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2022 International Conference on Artificial Intelligence of Things, ICAIoT 2022

作者： Ashahril, Siti Mahfudzah Isa, Azman Mat Anwar, Norizan College of Computing Informatics and Media School of Information Science Selangor Malaysia

ISBN: (纸本)9798350396768

Many obstacles must be considered when implementing Open Government Data (OGD), which is widely known as one of the open data initiatives by governments around the world. A systematic literature review has been done to recognize and identify challenges that may come along the way such as data privacy, protection & security, low data quality, and inaccuracy of data. 93 articles have been identified and grouped into two categories which are individual level and organizational level. As a result, only 18.28% out of 93 papers, or 17 publications, were ultimately chosen as being appropriate for the analysis step. This literature review's objective is sought to identify the challenges encountered by individuals or organizations that have implemented OGD. © 2022 IEEE.

关键词： Open Data

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Distributed intelligence for IoT-based smart cities: a survey

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Neural computing and Applications 2024年第27期36卷 16621-16656页

作者： Hashem, Ibrahim Abaker Siddiqa, Aisha Alaba, Fadele Ayotunde Bilal, Muhammad Alhashmi, Saadat Mehmood Department of Computer Science College of Computing and Informatics University of Sharjah Sharjah27272 United Arab Emirates School of Computing College of Arts and Sciences Universiti Utara Malaysia Kedah Sintok06010 Malaysia Department of Computer Science Federal College of Education Zaria Kaduna Tudun Wada810282 Nigeria Department of Pharmaceutical Outcomes and Policy University of Florida GainesvilleFL32610 United States Department of Computing and Information Systems School of Engineering and Technology Sunway University Selangor Petaling Jaya47500 Malaysia Department of Information Systems College of Computing and Informatics University of Sharjah Sharjah27272 United Arab Emirates

The remarkable miniaturization of Internet of Things (IoT)-based systems and the rise of distributed intelligence are promising research paradigms in the design of smart cities. IoT and distributed intelligence are conjoined. On the one hand, IoT provides a digital connection to everyday physical devices, and on the other hand, distributed intelligence allows these connected devices to work together in a distributed environment to solve complex problems through learning and reasoning. In this article, we investigate and report the recent premier advances in distributed intelligence for IoT-based smart cities. We use bibliometric techniques which provide essential insights into many studies to evaluate the literature including publication year, type, and citation status on distributed intelligence and its variations published between 2013 and 2023. We categorize and classify literature by devising a taxonomy based on essential parameters, technologies, approaches, applications, and implications with respect to distributed intelligence. Moreover, we provide recent ongoing advancements in distributed intelligence and IoT such as sustainability, blockchain, 5G technologies, AI, edge computing expansion and IoT expansion. We also highlight some of the use cases which include traffic management, energy management, waste management, public safety, and healthcare. We provide core layers and services for implementing distributed intelligence in IoT-based smart cities and present several research challenges and issues. © The Author(s), under exclusive licence to Springer-Verlag London Ltd., part of Springer Nature 2024.

关键词： Smart city

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Content Validity Assessment of Metaverse Characteristics Instrument for High school Teachers' Adoption 10

Content Validity Assessment of Metaverse Characteristics Ins...

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10th International Conference on Smart computing and Communication, ICSCC 2024

作者： Cassandra, Cadelina Masrek, Mohamad Noorman Aman, Fadhilah School of Information Science College of Computing Informatics and Media University Teknologi MARA Selangor Shah Alam Malaysia School of Information Systems Bina Nusantara University Information Systems Department Jakarta11480 Indonesia

ISBN: (纸本)9798350363104

This study's aim is to investigate the content validity of an instrument designed to evaluate the Metaverse characteristic assessment for high school teachers' adoption. The content validity of the instrument was explored based on the perspectives of five experts who were chosen based on their expertise and experiences. The Content Validity use content validity index (I-CVI) and scale content validity index (S-CVI). In the pre-testing process, two contexts were tested: the relevant context and clarity context. In the Relevant context, the mean I-CVI ranged from 0.9 to 1, the S-CVI/UA ranged from 0.5 to 1, and the S-CVI/AVE ranged from 0.9 to 1 for the construct of Interactivity, Persistency and Corporeity, the result shows three items need to be revised. In the Clarity context, the mean I-CVI ranged from 0.95 to 1, the S-CVI/UA ranged from 0.75 to 1, and the S-CVI/AVE ranged from 0.95 to 1 for the construct of Interactivity, Persistency and Corporeity, the result show one items need to be revised. The revised items are also proposed in this study for better instruments. © 2024 IEEE.

关键词： Teaching

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Enabling Knowledge Management Practices in Museums: The Benefits of and Barriers to Achieving Public Value 18th

Enabling Knowledge Management Practices in Museums: The Bene...

