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4th Research, Invention, and Innovation Congress: Innovative Electricals and Electronics, RI2C 2023

作者： Ketcham, Mahasak Ganokratanaa, Thittaporn Pramkeaw, Patiyuth Boonthai, Phumraphi Chumuang, Narumol Department of Information Technology Management King Mongkut's University of Technology North Bangkok Bangkok Thailand Applied Computer Science Program King Mongkut’s University of Technology Thonburi Bangkok Thailand Media Technology Program King Mongkut’s University of Technology Thonburi Bangkok Thailand Department Media Technology Muban Chombueng Rajabhat University Ratchaburi Thailand

ISBN: (纸本)9798350330618

This research study presents an algorithmic approach for the detection and identification of key components on license plates, including numerical digits, province codes, vehicle colors, and vehicle makes and types. The methodology integrates image processing techniques and deep learning methodologies to achieve comprehensive image analysis. The algorithm incorporates image preprocessing techniques to optimize the input images, followed by a deep neural network trained on a large annotated dataset. The algorithm utilizes image segmentation and character recognition techniques to detect and classify numerical digits on license plates. Similarly, it employs segmentation and classification processes for identifying province codes, vehicle colors, makes, and types. Extensive training ensures the algorithm's accuracy and robustness under varying conditions. The proposed algorithm demonstrates the potential for accurate license plate component detection and identification, with applications in law enforcement and traffic monitoring systems. . ©2023 IEEE.

关键词： License plates (automobile)

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Food delivery app continuance: a dual model and segmentation approach

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International Journal of Retail & Distribution management 2023年第5期51卷 569-589页

作者： Trieu Nguyen Echo Huang Dung Minh Nguyen IMBA program College of Management National Kaohsiung University of Science and Technology Kaohsiung Taiwan Department of Information Management College of Management National Kaohsiung University of Science and Technology Kaohsiung Taiwan Department of Marketing and Distribution Management College of Management National Kaohsiung University of Science and Technology Kaohsiung Taiwan

Purpose The outbreak of the COVID-19 pandemic has led to the pervasiveness of food delivery apps (FDAs) and the increased scholars’ attention for the topic of FDA continuance usage intention. However, the limited understanding about possible segments of FDA users has hindered food retailers from providing FDAs with a personalized manner, which impairs the effectiveness of marketing strategies. Thus, this study aims to first explore key antecedents of users’ continuance intention toward FDAs and then segment and profile Taiwanese users based on the identified antecedents of FDA continuance intention and demographics. Design/methodology/approach An online survey was implemented to collect responses from FDA users in Taiwan. With a response rate of 82.4%, the final sample of 326 respondents (average age = 28.3; female = 54.9%) was analyzed by using two techniques of structural equation modeling (SEM) and cluster analysis. Findings The results indicate six antecedents of users’ continuance usage intention towards FDAs, including information quality, system quality, information quality, perceived usefulness, perceived enjoyment and satisfaction. Additionally, three distinct clusters of FDA users are successfully identified, labeled as “value sensitive users”, “time-sensitive users” and “security sensitive users”. Originality/value This study is one of the pioneers that explores the possible segments in FDA market, which helps FDA providers and food retailers develop more focused and appropriate strategies to encourage users to continue using FDAs. Our findings contribute to building an optimized version of “FDA Tech” that becomes an omni-channel solution to serve the increased home-delivery needs in the new normal era.

关键词： Continuance usage intention Food delivery apps Food retailers COVID-19 Segmentation Cluster analysis

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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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Exploring Regression and Classification in Big Data with Deep Learning

Exploring Regression and Classification in Big Data with Dee...

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2023 International Conference on Power Energy, Environment and Intelligent Control, PEEIC 2023

作者： Pandey, Ravindra Rongali, Aruna Sri Gopinath, S. Anute, Nilesh Nama, Forda Pund, Sachin Hult International Business School United States University of the Cumberlands Doctoral Information Technology Information Technology Emphasis Information Technology United States Karpagam Institute of Technology Department of Electronics and Communication Engineering Coimbatore India ASM's Institute of Business Management and Research Pune India University of Lampung Doctoral Program of Environtmental Science Department of Informatics Bandar Lampung Indonesia Shri Ramdeobaba College of Engineering and Management Department of Industrial Engineering Maharashtra Nagpur India

ISBN: (纸本)9798350357769

Deep gaining knowledge is a synthetic intelligence approach used to recognize complex facts. It uses many facts to recognize the complicated relationships between various factors. With deep learning, models can be built which might be capable of understanding the complicated patterns within big datasets. In this paper, we can explore using deep mastering in regression and type tasks on large datasets. In particular, we can use deep learning strategies to build a regression model that predicts a target value primarily based on the functions in a massive dataset and a classification version that can classify an object into one of the many classes of an extensive dataset. We can then discuss the overall performance of the fashions in comparison to standard models and talk about capability areas for development. Moreover, we will analyze the scalability of deep mastering strategies used on large datasets and discuss exceptional practices for building deep mastering fashions on massive datasets. Finally, we will summarize our findings and offer our conclusions approximately the use of deep studying in regression and type obligations on large datasets. © 2023 IEEE.

