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A Power and Area Optimization Approach of Mixed Polarity Reed-Muller Expression for Incompletely Specified Boolean Functions

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Journal of computer Science & Technology 2017年第2期32卷 297-311页

作者： Zhen-Xue He Li-Min Xiao Li Ruan Fei Gu Zhi-Sheng Huo Guang-Jun Qin Ming-Fa Zhu F Long-Bing Zhang Rui Liu Xiang Wang State Key Laboratory of Software Development Environment Beihang University Beijing 100191 China School of Computer Science and Engineering Beihang University Beijing 100191 China School of Electronic and Information Engineering Beihang University Beijing 100191 China State Key Laboratory of Computer Architecture Institute of Computing Technology Chinese Academy of Sciences Beijing 100190 China University of Chinese Academy of Sciences Beijing 100049 China National Engineering Research Center for Science and Technology Resources Sharing Service Beihang University Beijing 100191 China

The power and area optimization of Reed-Muller （RM） circuits has been widely concerned. However, almost none of the exiting power and area optimization approaches can obtain all the Pareto optimal solutions of the original problem and are efficient enough. Moreover, they have not considered the don＇t care terms, which makes the circuit performance unable to be further optimized. In this paper, we propose a power and area optimization approach of mixed polarity RM expression （MPRM） for incompletely specified Boolean functions based on Non-Dominated Sorting Genetic Algorithm II （NSGA-II）. Firstly, the incompletely specified Boolean function is transformed into zero polarity incompletely specified MPRM （ISMPRM） by using a novel ISMPRM acquisition algorithm. Secondly, the polarity and allocation of don＇t care terms of ISMPRM is encoded as chromosome. Lastly, the Pareto optimal solutions are obtained by using NSGA-II, in which MPRM corresponding to the given chromosome is obtained by using a chromosome conversion algorithm. The results on incompletely specified Boolean functions and MCNC benchmark circuits show that a significant power and area improvement can be made compared with the existing power and area optimization approaches of RM circuits.

关键词： power and area optimization Reed-Muller （RM） circuit Pareto optimal solution don＇t care term chromosomeconversion

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INTELLIGENT INFORMATION network SECURITY AND MANAGEMENT

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China Communications 2016年第7期13卷 3-6页

作者： Yixian Yang Zhongshan Zhang Wenjing Li Information Security Center(ISC) Beijing University of Posts and Telecommunications(BUPT) National Engineering Laboratory for Disaster Backup and Recovery the School of Computer and Communication Engineering in the University of Science and Technology Beijing(USTB) State Key Lab of Networking and Switching Technologies Network Management Research Center at BUPT National Innovation Research Group of China

Intelligent Information network Security and Management(IINSM)is an emerging direction in future Internet architecture research,which has gained significant tractions among academia and *** the rapid development of modern society,intelligent information network with the computer as the core technology is widely used in every aspect of social ***

关键词： DCT INTELLIGENT INFORMATION network SECURITY AND MANAGEMENT Simulation DWT DCNN

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A duplicate data detection approach based on MapReduce and HDFS

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Recent Patents on computer Science 2017年第2期10卷 140-148页

作者： Wei, Fang Xue-Zhi, Wen Yu, Zheng Jiangsu Engineering Center of Network Monitoring Nanjing University of Information Science & Technology Nanjing210044 China School of Computer and Software Nanjing University of Information Science & Technology Nanjing210044 China State Key Laboratory for Novel Software Technology Nanjing University Nanjing210066 China Department of Electrical & Computer Engineering University of Florida GainesvilleFL32611 United States

