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Reducing dropout rate through a deep learning model for sustainable education: long-term tracking of learning outcomes of an undergraduate cohort from 2018 to 2021

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Smart Learning Environments 2023年第1期10卷 1-16页

作者： Shiao, Yi-Tzone Chen, Cheng-Huan Wu, Ke-Fei Chen, Bae-Ling Chou, Yu-Hui Wu, Trong-Neng Center of Institutional Research and Development Asia University Taichung City Taiwan ROC Department of Education National Taichung University of Education Taichung City Taiwan ROC Department of M-Commerce and Multimedia Applications Asia University Taichung City Taiwan ROC Department of Business Management National Taichung University of Science and Technology Taichung City Taiwan ROC Doctoral Program of Intelligent Engineering National Taichung University of Science and Technology Taichung City Taiwan ROC Department of Healthcare Administration Asia University Taichung City Taiwan ROC

In recent years, initiatives and the resulting application of precision education have been applied with increasing frequency in Taiwan; the accompanying discourse has focused on identifying potential applications for artificial intelligence and how to use learning analytics to improve teaching quality and learning outcomes. This study used the established dropout risk prediction model to improve student learning effectiveness. The model was based on the academic portfolios of past students and built with statistical learning and deep learning methods. This study used this model to predict the dropout risk of 2205 freshmen enrolled in the fall semester of 2018 (graduated in June 2022) in the field of sustainable education. A total of 176 students with a dropout risk of more than 20% were considered high-risk students. After tracking and the appropriate guidance, the dropout risk of 91 students fell from > 20% to < 20%. To discuss the results from the perspective of gender and financial disadvantages, the improvement rate of the dropout risk for male students was 10.2% better than that of female students at 2.9%. The improvement rate in dropout risk for students with disadvantageous financial situations was as high as 12.0%, surpassing the 5.9% rate among general students. Overall, the dropout rate in the second year of the 2018 freshman cohort was lower than that of the 2016 and 2017 freshman cohorts. A predictive model established by statistical learning and deep learning methods was used as a tool to promote precision education, accurately and efficiently identifying students who are having difficulty learning, as well as leading to a better understanding of AI (artificial intelligence) in smart learning for sustainable education.

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Evolutionary Algorithms for Optimal Operation of Gas Networks

SSRN

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SSRN 2023年

作者： Lence, Barbara J. Moosavian, Naser Lee, Andy J. Rivera, Daniela D. University of British Columbia Department of Civil Engineering 6250 Applied Science Lane VancouverBCV2T 1Z4 Canada Department of Civil Engineering Integrated Water Management University of British Columbia 6250 Applied Science Lane VancouverBCV2T 1Z4 Canada Metro Vancouver Metrotower III 4515 Central Boulevard BurnabyBCV5R 6G4 Canada Integrated Water Management Program University of British Columbia 6250 Applied Science Lane VancouverBCV2T 1Z4 Canada

This study presents an analysis of the use of Evolutionary Algorithms for determining the optimal operating strategy of gas transmission networks that minimize the total operating cost of the gas network and identify the optimal demand and supply flows. In comparison with water distribution networks, gas transmission networks, are complex due to their use of compressor equipment and the large lengths and diameters of their pipelines. The optimal operations model minimizes the gas purchase cost, while satisfying all system demands and other operating constraints in a network. The constraints of the gas network are flow continuity at nodes and energy relationships in pipelines, along with constraints associated with the contracted gas flow rate and pressure requirements at each node, and the power limits and flow requirements of *** heuristic algorithms, namely the Genetic Algorithm (GA), Differential Evolution Algorithm (DE), Artificial Bee Colony Algorithm (ABC), and Covariance Matrix Adaptation Evolution Strategy (CMA-ES), are applied to optimize the Belgium Gas Transmission Network. These are compared in terms of their computational burden, and the quality of the obtained solutions with respect to practical management concerns. Among the four algorithms, CMA-ES is found to be most efficient at achieving the global optimum, consistently meeting pressure and flow requirements, while conserving compressor power. © 2023, The Authors. All rights reserved.

