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7th International Conference on New Media Studies, CONMEDIA 2023

作者： Fernando, Erick Hidayat, Desman Pengaribuan, Christian Haposan Prabowo, Yulius Denny Universitas Multimedia Nusantara Faculty of Engineering and Informatics Department of Information System Tangerang Indonesia Bina Nusantara University Binus Entrepreneurship Center Management Department Jakarta11480 Indonesia Sampoerna University Management Study Program Faculty of Business Jakarta12780 Indonesia Bina Nusantara University Binus Online Learning Computer Science Department Jakarta11480 Indonesia

ISBN: (纸本)9798350307504

Along with technological improvements, online shopping is currently developing quickly. Online shops started by selling electronics, clothing, food, and home appliances and continue to evolve, selling various things. Currently, digital marketing has a novel technique, namely live shopping, where sellers can present, promote and offer their products directly through live streaming on social media and e-commerce platforms. This research will focus on gaining insight into the factors influencing customers to watch and purchase through live streaming. This research is an early-stage study of exploring and searching for research models. The study used a literature review approach by reviewing similar previous research articles. Several variable components were used in this study. The findings of the factors include visibility capacity, meta-vocation capacity, purchase orientation capacity, social presence, price, perceived product quality, perceived enjoyment, purchase orientation, perceived usefulness, and intention to buy. These factors were tested and proved to be valid with Cronbach's Alpha value being more than 0.5 and reliable with the value of the loading factor a greater than 0.6. Criteria The factors of the findings for further analysis of the relationship between factors and other variables. © 2023 IEEE.

关键词： Domestic appliances

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A model of service-oriented architecture of e-certification system to support boat registration and site visit inspection to support maritime safety and crew health inspection

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Marine systems and Ocean technology 2023年第1-2期18卷 45-63页

作者： Saputra, Diaz Gaol, Ford Lumban Abdurachman, Edi Sensuse, Dana Indra Matsuo, Tokuro Department of Computer Science BINUS Graduate Program - Doctor of Computer Science Bina Nusantara University Jakarta11480 Indonesia Department of Computer Science Binus Graduate Program - Master in Information System Bina Nusantara University Jakarta11480 Indonesia Department of Research in Management Bina Nusantara University Jakarta Indonesia Faculty of Computer Science University of Indonesia Jakarta Indonesia Advanced Institute of Industrial Technology Tokyo Japan City University of Macau China Asia University Taichung Taiwan

This article describes the architecture of software services that provide registration of small boat data to build maritime safety. The proposed system architecture which so-called SIMKAPEL aims to support small boat registration for maritime safety. It is developed from a conventional service-oriented architecture (SOA) with an open standard for data interoperability between elements. The goal of this research is to implement and evaluate the proposed architecture to support small boat registration and e-certification. Several parts of the architecture have been implemented as a platform that provides core services and data sources to be used by Ministry of Transportation, Directorate General of Sea Transportation, and other government agencies. Finally, the proposed SIMKAPEL platform with the SOA architecture is evaluated for its benefits to users through the expert opinion survey to measure its efficiency. The analysis results showed that SOA-based SIMKAPEL is feasible to use as a boat e-certification system. Furthermore, experiment results provide three parameters (e.g., maritime safety, namely, cargo/passengers, boat safety facilities, and maritime safety systems) with efficiency values of 42%, 46%, and 42%, respectively. The parameter with the highest efficiency shows a big effect on the level of safety of the boat and passengers. Thus, the parameters that need to be prioritized and need boat owners’ attention are cargo/passenger, boat safety equipment, and maritime safety system. © 2023, The Author(s).

关键词： Boat e-certification Boat online certification Cloud-based service Integrated system SOA architecture

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Factors Influencing the Acceptance of Collaboration Platform for Fleet Maintenance

Factors Influencing the Acceptance of Collaboration Platform...

