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A Spinal Bistable Oscillator for Autonomous Actuation and Tunable Frequency on Crawling Robot

Journal of Bionic Engineering 2025年第1期22卷 96-106页

作者： Wenwei Wang Jitao Peng Lei Liu Yehui Shen Jinfang Shi Hongbin Zang School of Manufacturing Science and Engineering Key Laboratory of Testing Technology for Manufacturing ProcessMinistry of EducationSouthwest University of Science and TechnologyMianyang621010China Tianfu Institute of Research and Innovation Southwest University of Science and TechnologyChengdu610299China

Pneumatic soft robots have undergone significant advancements in recent ***,the majority of robot motion control still relies on electronic computers to regulate the valves and air *** the potential reduction in controller dependency by utilizing soft pneumatic oscillators,challenges such as low flow rates,complex manufacturing processes,and lack of adjustment ability *** by the geckos'spine,we propose a Spinal Bistable Oscillator(SBO)that operates without discrete components or electronic control hardware,achieving stable oscillatory motion under constant air *** oscillator employs a soft control valve and lagging pin,which can switch the direction of airflow conduction based on the oscillation angle of the *** types of actuators can be controlled using a series *** this study,the effective working range of the soft control valve,influence of the spring pretension force on the torque during oscillation,and effect of different throttle tube lengths on the oscillation frequency were ***,a self-crawling robot was *** results demonstrate that the robot can crawl at speeds ranging from 3.6 to 5.7 mm/s(or 3.1 to 4.9 body length/min)and overcome its own gravity(with a weight of 165 g)to climb *** SBO proposed in this study exhibits characteristics of lightweight,low cost,high oscillation torque,and tunable *** holds promise for application in joint control of future pneumatic soft robots.

关键词： Spinal bistable oscillator Self-crawling robot Physical intelligence Pneumatic soft robot

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Mode Competition of Low Voltage Backward Wave Oscillator near 500 GHz with Parallel Multi-Beam

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Chinese Journal of Electronics 2024年第2期33卷 488-495页

作者： Xiaoyan ZHAO Jincheng HU Haoran ZHANG Sidou GUO Yuming FENG Lin TANG Kaichun ZHANG Diwei LIU THz Center School of Electronic Science and Engineering University of Electronic Science and Technology of China School of Computer Science Southwest Petroleum University

A backward wave oscillator with parallel multiple beams and multi-pin slow-wave structure(SWS)operating at the frequency above 500 GHz is studied. Both the cold-cavity dispersion characteristics and CST Particle Studio simulation results reveal that there are obvious mode competition problems in this kind of terahertz *** that the structure of the multi-pin SWS is similar to that of two-dimensional photonic crystals, we introduce the defects of photonic crystal with the property of filtering into the SWS to suppress high-order ***, a detailed study of the effect of suppressing higher-order modes is carried out in the process of changing location and arrangement pattern of the point defects. The stable, single-mode operation of the terahertz source is realized. The simulation results show that the ratio of the output peak power of the higher-order modes to that of the fundamental mode is less than 1.9%. Also, the source can provide the output peak power of 44.8 m W at the frequency of 502.2 GHz in the case of low beam voltage of 4.7 kV.

关键词： Mode competition Backward wave oscillator Multi-pin slow-wave structure Parallel multiple beams Defects

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Towards High-Performance Graph Processing: From a Hardware/Software Co-Design Perspective

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Journal of computer science & technology 2024年第2期39卷 245-266页

作者：廖小飞赵文举金海姚鹏程黄禹王庆刚赵进郑龙张宇邵志远 National Engineering Research Center for Big Data Technology and System School of Computer Science and Technology Huazhong University of Science and TechnologyWuhan 430074China Services Computing Technology and System Laboratory School of Computer Science and Technology Huazhong University of Science and TechnologyWuhan 430074China Cluster and Grid Computing Laboratory School of Computer Science and TechnologyHuazhong University of Science and TechnologyWuhan 430074China Zhejiang Lab Hangzhou 311121China

