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23rd International Symposium on Algorithms and Computation, ISAAC 2012

作者： Chen, Danny Z. Tan, Xuehou Wang, Haitao Wu, Gangshan Department of Computer Science and Engineering University of Notre Dame Notre Dame IN 46556 United States Tokai University 4-1-1 Kitakaname Hiratsuka 259-1292 Japan Department of Computer Science Utah State University Logan UT 84322 United States State Key Lab. for Novel Software Technology Nanjing University Hankou Road 22 Nanjing 210093 China

ISBN: (纸本)9783642352607

Given n points in a circular region C in the plane, we study the problem of moving these points to the boundary of C to form a regular n-gon such that the maximum of the Euclidean distances traveled by the points is minimized. These problems find applications in mobile sensor barrier coverage of wireless sensor networks. The problem further has two versions: the decision version and optimization version. In this paper, we present an O(n log2 n) time algorithm for the decision version and an O(n log3 n) time algorithm for the optimization version. The previously best algorithms for these two problem versions take O(n3.5) time and O(n3.5 log n) time, respectively. A by-product of our techniques is an algorithm for dynamically maintaining the maximum matching of a circular convex bipartite graph;our algorithm performs each vertex insertion or deletion on the graph in O(log 3.5 n) time. This result may be interesting in its own right. © Springer-Verlag 2012.

关键词： Wireless sensor networks

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Targeting Requirements Violations of Autonomous Driving systems by Dynamic Evolutionary Search 36

Targeting Requirements Violations of Autonomous Driving Syst...

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36th IEEE/ACM International Conference on Automated software Engineering, ASE 2021

作者： Luo, Yixing Zhang, Xiao-Yi Arcaini, Paolo Jin, Zhi Zhao, Haiyan Ishikawa, Fuyuki Wu, Rongxin Xie, Tao Peking University Ministry of Education Key Lab. of High-Confidence Software Technologies Beijing China Department of Computer Science and Technology School of EECS Peking University Beijing China National Institute of Informatics Tokyo Japan Xiamen University School of Informatics Xiamen China

ISBN: (纸本)9781665403375

Autonomous Driving systems (ADSs) are complex systems that must satisfy multiple requirements such as safety, compliance to traffic rules, and comfortableness. However, satisfying all these requirements may not always be possible due to emerging environmental conditions. Therefore, the ADSs may have to make trade-offs among multiple requirements during the ongoing operation, resulting in one or more requirements violations. For ADS engineers, it is highly important to know which combinations of requirements violations may occur, as different combinations can expose different types of failures. However, there is currently no testing approach that can generate scenarios to expose different combinations of requirements violations. To address this issue, in this paper, we introduce the notion of requirements violation pattern to characterize a specific combination of requirements violations. Based on this notion, we propose a testing approach named EMOOD that can effectively generate test scenarios to expose as many requirements violation patterns as possible. EMOOD uses a prioritization technique to sort all possible patterns to search for, from the most to the least critical ones. Then, EMOOD iteratively includes an evolutionary many-objective optimization algorithm to find different combinations of requirements violations. In each iteration, the targeted pattern is determined by a dynamic prioritization technique to give preferences to those patterns with higher criticality and higher likelihood to occur. We apply EMOOD to an industrial ADS under two common traffic situations. Evaluation results show that EMOOD outperforms three baseline approaches in generating test scenarios by discovering more requirements violation patterns. © 2021 IEEE.

关键词： Iterative methods

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SAR: Semantic analysis for recommendation

arXiv

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arXiv 2017年

作者： Xiao, Han Meng, Lian State Key Lab. of Intelligent Technology and Systems National Lab. for Information Science and Technology Dept. of Computer Science and Technology Tsinghua University Beijing100084 China

Recommendation system is a common demand in daily life and matrix completion is a widely adopted technique for this task. However, most matrix completion methods lack semantic interpretation and usually result in weak-semantic recommendations. To this end, this paper proposes a Semantic Analysis approach for Recommendation systems (SAR), which applies a two-level hierarchical generative process that assigns semantic features and categories for user/item. SAR learns the semantic representations of users/items merely from user ratings on items, which offers a novel path to recommendation by semantic matching with the learned semantic representations. Extensive experiments demonstrate SAR outperforms other state-of-the-art baselines substantially. Copyright © 2017, The Authors. All rights reserved.

