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A New Approach to Information Literacy in Higher Education in smart Learning Environment

A New Approach to Information Literacy in Higher Education i...

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international conference on Inventive Research in computing Applications (ICIRCA)

作者： B.Anjanee Kumar Rohit Kar K. K. Sunalini Kaneenika Jain Nitin Girdharwal Mohd Asif Shah Department of Electronics and Communication Engineering Dadi Institute of Engineering and Technology Anakapalle Andhra Pradesh India Department of Management St. Claret College Bangalore Karnataka India Department of English Koneru Lakshmaiah Education Foundation Guntur Andhrapradesh India S. S. Jain Subodh Management Institute Jaipur Rajasthan India Faculty of Management Prestige Institute of Management & Research (PIMR) Indore Madhya Pradesh India University School of Business Chandigarh University Gharuan Mohali Punjab India

In light of the current epidemic, it is crucial that children acquire better literary skills. That blended learning is considered as one of the most cutting-edge pedagogical strategies. The goal of blended learning is to develop a new learning environment that combines traditional learning with modern methods like e-learning, analytics, game-based learning, and open educational materials in order to improve learning effectiveness and enrich the learning experience. Meanwhile, the idea of smart learning environment has developed with a number of successful implementations as a significant and usable product of smart environments research. This research aims to show that the notion of mixed learning offers a positive outlook for the incorporation of emotional learning methodologies into the increasingly prevalent smart learning environments. Here, the first smart learning environment-based paradigm for enhancing students' information literacy. The outline the components of the intelligent learning environment for the development of students' information literacy based on reviews of the relevant literature and results from prior studies. Researchers found that blended learning increased students' engagement throughout the learning process, which led to better grades and deeper understanding. In addition, this approach could address the drawbacks of both online and in-person instruction, realize big data recording and representation of pedagogical, instructional, and curricular behavior, fully exploit instructors' potential in their various roles, and accurately reflect students' actual knowledge gain.

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LEXIS Weather and Climate Large-Scale Pilot 14th

LEXIS Weather and Climate Large-Scale Pilot

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14th international conference on Complex, intelligent and Software Intensive Systems (CISIS)

作者： Parodi, Antonio Danovaro, Emanuele Hawkes, James Quintino, Tiago Lagasio, Martina Delogu, Fabio D'Andrea, Mirko Parodi, Andrea Sardo, Biagio Massimo Ajmar, Andrea Mazzoglio, Paola Brocheton, Fabien Ganne, Laurent Garcia-Hernandez, Ruben J. Hachinger, Stephan Hayek, Mohamad Terzo, Olivier Krenek, Jan Martinovic, Jan CIMA Res Fdn Savona Italy ECMWF Reading Berks England ITHACA POLITO Turin Italy NUMTECH Aubiere France ATOS BULL Grenoble France LRZ Garching Germany LINKS Fdn Turin Italy VSB Tech Univ Ostrava IT4Innovat Ostrava Czech Republic

ISBN: (纸本)9783030504540;9783030504533

The LEXIS Weather and Climate Large-scale Pilot will deliver a system for prediction of water-food-energy nexus phenomena and their associated socio-economic impacts. The system will be based on multiple model layers chained together, namely global weather and climate models, high-resolution regional weather models, domain-specific application models (such as hydrological, forest fire risk forecasts), impact models providing information for key decision and policy makers (such as air quality, agriculture crop production, and extreme rainfall detection for flood mapping). This paper will report about the first results of this pilot in terms of serving model output data and products with Cloud and High Performance data analytics (HPDA) environments, on top a Weather Climate data APIs (ECMWF), as well as the porting of models on the LEXIS Infrastructure via different virtualization strategies (virtual machine and containers).

关键词： Hydro-meteorology data assimilation High-performance computing Cloud computing

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SemCom for Metaverse: Challenges, Opportunities and Future Trends

SemCom for Metaverse: Challenges, Opportunities and Future T...

