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10th International Conference on Applied System Innovation, ICASI 2024

作者： Wu, Wen-Chuan Lee, Ming-Han National Ilan University Dep. of Computer Science and Information Engineering Yilan City Taiwan National Ilan University Master Program of E-Learning for Multimedia and Network Communications Yilan City Taiwan

ISBN: (纸本)9798350394924

Digital content industry, encompassing areas such as digital games, computer animation, digital audio-visual applications, and digital art, plays a pivotal role in today's and future developmental trends. Maya 3D software stands out as a crucial development tool in these domains. However, the multitude of built-in tools in Maya 3D can lead to overly complex interfaces, impacting development efficiency for software developers. To address this issue, this paper designs a digital toolkit for Maya 3D software, presented in a Menu Bar format. This toolkit offers features like naming, sorting, categorization, and automatic saving to JSON files for future use. Through a crossover experimental design, this paper investigates the impact of this proposed toolkit on 3D software developers' individual work performance, work engagement, and stress perception. Results shows a significant positive influence of that toolkit on software developers, particularly in enhancing work performance. It means that the proposed digital toolkit effectively improves the performance of software developers' work and reduces their stress during the software development process. © 2024 Ieee.

关键词： Digital devices

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Brainwave Analysis of the Correlation Between Listening to the Rain/Water Sounds and Reducing Human-Perceived Temperature 18th

Brainwave Analysis of the Correlation Between Listening to t...

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18th International Conference on Intelligent Information Hiding and multimedia Signal Processing, IIH-MSP 2022

作者： Tey, Fu Jie Wu, Tin-Yu Liu, Mei-Yin Chen, Yi-Kai Department of Electrical Engineering National Taiwan University of Science and Technology Taipei City Taiwan Department of Management Information Systems National Pingtung University of Science and Technology Neipu Taiwan Master Program of E-Learning for Multimedia and Network Communications National Ilan University Yilan City Taiwan

ISBN: (纸本)9789819901043

This study focuses on the brainwave analysis of the correlation between listening to the rain and water sounds and reducing human-perceived temperature. Brainwave changes are monitored when experimental subjects listen to rain and water sounds at various frequencies. The experiment result shows that listening to the sounds of rain and water in an environment of high temperature and high humidity can boost α waves to induce feelings of calm and relaxed mental state. In order to investigate subjects’ psychological and physiological changes induced by brainwave changes while listening to rain and water sounds for different time durations in a high temperature and humidity environment, this study uses the Fourier transform to obtain the spectra of natural rain/water sounds and analyzes the sound frequencies. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Fourier analysis

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Using LSTM and Regression Analysis for Railway Passenger Traffic Volume Prediction 11

Using LSTM and Regression Analysis for Railway Passenger Tra...

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11th Ieee Global Conference on Consumer electronics, GCCe 2022

作者： Tey, Fu Jie Tuan, Chih-Chi Cai, Cheng-en Wu, Ming-Xuan Wu, Yun-Sheng Wu, Tin-Yu National Taiwan University of Science and Technology Department of Electrical Engineering Taipei Taiwan National Ilan University Master Program of E-Learning for Multimedia and Network Communications Yilan Taiwan National Pingtung University of Science and Technology Department of Management Information Systems Pingtung County Taiwan

ISBN: (纸本)9781665492324

The purpose of this paper is to investigate the factors affecting the passenger traffic volume on the high-capacity MRT, to analyze the traffic volume trends, and to make traffic volume predictions more accurately. This paper uses the LSTM (Long Short-term Memory) model and regression analysis for Taipei MRT passenger traffic volume prediction. The training data, including dates, temperatures and number of passengers, were collected, and a regression analysis was performed to find trends in the data. © 2022 Ieee.

