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A Function-Aware Mimic Defense Theory and Its Practice

China Communications 2024年第8期21卷 192-210页

作者： He Jiajun Yuan Yali Liang Sichu Fu Jiale Zhu Hongyu Cheng Guang School of Mathematics Southeast UniversityNanjing 211189China School of Cyber Science and Engineering Southeast UniversityNanjing 211189China School of Artificial Intelligence Southeast UniversityNanjing 211189China State Key Laboratory for Novel Software Technology Nanjing UniversityNanjing 210093China

In recent years,network attacks have been characterized by diversification and scale,which indicates a requirement for defense strategies to sacrifice generalizability for higher *** the latest theoretical achievement in active defense,mimic defense demonstrates high robustness against complex *** study proposes a Function-aware,Bayesian adjudication,and Adaptive updating Mimic Defense(FBAMD)theory for addressing the current problems of existing work including limited ability to resist unknown threats,imprecise heterogeneous metrics,and over-reliance on relatively-correct *** incorporates three critical ***,the common features of executors’vulnerabilities are obtained from the perspective of the functional implementation(i.e,input-output relationships extraction).Secondly,a new adjudication mechanism considering Bayes’theory is proposed by leveraging the advantages of both current results and historical ***,posterior confidence can be updated regularly with prior adjudication information,which provides mimic system *** experimental analysis shows that FBAMD exhibits the best performance in the face of different types of attacks compared to the state-of-the-art over real-world *** study presents a promising step toward the theo-retical innovation of mimic defense.

关键词： Bayesian theory confidence functional implementation mimic defense

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ProCQA: A Large-scale Community-based Programming Question Answering Dataset for Code Search 30

ProCQA: A Large-scale Community-based Programming Question A...

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Joint 30th International Conference on Computational Linguistics and 14th International Conference on Language Resources and Evaluation, LREC-COLING 2024

作者： Li, Zehan Zhang, Jianfei Yin, Chuantao Ouyang, Yuanxin Rong, Wenge State Key Laboratory of Complex & Critical Software Environment Beihang University China Sino-French Engineer School Beihang University China School of Computer Science and Engineering Beihang University China

ISBN: (纸本)9782493814104

Retrieval-based code question answering seeks to match user queries in natural language to relevant code snippets. Previous approaches typically rely on pretraining models using crafted bi-modal and uni-modal datasets to align text and code representations. In this paper, we introduce ProCQA, a large-scale programming question answering dataset extracted from the StackOverflow community, offering naturally structured mixed-modal QA pairs. To validate its effectiveness, we propose a modality-agnostic contrastive pre-training approach to improve the alignment of text and code representations of current code language models. Compared to previous models that primarily employ bimodal and unimodal pairs extracted from CodeSearchNet for pre-training, our model exhibits significant performance improvements across a wide range of code retrieval benchmarks. © 2024 ELRA Language Resource Association: CC BY-NC 4.0.

关键词： Benchmarking

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RAT: A Refactoring-Aware Tool for Tracking Code History 24

RAT: A Refactoring-Aware Tool for Tracking Code History

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46th International Conference on software engineering: Companion, ICSE-Companion 2024

作者： Niu, Feifei Shao, Junqian Xu, Chaofan Mayr-Dorn, Christoph Assunção, Wesley K. G. Huang, Liguo Li, Chuanyi Ge, Jidong Luo, Bin Egyed, Alexander State Key Laboratory for Novel Software Technology Nanjing University Nanjing China Institute for Software Systems Engineering Johannes Kepler University Linz Austria Department of Computer Science North Carolina State University North Carolina United States Department of Computer Science and Engineering Southern Methodist University DallasTX United States

ISBN: (纸本)9798400705021

History of code elements is essential for software maintenance tasks. However, code refactoring is one of the main causes that makes obtaining a consistent view on code evolution difficult as renaming or moving source code elements break such history. To this end, this paper presents RAT, a refactoring-aware tool for keeping track of code elements evolution across time, not just in terms of revisions but also in terms of refactoring. This is the first tool that enables fine-grained code element traceability of the whole repository. Empirical evaluation of leveraging our tool in three bug localization techniques relying on code history shows significant improvement in localization accuracy. Based on our findings, we believe that many of the state-of-the-art approaches using past source code data would benefit from our tool. Demo Tool: https://***/feifeiniu-se/RAT-Demo. Demo Video: https://***/VI-xwUaIPp4. © 2024 IEEE Computer Society. All rights reserved.

