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检索条件"机构=Program in Computer Science & Technology"

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Use of E-Wallet as a Substitute for Physical Money in Transactions at Malls 4th

Use of E-Wallet as a Substitute for Physical Money in Transa...

引用

4th International Conference on Inventive Computation and Information Technologies, ICICIT 2022

作者： Kurniawan, Achmad Rizky Imam, Rafif Zhalifunnas, Rifqi Farhan Putra, Armando Rama Gaol, Ford Lumban Matsuo, Tokuro School of Information System Bina Nusantara University Alam Sutera Jakarta Indonesia Binus Graduate Program—Doctor of Computer Science Jakarta Indonesia Advanced Institute of Industrial Technology Tokyo Japan

ISBN: (纸本)9789811974014

Several challenges have emerged as a result of the rapid spread of Covid-19 in Indonesia. To combat the pandemic, the government has also issued general guidelines for avoiding/limiting direct contact with common people who do not live with them. However, in some unavoidable cases, such as cash transactions, the social distancing has not yet been followed properly. These type of challenges can be avoided by the introduction of e-wallets and e-money. This research study examines the transactions made using e-wallets and e-money and how these methods are increasing sales in public places. The proposed research study has attempted to utilize both qualitative and a quantitative method to observe the customer behavior while using e-wallet as a substitute for physical money when making a transaction in a shopping mall. The result of the proposed research work will be compared with the existing literature to provide a conclusion based on existing research data and literature. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Electronic money

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Analyzing STEM Women’s Employability: A Machine Learning Framework with Clustering and Multi-Target Classification

Analyzing STEM Women’s Employability: A Machine Learning Fr...

引用

computer sciences, Engineering, and technology Innovation (ICoCSETI), International Conference on

作者： Nadzla Andrita Intan Ghayatrie Wina Permana Sari Devi Fitrianah Esyin Chew Computer Science Department BINUS Graduate Program – Master of Computer Science Bina Nusantara University Jakarta Indonesia Computer Science Department School of Computer Science Bina Nusantara University Jakarta Indonesia Cardiff School of Technology Cardiff Metropolitan University Cardiff United Kingdom

ISBN: (数字)9798331508616

ISBN: (纸本)9798331508623

The gender gap in science, technology, Engineering, and Mathematics (STEM) fields highlights significant research opportunities, particularly in examining the employability of female graduates. This study introduces a novel machine learning framework integrating Clustering and Multi-target Classification to analyze employment waiting time and job linearity among women STEM alumni. Using K-Means Clustering and Multi-Target Logistic Regression, the framework achieved a classification accuracy of 77% and a silhouette score of 0.61, demonstrating its effectiveness in predictive analysis. Beyond these results, the framework offers a robust methodology for integrating Clustering with Classification, enabling a nuanced understanding of the employability challenges faced by women in STEM. This approach identifies key patterns in employment data, paving the way for targeted interventions and actionable insights. Furthermore, the findings aim to inform data-driven policymaking and future research to improve employability outcomes. This work contributes to addressing systemic challenges and fostering gender diversity in STEM careers while enhancing opportunities for women.

关键词： Logistic regression Technological innovation Accuracy Computational modeling Employment Linearity Machine learning Predictive analytics STEM Gender issues

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Automatic computer Shutdown with Image Processing via Webcam to Save Energy 2

Automatic Computer Shutdown with Image Processing via Webcam...

