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Ecological and Economic Security Processes Modeling with Cloud-Based Soft computing 14th

Ecological and Economic Security Processes Modeling with Clo...

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14th international conference on Applications of Fuzzy Systems, Soft computing, and Artificial Intelligence Tools, ICAFS 2020

作者： Fedorova, Yana V. Popova, Ludmila K. Sharypova, Tatyana N. Lozina, Ekaterina N. Rostov State University of Economics Rostov-on-Don Russia

ISBN: (纸本)9783030640576

In practice the environmental and economic security is a simple analytics in the form of the ratings such as "the best regions to live" or "investment attractiveness", or vice versa, the regions with the least favorable environment. Thus, both the analysis and research are aimed at revealing weak point of the territorial environmental and economic system functioning. While compiling and analyzing the mathematical models for different economic phenomena and processes, it is necessary to recognize clearly the integral structures and systems that compose them as well as to understand the correlation interconnections of the considered processes and their characteristics. The ecological and economic model presented in the form of a function of the time dependence of the state of an object characterized by vector dynamic quantities is considered in the article. The research of the industrial enterprises in relation of their level of the ecological and economic security based on three states: normal, critical and emergency was conducted. Then on the basis of these data the integral indicator of environmental and economic safety of an industrial enterprise using fuzzy sets was identified. The experts’ quantitative assessments were used as the intermediate data. Based on the resulting data the information system structure was worked out to support the decisions taken in the sphere of the environmental and economic security with a cloud-based database. © 2021, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Soft computing

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Research on Perceived Information Model in Product Design Under Cloud computing

Research on Perceived Information Model in Product Design Un...

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international conference on Machine Learning and Big data analytics for IoT Security and Privacy, SPIoT 2020

作者： Fan, Qiangqiang Hyoung, SungEun College of Arts Northeastern University ShenyangLiaoning110819 China College of Arts South China Agricultural University GuangzhouGuangdong510642 China

ISBN: (纸本)9783030627454

In product design, it is an important ability for modern design to find the intersection of the image that the designer wants to express and the perceptual meaning of the product audience. There have been a lot of research results about the approach method of perceptual design, but there is no saying that which approach method is the standard. As a new approach method, this study puts forward the structural modeling process of sensibility. By introducing a new concept of sensibility, this approach to perceptual design can improve the creativity of analysts and make more use of it by proposing a rational structure. The modeling process of perceptual structure is based on rational and perceptual evaluation. It is a method to improve the accuracy of model construction and to explain perceptual evaluation objectively. © 2021, The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Product design

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An intelligent Agent-Based Industrial IoT Framework for Time-Critical data Stream Processing 1

引用

6th international conference on Mobile, Secure and Programmable Networking, MSPN 2020

作者： Gharbi, Ines Barkaoui, Kamel Samir, Ben Ahmed CEDRIC Conservatoire National des Arts et Métiers Paris France LIPSIC Faculté des Sciences de Tunis Université de Tunis El Manar Tunis Tunisia

ISBN: (数字)9783030675509

ISBN: (纸本)9783030675493

The Industrial Internet of Things (IIoT) intends to speed up digital manufacturing transformation. As a crucial role, Industrial IoT aims to improve the performance and reliability of the processing of massive time-critical data continually generated by heterogeneous smart objects. To resolve these challenges, Industrial IoT incorporates the Fog computing paradigm to support intelligence near the Edge level as an additional alternative to Cloud computing. However, a Fog node allows dealing with only limited data processing, storage, and communications. Indeed, a heavy load processing task requires multiple Fog nodes to achieve its execution and may need an intelligent dynamic pooling of Cloud resources. In this paper, we propose PIAF (A Processing intelligent Agent Running on Fog Infrastructure). An intelligent agent-based IIoT framework that runs on the Fog infrastructure to distribute the processing of time-critical data streams. We outline its several components and their interactions. Then, for this purpose, we model the PIAF framework using the Time Petri Nets modeling. © 2021, Springer Nature Switzerland AG.

关键词： Multi agent systems

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Indicators for smart Cities: Tax Illicit Analysis Through data Mining

Indicators for Smart Cities: Tax Illicit Analysis Through Da...

