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Women in Data Science at Prince Sultan University (WiDS PSU), International Conference of

作者： Tahira Jehan Makda Ana Luiza Barros Selma Dilek College of Business Management University of Doha for Science and Technology Doha Qatar Computer Science Program State University of Ceará Fortaleza Brazil Department of Computer Engineering Hacettepe University Ankara Turkey

Recent work has proven the effort of researchers to integrate small sensors and a cloud environment, delivering the Internet of Things (IoT). Sensors as a service are one of the leading research concerns in this context. Nevertheless, security is becoming one of the most significant attributes of the IoT as sensors become more human-independent and are being extensively used to monitor human lives. That way, IoT brings many key security challenges that need attention, some of which we address in this position paper. We present a cloud-based infrastructure that can deliver sensors and actuators as a service, providing secure communication between them and the control nodes on which IoT applications rely while implementing Big Data algorithms. For mapping our proposal, two scenarios related to Health Assistance are discussed, considering secure communications in a sensor network. In conclusion, we propose a scope for future research in this field considering digital twin concepts. Since domains exploiting IoT technologies can benefit from adopting Digital Twin, our goal is to evolve a virtual sensor and actuator system into this technology.

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Research on Traffic Sign Detection and Recognition System Using Deep Ensemble Learning

Research on Traffic Sign Detection and Recognition System Us...

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IEEE International Conference on Computer Communication and the Internet (ICCCI)

作者： Lung-Jen Wang Taweelap Suwattanapunkul Jarinya Thalauy Parinya Jansengrat Department of Computer Science and Information Engineering National Pingtung University Pingtung Taiwan International Master Program in Information Technology and Applications International College National Pingtung University Pingtung Taiwan Department of Big Data Management and Analytics Rajamangala University of Technology Thanyaburi Pathum Thani Thailand

ISBN: (数字)9798350351767

ISBN: (纸本)9798350351774

There is a rise in car accidents due to human errors on the road. A critical task of self-driving cars that can reduce accidents on the road is traffic sign detection and recognition (TSDR), which is vital in alerting drivers to the presence of traffic signs in advance. This research will separate the proposed deep ensemble learning algorithm into two methods. First, after the traffic scene process, the algorithm will detect the traffic sign as two categories with the YOLOv5s network. Then, process the traffic sign to recognize the traffic sign into seven classes with the MobileNet network. The detection model was trained with the Taiwan Traffic Sign Detection (TTSD) dataset collected from Taiwan roads. The recognition model was trained with the Taiwan Traffic Sign Recognition (TTSR) dataset. The result of the proposed algorithm showed high performance when experimenting with 95.83% accuracy, 87.34% true prediction, and 191.3 milliseconds (ms) of inference time.

关键词： YOLO Roads Prediction algorithms Inference algorithms Internet Autonomous automobiles Ensemble learning

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Energy consumption of high-rise double skin façade buildings, a machine learning analysis

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Journal of Building engineering 2024年 89卷

作者： Rezaie, Maedeh Kariminia, Shahab Band, Shahab S. Ameri, Rasoul Farokhi, Maryam Pai, Hao-Ting Gocer, Ozgur Rismanchi, Behzad Shooshtarian, Salman Department of Architecture Advancement in Architecture and Urban Planning Research Center Najafabad Branch Islamic Azad University Najafabad Iran Future Technology Research Center National Yunlin University of Science and Technology Douliu Taiwan Department of Information Management International Graduate School of Artificial Intelligence National Yunlin University of Science and Technology Taiwan Department of Information Management National Yunlin University of Science and Technology Taiwan Bachelor Program of Big Data Applications in Business National Pingtung University Pingtung Taiwan School of Architecture Design and Planning The University of Sydney SydneyNSW Australia Renewable Energy and Energy Efficiency Group Department of Infrastructure Engineering Faculty of Engineering and Information Technology The University of Melbourne Australia School of Property Construction and Project Management RMIT University Melbourne Australia