Background: With the surge in the volume of collected data, deduplication will undoubtedly become one of the problems faced by researchers. There is significant advantage for deduplication to reduce storage, network bandwidth, and system scalability of coarse-grained redundant data. Since the conventional methods of deleting duplicate data include hash comparison and binary differential incremental. They will lead to several bottlenecks for processing large scale data. And, the traditional Simhash similarity method has less consideration on the natural similarity of text in some specific fields and cannot run in parallel program with large scale text data processing efficiently. This paper examines several most important patents in the area of data detection. Then, this paper will focus on large scale of data deduplication based on MapReduce and HDFS. Methods: We propose a duplicate data detection approach based on MapReduce and HDFS, which uses the Simhash similarity computing algorithm and SSN algorithm, and explain our distributed duplicate detection workflow. The important technical advantages of the invention include generating a checksum for each processed record and comparing the generated checksum to detect duplicate record. It produces the fingerprints of short text with Simhash similarity algorithm. It clusters the fingerprint results using Shared Nearest Neighbor (SNN) algorithm. The whole parallel progress is implemented using MapReduce programming model. Results: From the experimental results, we conclude that our proposed approach obtains MapReduce job schedules with significantly less executing time, making it suitable for processing large scale datasets in real applications. The experimental results show the proposed approach has better performance and efficiency. Conclusion: In this patent, we propose a duplicate data detection approach based on MapReduce and HDFS, which uses the Simhash similarity computing algorithm and SSN algorithm. The results

关键词： MapReduce

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Real-time and generic queue time estimation based on mobile crowdsensing

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Frontiers of computer Science 2017年第1期11卷 49-60页

作者： Jiangtao WANG Yasha WANG Daqing ZHANG Leye WANG Chao CHEN Jae Woong LEE Yuanduo HE Key Laboratory of High Confidence Software Technologies Ministry of Education Beijing 100871 China School of Electronics Engineering and Computer Science Peking University Beijing 100871 China Beida (Binhai) Information Research Tianjin 300450 China National Engineering Research Center of Software Engineering Peking University Beijing 100871 China Network & Services Department Institut Mines-Telecom/Telecom SudParis Evry 91011 France Department of Computer Science Chongqing University Chongqing 400044 China Department of Mathematics and Computer Science University of Central Missouri Warrensburg MO 64093 USA

People often have to queue for a busy service in many places around a city, and knowing the queue time can be helpful for making better activity plans to avoid long queues. Traditional solutions to the queue time monitoring are based on pre-deployed infrastructures, such as cameras and infrared sensors, which are costly and fail to deliver the queue time information to scattered citizens. This paper presents CrowdQTE, a mobile crowdsensing system, which utilizes the sensor-enhanced mobile devices and crowd hu- man intelligence to monitor and provide real-time queue time information for various queuing scenarios. When people are waiting in a line, we utilize the accelerometer sensor data and ambient contexts to automatically detect the queueing behav- ior and calculate the queue time. When people are not waiting in a line, it estimates the queue time based on the information reported manually by participants. We evaluate the perfor- mance of the system with a two-week and 12-person deploy- ment using commercially-available smartphones. The results demonstrate that CrowdQTE is effective in estimating queu- ing status.

关键词： mobile crowdsensing queue time estimation opportunistic and participatory sensing

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Experience report:investigating bug fixes in machine learning frameworks/libraries

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Frontiers of computer Science 2021年第6期15卷 43-58页

作者： Xiaobing SUN Tianchi ZHOU Rongcun WANG Yucong DUAN Lili BO Jianming CHANG School of Information Engineering Yangzhou UniversityYangzhou 225100China State Key Laboratory for Novel Software Technology Nanjing UniversityNanjing 210023China Jiangsu Engineering Research Center of Knowledge Management and Intelligent Service Yangzhou University Yangzhou 225127China School of Computer Science and Technology China University of Mining and TechnologyXuzhou 221116China School of Computer Science and Cyberspace Security Hainan UniversityHaikou 570228China

Machine learning(ML)techniques and algorithms have been successfully and widely used in various areas including software engineering *** other software projects,bugs are also common in ML projects and *** order to more deeply understand the features related to bug fixing in ML projects,we conduct an empirical study with 939 bugs from five ML projects by manually examining the bug categories,fixing patterns,fixing scale,fixing duration,and types of *** results show that(1)there are commonly seven types of bugs in ML programs;(2)twelve fixing patterns are typically used to fix the bugs in ML programs;(3)68.80%of the patches belong to micro-scale-fix and small-scale-fix;(4)66.77%of the bugs in ML programs can be fixed within one month;(5)45.90%of the bug fixes belong to corrective activity from the perspective of software ***,we perform a questionnaire survey and send them to developers or users of ML projects to validate the results in our empirical *** results of our empirical study are basically consistent with the feedback from *** findings from the empirical study provide useful guidance and insights for developers and users to effectively detect and fix bugs in MLprojects.