关键词： approximately gaining knowledge mastering performance regression

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Linkedin's Influence on User Success in The Professional World 9

Linkedin's Influence on User Success in The Professional Wor...

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9th International Conference on ICT for Smart Society, ICISS 2022

作者： Oktavia, Tanty Roekman, Faza Fakhriansyah Putera, Muhammad Ikhsan Hidayah, Muhammad Alif Rafi, Muhammad Hosoda, Takaaki Gaol, Ford Lumban BINUS Graduate Program Information System Management Bina Nusantara University Information System Management Department Jakarta Indonesia School of Information Systems Bina Nusantara University Information System Department Jakarta Indonesia Advanced Institute of Industrial Technology Decision Science Department Tokyo Japan BINUS Graduate Program Bina Nusantara University Computer Science Department Jakarta Indonesia

ISBN: (数字)9781665471350

ISBN: (纸本)9781665471350

Social media has now become a place for others to exchange information in the form of writing, photos, videos, and audio. Social media has become a place for humans to interact from all over the world. In the use of social media, attractive professional information is conceptualized as access to relevant information and opening up better career opportunities. User content about work and choosing personal information compilation strategies consistently predict information usefulness. This study discusses the effect of using a linked-in application on the success of its users in the professional world. It is hoped that it can provide insight into the use of this recruitment application, making it easier for users to find work. The research model used in this research is quantitative. The survey was conducted on connected users in Indonesia using an online questionnaire, and the data collected was analyzed using PLS-SEM. Of the 68 respondents who took the survey, it can be said that all research models have a positive relationship with the successful use of the linked-in platform. © 2022 IEEE.

关键词： Surveys

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Long Distance Communication System for Areas without Network Infrastructure 4

Long Distance Communication System for Areas without Network...

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4th IEEE Eurasia Conference on Biomedical Engineering, Healthcare and Sustainability, ECBIOS 2022

作者： Pan, Telung Hsu, Wei Chun Bachelor Program in Interdisciplinary National Yunlin University of Science and Technology Douliu Taiwan National Chung Cheng University Departmentept. of Information Management Chiayi Taiwan

ISBN: (数字)9781728195797

ISBN: (纸本)9781728195797

Communication infrastructure is vital for the activities in an area. However, off-grid is still common in many rural areas, which results in a significant gap from the outside of the area. To provide home care and emergency call functions, we propose a scalable wireless signal transmission architecture based on AIoT and Edge Computing, featuring low power consumption, long distance, and low transmission volume, which are applied to off-grid infrastructure lacking area. © 2022 IEEE.

关键词： Computing power

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The Effectiveness of Online Project-Based Learning (PJBL) to Improve Sustainability Education at Private University 7

The Effectiveness of Online Project-Based Learning (PJBL) to...

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7th International Conference on information management and technology, ICIMTech 2022

作者： Oktavia, Tanty Prayoga, Agung Vincent Kenth Devani, Vannesa Milewis, Ivena Gaol, Ford Lumban Hosoda, Takaaki 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 BINUS Graduate Program - Doctor of Computer Science Bina Nusantara University Computer Science Department Jakarta11480 Indonesia Advanced Institute of Industrial Technology Decision Science Department Tokyo Japan

ISBN: (数字)9781665450904

ISBN: (纸本)9781665450904

Currently, online project-based learning is one of the methodologies used in university student assessment. Furthermore, this study is supported by several factors and current conditions applied to learning, such as the pandemic situation where all learning activities and assignments are carried out online and also the many applications of online project-based learning as a learning method to increase students' knowledges and abilities. The purpose of this study is to see how flow experience perception, self-efficacy, product evaluation, and learning motivation affect online PjBL effectiveness at a private university in Jakarta to improve sustain ability education. We surveyed 62 active undergraduate students with online PjBL experience and interviewed one of these five responders from various majors for more information. Flow experience perception, self-efficacy, product evaluation, and learning motivation all have a positive influence on online PjBL, according to multiple linier regression. © 2022 IEEE.

关键词： Students

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The Smart Analysis of Performing Scalable Inference for Big Data Analytics

The Smart Analysis of Performing Scalable Inference for Big ...