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18th International Conference on Information for a Better World: Normality, Virtuality, Physicality, Inclusivity, iConference 2023

作者： Vakharia, Neville Poole, Alex H. Department of Arts and Entertainment Enterprise College of Media Arts and Design Drexel University PhiladelphiaPA19104 United States Department of Information Science College of Computing and Informatics Drexel University PhiladelphiaPA19104 United States

ISBN: (纸本)9783031280313

This qualitative case study explores a new approach to understanding knowledge management in a specific type of information organization: museums. We adapt the broader constructs of knowledge management enablers (KMEs) and a knowledge management orientation (KMO) to study how museums augment their public value through inclusive and equitable community engagement. Semistructured interviews with 45 senior leaders of art and science museums teased out 26 beneficial practices and barriers related to knowledge management enablers and a knowledge management orientation. We found that museums who exhibited these beneficial practices were more successful in creating public value than those who faced barriers in doing so. This critical link between enabling knowledge management practices and public value both opens new research opportunities and suggests practical implications. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Knowledge management

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Towards Predictable Process and Consequence Attributes of Data-Driven Group Work: Primary Analysis for Assisting Teachers with Automatic Group Formation

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Educational Technology and Society 2023年第4期26卷 90-103页

作者： Liang, Changhao Horikoshi, Izumi Majumdar, Rwitajit Flanagan, Brendan Ogata, Hiroaki Graduate School of Informatics Kyoto University Japan Academic Center for Computing and Media Studies Kyoto University Japan Center for Innovative Research and Education in Data Science Kyoto University Japan

Data-driven platforms with rich data and learning analytics applications provide immense opportunities to support collaborative learning such as algorithmic group formation systems based on learning logs. However, teachers can still get overwhelmed since they have to manually set the parameters to create groups and it takes time to understand the meaning of each indicator. Therefore, it is imperative to explore predictive indicators for algorithmic group formation to release teachers from the dilemma with explainable group formation indicators and recommended settings based on group work purposes. Employing learning logs of group work from a reading-based university course, this study examines how learner indicators from different dimensions before the group work connect to the subsequent group work processes and consequences attributes through correlation analysis. Results find that the reading engagement and previous peer ratings can reveal individual achievement of the group work, and a homogeneous grouping strategy based on reading annotations and previous group work experience can predict desirable group performance for this learning context. In addition, it also proposes the potential of automatic group formation with recommended parameter settings that leverage the results of predictive indicators. © (2023). All Rights Reserved.

关键词： Correlation analysis CSCL GLOBE Group formation Group work indicator Group work prediction Teacher assistance

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Chatbots and EFL Learning: A Systematic Review

Chatbots and EFL Learning: A Systematic Review

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2024 Joint of International Conference on Learning Analytics and Knowledge Workshops, LAK-WS 2024

作者： Woollaston, Steve Flanagan, Brendan Ogata, Hiroaki Graduate School of Social Informatics Kyoto University Kyoto Japan Center for Innovative Research and Education in Data Science Kyoto University Japan Academic Center for Computing and Media Studies Kyoto University Kyoto Japan

Chatbots have been increasingly playing a greater role in English as a foreign language education, offering learners the opportunity to practise with a conversational agent at any time and in different contexts. To grasp how this field has developed and identify emerging trends and opportunities, we conducted a systematic bibliometric analysis of research on chatbots in English language learning from 2006 to 2023. The analysis highlights the increasing importance of Large Language Models in language learning, exploring their potential to overcome previous limitations of chatbot technology. The implications of these findings for future research are discussed, particularly the potential for chatbot designs tailored to the specific needs of English language learners. © 2024 CEUR-WS. All rights reserved.

关键词： Speech processing

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Carrying Out CNN Channel Pruning in a White Box

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IEEE Transactions on Neural Networks and Learning Systems 2023年第10期34卷 7946-7955页

作者： Zhang, Yuxin Lin, Mingbao Lin, Chia-Wen Chen, Jie Wu, Yongjian Tian, Yonghong Ji, Rongrong Xiamen University Media Analytics and Computing Laboratory Department of Artificial Intelligence School of Informatics Xiamen361005 China Youtu Laboratory Tencent Shanghai200233 China National Tsing Hua University Department of Electrical Engineering The Institute of Communications Engineering Hsinchu30013 Taiwan Peng Cheng Laboratory Shenzhen518000 China Peking University Department of Computer Science and Technology Beijing100871 China School of Informatics and the Institute of Artificial Intelligence Xiamen University Media Analytics and Computing Laboratory Department of Artificial Intelligence Xiamen361005 China