关键词： bug fixing machine learning project empirical study questionnaire survey

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Identification and evaluation of sharing memory covert timing channel in Xen virtual machines

Identification and evaluation of sharing memory covert timin...

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International Conference on Cloud Computing

作者： Wu, Jing Zheng Ding, Liping Wang, Yongji Han, Wei National Engineering Research Center for Fundamental Software Institute of Software Beijing China State Key Laboratory of Computer Science Institute of Software Beijing China Graduate School Chinese Academy of Science Beijing China

ISBN: (纸本)9780769544601

Virtualization technology is the basis of cloud computing, and the most important property of virtualization is isolation. Isolation guarantees security between virtual machines. However, covert channel breaks the isolation and leaks sensitive message covertly. In this paper, we formally model the isolation into noninterference, and define that all the transmission channels violating noninterference are covert channels. With this definition, we present an identification method based on information flow. This method first compiles the source code into a more structured equivalent code with LLVM. And then a search algorithm is proposed to obtain the shared resources and the operational processes in the equivalent code. A new covert channel termed sharing memory covert timing channel (SMCTC) is identified from Xen source code. We construct channel scenario for SMCTC, and evaluate its threat with the metrics of channel capacity and transmission accuracy. The results show that SMCTC is much more threatened than CPU load based and cache based covert channels etc. © 2011 IEEE.

关键词： Virtual machine

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Virtual brain surgery simulation system based on haptic interaction

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High Technology Letters 2015年第2期21卷 185-191页

作者：张小瑞 Zhu Jiandong Sun Wei Norman I.Badler Song Aiguo Niu Jianwei Liu Jia School of Computer and Software Nanjing University of Information Science & Technology Jiangsu Engineering Center of Network Monitoring Nanjing University of Information Science and Technology School of Information and Control Nanjing University of Information Science & Technology School of Engineering and Applied Science University of Pennsylvania School of Instrument Science and Engineering Southeast University State key Laboratory of Virtual Reality Technology and Systems Beihang University

To improve the accuracy and interactivity of soft tissue delormatlon simulation, a new plate spring model based on physics is proposed. The model is parameterized and thus can be adapted to simulate different organs. Different soft tissues are modeled by changing the width, number of pieces, thickness, and length of a single plate spring. In this paper, the structural design, calcula- tion of soft tissue deformation and real-time feedback operations of our system are also introduced. To evaluate the feasibility of the system and validate the model, an experimental system of haptic in- teraction, in which users can use virtual hands to pull virtual brain tissues, is built using PHANTOM OMNI devices. Experimental results show that the proposed system is stable, accurate and promising for modeling instantaneous soft tissue deformation.

关键词： haptic feedback human-computer interaction surgery simulation soft tissue deformation

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Ranking the importance of classes via software structural analysis

Ranking the importance of classes via software structural an...

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2011 International Conference on Future Communication, Computing, Control and Management, ICF4C 2011

作者： Ding-Wei, Li Bing, Li Peng, He Wei-Feng, Pan State Key Laboratory of Software Engineering Wuhan University Wuhan 430072 China Complex Networks Research Center Wuhan University Wuhan 430072 China School of Computer Science and Information Engineering Zhejiang Gongshan University Hangzhou 310018 China

ISBN: (纸本)9783642273100

How to identify important classes in an object-oriented system is a significant task for resources allocation and decision making. However, the work on ranking the importance of classes is scarce. This paper introduces a weighted software network model to represent the structure of object-oriented software, and based on which an indicator, IC, is defined to measure the importance of classes. By ranking the ICs of all classes we can obtain the important classes we should focus on. Manually inspection of the source code verifies the meaningfulness of the classes obtained and also validates the feasibility of our approach. © 2012 Springer-Verlag GmbH.