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2023 International Conference on Power Energy, Environment and Intelligent Control, PEEIC 2023

作者： Bhandarkar, Vishakha D. Rongali, Aruna Sri Shamout, Mohamed Dawood Pund, Sachin Nama, Gigih Forda Patil, Shrishailappa Yeshwantrao Chavan College of Engineering Applied Mathematics and Humanities India University of the Cumberlands Graduate Doctoral Information Technology Information Technology Emphasis/Information Technology United States College of Business Administration University of Sharjah Department of Management Sharjah United Arab Emirates Shri Ramdeobaba College of Engineering and Management Department of Industrial Engineering Maharashtra Nagpur India Doctoral Program of Environtmental Science University of Lampung Department of Informatics Bandar Lampung Indonesia Vishwakarma Institute of Technology Computer Engineering Pune India

ISBN: (纸本)9798350357769

This paper examines the reproducibility of massive information analytics under particular factors. The paper proposes the 'performing Scalable Inference' technique to cope with scalability troubles and to exploit current big statistics platforms for efficient computing and statistics garage of the statistics. In particular, the paper describes how to perform leak-free, parallelizable visible analytics over massive datasets using present extensive records analytics frameworks such as Apache Flink. This method presents an automated manner to execute analytics that preserves reproducibility and the ability to make adjustments without re-running the entire technique. The paper also demonstrates how these analytics may help several real-world use instances, explore affected person cohorts for studies, and develop stratified patient cohorts for hospital therapy. In the end, the paper observes how the proposed method may be exercised within the real world. Actively scalable inference for massive information analytics is pivotal in optimizing decision-making and allocation of assets. Typically, such inferences are made based on information accumulated from numerous sources, databases, unstructured data, and different digital sources. So one can ensure scalability, a complete cloud-primarily based platform has to be hired. This solution will permit the ***, deploying the essential records series and evaluation algorithms are prime here. It could permit the platform to recognize the styles inside the statistics and discover any ability correlations or traits. Additionally, predictive analytics and system mastering strategies may be incorporated to provide insights into the results of the information. In the long run, by leveraging those techniques, the platform can draw efficient inferences and appropriately compare situations in an agile and green way.. © 2023 IEEE.

关键词： adjustments an a lytics automated preserves statistics

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Understanding donation intention in live streaming: A dedication-constraint approach

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Computers in Human Behavior 2023年 144卷

作者： Chou, Shih-Wei Nguyen, Trieu Department of Information Management National Kaohsiung University of Science and Technology Kaohsiung Taiwan IMBA Program College of Management National Kaohsiung University of Science and Technology Kaohsiung Taiwan

Live streaming has gained popularity and is helpful in facilitating real-time interactions. Unlike face-to-face interactions, relationship development between viewers and streamers faces uncertainty due to low commitment to the relationship. Considering the distinctive features of live streaming interactions, this study builds on the dedication-constraint framework to analyze how live streaming relationship development affects post-adoption behaviors and is facilitated by live streaming interactions. We theorize this relationship development as motivational feedback and self-regulation deficiency that represent dedication and constraint, respectively. Live streaming interactions are captured by personalization, responsiveness, and entertainment. Our model is empirically assessed using data collected from 211 experienced live streaming users in Taiwan. The proposed hypotheses are largely supported, showing that donation is jointly affected by motivational feedback and self-regulation deficiency. Live streaming interactions positively influence the dedication-constraint factors for relationship development. We discuss the theoretical and practical implications. © 2023 Elsevier Ltd

关键词： Deregulation

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Enhancing Educational Innovation: A Comparative Analysis of Blockchain Adoption Strategies in Smart Learning Environments 8

Enhancing Educational Innovation: A Comparative Analysis of ...

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8th International Conference on Informatics and Computing, ICIC 2023

作者： Chakim, Mochamad Heru Riza Ahmad, Daelami Rusilowati, Umi Oganda, Fitra Putri Sanjaya, Yulia Putri Ayu Sunarya, Po Abas University of Raharja Economics and Business Indonesia Commercial Administration Study Program Sekolah Tinggi Ilmu Administrasi Banten Indonesia Pamulang University Management Indonesia University of Raharja Information Systems Indonesia University of Raharja Retail Management Indonesia University of Raharja Faculty of Science and Technology Indonesia

ISBN: (纸本)9798350342604

The recent improvement of traditional education systems in developing countries is supported by the adoption of the latest blockchain technology. This disruptive technology is key to improving accountability and transparency. This study investigates the main factors that influence educational institutions' intention to implement blockchain technology in e-learning. By combining blockchain adoption strategies, smart learning environments, and enhancing educational innovation this study develops an updated model of the technology Acceptance Model. This conceptual model was evaluated and validated using online survey-based structural analysis. The results revealed that the blockchain adoption strategy factor has a significant influence on blockchain adoption in smart learning environments. Other findings also had important significant effects on the adoption of blockchain technology. This research presents an updated technology Acceptance Model for blockchain adoption, providing guidance for decision-makers in developing smart learning environments for educational institutions in developing countries. © 2023 IEEE.

关键词： Blockchain

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