关键词： Long short-term memory

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Accuracy improvements for cold-start recommendation problem using indirect relations in social networks

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JOURNAL OF BIG DATA 2021年第1期8卷 1-18页

作者： Tey, Fu Jie Wu, Tin-Yu Lin, Chiao-Ling Chen, Jiann-Liang Natl Taiwan Univ Sci & Technol Dept Elect Engn Taipei Taiwan Natl Pingtung Univ Sci & Technol Dept Management Informat Syst Pingtung Taiwan Natl Ilan Univ Master Program E Learning Multimedia & Network Co Yilan Taiwan

Recent advances in Internet applications have facilitated information spreading and, thanks to a wide variety of mobile devices and the burgeoning 5G networks, users easily and quickly gain access to information. Great amounts of digital information moreover have contributed to the emergence of recommender systems that help to filter information. When the rise of mobile networks has pushed forward the growth of social media networks and users get used to posting whatever they do and wherever they visit on the Web, such quick social media updates already make it difficult for users to find historical data. For this reason, this paper presents a social network-based recommender system. Our purpose is to build a user-centered recommender system to exclude the products that users are disinterested in according to user preferences and their friends' shopping experiences so as to make recommendations effective. Since there might be no corresponding reference value for new products or services, we use indirect relations between friends and "friends' friends" as well as sentinel friends to improve the recommendation accuracy. The simulation result has proven that our proposed mechanism is efficient in enhancing recommendation accuracy.

关键词： Social network Indirect relation Cold-start

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An effective method for incentivizing groups implemented in a collaborative problem-based learning system to enhance positive peer interaction and learning performance

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INTeRACTIVe learning eNVIRONMeNTS 2022年第3期30卷 435-454页

作者： Chen, Chih-Ming Wang, Jung-Ying Zhao, Rong-Hua Natl Chengchi Univ Grad Inst Lib Informat & Archival Studies Taipei Taiwan Lunghwa Univ Sci & Technol Dept Multimedia & Game Sci Taoyuan Taiwan Natl Chengchi Univ E Learning Master Program Lib & Informat Studies Taipei Taiwan

Many studies have verified that the effective promotion of both positive interactions among individual group members and group accountability is a critical issue in collaborative problem-based learning (CPBL). This work, therefore, proposes a group incentive mechanism (GIM) that is based on considering several important factors that influence peers' interactions and group accountability in collaborative learning to improve learning performance, interactive relationships, group efficacy, and the cohesiveness of groups of learners in a CPBL system. To evaluate the effectiveness of the proposed GIM, 48 Grade 4 students from two classess were recruited from an elementary school in Taoyuan City, Taiwan, to participate in an instruction experiment. Two classess were randomly assigned to the experimental group using CPBL with the proposed GIM and the control group using CPBL with the individual incentive mechanism (IIM) to solve a target problem collaboratively. Analytical results reveal that although the control group of learners with the IIM exhibited greater social interactions than the experimental group of learners with the proposed GIM, the experimental group exhibited better learning performance, group efficacy, and positive interactive relationships than the control group.

关键词： Problem-based learning collaborative learning group incentive mechanism interactive relationships group efficacy group cohesiveness

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The Influence of Applying Digital Toolkits to Assist 3D Software Development on Individual Work Performance and Perceived Stress

The Influence of Applying Digital Toolkits to Assist 3D Soft...

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International Conference on Applied System Innovation (ICASI)

作者： Wen-Chuan Wu Ming-Han Lee Dep. of Computer Science and Information Engineering National Ilan University Yilan City Taiwan R.O.C. Master Program of E-Learning for Multimedia and Network Communications National Ilan University Yilan City Taiwan R.O.C.

ISBN: (数字)9798350394924

ISBN: (纸本)9798350394931

关键词： Industries Technological innovation Three-dimensional displays Market research Software Stress Software development management

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A Genetic Algorithm to Optimize Cargo Stability in Container Transportation 11

A Genetic Algorithm to Optimize Cargo Stability in Container...

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11th Ieee Global Conference on Consumer electronics, GCCe 2022

作者： Hsieh, Chi-Jung Wu, Kuang-Sung Wu, Tin-Yu Tey, Fu Jie Chen, Yi-Kai Ho, Jye Yi National Ilan University Department of Computer Science and Information Engineering Ilan County Taiwan National Ilan University Master Program of E-Learning for Multimedia and Network Communications Yilan Taiwan National Pingtung University of Science and Technology Department of Management Information Systems Pingtung County Taiwan National Taiwan University of Science and Technology Department of Electrical Engineering Taipei Taiwan

ISBN: (纸本)9781665492324

In the era of the global village, frequent cross-border trade in goods has made container transportation a significant part in delivery of cargo. However, rollover accidents of container trucks often occur because of tall truck height, improper cargo stowage or crooked roads. Therefore, how to find the optimal center of gravity (CG) of the packed cargo remains an issue that the transportation industry should not neglect. To optimize cargo stability and reduce the incidence of rollovers, this paper proposes a genetic algorithm that scores the cargo stacking process to find the best CG of the cargo based on the CG of the vehicle. According to the deviation angle and the point closest to the best CG, we can Figure out the optimal cargo stacking method. © 2022 Ieee.