引用

2nd International Conference on Cybernetics and Innovations, ICCI 2023

作者： Chumuang, Narumol Ketcham, Mahasak Ganokratanaa, Thittaporn Pramkeaw, Patiyuth Yimyam, Worawut Chuamoo Dep. of Digital Media Technology Thailand King Mongkut's University of Technology North Bangkok Dep. of Information Technology Management Thailand King Mongkut's University of Technology Thonburi Applied Computer Science Program Bangkok Thailand King Mongkut's University of Technology Thonburi Media Technology Program Bangkok Thailand Phetchaburi Rajabhat University Dep. of Business Information Management Thailand

ISBN: (纸本)9798350336573

The purpose of this research is to help save electricity within organizations and workplaces that use computers. Due to the behavior of general users today, they do not give importance to saving electricity. The researcher has developed an automatic computer shutdown system. with image processing via a webcam By using image processing techniques (Image Processing) applied to a webcam. By using a webcam to capture the user on the computer screen. Then the images are analyzed and examined with the principles of image processing with the Face Detection technique using the algorithm of Haar-like Features to detect human faces and ROI. Define a specific area of interest The system will then check the amount of inactivity on the screen. or does not show the face image within 10 minutes, the system will automatically turn off the computer. with image processing This research can make it easier to turn off computers when not in use. and helps to save electricity for the organization or agencies as well. © 2023 IEEE.

关键词： Face recognition

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Twenty years of e-learning in health science: A bibliometric 7

Twenty years of e-learning in health science: A bibliometric

引用

7th International Conference on computer science and Computational Intelligence, CSCI 2022

作者： Maulana, Fairuz Iqbal Febriantono, M. Aldiki Raharja, Dwi Risza Budi Khaeruddin Herasmara, Ridho Computer Science Department School of Computer Science Bina Nusantara University Jakarta11480 Indonesia Diploma III Electronic Technology Vocational Study Program University of Muhammadiyah Malang Indonesia Electrical Engineering Faculty of Science and Technology Raden Rahmat Islamic University Malang Indonesia

Education about health sciences has historically been limited in the curriculum of health professionals and largely inaccessible to the public. In practice, most of the health science education is still running conventionally. Supposedly with the advancement of technology and the use of the internet everywhere, learning such as e-learning can be important, especially in the health sector. Until this research was conducted, only 514 academic documents about e-learning in health sciences were found for 20 years from 2001 to 2020, obtained in searching on the Scopus database. This study presents a comprehensive overview of studies related to E-learning in the Health sciences sector. This study uses bibliometric analysis and indexed digital methods to map scientific publications throughout the world. This research employs the Scopus database to gather information, as well as the Scopus online analysis tool and Vosviewer to show the bibliometric network. The method consists with five stages: determining search keywords, initial search results, refinement of search results, initial compilation, and data analysis. Among the most published and indexed articles by Scopus, papers published by researchers in the United States have the highest number of publications (80), followed by United Kingdom (63) and Australia with 45 academic publications. The processed data shows the pattern and trend of increasing the number of international publications in E-learning in Health sciences field, which Scopus index. © 2022 Elsevier B.V.. All rights reserved.

关键词： Publishing

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Hybrid Classical-Quantum Optimization for Ensemble Learning 9

Hybrid Classical-Quantum Optimization for Ensemble Learning

引用

9th International Conference on Advanced Informatics: Concepts, Theory and Applications, ICAICTA 2022

作者： Yulianti, Lenny Putri Santoso, Judhi Trisetyarso, Agung Surendro, Kridanto Bandung Institute of Technology School of Electrical Engineering and Informatics Bandung Indonesia Bina Nusantara University Program - Computer Science Bandung Indonesia

ISBN: (数字)9781665456685

ISBN: (纸本)9781665456685

Ensemble learning has gained attention due to its ability to improve predictive performance in classification and regression problems. However, there are several issues related to optimizing accuracy, diversity, and efficiency simultaneously in the ensemble learning process. Existing studies mostly focus on one or two of them, or focus on all three but only on the specific process of ensemble learning. Besides, the quantum approach has been expected to accelerate the optimization process while maintaining accuracy. The contribution of this study is to design a hybrid classical-quantum methodology for optimizing ensemble learning in a holistic way. This methodology combines classical (i.e. clustering, improved evaluation measures, and generalized weighted ensemble with internally tuned hyperparameters) and quantum (i.e. quantum annealing) approaches, and this methodology is analyzed to provide more optimal results. © 2022 IEEE.