Graph processing has been widely used in many scenarios,from scientific computing to artificial *** processing exhibits irregular computational parallelism and random memory accesses,unlike traditional ***,running graph processing workloads on conventional architectures(e.g.,CPUs and GPUs)often shows a significantly low compute-memory ratio with few performance benefits,which can be,in many cases,even slower than a specialized single-thread graph *** domain-specific hardware designs are essential for graph processing,it is still challenging to transform the hardware capability to performance boost without coupled software *** article presents a graph processing ecosystem from hardware to *** start by introducing a series of hardware accelerators as the foundation of this ***,the codesigned parallel graph systems and their distributed techniques are presented to support graph ***,we introduce our efforts on novel graph applications and hardware *** results show that various graph applications can be efficiently accelerated in this graph processing ecosystem.

关键词： graph processing hardware accelerator software system high performance ecosystem

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Optimizing B^(+)-tree for hybrid memory with in-node hotspot cache and eADR awareness

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Frontiers of computer science 2024年第5期18卷 133-145页

作者： Peiquan JIN Zhaole CHU Gaocong LIU Yongping LUO Shouhong WAN School of Computer Science and Technology University of Science and Technology of ChinaHefei 230027China

he advance in Non-Volatile Memory(NVM)has changed the traditional *** to DRAM,NVM has the advantages of nonvolatility and large ***,as the read/write speed of NVM is still lower than that of DRAM,building DRAM/NVM-based hybrid memory systems is a feasible way of adding NVM into the current computer *** paper aims to optimize the well-known B^(+)-tree for hybrid *** novelty of this study is ***,we observed that the space utilization of internal nodes in B^(+)-tree is generally below 70%.Inspired by this observation,we propose to maintain hot keys in the free space within internal nodes,yielding a new index named HATree(Hotness-Aware Tree).The new idea of HATree is to use the unused space of the parent of leaf nodes(PLNs)as the hotspot data ***,no extra space is needed,and the in-node hotspot cache can efficiently improve query ***,to further improve the update performance of HATree,we propose to utilize the eADR technology supported by the third-generation Intel Xeon Scalable Processors to enhance HATree with instant log persistence,which results in the new HATree-Log *** conduct extensive experiments on real hybrid memory architecture involving DRAM and Intel Optane Persistent Memory to evaluate the performance of HATree and *** state-of-the-art indices for hybrid memory,namely NBTree,LBTree,and FPTree,are included in the experiments,and the results suggest the efficiency of HATree and HATree-Log.

关键词： hybrid memory B^(+)-tree hotspot in-node cache eADR

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Task-specific Part Discovery for Fine-grained Few-shot Classification

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Machine Intelligence Research 2024年第5期21卷 954-965页

作者： Yongxian Wei Xiu-Shen Wei School of Computer Science and Technology Nanjing University of Science and TechnologyNanjing210094China

Localizing discriminative object parts(e.g.,bird head)is crucial for fine-grained classification tasks,especially for the more challenging fine-grained few-shot *** work always relies on the learned object parts in a unified manner,where they attend the same object parts(even with common attention weights)for different few-shot episodic *** this paper,we propose that it should adaptively capture the task-specific object parts that require attention for each few-shot task,since the parts that can distinguish different tasks are naturally *** for a few-shot task,after obtaining part-level deep features,we learn a task-specific part-based dictionary for both aligning and reweighting part features in an ***,part-level categorical prototypes are generated based on the part features of support data,which are later employed by calculating distances to classify query data for *** retain the discriminative ability of the part-level representations(i.e.,part features and part prototypes),we design an optimal transport solution that also utilizes query data in a transductive way to optimize the aforementioned distance calculation for the final *** experiments on five fine-grained benchmarks show the superiority of our method,especially for the 1-shot setting,gaining 0.12%,8.56%and 5.87%improvements over state-of-the-art methods on CUB,Stanford Dogs,and Stanford Cars,respectively.