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computing and Information Technology (ICCIT-1441), 2020 international conference on

作者： Saeed Hamood Alsamhi Ammar Hawbani Nabil Mohsen Santosh Kumar Lukasz Porwol Edward Curry Insight Centre for Data Analytics University of Galway Galway Ireland University of Science and Technology of China Heifa China Department of CSE IIIT Naya Raipur Chhattisgarh India

Metaverse is a new paradigm yet to come, gaining popularity in many applications and being developed using a combination of technologies, including Virtual Reality (VR), Augmented Reality (AR), blockchain, and other immersive technologies. One key technology critical to the success of the Metaverse is Semantic Communication (SemCom), which enables efficient and effective communication between humans and intelligent agents. This paper discusses the challenges and opportunities associated with SemCom in the Metaverse and potential future trends. We identify the critical challenges in SemCom, such as context awareness, scalability, and interoperability, and discuss potential solutions to address these challenges. Furthermore, we explore the various opportunities that SemCom can bring to the Metaverse, such as improved user experiences, interactions with virtual assistants, and enhanced data analysis capabilities. Moreover, we examine the emerging trends in SemCom for the Metaverse and highlight some key research directions that will be important in the future.

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Towards Seamless Connectivity: Implementing 6G Communication Technologies In Next-Generation Networks

Towards Seamless Connectivity: Implementing 6G Communication...

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Advancement in Technology (ICONAT), international conference for

作者： K. Kalaiselvi R. Sankar S Supriya G Kaushik Hemanth Swamy M Devika Department of Data Analytics Saveetha College of Liberal Arts and Sciences SIMATS Chennai Tamilnadu India Department of Electrical and Electronics Engineering Chennai Institute of Technology Chennai Tamil Nadu India Department of Computer Science and Engineering Vel Tech Rangarajan Dr. Sagunthala R&D Institute of Science and Technology Chennai Tamil Nadu India Department of Electronics and Communication Engineering MLR Institute of Technology Hyderabad India Senior Software Engineer Motorola Solutions Department of AI& DS Dhanalakshmi College of Engineering Chennai Tamil Nadu India

ISBN: (数字)9798350354171

ISBN: (纸本)9798350354188

Advanced wireless networks are essential given the increase in demand for smart services enabled by the Internet of Everything (IoE). Despite the fact that 5G networks could enable Internet of Everything (IoE)-based services, they can’t meet all of the requirements needed to create intelligent applications. In order to overcome the shortcomings of the current infrastructure, there is an increasing demand to investigate the potential of 6G wireless communication technologies. Complex network optimization problems can be resolved by integrating artificial intelligence into sixth generation networks. An increasing user base and support for large-scale data-driven applications are essential given the fast evolving 6G landscape. In addition to highlighting network needs, critical supporting technologies, and a comparison of 5G and 6G networks, this study looks at recent advancements and trends in 6G technology. The report also explores new approaches to 6G connectivity, such as edge computing, backscatter communications, AI-driven IoT networks, and holographic beamforming, all of which are meant to support intelligent communities. In order to achieve the goal of 6Gbased IoT networks, it concludes by outlining potential research avenues.

关键词： 6G mobile communication 5G mobile communication Wireless networks Complex networks Market research Communications technology Internet of Things Optimization Next generation networking Edge computing

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Visual analytics methods for eye tracking data

Visual analytics methods for eye tracking data

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international KES conference on Human Centred intelligent Systems, KES-HCIS 2020

作者： Quadar, Nordine Chehri, Abdellah Geon, Gwanggil School of Electrical Engineering and Computer Science University of Ottawa OttawaONK1N 6N5 Canada Department of Applied Sciences University of Québec in Chicoutimi ChicoutimiQCG7H 2B1 Canada Department Embedded Systems Engineering Incheon National University Incheon Korea Republic of

ISBN: (纸本)9789811557835

Nowadays, eye tracking data have become important and valuable information that help to understand the behavior of users. The gathering of these data is not an issue anymore. However, the problem is the analysis process and especially how can these raw data be converted to understandable and useful information. Visual analytics can solve this issue by combining human analytics skills and the advanced computer analytics. This leads to the novel discoveries and helps humans take control of the analytical process. These visualizations can be used to solve difficult problems by discovering new unknown patterns of available data. In this work, we discussed different methods that are used in the case of eye tracking data, and we addressed the challenges of visual analytics in this context. © The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2020.