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technology Innovation management and engineering Science International Conference (TIMES-iCON)

作者： Prush Sa-nga-ngam Kittichai Athikulrat Werachart Muttitanon Technology of Information System Management Division Faculty of Engineering Mahidol University Nakhon Pathom Thailand Department of Materials Handling and Logistics Engineering Faculty of Engineering King Mongkut's University of Technology North Bangkok Bangkok Thailand Faculty of Business Administration and Information Technology Rajamangala University of Technology Tawan-ok Bangkok Thailand

ISBN: (数字)9798350362602

ISBN: (纸本)9798350362619

Maintenance management plays a crucial role in the cost dimension of transportation company. Repair and maintenance expenses constitute a significant portion of overall manageable costs and directly impact the revenue generation of these businesses. Effective maintenance manage management is therefore essential for transportation companies to ensure the constant readiness of their vehicles for transportation tasks. This research aimed to study the factors that influence the acceptance of collaborative fleet maintenance platform by conducting a comprehensive in-depth interview with 3 groups 1. Transportation company with in-house fleet maintenance units and nationwide transport services 2. Transportation company without in-house fleet maintenance units and nationwide transport services and 3. Truck repair and maintenance service providers which 20 business per groups. Data was collected through semi-structured interviews. The interviews were transcribed verbatim. Data analysis employed thematic analysis, a qualitative data analysis method that identifies patterns and themes within the collected data. The research results demonstrated the factors that influence the acceptance of collaboration platforms for fleet maintenance are price format, data and information, ease of use and perceived usefulness.

关键词： Data analysis Costs Collaboration Transportation Companies Predictive models Maintenance

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Ideation of engineering Solutions for Sustainable Development Goals: A Collaborative Course Between Thai and Japanese Students 38

Ideation of Engineering Solutions for Sustainable Developmen...

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38th IEEE Region 10 Conference, TENCON 2023

作者： Krutphong, Kodchakorn Leelawat, Natt Tang, Jing Ota, Eri Suzuki, Rie Murakami Taoka, Yuki Punyabukkana, Proadpran Environmental Engineering and Disaster Management Program Mahidol University Thailand Department of Industrial Engineering Faculty of Engineering Chulalongkorn University Thailand Disaster and Risk Management Information Systems Research Unit Chulalongkorn University Thailand International School of Engineering Chulalongkorn University Thailand Center for International Education Tokyo Institute of Technology Japan School of Environmet and Society Tokyo Institute of Technology Japan Department of Computer Engineering Faculty of Engineering Chulalongkorn University Thailand The Learning Innovation Center Chulalongkorn University Thailand

ISBN: (纸本)9798350302196

A collaborative course called Global Awareness for technology Implementation was conducted by the faculty of engineering, Chulalongkorn University, Thailand, and the Tokyo Institute of technology, Japan. The objective of this course was to facilitate the exchange of knowledge, perspectives, and experiences between Thai and Japanese students through project work, using an engineering design approach and the design thinking process to create innovation relevant to the Sustainable Development Goals (SDGs). During the class, experts shared their knowledge and experiences with the students. The students then worked on their respective projects to develop solution concepts using the design thinking process. The proposed ideas include the application for English class, smart water quality checker, hydrogen-based energy system for rural area, reduced wasted fashion solution, and auto waste sorting machine. Finally, this study concluded with a summary of the results and findings on the empathy process in the chosen SDGs, and of the commonalities and differences between Thailand and Japan in terms of ideation. © 2023 IEEE.

关键词： Students

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Two-Stage Robust Optimization Under Decision Dependent Uncertainty

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IEEE/CAA Journal of Automatica Sinica 2022年第7期9卷 1295-1306页

作者： Yunfan Zhang Feng Liu Yifan Su Yue Chen Zhaojian Wang João P.S.Catalão State Key Laboratory of Power System and Generation Equipment the Department of Electrical EngineeringTsinghua UniversityBeijing 100084China Department of Mechanical and Automation Engineering the Chinese University of Hong KongHong Kong SARChina Ministry of Education Key Laboratory of System Control and Information Processing the Department of AutomationShanghai Jiao Tong Universityand also with Shanghai Engineering Research Center of Intelligent Control and ManagementShanghai 200240China Faculty of Engineering of the University of Porto and Institute for Systems and Computer Engineering Technology and Science(INESC TEC)Porto 4200-465Portugal IEEE

