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检索条件"任意字段=International Conference on Big Data Intelligence and Computing, DataCom 2022"

共 1359 条记录，以下是431-440 订阅

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Distributed Dual-layer Differential Privacy Protection in Smart Meter bigdata Mining 2

Distributed Dual-layer Differential Privacy Protection in Sm...

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2nd international conference on Algorithms, High Performance computing and Artificial intelligence, AHPCAI 2022

作者： Li, Zhihao Wang, Junling Cai, Yan School of Information Engineering Jiangxi University of Science and Technology Jiangxi Province Ganzhou China Ganzhou Power Supply Company Jiangxi Province Ganzhou China

ISBN: (纸本)9798350334784

With the continuous development of smart grid technology, smart meter serves as an important source of big data power. Its data security problem can not be ignored, and its privacy protection is the foundation and important guarantee of power grid security. This paper proposes a distributed dual-layer differential privacy protection mechanism for the two key nodes of the smart meter life cycle, the user side, and the server side. It is proved that this method satisfies the conditions of differential privacy protection. Experimental results show that the distributed dual-layer differential privacy protection mechanism plus noise mechanism will not affect the accurate billing of energy consumption. It eliminates the privacy problem of the entire life cycle of smart meter data and is perfectly realized which balances smart meter data mining and privacy protection. © 2022 IEEE.

关键词： data privacy

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big data collaborative artificial intelligence and high-performance computing to drive physical design of fusion

Big data collaborative artificial intelligence and high-perf...

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2022 international conference on Cloud computing, big data Applications and Software Engineering, CBASE 2022

作者： Liu, Pan Liu, Gongjie Liu, Jie Liu, Chencheng Xiong, Wenbin Tang, Zhangcun Zhou, Yinzhao Wang, Yonggang Yuan, Zhouming Beijng Paratera Technology Corp. Ltd Beijing100000 China National University of Defense Technology Science and Technology on Parallel and Distributed Processing Laboratory Changsha410073 China National University of Defense Technology Laboratory of Software Engineering for Complex Systems Changsha410073 China Central South University of Forestry and Technology Changsha410000 China Nuclear and Radiation Safety Center Mee Beijing100000 China University of Electronic Science and Technology of China Chengdu610000 China Tianfu Innovation Energy Establishment Chengdu610000 China

ISBN: (纸本)9798350396393

Controlled thermonuclear fusion has always been a dream pursued by mankind. However, the physical processes of controlled thermonuclear fusion are complex, requiring numerical simulations with high performance computing, and the amount of data generated by the physical processes on spatial, temporal and temperature scales is too large to be captured, managed, processed and collated in a reasonable time frame by mainstream software tools to achieve more aggressive fusion physical design. The data are too large to be captured, managed, processed, and collated into more aggressive targets for fusion physical design in a reasonable time by mainstream software tools. At the same time, the failure of fusion ignition can be caused by the distortion of various key physical quantities, and only by decomposing the process step by step and clarifying the changes of key physical quantities in the fusion physics process, can an effective mechanism be formed to prevent the distortion of key physical quantities from causing ignition failure in experimental physics. big data in collaboration with artificial intelligence and high performance computing to drive the physical design of fusion is a novel avenue. By data acquisition with and pre-processing, this allows the creation of small sample libraries and deep learning. With supervised learning function convergence, incorporating solid/fluid computational methods, further network layering and cell expansion, the parameters of the physical model conforming to Lawson's criterion will become experimental physical parameters, and we find the new approach in data capacity, Model combination approach, Type of material, Calculation speed, Optimisation of design iteration times, etc. are superior to the traditional approach. © 2022 IEEE.

关键词： big data

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data Storage Design of international Students Comprehensive Information Management System based on SqlServer database

Data Storage Design of International Students Comprehensive ...

引用

2022 international conference on Information System, computing and Educational Technology, ICISCET 2022

作者： Xiu, Hehong College of International Education Bohai University Jinzhou China

ISBN: (数字)9781665460446

ISBN: (纸本)9781665460446

In the new era of continuous breakthroughs in technologies such as computers, big data, the Internet of Things and artificial intelligence, various new technologies have realized the ubiquitous and borderless sharing of information. In particular, the transition from the Internet to the mobile Internet has created a way of living, working and learning across time and space, and fundamentally changed the way of knowledge acquisition. Educational informatization promotes the development of international education, gives full play to the advantages of information technology, and develops a comprehensive information management system for international students to meet the needs of education management in the information age. Based on SqlServer database management system, this paper designs conceptual structure and logical structure, provides a complete data storage structure for the development of comprehensive information management system for international students, and solves the key problems of system development. © 2022 IEEE.

关键词： Students

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EEAI: An End-edge Architecture for Accelerating Deep Neural Network Inference 23

EEAI: An End-edge Architecture for Accelerating Deep Neural ...