关键词： Big data

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Research on Key Technologies of Cloud-Side Collaboration for Urban Rail intelligent Security 5th

Research on Key Technologies of Cloud-Side Collaboration for...

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5th international conference on Electrical Engineering and Information Technologies for Rail Transportation, EITRT 2021

作者： Zhou, Chao Du, Chengxin Wang, Zhifei Meng, Yukun Han, Peiyao Institute of Computing Technology China Academy of Railway Sciences Corporation Limited Beijing100081 China National Engineering Laboratory of Rail Transit System Testing China Academy of Railway Sciences Corporation Limited Beijing100081 China

ISBN: (纸本)9789811699122

smart subway is an important part of the comprehensive, green, safe and intelligent three-dimensional modern urban transportation system, Among them, The Urban Rail intelligent Security has become an important guarantee for subway safety. Aiming at the problems of scattered security system construction, delayed data transmission and low intellectualization, this paper explores a kind of urban rail security system architecture under the cooperation of computing center and edge equipment. The video surveillance system is taken as a typical research object to carry out the research on cloud edge collaboration technology. Based on resource virtualization technology, this architecture uses multi-source data fusion and double-stream convolution algorithm to identify abnormal behaviors, and an effective cloud edge resource allocation mechanism is established by combining two-way auction algorithm. Furthermore, a video surveillance system based on cloud edge collaboration is built, and the relevant functions are tested experimentally. The results show that the video surveillance system based on cloud edge collaboration theory can intelligently identify various application scenarios of rail transit, reduce the pressure of station security and improve the level of station operation and management. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Security systems

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Research on Enterprise data Governance Based on Knowledge Map

Research on Enterprise Data Governance Based on Knowledge Ma...

引用

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

作者： Qi, Xiaoying School of Management Hebei University Baoding071002 China

ISBN: (纸本)9783030627454

data governance is a system integrating data management, improvement of data quality and data application and the whole process is a closed-loop procedure that is mutually associated, mutually promoted and improved, which serves as a solution to problems ignorance of data, uncontrollable of data and invalid data. With the development and application of big data, data governance plays an important role in improving utilization of enterprise data, enhancing enterprise performance and competitiveness. Based on the literature on corporate data governance, this paper analyzes the status quo, hot topics and research frontiers of corporate data governance at home and abroad based on the knowledge map. It is found that research objects of corporate data governance mainly focus on multinational enterprises, family enterprises, high-tech enterprises and smart cities. The research is conducted with focuses on data warehouse, data governance framework, methods, models and risk management. The future research of enterprise data governance is mainly on determining the scope of master data objects and metadata management. © 2021, The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： data warehouses

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intelligent Communication for Internet of Things (IoRT) 5th

Intelligent Communication for Internet of Things (IoRT)

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5th international conference on Recent Innovations in computing , ICRIC 2022

作者： Bhat, Kaleem Ullah Kumar, Neerendra Koul, Neha Verma, Chaman Enescu, Florentina Magda Raboaca, Maria Simona Department of Computer Science and IT Central University of Jammu Jammu & Kashmir Jammu India Department of Media and Educational Informatics Faculty of Informatics Eötvös Loránd University Budapest Hungary Department of Electronics Communications and Computers University of Pitesti Pitești Romania National Research and Development Institute for Cryogenic and Isotopic Technologies-ICSI Rm. Valcea Romania

