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LMM:A Fixed-Point Linear Mapping Based Approximate Multiplier for IoT

Journal of Computer science & technology 2023年第2期38卷 298-308页

作者：吴莹温晨怡尹勋钊卓成 College of Information Science and Electronic Engineering Zhejiang UniversityHangzhou 310027China Key Laboratory of Collaborative Sensing and Autonomous Unmanned Systems of Zhejiang Province Hangzhou 310027 China

The development of IoT(Internet of Things)calls for circuit designs with energy and area efficiency for edge *** computing which trades unnecessary computation precision for hardware cost savings is a promising direction for error-tolerant ***,as frequently invoked basic modules which consume non-trivial hardware costs,have been introduced approximation to achieve distinct energy and area savings for data-intensive *** this paper,we propose a fixed-point approximate multiplier that employs a linear mapping technique,which enables the configurability of approximation levels and the unbiasedness of computation *** then introduce a dynamic truncation method into the proposed multiplier design to cover a wider and more fine-grained configuration range of approximation for more flexible hardware cost *** addition,a novel normalization module is proposed for the required shifting operations,which balances the occupied area and the critical path delay compared with normal *** introduced errors of our proposed design are analyzed and expressed by formulas which are validated by experimental *** evaluations show that compared with accurate multipliers,our proposed approximate multiplier design provides maximum area and power savings up to 49.70%and 66.39%respectively with acceptable computation errors.

关键词： approximate computing fixed-point linear mapping multiplier Internet of Things(IoT)

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Image Enhancement via Associated Perturbation Removal and Texture Reconstruction Learning

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IEEE/CAA Journal of Automatica Sinica 2024年第11期11卷 2253-2269页

作者： Kui Jiang Ruoxi Wang Yi Xiao Junjun Jiang Xin Xu Tao Lu IEEE the School of Computer Science and Technology Harbin Institute of Technology Zhengzhou Research Institute Harbin Institute of Technology the School of Artificial Intelligence Jianghan University the School of Geodesy and Geomatics Wuhan University the Hubei Province Key Laboratory of Intelligent Information Processing and Real-Time Industrial System Wuhan University of Science and Technology the School of Computer Science and Engineering and also with the Hubei Province Key Laboratory of Intelligent Robot Wuhan Institute of Technology

Degradation under challenging conditions such as rain, haze, and low light not only diminishes content visibility, but also results in additional degradation side effects, including detail occlusion and color distortion. However, current technologies have barely explored the correlation between perturbation removal and background restoration, consequently struggling to generate high-naturalness content in challenging scenarios. In this paper, we rethink the image enhancement task from the perspective of joint optimization: Perturbation removal and texture reconstruction. To this end, we advise an efficient yet effective image enhancement model, termed the perturbation-guided texture reconstruction network(PerTeRNet). It contains two subnetworks designed for the perturbation elimination and texture reconstruction tasks, respectively. To facilitate texture recovery,we develop a novel perturbation-guided texture enhancement module(PerTEM) to connect these two tasks, where informative background features are extracted from the input with the guidance of predicted perturbation priors. To alleviate the learning burden and computational cost, we suggest performing perturbation removal in a sub-space and exploiting super-resolution to infer high-frequency background details. Our PerTeRNet has demonstrated significant superiority over typical methods in both quantitative and qualitative measures, as evidenced by extensive experimental results on popular image enhancement and joint detection tasks. The source code is available at https://***/kuijiang94/PerTeRNet.

