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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521-530 订阅

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Digital Campus Financial data Sharing Based on Distributed Reinforcement Learning Algorithm

Digital Campus Financial Data Sharing Based on Distributed R...

引用

2022 international conference on Artificial intelligence and Autonomous Robot Systems, AIARS 2022

作者： Hu, Yuejun Jiangxi Vocational and Technical College of Industry and Trade Nanchang China

ISBN: (数字)9781665454575

ISBN: (纸本)9781665454575

Times are changing rapidly. In recent years, the application of financial data sharing on campus is becoming more and more common. It can not only change the traditional financial management mode, but also bring many advantages such as cost reduction and efficiency increase, risk control and so on. With the strong support of national policies, many emerging technologies have gradually come into the campus. Managers find that big data, cloud computing, artificial intelligence and other technologies can promote the further reform of financial data sharing service center, bring new development opportunities, and make business processes tend to be automated and intelligent. Among many new technologies, big data technology brings the most obvious advantages. Distributed reinforcement learning with reinforcement learning decision-making ability and deep learning awareness, has realized from the input to the output of end-to-end approach to learning, it simulates animal learning process, corrected by the method of testing from the state to the action of mapping strategy, finally learned in various environmental conditions to take the best response behavior, thus improve the intelligent system should be white and robustness. In this paper, the distributed reinforcement learning algorithm is used to effectively solve the data management dilemma brought by the diversification of financial information, help financial personnel to cultivate data analysis ability, and further simplify the business process, improve work efficiency. © 2022 IEEE.

关键词： Deep learning

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Security Authentication Scheme for Power Internet of Things 14

Security Authentication Scheme for Power Internet of Things

引用

14th international conference on Communication Software and Networks (ICCSN)

作者： Dang, Fang Fang Li, Shuai Yan, Li Jing Li, Ding Ding State Grid Henan Informat & Telecommun Co Data Ctr Zhengzhou Henan Peoples R China

ISBN: (纸本)9781665453288

The development of new technologies such as "big data, Cloud computing, The Internet of things, Mobile Internet, artificial intelligence" has also driven the rapid development of the Power Internet of Things. They have broken the barriers of each link of the power system, but also highlighted the security issues of the power Internet of Things terminals and the many shortcomings of the terminal authentication mechanism. In order to solve these problems, this paper proposed a new security authentication scheme for the power Internet of Things. This scheme mainly used hash function and RSA algorithm, Using the terminal's global identity, timestamp, large random number and fuzzy identity to encrypt data transmission, it can effectively resist various attacks, and achieving the integrity and reliability of information transmission.

关键词： Power Internet of Things identity authentication data encryption

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Design and Implementation of Intelligent Senior Care Service Cloud Platform System in the Context of big data 22

Design and Implementation of Intelligent Senior Care Service...

引用

5th international conference on Computer Science and Software Engineering, CSSE 2022

作者： Kong, Weiwei Du, Sijia School of Public Finance and Administration Harbin University of Commerce China

ISBN: (纸本)9781450397780

With the intensification of the aging of China's population, the accompanying problems of aging and sub-replacement fertility have become increasingly prominent, and traditional senior care methods are challenging to meet the increasing demand for senior care service. As a new way of senior care derived from the background of big data, intelligent senior care has expanded a new space for the cause of senior care service in China in the new era and provided a new scientific and practical way to solve the senior care problems. This paper takes big data, the Internet of Things, cloud computing, and other information technologies as the core, designs and evaluates a cloud platform for intelligent senior care service, and builds a five-layer platform architecture of perception layer, application layer, interface layer, and business layer, the processing layer, and the big data layer. Six major systems realize the cloud platform display of intelligent senior care service: call and service system, data and information management system for the elderly, senior care meal assistance service system, sojourn senior care service system, elderly health management system, and volunteer service system. It effectively meets the needs of the elderly in terms of safety care, emergency assistance, healthy life, spiritual care, etc., and realizes the intelligence, informatization, dataization, and convenience of elderly care. © 2022 ACM.

关键词： big data

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A long term impact of artificial intelligence and robotics on higher education

A long term impact of artificial intelligence and robotics o...

