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2024 IEEE International Conference on systems, Man, and Cybernetics, SMC 2024

作者： Kerk, Yi Wen Tay, Kai Meng Jong, Chian Haur Chai, Chee Shee Lim, Chee Peng Universiti Kebangsaan Malaysia Faculty of Information Science & Technology Bangi43600 Malaysia Universiti Kebangsaan Malaysia Faculty of Engineering Kota Samarahan94300 Malaysia School of Engineering & Technology Universty of Technology Sarawak Sibu96000 Malaysia Universiti Malaysia Sarawak Faculty of Medicine & Health Sciences Kota Samarahan94300 Malaysia Institute for Intelligent Systems Research and Innovation Deakin University GeelongVIC3216 Australia

ISBN: (纸本)9781665410205

Leveraging the concept of Failure Mode and Effect Analysis (FMEA), we propose a simple and systematic approach, namely Transmission Cause and Effect Analysis (TCEA), to achieve a defined goal of reducing transmission risk through effective preventive and control actions in real-world environments. Specifically, the transmission risk of an infectious disease (e.g., COVID-19) is perceived as a combination of the presence of a transmission agent (e.g., SARS-CoV-2 virus or its variants) and the requisite factors that lead to infection of humans and the associated aftermath of infection. TCEA adopts a causal map to represent all possible transmission risks via a brainstorming process. Next, appropriate preventive and control actions associated with each transmission risk are identified. Similar to FMEA, a Risk Priority Number model with Severity, Occurrence, and Detection ratings is adopted for analysis, prioritization, and decision-making. To demonstrate the usefulness of TCEA, a real-world case study on COVID-19 is conducted. The empirical results indicate that TCEA provide a simple, systematic and easy-to-implement approach to effectively analyze and manage transmission risks of COVID-19 in non-healthcare workplaces. © 2024 IEEE.

关键词： COVID-19

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ChatGPT: Applications, Opportunities, and Threats

ChatGPT: Applications, Opportunities, and Threats

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2023 systems and Information engineering Design Symposium, SIEDS 2023

作者： Bahrini, Aram Khamoshifar, Mohammadsadra Abbasimehr, Hossein Riggs, Robert J. Esmaeili, Maryam Majdabadkohne, Rastin Mastali Pasehvar, Morteza University of Virginia Department of Systems and Information Engineering CharlottesvilleVA United States Iran University of Science and Technology School of Computer Engineering Tehran Iran Azarbaijan Shahid Madani University Faculty of Information Technology and Computer Engineering Tabriz Iran Alzahra University Faculty of Engineering Department of Industrial Engineering Tehran Iran The American University Faculty of Medical Sciences Department of Medicine Managua Nicaragua Islamic Azad University Faculty of Engineering Department of Industrial Engineering Tehran Iran

ISBN: (纸本)9798350300642

Developed by OpenAI, ChatGPT (Conditional Generative Pre-trained Transformer) is an artificial intelligence technology that is fine-tuned using supervised machine learning and reinforcement learning techniques, allowing a computer to generate natural language conversation fully autonomously. ChatGPT is built on the transformer architecture and trained on millions of conversations from various sources. The system combines the power of pre-trained deep learning models with a programmability layer to provide a strong base for generating natural language conversations. In this study, after reviewing the existing literature, we examine the applications, opportunities, and threats of ChatGPT in 10 main domains, providing detailed examples for the business and industry as well as education. We also conducted an experimental study, checking the effectiveness and comparing the performances of GPT-3.5 and GPT-4, and found that the latter performs significantly better. Despite its exceptional ability to generate natural-sounding responses, the authors believe that ChatGPT does not possess the same level of understanding, empathy, and creativity as a human and cannot fully replace them in most situations. © 2023 IEEE.

关键词： Deep learning

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Encryption Algorithm for Securing Non-Disclosure Agreements in Outsourcing Offshore Software Maintenance

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Computers, Materials & Continua 2022年第11期73卷 3827-3845页

作者： Atif Ikram Masita Abdul Jalil Amir Bin Ngah Nadeem Iqbal Nazri Kama Azri Azmi Ahmad Salman Khan Yasir Mahmood Assad Alzayed Faculty of Ocean Engineering Technology and Informatics University Malaysia TerengganuKuala TerengganuMalaysia Department of Computer Science&Information Technology Faculty of Information TechnologyThe University of LahoreLahore54000Pakistan Department of Software Engineering Faculty of Information TechnologyThe University of LahoreLahore54000Pakistan Advanced Informatics Department Razak Faculty of Technology and InformaticsUniversiti Teknologi Malaysia54100Kuala LumpurMalaysia Computer Science and Information Systems Department College of Business Studies Public Authority for Applied Education and Training(PAAET)AdailiyaKuwait