Most energy exchanges take place through the building skin. The skin characteristics play a decisive role in the extent of these exchanges, but they are somewhat more varied in the double skin façade (DSF). Among these characteristics, cavity segmentation has a noticeable effect on the implementation of the DSF in different directions during the hot and cold seasons. The aim of this study was to investigate the role of DSF segmentation in energy consumption and natural ventilation of high-rise buildings in hot and dry climates. This study used DesignBuilder software to study sixty-four segmentation component scenarios in an eight-story residential building in Isfahan, Iran. Moreover, a proposed hybrid model utilizing the hybridization of the Hunger Game Search and Gradient Boosting (HGS-GB) algorithm was employed to estimate energy consumption in various scenarios involving lighting, heating, cooling, and total scenarios. The available outcomes revealed that the HGS-GB model had a better performance in comparison with other individual models, such as Gradient Boosting (GB), Random Forest (RF), and K-nearest neighbors (KNN). The R2 values for lighting, heating, cooling, and total energy estimation were 0.9993, 0.9958, 0.9991, and 0.9922, respectively. The findings of this study suggest the significance of DSF segmentation in energy consumption and natural ventilation in high-rise buildings in hot and dry climates. © 2024 Elsevier Ltd

关键词： Forestry

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University Students’ Attitudes toward Adoption of Mobile Health Application for Serving Older People

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Sensors and Materials 2023年第7期35卷 2581-2601页

作者： Chao, Pei-Ju Cheng, Yu-Huei Liu, Yi-Hui Hsu, Tsu-Hsuan Travel & Tourism Program International College Ming Chuan University 5 De Ming Rd. Gui Shan District Taoyuan333 Taiwan Department of Information and Communication Engineering Chaoyang University of Technology 168 Jifeng E. Rd. Wufeng District Taichung413 Taiwan Department of Senior Citizen Service Management National Taichung University of Science and Technology No. 129 Sec. 3 Sanmin Rd. North District Taichung404 Taiwan Graduate Institute of Rehabilitation Counseling National Changhua University of Education 1 Jin-De Rd. Changhua City500 Taiwan

In this quantitative study, we examined the awareness of mobile health (mHealth) applications among Taiwan’s university students, particularly the government-operated My Health Bank application. The My Health Bank application allows users to access their personal health information simply through their smartphone’s sensor-assisted facial recognition camera and fingerprint sensor. Whether these university students might help older adults to use this application if they perceive it to be helpful was also explored. Two instruments were used in this study, namely, the Perceptions toward My Health Bank (PMHB) and Geriatric Attitudes Scale (GAS). Two hundred twenty-five (225) university students from the Departments of Senior Citizen Service management (n = 136) and Nursing (n = 89) at two universities participated in this study. The findings indicated low adoption of My Health Bank and related mHealth applications among students even though they had high adoption rates of smartphones. However, they perceived that the functions of this application are useful and should be promoted to older adults. Thus, building a basic foundation of mHealth and related technology courses is recommended to assist healthcare students in being well-prepared for working with older adults in the digital society. © MYU K.K.

关键词： mHealth

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Environmental and economic impacts of nitrogen trifluoride at an idaho semiconductor facility

Environmental and economic impacts of nitrogen trifluoride a...

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ASME 2020 International Design engineering Technical Conferences and Computers and Information in engineering Conference, IDETC-CIE 2020

作者： Thompson, Matthew A. Mohajeri, Amir Mirkouei, Amin Technology Management Program Department of Mechanical Engineering University of Idaho ID United States

ISBN: (纸本)9780791883952

Nitrogen Trifluoride (NF3) is an inorganic compound widely used in the electronics industry for manufacturing various products, such as semiconductors, solar panels, and touch screens. However, NF3 emissions that accumulate in the atmosphere have 17,200 times the global warming potentials of CO2 over a 100-year time horizon. The abatement efficiency for NF3 is high, although some amount of NOx is generated. This study aims to provide economic and environmental impact assessments on the use of NF3. Life cycle assessment method is applied for evaluating environmental aspects. Additionally, a real case study for the Idaho semiconductor facility is used to assess the method and demonstrate the application of this study. The results show that slight reductions in abatement efficiency have dramatic impacts on mitigating greenhouse gas (GHG) emissions. Even small unplanned releases of NF3, either through mechanical failure or human error, have significant environmental impacts, and every reasonable effort should be taken to avoid such incidents. The results also indicate that the cost of abatement is the primary driver of economic impact. It is found that the considerable distance from the chemical plant in Arizona to the point of use in Idaho contributed a minor portion of GHGs associated with the use of NF3. It is also found that contaminants (e.g., SF6 and CF4) within the cylinder potentially have more substantial GHG impacts than the actual NF3, owing in part to the relative ease with which NF3 is destroyed through abatement. © 2020 American Society of Mechanical Engineers (ASME). All rights reserved.

关键词： Sustainable development

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Optimizing Distribution Network Models for a Fruit Trading Company in Thailand: A Comparative Study Using Linear programming and Optimization

Optimizing Distribution Network Models for a Fruit Trading C...