In the conventional robust optimization(RO)context,the uncertainty is regarded as residing in a predetermined and fixed uncertainty *** many applications,however,uncertainties are affected by decisions,making the current RO framework *** paper investigates a class of two-stage RO problems that involve decision-dependent *** introduce a class of polyhedral uncertainty sets whose right-hand-side vector has a dependency on the here-and-now decisions and seek to derive the exact optimal wait-and-see decisions for the second-stage problem.A novel iterative algorithm based on the Benders dual decomposition is proposed where advanced optimality cuts and feasibility cuts are designed to incorporate the uncertainty-decision *** computational tractability,robust feasibility and optimality,and convergence performance of the proposed algorithm are guaranteed with theoretical *** motivating application examples that feature the decision-dependent uncertainties are ***,the proposed solution methodology is verified by conducting case studies on the pre-disaster highway investment problem.

关键词： Benders decomposition decision-dependent uncertainty endogenous uncertainty robust optimization(RO)

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Machine Learning Stroke Prediction in Smart Healthcare:Integrating Fuzzy K-Nearest Neighbor and Artificial Neural Networks with Feature Selection Techniques

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Computers, Materials & Continua 2025年第3期82卷 5115-5134页

作者： Abdul Ahad Ira Puspitasari Jiangbin Zheng Shamsher Ullah Farhan Ullah Sheikh Tahir Bakhsh Ivan Miguel Pires Department Information System Study Program Faculty of Science and TechnologyUniversitas AirlanggaSurabaya60286Indonesia School of Software Northwestern Polytechnical UniversityXi’an710072China Research Center for Quantum Engineering Design Faculty of Science and TechnologyUniversitas AirlanggaSurabaya60286Indonesia School of Computer Science and Software Engineering Shenzhen UniversityShenzhen518061China Cybersecurity Center Prince Mohammad Bin Fahd University617Al JawharahKhobarDhahran34754Saudi Arabia Cardiff School of Technologies Cardiff Metropolitan UniversityWestern AvenueCardiffCF52YBUK Instituto de Telecomunicacoes Escola Superior de Tecnologia e Gestao de AguedaUniversidade de Aveiroágueda3750-127Portugal

This research explores the use of Fuzzy K-Nearest Neighbor(F-KNN)and Artificial Neural Networks(ANN)for predicting heart stroke incidents,focusing on the impact of feature selection methods,specifically Chi-Square and Best First Search(BFS).The study demonstrates that BFS significantly enhances the performance of both *** BFS preprocessing,the ANN model achieved an impressive accuracy of 97.5%,precision and recall of 97.5%,and an Receiver Operating Characteristics(ROC)area of 97.9%,outperforming the Chi-Square-based ANN,which recorded an accuracy of 91.4%.Similarly,the F-KNN model with BFS achieved an accuracy of 96.3%,precision and recall of 96.3%,and a Receiver Operating Characteristics(ROC)area of 96.2%,surpassing the performance of the Chi-Square F-KNN model,which showed an accuracy of 95%.These results highlight that BFS improves the ability to select the most relevant features,contributing to more reliable and accurate stroke *** findings underscore the importance of using advanced feature selection methods like BFS to enhance the performance of machine learning models in healthcare applications,leading to better stroke risk management and improved patient outcomes.

关键词： Fuzzy K-nearest neighbor artificial neural network accuracy precision recall F-measure Chi-Square best search first heart stroke

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Leaf Disease image classification method based on improved convolutional neural network

Leaf Disease image classification method based on improved c...

