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arXiv 2022年

作者： Tsai, Yun-Cheng The Department of Technology Application and Human Resource Development The National Taiwan Normal University Taiwan

Since the end of 2021, the Metaverse has been booming. Many unknown possibilities are gradually being realized, but many people only determined that they use Virtual Reality (VR), Augmented Reality (AR), and Mixed Reality (MR) in the Metaverse. It is even considered that as long as the above realities (VR, AR, MR) are used, it is equal to the Metaverse. However, this is not true, for Reality-based display tools are only one of the presentation methods of the Metaverse. If we cannot return to the three main characteristics of the Metaverse: "digital avatars," a decentralized "consensus value system," and "Immersive experience," the practice and imagination of the Metaverse will become very narrow. Since 2022, the concept of Metaverse has also been widely used in classroom teaching to integrate into teaching activities. Therefore, to prevent teachers and students from understanding the Metaverse not only in the "Using VR, AR, MR is equivalent to Metaverse" but also pay more attention to the other two characteristics of the Metaverse: "digital avatars" and a decentralized "consensus value system.". © 2022, CC BY.

关键词： Mixed reality

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Effects of virtual reality on creative performance and emotions: A study of brainwaves

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Computers in human Behavior 2023年 146卷

作者： Huang, Huai-Te Chang, Yu-Shan Department Of Technology Application And Human Resource Development National Taiwan Normal University Taiwan Department of Industrial Education National Taiwan Normal University Taiwan

Creativity is the basis for innovation and a source of national and industrial competitiveness. Thus, pedagogical enhancement of creativity is desirable, particularly via application of new technologies such as virtual reality (VR). The purpose of this study was to examine the effects of VR on creativity (creative outcomes and the creative process), emotions, and brainwaves using a nonequivalent-group pre-post-test quasi-experimental design involving 76 tenth-grade students. An experimental group received training that incorporated VR elements, and a comparison group was taught via lectures combined with multimedia presentations. The main conclusions are as follows: VR exerted large positive effects on the elaboration, vividness, and novelty creative outcomes;VR exerted above-moderate positive effects on feasibility but not novelty;VR exhibited small effect sizes in terms of enjoyment, anger, and anxiety, but a large effect size for boredom, and these emotions positively influenced creativity;and beta and gamma brainwave activity during the ideation and elaboration stages, and delta brainwave activity during the latter stage, were significantly lower in the experimental than comparison group. © 2023

关键词： Virtual reality

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Palmyra and coconut haustorium: A comprehensive review on nutritional composition, bioactive potential, value-added products and its health benefits

Food Chemistry Advances

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Food Chemistry Advances 2024年 5卷

作者： E, Raja Rajeshwari P S, Sathanya S, Vignesh N, Baskaran Department of Academics and Human Resource Development National Institute of Food Technology Entrepreneurship and Management – Thanjavur (NIFTEM-T) Tamil Nadu 613005 India

The various parts of the palmyra and coconut trees which are widely distributed in the southern parts of the Indian subcontinent have been studied and utilized for many years. These contain a white and spongy edible component in them which is found during the germination of the seeds called haustorium. The palmyra and coconut trees each have different sections with special medical properties. Recently, the haustorium of both coconut and palmyra trees has been gaining increased attention from researchers due to its nutritional properties. Certain studies on the haustoria have revealed the presence of various compounds that are beneficial for human health. The bioactive compounds found in the previous studies include phenols, flavonoids, terpenoids, pyrimidine groups and certain vitamins which act as antioxidant, anti-inflammatory, anti-ulcer, anti-diabetic, anti-cancer, and anti-mutagenic agents. This review focuses on comparing the nutritional composition, bioactive compounds, sugar profile fatty acid profile, amino acid profile, minerals, and vitamins of both palmyra and coconut haustorium. This review also reports on the value addition of the haustoria as usually they are consumed in their raw form. These value-added products not only enhance the economic viability of these underutilized resources but also contribute to extending their shelf life, making them more accessible in the market. Also, this review emphasizes the haustorium's potential defence against negative consequences. Therefore, this review paper helps in understanding the palmyra and coconut haustorium and its potential health benefits. © 2024 The Author(s)

