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Application of Multimedia Education System Under Clustering Algorithm in Value Orientation of College Students 2nd

Application of Multimedia Education System Under Clustering ...

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2nd Big data analytics for Cyber-Physical System in smart City, BDCPS 2020

作者： Xinfu, Wang Sichuan International Vocational College Polus International College Chengdu610103 China

ISBN: (纸本)9789813345737

College students are the precious wealth of the country, the builders and successors of the socialist cause. How to guide college students to establish a correct world outlook, outlook on life and values is very important and of great practical significance. In the teaching practice of guiding college students’ value orientation, multimedia technology has been fully utilized, which is the inevitable trend of the development of higher education. The emergence of multimedia teaching has not only changed the study and thinking habits of college students in the past, but also brought new challenges to the value orientation of college students to a certain extent. Therefore, in order to improve the efficiency of College Students’ value orientation education, it is necessary to study the influence of multimedia teaching on Contemporary College Students’ value orientation education from many aspects. Based on this, this paper analyzes the importance of the value orientation education of contemporary college students, discusses the current situation and existing problems of the value orientation education of contemporary college students, and on this basis discusses the specific impact of multimedia teaching on the value orientation education of contemporary college students, in order to provide some beneficial basis for future research. © 2021, The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Students

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Adaptive Online Learning Model Based on Big data

Adaptive Online Learning Model Based on Big Data

引用

international conference on Application of intelligent Systems in Multi-modal Information analytics, MMIA 2020

作者： Lei, Guoping Luo, Xiuying Yang, Sen Xiao, Ke College of Electronics and Information Engineering Chongqing Three Gorges University Wanzhou Chongqing404020 China

ISBN: (纸本)9783030514303

By analyzing the big data model, you can learn more about the learning process of the learners and summarize the learning rules, and then develop personalized learning schemes according to their needs for knowledge and existing abilities. This paper reviews the connotation of the application of big data, points out that the "big" not only means the "large capacity", but also reflects the comprehensiveness of the collected data and the hidden "big value" brought by the analysis. The adaptive online learning analysis model is established based on the big data, which is related to the environment, stakeholders, methods and goals. Taking the learning of C Language Programming as an example, the learners’ learning process, learning process visualization and learning effects, etc. are studied. According to the research results, the collected and analyzed learning behavior and learning knowledge can not only recommend appropriate learning methods and provide reasonable learning resources for learners, but also provide timely feedback on learners’ learning effects. For example, when the learner’s attitude becomes incorrect, they provide personalized intervention services to improve learning efficiency. © 2021, Springer Nature Switzerland AG.

关键词： Big data

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Way Forward to Digital Society – Digital Transformation of Msmes from Industry 4.0 to Industry 5.0

Way Forward to Digital Society – Digital Transformation of ...

引用

international conference on Emerging Research in Electronics, Computer Science and Technology (ICERECT)

作者： Kavita Bhatt S. Mohan Kumar School of Engineering and Technology CMR University Bangalore India

Digital Transformation is a new buzz word in industrial world which transforms the physical world into virtual space. It leverages the implementation of digital technologies to accelerate the growth of the industry/business. It refers to automation, digitalization of process, infrastructure, organization, management with the help of Industry 4.0 technologies like Cloud computing, 5G& 6G, analytics, Big data, Additive manufacturing, Artificial Intelligence, augmented reality, cyber-physical system, smart sensors, IoT Platforms, cloud computing. The field is continuously evolving and shaping the future of Medium, Small and micro industries (MSMEs). Digital Transformation (DX) provides opportunities and possibilities to MSMEs to accelerate their growth via recent disruption in technologies and its attached benefits. The industry is shifting towards virtual work from mechanized systems leveraging benefits of industry 4.0 practices like AI, big data, intelligent network system, machine learning, strong network connection and making effective use of digital transformation. Since end users' requirements and consumption of goods keep increasing product industry 5.0 is gaining much attention which refers to the integration of Artificial Intelligence matching to the level of human capabilities. This paper discusses the evolution of industry 4 and emerging I4.0 technology, major drivers and factors impacting the implementation of I4.0 practices. It also covers the paradigm shift in how next-generation industry is getting shifted with the help of I5.0. It highlights the prospects of the development of technologies that is contributing to the transition of Industry 4.0 to Industry 5.0. This study provides a high-level overview of industry 4.0, its emergences and emerging technologies and transition from Industry 4.0 to Industry 5.0. This paper also highlights the main components of Industry 5.0 and how digital transformation can be moved from machine to human-machine collaborati

关键词： Industries Productivity Cloud computing intelligent networks Computational modeling Transforms Big data

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Short Term Load Forecasting Model of Building Power System with Demand Side Response Based on Big data of Electrical Power

Short Term Load Forecasting Model of Building Power System w...