关键词： Association learning attention mechanism image enhancement perturbation modeling

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Learning to Branch in Combinatorial Optimization With Graph Pointer Networks

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IEEE/CAA Journal of Automatica Sinica 2024年第1期11卷 157-169页

作者： Rui Wang Zhiming Zhou Kaiwen Li Tao Zhang Ling Wang Xin Xu Xiangke Liao IEEE the Xiangjiang Laboratory and the College of Systems Engineering National University of Defense TechnologyChangsha 410073China the Institute of Automation Chinese Academy of SciencesBeijing 100190China the College of Systems Engineering National University of Defense TechnologyChangsha 410073 the Hunan Key Laboratory of Multi-Energy System Intelligent Interconnection Technology Changsha 410073China the Department of Automation Tsinghua UniversityBeijing 100084China the College of Intelligence Science and Technology National University of Defense TechnologyChangsha 410073China the College of Computer Science and Technology National University of Defense TechnologyChangsha 410073China

Traditional expert-designed branching rules in branch-and-bound(B&B) are static, often failing to adapt to diverse and evolving problem instances. Crafting these rules is labor-intensive, and may not scale well with complex *** the frequent need to solve varied combinatorial optimization problems, leveraging statistical learning to auto-tune B&B algorithms for specific problem classes becomes attractive. This paper proposes a graph pointer network model to learn the branch rules. Graph features, global features and historical features are designated to represent the solver state. The graph neural network processes graph features, while the pointer mechanism assimilates the global and historical features to finally determine the variable on which to branch. The model is trained to imitate the expert strong branching rule by a tailored top-k Kullback-Leibler divergence loss function. Experiments on a series of benchmark problems demonstrate that the proposed approach significantly outperforms the widely used expert-designed branching rules. It also outperforms state-of-the-art machine-learning-based branch-and-bound methods in terms of solving speed and search tree size on all the test instances. In addition, the model can generalize to unseen instances and scale to larger instances.

关键词： Branch-and-bound(B&B) combinatorial optimization deep learning graph neural network imitation learning

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Rock fracture mechanism of buffer blasting with cushion layer at the borehole bottom

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International Journal of Minerals,Metallurgy and Materials 2025年第2期32卷 325-334页

作者： Xinguang Zhu Chenxi Ding Zhe Sui Hong Su Xu Guo School of Civil and Resources Engineering University of Science and Technology BeijingBeijing 100083China Key Laboratory for Mechanics in Fluid Solid Coupling Systems Institute of MechanicsChinese Academy of SciencesBeijing 100190China School of Mechanics and Civil Engineering China University of Mining and Technology(Beijing)Beijing 100083China School of Chemical and Blasting Engineering Anhui University of Science and TechnologyHuainan 232001China

This study primarily investigates the rock fracture mechanism of bottom cushion layer blasting and explores the effects of the bottom cushion layer on rock *** involves analyses of the evolution patterns of blasting stress,characteristics of crack distribution,and rock fracture features in the ***,blasting model experiments were carried out using the dynamic caustics principle to investigate the influence of bottom cushion layers and initiation methods on the integrity of the bottom rock *** experimental results indicate that the combined use of bottom cushion layers and inverse initiation effectively protects the integrity of the bottom rock ***,the process of stress wave propagation and dynamic crack propagation in rocks was simulated using the continuum-discontinuum element method(CDEM)and the Landau explosion source model,with varying thicknesses of bottom cushion *** numerical simulation results indicate that with increasing cushion thickness,the absorption of energy generated by the explosion becomes more pronounced,resulting in fewer cracks in the bottom rock *** illustrates the positive role of the cushion layer in protecting the integrity of the bottom rock mass.

关键词： bottom cushion layer blasting crack propagation continuum-discontinuum element method dynamic stress intensity factor

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Direct Synthesis of Layer-Tunable and Transfer-Free Graphene on Device-Compatible Substrates Using Ion Implantation Toward Versatile Applications

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Energy & Environmental Materials 2024年第5期7卷 408-418页