Channel pruning has been long studied to compress convolutional neural networks (CNNs), which significantly reduces the overall computation. Prior works implement channel pruning in an unexplainable manner, which tends to reduce the final classification errors while failing to consider the internal influence of each channel. In this article, we conduct channel pruning in a white box. Through deep visualization of feature maps activated by different channels, we observe that different channels have a varying contribution to different categories in image classification. Inspired by this, we choose to preserve channels contributing to most categories. Specifically, to model the contribution of each channel to differentiating categories, we develop a class-wise mask for each channel, implemented in a dynamic training manner with respect to the input image's category. On the basis of the learned class-wise mask, we perform a global voting mechanism to remove channels with less category discrimination. Lastly, a fine-tuning process is conducted to recover the performance of the pruned model. To our best knowledge, it is the first time that CNN interpretability theory is considered to guide channel pruning. Extensive experiments on representative image classification tasks demonstrate the superiority of our White-Box over many state-of-the-arts (SOTAs). For instance, on CIFAR-10, it reduces 65.23% floating point operations per seconds (FLOPs) with even 0.62% accuracy improvement for ResNet-110. On ILSVRC-2012, White-Box achieves a 45.6% FLOP reduction with only a small loss of 0.83% in the top-1 accuracy for ResNet-50. Code is available at https://***/zyxxμWhite-Box. © 2012 IEEE.

关键词： Visualization

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Public Interest Research on Digital Learning Content Produced by Artificial Intelligence 7

Public Interest Research on Digital Learning Content Produce...

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7th International Conference on New media Studies, CONmedia 2023

作者： Kurniawan, Yohannes Jordan Ongko, Jastin Gabriel Julianto Anwar, Norizan School of Information Systems Bina Nusantara University Information Systems Department Jakarta11480 Indonesia School of Information Science College of Computing Informatics and Media Universiti Teknologi Mara Shah Alam Malaysia

ISBN: (纸本)9798350307504

The development of Artificial Intelligence (AI) has been extensively applied in education. Especially in Indonesia, there is an urgency to apply AI in education as it improves the quality of education due to poor management of learning systems, human resource deficits, and perverse incentive structures. A poor learning environment can lead to students lacking knowledge and resources. Besides that, the widespread adoption of AI in various fields is inevitable, so students must prepare for future challenges by starting to adopt AI themselves. This research aims to study the use of AI to create digital learning content that supports knowledge, tools, and learning empowerment. The study used a qualitative approach to analyze video learning created using AI tools and collected respondents' assessments through Google Forms. As a result, AI-generated video has a positive effect on student learning, increasing their understanding and providing them with reliable information. Furthermore, this research found that students are excited about using AI in creating digital learning content, as they believe it can help them learn and improve their learning methods. Although digital learning content is not as interactive and engaging as expected, users still believe that with the help of AI, they may improve and create a better learning environment. © 2023 IEEE.

关键词： Learning systems

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Advancing Education Through Metaverse Virtual Reality Simulation 8

Advancing Education Through Metaverse Virtual Reality Simula...

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8th International Conference on Business and Industrial Research, ICBIR 2023

作者： Kurniawan, Yohannes Jayamuni, James Henderson Kwandou, Natasya Anwar, Norizan Bina Nusantara University Information Systems Department School of Information Systems Jakarta11480 Indonesia School of Information Science College of Computing Informatics and Media Universiti Teknologi Mara Shah Alam40450 Malaysia

ISBN: (纸本)9798350399646

Metaverse refers to the next generation of the internet. Through the technology development, it allows users to interact with others by using 3D avatars. Education has been one of the highly compatible metaverse applications. Nowadays, the way of learning has also gradually changed and shifted to online with the collaboration of various tools. By using metaverse in the future, the learning process can be much more elevated with an immersive experience. Therefore, this study aimed to analyze user satisfaction using Mozilla Hub, an online tool that enables users to explore virtual worlds. We gathered the data by conducting a web-based simulation for 20 students to try the experiences and features. From the simulation, we asked some questions related to the experience of using it and analyzed the results by using a descriptive statistical method. The result showed that most participants gave a positive response toward the implementation of the metaverse. However, some improvement is still needed in developing the metaverse to be more optimally used. © 2023 IEEE.

关键词： E-learning

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Bibliometric Analysis of Trend in Metaverse Research 8

Bibliometric Analysis of Trend in Metaverse Research

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8th International Conference on Information Management and Technology, ICIMTech 2023

作者： Cassandra, Cadelina Masrek, Mohamad Noorman Aman, Fadhilah School of Information Systems Bina Nusantara University Information Systems Department Jakarta11480 Indonesia School of Information Science College of Computing Informatics and Media University Teknologi Mara Shah Alam Selangor Malaysia

ISBN: (纸本)9798350326093

Metaverse is currently going to be a popular topic. This study aims to investigate the research trends in metaverse topics to provide a new point of view for future research direction. This study performed a bibliometric analysis systematic literature review by reviewing the specific term in the Scopus database. The data were obtained from publish or perish app and analyzed using the VOSviewer Software. This research article was limited from 2018 - 2022, and 119 were analyzed using the VOSViewer Software. The result shows that the metaverse topic is increasing very fast in 2022. The most popular term in the title and abstract combination are Experience, Study, Application, and Education, which indicates the opportunity for future research, trend, and topic that the public and researchers are interested in. Meanwhile, the keyword of a metaverse in education is still limited, which opens new opportunities to be discussed in the future. © 2023 IEEE.

关键词： Application programs

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