关键词： Bioactive compounds Coconut haustorium Nutritional composition Palmyra haustorium Phytochemical properties Value-added products

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Nexus Between Employee Engagement and Job Performance: A Study of MSMEs in Ghana During COVID-19: The Moderating Roles of Job Demand and Job resources

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Jindal Journal of Business Research 2023年第1期13卷 30 - 56页

作者： Daniel Nkansah Raymond Gyimah Daniel Agyemfour-Agyemang Sarpong James Kwasi Annan Department of Human Resource and Organisational Development KNUST School of Business Kwame Nkrumah University of Science and Technology Kumasi Ghana Faculty of Business and Management Studies Koforidua Technical University Koforidua Ghana

Micro, small, and medium-sized enterprises (MSMEs) across the globe have been the major victims of the COVID-19 pandemic, which has plunged the business world into a crisis. However, employee engagement (EE) has been labeled as an essential nutrient that organizations need in order to survive in these turbulent times. This study was to investigate the effect of EE on employee performance during the COVID-19 pandemic and how job demands and job resources moderate this relationship. A sample size of 395 respondents were selected from a variety of MSMEs via a convenience sampling method. The study used a survey questionnaire approach as the main method for collecting primary data. The result of the correlation analysis showed that there was a significant relationship between EE and employee performance. It was revealed that job demands and job resources moderated the relationship between EE and employee performance. Finally, the result showed that job demands had an insignificant effect on EE, but job resources had a significant effect on EE. Thus, it can be concluded that, in the face of COVID-19, EE is a significant predictor of EP in the MSME sector.

关键词： Employee engagement job demand MSMEs employee performance job resources Ghana

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YouTuber’s Video as Cross-Cultural Learning resource for Chinese-as-Foreign-Language Learners – Perspective of Big ‘C’ and Small ‘c’ Culture 5th

YouTuber’s Video as Cross-Cultural Learning Resource for Ch...

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5th International Conference on Innovative Technologies and Learning, ICITL 2022

作者： Kao, I.-Lin Chang, Chi-Cheng Yen, Wan-Hsuan Master’s and Doctor’s Program in Teaching Chinese as a Second Language National Chengchi University Taipei City Taiwan Department of Technology Application and Human Resource Development National Taiwan Normal University Taipei City Taiwan

ISBN: (纸本)9783031152726

Due to the influence of the global pandemic, online and distance learning has replaced traditional classroom and face-to-face interaction so students can continue learning. Internet mediated self-directed learning also climbed to a new height and foreign language learning from YouTube video is a very popular learning method for many. Furthermore, YouTube videos can supplement cross-cultural knowledge for foreign language (FL) learners, which is a critical yet hard to develop ability for FL teachers. However, unlike for FL textbooks, the cross-cultural elements have not been examined thoroughly for YouTube videos. Therefore, this study analyzed the most subscribed and watched Japanese Chinese-as-FL YouTuber, "Lee Sisters ch", which is also the official representative of HSK (Hanyu Shuiping Kaoshi) test. We selected 30 most watched videos and analyzed their contents according to Chastain’s Big ‘C’ small ‘c’ culture framework. The result showed 86.67% of the most popular 30 videos covered topics about culture: 23.33% of the videos were related to big ‘C’ culture and 63.33% were about small ‘c’ culture. Similar to earlier researches on FL textbooks, "Literature" was the main theme of big ‘C’. On the other hand, "Everyday living" was the most frequent small ‘c’ topic, which is a unique phenomenon for YouTube FL channels. Furthermore, not only did the portion of big ‘C’ and small ‘c’ cultures match the suggestions of FL scholars, the language used in all videos were also mainly in Japanese that fit the needs of Japanese CFL learners. It is concluded YouTube video may be suitable to learn cross-cultural knowledge for FL learner, especially for Japanese students. © 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Students

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Legalities in Metaverse – Ethereum Fraud Detection

Legalities in Metaverse – Ethereum Fraud Detection

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International Conference on Science technology Engineering and Management (ICONSTEM)