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2022 IEEE International Conference on Industry 4.0, Artificial Intelligence, and Communications technology, IAICT 2022

作者： Wenxuan, Wei Qianshu, Wang Chaofan, Hao Xizhe, Sun Ruiming, Bao Toe, Teoh Teik Beijing University of Chemical Technology Information Management and Information System Beijing China Cyber Security Harbin Institute of Technology Weihai China Beijing University of Technology Faculty of Information Technology Beijing China Sichuan University Faculty of Engineering Mechanic Chengdu China Shanghai Polytechnic University School of Resources and Environmental Engineering Shanghai China Nanyang Technological University NTU Business AI Lab Singapore

ISBN: (数字)9781665451260

ISBN: (纸本)9781665451260

This paper attempts to apply neural networks to classify maize disease images. The classification model is based on thousands of images of actual maize diseased leaves, which are relatively belonging to maize leaf blight leaves, corn rusty leaves, corn gray spot disease leaves, and corn healthy leaves. Classification neural networks are a popular machine learning method that will serve as an adjunct to help diagnose whether corn leaves are diseased. This article analyzes and contains details of the algorithms we use. This article demonstrates our proposed VGG-16-based neural network model. The average recognition rate of the final model is 94.64%. © 2022 IEEE.

关键词： Image classification

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A preliminary model analysis of knowledge management design: spiritual leadership on knowledge worker productivity

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technology Analysis and Strategic management 2023年第3期35卷 270-285页

作者： Ratna, Silvia Saide, Saide Herzavina, Herzavina Muwardi, Didi Faculty of Information Technology Department of Informatics Engineering and Department of Information System Universitas Islam Kalimantan Muhammad Arsyad Al Banjari Banjarmasin (UNISKA MAB) South Kalimantan Indonesia Department of Information System Faculty of Science and Technology State Islamic University of Sultan Syarif Kasim Riau (Universitas Islam Negeri Sultan Syarif Kasim Riau - UIN SUSKA Riau) Riau Indonesia EnReach (Energy Research Center) UIN SUSKA Riau Riau Indonesia PRO-Knowledge Research Group Tanjung Baru Pekanbaru Indonesia Department of Information Management National Taiwan University of Science and Technology Taipei Taiwan Department of Agribusiness Universitas Riau Riau Indonesia

The productivity of worker is crucial not only for company performance but also for sustainable development. In the context of knowledge-economy firms, leadership issues and knowledge resources capabilities are likely to enhance knowledge worker productivity. The purpose of this study is to design a preliminary conceptual analysis of spiritual leadership and knowledge explorative-exploitative on knowledge worker productivity. This study adopts a systematic literature review (SLR) through searching, analysing, and selecting research studies comprising a total of 1355 research papers. The literature was searched in digital scientific libraries and big indexing systems such as Web of Science and Scopus. This research essentially contributes to providing a conceptual/theoretical model of effective knowledge explorative-exploitative in the context of knowledge workers productivity. Several enabler factors such as spiritual leadership (vision, hope/faith, altruistic), knowledge explorative (socialization and internalization), knowledge exploitative (combination and externalization), and knowledge worker productivity (job outcome, problem-solving, work scheduling) were explored and explained. The research provides beneficial knowledge and strategy for managers/leaders on ways to initiate and develop a knowledge-sharing strategy to enhance employee’s effectiveness through pursuing and maximizing leadership contributions. Multifarious constructs and theories are combined. This model further offers a new paradigm for upcoming research. © 2021 Informa UK Limited, trading as Taylor & Francis Group.

关键词： knowledge explorative-exploitative Knowledge management spiritual leadership workers productivity

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Robust Tweets Classification Using Arithmetic Optimization with Deep Learning for Sustainable Urban Living

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SN Computer Science 2024年第5期5卷 549页

作者： Hamza, Manar Ahmed Hashim, Aisha Hassan Abdalla Motwakel, Abdelwahed Elhameed, Elmouez Samir Abd Osman, Mohammed Kumar, Arun Singla, Chinu Munjal, Muskaan Department of Electrical and Computer Engineering International Islamic University Malaysia Kuala Lumpur 53100 Malaysia Department of Computer and Self Development Preparatory Year Deanship Prince Sattam bin Abdulaziz University AlKharj Saudi Arabia Department of Management Information Systems College of Business Administration in Hawtat bani Tamim Prince Sattam bin Abdulaziz University AlKharj Saudi Arabia Department of Computer Science College of Post-Graduated Studies University of Science and Technology Omdurman Sudan Department of Information System Faculty of Computer Science and Information Technology Omdurman Islamic University Omdurman Sudan Department of Electronics and Communication Engineering New Horizon College of engineering Bengaluru India Computer Engineering Thapar Institute of Engineering and Technology Punjab Patiala India