关键词： Genetic algorithms

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Hardware Resource Reliability Analysis based on Deep learning for Virtual Machine Deployment Optimization 9

Hardware Resource Reliability Analysis based on Deep Learnin...

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9th Ieee Global Conference on Consumer electronics, GCCe 2020

作者： Huang, Chih-Hao Huang, Bo-Hong Wu, Tin-Yu National Ilan University. Master Program of E-Learning for Multimedia and Network Communications Yilan Taiwan National Ilan University Department of Computer Science and Information Engineering Yilan Taiwan

This paper proposes a new method based on the Apriori algorithm and deep learning technology to improve the flexibility of hardware deployment and to analyze hardware usage reliability for VM. This method can signific... 详细信息

ISBN: (纸本)9781728198026

关键词： Reliability analysis

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Using LSTM and Regression Analysis for Railway Passenger Traffic Volume Prediction

Using LSTM and Regression Analysis for Railway Passenger Tra...

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Ieee Global Conference on Consumer electronics (GCCe)

作者： Fu Jie Tey Chih-Chi Tuan Cheng-en Cai Ming-Xuan Wu Yun-Sheng Wu Tin-Yu Wu Department of Electrical Engineering National Taiwan University of Science and Technology Taipei Taiwan Master Program of E-Learning for Multimedia and Network Communications National Ilan University Yilan Taiwan Department of Management Information Systems National Pingtung University of Science and Technology Pingtung County Taiwan

ISBN: (纸本)9781665492331

关键词： Temperature distribution Solid modeling Government Transportation Training data Predictive models Market research

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Predicting Metabolic Syndrome With Machine learning Models of Hybrid Analysis

Predicting Metabolic Syndrome With Machine Learning Models o...

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2023 International Conference on Consumer electronics - Taiwan, ICCe-Taiwan 2023

作者： Wu, Yi-Syuan Wang, Wei-Yun Wu, Hao-Yi Chen, Chao-Wen Chu, Chi-Ming Wu, Cheng-Wei Division of Trauma and Surgical Critical Care Department of Surgery Kaohsiung Medical University Hospital Kaohsiung Medical University Kaohsiung Taiwan Master Program of E-Learning for Multimedia and Network Communications National I-Lan University Yilan Taiwan National Defense Medical Center Tri-Service General Hospital Songshan Branch School of Nursing Department of Nursing Taipei Taiwan National Defense Medical Center Department of Nursing Tri-Service General Hospital Taipei Taiwan Kaohsiung Medical University Hospital Kaohsiung Medical University Trauma and Critical Care Service Department of Surgery Kaohsiung Taiwan National Defense Medical Center School of Public Health Taipei Taiwan National I-Lan University Department of Computer Science and Information Engineering Yilan Taiwan

ISBN: (纸本)9798350324174

The study uses machine learning to determine the accuracy of different algorithms for predicting MetS. early prediction of MetS through routine health screening is an important goal for preventive medicine. The subjects in this study were employees aged 20 to 65 years old who signed a consent form for in-hospital health screening data were collected from 2015 to 2020. Total of 3538 individuals who underwent health screening were included in this study. Baseline characteristics of the 315 participants diagnosed with metabolic syndrome and 3222 participants without metabolic syndrome. This is a machine learning approach to identify metabolic syndrome using biochemical values and lifestyle habits. We found that the F1 score for detection of metabolic syndrome by neural network is the most accurate and higher compared to other models. Our study also identified some new indicators, including heart rhythm, RBC, WBC, Hb, and uric acid, as candidates for better detection of metabolic syndrome. © 2023 Ieee.

关键词： Forecasting

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