decides on how to split task execution between its local onboard processor and the ES. We employ the weighted average age of information (AoI) metric to quantify information freshness at the UEs. Increased on-board processing consumes more local power, while increased offloading may potentially incur a higher average AoI due to other UEs’ packets being offloaded to the same ES. Thus, we use the mean-field game (MFG) formulation to compute approximate decentralized Nash equilibrium offloading and local computation policies for the UEs to balance between the information freshness and local power consumption. Finally, we provide a projected gradient descent-based algorithm to numerically assess the merits of our approach. Copyright © 2025, The Authors. All rights reserved.

关键词： Computation offloading

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Secure Communication in Dynamic RDARS-Driven systems

arXiv

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arXiv 2025年

作者： Pei, Ziqian Wang, Jintao Zhang, Pingping Shi, Zheng Yang, Guanghua Ma, Shaodan State Key Laboratory of Internet of Things for Smart City The Department of Electrical and Computer Engineering University of Macau Macau999078 China School of Intelligent Systems Science and Engineering Jinan University Zhuhai519070 China

In this letter, we investigate a dynamic reconfigurable distributed antenna and reflection surface (RDARS)driven secure communication system, where the working mode of the RDARS can be flexibly configured. We aim to maximize the secrecy rate by jointly designing the active beamforming vectors, reflection coefficients, and the channel-aware mode selection matrix. To address the non-convex binary and cardinality constraints introduced by dynamic mode selection, we propose an efficient alternating optimization (AO) framework that employs penalty-based fractional programming (FP) and successive convex approximation (SCA) transformations. Simulation results demonstrate the potential of RDARS in enhancing the secrecy rate and show its superiority compared to existing reflection surface-based schemes. Copyright © 2025, The Authors. All rights reserved.

关键词： Secure communication

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A Globally Convergent Method for Computing B-stationary Points of Mathematical Programs with Equilibrium Constraints

arXiv

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arXiv 2025年

作者： Nurkanovic, Armin Leyffer, Sven Systems Control and Optimization Laboratory Department of Microsystems Engineering University of Freiburg Germany Mathematics and Computer Science Division Argonne National Laboratory United States

This paper introduces a method that globally converges to Bstationary points of mathematical programs with equilibrium constraints (MPECs) in a finite number of iterations. B-stationarity is necessary for optimality and means that no feasible first-order direction improves the objective. Given a feasible point of an MPEC, B-stationarity can be certified by solving a linear program with equilibrium constraints (LPEC) constructed at this point. The proposed method solves a sequence of LPECs, which either certify B-stationarity or provide an active-set estimate for the complementarity constraints, and nonlinear programs (NLPs) - referred to as branch NLPs (BNLPs) - obtained by fixing the active set in the MPEC. A BNLP is more regular than the MPEC, easier to solve, and with the correct active set, its solution coincides with the solution of the MPEC. The method has two phases: the first phase identifies a feasible BNLP or certifies local infeasibility, and the second phase solves a finite sequence of BNLPs until a B-stationary point of the MPECis found. The paper provides a detailed convergence analysis and discusses implementation details. In addition, extensive numerical experiments and an open-source software implementation are provided. The experiments demonstrate that the proposed method is more robust and faster than relaxation-based methods, while also providing a certificate of B-stationarity without requiring the usual too-restrictive *** Codes 90C30, 90C33, 49M37, 65K10, 90C11 © 2025, CC BY.

关键词： Nonlinear programming

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Sparse-view CBCT reconstruction using meta-learned neural attenuation field and hash-encoding regularization

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computers in Biology and Medicine 2025年 189卷 109900-109900页

作者： Shin, Heejun Kim, Taehee Lee, Jongho Chun, Se Young Cho, Seungryong Shin, Dongmyung Artificial Intelligence Engineering Division Radisen Co. Ltd. Seoul Korea Republic of Laboratory for Imaging Science and Technology Department of Electrical and Computer Engineering Seoul National University Seoul Korea Republic of Intelligent Computational Imaging Laboratory Department of Electrical and Computer Engineering Seoul National University Seoul Korea Republic of Medical Imaging and Radiotherapy Laboratory Department of Nuclear and Quantum Engineering Korea Advanced Institute of Science and Technology Daejean Korea Republic of

Cone beam computed tomography (CBCT) is an emerging medical imaging technique to visualize the internal anatomical structures of patients. During a CBCT scan, several projection images of different angles or views are collectively utilized to reconstruct a tomographic image. However, reducing the number of projections in a CBCT scan while preserving the quality of a reconstructed image is challenging due to the nature of an ill-posed inverse problem. Recently, a neural attenuation field (NAF) method was proposed by adopting a neural radiance field algorithm as a new way for CBCT reconstruction, demonstrating fast and promising results using only 50 views. However, decreasing the number of projections is still preferable to reduce potential radiation exposure, and a faster reconstruction time is required considering a typical scan time. In this work, we propose a fast and accurate sparse-view CBCT reconstruction (FACT) method to provide better reconstruction quality and faster optimization speed in the minimal number of view acquisitions ( © 2025 Elsevier Ltd

关键词： Image reconstruction

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systems Analysis of Decision-Making Under Ambiguity With Comparative Out-of-Sample Experimental Study of Geometric Dispersion Theory and Cumulative Prospect Theory

