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UAV-Mounted Intelligent Reflecting Surface in Maritime Wireless Powered Communication Network

China Communications 2025年第3期22卷 254-269页

作者： Liu Yuan Han Fengxia Zhao Shengjie School of Information Science and Electrical Engineering Shandong Jiaotong UniversityJinan 250357China College of Electronic and Information Engineering Tongji UniversityShanghai 201804China School of Software Engineering Tongji UniversityShanghai 201804China Engineering Research Center of Key Software Technologies for Smart City Perception and Planning Ministry of EducationShanghai 200003China Key Laboratory of Embedded System and Service Computing Tongji University Shanghai 201804China

Intelligent reflecting surface(IRS)assisted with the wireless powered communication network(WPCN)can enhance the desired signal energy and carry out the power-sustaining problem in ocean monitoring *** this paper,we investigate a reliable communication structure where multiple buoys transmit data to a base station(BS)with the help of the unmanned aerial vehicle(UAV)-mounted IRS and harvest energy from the base station *** organically combine WPCN with maritime data collection scenario,a scheduling protocol that employs the time division multiple access(TDMA)is proposed to serve multiple buoys for uplink data ***,we compare the full-duplex(FD)and half-duplex(HD)mechanisms in the maritime data collection system to illustrate different performances under these two *** maximize the fair energy efficiency under the energy harvesting constraints,a joint optimization problem on user association,BS transmit power,UAV’s trajectory and IRS’s phase shift is *** solve the non-convex problem,the original problem is decoupled into several subproblems,and successive convex optimization and block coordinate descent(BCD)methods are employed obtain the near-optimal solutions *** results demonstrate that the UAV-mounted IRS can significantly improve energy efficiency in our considered system.

关键词： full-duplex IRS joint optimization TDMA UAV WPCN

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Understanding the effect of cathodic reaction on corrosion-enhanced erosion in sand-entraining electrolyte

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材料科学技术（英文版） 2025年第6期209卷 103-116页

作者： Qiliang Zhang Long Hao Wanbin Chen Yi Huang Yunze Xu State Key Laboratory of Structural Analysis Optimization and CAE Software for Industrial EquipmentDalian University of TechnologyDalian 116024China School of Naval Architecture and Ocean Engineering Dalian University of TechnologyDalian 116024China State Key Laboratory for Corrosion and Protection Institute of Metal ResearchChinese Academy of SciencesShenyang 110016China

In this study,the pure erosion behaviour of pure iron and its erosion-corrosion behaviour under different anodic polarization currents were investigated in various cathodic reactions(oxygen reduction,hydrogen ion reduction,and water reduction)using a cylindrical stirring *** corrosion-enhanced erosion(C-E)rates were determined for each *** results revealed that pure iron displayed similar pure erosion behaviour across all three cathodic *** the cathodic reactions involve hydrogen ion reduction or water reduction,the erosion-corrosion of pure iron manifested as uniform damage,with the reduction in hardness being the main cause of the C-E in this ***,in the case of oxy-gen reduction reaction as the cathodic reaction,the erosion-corrosion presented as pitting damage,with the reduction in hardness resulting from localized concentration of anodic current and the formation of easily worn protruding flaky iron structures at the edges of the pits as the main mechanism of the ***,linear and exponential relationships were found between the C-E rate and the anodic current density for uniform damage and pitting damage,***,the concept of surface equivalent hardness was proposed,along with the establishment of a mathematical model for surface equivalent hardness based on the relationships between the C-E rate and the anodic current *** the surface equivalent hardness enables the evaluation of the erosion rate on material surfaces considering the coupled effect.

关键词： Corrosion-enhanced erosion Cathodic reaction Pitting damage Uniform damage Hardness

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1+1>2: A Dual-Function Defense Framework for Adversarial Example Mitigation

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IEEE Transactions on Information Forensics and Security 2025年 20卷 4121-4136页

作者： Yang, Rui Sun, Qindong Cao, Han Shen, Chao Cai, Jiaming Rong, Dongzhu Xi’an Jiaotong University School of Cyber Science and Engineering Xi’an710049 China Xi’an University of Technology Shaanxi Key Laboratory of Network Computing and Security Xi’an710049 China Xi’an Jiaotong University School of Software Engineering Xi’an710049 China