作者： Bingkun Wang Jun Jiang Kevin Baldwin Huijuan Wu Li Zheng Mingming Gong Xuehai Ju Gang Wang Caichao Ye Yongqiang Wang Department of Microelectronic Science and Engineering School of Physical Science and TechnologyNingbo UniversityNingbo 315211China Key Laboratory of Soft Chemistry and Functional Materials of MOE School of Chemistry and Chemical Engineering Nanjing University of Science and TechnologyNanjing 210094China Center for Integrated Nanotechnologies Los Alamos National LaboratoryLos Alamos 87545New MexicoUSA National Key Laboratory of Materials for Integrated Circuits Shanghai Institute of Microsystem and Information TechnologyChinese Academy of SciencesShanghai 200050China Academy for Advanced Interdisciplinary Studies&Department of Materials Science and Engineering Southern University of Science and TechnologyShenzhen 518055China Guangdong Provincial Key Laboratory of Computational Science and Material Design Southern University of Science and TechnologyShenzhen 518055China Materials Science and Technology Division Los Alamos National LaboratoryLos Alamos 87545New MexicoUSA

Direct synthesis of layer-tunable and transfer-free graphene on technologically important substrates is highly valued for various electronics and device *** of the art in the field is currently a two-step process:a high-quality graphene layer synthesis on metal substrate through chemical vapor deposition(CVD)followed by delicate layer transfer onto device-relevant ***,we report a novel synthesis approach combining ion implantation for a precise graphene layer control and dual-metal smart Janus substrate for a diffusion-limiting graphene formation to directly synthesize large area,high quality,and layer-tunable graphene films on arbitrary substrates without the post-synthesis layer transfer ***(C)ion implantation was performed on Cu-Ni film deposited on a variety of device-relevant substrates.A well-controlled number of layers of graphene,primarily monolayer and bilayer,is precisely controlled by the equivalent fluence of the implanted C-atoms(1 monolayer~4×10^(15)C-atoms/cm^(2)).Upon thermal annealing to promote Cu-Ni alloying,the pre-implanted C-atoms in the Ni layer are pushed toward the Ni/substrate interface by the top Cu layer due to the poor C-solubility in *** a result,the expelled C-atoms precipitate into a graphene structure at the interface facilitated by the Cu-like alloy *** removing the alloyed Cu-like surface layer,the layer-tunable graphene on the desired substrate is directly *** layer-selectivity,high quality,and uniformity of the graphene films are not only confirmed with detailed characterizations using a suite of surface analysis techniques but more importantly are successfully demonstrated by the excellent properties and performance of several devices directly fabricated from these graphene *** dynamics(MD)simulations using the reactive force field(ReaxFF)were performed to elucidate the graphene formation mechanisms in this novel synthesis *** the wide use of ion

关键词： device applications dual-metal smart Janus substrate growth mechanism Ion implantation layer-tunable and transfer-free graphene

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Interfacial engineering for efficient and stable two-terminal perovskite-based tandem solar cells

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Rare Metals 2024年第11期43卷 5573-5624页

作者： Ying Li Di-Sheng Yao Fei Long Guo-Zhen Zhang Feng Yu Guangxi Key Laboratory of Optical and Electronic Material and Devices School of Materials Science and EngineeringGuilin University of TechnologyGuilin 541004China Guangxi Key Laboratory of Optical and Electronic Material and Devices School of Materials Science and EngineeringCollaborative Innovation Center for Exploration of Nonferrous Metal Deposits and Efficient Utilization of ResourcesGuilin University of TechnologyGuilin 541004China School of Chemistry and Materials Science Nanjing University of Information Science and TechnologyNanjing 210044China