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international conference on Recent Trends in Machine Learning, IOT, smart Cities and Applications, ICMISC 2020

作者： Silva, Jesús Solano, Darwin Fernández, Claudia Ramos, Lainet Nieto Urdanegui, Rosella Herz, Jeannette Mercado, Alberto Ovallos-Gazabon, David Universidad de la Costa Street 58 #66 BarranquillaAtlántico Colombia Corporación Universitaria Minuto de Dios. UNIMINUTO Barranquilla Colombia Universidad Simón Bolívar Barranquilla Colombia

ISBN: (纸本)9789811572333

The anomalies in the data coexist in the databases and in the non-traditional data that can be accessed and produced by a tax administration, whether these data are of internal or external origin. The analysis of certain anomalies in the data could lead to the discovery of patterns that respond to different causes, being able to evidence these causes certain illicit by taxpayers or acts of corruption when there is the connivance of the taxpayer with the public employee or public official. The purpose of this research is the theoretical development of the causal analysis of certain anomalies of tax data, demonstrating that the data mining methodology contributes to evidence of illicit and corrupt acts, through the application of certain algorithms. © 2021, Springer Nature Singapore Pte Ltd.

关键词： data mining

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AI-Powered Demand Response Mechanisms for Sustainable smart Grids

AI-Powered Demand Response Mechanisms for Sustainable Smart ...

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Electronics and Sustainable Communication Systems (ICESC), 2020 international conference on

作者： R. Santhana Krishnan C. Ashokkumar Ezhil E Nithila N. Soundiraraj P.Stella Rose Malar P. Alice Rani Department of Electronics and Communication Engineering SCAD College of Engineering and Technology Cheranmahadevi India Department of Computing Technologies School of Computing College of Engineering and Technology SRM Institute of Science and Technology Kattankulathur Chennai India Department of Electronics and Communication Engineering Vel Tech Rangarajan Dr.Sagunthala R&D Institute of Science and Technology Chennai India Department of Electronics and Communication Engineering PSNA College of Engineering and Technology Dindigul India Department of Electronics and Communication Engineering JP College of Engineeringology Thenkasi India Department of Tamil Sarah Tucker College Tirunelveli India

ISBN: (数字)9798350379945

ISBN: (纸本)9798350379952

The integration of renewable energy sources into smart grids is a critical strategy for achieving sustainable energy systems. This necessitates effective management of energy resources, demand, and grid operations to fully exploit the potential of renewables while ensuring grid stability and reliability. Demand response (DR) mechanisms play a key role in optimizing energy use and grid stability within smart grids. This research explores the application of artificial intelligence (AI) for developing advanced DR mechanisms. The proposed approach leverages machine learning techniques to analyze energy consumption patterns and predict future demand. This enables the implementation of intelligent DR programs that incentivize consumers to adjust their energy usage during peak demand periods. By optimizing energy consumption in response to grid conditions, AI-powered DR mechanisms can significantly contribute to the integration of renewable energy sources and the creation of a sustainable energy future. The research investigates the design and implementation of these AI-powered DR mechanisms. In the proposed research, Machine learning algorithms are employed to analyze historical energy consumption data and predict future demand with high accuracy. This enables the development of DR programs that are tailored to anticipated grid conditions. Also, AI algorithms continuously monitor grid conditions and dynamically adjust DR incentives in real-time. This ensures that DR programs effectively address fluctuations in energy demand and supply. The research explores methods to incentivize consumer participation in DR programs. This may involve offering rebates or other benefits to consumers who adjust their energy consumption during peak demand periods. The effectiveness of the proposed AI-powered DR mechanisms will be evaluated through extensive simulations. The simulations will compare the performance of the proposed approach with existing DR methods. Key metrics such as forecas

关键词： Renewable energy sources Energy consumption Machine learning algorithms Accuracy Power system stability Prediction algorithms Demand response Stability analysis Real-time systems smart grids

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Learning How Spectator Reactions Affect Popularity on Twitch

Learning How Spectator Reactions Affect Popularity on Twitch

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IEEE international conference on Big data and smart computing (BigComp)

作者： Kim, Jeongmin Park, Kunwoo Song, Hyeonho Park, Jaimie Y. Cha, Meeyoung Hyperconnect Seoul South Korea Qatar Comp Res Inst Doha Qatar Korea Adv Inst Sci & Technol Sch Comp Daejeon South Korea Samsung Elect Mobile Div Seoul South Korea Inst for Basic Sci Korea Data Sci Grp Daejeon South Korea

ISBN: (纸本)9781728160344

Gameplay live streaming has become a highly demanded online entertainment traffic on services like ***. The live chat concurrent with on-air streams allows viewers to talk about the content with each other. This new form of online content carries numerous spectator reactions, including text and emojis, and brings a unique opportunity to predict which video becomes popular in the end. This study presents a prediction model of viewer counts on a newly compiled dataset describing the video popularity of Twitch live streams and chat reactions of spectators. Our analysis demonstrates that the spectator reactions captured from the early-stage of live streams, such as the first 15 minutes out of several hours of content, hold essential markers of the eventual popularity of video streams. We discuss the implications of the findings and future directions.