关键词： Rats

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Energy-AOI-Aware UAV-Assisted Data Collection: A Multi-Agent Deep Reinforcement Learning-Based Trajectory Optimization 23

Energy-AOI-Aware UAV-Assisted Data Collection: A Multi-Agent...

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23rd IEEE International Conference on Communication Technology, ICCT 2023

作者： Wan, Liangtian Zhang, Kun Sun, Lu Xu, Gang Wang, Xianpeng School of Software Dalian University of Technology Key Laboratory for Ubiquitous Network and Service Software of Liaoning Province Dalian China Institute of Information Science Technology Dalian Maritime University Department of Communication Engineering Dalian China School of Information Science and Engineering Southeast University State Key Laboratory of Millimeter Waves Nanjing China School of Information and Communication Engineering Hainan University State Key Laboratory of Marine Resource Utilization in South China Sea Haikou China

ISBN: (纸本)9798350325959

With the development of Internet of Things (IoT) technology, sensor networks are widely used for data collection in various IoT scenarios. Traditional sensors use multi-hop communication to transmit data back to the data center, which can lead to excessive energy consumption in some nodes and cause the collapse of sensor networks. Solving the data transmission problem in sensor networks has become a critical issue. In recent years, unmanned aerial vehicles (UAVs) capable of hovering have been increasingly applied in military and civilian fields, such as smart logistics, edge computing, and wireless power transfer (WPT). UAVs, with their strong controllability and high mobility, can effectively perform the task of data transmission in sensor networks. In the task of UAV -assisted sensor data collection, UAVs can establish communication connections with ground sensors through small communication devices and act as mobile aggregation nodes to collect data from the ground wireless sensor network. To achieve energy balance among sensor network nodes as much as possible while ensuring service quality based on information age, we propose a combinatorial optimization problem. Ultimately, we solve the combinatorial optimization problem by optimizing the trajectory of UAV flight. As the problem is a mixed-integer non-convex optimization which is difficult to solve, we propose a UAV swarm-based sensor trajectory planning algorithm using multi-agent reinforcement learning. Simulation results show that the proposed algorithm has a better effect than baseline approaches on optimization objective. © 2023 IEEE.

关键词： Age of Information data collection deep rein-forcement learning unmanned aerial vehicle (UAV) trajectory planning

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25th International Conference on Web Information Systems engineering, WISE 2024

作者： Tu, Longchuan Meng, Shunmei Liu, Xiao Liu, Guanfeng Beheshti, Amin Zhang, Xuyun School of Computer Science and Engineering Nanjing University of Science and Technology Nanjin China State Key Laboratory for Novel Software Technology Nanjing University Nanjin China School of Computing Macquarie University Sydney Australia

ISBN: (纸本)9789819605699

Recently, graph neural networks(GNNs) have played a key crucial in many recommendation situations. In particular, contrastive learning-based hypergraph neural networks (HGNNs) are gradually becoming a research focus for addressing issues of data sparsity and noise. Despite many studies proving their outstanding performance, there are still some shortcomings: i) Most contrastive learning-based HGNNs primarily rely on cross-view contrastive learning, while neglecting contrastive learning on the interaction graph. ii) Utilizing node embedding for hypergraph structure learning is susceptible to the influence of low-quality representations, thereby constraining the learning capability of HGNNs. To address these issues, we offer a Semantic Similarity-based Graph Contrastive Learning framework (SSGCL), which aims to jointly learn representations with rich semantic information through within-view and cross-view contrastive learning. Specifically, we first introduce consistency contrastive learning, which captures self-supervised signals through semantic similarity between nodes and their neighborhoods. It better captures the unique features of nodes through the connections between nodes and their neighborhoods. Then, we utilize interaction graph learning hypergraph structure, promoting it to extract potential node connections and thus improving its ability to describe homogeneous node relationships. Experimental evaluations on three actual datasets show that SSGCL performs much better than the current baseline models. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Contrastive Learning