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23rd IEEE international conference on High Performance computing and Communications, 7th IEEE international conference on data Science and Systems, 19th IEEE international conference on Smart City and 7th IEEE international conference on Dependability in Sensor, Cloud and big data Systems and Applications, HPCC-DSS-SmartCity-DependSys 2021

作者： Liu, Guozhi Dai, Fei Huang, Bi Qiang, Zhenping Li, LeCheng Wang, Shuai School of Big Data and Intelligent Engineering Southwest Forestry University Kunming China

ISBN: (纸本)9781665494571

Deep Neural Networks (DNNs), as a key technology for Artificial intelligence (AI) applications in the 5G era, have been widely used in the field of mobile intelligence. However, it is challenging to run computation-intensive DNN-based applications on mobile devices due to the limited resources. What's worse, traditional cloud-assisted approach requires significant amounts of data to be uploaded to the cloud through wireless network, leading to poor real-time performance and low quality of user experience. To address these challenges, in this paper, we propose EEAI, a framework that end-edge collaborative DNN inference. Firstly, we analyze the characteristics of DNN-based applications. Then, we introduce edge computing, and design EEAI, a light-weight scheduler to automatically partition DNN computation between mobile devices and edge servers at the granularity of DNN layers. Finally, we verify the effectiveness of the EEAI under different network environments (4G, 5G, and Wi-Fi). Experiments show that the proposed method is effective and has good performance. © 2021 IEEE.

关键词： Deep learning Performance evaluation Energy consumption 5G mobile communication Neural networks Collaboration Computer architecture

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STATE-OF-THE-ART ANALYSIS OF ARTIFICIAL intelligence APPROACHES IN THE MARITIME INDUSTRY

STATE-OF-THE-ART ANALYSIS OF ARTIFICIAL INTELLIGENCE APPROAC...

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international conference on Applied computing 2022 and WWW/Internet 2022

作者： Kontzinos, Christos Kanellou, Ioanna Michalakopoulos, Vasilis Mouzakitis, Spiros Tsapelas, Giannis Kapsalis, Panagiotis Kormpakis, Giorgos Askounis, Dimitris Electrical & Computer Engineering Decision Support Systems Lab National Technical University of Athens Greece Energy Processing Unit National Technical University of Athens Greece School of Electrical and Computer Engineering National Technical University of Athens Greece

ISBN: (纸本)9781713863793

The beginning of 2020 finds Artificial intelligence and big data in the forefront of digital transformation. The maritime industry is embracing them wholeheartedly due to their true potential to meet the ever-increasing and complex traffic and shipping demand for safety, performance, energy efficiency, automation, and environmental impact. The implementation of AI approaches in maritime stems from the need to effectively process and analyse the extremely large amounts of data that are being generated by maritime vessels. The key to addressing these challenges lies in research and innovation, especially in novel algorithms, tools, and platforms within the areas of AI and big data to unlock the new possibilities of a diverse range of current maritime applications. Under this context, the current publication aims at showcasing AI approaches and research initiatives in the maritime industry by performing an indicative landscape analysis of research publications in the aforementioned domains, between the period 2016-2022. The various AI initiatives uncovered from the research are grouped and presented in three representative categories to provide a clear picture of the research effort of integrating AI in maritime processes. Copyright © (2022) by international Association for Development of the Information Society (IADIS). All rights reserved.

关键词： big data

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Online Aesthetic Education Information Teaching System Based On big data Cloud Platform

Online Aesthetic Education Information Teaching System Based...

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2022 IEEE international conference on Knowledge Engineering and Communication Systems, ICKES 2022

作者： Zou, Jing Chen, Yiling School of Packaging Design Art HunanUniversity of Technology Hunan zhuzhou410072 China

ISBN: (纸本)9781665456371

With the continuous in-depth integration and innovation of emerging information technologies represented by big data, cloud computing, artificial intelligence and mobile Internet with higher education, higher education has ushered in unprecedented strategic opportunities in the field of innovating education and teaching methods and building high-quality online teaching resources. Aesthetic education in Colleges and universities undertakes the important task of improving students' aesthetic and humanistic accomplishment and cultivating their aesthetic appreciation, expressiveness and creativity on the basis of specialization. Its teaching reform is also imperative. The big data cloud platform-based online aesthetic education information teaching system is a web-based application that offers online training and instruction for aesthetic education specialist. The system uses the latest technology to easily access various courses, including beauty, massage therapy and other related subjects. In addition, it allows users to create their own courses by uploading content from any source they want. © 2022 IEEE.

关键词： big data

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Recognize Illegal Transactions in the Bitcoin Network Using Graph Attention with DIKW 23

Recognize Illegal Transactions in the Bitcoin Network Using ...

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作者： Zheng, Haixiao Wen, Bin Li, Yuhan School of Information Science and Technology Hainan Normal University Key Laboratory of Data Science and Smart Education of the Ministry of Education of China Haikou China

ISBN: (纸本)9781665494571

Bitcoin has become the choice of many illegal transactions due to its anonymity. To fight crime and maintain the order of the financial market, it is necessary to identify illegal transaction activities in the Bitcoin network. On the basis of referring to the relationship between data, information, and knowledge in the DIKW architecture, this article proposes a new method called MP-GAT to convert discrete data in the Bitcoin network into usable information and knowledge to help identify illegal transactions. MP-GAT uses a combination of multi-layer perceptron and graph attention networks to build a model for identifying illegal transactions. Specifically, the concept of artificial intelligence is used to simulate the human reasoning system and learn from the data. Use the MP-GAT model to convert Bitcoin data into information and knowledge. The method of artificial intelligence is used to complete the transformation of data, information, and knowledge in the DIKW system to achieve the purpose of detecting and identifying illegal transactions in the Bitcoin network. © 2021 IEEE.