Properly created and securely communicated,non-disclosure agreement(NDA)can resolve most of the common disputes related to outsourcing of offshore software maintenance(OSMO).Occasionally,these NDAs are in the form of *** the work is done offshore,these agreements or images must be shared through the Internet or stored over the *** breach of privacy,on the other hand,is a potential threat for the image owners as both the Internet and cloud servers are not void of *** article proposes a novel algorithm for securing the NDAs in the form of *** an agreement is signed between the two parties,it will be encrypted before sending to the cloud server or travelling through the public network,the *** the image is input to the algorithm,its pixels would be scrambled through the set of randomly generated rectangles for an arbitrary amount of *** confusion effects have been realized through an XOR operation between the confused image,and chaotic ***,5D multi-wing hyperchaotic system has been employed to spawn the chaotic vectors due to good properties of chaoticity it *** machine experimentation and the security analysis through a comprehensive set of validation metric vividly demonstrate the robustness,defiance to the multifarious threats and the prospects for some real-world application of the proposed encryption algorithm for the NDA images.

关键词： Non-disclosure agreement encryption decryption secret key chaoticmap confusion diffusion

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Integration of Machine Learning and Kalman Filter Approach for Fingerprint Indoor Positioning 20

Integration of Machine Learning and Kalman Filter Approach f...

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20th International Conference on Electrical engineering/Electronics, Computer, Telecommunications and Information technology, ECTI-CON 2023

作者： Rithanasophon, Thanasit Wannaboon, Chatchai Intelligent Electronics Systems Research Laboratory Faculty of Engineering Thai-Nichi Institute of Technology Patthanakarn Rd. Suanlaung Bangkok10250 Thailand

ISBN: (纸本)9798350310467

Fingerprint-based indoor positioning systems are simple and widely used to determine the location of a device inside a building or other enclosed area. However, the accuracy and reliability are still a major concern due to the turbulence in the environment and the presence of noise in the data. This paper presents a machine learning integrated with Kalman filter approach for improving the accuracy of fingerprint-based indoor positioning systems. The proposed approach combines the power of machine learning techniques for feature extraction and classification with the noise-filtering capabilities of the Kalman filter. Implementation is achieved by a real-world dataset collected from multiple Bluetooth low energy access points. The experiment results indicate that the proposed approach significantly improves the accuracy of fingerprint-based indoor positioning compared to traditional machine learning approaches. This study also offers a potential of cost-effective and high accuracy algorithm for the indoor positioning applications. © 2023 IEEE.

关键词： Kalman filters

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USTW Vs. STW: A Comparative Analysis for Exam Question Classification based on Bloom’s Taxonomy

Mendel

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Mendel 2022年第2期28卷 25-40页

作者： Gani, Mohammed Osman Ayyasamy, Ramesh Kumar Fui, Tien Sangodiah, Anbuselvan Faculty of Information and Communication Technology Universiti Tunku Abdul Rahman Kampar Malaysia Department of Information Systems Faculty of Information and Communication Technology Universiti Tunku Abdul Rahman Kampar Malaysia School of Computing Faculty of Computing and Engineering Quest International University Perak Ipoh Malaysia

Bloom’s Taxonomy (BT) is widely used in educational institutions to produce high-quality exam papers to evaluate students’ knowledge at different cognitive levels. However, manual question labeling takes a long time, and not all evaluators are familiar with BT. The researchers worked to automate the exam question classification process based on BT as a solution. Enhancement in term weighting is one of the ways to increase classification accuracy while working with text data. However, all the past work on the term weighting in exam question classification focused on unsupervised term weighting (USTW) schemes. The supervised term weighting (STW) schemes showed effectiveness in text classification but were not addressed in past studies of exam question classification. As a result, this study focused on the effectiveness of STW in classifying exam questions using BT. Hence, this research performed a comparative analysis between the USTW schemes and STW for exam question classification. The STW schemes used in this study are TF-ICF, TF-IDF-ICF, and TF-IDF-ICSDF, whereas the USTW schemes used for comparison are TF-IDF, ETF-IDF, and TFPOS-IDF. This study used Support Vector Machines, Naïve Bayes, and Multilayer Perceptron to train the models. Accuracy and F1 score were used in this study to evaluate the classification results. The experiment results showed that overall, the STW scheme TF-ICF outperformed all the other schemes, followed by the USTW scheme ETF-IDF. Both the ETF-IDF and TFPOS-IDF outperformed standard TF-IDF. The outcome of this study indicates the future research direction where the combination of STW and USTW schemes may increase the accuracy of BT-based exam question classification. © 2022, Brno University of technology. All rights reserved.