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IEEE Transactions on systems, Man, and Cybernetics: systems 2025年

作者： Al-Najjar, Camelia Malakooti, Behnam Case Western Reserve University Department of Electrical Computer and Systems Engineering Cleveland 44106 OH United States

In this article, we develop a new descriptive model for ambiguity decision-making called Ambiguity Geometric Dispersion Theory (A-GDT). In out-of-sample predictions, we find that A-GDT is experimentally superior to all models which it generalizes;specifically, cumulative prospect theory (CPT), subjective expected utility (SEU), alpha-maxmin expected utility (α-MEU), vector expected utility (VEU), and expected utility theory (EUT). We ran an experimental study of 150 decisions under ambiguity by 310 subjects by operationalizing payoffs, probability, and ambiguity. We show that subjects exhibit behavior that contradicts many decision models, such as CPT, SEU, α-MEU, and EUT;but not A-GDT. In out-of-sample studies with the same number of parameters, the A-GDT model predicts both representative (aggregate) agent and individual preferences substantially better than other well-known ambiguity models. Specifically, a three-parameter A-GDT is substantially superior to CPT and all other important models. Furthermore, significance testing in a paired comparison of models shows that subjects’ behavior matches the A-GDT model markedly better than other models. A new rate-of-degradation analysis demonstrates that A-GDT’s predictions are far more stable than other models as the in-sample size is decreased. In addition, the A-GDT model not only can resolve typical Ellsberg-like behavior, but it can also resolve hypothetical and real-life ambiguity problems with multiple sources of ambiguity including the paradoxes by Machina. © 2013 IEEE.

关键词： Ambiguity decision-making modeling out-of-sample sources of ambiguity tail-separability uncertainty

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A Review of Pseudonym Change Strategies for Location Privacy Preservation Schemes in Vehicular Networks

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ACM Computing Surveys 2025年第8期57卷 1-37页

作者： Benarous, Leila Zeadally, Sherali Boudjit, Saadi Mellouk, Abdelhamid Department of Computer science Amar Telidji University of Laghouat Laghouat Algeria LISSI-Tinc-NET Laboratory University of Paris-Est Creteil Créteil France College of Communication and Information University of Kentucky Lexington United States Department of Electronic Engineering Kyung Hee University Seoul Korea Republic of Litis Lab Intelligent Transportation Systems Group University of Rouen Normandy Mont-Saint-Aignan France Lissi Laboratory Department of Networks and Telecom University Paris-Est Créteil Val de Marne Créteil France

Location privacy protection in vehicular networks has been a primary priority to ensure because of its direct impact on human physical safety. Leakage and violation of road users' location privacy may be perilous beyond simple curiosity as it may scale to cyberstalking and tracking. This may lead to road users being subjected to mental and physical distress, from blackmailing to targeted advertising, and trap planning. The results of tracking may be fatal to road users. Over the past 17 years, researchers have been actively investigating location privacy protection mechanisms for vehicular networks. Numerous research results have been published that examined the use of pseudonym change strategies, which have been considered as the most appropriate solution that maintains the tradeoff between ease of application, good protection level, and the correct functionality of the network. We evaluate, classify, and analyze pseudonym change strategies aimed at location privacy preserving solutions for vehicular networks and discuss their performance. We also review the simulation tools used for evaluating pseudonym change techniques used in location privacy preserving solutions for the vehicular environment. The results of this survey will help researchers in this field to develop more robust, efficient, and cost-effective location privacy protection schemes in the future. © 2025 Copyright held by the owner/author(s). Publication rights licensed to ACM.

关键词： Differential privacy

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Quantifying the Satisfaction of Spatio-Temporal Logic Specifications for Multi-Agent Control

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IEEE Transactions on Automatic Control 2025年

作者： Liu, Wenliang Alsalehi, Suhail Mehdipour, Noushin Bartocci, Ezio Belta, Calin Boston University Department of Mechanical Engineering BostonMA United States Boston University Division of Systems Engineering BostonMA United States Motional BostonMA United States TU Wien Vienna Austria University of Maryland Department of Electrical and Computer Engineering and the Department of Computer Science College ParkMD United States

In this paper, we study control synthesis problems for multi-agent systems (MAS) that must comply with spatio-temporal logic requirements. We define a logic called team Spatio-Temporal Reach and Escape Logic (t-STREL) and a robustness metric for it that is continuous everywhere and differentiable almost everywhere. These properties facilitate the use of gradient-based optimization and learning-based control techniques, offering greater efficiency compared to traditional gradient-free methods. We propose three approaches leveraging these robustness properties to control the MAS. The first combines a gradient-based optimization algorithm with a heuristic one (hybrid optimization). The second uses imitation learning to learn a Recurrent Neural Network (RNN) controller from a dataset generated by off-line optimizations. The third approach employs a model-based policy search algorithm to learn an RNN controller directly without a dataset. We showcase our proposed approaches in a simulated example. We demonstrate that, with hybrid optimization, the MAS can achieve a high success rate of compliance with the t-STREL requirement, while the imitation learning approach can be used for real-time control. The model-based policy search approach can concurrently achieve both objectives within a relatively short training time. © 1963-2012 IEEE.

关键词： Temporal logic

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