关键词： Cost benefit analysis

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Innovative Solutions in Breath Alcohol Measurement for Improving Road Safety

Innovative Solutions in Breath Alcohol Measurement for Impro...

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Cybernetics and Innovations (ICCI), International Conference on

作者： Patiyuth Pramkeaw Pimyada Suksomboon Warit Leangruttananon Thittaporn Ganokratanaa Davids Makararpong Narumol Chumuang Worawut Yimyam Chayawee Angsusingha Adil Farooq Mahasak Ketcham Media Technology Program King Mongkut's University of Technology Thonburi Bangkok Thailand Faculty of Science King Mongkut's University of Technology Thonburi Bangkok Thailand Thailand Business school The University of the Thai Chamber of Commerce Bangkok Thailand Digital Media Technology Muban Chombueng Rajabhat University Ratchaburi Thailand Business Information Management Phetchaburi Rajabhat University Phetchaburi Thailand The national broadcasting and Telecommunications Commission Bangkok Thailand Department of Electronic Engineering Maynooth University Ireland Management of Information Systems King Mongkut's University of Technology North Bangkok Bangkok Thailand

ISBN: (数字)9798331533267

ISBN: (纸本)9798331533274

This research presents the development and evaluation of a breath alcohol measurement device utilizing the MQ-3 alcohol sensor and an Arduino Nano-based control system. The primary objective was to design an accurate and reliable system for detecting breath alcohol concentration, with real-time feedback provided through an OLED display and an active buzzer for alerts. The device operates by measuring the alcohol concentration in the breath and converting the sensor data into parts per million (ppm). When the alcohol concentration exceeds the predefined threshold of 5% ABV, the system activates an audible alarm via the buzzer and displays the corresponding ppm value on the OLED screen. A series of tests were conducted with eight volunteers who consumed varying amounts of alcohol. The results demonstrated the system's high accuracy and responsiveness, with the ability to detect alcohol concentrations ranging from safe levels to dangerous thresholds. The device was tested multiple times to ensure consistency and minimize errors, with the final results confirming its effectiveness in providing reliable alcohol measurements. This system holds significant potential for applications in monitoring alcohol levels in drivers and individuals involved in safety-critical activities. The research underscores the importance of real-time alcohol detection systems in enhancing public safety and ensuring compliance with safety regulations.

关键词： Accuracy Measurement uncertainty Organic light emitting diodes Control systems Real-time systems Public security Nanoscale devices Monitoring Vehicles Testing

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Prioritizing Strategies for Building the Resilience of Public Health Systems to Disasters Across Multiple Communities and Countries

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International Journal of Disaster Risk science 2024年第1期15卷 1-17页

作者： Benjamin J.Ryan Mayumi Kako Shelby Garner Rok Fink Ismail Tayfur Jonathan Abrahams Sanjaya Bhatia Adriana Campelo Matthew Fendt Alicia Fontenot Nahuel Arenas Garcia Tim Hatch Ryoma Kayano LaShonda Malrey‑Horne Makiko MacDermot Md Moshiur Rahman Chaverle Noel Shuhei Nomura Jeremy P.Novak Maria Opazo Kendell Oliver Luciana Peters Sohel Rahman PerihanŞimşek Andrew Stricklin Raymond Swienton Bryan W.Brooks Frist College of Medicine Belmont UniversityNashvilleTN 37212USA Department of Environmental Science Environmental Health Science ProgramCollege of Arts and SciencesBaylor UniversityWacoTX 76798USA Division of Nursing Science School of Biomedical and Health SciencesHiroshima UniversityHiroshima 734-8553Japan Gordon E.Inman College of Health Sciences and Nursing Belmont UniversityNashvilleTN 37212USA Faculty of Health Sciences University of Ljubljana1000 LjubljanaSlovenia Department of Emergency Medicine University of Health Sciences34668 IstanbulTurkey Monash University Accident Research Center MelbourneVIC 3800Australia Global Education and Training Institute United Nations Ofce for Disaster Risk ReductionIncheon 22004Republic of Korea Regional Ofce for the Americas and Caribbean United Nations Ofce for Disaster Risk ReductionPanama City 0843-03441Panama Engineering and Computer Science Baylor UniversityWacoTX 76798USA Department of Public Health Robbins College of Health and Human SciencesBaylor UniversityWacoTX 76798USA Alabama Department of Public Health MontgomeryAL 36092USA World Health Organization Centre for Health Development(WHO Kobe Centre) Kobe 651-0073Japan Waco-McLennan County Public Health District WacoTX 76707USA Department of Health Policy and Management School of MedicineKeio UniversityTokyo 160-8582Japan Department of Global Health Policy Graduate School of MedicineThe University of TokyoTokyo 113-0033Japan Tokyo Foundation for Policy Research Tokyo 106-6234Japan Global Development College BrisbaneQLD 4000Australia Municipality of Pudahuel 13124 PudahuelChile City Hall of Porto Alegre Porto Alegre 90010-170Brazil Ministry of Health and Family Welfare Government of the People’s Republic of BangladeshDhaka 1000Bangladesh Department of Emergency Aid and Disaster Management Trabzon University61335 TrabzonTurkey Department of Emergency Medicine UT SouthwesternDallasTX 75390USA