作者： Manoj Hudnurkar Kartik Singh Suhas Ambekar Geeta Sahu Harshil Yecho Symbiosis Centre for Management & Human Resource Development (SCMHRD) Symbiosis International (Deemed University) Pune India Department of Information Technology and Data Science Vidyalankar School of Information Technology (VSIT) (University of Mumbai) Mumbai India

ISBN: (数字)9798350365092

ISBN: (纸本)9798350365108

The spread of the Metaverse has created new moral and legal challenges, especially when it comes to protecting against fraud. This study explores the legal complexities surrounding Ethereum-specific metaverse transactions and provides guidance on how to identify and address fraudulent activity. The focus of this investigation is the field of fraud detection in the Ethereum environment. Current methods of detecting fraud, such as Blockchain analysis and machine learning-based algorithms, are carefully examined. Next, a new approach to fraud detection is put out, which is predicated on a collection of seven machine learning algorithms: K-Nearest Neighbours (KNN), Decision Tree, Support Vector Machine (SVM), Random Forest, KNN, XGBoost (XGB), and Artificial Neural Network (ANN). The results of this study are carefully outlined, demonstrating the accuracy, recall, F1 score, and precision that each of the previously listed algorithms demonstrated. Moreover, this article lays out possible directions for further research, including the incorporation of group approaches and the investigation of creating characteristics to strengthen fraud detection abilities. This academic paper provides a significant and novel insight into the identification of fraudulent activity in Ethereum transactions, highlighting the potential benefits of using machine learning algorithms for this kind of discernment.

关键词： Support vector machines Machine learning algorithms Accuracy Metaverse Artificial neural networks Fraud Decision trees

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Predicting Delays for Truck Delivery Logistics: An Application of AI and ML

Predicting Delays for Truck Delivery Logistics: An Applicati...

引用

International Conference on Science technology Engineering and Management (ICONSTEM)

作者： Manoj Hudnurkar Kuriakose M. Renji Suhas Ambekar Geeta Sahu Kavitha Mary Joseph Symbiosis Centre for Management & Human Resource Development (SCMHRD) Symbiosis International (Deemed University) Pune India Department of Information Technology and Data Science Vidyalankar School of Information Technology (VSIT) (University of Mumbai) Mumbai India

ISBN: (数字)9798350365092

ISBN: (纸本)9798350365108

Supply chain management has a lot of logistical challenges, which can significantly affect the efficacy and efficiency of logistics operations as a whole. Machine learning techniques are increasingly popular because they can evaluate vast data volumes and produce precise predictions. Logistics management must include the forecast of delays in the supply chain. It entails anticipating delays in logistics operations, which can assist logistics managers in effectively planning and allocating resources. This paper summarizes the logistics delay prediction in truck delivery systems and identifies some opportunities and problems. The article also suggests a framework for predicting logistics delays based on machine learning methods and assesses the framework's effectiveness using actual data. Thus, the research uses machine learning and AI approaches to anticipate logistics delays. The study gathered information on previous logistical operations and determined the major causes of delays. Then, models for predicting logistical delays were used using machine learning techniques, such as Artificial Neural Networks (ANN), decision trees, random forests, and support vector machines. Our findings demonstrate that these methods have an accuracy rate of up to 97.6 % in predicting logistics delays. Also, we discovered that the Adaboost classifier model performed better than the other models in accuracy and precision. Our study offers insightful information on the application of machine learning methods for anticipating logistics delays, which can assist supply chain managers and logistics firms in better organizing and manage their operations to cut down on delays and increase overall effectiveness.

关键词： Costs Accuracy Machine learning algorithms Supply chains Machine learning Predictive models Real-time systems

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Review of Remote Audit in Occupational Safety and Health Management System through the Mixed-Reality Spectrum 7

Review of Remote Audit in Occupational Safety and Health Man...

