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An adaptive particle filter for mobile robot fault diagnosis

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Journal of Central South University of technology 2006年第6期13卷 689-693页

作者： DUAN Zhuo-hua FU Ming CAI Zi-xing YU Jin-xia computer science and technology Postdoctoral Research Station School of Information Science and EngineeringCentral South UniversityChangsha 410083China Department of computer science Shaoguan UniversityShaoguan 512003China Department of computer science and technology Henan Polytechnic UniversityJiaozuo 454000China

An adaptive particle filter for fault diagnosis of dead-reckoning system was presented,which applied a general framework to integrate rule-based domain knowledge into particle *** knowledge was exploited to constrain the state space to certain *** state space was adjusted by setting the transition ***,the monitored mobile robot and its kinematics models,measurement models and fault models were ***,5 kinds of planar movement states of the robot were estimated with driving speeds of left and right *** that,the possible(or detectable)fault modes were obtained to modify the transitional *** are two typical advantages of this method,*** will never be drawn from hopeless area of the state space,and the particle number is reduced.

关键词： mobile robot fault diagnosis particle filter adaptive

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DSI： Distributed Service Integration for Service Grid

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Journal of computer science & technology 2003年第4期18卷 474-483页

作者：杨广文史树明王鼎兴黄启锋刘学铮 Department of computer science and technology Tsinghua University Beijing 100084 P.R. China

This paper presents DSI, a distributed service discovery and integration utility for service grid. The goal of DSI is efficiently to improve service publishing, deletion and lookup,decentralized control, scalability, and availability. DSI comprises a logically global metadata pool and a double-layered DHT (Distributed Hash Table). Efficient service publishing and lookup are achieved by adopting DHT. Clean service deletion is guaranteed by time-stamping. And system availability is improved by replication combined with automatic indexer selection. Experiments show that DSI can achieve short response time, low processing cost and high availability.

关键词： grid servise integration double-layered DHT UDDI

A Semantic Matchmaker for Ranking Web Services

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Journal of computer science & technology 2006年第4期21卷 574-581页

作者：许斌张钋李涓子杨文军 Department of computer science and technology Tsinghua University Beijing 100084 P.R. China

This paper is concerned with the matchmaker for ranking web services by using semantics. So far several methods of semantic matchmaker have been proposed. Most of them, however, focus on classifying the services into predefined categories rather than providing a ranking result. In this paper, a new method of semantic matchmaker is proposed for ranking web services. It is proposed to use the semantic distance for estimating the matching degree between a service and a user request. Four types of semantic distances are defined and four algorithms are implemented respectively to calculate them. Experimental results show that the proposed semantic matchmaker significantly outperforms the keywordbased baseline method.

关键词： semantic web services semantic distance services ranking

Taxonomy of Data Prefetching for Multicore Processors

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Journal of computer science & technology 2009年第3期24卷 405-417页

作者： Surendra Byna 陈勇孙贤和 Department of computer science Illinois Institute of TechnologyChicagoIllinois 60616U.S.A.

Data prefetching is an effective data access latency hiding technique to mask the CPU stall caused by cache misses and to bridge the performance gap between processor and memory. With hardware and/or software support, data prefetching brings data closer to a processor before it is actually needed. Many prefetching techniques have been developed for single-core processors. Recent developments in processor technology have brought multicore processors into mainstream. While some of the single-core prefetching techniques are directly applicable to multicore processors, numerous novel strategies have been proposed in the past few years to take advantage of multiple cores. This paper aims to provide a comprehensive review of the state-of-the-art prefetching techniques, and proposes a taxonomy that classifies various design concerns in developing a prefetching strategy, especially for multicore processors. We compare various existing methods through analysis as well.

关键词： taxonomy of prefetching strategies multicore processors data prefetching memory hierarchy

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Reflection and Refraction on Implicit Surfaces

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Journal of computer science & technology 2006年第2期21卷 166-172页

作者：胡伟秦开怀王华维李亚峰 Department of computer science and technology Tsinghua University Beijing 100084 P.R. China

Implicit surfaces are often used in computer graphics. They can be easily modeled and rendered, and many objects are composed of them in our daily life. In this paper, based on the concept of virtual objects, a novel method of real-time rendering is presented for reflection and refraction on implicit surface. The method is used to construct virtual objects from real objects quickly, and then render the virtual objects as if they were real objects except for one more step of merging their images with the real objects＇ images. Characteristics of implicit surfaces are used to compute virtual objects effectively and quickly. GPUs （Graphics Processing Units） are used to compute virtual vertices quickly and further accelerate the computing and rendering processes. As a result, realistic effects of reflections and refractions on implicit surfaces are rendered in real time.

关键词： reflection refraction implicit surface GPU

PRAP-PIM:A weight pattern reusing aware pruning method for ReRAM-based PIM DNN accelerators

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High-Confidence Computing 2023年第2期3卷 50-59页

作者： Zhaoyan Shen Jinhao Wu Xikun Jiang Yuhao Zhang Lei Ju Zhiping Jia School of computer science and technology Shandong UniversityQindao 266237China School of Cyber science and technology Shandong UniversityQindao 266237China Department of computer science and technology Tsinghua UniversityBeijing 100084China

Resistive Random-Access Memory(ReRAM)based Processing-in-Memory(PIM)frameworks are proposed to accelerate the working process of DNN models by eliminating the data movement between the computing and memory *** further mitigate the space and energy consumption,DNN model weight sparsity and weight pattern repetition are exploited to optimize these ReRAM-based ***,most of these works only focus on one aspect of this software/hardware codesign framework and optimize them individually,which makes the design far from *** this paper,we propose PRAP-PIM,which jointly exploits the weight sparsity and weight pattern repetition by using a weight pattern reusing aware pruning *** relaxing the weight pattern reusing precondition,we propose a similarity-based weight pattern reusing method that can achieve a higher weight pattern reusing *** results show that PRAP-PIM achieves 1.64×performance improvement and 1.51×energy efficiency improvement in popular deep learning benchmarks,compared with the state-of-the-art ReRAM-based DNN accelerators.