The COVID-19 pandemic highlighted the urgent need to strengthen public health *** response,the United Nations Disaster Risk Reduction(UNDRR) Public Health System Resilience Scorecard(Scorecard) was applied in workshops across multiple *** aim of our research was to explore the workshop findings to develop priority strategies for strengthening public health system *** conducted a workshop from 14 to 16 March 2023,at the UNDRR Global Education and Training Institute in Incheon,Republic of Korea.A sequential modified Delphi method was utilized to develop a set of prioritized resilience *** were drawn from 70 strategies identified from 13 distinct workshops in eight *** two surveys,23 strategies were *** received ratings of "High" or Very High" from89% of *** related to the inclusion of public health risks in emergency plans,integrating multidisciplinary teams into public health,enabling local transport mechanisms,and improving the ability to manage an influx of *** Scorecard provides an adaptable framework to identify and prioritize strategies for strengthening public health system *** leveraging this methodology,our study demonstrated how resilience strategies could inform disaster risk reduction funding,policies,and actions.

关键词： Health system resilience Public policy Resilience scorecard Workshops

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Lifecycles, pipelines, and value chains: toward a focus on events in responsible artificial intelligence for health

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AI and Ethics 2024年第3期5卷 2815-2828页

作者： Donia, Joseph Oyefeso, Lola Embuldeniya, Gayathri Whyne, Cari Burns, David Boyer, Philip Razmjou, Helen Shaw, James A. Institute of Health Policy Management & Evaluation Dalla Lana School of Public Health University of Toronto Toronto Canada Department of Biology Faculty of Arts and Science University of Toronto Toronto Canada Department of Physical Therapy Temerty Faculty of Medicine University of Toronto Toronto Canada Holland Bone and Joint Program Sunnybrook Research Institute Sunnybrook Health Sciences Centre Toronto Canada Institute of Biomedical Engineering Faculty of Applied Science and Engineering University of Toronto Toronto Canada Institute of Medical Sciences Temerty Faculty of Medicine University of Toronto Toronto Canada Division of Orthopedic Surgery Department of Surgery Temerty Faculty of Medicine University of Toronto Toronto Canada Joint Centre for Bioethics Dalla Lana School of Public Health University of Toronto Toronto Canada

Process-oriented approaches to the responsible development, implementation, and oversight of artificial intelligence (AI) systems have proliferated in recent years. Variously referred to as lifecycles, pipelines, or value chains, these approaches demonstrate a common focus on systematically mapping key activities and normative considerations throughout the development and use of AI systems. At the same time, these approaches risk focusing on proximal activities of development and use at the expense of a focus on the events and value conflicts that shape how key decisions are made in practice. In this article we report on the results of an ‘embedded’ ethics research study focused on SPOTT– a ‘Smart Physiotherapy Tracking Technology’ employing AI and undergoing development and commercialization at an academic health sciences centre. Through interviews and focus groups with the development and commercialization team, patients, and policy and ethics experts, we suggest that a more expansive design and development lifecycle shaped by key events offers a more robust approach to normative analysis of digital health technologies, especially where those technologies’ actual uses are underspecified or in flux. We introduce five of these key events, outlining their implications for responsible design and governance of AI for health, and present a set of critical questions intended for others doing applied ethics and policy work. We briefly conclude with a reflection on the value of this approach for engaging with health AI ecosystems more broadly.