关键词： Recommender systems

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Defending P2P networks based on benign worms

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Journal of Computational Information systems 2011年第7期7卷 2532-2539页

作者： Liu, Xin Hu, Zhichao Liu, Guoyou Wang, Zhi Jia, Chunfu College of Information Technical Science Nankai University Tianjin 300071 China State Key Lab. for Novel Software Technology Nanjing University China

Malicious worms can be exploited to destroy the user system and launch DDoS attack against computer networks. We proposed a method of forming secure P2P network using benign worms against malicious worms. The corresponding benign worm with a hitlist is generated to clean the malicious worm and patch peers in the P2P network which is based on the largest distance list. The benign worm propagates along the histlist. The spread of the benign worm is also a distributed patching process. The patch can be disseminated more quickly and the network congestion is much less than centralized patching scheme in P2P networks. In the experiments, after the benign worm accomplished its mission in the P2P network, all the malicious worms on infected peers are cleaned and almost all of the vulnerable peers are patched. Copyright © 2011 Binary Information Press.

关键词： Denial-of-service attack

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DeePMD-kit v3: A Multiple-Backend Framework for Machine Learning Potentials

arXiv

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arXiv 2025年

作者： Zeng, Jinzhe Zhang, Duo Peng, Anyang Zhang, Xiangyu He, Sensen Wang, Yan Liu, Xinzijian Bi, Hangrui Li, Yifan Cai, Chun Zhang, Chengqian Du, Yiming Zhu, Jia-Xin Mo, Pinghui Huang, Zhengtao Zeng, Qiyu Shi, Shaochen Qin, Xuejian Yu, Zhaoxi Luo, Chenxing Ding, Ye Liu, Yun-Pei Shi, Ruosong Wang, Zhenyu Bore, Sigbjørn Løland Chang, Junhan Deng, Zhe Ding, Zhaohan Han, Siyuan Jiang, Wanrun Ke, Guolin Liu, Zhaoqing Lu, Denghui Muraoka, Koki Oliaei, Hananeh Singh, Anurag Kumar Que, Haohui Xu, Weihong Xu, Zhangmancang Zhuang, Yong-Bin Dai, Jiayu Giese, Timothy J. Jia, Weile Xu, Ben York, Darrin M. Zhang, Linfeng Wang, Han School of Artificial Intelligence and Data Science Unversity of Science and Technology of China Hefei China AI for Science Institute Beijing100080 China DP Technology Beijing100080 China Academy for Advanced Interdisciplinary Studies Peking University Beijing100871 China State Key Lab of Processors Institute of Computing Technology Chinese Academy of Sciences Beijing100871 China University of Chinese Academy of Sciences Beijing China Baidu Inc. Beijing China Department of Computer Science University of Toronto TorontoON Canada Department of Chemistry Princeton University PrincetonNJ08540 United States University of Chinese Academy of Sciences Beijing100871 China State Key Laboratory of Physical Chemistry of Solid Surfaces iChEM College of Chemistry and Chemical Engineering Xiamen University Xiamen361005 China College of Integrated Circuits Hunan University Changsha410082 China State Key Laboratory of Advanced Technology for Materials Synthesis and Processing Center for Smart Materials and Device Integration School of Material Science and Engineering Wuhan University of Technology Wuhan430070 China College of Science National University of Defense Technology Changsha410073 China Hunan Key Laboratory of Extreme Matter and Applications National University of Defense Technology Changsha410073 China ByteDance Research Beijing100098 China Ningbo Institute of Materials Technology and Engineering Chinese Academy of Sciences Ningbo315201 China College of Materials Science and Opto-Electronic Technology University of Chinese Academy of Sciences Beijing100049 China Key Laboratory of Theoretical and Computational Photochemistry of Ministry of Education College of Chemistry Beijing Normal University Beijing100875 China Department of Geosciences Princeton University PrincetonNJ08544 United States Department of Applied Physics and Applied Mathematics Columbia University New YorkNY10027 United States IKKEM Fujian Xiamen361005 China Graduate