Current state-of-the-art plug-and-play countermeasures for mitigating adversarial examples (i.e., purification and detection) exhibit several fatal limitations, impeding their deployment in safety-critical real-world applications. These limitations include susceptibility to adaptive attacks, adverse impact on benign samples, high time consumption for conducting a complete defense cycle, etc. To bridge the gap, developing more advanced plug-and-play countermeasures is urgently needed to safeguard these applications. Specifically, this paper first proposes a novel method named Gaussian-augmented GAN-based Adversarial Purification (GA-GAP). Unlike previous methods, GA-GAP enhances the density of the training data in low-robustness regions by using random Gaussian noise. Moreover, GA-GAP incorporates a pre-trained deep learning classifier into the training architecture and integrates its classification loss into the training loss function. Then, following the development of GA-GAP, this paper innovatively proposes a dual-function defense framework named Adversarial Detection on Purification (ADoP) to mitigate adversarial examples further. In ADoP, purification and detection complement each other, achieving the effect of 1+1 >2 , which can more efficiently avoid adaptive attacks. Extensive experiments on ImageNet demonstrate that ADoP outperforms other countermeasures in multiple aspects. These aspects include superior generalization capability in purifying and detecting various adversarial examples, less adverse impact on benign samples, and practical time consumption for conducting a complete defense cycle. © 2005-2012 IEEE.

关键词： Adversarial machine learning

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Retrieval-Augmented Fine-Tuning for Improving Retrieve-and-Edit Based Assertion Generation

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IEEE Transactions on software engineering 2025年第5期51卷 1591-1614页

作者： Li, Hongyan Sun, Weifeng Yan, Meng Xu, Ling Li, Qiang Zhang, Xiaohong Zhang, Hongyu Key Laboratory of Dependable Service Computing in Cyber Physical Society Chongqing University Ministry of Education Chongqing400044 China School of Big Data and Software Engineering Chongqing University Chongqing400044 China

Unit Testing is crucial in software development and maintenance, aiming to verify that the implemented functionality is consistent with the expected functionality. A unit test is composed of two parts: a test prefix, which drives the unit under test to a particular state, and a test assertion, which determines what the expected behavior is under that state. To reduce the effort of conducting unit tests manually, Yu et al. proposed an integrated approach (integration for short), combining information retrieval with a deep learning-based approach to generate assertions for test prefixes, and obtained promising results. In our previous work, we found that the overall performance of integration is mainly due to its success in retrieving assertions. Moreover, integration is limited to specific types of edit operations and struggles to understand the semantic differences between the retrieved focal-test (focal-test includes a test prefix and a unit under test) and the input focal-test. Based on these insights, we then proposed a retrieve-and-edit approach named EditAS to learn the assertion edit patterns to improve the effectiveness of assertion generation in our prior study. Despite being promising, we find that the effectiveness of EditAS can be further improved. Our analysis shows that: ① The editing ability of EditAS still has ample room for improvement. Its performance degrades as the edit distance between the retrieval assertion and ground truth increases. Specifically, the average accuracy of EditAS is 12.38% when the edit distance is greater than 5. ② EditAS lacks a fine-grained semantic understanding of both the retrieved focal-test and the input focal-test themselves, which leads to many inaccurate token modifications. In particular, an average of 25.57% of the incorrectly generated assertions that need to be modified are not modified, and an average of 6.45% of the assertions that match the ground truth are still modified. Thanks to pre-trained models employing

关键词： software design

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An Uncertainty Quantization-Based Method for Anti-UAV Detection in Infrared Images

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Computers, Materials & Continua 2025年第4期83卷 1439-1458页

作者： Can Wu Wenyi Tang Yunbo Rao Yinjie Chen Hui Ding Shuzhen Zhu Yuanyuan Wang School of Information and Software Engineering University of Electronic Science and Technology of ChinaChengdu610054China State Key Laboratory of Air Traffic Management System Nanjing210000China National Airspace Management Center Beijing100094China

Infrared unmanned aerial vehicle(UAV)target detection presents significant challenges due to the inter-play between small targets and complex *** methods,while effective in controlled environments,often fail in scenarios involving long-range targets,high noise levels,or intricate backgrounds,highlighting the need for more robust *** address these challenges,we propose a novel three-stage UAV segmentation framework that leverages uncertainty quantification to enhance target *** framework incorporates a Bayesian convolutional neural network capable of generating both segmentation maps and probabilistic uncertainty *** utilizing uncer-tainty predictions,our method refines segmentation outcomes,achieving superior detection ***,this marks the first application of uncertainty modeling within the context of infrared UAV target *** evaluations on three publicly available infrared UAV datasets demonstrate the effectiveness of the proposed *** results reveal significant improvements in both detection precision and robustness when compared to state-of-the-art deep learning *** approach also extends the capabilities of encoder-decoder convolutional neural networks by introducing uncertainty modeling,enabling the network to better handle the challenges posed by small targets and complex environmental *** bridging the gap between theoretical uncertainty modeling and practical detection tasks,our work offers a new perspective on enhancing model interpretability and *** codes of this work are available openly at https://***/general-learner/UQ_Anti_UAV(acceessed on 11 November 2024).

