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14th International Conference on Frontier Computing, FC 2024

作者： Yang, Hsuan-Che Chang, Wen-Chih Huang, Wei-Han Hsu, Chia-Hao Lin, Yen-Chen Li, Jie-Syuan Lee, Yun-Cheng Luo, Zeng-Sheng Department of Information Management Chihlee University of Technology New Taipei City220 Taiwan International Master Program of Information Technology and Applications National Ping-Tung University Ping-Tung Taiwan

ISBN: (纸本)9789819623945

The worldwide aging population has been on the rise due to the advancement of medical science and decreasing birth rates. Unfortunately, this has led to an increase in falls among the elderly, which has emerged as one of the top ten causes of death for elderly individuals in Taiwan. To address this issue, our study aims to leverage the widespread use of smartphones and smartwatches to detect and prevent falls in older adults. Our machine learning model is trained using the UMAFall dataset, which collects data on daily activities and falling actions through five sensing devices. We used Azure Machine Learning Studio to test six different machine learning algorithms to evaluate suitable algorithms. In the end, the Two-Class Decision Tree algorithm achieved the best results. In our next step, this method will be programmed with the TensorFlow Lite and train the model. This model will be integrated into Android-based apps that can be installed on smartphones. By continuously connecting the smartwatch and smartphone Apps, the accelerometer, gyroscope, and magnetometer in both devices can be compared and analyzed in real time using the TensorFlow Lite model, accurately determining the wearer's actions. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Adversarial machine learning

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Key Factors for Unsubscribing from YouTube Channels: A Study of YouTubers in Taiwan 1

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13th International Conference on Frontier Computing, FC 2023

作者： Yang, Hsuan-Che Chang, Wen-Chih Department of Information Management Chihlee University of Technology New Taipei City220 Taiwan International Master Program of Information Technology and Applications National Pingtung University Pingtung City Taiwan

ISBN: (数字)9789819993420

ISBN: (纸本)9789819993413

YouTube has become a major advertisement media for industries. People watch TV shows, movie trailers, news and episodes, on-line shows streaming as well. When people want to purchase something, they can find some unboxing reviews, experiences shares, using instructions and services introductions on YouTube before making orders. Traveling guides and educational tutorials are also can be found on YouTube. Thousands of YouTube channels need channel’s subscribers directly or indirectly affect the revenue of channel owners. In addition to YouTube’s own profit from watching, the subscribers are also an important reference when manufacturers want to choose key opinion leaders (KOL) or internet celebrities to promote their products or services. Since, maintaining a stable growth of channel subscribers and reducing the occurrence of unsubscribing are the key issue that every YouTuber needs to understand urgently. In this study, we used a survey to understand subscribers and YouTubers on unsubscribing, and analyzed some key factors for unsubscribing. The data analyses include descriptive analysis, factor analysis, reliability analysis, t-test, one-way ANOVA, and Pearson’s correlation analysis. Through this study, people can understand key factors for unsubscribing reasons on YouTube platform and the priority of these factors. Whether there is special unsubscribe factors for different channel types and attributes. The key contribution of this study is: a questionnaire on key factors for unsubscribing on the YouTube platform was designed, and it could be utilized for further use in related studies in the future. We also summarize the responses and suggestions of we-media channel owners on the factors for unsubscribing. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd 2024.

关键词： Reliability analysis

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Distributed Flexible Job Shop Scheduling through Deploying Fog and Edge Computing in Smart Factories Using Dual Deep Q Networks

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Mobile Networks and Applications 2024年第3期29卷 886-904页

作者： Lin, Chun-Cheng Peng, Yi-Chun Chen, Zhen-Yin Annie Fan, Yu-Hong Chin, Hui-Hsin Department of Industrial Engineering and Management National Yang Ming Chiao Tung University Hsinchu300 Taiwan International Master Program of Smart Manufacturing and Applied Information Science National Chin-Yi University of Technology Taichung411 Taiwan Department of Information Technology Overseas Chinese University Taichung407 Taiwan