Natural Language Processing (NLP) with Deep Learning (DL) for Tweets Classification includes use of advanced neural network designs to analyse and classify Twitter messages. DL techniques like recurrent neural network (RNN) or transformer-based frameworks like BERT are used to mechanically learn difficult linguistic patterns and contextual info from tweet data. These techniques able to capture subtleties of language with sarcasm, sentiment, and context-specific meanings and making them suitable for tasks like sentiment analysis or topic classification in realm of social media. Leveraging deep symbols learned from great amounts of textual data, these NLP techniques permit precise and nuanced classification of tweets, donating to enhanced information retrieval, sentiment tracking, and trend analysis in dynamic and fast-paced world of social media communication. In this view, this research develops an arithmetic optimization algorithm with deep learning based tweets classification (AOADL-TC) approach for sustainable living. The goal of the AOADL-TC technique is to identify and discriminate different kinds of sentiments that exist in the tweet data. At the initial stage, the AOADL-TC model pre-processes tweet data to convert uniform data into a useful format. For sentiment detection, the AOADL-TC technique applies a parallel bidirectional gated recurrent unit (BiGRU) model. At last, tuning of parameters related to parallel BiGRU model performed by AOA. An wide set of tests carried out to illustrate better performance of AOADL-TC model. The experimental outcomes portrayed that AOADL-TC technique demonstrates the supremacy of the AOADL-TC technique in terms of different evaluation metrics. © The Author(s), under exclusive licence to Springer Nature Singapore Pte Ltd. 2024.

关键词： Deep learning Machine learning Natural language processing Sentiment analysis Social media

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Introduction of information Security Fatigue Scale for Teleworking and its Effectiveness

Introduction of Information Security Fatigue Scale for Telew...

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Big Data, Cloud Computing, Data Science & engineering (BCD)

作者： Hiroki Koyama Shigeaki Tanimoto Atsushi Shimoda Seiko Taki Atsushi Kanai Faculty of Social System Science Chiba Institute of Technology Chiba Japan Faculty of Management and Information Studies Japan International University Ibaraki Japan Faculty of Information and Transformation Science Chiba Institute of Technology Chiba Japan Faculty of Science and Engineering Hosei University Tokyo Japan

ISBN: (数字)9798350394191

ISBN: (纸本)9798350394207

In recent years, government-led “work style reform” has been promoted, and the teleworking style of work has been attracting attention. In particular, the spread of COVID-19 infection in 2020 has led to the rapid spread of telework. The spread of teleworking has led to a shift to paperless and web conferencing, and the risk of information security has increased due to the location-independent work style. In particular, unlike the face-to-face environment of an office, the telework environment poses psychological risks such as loneliness due to lack of communication. This paper clarifies information security fatigue in a telework environment based on previous research on security fatigue in a face-to-face environment that also considers such psychological aspects, and proposes countermeasures against it. First, we designed a questionnaire that took into account the telework environment based on the questionnaire survey of a previous study, and conducted a questionnaire survey using a web-based questionnaire. Considering the impact of COVID-19, a questionnaire survey was conducted twice, once in December 2020 at the early stage of COVID-19 expansion and once in January 2023 after COVID-19 establishment, both times targeting approximately 500 Japanese teleworkers. The results of these surveys showed that the security fatigue scale in the telework environment was similar to the information security fatigue results in the face-to-face environment of the previous study, with approximately 20% in the ideal state. In other words, security fatigue was found to be the same in a telework environment as in a face-to-face environment. Furthermore, the results of the analysis of the open-ended responses to the questionnaire survey showed similar trends to those indicated in previous studies. As a result of these findings, it was clarified that countermeasures such as “implementation of education to arouse awareness of the concerned parties” and “interviews regarding information s

关键词： Surveys COVID-19 Education information security Psychology Web conferencing Fatigue Market research Remote working Interviews

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