关键词： Taxonomies

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Data-Driven State Feedback Gain Update Based on Model Matching in Frequency Domain

Data-Driven State Feedback Gain Update Based on Model Matchi...

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2024 International Conference on Advanced Mechatronic systems, ICAMechS 2024

作者： Matsui, Yoshihiro Ayano, Hideki Masuda, Shiro Nakano, Kazushi Fukuoka Institute of Technology Faculty of Engineering Fukuoka Fukuoka Japan Tokyo College National Institute of Technology Department of Electrical Engineering Hachioji Tokyo Japan Tokyo Metropolitan University Graduate School of Systems Design Engineering Hino Tokyo Japan The University of Electro-Communications Chofu Tokyo Japan

ISBN: (纸本)9798350366204

This paper presents a method for updating the state feedback gain of an LTI single-input nth-order system using data-driven techniques. The goal is to match the closed-loop system to a desired reference model, which is represented by a complementary sensitivity function. To achieve this, a new model matching error is introduced. The appropriate gain can be determined using the least squares method in the frequency domain, based on closed-loop data obtained from an improperly tuned system due to model errors. Although the proposed method is specialized for updating the state feedback gain, it can perform gain updates that take into account the effects of noise at an extremely low computational cost. The method's effectiveness is demonstrated through numerical experiments. © 2024 IEEE.

关键词： State feedback

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Implementation of an Automated Vegetation Drought Monitoring System Based on Long-Term Satellite Remote Sensing 11

Implementation of an Automated Vegetation Drought Monitoring...

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11th International Conference on Agro-Geoinformatics, Agro-Geoinformatics 2023

作者： Yue, Zichen Mei, Xin Zhong, Shaobo Hubei University Faculty of Resources and Environmental Science Wuhan China Institute of Urban Systems Engineering Beijing Academy of Science and Technology Beijing China

ISBN: (纸本)9798350303513

Droughts are a severe problem globally, and although satellite remote sensing is an effective tool for monitoring drought, current methods require manual intervention and operation to detect drought. This paper proposes a full-automatic drought monitoring system(FADMS) consisting of four main phases: remote sensing data acquisition and preprocessing, drought index calculation and analysis, time-series image service publishing, and analysis and visualization. This system uses Python-based automation scripts, which can automatically download and preprocess satellite remote sensing data efficiently and reliably. We also employed Web Service technology to serve different vegetation drought index algorithms such as Normalized Difference Vegetation Index (NDVI), Vegetation Condition Index (VCI), Temperature Condition Index (TCI), and Temperature Vegetation Dryness Index (TVDI). Moreover, we designed a time-series image service publishing architecture based on GeoServer and ImageMosaic plug-in, enabling the rapid publication of long-term vegetation drought products. Lastly, we used the GIS spatial statistical analysis module to analyze and visualize drought characteristics such as grade, scope, and duration. To demonstrate the effectiveness of our approach, we conducted experiments using MODIS-derived products from 2000 to 2022 in China's northern region. The results confirmed that FADMS could detect and monitor vegetation droughts accurately and timely, identifying drought events' spatiotemporal distribution and evolution trends. FADMS significantly enhances the efficiency and accuracy of vegetation drought monitoring and is highly reliable and practical. © 2023 IEEE.

关键词： Time series

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Dynamic Value Stream Mapping—How Industry 4.0 Can Help Us to Learn to See Better 9th

Dynamic Value Stream Mapping—How Industry 4.0 Can Help Us t...

