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IEEE International Conference on Industrial engineering and engineering management

作者： A. D. Yamanaka M.N. Young T.N. Chuahay Y. Pratseyo S. Persada R. Nadlifatin School of Graduate Studies Mapua University Manila Philippines School of Industrial Engineering and Engineering Management Mapua University Manila Philippines Department of Finance Chung Yuan University Taoyuan City Taiwan Department of Industrial Engineering and Management Yuan Ze University Taoyuan City Taiwan International Bachelor Program in Engineering Yuan Ze University Taoyuan City Taiwan Entrepreneurship Business Creation Business School Binus University West Jakarta Indonesia Department of Information Systems Institut Teknologi Sepuluh Nopember Surabaya Indonesia

ISBN: (数字)9798350386097

ISBN: (纸本)9798350386103

Portfolio selection is an important part of investment management that aims to select the right combination of assets to achieve an optimal risk-return ratio. This study integrates the Mean-Variance Theory utilizing the 30-year historical returns of the Philippine Stock Exchange. Three subsectors of the Industrial Sector were used as the investment pool. The back-test results showed that the MeanVariance portfolios of selected subsectors can outperform the industrial sector and not the market. Stakeholders must be cautious when investing in these three subsectors, considering the values obtained from the simulations. There are recommended portfolio selections wherein companies have a specific allocation that investors and financial managers can use whenever they decide to invest in these subsectors. Overall, this study offers a framework for investors to use as a guide in diversifying their stakes in the Philippine Stock Exchange.

关键词： Companies Benchmark testing Industrial engineering Market research Stakeholders Resource management Stock markets Portfolios Optimization Investment

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Mean Variance Portfolio Selection Utilizing Services Subsector’s (Media, Telecommunications, and Information Technology) 30-Year Philippine Stock Exchange Trading Data

Mean Variance Portfolio Selection Utilizing Services Subsect...

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IEEE International Conference on Industrial engineering and engineering management

作者： E.D. Salazar M.N. Young T.N. Chuahay Y. Pratseyo S. Persada R. Nadilfatin Myra F. Contreras School of Industrial Engineering and Engineering Management Mapúa University Intramuros School of Graduate Studies Mapúa University Intramuros Department of Finance Chung Yuan Christian University Taoyuan City Taiwan Department of Industrial Engineering and Management Yuan Ze University Taoyuan City Taiwan International Bachelor Program in Engineering Yuan Ze University Taoyuan City Taiwan Entrepreneurship Business Creation Business School Binus University West Jakarta Indonesia Department of Information Systems Institur Teknologi Sepuluh Nopember Surabaya Indonesia

ISBN: (数字)9798350386097

ISBN: (纸本)9798350386103

The Philippine Stock Exchange (PSE), established in 1927, has significantly evolved, especially since the 1980s with major reforms and technological advancements. This paper analyzes the performance of portfolios in the Media, Telecommunications, and Information Technology sectors listed on the PSE over a 30year span. Using mean-variance analysis, it evaluates portfolio optimization by balancing risk and return. Drawing on data from 1993 to 2022, the study examines portfolios across various risk-return frontiers (RRFs) and compares the service sector’s performance. The results highlight varying portfolio metrics across RRFs, with some showing outperformance and higher RRFs leading to diminishing returns. The study also identifies key companies with significant stock allocations, providing strategic insights for portfolio construction. These findings offer investors guidance on optimizing portfolio strategies within the PSE for better decision-making and investment outcomes.

关键词： Measurement Decision making Companies Media Telecommunications Resource management Stock markets Portfolios Optimization Investment

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Investigating the dynamic memory effect of human drivers via ON-LSTM

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Science China(Information Sciences) 2020年第9期63卷 83-93页

作者： Shengzhe DAI Zhiheng LI Li LI Dongpu CAO Xingyuan DAI Yilun LIN Department of Automation Tsinghua University Shenzhen International Graduate School Tsinghua University Department of Mechanical and Mechatronics Engineering University of Waterloo State Key Laboratory of Management and Control for Complex Systems Institute of AutomationChinese Academy of Sciences

It is a widely accepted view that considering the memory effects of historical information(driving operations) is beneficial for vehicle trajectory prediction models to improve prediction accuracy. However,many commonly used models(e.g., long short-term memory, LSTM) can only implicitly simulate memory effects, but lack effective mechanisms to capture memory effects from sequence data and estimate their effective time range(ETR). This shortage makes it hard to dynamically configure the most suitable length of used historical information according to the current driving behavior, which harms the good understanding of vehicle motion. To address this problem, we propose a modified trajectory prediction model based on ordered neuron LSTM(ON-LSTM). We demonstrate the feasibility of ETR estimation based on ON-LSTM and propose an ETR estimation method. We estimate the ETR of driving fluctuations and lane change operations on the NGSIM I-80 dataset. The experiment results prove that the proposed method can well capture the memory effects during trajectory prediction. Moreover, the estimated ETR values are in agreement with our intuitions.