关键词： Learning systems

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Sorting Red and Green Chilies by Digital Image Processing 2

Sorting Red and Green Chilies by Digital Image Processing

引用

2nd International Conference on Cybernetics and Innovations, ICCI 2023

作者： Chumuang, Narumol Ketcham, Mahasak Ganokratanaa, Thittaporn Pramkeaw, Patiyuth Chongsri, Jiratha Yimyam, Worawut Dep. of Digital Media Technology Thailand King Mongkut's University of Technology North Bangkok Dep. of Information Technology Management Thailand King Mongkut's University of Technology Thonburi Applied Computer Science Program Bangkok Thailand King Mongkut's University of Technology Thonburi Media Technology Program Bangkok Thailand Phetchaburi Rajabhat University Dep. of Business Information Management Thailand

ISBN: (纸本)9798350336573

The purpose of this research is to help save electricity within organizations and workplaces that use computers. Due to the behavior of general users today, they do not give importance to saving electricity. This work has developed an automatic computer shutdown system. with image processing via a webcam by using image processing techniques (image processing) applied to a webcam by using a webcam to capture the user on the computer screen. Then the images are analyzed and examined with the principles of image processing with the face detection technique using the algorithm of Haar -like features to detect human faces and ROI. define a specific area of interest. The system will then check the amount of inactivity on the screen. or does not show the face image within 10 minutes, the system will automatically turn off the computer. with image processing. This work can make it easier to turn off computers when not in use. and helps to save electricity for the organization or agencies as well. © 2023 IEEE.

关键词： Face recognition

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Using SYCLomatic to Migrate CUDA Code to oneAPI Adapting NVIDIA GPU

Using SYCLomatic to Migrate CUDA Code to oneAPI Adapting NVI...

引用

IEEE International Conference on Cluster Computing Workshops and Posters (CLUSTER WORKSHOPS)

作者： Wentao Liang Norihisa Fujita Ryohei Kobayashi Taisuke Boku Master's Program in Computer Science Degree Program in Systems and Information Engineering Graduate School of Science and Technology University of Tsukuba Center for Computational Sciences University of Tsukuba

ISBN: (数字)9798350383454

ISBN: (纸本)9798350383461

Nowadays, the use of accelerators in high performance computing has become more common than ever before. The most used accelerators must be the Graphics Processing Unit (GPU). It has emerged as an important component in most of the parallel computing scenarios, surpassing the capabilities of the traditional Central Processing Unit (CPU) in perspective of both performance and energy efficiency.

关键词： Codes Conferences High performance computing Graphics processing units Cluster computing Parallel processing Energy efficiency Central Processing Unit

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Comparative Analysis of Real-Time Multi-Person Pose Detection in Electrical Industrial Safety Scenarios Using YOLOv8-Pose and OpenPose 4

Comparative Analysis of Real-Time Multi-Person Pose Detectio...

引用

4th IEEE International Conference on Electronic Communications, Internet of Things and Big Data, ICEIB 2024

作者： Tsai, Shang-Te Wu, Zong-Rong Lin, Pin-Hsuan Chen, Chin-Hsiung Chien, Wei Chang, Yu-Cheng School of Art and Design Sanming University Fujian365004 China National Yunlin University of Science and Technology Department of Technical and Vocational Program in Artificial Intelligence Yunlin Taiwan National Central University Department of Business Administration Taoyuan Taiwan Commercial Industrial Vocational Senior High School Department of Electrical Engineering New Taipei Municipal Tamsui New Taipei Taiwan Lunghwa University of Science and Technology Department of Computer Information and Network Engineering Taoyuan Taiwan National Taipei University of Technology Department of Computer Science and Information Engineering Taipei Taiwan

ISBN: (纸本)9798350360721

We reviewed the application of modern technology for rapid and accurate multi-person real-time pose detection in the hazardous field of electrical engineering. We focused on two leading pose detection technologies: YOLOv8 and OpenPose. To optimize performance, we integrated these two techniques into the LSTM model for training and investigated frame rates and accuracy. © 2024 IEEE.