引用

2022 IEEE international conference on Advances in computing, Communication and Applied Informatics, ACCAI 2022

作者： Sharma, A.K. Pareta, Avikant Meena, Jitender Sharma, Rupak Modi Institute of Technology Dept. of AI ML Kota India Lovely Professional University Dept. of CSE Jalandhar India Government Women Polytechnic College Dept of CSE Jaipur India SRM Institute of Science Technology Faculty of Science Humanities NCR Campus Delhi NCR Campus Ghaziabad India

ISBN: (纸本)9781665495295

Artificial intelligence and robotics are expected to substantially impact higher education (HE). Due to the fragmented literature and evolving definitions of terminology, it is impossible to determine the extent of its effect. In terms of technical feasibility and educational or societal benefit, these modifications are controversial. To better understand and examine the potential of AI and robotics, imagine what they could look like in the future. A thorough narrative literature review was conducted to identify eight design roles representing AI and robots' potential in education, administration, and research. Higher-order skills training, teacher obligations, and the effect of human agency and datafication are all raised by these concerns. © 2022 IEEE.

关键词： big data

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Cross-System data Integration Based on Rule-Based NLP and Node2Vec 8

Cross-System Data Integration Based on Rule-Based NLP and No...

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8th international conference on data Science in Cyberspace, DSC 2023

作者： Xiao, Jiakai Dut, Wei Xu, Zhengxiang Qian, Yang State Grid Anhui Electric Power Company Department of Internet China School of Management Hefei University of Technology China

ISBN: (纸本)9798350331035

In the era of big data, a growing number of enterprises are paying attention to data governance and data services. Large enterprises (e.g., state grid corporations), have numerous information systems, which have caused issues such as inconsistent data standards, and different data storage methods. This makes it very difficult to share data information among different enterprises and departments. In this situation, enterprises have begin to use various methods to integrate data across different systems. In this study, we select the power industry and design a cross-system data fusion framework. Specifically, there are many types of power grid equipment, and the topology data, equipment data, and operation data associated with them are stored in different ways. For cross-system data, we first use equipment name information and design a ruled-based Natural Language Processing (NLP) technique to match the same data between different systems. However, the equipment names in different systems do not follow a strict and unified naming standard, which leads to a set of equipment nodes that cannot be accurately matched. To solve this issue, we use network structure information about equipment and design a node representation technique based on Node2vec. Based on the node representation, we further optimize the results of equipment matching. For evaluation, we use a cross-system dataset from a state grid corporation in China. Through experiments, we show that the proposed framework performs very well in cross-system data integration. © 2023 IEEE.

关键词： Artificial intelligence computing methodologies computing methodologies data Integration Electricity Industry Graph Embedding Information extraction Learning latent representations Machine learning Machine learning approaches Naturallanguage processing NLP

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A Cooperative Flow Simulator for Distributed computing Based on Full-Dimensional Definable Network 4

A Cooperative Flow Simulator for Distributed Computing Based...

引用

4th international conference on data-Driven Optimization of Complex Systems, DOCS 2022

作者： Liang, Yuan Xiao, Geyang Yao, Shaofeng Wang, Hongsheng Yi, Xiaoyu Tu, Yonggang Intelligent Network Research Institute Zhejiang Lab Hangzhou China Intelligent Computing Institute Zhejiang Lab Hangzhou China Jiaxing Big Data Center Jiaxing Municipal Peoples Government Jiaxing China

ISBN: (数字)9781665459822

ISBN: (纸本)9781665459822

To improve the efficiency of cluster computing, the research of cooperative flow scheduling algorithms provides another idea for further optimization. Cluster computing frameworks such as Spark and Map-Reduce carry running cluster computing tasks and have distinct stage division and dependency characteristics. With limited network resources, the overall completion time of the job can be reduced by minimizing the wait time of the computing phase due to the bottleneck of transmission capacity. The introduction of an artificial intelligence algorithm can provide a solution to this NP-hard problem. The simulator designed in this paper can realize the overall process of cooperative traffic generation, scheduling policy configuration, and scheduling effect feedback closed-loop through packet sender, packet receiver, scheduler, and programmable switch components according to the dependency between cluster computing stages. © 2022 IEEE.

关键词： Cluster computing

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Application Exploration and Practice Research of Management Accounting Under the Background of big data Artificial intelligence 4th

Application Exploration and Practice Research of Management ...