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Enhanced Crystallization of Poly(butylene adipate-co-terephthalate)by a Self-assembly Nucleating Agent

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Chinese Journal of Polymer Science 2024年第5期42卷 663-674,I0010页

作者： Cheng Zhou Kun Chen Zi-Heng Zhang Meng-Fan Jing Chun-Tai Liu Chang-Yu Shen Ya-Ming Wang State Key Laboratory of Structural Analysis Optimization and CAE Software for Industrial EquipmentNational Engineering Research Center for Advanced Polymer Processing TechnologyZhengzhou UniversityZhengzhou450002China

Poly(butylene adipate-co-terephthalate)(PBAT)is a promising biodegradable flexible polymer but suffers from slow crystallization rate,making it less attractive for some applications like the injection-molded products in comparison with low-density polyethylene(LDPE).This work aimed to accelerate the crystallization of PBAT by adding a self-assembly nucleating agent octamethylenedicarboxylic dibenzoylhydrazide(OMBH).PBAT/OMBH composites with various OMBH contents(0 wt%,0.5 wt%,0.7 wt%,1 wt%,2 wt%,3 wt%and 5 wt%)were prepared through *** effect of OMBH on the crystallization behavior,morphologies and mechanical properties of PBAT was *** highest nucleation efficiency value of 59.6%was achieved for PBAT with 0.7 wt%OMBH,much higher than that of 22.7%for PBAT with 0.7 wt%*** force microscopy results showed that OMBH formed fine fibers and induced the formation of transcrystalline layers of *** transform infrared spectroscopy(FTIR)combined with two-dimensional correlation spectra suggested that the intermolecular dipole-dipole N—H…O=C interactions but not hydrogen bond between OMBH and PBAT promoted the crystallization of PBAT in the initial period of *** presence of OMBH did not change the crystal form of PBAT but had positive contribution in enhancing its crystallinity and mechanical *** work is essential for preparing PBAT with high crystallization rate,enhancing its potential applications in injection-molded products.

关键词： Poly(butylene adipate-co-terephthalate) Biodegradable Self-assembly nucleating agent Crystallization

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分子间相互作用调控丝素蛋白/聚丙烯酰胺水凝胶的网络形貌和β片结晶,赋予水凝胶优异的黏附、应变和传感性能

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Science China Materials 2024年第5期67卷 1533-1542页

作者：杨德桢孙传强韩哲袁宝刚潘栋陈金传许华杰刘春太申长雨 State Key Laboratory of Structural Analysis Optimization and CAE Software for Industrial EquipmentNational Engineering Research Center for Advanced Polymer Processing Technologythe Key Laboratory of Advanced Materials Processing&Mold of Ministry of EducationZhengzhou UniversityZhengzhou450002China

丝素蛋白(SF)作为一种特殊的天然聚合物,具有优异的生物相容性、生物降解性和双亲性,是制备柔性传感器的良好候选者.然而,丝素蛋白的高结晶度和结晶不可控性使获得这种出色的仿生水凝胶传感器具有挑战性.纯SF水凝胶是脆性的,没有黏性.在... 详细信息