关键词： Twitch chat analysis User response Live streaming Video popularity prediction Big data analytics

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intelligent Recognition System for High Precision Image Significant Features in Large data Background

Intelligent Recognition System for High Precision Image Sign...

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international conference on Cyber Security Intelligence and analytics (CSIA)

作者： Lu, Kong Jiangxi Modern Polytech Coll Nanchang 330095 Jiangxi Peoples R China

ISBN: (纸本)9783030152352;9783030152345

High precision image pattern recognition technology based on large data background is an important part of computer application technology. With the rapid development of digital image processing technology and pattern recognition technology, image pattern recognition technology has been applied more comprehensively in various fields. This paper briefly introduces image processing technology and its new development trend, focusing on image recognition technology and new development.

关键词： Image features Image intelligent recognition Image processing

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Secure Cognitive Protocols for data Fusion in Transformative computing 23rd

Secure Cognitive Protocols for Data Fusion in Transformative...

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23rd international conference on Network-Based Information Systems, NBiS 2020

作者： Ogiela, Lidia Takizawa, Makoto Ogiela, Urszula Department of Cryptography and Cognitive Informatics Pedagogical University of Krakow Podchorążych 2 Street Kraków30-084 Poland Department of Advanced Sciences Hosei University 3-7-2 Kajino-cho Koganei-shi Tokyo184-8584 Japan Pedagogical University of Krakow Podchorążych 2 Street Kraków30-084 Poland

ISBN: (纸本)9783030578107

Transformative computing is a new computational paradigm, which join communication technologies with sensor devices, and artificial intelligence methods. It allows to acquire sensor signals and evaluate those using different AI technologies towards determining some analytics factors. Application of cognitive systems in such analysis can extend possibilities of semantic analysis and evaluation of signals towards performing semantic evaluation of their meaning. data fusion using cognitive approach can facilitate fast analysis, management, and creation new areas of such systems application in security and management protocols. © 2021, Springer Nature Switzerland AG.

关键词： Semantics

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data Analytical Framework for Internet of Things

Data Analytical Framework for Internet of Things

引用

2020 international conference on Decision Aid Sciences and Application, DASA 2020

作者： Saleem, Tausifa Jan Zahra, Syed Rameem Chishti, Mohammad Ahsan National Institute of Technology Department of Computer Science and Engineering Srinagar India Central University of Kashmir Department of Information Technology India

ISBN: (纸本)9781728196770

Internet of Things (IoT) is characterized by a colossal scale of smart objects that collaborate impeccably with each other through a worldwide network. data obtained from these smart objects can be used to recognize, inspect and manage complicated environments around us, enabling better understanding, intelligent decision-making, and performance optimisation. data analytics plays an incredible part in creating efficient IoT applications. It is used to dig out consequential insights from IoT data and these insights are typically in the form of smart management decisions, trends, and statistics that assist IoT applications in making potent decisions. Hence, exploitation of data analytics in IoT applications provides tremendous benefits including enhanced quality, increased efficiency, automation and better decision-making. This paper provides a knowhow of data analytics in IoT and presents the benefits of data analytics in IoT applications. Moreover, the data analytical frameworks for delay-tolerant and delay-critical applications are also presented. © 2020 IEEE.

关键词： Internet of things

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Research and Guidance on the Use of New Media by Grassland Herdsmen in the Big data Era

Research and Guidance on the Use of New Media by Grassland H...

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international conference on Cyber Security Intelligence and analytics (CSIA)

作者： Cui, Yan Shaanxi Normal Univ Fac Arts Xian Shaanxi Peoples R China Inner Mongolia Univ Nationalities Tongliao Peoples R China

ISBN: (纸本)9783030152352;9783030152345

With the rapid development of economy and technology, new media has been widely promoted in urban and rural areas. The popularity of the Internet and smart phones especially increase the rate of communication among people. The combination of new media and communication technology brings mass communication into a new lane of development. For the northern prairie nomads whose economic development is slightly backward, it is necessary to make a intensive study on how the new media is used, what problems appear in the popularization process, and what impact it has on herdsmen's interpersonal communication, family life and national culture. So as to better understand the situation of the cultural transmission of farmers and herdsmen in grassland area. To formulate corresponding policies and promote the development of grassland national culture.

关键词： Grassland pastoral area New media Internet

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