关键词： Resistive Random-Access Memory Processing-in-Memory Deep neural network Model compression

Insider Attack Detection Using Deep Belief Neural Network in Cloud Computing

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computer Systems science & Engineering 2022年第5期41卷 479-492页

作者： A.S.Anakath R.Kannadasan Niju P.Joseph P.Boominathan G.R.Sreekanth School of Computing E.G.S.Pillay Engineering CollegeNagapattinam611002TamilnaduIndia Department of Software Systems School of Computer Science and Engineering(SCOPE)Vellore Institute of Technology UniversityVellore632014TamilnaduIndia Department of computer science CHRIST(Deemed to be University)Bengaluru560029India Department of Information Security School of Computer Science and Engineering(SCOPE)Vellore Institute of Technology UniversityVellore632014TamilnaduIndia Department of computer science and Engineering Kongu Engineering CollegeErode638060TamilnaduIndia

Cloud computing is a high network infrastructure where users,owners,third users,authorized users,and customers can access and store their information *** use of cloud computing has realized the rapid increase of information in every field and the need for a centralized location for processing *** cloud is nowadays highly affected by internal threats of the *** applications such as banking,hospital,and business are more likely affected by real user *** intruder is presented as a user and set as a member of the *** becoming an insider in the network,they will try to attack or steal sensitive data during information sharing or *** major issue in today's technological development is identifying the insider threat in the cloud *** data are lost,compromising cloud users is *** and security are not ensured,and then,the usage of the cloud is not *** solutions are available for the external security of the cloud ***,insider or internal threats need to be *** this research work,we focus on a solution for identifying an insider attack using the artificial intelligence *** insider attack is possible by using nodes of weak users’*** will log in using a weak user id,connect to a network,and pretend to be a trusted ***,they can easily attack and hack information as an insider,and identifying them is very *** types of attacks need intelligent solutions.A machine learning approach is widely used for security *** date,the existing lags can classify the attackers *** information hijacking process is very absurd,which motivates young researchers to provide a solution for internal *** our proposed work,we track the attackers using a user interaction behavior pattern and deep learning *** usage of mouse movements and clicks and keystrokes of the real user is stored in a *** deep belief neural

关键词： Cloud computing security insider attack network security privacy user interaction behavior deep belief neural network

Cumulative activation in social networks

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science China(Information sciences) 2019年第5期62卷 108-128页

作者： Xiaohan SHAN Wei CHEN Qiang LI Xiaoming SUN Jialin ZHANG Department of computer science and technology Tsinghua University Microsoft CAS Key Lab of Network Data science and technology Institute of Computing TechnologyChinese Academy of Sciences University of Chinese Academy of sciences

Most studies on influence maximization focus on one-shot propagation, i.e., the influence is propagated from seed users only once following a probabilistic diffusion model and users’ activation are determined via single cascade. In reality it is often the case that a user needs to be cumulatively impacted by receiving enough pieces of information propagated to her before she makes the final purchase decision. In this paper we model such cumulative activation as the following process: first multiple pieces of information are propagated independently in the social network following the classical independent cascade model, then the user will be activated(and adopt the product) if the cumulative pieces of information she received reaches her cumulative activation threshold. Two optimization problems are investigated under this framework: seed minimization with cumulative activation(SM-CA), which asks how to select a seed set with minimum size such that the number of cumulatively active nodes reaches a given requirement η; influence maximization with cumulative activation(IM-CA), which asks how to choose a seed set with fixed budget to maximize the number of cumulatively active nodes. For SM-CA problem, we design a greedy algorithm that yields a bicriteria O(ln n)-approximation when η = n, where n is the number of nodes in the network. For both SM-CA problem with η < n and IM-CA problem, we prove strong inapproximability results. Despite the hardness results, we propose two efficient heuristic algorithms for SM-CA and IM-CA respectively based on the reverse reachable set approach. Experimental results on different real-world social networks show that our algorithms significantly outperform baseline algorithms.

关键词： social networks cumulative activation influence maximization seed minimization

A New Method to Locate the Region of Interest( ROI) of Palmprint

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Journal of Harbin Institute of technology(New Series) 2013年第2期20卷 111-117页

作者： Ping Xue Wen-Chao Li Tian-Yu Liu college of Automation Harbin University of Science and Technology

Biometric identification was a kind of identity recognition technology by making use of the human's unique physiological or behavioral characteristics,it provided a high reliability and stability way for the identification. Global threshold binarization palmprint image is used in this paper,and the bio-morphological methods are used to get the sensitive area of palmprint image's positioning point,so as to extract the region of interest. The palmprint collection is realized on the FPGA chip,and this kind of collection method uses the DSP Builder toolbox to realize visual programming in Matlab / Simulink and achieve fast modeling and development. The practice proves that this method is simple,flexible and its equipment is portable and fast.

关键词： DSP builder FPGA palmprint identification region of interest( ROI)

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