关键词： driving behavior memory effect trajectory prediction historical information ON-LSTM

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

Realizing Global Citizen Solutions for Sustainable Developme...

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International Symposium on Communications and Information Technologies (ISCIT)

作者： Thanachot Sae-Jia Natt Leelawat Jing Tang Rie Murakami Yuki Taoka Eri Ota Proadpran Punyabukkana Department of Environmental Engineering Faculty of Engineering Chulalonkorn University Bangkok Thailand Department of Industrial Engineering Faculty of Engineering Chulalongkorn University Bangkok Thailand Disaster and Risk Management Information Systems Research Unit Chulalongkorn University Bangkok Thailand Graduate School of System Design and Management Keio University Yokohama Japan Faculty of Engineering International School of Engineering Chulakongkorn University 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 Department of Computer Engineering Faculty of Engineering Chulalongkorn University Bangkok Thailand

ISBN: (数字)9798350353952

ISBN: (纸本)9798350353969

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.

关键词： Waste management Knowledge engineering Collaboration Transportation Focusing Information and communication technology Cultural differences Global communication Sustainable development

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Stacking ensemble approach to diagnosing the disease of diabetes

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Informatics in Medicine Unlocked 2024年 44卷

作者： Daza, Alfredo Ponce Sánchez, Carlos Fidel Apaza-Perez, Gonzalo Pinto, Juan Zavaleta Ramos, Karoline Faculty of Engineering and Architecture School of Systems Engineering Universidad César Vallejo Lima Peru Faculty of Industrial and Systems Engineering School of Industrial Engineering Universidad Nacional de Ingeniería Lima Peru Graduate School Professional School of Systems Engineering Universidad Nacional del Altiplano UNAP Puno Peru Faculty of Systems Engineering Professional School of System Engineering Universidad Andina Néstor Cáceres Velasquez Puno Peru Faculty of Business Sciences School of Management Universidad César Vallejo Trujillo Peru

Background: Diabetes is a very common disease today and has acquired a worrying focus in the field of public health globally, in fact, it is estimated that the number of people with diabetes worldwide has reached 415 million. Objective: Propose a method and 4 combined models based on Stacking ensemble to diagnose Diabetes. In addition, a web interface was developed with the best model proposed in this study. Methods: The dataset collected from the Diabetes Dataset composed of 768 patient records was used. The data was then pre-processed using the Python programming language. To balance the data, it was divided into 4 values and an oversampling method was applied to distribute the data proportionally. Then, divisions were made on the balanced data using the cross-validation method for data training, and the models were calibrated. Regarding the development of base algorithms, 7 independent algorithms were used, and 4 combined algorithms based on Stacking were proposed, and finally obtain the evaluation of the model with their respective metrics. Results: Stacking 1A (Logistic regression) with Oversampling reached the best value of Accuracy = 91.5 %, Sensitivity = 91.6 %, F1-Score = 91.49 % and Precision = 91.5 %, while with respect to the metric ROC Curve, Stacking 1A (Logistic regression) with Oversampling, Stacking 2A (Random Forest) with oversampling, and Random Forest (Independent) reached the best percentage, this being 97 %. Conclusions: Implementing 4 stacking models using the oversampling method, helps to make an adequate diagnosis of diabetes. Therefore, by using the combined method, an improvement in diabetes prediction was observed, surpassing the performance of the independent algorithms used. © 2023 The Authors

关键词： Diabetes Hyperparameters Machine learning Oversampling Prediction Stacking

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Awareness of Disaster Risk and Preparedness: Insights from a Survey of Children and Adults in Thailand

Awareness of Disaster Risk and Preparedness: Insights from a...

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International Symposium on Communications and Information Technologies (ISCIT)

作者： Ampan Laosunthara Natt Leelawat Takumi Ohashi Titaya Sararit Mongkonkorn Srivichai Jing Tang School of Environment and Society Tokyo Institute of Technology Tokyo Japan Department of Industrial Engineering Faculty of Engineering Chulalongkorn University Bangkok Thailand Disaster and Risk Management Information Systems Research Unit Chulalongkorn University Bangkok Thailand Graduate School of System Design and Management Keio University Kanagawa Japan Department of Transdisciplinary Science and Engineering Tokyo Institute of Technology Tokyo Japan Faculty of Architecture Chiangmai University Chiangmai Thailand Department of Civil Engineering Faculty of Engineering Rajamangala University of Technology Lanna Chiangrai Thailand Faculty of Engineering International School of Engineering Chulakongkorn University Bangkok Thailand