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Cigarette smoke-induced dysbiosis: comparative analysis of lung and intestinal microbiomes in COPD mice and patients

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Respiratory Research 2024年第1期25卷 1-14页

作者： Laiman, Vincent Chuang, Hsiao-Chi Lo, Yu-Chun Yuan, Tzu-Hsuen Chen, You-Yin Heriyanto, Didik Setyo Yuliani, Fara Silvia Chung, Kian Fan Chang, Jer-Hwa Department of Radiology Faculty of Medicine Public Health and Nursing Universitas Gadjah Mada – Dr. Sardjito Hospital Yogyakarta Indonesia School of Respiratory Therapy College of Medicine Taipei Medical University 250 Wuxing Street Taipei 11031 Taiwan Division of Pulmonary Medicine Department of Internal Medicine Shuang Ho Hospital Taipei Medical University New Taipei Taiwan Cell Physiology and Molecular Image Research Center Wan Fang Hospital Taipei Medical University Taipei Taiwan National Heart and Lung Institute Imperial College London London United Kingdom The Ph.D. Program for Neural Regenerative Medicine College of Medical Science and Technology Taipei Medical University Taipei Taiwan Department of Health and Welfare College of City Management University of Taipei Taipei Taiwan Industrial Ph.D. Program of Biomedical Science and Engineering National Yang Ming Chiao Tung University Taipei Taiwan Department of Biomedical Engineering National Yang Ming Chiao Tung University Taipei Taiwan Department of Anatomical Pathology Faculty of Medicine Public Health and Nursing Universitas Gadjah Mada – Dr. Sardjito Hospital Yogyakarta Indonesia Department of Pharmacology and Therapy Faculty of Medicine Public Health and Nursing Universitas Gadjah Mada Yogyakarta Indonesia Division of Pulmonary Medicine Departments of Internal Medicine Wan Fang Hospital Taipei Medical University Taipei Taiwan Collaboration Research Center for Precision Oncology based Omics- PKR Promics Universitas Gadjah Mada Yogyakarta Indonesia

Background: The impact of cigarette smoke (CS) on lung diseases and the role of microbiome dysbiosis in chronic obstructive pulmonary disease (COPD) have been previously reported;however, the relationships remain unclear. Methods: Our research examined the effects of 20-week cigarette smoke (CS) exposure on the lung and intestinal microbiomes in C57BL/6JNarl mice, alongside a comparison with COPD patients’ intestinal microbiome data from a public dataset. Results: The study found that CS exposure significantly decreased forced vital capacity (FVC), thickened airway walls, and induced emphysema. Increased lung damage was observed along with higher lung keratinocyte chemoattractant (KC) levels by CS exposure. Lung microbiome analysis revealed a rise in Actinobacteriota, while intestinal microbiome showed significant diversity changes, indicating dysbiosis. Principal coordinate analysis highlighted distinct intestinal microbiome compositions between control and CS-exposed groups. In the intestinal microbiome, notable decreases in Patescibacteria, Campilobacterota, Defferibacterota, Actinobacteriota, and Desulfobacterota were observed. We also identified correlations between lung function and dysbiosis in both lung and intestinal microbiomes. Lung interleukins, interferon-ɣ, KC, and 8-isoprostane levels were linked to lung microbiome dysbiosis. Notably, dysbiosis patterns in CS-exposed mice were similar to those in COPD patients, particularly of Global Initiative for Chronic Obstructive Lung Disease (GOLD) stage 4 patients. This suggests a systemic impact of CS exposure. Conclusion: In summary, CS exposure induces significant dysbiosis in lung and intestinal microbiomes, correlating with lung function decline and injury. These results align with changes in COPD patients, underscoring the important role of microbiome in smoke-related lung diseases. © The Author(s) 2024.