引用

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

作者： Fang, Xiang Wang, Yi Xia, Lin Yang, Xuan Lai, Yibo State Grid Hangzhou Power Supply Company HangzhouZhejiang310000 China

ISBN: (纸本)9783030627423

With the development of the times, modern people’s life is more and more inseparable from electric energy, which leads to the rapid growth of the pace of power marketization, rapid development at the same time, users’ demand for related service quality is also increasing. Because of all kinds of reasons, the development direction of distribution enterprises is moving towards convenience, safety, flexibility and stability. In the daily management of the building, to ensure the uninterrupted power supply is an important factor affecting the service quality of the building. Whenever there is a power outage, it will cause unpleasant impact and experience to users and tourists, bring fright to employees, and cause unnecessary trouble to daily management. Therefore, this paper introduces the demand side response, which is based on an important interactive mode for the active distribution of power grid. According to the implementation of a series of incentive mechanisms, guide users to actively cooperate with the operation of the distribution network management. In recent years, according to the corresponding measures for energy consumption, adjusting the energy consumption mode can prevent the random fluctuation caused by intermittent renewable energy, distribute the demand side resources on demand, control the distributed power supply more effectively and operate the energy storage equipment more flexibly. According to the analysis and summary of the demand response of the system, this paper discusses the examples of short-term load forecasting and demand side response, which shows that the experiment of load forecasting model in this paper has high accuracy. © 2021, The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： smart power grids

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Reflection on AI: The Cognitive Difference Between Libraries and Scientists 5th

Reflection on AI: The Cognitive Difference Between Libraries...

引用

5th international conference on Cognitive Systems and Signal Processing, ICCSIP 2020

作者： Zou, Xiaohui Wu, Xueqiu Zhang, Baoping Yang, Qiang Li, Jian Sino-American Searle Research Center UC Berkeley Berkeley United States Zhuhai Hengqin Macau Youth Entrepreneur Valley 21C Zhuhai Fudan Innovation Research Institute Room 106 IoT Smart City Innovation Platform Room D623 Building 13 Macau Youth Entrepreneur Valley Talent Apartment Hengqin Zhuhai519000 China Shuangyashan Radio and Television University Shuangyashan Heilongjiang China Shenzhen Zhongzhi Autolink Pansystems IoT Research Institute Shenzhen Guangdong China Sichuan Technology and Business College Chengdu China

ISBN: (纸本)9789811623356

The aim is to make appropriate reflections on artificial intelligence AI through the differences in cognitive systems between intelligent digital libraries and well-trained experts, especially scientists. The method is: first, compare the difference and connection between data structure and knowledge reserve, then compare the difference and connection between query, retrieval or search algorithm path, finally, compare the difference and connection between cognitive computing and cognitive ability. Its characteristics are: data query or search algorithm and logical reasoning or cognitive computing, knowledge graph and cognitive graph are all conducive to the construction of intelligent digital library. The result is: it is found that whether it is based on rules or statistics or a combination of the two cognitive systems, there are limitations in cognitive computing and cognitive ability or intelligence. Its significance lies in: from this we can at least reflect on the theoretical limits of AI and some worthy questions, such as the calculability problem and Turing test problem and the Chinese Room Argument of the intelligent digital library. The problem of isomorphism with the information processing mode of the intelligent digital computer, and why can’t the intelligent digital library become a well-trained expert or even a scientist, and so on are worthy of the philosophy of logic and mind with Cognitive Science. © 2021, Springer Nature Singapore Pte Ltd.

关键词： Cognitive systems

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Pattern Synthesis of MIMO Radar Based on Immune Differential Evolution Algorithm

Pattern Synthesis of MIMO Radar Based on Immune Differential...

引用

2020 international conference on Modeling, Big data analytics and Simulation, MBDAS 2020

作者： Jiang, Ling Jiang, Yi Chen, Guangfu Shi, Guimin Cheng, Qi School of Mathematics and Computer Wuyi University Wuyishan354300 China Key Lab. of Cogn. Computing and Intelligent Information Processing of Fujian Education Institutions Wuyishan354300 China Big Data Development Administration of Anji County Huzhou313000 China

In order to optimize the pattern synthesis of multiple input and multiple output (MIMO) radar, immune mechanism is adopted to overcome the premature risk of differential evolution (DE) algorithm, namely immune differential evolution (IDE). Firstly, the modeling of MIMO radar is introduced by encoding the position of array in the binary. Secondly, the immune mechanism is employed to improve the DE. In IDE, two parameters are self-adapted for the mutation operator by immune mechanism to enhance the convergence ability of DE, including scaling factor and crossover rate. Several experiments are conducted to analysis the performance of IDE. The simulation results show that the IDE with variable parameters can get optimal results in MIMO radar with lower the peak side-lobe level (PSLL) and maintain the diversity with stronger convergence ability and shorter calculation speed. © Published under licence by IOP Publishing Ltd.