Flexible job shop scheduling (FJSP) has garnered enormous attention within the realm of smart manufacturing, where, beyond job sequencing, the selection of machines holds considerable importance. As smart factories progress with the Internet of things (IoT) and cyber-physical systems (CPS), scheduling methodologies are advancing towards intelligent decentralization. However, with the expansion of factories, conventional cloud computing struggles to manage the substantial influx of data. To tackle this issue, this work incorporates a fog computing and edge computing framework into the distributed FJSP workstations. In this framework, the workstations each of which consists of multiple machines are categorized based on the different nature of the accommodated machines, and operate independently to reduce unnecessary information transmission, in which each machine is equipped with edge computing capacity. The fusion of fog computing and edge computing allows for the offloading of computational tasks from cloud computing, effectively reducing latency. While previous solutions for FJSP have predominantly relied on linear programming or metaheuristic algorithms, this work proposed a novel distributed approach based on a dual deep Q networks (dual DQN) architecture, integrating deep learning (DL) with reinforcement learning (RL). Within the cloud center, the initial neural network determines the machine selection rules for fog computing, while the secondary neural network decides the job dispatching rules for edge computing devices. Edge computing devices execute the schedule and provide feedback to the cloud, which refines the results through an iterative training process, so that to minimize the makespan. The experimental findings indicate that employing dual DQNs outperforms the methods of utilizing only one single machine selection rule. © The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2024.

关键词： Reinforcement learning

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A Novel Finite Mixture Model Based on the Generalized t Distributions with Two-Sided Censored Data

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Annals of Data Science 2025年第1期12卷 341-379页

作者： Guan, Ruijie Rong, Yaohua Cheng, Weihu Xin, Zhenyu Key Laboratory of Network Information System Technology Aerospace Information Research Institute Chinese Academy of Sciences Beijing100094 China Faculty of Science Beijing University of Technology Beijing100124 China Master of management EBS Universität für Wirtschaft und Recht Oestrich-Winkel65375 Germany

In light of the rapid technological advancements witnessed in recent decades, numerous disciplines have been inundated with voluminous datasets characterized by multimodality, heavy-tailed distributions, and prevalent missing information. Consequently, the task of effectively modeling such intricate data poses a formidable yet indispensable challenge. This paper endeavors to address this challenge by introducing a novel finite mixture model predicated upon the generalized t distribution, tailored specifically to accommodate two-sided censored observations, thereby establishing a foundational framework for modeling this complex data structure. To facilitate parameter estimation within this model, we devise a variant of the EM-type algorithm, amalgamating the profile likelihood approach with the classical Expectation Conditional Maximization algorithm. Notably, this hybridized methodology affords analytical expressions in the E-step and a tractable M-step, thereby substantially enhancing computational expediency and efficiency. Furthermore, we furnish closed-form expressions delineating the observed information matrix, pivotal for approximating the asymptotic covariance matrix of the MLEs within this mixture model. To empirically evaluate the efficacy of the proposed algorithm, a series of simulation studies are conducted, demonstrating promising performance across various artificial datasets. Additionally, the practical applicability of the proposed methodology is elucidated through its deployment on two real-world datasets, thereby underscoring its feasibility and utility in practical settings. © The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2024.

关键词： Expectation maximization algorithm

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Development of a Serious Game-Based Mechanism for Sarcopenia Training - A Case Study on Limb-Specific Exercise

Development of a Serious Game-Based Mechanism for Sarcopenia...