关键词： Fine-grained image recognition few-shot learning transductive learning visual dictionary part feature discovery

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Privacy-preserving filtering, control and optimization for industrial cyber-physical systems

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science China(Information sciences) 2025年第4期68卷 267-283页

作者： Derui DING Qing-Long HAN Xiaohua GE Xian-Ming ZHANG Jun WANG Department of Control Science and Engineering University of Shanghai for Science and Technology School of Engineering Swinburne University of Technology Department of Computer Science City University of Hong Kong

Industrial cyber-physical systems closely integrate physical processes with cyberspace, enabling real-time exchange of various information about system dynamics, sensor outputs, and control decisions. The connection between cyberspace and physical processes results in the exposure of industrial production information to unprecedented security risks. It is imperative to develop suitable strategies to ensure cyber security while meeting basic performance *** the perspective of control engineering, this review presents the most up-to-date results for privacy-preserving filtering,control, and optimization in industrial cyber-physical systems. Fashionable privacy-preserving strategies and mainstream evaluation metrics are first presented in a systematic manner for performance evaluation and engineering *** discussion discloses the impact of typical filtering algorithms on filtering performance, specifically for privacy-preserving Kalman filtering. Then, the latest development of industrial control is systematically investigated from consensus control of multi-agent systems, platoon control of autonomous vehicles as well as hierarchical control of power systems. The focus thereafter is on the latest privacy-preserving optimization algorithms in the framework of consensus and their applications in distributed economic dispatch issues and energy management of networked power systems. In the end, several topics for potential future research are highlighted.

关键词： industrial cyber-physical systems privacy preservation distributed control distributed optimization power systems

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Epitaxial growth of ultrathin gallium films on Cd(0001)

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Chinese Physics B 2024年第1期33卷 722-727页

作者：李佐石明霞姚钢陶敏龙王俊忠 School of Physical Science and Technology Southwest UniversityChongqing 400715China School of Science Guizhou University of Engineering ScienceBijie 551700China

Growth and electronic properties of ultrathin Ga films on Cd(0001) are investigated by low-temperature scanning tunneling microscopy(STM) and density functional theory(DFT) calculations. It is found that Ga films exhibit the epitaxial growth with the pseudomorphic 1×1 lattice. The Ga islands deposited at 100 K show a ramified shape due to the suppressed edge diffusion and corner crossing. Furthermore, the majority of Ga islands reveal flat tops and a preferred height of three atomic layers, indicating the electronic growth at low temperature. Annealing to room temperature leads to not only the growth mode transition from electronic growth to conventional Stranski–Krastanov growth, but also the shape transition from ramified islands to smooth compact islands. Scanning tunneling spectroscopy(STS) measurements reveal that the Ga monolayer exhibits metallic behavior. DFT calculations indicate that all the interfacial Ga atoms occupy the energetically favorable hcp-hollow sites of the substrate. The charge density difference analysis demonstrates that the charge transfer from the Cd substrate to the Ga atoms is negligible, and there is weak interaction between Ga atoms and the Cd substrate. These results shall shed important light on fabrication of ultrathin Ga films on metal substrates with novel physical properties.

关键词： gallium films electronic growth STM/STS density functional theory

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FEA-Sketch: flow entries assisted sketch for heavy flow detection in software-defined networking

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science China(Information sciences) 2025年第3期68卷 80-94页

作者： Xiaocan WU He HUANG Yang DU Yu-E SUN Yifan HAN School of Computer Science and Technology Soochow University School of Rail Transportation Soochow University

Software-defined networking decouples the control plane from the data plane to enable centralized flow-level network management, while requiring periodically collecting traffic statistics from the data plane to enforce optimal management. As one of the most important traffic measurement tasks, heavy flow detection has received wide attention for its providing fundamental statistics in various practical applications. Existing studies have proposed sketch-based detection solutions to address the mismatch problem between massive traffic and limited high-speed memory resources for measurement in the data plane. However,they overlook the potential of integrating the flow table, where each entry simultaneously enforces forwarding rules for specific flows and records flow statistics into the sketch design, leading to redundant measurement between the flow table and sketch and being unable to utilize their statistics to jointly enhance estimation accuracy. We propose flow entries assisted sketch(FEA-Sketch) in this work, which employs a differentiated flow recording strategy to record flow statistics jointly using the flow table and sketch for memory-efficient and computationally efficient heavy flow detection. We also propose an optimization-based estimation algorithm to accurately recover per-flow sizes for the flows that only have aggregated statistics due to the sharing of entries in the table(or counters in the sketch). We extend the FEA-Sketch to the distributed measurement setting with a hop-based collaborative measurement strategy, which reduces the measurement workload on switches across the network by avoiding redundant measurements. The experimental results on real Internet traces show that the accuracy of heavy flow detection is improved up to 1.95 times, and the bias of flow size estimation is improved up to 2.99 times, demonstrating that integrating flow entries can significantly improve the performance of heavy flow detection.