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7th International Conference on Research and Innovation in Information Systems, ICRIIS 2021

作者： Fuad Mohd Isa, Mohd Zairah Ab Rahim, Nor Syazli Bin Fathi, Mohamad Ministry of Human Resource Department of Skills Development Putrajaya Malaysia Universiti Teknologi Malaysia Razak Faculty of Technology and Informatics Kuala Lumpur Malaysia

ISBN: (纸本)9781665408059

The Occupational Safety and Health Management System (OSHMS) is a collection of interconnected or interacting elements that work together to define and implement Occupational Safety and Health (OSH) policies and objectives. Employers must guarantee that this system is effectively implemented to safeguard employees from hazards in order to attain those goals and eliminating work-related injuries, illnesses, diseases, incidents and deaths by using the guideline given by the International Labor Organization (ILO) as well as the department of Safety and Health (DOSH) of Malaysia. Auditing is among the vital process in analyzing the performance of OSHMS. The audit process is part of the evaluation element, as described by ILO where the auditor needs to evaluate the OSH performance. However, due to the Covid-19 pandemic situation, the traditional audit could not be conducted, thus the remote audit is considered to be a viable option to ensure the audit process continues. Therefore, this paper intends to understand how the OSHMS especially in the university context can be remotely audited using Mixed Reality (MR) applications through a review of the literature. The findings indicate appropriate contexts of discussion for the study and also identified MR technology namely the 360-degree panoramic view technology that could be further studiedThe paper's contribution is a better knowledge of the OSHMS remote audit process through the usage of MR applications in a specialized setting. The findings of this study would be beneficial to the stakeholders in the relevant context particularly in the university in their investment decision-making for a future-ready ecosystem by digitising their enterprises. © 2021 IEEE.

关键词： Mixed reality

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Do Job Candidates Perform Honest and Deceptive Impression Management Differently in Automated Video Interviews with Different Ai Interfaces?

SSRN

引用

SSRN 2022年

作者： Suen, Hung-Yue Collin Hung, Kuo-En Department of Technology Application and Human Resource Development National Taiwan Normal University Taipei City Taiwan

Automated video interviews powered by artificial intelligence (AI) are increasingly being adopted by employers to screen job candidates despite concerns regarding the humanity and transparency of AI. Accordingly, researchers and practitioners advocate overcoming these concerns by refining AI interfaces in terms of tangibility, immediacy, and transparency. However, AI video interviews featuring different interfaces may impact interviewees’ tendencies to engage in impression management behaviors (IMs), which can either improve or impair personnel selection validity. This study addressed calls for research to investigate the issues mentioned above by conducting a field study to explore the ways in which AI and AI interfaces affect candidates’ IMs in asynchronous video interviews (AVIs). We developed three AVI interfaces and measured real job applicants’ self-reported IMs across four experimental treatments. We found that different AI interfaces could increase or decrease candidates’ honesty IMs and deceptive IMs in different ways. An exploratory analysis also found that candidates’ interview anxiety could be mitigated by an AI interface. © 2022, The Authors. All rights reserved.

关键词： Transparency

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Advancing Elderly Care Through AI: The Jubo VitalLink System's Role in Home Nursing and Intelligent Monitoring 1

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8th International Conference on Information and Communication technology for Intelligent Systems, ICTIS 2024

作者： Tsai, Yun-Cheng Liu, Cheng-Yang Peter Li, Yi-Fen Kang, Shih-Chung Department of Technology Application and Human Resource Development National Taiwan Normal University No. 162 He-Ping East Road Sec1 Taipei10610 Taiwan Smart Ageing Tech Co. Ltd. 6F No. 213 Sec. 3 Beixin Rd. Xindian District New Taipei City231030 Taiwan

ISBN: (数字)9789819758104

ISBN: (纸本)9789819758098

This study explores the use of AI in nursing care, focusing on the Jubo VitalLink VS-3 AI Vital Signs Measurement Cart in Long-Term Care (LTC) facilities. It highlights AI's role in improving patient outcomes and operational efficiency in LTC, using deep learning and the Isolation Forest algorithm for vital signs anomaly detection. The research addresses challenges such as algorithmic biases and privacy concerns, showing the AI model's high accuracy and recall rates in anomaly detection. It also discusses the importance of explainable AI in enhancing decision-making and integrating AI into LTC practices, emphasizing AI's potential to complement human judgment and improve nursing care in LTC settings. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： Nursing

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