关键词： Knowledge engineering Smart cities Bitcoin data models Cognition

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Accelerating big data Application by Eliminating Redundancy on Hadoop Cluster 29

Accelerating Big Data Application by Eliminating Redundancy ...

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29th IEEE international conference on Parallel and Distributed Systems, ICPADS 2023

作者： Lei, Kelun Du, Shaokang You, Xin Xuan, Zhibo Kong, Haoran Yang, Hailong Shang, Jing Xiao, Zhiwen Wu, Zhihui Luan, Zhongzhi Qian, Depei Beihang University School of Computer Science and Engineering Beijing China China Mobile Information Technology Center China

ISBN: (纸本)9798350330717

big data applications are widely adopted to mine valuable information from a tremendous amount of industry data, which is commonly represented as a series of map-reduce operations. Among various map-reduce frameworks, Hadoop is most commonly adopted for data processing at large scale. Although Hadoop eases the development of highly scalable distributed big data applications, inefficient implementation due to poor coding practice and deep software abstractions can cause severe performance issues such as unreasonable slowdown, high response latency, and waste of computing resources, which can lead to unsatisfactory serving delay or significant maintenance cost. In this paper, we first categorize three common types of redundant patterns in big data applications. Then we propose a tool-assisted optimization workflow to detect the redundant patterns automatically, which profiles the application by sampling hardware performance monitoring units. Moreover, we present a profiling visualization method that can help to pinpoint the redundant codes. Based on these approaches, we optimize several big data applications by eliminating redundancies, yielding up to 14.8% performance improvement. © 2023 IEEE.

关键词： Hadoop Performance Optimization Redundant Patterns

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Research on smart city technology system under the background of big data 2

Research on smart city technology system under the backgroun...

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2nd international conference on Internet of Things and Smart City, IoTSC 2022

作者： Ying, Sun Institute of governance Party school of Liaoning provincial Party committee Shenyang110161 China

ISBN: (纸本)9781510654990

Smart city is a developing concept and the product of the development of urban informatization to a certain stage. It is constantly improved with the development of technology, economy and society. With the powerful driving force of new generation information technologies such as big data, cloud computing, Internet of things, geographic information and mobile Internet, develop smart applications and establish a new and sustainable urban development model, so as to outline a blueprint of "smart city" in the future. The construction of intelligent city is a systematic project. The overall planning and design of smart city is to integrate the information elements required for construction objectives, implementation objectives, knowledge system, construction system, technology application and achievement into the overall scheme, which is the construction purpose, objective and implementation strategy of smart city. The overall planning and design of smart city shall ensure the consistency of the overall strategy of urban management and public services with the city, and develop the corresponding business application platform on this basis. Smart city big data analysis platform integrates various government information platforms and smart city application systems based on big data, cloud computing, artificial intelligence, Internet of things and other technologies, eliminates urban information islands, and realizes the interconnection and sharing of government information systems and smart city public data. The platform provides one-stop city level data development, analysis and application platform support, including big data application solutions such as big data storage, computing, security, tools and services. The platform is simple and easy to use. Through XML and web services technology, big data technology, cloud storage technology, UML modelling language, workflow technology, etc., it can quickly realize the in-depth data analysis of city level applications, indu

关键词： big data

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Prototype data System of Highly Reliable Ship Message Queue based on AMQP 8

Prototype Data System of Highly Reliable Ship Message Queue ...

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8th international conference on big data computing and Communications (bigCom)

作者： Jiang, Yongguo Liu, Ketao Huang, Tingting Kang, Ce Yang, Yaqi Ocean Univ China Coll Comp Sci & Teclmol Qingdao Peoples R China

ISBN: (纸本)9781665473842

With the rapid development of artificial intelligence and information fusion technology in the shipbuilding industry, the difficulty and complexity of ship information system (SIS) integration have significantly increased, making it easy to form an information island between shipborne equipment and information platforms. Therefore, the SIS puts forward higher requirements for the real-time, reliability, availability, and expansibility of data communication. By summarizing and analyzing the advantages and disadvantages of SIS communication, as well as the needs of ship information fusion technology. Based on AMQP, this paper provides a unified message model of the queue and flow for data communication between the shipboard information platform and shipboard equipment. The model solves the problems of real-time transmission of ship key hotspot data and stateful data. In addition, this paper designs the storage and message delivery process of the prototype data system and adopts solutions such as distributed redundant storage, double response, and clustering to ensure the reliability and availability of services. The experimental results show that it is very effective to combine the message queue with the SIS to solve the data communication problem between the systems under the ship's heterogeneous platform.

关键词： Ship information system integration AMQP Message-oriented middleware(MOM) Message queuing service

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