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Production Processes and Product Evolution in the Age of Disruption - Proceedings of the 9th Changeable, Agile, Reconfigurable and Virtual Production Conference CARV2023 and the 11th World Mass Customization and Personalization Conference MCPC2023

作者： Tomidei, Laura Sick, Nathalie Guertler, Matthias Schallow, Julian Lenze, David Deuse, Jochen Faculty of Engineering and IT Centre for Advanced Manufacturing University of Technology Sydney Sydney Australia Institute of Production Systems Technical University Dortmund Dortmund Germany

ISBN: (纸本)9783031348204

Companies have been adopting lean management for decades to increase productivity, customer satisfaction and profitability. A foundational and powerful tool in lean management is value stream mapping (VSM). VSM is still widely used as a static pen and paper-based tool. However, as industrial processes have become more advanced and digitalized, static VSM methods struggle to handle the complexities related to flexible and changeable elements in production. Factors including increasing range of parts, processes, and dynamic elements challenge the economic application of static VSM approaches. In the meantime, wireless connectivity together with low-cost sensors in the context of Industry 4.0 have enabled advanced industrial infrastructures, allowing for dynamic VSM (DVSM) approaches. While the potential benefits are promising, research and application in this interdisciplinary field are just evolving. Addressing this gap, this study sets out to map the DVS research landscape. More specifically, we (1) identify the requirements to overcome the limitations of static VSM, (2) analyze and structure existing DVSM approaches, (3) map DVSM approaches against requirements and (4) derive a research agenda for developing DVSM approaches. This study contributes by providing requirements for and a taxonomy of existing DVSM approaches, guiding the development of new DVSM approaches. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Lean production

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Realizing Global Citizen Solutions for Sustainable Development Goals: A Collaborative engineering Course Between Thai and Japanese Students 23

Realizing Global Citizen Solutions for Sustainable Developme...

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23rd International Symposium on Communications and Information Technologies, ISCIT 2024

作者： Sae-Jia, Thanachot Leelawat, Natt Tang, Jing Murakami, Rie Taoka, Yuki Ota, Eri Punyabukkana, Proadpran Chulalonkorn University Faculty of Engineering Department of Environmental Engineering Bangkok Thailand Chulalongkorn University Faculty of Engineering Department of Industrial Engineering Bangkok Thailand Chulalongkorn University Disaster and Risk Management Information Systems Research Unit Bangkok Thailand Graduate School of System Design and Management Keio University Yokohama Japan International School of Engineering Chulakongkorn University Faculty of Engineering Bangkok Thailand Global Education Section Center for Entrepreneurship Education Tokyo Institute of Technology Tokyo Japan School of Environment and Society Tokyo Institute of Technology Tokyo Japan Chulalongkorn University Faculty of Engineering Department of Computer Engineering Bangkok Thailand

ISBN: (纸本)9798350353952

One of the problems faced by engineering and science students is focusing solely on technical knowledge while needing more cultural context. In today's interconnected world, addressing global challenges necessitates collaborative efforts from individuals across nations. Accordingly, a joint course between Chulalongkorn University in Thailand and the Tokyo Institute of technology in Japan has been established. The recent theme of the course, 'Gamification towards Sustainable Development Goals (SDGs),' aimed to foster global citizenship and address SDGs through multicultural collaboration. This study examines the similarities and differences in problem identification between Thai and Japanese student groups participating in the course. Data was collected from discussions, presentations, and group assignments throughout the course. The findings indicate that while both groups share common concerns, such as waste management, language barriers, and transportation issues, their perspectives and proposed solutions are influenced by cultural characteristics. Thai students emphasized infrastructural inadequacies and local traditions, whereas Japanese students focused on efficiency and the impacts of tourism. The study highlights the importance of understanding cultural nuances in collaborative international projects to achieve effective and innovative solutions to global challenges. © 2024 IEEE.

关键词： Sustainable development goals

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Outage Prediction and Improvement in 6G for UAV Swarm Relays Using Machine Learning

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Progress In Electromagnetics Research B 2024年 107卷 33-45页

作者： Khalil, Hisham Ali, Gauhar Rahman, Saeed Ur Asim, Muhammad Affendi, Mohammed El Department of Intelligent Systems Faculty of Information Technology University of Lahore Pakistan EIAS Data Science and Block chain Lab College of Computer and Information Sciences Prince Sultan University Riyadh11586 Saudi Arabia School of Electronic Engineering Xidian University Xi’an China

The issue of signal outages in sub-THz frequency communication for future 6G networks is addressed by this research. A machine learning method is proposed, employing Random Forest and K-Means algorithms to predict the optimal frequency band and outage probabilities for UAV relays. Both space and frequency diversity are explored to enhance signal strength, and metasurface-carrying UAVs are introduced with a 16 × 16 mm2 design. This design significantly reduces the predicted outage probability from 0.1% to 0.0178%. Finally, triangular and hexagonal UAV swarm formations with metasurfaces are investigated, demonstrating improved performance through heatmap results. © (2024), (Electromagnetics Academy). All rights reserved.

关键词： Unmanned aerial vehicles (UAV)

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