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2024 International Conference on information technology, Data Science, and Optimization, I-DO 2024

作者： Lin, Wei-Tong Chang, Yu-Tung Hung, Lun-Ping The Master Program of College of Health Technology National Taipei University of Nursing and Health Sciences Taipei Taiwan College of Health Technology National Taipei University of Nursing and Health Sciences Taiwan Department of Information Management National Taipei University of Nursing and Health Sciences Taipei Taiwan

ISBN: (纸本)9798400709180

In recent years, the global elderly population has been on the rise, and Taiwan is projected to enter the super-aged society by 2025. The health of the elderly has become a crucial global issue, particularly with diseases like sarcopenia affecting cognition and physical functions. In response to this trend, the government has actively promoted senior fitness clubs;however, the quantity of these clubs is insufficient for the elderly population, and some seniors find it challenging to participate. Traditional home-based exercise programs also tend to be monotonous or tedious. Therefore, this study introduces a supportive mechanism using serious games, incorporating image recognition technology to provide customized home-based physical training games for the elderly. The system features a senior-friendly gaming environment, is non-wearable, and easy to set up. It dynamically adjusts difficulty levels through real-time data, ensuring both safety and engagement in training. In summary, the system aims to offer the elderly a safe, enjoyable, and personalized platform for physical training assistance, addressing the ongoing challenges of maintaining health in aging populations. © 2024 Copyright held by the owner/author(s). Publication rights licensed to ACM.

关键词： Serious games

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The Banking Industry is Undergoing a Digital Transformation as Part of Industrial 4.0 10

The Banking Industry is Undergoing a Digital Transformation ...

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

作者： Sardjono, Wahyu Pranata, Dewi Sagita Ramdhana, Aditya Agung Dwi BINUS Graduate Program - Master of Information Systems Management Bina Nusantara University Information Systems Management Department Jakarta11480 Indonesia Mathematical & Engineering Sciences King's College London Cyber Security Studi Program Faculty of Natural Department of Informatics West Minster Strands WC2R 2LS United Kingdom University of Airlangga Master of Management Faculty of Economics and Business Surabaya60286 Indonesia

ISBN: (纸本)9798350363104

In the current day, digital transformation is imperative;both customer demand and market competitiveness are mostly driving that trend. The fourth industrial revolution has also affected the financial sector. One difficulty that has to be addressed is the desire from customers for quick and useful services. Traditional procedures need to be replaced with digital ones. Furthermore, banking organizations will have a competitive edge in the current market if they are successful in this digital transformation process. Successful transformation, however, does not happen by accident;in fact, the likelihood of completing this change is seen to be very low, necessitating rigorous planning for a company that is ready for the future. There are several components to the preparation in question, both internal and external. In this situation, the company's ability to combine and rearrange its resources quickly is essential for adapting to the ever-changing business environment. © 2024 IEEE.

关键词： Commerce

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Risk management of Bank and FinTech Collaboration: A Phenomenological Research 6

Risk Management of Bank and FinTech Collaboration: A Phenome...

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6th International Conference on Computer and Informatics Engineering, IC2IE 2023

作者： Legowo, Mercurius Broto Sorongan, Fangky Antoneus Subanidja, Steph Institute of Perbanas Study Program of Information System Faculty of Information Technology Jakarta Indonesia Institute of Perbanas Study Program of Accounting Faculty of Economic and Business Jakarta Indonesia Post Graduate School Institute of Perbanas Program of Master of Management Jakarta Indonesia

ISBN: (纸本)9798350345162

Banking and Fintech are encouraged to collaborate to fill each other's deficiencies and further grow the digital economy. This collaboration will create benefits for both banks, Fintech, and customers. However, this collaboration also comes with risks. The Financial Services Authority has stated that several risk phenomena can occur in the collaboration of banks and Fintech. First, no law guarantees the protection and exchange of customer personal data. Second, the risk of customer data leakage. Third, the risk of cyberattacks. The fourth is the risk of outsourcing. This research aims to analyze the risk phenomenon of bank and fintech collaboration through the Enterprise Risk management Framework approach. This study uses a phenomenological research approach, which is a study to study how individuals subjectively experience and give meaning to the phenomenon. Data analysis based on this phenomenon data uses qualitative methods involving banking and fintech practitioners. The results of this study describe the phenomenon of risks that occur in banking-fintech collaboration, as approached by the Enterprise Risk management framework. Proper risk management will minimize risks when the Bank collaborates with FinTech. This study hopefully contributes to making brief policy recommendations on bank and fintech collaboration risk management for Indonesian financial regulators. © 2023 IEEE.