In recent years, machine learning potentials (MLPs) have become indispensable tools in physics, chemistry, and materials science, driving the development of software packages for molecular dynamics (MD) simulations and related applications. These packages, typically built on specific machine learning frameworks such as TensorFlow, PyTorch, or JAX, face integration challenges when advanced applications demand communication across different frameworks. The previous TensorFlow-based implementation of DeePMD-kit exemplified these limitations. In this work, we introduce DeePMD-kit version 3, a significant update featuring a multi-backend framework that supports TensorFlow, PyTorch, JAX, and PaddlePaddle backends, and demonstrate the versatility of this architecture through the integration of other MLPs packages and of Differentiable Molecular Force Field. This architecture allows seamless backend switching with minimal modifications, enabling users and developers to integrate DeePMD-kit with other packages using different machine learning frameworks. This innovation facilitates the development of more complex and interoperable workflows, paving the way for broader applications of MLPs in scientific research. Copyright © 2025, The Authors. All rights reserved.

关键词： Molecular dynamics

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Image segmentation with texture clustering based JSEG

Image segmentation with texture clustering based JSEG

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International Conference on Machine Learning and Cybernetics (ICMLC)

作者： Jing Zhang Yong-Wei Gao Sheng-Wei Feng Zhi-Hua Chen Yu-Bo Yuan Department of Computer Science and Engineering East China University of Science and Technology Shanghai State Key Lab. for Novel Software Technology Nanjing University Nanjing China

ISBN: (纸本)9781467372220

Image segmentation is one of the most crucial techniques in computer vision. In this paper, we propose an improved approach for color image segmentation, Texture clustering based JSEG (T-JSEG). The T-JSEG combines the texture information with the classical JSEG algorithm. We use the Gabor feature clustering to produce texture map and combine it with color map to achieve a new map for J value computing. The color image segmentation result is improved by adding the texture information to the JSEG. Experiments on natural color images of Berkeley Segmentation Database verify that our method is very effective on color image segmentation and more accurate boundaries of regions are found in comparison with the classical JSEG algorithm.

关键词： Color information Image segmentation JSEG Texture structure image segmentation chromatic information texture structure color image texture texture map segmentation Segmentation images natural color textures

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Automatic detection and removal of color comments from book images

Automatic detection and removal of color comments from book ...

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International Conference on Machine Learning and Cybernetics (ICMLC)

作者： Guang-Hui Dai Yu-Bo Yuan Jing Zhang Zhi-Hua Chen Department of Computer Science and Engineering East China University of Science and Technology Shanghai State Key Lab. for Novel Software Technology Nanjing University Nanjing China

ISBN: (纸本)9781467372220

Locating the salient parts or regions is a very challenging and important step in image processing. It will be very helpful for image denoising, inpainting or smoothing. In this work, we propose a novel algorithm to detect the regions with color comments in book images automatically. A truncated function is employed to locate positions with high values of Gaussian curvature. Each channel information of a book image is treated as a surface on a given square and corresponding values of the Gaussian curvature are calculated. Finally, with the training cutoff, pixels with high Gaussian curvature will be removed from the original image and replaced by white points. Experimental results ensure that the proposed algorithm is very effective and removes comments automatically.

关键词： Content Detection Guassian Curvature Image processing Mathematical modelling Total curvature Image processing mathematical modeling automatic detection original image images Color

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A Dynamic Load Balancing Algorithm for Stable Pushing of Docker Images in Nginx 6

A Dynamic Load Balancing Algorithm for Stable Pushing of Doc...