ISBN: (纸本)9789819906000

To enable Machine-to-Machine (M2M) communication and data transmission using fundamental network protocols like TCP/IP, the Internet of Things (IoT) provides a sturdy framework for attaching things to the internet. Its cutting-edge technology is having an impact on numerous fields of study and development of smart solutions. IoRT is the integration of diverse technologies which encompasses cloud computing, machine learning, artificial intelligence, and Internet of Things (IoT). With so many devices and so few resources, security issues like device authorization and authentication and maintaining the integrity and privacy of data arise. IoT was forced to apply conventional security techniques because of a variety of new circumstances, including restricted computational power, RAM size, ROM size, register width, different operating environments, and others. The consequences of the several cryptanalyses performed on these ciphers by various cryptanalysts are also examined in this study. This paper provides background information on lightweight block ciphers in order to protect transmitted data within the network. For more secure communication, we have also implemented the PRESENT block cipher due to its lightweight behavior. A future dimension is also proposed to develop a good lightweight cipher. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Cryptography

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Special Session: Approximate TinyML Systems: Full System Approximations for Extreme Energy-Efficiency in intelligent Edge Devices 39

Special Session: <i>Approximate TinyML Systems</i>: Full Sys...

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39th IEEE international conference on Computer Design ICCD)

作者： Raha, Arnab Ghosh, Soumendu Mohapatra, Debabrata Mathaikutty, Deepak A. Sung, Raymond Brick, Cormac Raghunathan, Vijay Intel Corp Edge AI Adv Architecture Grp VPU IP Santa Clara CA 95051 USA Purdue Univ Elmore Family Sch Elect & Comp Engn W Lafayette IN 47907 USA

ISBN: (纸本)9781665432191

Approximate computing (AxC) has advanced from being an emerging design paradigm to becoming one of the most popular and effective methods of energy optimization for applications in the domains of computer vision, image/video processing, data mining, analytics, and search. The simultaneous rise of artificial intelligence (AI) has provided an additional thrust to the adoption of various AxC techniques in intelligent edge platforms where energy-efficiency is not only desirable but necessary. In spite of the big rise in interest for AxC, the adoption of approximate hardware has mostly been limited to only one component of the system (usually the processing subsystem) which often contributes only a fraction of the overall system-level power. A full system approach to AxC enables us to extend approximations to other subsystems, such as the memory, sensor, and communications subsystems. This paper presents the foundational concepts of an approximate TinyML system that applies approximations synergistically to multiple subsystems in an edge inference device. These approximations are applied intelligently to significantly reduce energy while incurring a negligible loss in application-level quality. We demonstrate multiple versions of an approximate smart camera system that can execute state-of-the-art deep neural networks (DNNs) while consuming only a fraction of the total energy in a typical system.

关键词： Deep Learning Computer Vision TinyML Edge AI Approximate computing Approximate System

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Lean 4.0, Six Sigma-Big data Toward Future Industrial Opportunities and Challenges: A Literature Review 1st

Lean 4.0, Six Sigma-Big Data Toward Future Industrial Opport...

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1st international conference of Advanced computing and Informatics, ICACIN 2020

作者： Rifqi, Hanane Zamma, Abdellah Ben Souda, Souad SSDIA Laboratory ENSETM Hassan II University Casablanca Morocco

ISBN: (纸本)9789811560477

Industry 4.0 technologies are generating a huge amount of data more than ever before. Heterogeneous and voluminous data puts a project's decision makers at risk of making poor decisions. For a Lean Six Sigma methodology that uses traditional statistical tools such as Analysis of Variance (ANOVA), design of experiments, etc., we found a risk to carry out both the right data collection and data processing. In our article, we discuss the advantage of Big data analytics for good Lean Six Sigma project processing and show its benefits for the methodology and also on all elements of the supply chain. © 2021, The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： data analytics

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