关键词： complex networks

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FedIERF: Federated Incremental Extremely Random Forest for Wearable Health Monitoring

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Journal of computer Science & Technology 2023年第5期38卷 970-984页

作者：胡春雨忽丽莎袁林陆佃杰吕蕾陈益强 Key Laboratory of Computing Power Network and Information Security Ministry of EducationShandong Computer Science Center(National Supercomputer Center in Jinan)Qilu University of Technology(Shandong Academy of Sciences)Jinan 250353China Shandong Provincial Key Laboratory of Computer Networks Shandong Fundamental Research Center for Computer ScienceJinan 250000China Shandong Provincial Key Laboratory for Novel Distributed Computer Software Technology Jinan 25000China Institute of Information Technology Hebei University of Economics and BusinessShijiazhuang 050061China School of Information Science and Engineering Shandong Normal UniversityJinan 250358China Institute of Computing Technology Chinese Academy of SciencesBeijing 100190China

Wearable health monitoring is a crucial technical tool that offers early warning for chronic diseases due to its superior portability and low power ***,most wearable health data is distributed across dfferent organizations,such as hospitals,research institutes,and companies,and can only be accessed by the owners of the data in compliance with data privacy *** first challenge addressed in this paper is communicating in a privacy-preserving manner among different *** second technical challenge is handling the dynamic expansion of the federation without model *** address the first challenge,we propose a horizontal federated learning method called Federated Extremely Random Forest(FedERF).Its contribution-based splitting score computing mechanism significantly mitigates the impact of privacy protection constraints on model *** on FedERF,we present a federated incremental learning method called Federated Incremental Extremely Random Forest(FedIERF)to address the second technical *** introduces a hardness-driven weighting mechanism and an importance-based updating scheme to update the existing federated model *** experiments show that FedERF achieves comparable performance with non-federated methods,and FedIERF effectively addresses the dynamic expansion of the *** opens up opportunities for cooperation between different organizations in wearable health monitoring.

关键词： federated learning incremental learning random forest wearable health monitoring

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Biological Classification System Knowledge Graph and Semi-automatic Construction of Its Invertebrate Fossil Branches

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Journal of Earth Science 2024年第6期35卷 2119-2128页

作者： Shaochun Dong Yukun Shi Yizao Ran Haijun Wu Yiying Deng Junxuan Fan Xinyu Dai School of Earth Sciences and Engineering Frontiers Science Center for Critical Earth Material CyclingNanjing UniversityNanjing210046China Jiangsu Deep-Time Digital Earth Research Center for Excellence Suzhou215004China School of Computer Science Nanjing UniversityNanjing210046China School of Resources and Environmental Engineering Hefei University of TechnologyHefei230009China State Key Laboratory for Mineral Deposits Research Nanjing210046China National Key Laboratory for Novel Software Technology Nanjing210046China

Biological classification is the foundation of biology and paleontology,as it arranges all the organisms in a hierarchy that humans can easily follow and *** is further used to reconstruct the evolution of life.A biological classification system(BCS)that includes all the established fossil taxa would be both useful and challenging for uncovering the life *** fossil taxa were originally recorded in various published books and articles written by natural languages,the primary step is to organize all those taxa information in a manner that can be deciphered by a computer system.A Knowledge Graph(KG)is a formalized description framework of semantic knowledge,which represents and retrieves knowledge in a machine-understandable way,and therefore provides an eligible method to represent the *** this paper,a model of the BCS KG including the ontology and fact layers is *** put it into practice,the ontology layer of the invertebrate fossil branches was manually developed,while the fact layer was automatically constructed by extracting information from 46 volumes of the Treatise of Invertebrate Paleontology series with the help of natural language processing *** a result,27348 taxa nodes spanning fourteen taxonomic ranks were extracted with high accuracy and high efficiency,and the invertebrate fossil branches of the BCS KG was thus *** study demonstrates that a properly designed KG model and its automatic construction with the help of natural language processing are reliable and efficient.

关键词： biological classification system knowledge graph ontology invertebrate fossil big data

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