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4th international conference on Innovative computing, IC 2021

作者： Wu, Yanhong Guangdong Ocean University Cunjin College Guangdong Zhanjiang524094 China

ISBN: (纸本)9789811642579

With the continuous development of big data artificial intelligence and the rapid development of Internet technology, people can access a variety of data and information more conveniently, and the world has been connected to form a huge network. With the rapid development of market economy, the decision-making management of enterprises is facing great competition and challenge. In the past, all business activities of enterprises mainly rely on various kinds of information of financial accounting, and the management of enterprises by entrepreneurs has increasingly relied on management accounting, which has gradually entered our vision. In order to study the convenience that management accounting brings to our life under the background of big data artificial intelligence, this paper dissects and analyzes the accounting informatization, accounting artificial intelligence and management accounting. The results show that the utilization rate of big data artificial intelligence management accounting is as high as 75%, which indicates that management accounting under the background of big data artificial intelligence is becoming more and more important. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： big data

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Research on threat modeling for 5G network data analytics function

Research on threat modeling for 5G network data analytics fu...

引用

2022 international conference on Networks, Communications and Information Technology, CNCIT 2022

作者： Wang, Haiyi Lin, Yanfei Li, Weichen China Telecom Research Institute Guangzhou China

ISBN: (数字)9781665452960

ISBN: (纸本)9781665452960

Network data Analytics Function (NWDAF) promotes the rapid development of artificial intelligence and big data technology in the field of 5G communication. In order to analyze the security challenges faced by NWDAF in the open 5G network operating environment, a threat modeling method for NWDAF was proposed in combination with the STRIDE framework. Several mature threat modeling methods and ideas in the industry were firstly introduced;then the attack surface was analysed and a data flow diagram was created for NWDAF, the STRIDE method and the OWASP risk rating idea were used for threat identification and threat rating;finally, the targeted threat mitigation measures and protective means were formulated. © 2022 IEEE.

关键词： data Analytics

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Fast Image matting based on matting pyramids and surrogate models 2

Fast Image matting based on matting pyramids and surrogate m...

引用

2nd international conference on Robotics, Artificial intelligence and Intelligent Control, RAIIC 2023

作者： Liang, Yihui Gou, Hongshan Liu, Guisong Huang, Sibo University of Electronic Science and Technology of China School of Computer Science and Engineering Chengdu China University of Electronic Science and Technology of China Zhongshan Institute School of Computer Zhongshan China Guiyang Institute of Humanities and Technology College of Big Data and Information Engineering Guiyang China Southwestern University of Finance and Economics School of Computing and Artificial Intelligence Chengdu China Huizhou University Network and Information Centre Huizhou China

ISBN: (纸本)9798350328004

Image matting is a foundation task in the field of computer vision. Pixel-pair-optimization-based image matting methods have attracted lots of attention due to their distinct advantages on parallelization and handling spatially disconnected foregrounds. However, these methods struggle when the computing time is limited. To address this issue, this study presents the image matting method based on matting pyramid and surrogate model (IMMPSM). IMMPSM speeds up the process of pixel pair optimization by replaces the evolutionary algorithm in the pyramid matting framework, which consumes a lot of computing time, with the efficient surrogate-model-based method. The constructed surrogate model is reused by the presented surrogate model share strategy to save computing time. Specifically, the constructed surrogate model is shared with the pixel pair optimization subproblem adjacent to current subproblem avoiding repeated computation on the surrogate model construction. Extensive experimental results show that IMMPSM can provide acceptable alpha mattes even under limited computing time. © 2023 IEEE.

关键词： Pixels

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When Federated Learning Meets Vision: An Outlook on Opportunities and Challenges 16th

When Federated Learning Meets Vision: An Outlook on Opportun...

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16th European-Alliance-for-Innovation (EAI) international conference on Body Area Networks (BodyNets)

作者： Khan, Ahsan Raza Zoha, Ahmed Mohjazi, Lina Sajid, Hasan Abbasi, Qammar Imran, Muhammad Ali Univ Glasgow James Watt Sch Engn Glasgow G12 8QQ Lanark Scotland SMME Natl Univ Sci & Technol NUST Dept Robot & Artificial Intelligence Islamabad Pakistan

ISBN: (纸本)9783030955939;9783030955922

The mass adoption of Internet of Things (IoT) devices, and smartphones has given rise to the era of big data and opened up an opportunity to derive data-driven insights. This data deluge drives the need for privacy-aware data computations. In this paper, we highlight the use of an emerging learning paradigm known as federated learning (FL) for vision-aided applications, since it is a privacy preservation mechanism by design. Furthermore, we outline the opportunities, challenges, and future research direction for the FL enabled vision applications.

关键词： Federated Learning Vision analytics Edge computing Decentralized data Internet-of-Things Collaborative AI

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