关键词： Object segmentation uncertainty quantification bayesian convolutional neural network

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RPPFL: Robust and Privacy-Preserving Federated Learning via Trusted Execution Environments

RPPFL: Robust and Privacy-Preserving Federated Learning via ...

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2025 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2025

作者： Zhang, Xiaolei Chen, Zhaoyu Chen, Guangpu Feng, Xinyu Shen, Qingni Wu, Zhonghai School of Computer Science Peking University China School of Software and Microelectronics Peking University China National Engineering Research Center for Software Engineering Peking University China PKU-OCTA Laboratory for Blockchain and Privacy Computing Peking University China

ISBN: (纸本)9798350368741

Federated Learning (FL) is a distributed framework that enables multi-participant collaborative model training without the need for data sharing. Despite its advantages, FL is vulnerable to poisoning and inference attacks, which compromise model accuracy and data privacy. Trusted execution environments (TEEs) offer a potential solution by providing a secure and isolated execution space to address these security and privacy concerns in FL. However, existing TEE-based FL schemes often suffer from reduced training speed and compromised model accuracy. To mitigate these issues, we propose a robust and privacy-preserving framework for federated learning (RPPFL) that leverages TEE and pseudorandom masking. In our approach, a trusted local model is trained on a secure subset of local data within the client-side TEE, which is then used for anomaly detection to resist poisoning attacks. Additionally, we employ pseudorandom masking to obfuscate local updates and global parameters. Experimental results indicate that RPPFL effectively counters both poisoning and inference attacks, with only a minimal decrease in training speed and no adverse impact on model accuracy. Compared to full-TEE approaches, our method improved local training efficiency by 10×, with less than a 9% loss in model performance under poisoning attacks. © 2025 IEEE.

关键词： Data Obfuscation Federated Learning Privacy Preservation Robustness Trusted Execution Environments

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ACbot:an IIoT platform for industrial robots

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Frontiers of Computer Science 2025年第4期19卷 13-27页

作者： Rui WANG Xudong MOU Tianyu WO Mingyang ZHANG Yuxin LIU Tiejun WANG Pin LIU Jihong YAN Xudong LIU School of Computer Science and Engineering Beihang UniversityBeijing 100191China Zhongguancun Laboratory Beijing 100194China School of Software Beihang UniversityBeijing 100191China School of Mechatronics Engineering Harbin Institute of TechnologyHarbin 150001China Hangzhou Innovation Institute Beihang UniversityHangzhou 310051China School of Information Engineering China University of GeosciencesBeijing 100083China

As the application of Industrial Robots(IRs)scales and related participants increase,the demands for intelligent Operation and Maintenance(O&M)and multi-tenant collaboration *** methods could no longer cover the requirements,while the Industrial Internet of Things(IIoT)has been considered a promising ***,there’s a lack of IIoT platforms dedicated to IR O&M,including IR maintenance,process optimization,and knowledge *** this context,this paper puts forward the multi-tenant-oriented ACbot platform,which attempts to provide the first holistic IIoT-based solution for O&M of *** on an information model designed for the IR field,ACbot has implemented an application architecture with resource and microservice management across the cloud and multiple *** this basis,we develop four vital applications including real-time monitoring,health management,process optimization,and knowledge *** have deployed the ACbot platform in real-world scenarios that contain various participants,types of IRs,and *** date,ACbot has been accessed by 10 organizations and managed 60 industrial robots,demonstrating that the platform fulfills our ***,the application results also showcase its robustness,versatility,and adaptability for developing and hosting intelligent robot applications.

关键词： IIoT platform industrial robots cloud-edge collaboration intelligent applications

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Learning Hierarchical Adaptive Code Clouds for Neural 3D Shape Representation

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Machine Intelligence Research 2025年第2期22卷 304-323页

作者： Yuanxun Lu Xinya Ji Hao Zhu Xun Cao State Key Laboratory for Novel Software Technology Nanjing UniversityNanjing 210023China School of Electronic Science and Engineering Nanjing UniversityNanjing 210023China School of Intelligence Science and Technology Nanjing UniversitySuzhou 215163China