关键词： Optimization

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5th international conference on Advanced Machine Learning Technologies and Applications, AMLTA 2020

5th International Conference on Advanced Machine Learning Te...

引用

5th international conference on Advanced Machine Learning Technologies and Applications, AMLTA 2020

ISBN: (纸本)9789811533822

The proceedings contain 67 papers. The special focus in this conference is on Advanced Machine Learning Technologies and Applications. The topics include: Lightweight access control algorithm for internet of things;named-entity recognition for legal documents;visual speech processing and recognition;predictive analytics for cardiovascular disease diagnosis using machine learning techniques;a novel approach for smart-healthcare recommender system;heart disorder prognosis employing knn, ann, id3 and svm;iot-based home security system with wireless communication;implementing internet of things in small businesses of bahrain;the adopting knowledge management proves vital for bahrain’s governmental sector;a comparative study of model-free reinforcement learning approaches;location-aware security system for smart cities using iot;an assessment study of gait biometric recognition using machine learning;a study on risk management practices in online banking in bahrain;deep learning techniques: an overview;a multilayer deep learning framework for auto-content tagging;case-based reasoning (cbr)-based anemia severity detection system (asds) using machine learning algorithm;ecg signal analysis, diagnosis and transmission;the effect of real-time feedback on consumer’s behavior in the energy management sector: empirical study;synchronization control in fractional discrete-time systems with chaotic hidden attractors;video surveillance for the crime detection using features;employment of cryptographic modus operandi based on trigonometric algorithm and resistor color code;experimental and dimensional analysis approach for human energy required in wood chipping process;impact of high-k gate dielectric and work functions variation on electrical characteristics of vesfet;correlating personality traits to different aspects of facebook usage;fractional-order control of a fuel cell–boost converter system.

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Changes in Enterprise Human Resource Management in the Context of Big data

Changes in Enterprise Human Resource Management in the Conte...

引用

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

作者： Wang, Jun Department of Human Resource Management Dalian Neusoft University of Information A7 8 Ruanjianyuan Road DalianLiaoning116023 China

ISBN: (纸本)9783030627423

As big data gradually becomes the focus of all walks of life, its role in enterprise human resource management cannot be ignored. The rapid development of Internet technology has also enabled companies to collect a large amount of data and process it effectively. Based on the background of big data, this article analyzes the changes in the six modules of human resource management, human resource planning, recruitment and allocation, training and development, performance management, salary management, and employee relations. Development provides theoretical guidance. © 2021, The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Big data

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Analysis of the Guiding Effect of Movie and TV Tourism Memes Based on Big data

Analysis of the Guiding Effect of Movie and TV Tourism Memes...

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international conference on Cyber Security Intelligence and analytics (CSIA)

作者： Liu, Yali Zhang, Meiyun Sanya Univ Sanya Hainan Peoples R China

ISBN: (纸本)9783030152352;9783030152345

The most influential information factors in movie and TV plays include tourism scenery, storyline, celebrity stars, folk culture and historical events. In the analysis of typical film and television works by using large data technology, it is found that in many film and television tourism memes, vivid storylines are the most important factors to impress the audience and the tourists. And the landscape meme is also very important, that is, "moving story + beautiful natural scenery" is the most influential factor. At the same time, we should avoid the negative effects caused by ecological damage.

关键词： Big data Tourism meme Guiding effect

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Fog computing for smart Healthcare data analytics: An Urgent Necessity 20

Fog Computing for Smart Healthcare data Analytics: An Urgent...

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3rd international conference on Networking, Information System and Security (NISS)

作者： Khaloufi, Hayat Abouelmehdi, Karim Beni-Hssane, Abederrahim Chouaib Doukkali Univ Dept Comp Sci LAROSERI Lab Fac Sci El Jadida El Jadida Morocco Mohamed First Univ Lab Appl Math & Informat Syst Fac Polydisciplinary Nador Nador Morocco

ISBN: (纸本)9781450376341

The advent of Internet of Things (IoT) technologies in the 21st century has led to exciting achievements. IoT smart medical devices along with wearables are generating and communicating high volume and high-velocity of heterogeneous data. Consequently, services provided by traditional methods such as cloud computing to manage these data become insufficient. Fog computing is seen as being the most effective solution for IoT-based healthcare. The stringy demand of this model was principally driven by a growing need for real-time analysis and low latency. It is apparently envisioned that the medicine field expects to draw enormous interest in combining IoT and fog computing. This in turn, improved the patient treatment, staff satisfaction, and operational efficiency and showed positive influence on all aspects of healthcare. This paper has reviewed fog computing in the context of medical IoT while comparing it with cloud computing and has attempted to present the three-layer architecture of fog-based healthcare system containing: edge, fog and cloud. It has also highlighted challenges facing IoT-driven healthcare in an ever-changing world.

关键词： Fog computing Big data Internet of Things (IoT) smart Healthcare Cloud computing

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