关键词： Cigarette smoke Emphysema Inflammation Intestine Lung Microbiome

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Expansion cooling prospects for large scale applications

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International Journal of Thermofluids 2023年 20卷

作者： Alami, Abdul Hai Alrashid, Rashid Mdallal, Ayman Yasin, Ahmad Ayoub, Mohamad Alasad, Shamma Aljaghoub, Haya Alashkar, Adnan Abdelkareem, Mohammad Ali Olabi, Abdul Ghani Orhan, Mehmet Department of Sustainable and Renewable Energy Engineering University of Sharjah P.O. Box 27272 Sharjah United Arab Emirates Sustainable Energy and Power Systems Research Centre RISE University of Sharjah P.O. Box 27272 Sharjah United Arab Emirates Department of Mechanical Engineering American University of Sharjah P.O. Box 26666 Sharjah United Arab Emirates Department of Mechatronics Engineering American University of Sharjah P.O. Box 26666 Sharjah United Arab Emirates Department of Industrial Engineering and Engineering Management University of Sharjah P.O. Box 27272 Sharjah United Arab Emirates Materials Science and Engineering PhD Program American University of Sharjah P.O. Box 26666 Sharjah United Arab Emirates Chemical Engineering Department Minia University Elminia Egypt Mechanical Engineering and Design School of Engineering and Applied Science Aston University Aston Triangle BirminghamB4 7ET United Kingdom

Air conditioning in general and cooling in particular are the biggest energy sinks among all electricity consumers. Mitigating energy needs of this sector by active or passive means is a necessity. This paper offers a comprehensive review of various cooling technologies for large scale applications and compares them in terms of economy, environmental footprint and most importantly, energy requirements. There is a main focus on the potential of using expansion cooling, which is defined in conjunction with cooling effects generated during the expansion process of a gas. The interest in such cooling technology stems from the double benefit of utilizing a large-scale compressed air energy storage (CAES) system that can also provide cooling via the expansion of air. This consequently manifests in reducing the electrical demand required for cooling applications. Such a concept is beneficial for hot climates, where most of the electrical demand is reserved for offsetting the cooling load. © 2023 The Author(s)

关键词： Compressed air energy storage

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Machine Learning Modeling for Hydrolysis Recycling of Pet Waste

SSRN

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SSRN 2025年

作者： Li, Jie Pan, Lanjia Abedsoltan, Hossein Wang, Hailong Liu, Taiyang Yuan, Xiangzhou Ok, Yong Sik Wang, Yin State Key Laboratory for Ecological Security of Regions and Cities Institute of Urban Environment Chinese Academy of Sciences Xiamen361021 China State Key Laboratory of Advanced Environmental Technology Institute of Urban Environment Chinese Academy of Sciences Xiamen361021 China University of Chinese Academy of Sciences Beijing100049 China Sustainable Waste Management Program Division of Environmental Science and Ecological Engineering Korea University Seoul02841 Korea Republic of Ministry of Education of Key Laboratory of Energy Thermal Conversion and Control School of Energy and Environment Southeast University Nanjing210096 China Department of Chemical Engineering The University of Toledo ToledoOH43607 United States Linda and Bipin Doshi Department of Chemical and Biochemical Engineering Missouri University of Science and Technology RollaMO65401 United States

Hydrolysis of polyethylene terephthalate (PET) into terephthalic acid (TPA) is one key approach for waste PET recycling. However, achieving an in-depth understanding in PET hydrolysis remains challenging. Herein, we employed machine learning (ML) methods to interpret the PET conversion with a dataset compiled, containing 942 data points and rich hydrolysis factors of PET-related information, heating type, acid/base catalyst (ABC), organic solvent (OS), co-solvent, phase transfer catalyst (PTC), and operational condition. A Neural Network model was found to be the best for predicting PET conversion, with a testing R2 and RMSE of 0.93 and 8.45%. The model-based interpretation suggested that operational conditions accounted for 45% of importance, followed by ABC (19%), OS (12%), and PTC (12%). Furthermore, hydrolysis time, temperature, and ABC concentration were identified as the top-three factors positively influencing PET conversion. This work facilitates the catalyst and process optimization for PET hydrolysis to promote the plastic circular economy. © 2025, The Authors. All rights reserved.