ISBN: (数字)9798350353952

ISBN: (纸本)9798350353969

Enhancing disaster awareness and preparedness is crucial for building resilient societies. This study comprehensively assessed the levels of disaster awareness and preparedness among children and adults in Thailand through qualitative and quantitative surveys. Children strongly emphasized the importance of disaster education in school curricula, leveraging multimedia channels for risk communication, and implementing early warning systems. In contrast, adults exhibited a greater understanding of the significance of business continuity and disaster management technologies. These findings revealed disparities in disaster awareness across age groups. The insights from this study suggest age-specific engineering system approaches to information dissemination, contributing to the development of inclusive disaster preparedness strategies that incorporate diverse stakeholder perspectives. Children highlighted the need for practical training on survival skills, accessible disaster communication through SMS alerts, and monitoring systems for timely information dissemination. Adults, on the other hand, placed greater importance on business continuity planning and recognized the usefulness of technologies like satellite imagery for disaster management. By identifying these gaps and areas for improvement, this research provides valuable guidance for tailoring interventions, fostering a culture of preparedness, and harnessing technological solutions that resonate with the needs and concerns of different age cohorts within Thai society.

关键词： Training Surveys Disasters Disaster management Satellite images Planning Business continuity Stakeholders Multimedia communication Resilience

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Prediction of Diabetes Disease Based on Stacking Ensemble Using Oversampling Method and Hyperparameters

SSRN

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SSRN 2023年

作者： Vergaray, Alfredo Daza Ponce Sánchez, Carlos Fidel Apaza Pérez, Oscar Gonzalo Pinto Larico, Juan Carlos Ramos, Karoline Zavaleta Faculty of Engineering and Architecture School of Systems Engineering Universidad César Vallejo Lima Peru Faculty of Industrial and Systems Engineering School of Industrial Engineering Universidad Nacional de Ingeniería Lima Peru Graduate School Professional School of Systems Engineering Universidad Nacional del Altiplano UNAP Puno Peru Faculty of Systems Engineering Professional School of System Engineering Universidad Andina Néstor Cáceres Velasquez Puno Peru Faculty of Business Sciences School of Management Universidad César Vallejo Trujillo Peru

Background: Diabetes is a very common disease today and has acquired a worrying focus in the field of public health globally, in fact, it is estimated that the number of people with diabetes worldwide has reached 415 ***: Propose a method and 4 combined models based on Stacking in order to predict diabetes. In addition, a web interface was developed with the best model proposed in this ***: The dataset collected from the Diabetes Dataset composed of 768 patient records was used. The data was then pre-processed using the Python programming language. To balance the data, it was divided into 4 values and an oversampling method was applied to distribute the data proportionally. Then, divisions were made on the balanced data using the cross-validation method for data training, and the models were calibrated. Regarding the development of base algorithms, 7 independent algorithms were used, and 4 combined algorithms based on Stacking were proposed, and finally obtain the evaluation of the model with their respective ***: Stacking 1A (Logistic regression) with Oversampling reached the best value of Accuracy=91.50%, Sensitivity=91.60%, F1-Score=91.49% and Precision= 91.50%, while with respect to the metric ROC Curve, Stacking 1A (Logistic regression) with Oversampling, Stacking 2A (Random Forest) with oversampling, and Random Forest (Independent) reached the best percentage, this being 97.00%.Conclusions: Implementing 4 stacking models using the oversampling method, helps to make an adequate diagnosis of diabetes. Therefore, by using the combined method, an improvement in diabetes prediction was observed, surpassing the performance of the independent algorithms used. © 2023, The Authors. All rights reserved.

关键词： Forecasting

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Portfolio Selection and Comparative Portfolio Analysis of Transportation Services, Hotel and Leisure, and Education Subsectors Against Service Sector in the Philippine Market Using Mean-variance Model

Portfolio Selection and Comparative Portfolio Analysis of Tr...

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IEEE International Conference on Industrial engineering and engineering management

作者： E. L. Cruz M. N. Young T. N. Chuahay Y. Prasetyo S. Persada R. Nadilfatin M. Contreras School of Industrial Engineering and Engineering Management Mapua University Manila Philippines School of Graduate Studies Mapua University Manila Philippines Department of Finance Chung Yuan Christian University Taoyuan City Taiwan Department of Industrial Engineering and Management Yuan Ze University Taoyuan City Taiwan International Bachelor Program in Engineering Yuan Ze University Taoyuan City Taiwan Entrepreneurship Business Creation Business School Binus University West Jakarta Indonesia Department of Information Systems Institut Teknologi Sepuluh Nopember Surabaya Indonesia