丝素蛋白(SF)作为一种特殊的天然聚合物,具有优异的生物相容性、生物降解性和双亲性,是制备柔性传感器的良好候选者.然而,丝素蛋白的高结晶度和结晶不可控性使获得这种出色的仿生水凝胶传感器具有挑战性.纯SF水凝胶是脆性的,没有黏性.在此,我们通过引入聚丙烯酰胺(PAM)到SF水凝胶中来解决这一问题.由于SF/PAM水凝胶具有较强的分子间相互作用,其网络形貌由欧几里得孔改变为非欧几里得孔.同时,其β片结晶很容易被抑制到纳米尺度.这些演变不仅使SF/PAM水凝胶具有优异的机械性能,而且具有出色的黏附性能.与纯PAM水凝胶相比,SF8/PAM水凝胶的拉伸强度、拉伸破坏应变、抗压强度(80%应变下)和黏附性能(在猪皮上)分别提高了133.1%、120.9%、610.8%和104.8%.此外,SF的双亲性可以使碳纳米管(CNTs)在水凝胶中分散良好.制备的CNT0.3/SF8/PAM水凝胶继承并进一步改善了上述性能.除此之外,它还表现出优异的自黏附传感性能,最大灵敏度因子高达10.13,工作应变范围超过1000%,大应变下稳定循环拉伸达500次以上.同时,六种人类活动的精确检测也得到了验证.本工作为实现高性能SF基水凝胶提供了新策略,并证实SF/PAM水凝胶在柔性可穿戴应变传感器中具有广阔的应用前景.

关键词： silk fibroin intermolecular interaction network morphology β-crystallization adhesion hydrogel strain sensor

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Journal of Computer Science & Technology 2022年第1期37卷 231-251页

作者： Jian-Zhe Zhao Xing-Wei Wang Ke-Ming Mao Chen-Xi Huang Yu-Kai Su Yu-Chen Li Software College Northeastern UniversityShenyang 110169China State Key Laboratory of Synthetical Automation for Process Industries Northeastern UniversityShenyang 110819China College of Computer Science and Engineering Northeastern UniversityShenyang 110819China

Differential privacy(DP)is widely employed for the private data release in the single-party *** utility could be degraded with noise generated by ubiquitous data correlation,and it is often addressed by sensitivity reduction with correlation ***,increasing multiparty data release applications present new challenges for existing *** this paper,we propose a novel correlated differential privacy of the multiparty data release(MP-CRDP).It effectively reduces the merged dataset's dimensionality and correlated sensitivity in two steps to optimize the *** also propose a multiparty correlation analysis *** on the prior knowledge of multiparty data,a more reasonable and rigorous standard is designed to measure the correlated degree,reducing correlated sensitivity,and thus improve the data ***,by adding noise to the weights of machine learning algorithms and query noise to the release data,MP-CRDP provides the release technology for both low-noise private data and private machine learning *** experiments demonstrate the effectiveness and practicability of the proposed method on the utilized Adult and Breast Cancer datasets.

关键词： correlated differential privacy multiparty data release machine learning

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Long-term and short-term plasticity independently mimicked in highly reliable Ru-doped Ge_(2)Sb_(2)Te_(5) electronic synapses

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InfoMat 2024年第8期6卷 85-96页

作者： Qiang Wang Yachuan Wang Yankun Wang Luyue Jiang Jinyan Zhao Zhitang Song Jinshun Bi Libo Zhao Zhuangde Jiang Jutta Schwarzkopf Shengli Wu Bin Zhang Wei Ren Sannian Song Gang Niu State Key Laboratory for Manufacturing Systems Engineering Electronic Materials Research LaboratoryKey Laboratory of the Ministry of Education&International Center for Dielectric ResearchSchool of Electronic Science and EngineeringXi'an Jiaotong UniversityXi'anthe People's Republic of China School of Integrated Circuits Peking UniversityBeijingthe People's Republic of China Beijing Microelectronics Technology Institute Beijingthe People's Republic of China National Key Laboratory of Human-Machine Hybrid Augmented Intelligence National Engineering Research Center for Visual information and Applicationsand School of SoftwareXi'an Jiaotong UniversityXi'anthe People's Republic of China State Key Laboratory of Functional Materials for Informatics Shanghai Institute of Microsystem and Information TechnologyChinese Academy of SciencesShanghaithe People's Republic of China Key Laboratory of Microelectronics Device and Integrated Technology The Institute of Microelectronics of Chinese Academy of SciencesBeijingthe People's Republic of China University of Chinese Academy of Sciences Beijingthe People's Republic of China The State Key Laboratory for Manufacturing Systems Engineering&The International Joint Laboratory for Micro/Nano Manufacturing and Measurement Technology Xi'an Jiaotong UniversityXi'anthe People's Republic of China Leibniz-Institut für Kristallzüchtung Max-Born-Straße 2BerlinGermany Key Laboratory of Physical Electronics and Devices Ministry of EducationSchool of Electronic Science and EngineeringXi'an Jiaotong UniversityXi'anthe People's Republic of China The International Joint Laboratory for Micro/Nano Manufacturing and Measurement Technology Xi'an Jiaotong UniversityXi'anthe People's Republic of China