关键词： software-defined networking traffic measurement heavy flow flow table sketch

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Fault-tolerant Quantized Control for Switched Neural Networks with Actuator Faults and Dynamic Output Quantization

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IAENG International Journal of Applied Mathematics 2025年第1期55卷 7-15页

作者： Su, Yue Wang, Xinrui Tai, Weipeng Zhou, Jianping School of Computer Science and Technology Anhui University of Technology Ma'anshan243032 China School of Computer Science and Technology Chengdu University of Technology Chengdu610051 China School of Computer Science and Technology Anhui University of Technology Ma'anshan243032 China School of Computer Science and Technology Anhui University of Technology Ma'anshan243032 China

This paper examines fault-tolerant quantized control for neural networks under persistent dwell-time switching, considering the presence of actuator faults and dynamic output quantization. The dynamic scaling factor (DSF) of the quantizer is designed as a piecewise function concerning the output to avoid the possibility of division by zero. To reduce conservatism, the controller is designed to combine the system model with a time scheduler constructed with a minimum time span. A sufficient condition for the asymptotic stability and L2-gain of the closed-loop system is derived using a piecewise Lyapunov functional and decoupling approach. When the condition is satisfied, the needed feedback gains and the parameter range associated with the DSF can be determined by exact mathematical expressions. For comparison, feedback gains that depend only on the system mode are also studied, and the corresponding design method is presented. The numerical simulation results demonstrate the effectiveness of the proposed control scheme. © (2025), (International Association of Engineers). All rights reserved.

关键词： Lyapunov functions

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A Federated Learning Incentive Mechanism for Dynamic Client Participation:Unbiased Deep Learning Models

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computers, Materials & Continua 2025年第4期83卷 619-634页

作者： Jianfeng Lu Tao Huang Yuanai Xie Shuqin Cao Bing Li School of Computer Science and Technology Wuhan University of Science and TechnologyWuhan430065China College of Computer Science South-Central Minzu UniversityWuhan430074China School of Computer Science and Technology Zhejiang Normal UniversityJinhua321004China

The proliferation of deep learning(DL)has amplified the demand for processing large and complex datasets for tasks such as modeling,classification,and ***,traditional DL methods compromise client privacy by collecting sensitive data,underscoring the necessity for privacy-preserving solutions like Federated Learning(FL).FL effectively addresses escalating privacy concerns by facilitating collaborative model training without necessitating the sharing of raw *** that FL clients autonomously manage training data,encouraging client engagement is pivotal for successful model *** overcome challenges like unreliable communication and budget constraints,we present ENTIRE,a contract-based dynamic participation incentive mechanism for *** ensures impartial model training by tailoring participation levels and payments to accommodate diverse client *** approach involves several key ***,we examine how random client participation impacts FL convergence in non-convex scenarios,establishing the correlation between client participation levels and model ***,we reframe model performance optimization as an optimal contract design challenge to guide the distribution of rewards among clients with varying participation *** balancing budget considerations with model effectiveness,we craft optimal contracts for different budgetary constraints,prompting clients to disclose their participation preferences and select suitable contracts for contributing to model ***,we conduct a comprehensive experimental evaluation of ENTIRE using three real *** results demonstrate a significant 12.9%enhancement in model performance,validating its adherence to anticipated economic properties.

关键词： Federated learning deep learning non-IID data dynamic client participation non-convex optimization contract

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