Two-terminal(2T)tandem solar cells(TSCs)are optically and electrically connected by two subcells with complementary bandgaps,which are designed to overcome the Shockley-Queisser(S-Q)limit of singlejunction solar ***-inorganic hybrid perovskites are ideal light-absorbing materials for 2T TSCs due to their tunable bandgaps,low-temperature solution-based processing,and excellent light absorption ***,2T perovskite-based TSCs(PTSCs)have aroused widespread interest among the photovoltaic *** present,the key to obtaining efficient and stable 2T PTSCs is establishing efficient interfaces and layers with good photoelectric properties and high compatibility of *** particular,interfacial engineering based on effective recombination layers(RCLs)and buffers has a prominent effect on achieving enhanced power conversion efficiency(PCE)of 2T PTSCs with improved operational *** this article,the current frontier issues of 2T PTSCs including different device structures and properties are reviewed in detail to analyze their merits,demerits and solutions to overcome ***,the component engineering,interface engineering and theoretical PCE analysis for designing 2T PTSCs proposed by material simulations are ***,the scalability of interfacial passivation from single-junction perovskite solar cells to 2T PTSCs is evaluated,and the function mechanisms of RCLs and buffers are also summarized and analyzed ***,the challenges faced by 2T PTSCs are pointed out,and their developme nt directions are *** article aims to provide viable guidance for realizing practical manufacturing technologies for the commercialization of 2T PTSCs.

关键词： Two-terminal tandem solar cells Organic-inorganic perovskites Passivation interfaces Recombination layers and buffers Efficiency and stability

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Leveraging Convolutional Neural Network and Explainable AI for Enhanced Pneumonia Detection 1

Leveraging Convolutional Neural Network and Explainable AI f...

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1st International Conference on Sustainable Energy Technologies and Computational Intelligence, SETCOM 2025

作者： Murugan, Ramalingam Patel, Harshita Vellore Institute of Technology School of Computer Science Engineering and Information Systems Tamil Nadu Vellore India

ISBN: (纸本)9798331520540

Advances in machine learning and computer vision have significantly improved the diagnostic capabilities of medical imaging. Convolutional Neural Networks (CNNs) have emerged as a crucial tool for image classification, particularly in detecting pneumonia from chest X-ray images. Despite their high accuracy, CNNs face challenges in clinical adoption due to their lack of interpretability. Medical practitioners require a clear understanding of the decision-making process to trust AI-generated diagnoses. To address the aforementioned challenge, we propose pneumonia classification model incorporating CNN with a combination of the model and Grad-CAM, for enhanced interpretability. Grad-CAM visually outlines critical regions, influencing the prediction, so the clinician can easily confirm AI-based diagnoses with a more confident and credible approach. It is exclusively for pediatric pneumonia, an accurate and explainable machine for early interventions that can also work in resource-scarce regions. Our research uses a set of 5,863 pediatric chest X-ray images, divided into Pneumonia and Normal classes. The dataset was acquired from Guangzhou Women and Children's Medical Center and divided into three subsets: training, validation, and test. By improving the accuracy and transparency of the diagnosis, this model can help bridge the gap between AI and the real world. This can help facilitate quicker and more reliable pneumonia diagnostics. © 2025 IEEE.

关键词： Convolutional neural networks

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Verifiable delay functions and delay encryptions from hyperelliptic curves

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Cybersecurity 2024年第4期7卷 110-121页

作者： Chao Chen Fangguo Zhang School of Computer Science and Engineering Sun Yat-sen UniversityGuangzhou 510006China Guangdong Province Key Laboratory of Information Security Technology Guangzhou 510006China

Verifiable delay functions(VDFs)and delay encryptions(DEs)are two important primitives in decentralized systems,while existing constructions are mainly based on time-lock puzzles.A disparate framework has been established by applying isogenies and pairings on elliptic *** this line,we first employ Richelot isogenies and non-degenerate pairings from hyperelliptic curves for a new verifiable delay function,such that no auxiliary proof and interaction are needed for the ***,we demonstrate that our scheme satisfies all security requirements,in particular,our VDF can resist several attacks,including the latest attacks for ***,resorting to the same techniques,a secure delay encryption from hyperelliptic curves is constructed by modifying Boneh and Frankiln's IBE scheme,which shares the identical setup with our VDF *** far as we know,these schemes are the first cryptographic applications from high-genus isogenies apart from basic protocols,i.e.,hash functions and key exchange protocols.