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6th International Conference on Machine Learning, Big Data and Business Intelligence, MLBDBI 2024

作者： Xi, Hajie Hu, Song Zhang, He Zhang, Shuang Weng, Jingnong Huang, Jian School of Computer Science and Engineering Beihang University Beijing China Research Institute of Highway Ministry of Transport State Key Lab of Transportation System Beijing China Transportation Comprehensive Enforcement Corps Beijing China School of Software Beihang University Beijing China

ISBN: (纸本)9798331541798

With the rapid development of artificial intelligence, a wide variety of deep learning models have emerged across various fields. Nevertheless, the quality of these models varies significantly, making the effective evaluation of model performance a pressing issue. In some open data competitions, remote evaluation based on Docker images has increasingly become a novel and reliable approach, providing a consistent environment to ensure the fairness of model evaluations. However, it imposes high demands on hardware resources, typically requiring dedicated resources for each participant to serve as Docker Registries for the pushing and management of Docker images. In this paper, we extend the load balancing module of the Nginx server by integrating Lua scripts and propose a Cache-based Dynamic Smooth Weighted Round-robin (CDSWRR) algorithm to optimize the pushing process of Docker images. By constructing a unified load balancing entry, the proposed approach simplifies the deployment of Docker Registry clusters. Experiments show that compared to weighted round-robin and IP hash algorithms of Nginx, the CDSWRR algorithm is able to ensure stable pushing of Docker images and reduce both response error rate and response time. © 2024 IEEE.

关键词： Deep learning

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Parameters adaption of Lebesgue sampling-based diagnosis and prognosis for Li-ion batteries

Parameters adaption of Lebesgue sampling-based diagnosis and...

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2015 Annual Conference of the Prognostics and Health Management Society, PHM 2015

作者： Yan, Wuzhao Dou, Wanchun Liu, Datong Peng, Yu Zhang, Bin Department of Electrical Engineering University of South Carolina ColumbiaSC29208 United States Department of Computer Science and Technology State Key Lab. for Novel Software Technology Nanjing University NanjingJiangsu210093 China Department of Automatic Test and Control Harbin Institute of Technology HarbinHeilongjiang150080 China

ISBN: (纸本)9781936263202

Traditional fault diagnosis and prognosis (FDP) approaches are based on Riemann sampling (RS), in which samples are taken and algorithms are executed in a periodic time interval. With the increase of system complexity, the real-time implementation of this Riemann sampling-based FDP (RS-FDP) becomes a bottleneck, especially for distributed applications. To overcome this problem, a Lebesgue sampling-based FDP (LS-FDP) is proposed. LS-FDP takes samples on the fault dimension axis and provides a need-based diagnostic philosophy in which the algorithm is executed only when necessary. In previous Lebesgue sampling-based FDP, the Lebesgue length is a constant. To accommodate the change of fault dynamics, it is desirable to execute FDP algorithm more frequently when the fault growth is fast while less frequently when fault growth is slow. This requires to change the Lebesgue length adaptively. The goal of this paper is to deliver an improved LS-FDP method with varying Lebesgue length, which enables the FDP to be executed according to needs. The design and implementation of varying Lebesgue length LS-FDP based on a particle filtering algorithm are illustrated with experimental results on Li-ion batteries to verify the performances of the proposed approach. The experimental results show that the new varying LS-FDP is accurate and time-efficient on long term prognosis and also keeps a closer monitoring on the fast increase of fault size. © 2015, Prognostics and Health Management Society. All rights reserved.

关键词： Real time control

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Optimal Pricing of Multi-model Hybrid system for PaaS Cloud Computing

Optimal Pricing of Multi-model Hybrid System for PaaS Cloud ...

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International Conference on Cloud and Service Computing (CSC)

作者： Hao Lu Xing Wu Wu Zhang Jin Liu School of Computer Engineering and Science Shanghai University Shanghai China State Key Laboratory for Novel Software Technology Nanjing University Nanjing China State Key Lab. Of Software Engineering Wuhan University Wuhan China

Success of cloud computing service depends on an acceptable pricing model, especially in the PaaS. As a dynamic platform, PaaS layer depends on the infrastructure layer and extends to the application layer. How to find an optimal pricing policy is the problem for the cloud providers in face of stochastic and dynamic demand. In this paper, we present an approach of dynamic pricing model in order to get max profits. We analyze the model by a multi-condition hybrid system. But we also use a theory of revenue maximization and cost minimization. When at a current state, the system content cost minimization to build a hybrid system for revenue maximization, we will get the most profits.

关键词： Pricing Cloud computing Computational modeling Mathematical model Educational institutions Optimal control Equations

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