关键词： Transfer learning

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Strategy for evaluation, characterization and adoption of immersive technologies to the public of the tourism industry in Maule Region

Strategy for evaluation, characterization and adoption of im...

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CHILEAN Conference on Electrical, Electronics engineering, Information and Communication Technologies (CHILECON)

作者： Yazmina Stappung Felipe Besoain Institute of Biological Science and Master’s Student in Technology Management Program University of Talca Chile Engineering of Videogames and Virtual Reality School and The Mauletec Laboratory University of Talca Chile

ISBN: (纸本)9781665408745

During the last few years, virtual reality technology has been introduced significantly in different economic sectors, even in the most conservative, such as tourism. Tourists have evolved; now there are Tourists 4.0, those who plan their trips using digital resources, seeking uniqueness and to enhance the emotions that a travel experience gives. Thus, there are users who are willing to explore innovative technologies, such as augmented reality. These immersive experiences open a window to bring the tourist closer to a possible destination and finalize the trip. The simplification of the process is the key to adding followers, and also understanding who the final user will be, connecting users to a new tourist destination through the adoption of this technology. In this context, a strategy is proposed that will characterize the user, their reception and evaluation of the technological adoption of local technological products developed with immersive technologies for tourists in the Maule Region. This study will allow the incorporation of orientation, experiences, and expectations, through the application of different instruments, to identify the users who adopted the technology and defined the travel process through an immersive reality experience.

关键词： Economics Instruments Conferences Tourism industry Information and communication technology Augmented reality IEEE Regions

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Association of seafood consumption with sleep quality according to high sensitivity C-reactive protein levels in Korean adults

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The journal of nutrition, health & aging 2025年第8期29卷

作者： Yeongeun Jeong Minji Kim Seungyoun Jung Yangha Kim Department of Nutritional Science and Food Management Ewha Womans University Seoul 03670 Republic of Korea Graduate Program in System Health Science and Engineering Ewha Womans University Seoul 03760 Republic of Korea. Graduate Program in System Health Science and Engineering Ewha Womans University Seoul 03760 Republic of Korea. Electronic address: yhmoon@ewha.ac.kr.

OBJECTIVE:The consumption of seafood, which is major sources of n-3 polyunsaturated fatty acids, such as docosahexaenoic and eicosapentaenoic acids, has been associated with sleep quality. Seafood and its bioactive components may enhance sleep quality by regulating systemic inflammation and neuroendocrine pathways. However, longitudinal studies examining the interplay between seafood consumption, sleep quality, and inflammatory status are lacking. Therefore, in this cohort study of 2332 participants from the Korean Genome and Epidemiology Study, we investigated the potential modulatory role of inflammatory status for the association between seafood consumption and the risk of poor sleep quality. METHODS AND MEASUREMENTS:Dietary intake was assessed using a validated 106-item food frequency questionnaire. High-sensitivity C-reactive protein (hs-CRP) levels were assessed as a marker of systematic inflammatory status. Sleep quality was assessed using Pittsburgh Sleep Quality Index. The hazard ratio (HR) and 95% confidence interval (CI) for the risk of poor sleep quality was estimated using Cox proportional hazards model. RESULTS:After 6 years of follow-up, 118 and 192 cases of poor sleep quality were documented among men and women, respectively. The greater seafood consumption was significantly associated with lower risk of poor sleep quality. The multivariable-adjusted HR (95% CI) comparing the highest with the lowest tertile of seafood consumption was 0.66 (0.45-0.98) (p-trend = 0.032). This inverse association appeared to be limited to participants with lower levels of hs-CRP. CONCLUSION:Our results suggested that the favorable effects of seafood consumption on sleep quality could vary by inflammatory status. Larger cohort studies are warranted to replicate our findings.

关键词： High-sensitivity C-reactive protein Seafood Sleep quality, longitudinal study n-3 polyunsaturated fatty acids

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