In order to fulfill the complex cognitive behaviors in neuromorphic systems with reduced peripheral circuits,the reliable electronic synapses mimicked by single device that achieves diverse long-term and short-term plasticity are *** change random access memory(PCRAM)is of great potential for artificial synapses,which faces,however,difficulty to realize short-term plasticity due to the long-lasting resistance *** work reports the ruthenium-doped Ge_(2)Sb_(2)Te_(5)(RuGST)based PCRAM,demonstrating a series of synaptic behaviors of short-term potentiation,pair-pulse facilitation,longterm depression,and short-term plasticity in the same single *** optimized RuGST electronic synapse with the high transformation temperature of hexagonal phase>380C,the outstanding endurance>108 cycles,the low resistance drift factor of 0.092,as well as the extremely high linearity with correlation coefficients of 0.999 and 0.976 in parts of potentiation and *** investigations also go insight to mechanisms of Ru doping according to thorough microstructure characterization,revealing that Ru dopant is able to enter GST lattices thus changing and stabilizing atomic arrangement of *** leads to the short-term plasticity realized by RuGST ***,the proposed RuGST electronic synapses performs a high accuracy of94.1%in a task of image recognition of CIFAR-100 database using ResNet *** work promotes the development of PCRAM platforms for large-scale neuromorphic systems.

关键词： electronic synapses neuromorphic computing PCRAM Ru-doped Ge_(2)Sb_(2)Te_(5)

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OpenSN: An Open Source Library for Emulating LEO Satellite Networks

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IEEE Transactions on Parallel and Distributed Systems 2025年第08期36卷 1574-1590页

作者： Lu, Wenhao Wang, Zhiyuan Zhang, Hefan Zhang, Shan Luo, Hongbin Beihang University School of Computer Science and Engineering Beijing 100191 China Zhongguancun Laboratory State Key Laboratory of Virtual Reality Technology and Systems Beijing 100191 China State Key Laboratory of Software Development Environment China

Low- earth-orbit (LEO) satellite constellations (e.g., Starlink) are becoming a necessary component of future Internet. There have been increasing studies on LEO satellite networking. It is a crucial problem how to evaluate these studies in a systematic and reproducible manner. In this paper, we present OpenSN, i.e., an open source library for emulating large-scale satellite network (SN). Different from Mininet-based SN emulators (e.g., LeoEM), OpenSN adopts container-based virtualization, thus allows for running distributed routing software on each node, and can achieve horizontal scalability via flexible multi-machine extension. Compared to other container-based SN emulators (e.g., StarryNet), OpenSN streamlines the interaction with Docker command line interface and significantly reduces unnecessary operations of creating virtual links. These modifications improve emulation efficiency and vertical scalability on a single machine. Furthermore, OpenSN separates user-defined configuration from container network management via a key-Value Database that records the necessary information for SN emulation. Such a separation architecture enhances the function extensibility. To sum up, OpenSN exhibits advantages in efficiency, scalability, and extensibility, thus is a valuable open source library that empowers research on LEO satellite networking. Experiment results show that OpenSN constructs mega-constellations 5X-10X faster than StarryNet, and updates link state 2X-4X faster than LeoEM. We also verify the scalability of OpenSN by successfully emulating the five-shell Starlink constellation with a total of 4408 satellites. © 1990-2012 IEEE.

关键词： Container low- earth-orbit satellite constellations satellite network emulator

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