ISBN: (数字)9798350386097

ISBN: (纸本)9798350386103

This paper presents a framework for portfolio selection in the transportation services, hotel and leisure, and education subsectors of the Philippine market using the mean-variance model. Using the service sector and the broader market as benchmarks, this study spans 7,670 test days from January 1, 1993, to December 31, 2022, identifying optimal risk-return factors (RRFs) of $\mathbf{0. 4}$ for transportation, 0.2 for hotel and leisure, and 0.3 for education. Furthermore, the higher percentage allocations the investors are recommended to invest in are International Container Terminal Services, Inc., Waterfront Philippines, Incorporated, and Far Eastern University, Incorporated. Paired t-test results, with p-values below 0.01 and 0.05, indicate these subsectors can outperform the service sector. The study also conducted a comparative analysis with 30-year historical data to crisis periods like the Global Financial Crisis (GFC) and the COVID-19 pandemic, exhibiting distinct performance trends and emphasizing the need for tailored strategies during economic disruptions. The findings of this research may provide an alternative portfolio selection model for investors seeking to optimize their investment portfolios.

关键词： COVID-19 Analytical models Pandemics Education Transportation Stability analysis Resource management Stock markets Portfolios Resilience

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Strategic legislation for the promotion of university–industry collaborations: a case study of Taiwan

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Journal of Technology Transfer 2025年第1期50卷 304-344页

作者： Truong, Thanh Hue Lin, Bou-Wen Tung, Ching-Pin International Degree Program in Climate Change and Sustainable Development National Taiwan University No. 1 Sec. 4 Roosevelt Road Taipei106 Taiwan Research Center for Future Earth National Taiwan University No. 1 Sec. 4 Roosevelt Road Taipei106 Taiwan Graduate Institute of Business Administration College of Management National Taiwan University No. 1 Sec. 4 Roosevelt Road Taipei106 Taiwan National Applied Research Laboratories No. 106 Sec. 2 Heping E. Rd. Da’an Dist. Taipei City106214 Taiwan Department of Bioenvironmental Systems Engineering National Taiwan University No. 1 Sec. 4 Roosevelt Road Taipei106 Taiwan

The strategic utilization of technology to enhance industrial competitiveness and product quality is pivotal for economic growth. As universities own more inventions, collaborative efforts between industry and academia become essential for regional competitiveness and overall economic advancement. This study explores Taiwan’s systematic approach to upgrading its infrastructure, emphasizing the significance of University–Industry Collaborations (UIC) in realizing Industry 4.0. Government strategies and policy decisions emerge as key drivers in fostering successful collaborative projects between industry and university teams. The relaxation of restrictions, particularly related to part-time teachers and technology transfer, along with the promotion of corporate programs, effective use of public funding, and the development of an innovative digital platform system for UIC, collectively contribute to establishing a robust university–industry cooperation mechanism. This mechanism has contributed to Taiwan’s move towards new digital advances in innovation and entrepreneurship, fostering industrial leadership and efficient governance. © The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2024.

关键词： Technology transfer

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Implementation of an Efficient IoT Enabled Automated Paralysis Healthcare System 8

Implementation of an Efficient IoT Enabled Automated Paralys...

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8th IEEE International Conference on engineering Technologies and Applied Sciences, ICETAS 2023

作者： Annepu, Visalakshi Jameel Al-Tamimi, Adnan Naji Aljibori, H.S.S. Challa, Naga Raju Bagadi, Kalapraveen Mohammed, M.N. Abdullah, Oday I. Alfiras, M. Abbas Helmi, Rabab Alayham School of Comp. Science & Eng. VIT-AP University Amaravati India College of Technical Engineering AI-Farahidi University Baghdad Iraq College of Engineering University of Warith Al-Anbiyaa Karbala Iraq Bapatla Engineering College Dept. of Elec. and Comm. Eng. Baptla India College of Engineering Gulf University Mechanical Engineering Department Sanad26489 Bahrain University of Baghdad Dept of Energy Engineering Iraq College of Engineering Gulf University Mechanical Engineering Dept Sanad26489 Bahrain Hamburg University of Technology Institute of Laser and Systems Technologies Hamburg Germany College of Engineering Gulf University Electrical and Electronic Engineering Department Sanad26489 Bahrain School of Graduate Studies Management and Science University Shah Alam Selangor Malaysia

ISBN: (纸本)9798350327090

This system aims to provide comprehensive care to individuals with paralysis, including symptom monitoring, medical treatment, and rehabilitation. The IoT-based system comprises interconnected devices, such as sensors, wearables, and mobile apps that communicate with one another and with healthcare providers. The system can track patients' vital signs, activity levels, and medication adherence, and provide immediate feedback to healthcare providers. Additionally, the system can aid with rehabilitation exercises, send reminders, and gather data on progress to enhance treatment outcomes. The system's intelligent analytics can also assist healthcare providers in detecting patterns in patient behavior and tailoring treatment plans more effectively. Overall, an IoT-based paralysis healthcare system has the potential to transform healthcare delivery by offering personalized, real-time care and monitoring to individuals with paralysis. © 2023 IEEE.

关键词： Internet of things

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