关键词： Accident prevention

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E-Learning Satisfaction: Analysis of the Support Factors 10

E-Learning Satisfaction: Analysis of the Support Factors

引用

10th International Conference on Information technology, computer, and Electrical Engineering, ICITACEE 2023

作者： Siswanto, Boby Alamsyah, Doni Purnama Morika, Doni Othman, Norfaridatul Akmaliah Wijaya, Billiam Christofer Adinda, Putri Giyan Bina Nusantara University Computer Science Study Program School of Computer Science Jakarta11480 Indonesia Bina Nusantara University BINUS Business School Entrepreneurship Department Jakarta11480 Indonesia Bina Nusantara University Interior Design Study Program School of Design Jakarta11480 Indonesia Universiti Teknikal Malaysia Melaka Department of Management Technology Melaka76100 Malaysia

ISBN: (纸本)9798350322729

E-learning satisfaction is an important factor in assessing the effectiveness and efficiency of distance learning. The use of Big Data technology can have a significant impact on e-learning satisfaction. The purpose of this research is to examine the implementation of big data in e-learning and the factors that can increase student e-learning satisfaction. This study uses a quantitative survey method with a questionnaire as a data collection tool. The research respondents were randomly selected e-learning students from several educational institutions that use Big Data technology in their e-learning platforms. There are 663 data collected through online questionnaires, then the data is processed through SmartPLS to test the research hypothesis. The results of the study show that the use of Big Data technology in an e-learning environment has a positive impact on student satisfaction. Several factors determine e-learning satisfaction including usability requirements, quality level, learning competence, and material relatedness. Relatedness to e-learning is more important in increasing student motivation in learning, as can be seen from the correlation value which is more dominant in forming student satisfaction. The e-learning platform must have navigation that is easy for users to understand and use. Learning content must be well-designed and follow established learning standards. The use of Big Data technology in e-learning can have a significant impact on student satisfaction and the quality of learning. Future research can develop a more personal and adaptive e-learning platform, using Big Data technology as the basis for its development. © 2023 IEEE.

关键词： E-learning

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Strengthening IT Governance in the Crypto Marketplace: Leveraging Penetration Testing and Standards Alignment

Strengthening IT Governance in the Crypto Marketplace: Lever...

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2023 International Conference on Informatics, Multimedia, Cyber and Information Systems, ICIMCIS 2023

作者： Yulianto, Semi Krisnanik, Erly Hartawan, Muhammad Syarif Bina Nusantara University Binus Graduate Program Computer Science Computer Science Department Jakarta11480 Indonesia University of Pembangunan Nasional Veteran Information System Department Jakarta12450 Indonesia University of Krisnadwipayana Faculty of Technology Jakarta13077 Indonesia Asia e University Ict Department Malaysia

ISBN: (纸本)9798350307306

This research explores the vital role of penetration testing in cybersecurity, specifically its alignment with ISO 27001:2022, COBIT 2019, and NIST CSF standards in the context of crypto asset exchange management. These sectors grapple with rapidly evolving threat landscapes, necessitating robust cybersecurity strategies. However, the integration of penetration testing with these standards remains underexamined. Through a comprehensive approach, including literature reviews, surveys, case studies, and interviews, this study investigates the incorporation of penetration testing into an organization's cybersecurity. It unveils the current state of penetration testing practices, interprets ISO 27001:2022, COBIT 2019, and NIST CSF perspectives, and pinpoints integration challenges and opportunities. This study offers practical insights and best practices for integrating penetration testing into cybersecurity frameworks by emphasizing alignment. It underscores the importance of aligning penetration testing with information security standards in the crypto asset exchange management sector, enhancing security, proactively identifying vulnerabilities, and effectively mitigating risks in the context of growing crypto asset importance. This research provides invaluable guidance for safeguarding digital assets in this evolving domain. © 2023 IEEE.

关键词： Cybersecurity

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