关键词： Verifiable delay functions Delay encryptions Hyperelliptic curves Richelot isogenies Pairings

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Optimizing Coverage in Wireless Sensor Networks Using the Tumbleweed Algorithm

Journal of Network Intelligence

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Journal of Network Intelligence 2025年第1期10卷 250-261页

作者： Zhang, Mengfei Chu, Shu-Chuan Liu, Nengxian Huang, Kuan-Chun Pan, Jeng-Shyang College of Computer Science and Engineering Shandong University of Science and Technology Qingdao266590 China College of Computer and Data Science Fuzhou University Fuzhou350108 China Department of Industrial and Systems Engineering Chung Yuan Christian University Taoyuan320314 Taiwan School of Artificial Intelligence Nanjing University of Information Science and Technology Nanjing210044 China Department of Information Management Chaoyang University of Technology Taichung41349 Taiwan

Wireless sensor networks (WSNs) have found extensive applications across various fields, significantly enhancing the convenience in our daily lives. Hence, an in-creasing number of researchers are directing their attention toward the performance of sensor nodes, with a particular emphasis on addressing the coverage challenges in WSNs. Node coverage plays a crucial role in determining the detection performance of WSNs, making it imperative to attain maximum coverage with a given number of sensor nodes. This paper applies the Tumbleweed Algorithm (TA) to the coverage problem in WSNs and validates its effectiveness through simulation experiments. The results demonstrate its unique advantages in global search and avoiding local optima, providing a new solution for the WSN coverage problem and offering valuable references for future research and practical applications. The TA algorithm simulates the lifecycle of tumbleweed from seedling to mature plant and includes the concept of growth cycles. This paper compares the TA algorithm with PSO, GWO, DE, BOA, SCA, and AOA, setting different numbers of wireless sensor nodes and varying sensing radii for the experiments. The experimental results show that the TA algorithm significantly improves coverage rates under various configurations and consistently outperforms other commonly used algorithms. © 2025, Taiwan Ubiquitous information CO LTD. All rights reserved.

关键词： Sensor nodes

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Learning Scalable Task Assignment with Imperative-Priori Conflict Resolution in Multi-UAV Adversarial Swarm Defense Problem

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Journal of systems science & Complexity 2024年第1期37卷 369-388页

作者： ZHAO Zhixin CHEN Jie XIN Bin LI Li JIAO Keming ZHENG Yifan School of Electronics and Information Engineering Tongji UniversityShanghai 201804China Shanghai Institute of Intelligent Science and Technology Tongji UniversityShanghai 201804China School of Automation Beijing Institute of TechnologyBeijing 100081China National Key Laboratory of Autonomous Intelligent Unmanned Systems Beijing 100081China Shanghai Institute of Intelligent Science and Technology Tongji UniversityShanghai 201804China.

The multi-UAV adversary swarm defense(MUASD)problem is to defend a static base against an adversary UAV swarm by a defensive UAV *** the problem into task assignment and low-level interception strategies is a widely used ***-based approaches for task assignment are a promising *** studies on learning-based methods generally assume decentralized decision-making architecture,which is not beneficial for conflict *** contrast,centralized decision-making architecture is beneficial for conflict resolution while it is often detrimental to *** achieve scalability and conflict resolution simultaneously,inspired by a self-attention-based task assignment method for sensor target coverage problem,a scalable centralized assignment method based on self-attention mechanism together with a defender-attacker pairwise observation preprocessing(DAP-SelfAtt)is ***,an imperative-priori conflict resolution(IPCR)mechanism is proposed to achieve conflict-free ***,the IPCR mechanism is parallelized to enable efficient *** validate the algorithm,a variant of proximal policy optimization algorithm(PPO)is employed for training in scenarios of various *** experimental results show that the proposed algorithm not only achieves conflict-free task assignment but also maintains scalability,and significantly improve the success rate of defense.

关键词： Conflict resolution reinforcement learning scalability task assignment.

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