关键词： bank collaboration ERM framework fintech risk management

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Disaster recovery plan implementation evaluation model at the corporation 7

Disaster recovery plan implementation evaluation model at th...

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7th information Systems International Conference, ISICO 2023

作者： Sardjono, Wahyu Perdana, Widhilaga Gia Putra, Gustian Rama Information Systems Management Department BINUS Graduate Program - Master of Information Systems Management Bina Nusantara University Jakarta11480 Indonesia Post Graduate Program of Management Science State University of Jakarta Jl. R.Mangun Muka Raya No.11 Jakarta Timur Jakarta13220 Indonesia Computer Science Study Program Faculty of Mathematics & Natural Sciences Pakuan University Bogor Indonesia

The application of information technology in addition to making internal business processes more effective and efficient, is also to improve customer service. This role is important for companies to maintain the sustainability of information systems as a strategic tool for competitive advantage so system availability is absolutely essential. Research related to the Disaster Recovery Plan (DRP) needs to be carried out to see the readiness of a corporation to build a backup system in different places and locations. By using the method of factor analysis and regression analysis to form an evaluation model, it will obtain an overview of what factors must be considered and what the current conditions are. The results of the study show that there are Core Technical DRP, Organizational Preparation, and Costing factors which are the main variables in supporting DRP readiness. The conclusion from this study, through these three new factors a mathematical model can be built as a reference for improving DRP implementation in corporations. © 2023 The Authors. Published by Elsevier B.V.

关键词： Factor analysis

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Development of Key Performance Indicators in e-Learning Implementation in Higher Education Institutions 8

Development of Key Performance Indicators in e-Learning Impl...

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8th International Conference on information management and technology, ICIMTech 2023

作者： Sardjono, Wahyu Kristin, Desi Maya Putra, Gustian Rama Binus Graduate Program - Master of Information Systems Management Bina Nusantara University Information Systems Management Department Jakarta11480 Indonesia School of Information Systems Bina Nusantara University Information Systems Department Jakarta11480 Indonesia Pakuan University Computer Science Study Program Faculty of Mathematics & Natural Sciences Bogor Indonesia

ISBN: (纸本)9798350326093

Companies or organizations usually use key performance indicators (KPI) as indicators to determine their performance. The company's performance achievements are reflected in the set indicators that will describe the overall performance, as well as higher education institutions can also set key performance indicators, to see their performance achievements. The use of e-learning as a tool to support teaching and learning processes to be more effective and efficient is an example of which performance needs to be measured. This article discusses how the process of developing key performance indicators is carried out through the stages of designing questionnaires and distributing questionnaires to students, data is processed using the method of factor analysis to obtain the main indicators determining performance and the method of regression analysis is also used to build performance models. obtain KPI determinants, and then develop KPI models. The results show that there are indicators of sharing knowledge, managing knowledge, understanding knowledge, and utilization knowledge as performance measurement indicators. © 2023 IEEE.

关键词： Regression analysis

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Model of Customer Relationship management Systems Evaluation Using Factor Analysis 8

Model of Customer Relationship Management Systems Evaluation...

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8th International Conference on information management and technology, ICIMTech 2023

ISBN: (纸本)9798350326093

Relationship with customers is one of the most crucial factors in business continuity and development. Many current businesses have started delving into Customer Relationship management (CRM) to establish and maintain their sales and customer relationships. This research was conducted on one retail company that implements CRM but experiencing a gap in their unit sales performance between their targeted sales and the realization. This study aims to analyze the gaps causing factors using Factor Analysis Method, constructing a suitable regression model, and proposing the company's necessary strategy. The research was conducted quantitatively using a questionnaire from 264 respondents. The result of this study showed that there are five causing factors which are CRM Reliability, Underutilization of CRM, CRM Capability, CRM Unpreparedness, and Customer Relation Quality, as well as forming a regression model of the company's CRM performance. © 2023 IEEE.

关键词： Sales

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