Neural implicit representation(NIR)has attracted significant attention in 3D shape representation for its efficiency,generalizability,and flexibility compared with traditional explicit *** works usually parameterize shapes with neural feature grids/volumes,which prove to be inefficient for the discrete position constraints of the *** recent advances make it possible to optimize continuous positions for the latent codes,they still lack self-adaptability to represent various kinds of shapes *** this paper,we introduce a hierarchical adaptive code cloud(HACC)model to achieve an accurate and compact implicit 3D shape ***,we begin by assigning adaptive influence fields and dynamic positions to latent codes,which are optimizable during training,and propose an adaptive aggregation function to fuse the contributions of candidate latent codes with respect to query *** addition,these basic modules are stacked hierarchically with gradually narrowing influence field thresholds and,therefore,heuristically forced to focus on capturing finer structures at higher *** formulations greatly improve the distribution and effectiveness of local latent codes and reconstruct shapes from coarse to fine with high *** qualitative and quantitative evaluations both on single-shape reconstruction and large-scale dataset representation tasks demonstrate the superiority of our method over state-of-the-art approaches.

关键词： Representation learning shape analysis deep implicit function 3D reconstruction 3D modeling

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SolarDesign:An online photovoltaic device simulation and design platform

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Chinese Physics B 2025年第1期34卷 135-141页

作者： Wei E.I.Sha Xiaoyu Wang Wenchao Chen Yuhao Fu Lijun Zhang Liang Tian Minshen Lin Shudi Jiao Ting Xu Tiange Sun Dongxue Liu College of Information Science and Electronic Engineering Zhejiang UniversityHangzhou 310027China State Key Laboratory of Integrated Optoelectronics Key Laboratory of Automobile Materials of MOEKey Laboratory of Material Simulation Methods&Software of MOESchool of Materials Science and EngineeringJilin UniversityChangchun 130012China ZJU-UIUC Institute International CampusZhejiang UniversityHaining 314400China Key Laboratory of Superhard Materials College of PhysicsJilin UniversityChangchun 130012China College of Electrical Engineering Zhejiang UniversityHangzhou 310027China Science and Technology Research Institute China Three Gorges CorporationBeijing 101199China

Solar Design(https://***/)is an online photovoltaic device simulation and design platform that provides engineering modeling analysis for crystalline silicon solar cells,as well as emerging high-efficiency solar cells such as organic,perovskite,and tandem *** platform offers user-updatable libraries of basic photovoltaic materials and devices,device-level multi-physics simulations involving optical–electrical–thermal interactions,and circuit-level compact model simulations based on detailed balance *** internationally advanced numerical methods,the platform accurately,rapidly,and efficiently solves optical absorption,electrical transport,and compact circuit *** achieves multi-level photovoltaic simulation technology from“materials to devices to circuits”with fully independent intellectual property *** to commercial softwares,the platform achieves high accuracy and improves speed by more than an order of ***,it can simulate unique electrical transport processes in emerging solar cells,such as quantum tunneling,exciton dissociation,and ion migration.

关键词： photovoltaic device simulation silicon solar cells organic and perovskite solar cells multi-physics and circuit simulation

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Optimizing Bevy-ECS Using Predictive JSSP Approach 5

Optimizing Bevy-ECS Using Predictive JSSP Approach

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5th IEEE International Conference on Power, Electronics and Computer Applications, ICPECA 2025

作者： Ma, Benchi Du, Yugen Software Engineering Institution East China Normal University Shanghai China Shanghai Key Laboratory of Trustworthy Computing Shanghai200062 China

ISBN: (纸本)9798331533694

Entity-Component-System (ECS) is a fundamental architecture of game engines. It consists of entities (identities), components (data), and systems (logical units). It schedules the system graph to drive the update loop. The most popular open-sourced game engine on ***, the Bevy engine, is designed in an ECS architecture, and Bevy-ECS is its ECS implementation. While Bevy-ECS is a flexible implementation and easy to expand, performance issues can be found with its original scheduler. The original Bevy-ECS scheduler is based on a greedy algorithm, the system's runtime is unknown to the scheduler, which leads to a poor scheduler in terms of CPU utilization and update loop time. In this paper, we found Bevy-ECS's update loop isomorphic to a traditional NP-Hard job shop scheduling problem (JSSP), then we researched JSSP solutions' approach. With reference to the predictive JSSP solution, we represented a multi-threaded ECS scheduler based on the predictive method in Bevy-ECS. We implement genetic methods for predicting system runtime and use the predicted runtime to schedule the systems. We set up test cases using Bevy-ECS's built-in samples, and then we did performance tests using the profiling tool Tracy. In our performance tests, we use CPU utilization and total runtime to evaluate the performance of the scheduler. The results showed that our optimized scheduler achieved higher CPU utilization and faster update loop time. © 2025 IEEE.

关键词： Job shop scheduling

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