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IEEE International Conference on Industrial engineering and engineering management

作者： P. Akkawuttiwanich P. Yenradee S. Horng T. Pichpibul Department of Aviation Industry Innovation and Service International Academy of Aviation Industry King Mongkut's Institute of Technology Ladkrabang Bangkok Thailand Industrial Engineering Program Sirindhorn International Institute of Technology Thammasat University PathumThani Thailand Faculty of Logistics and Transportation Management Panyapiwat Institute of Management Nonthaburi Thailand

This research investigates the distribution network model of a fruit trading company in Thailand, with a specific focus on the problem of excessive travel distances and vehicle requirements in the company's existing distribution system. Linear programming and optimization techniques are used to improve the distribution network model and to satisfy the daily demand. Results are compared between the current distribution scenario and the optimized model. The computational analysis reveals a significant 21.8% reduction (802 kilometers) in total traveling distance and a 33.33% decrease in the number of vehicles required. Additionally, a comprehensive cost analysis is proposed, incorporating fuel costs, CO2 emissions, and overtime expenses, which were previously overlooked. This research offers valuable insights into the potential benefits of optimization, including cost savings and environmental impact reduction, providing a practical template for managing distribution networks, reducing reliance on ad hoc practices, and fostering a sustainable business model to enhance competitiveness in a challenging market.

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H∞ gain-scheduled dynamic output feedback control with transient performance applied to electrical microgrid

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Journal of the Franklin Institute 2024年第7期361卷

作者： Fuentes, R.M. Lacerda, M.J. Morais, C.F. Oliveira, R.C.L.F. Palma, J.M. Engineering Systems Doctoral Program Faculty of Engineering Universidad de Talca Curicó3340000 Chile Centre for Communications Technology School of Computing and Digital Media London Metropolitan University LondonN7 8DB United Kingdom Pontifical Catholic University of Campinas – PUC-Campinas Polythecnic School Postgraduate Program in Telecommunication Networks Management SP Campinas13086-900 Brazil SP Campinas13083-852 Brazil Department of Electrical Engineering Faculty of Engineering Universidad de Talca Curicó334000 Chile

This paper introduces an approach for designing gain-scheduled dynamic output feedback controllers for continuous-time Linear Parameter-Varying (LPV) systems. The aim is to improve transient response by incorporating both D-stability and H∞ criteria into the synthesis conditions. We achieve this by employing changes of variables and congruence transformations, which lead to new synthesis conditions expressed as linear matrix inequalities. Additional fine-tuned scalar parameters can be used to enhance further the controller performance in terms of less conservative H∞ guaranteed costs. To assess the effectiveness of our proposed synthesis procedure, we conduct computational experiments in the context of a microinverter-based distributed power generation system. These experiments take into account real-world operational characteristics, providing a comprehensive evaluation of our approach. The results demonstrate that the designed controller effectively ensures the desired closed-loop system behavior, even when dealing with state noise and discretization errors originating from digital implementation. © 2024 The Franklin Institute

关键词： Transient analysis

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Solving Container Stowage Problem using Particle Swarm Optimization Algorithm with Multiple Social Learning Structures 2021

Solving Container Stowage Problem using Particle Swarm Optim...

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3rd International Conference on management Science and Industrial engineering, MSIE 2021

作者： Perwira Redi, A.A.N. Perwira Dwi Lasmana, Ina Layli Rachmawati, Nur Tri Prasetyo, Yogi Budiono, Doni Jewpanya, Parida Industrial Engineering Department BINUS Graduate Program - Master of Industrial Engineering Bina Nusantara University Jakarta Indonesia Department of Logistics Engineering Universitas Pertamina Jakarta Indonesia School of Industrial Engineering and Engineering Management Mapúa University Manila Philippines Department of Technology Management Institut Teknologi Sepuluh Nopember Surabaya Indonesia PT Jakarta International Container Terminal Jakarta Department of Industrial Engineering Rajamangala University of Technology Lanna Tak Tak Thailand

ISBN: (纸本)9781450388887

The growth of international trade resulted in the raising of the total containers transported annually. In Indonesia, the number of container throughput has reached 12.85 million TEUs in 2018. In providing fast and efficient port services, container terminals (CT) constantly face complex problems on its everyday operation, one of the operational level problems occurred at CT is Container Stowage Problem (CSP). CSP is an NP-Hard Problem, therefore metaheuristic algorithm is used to solve the problem. This study proposed the use of Global, Local, and Neighborhood - Particle Swarm Optimization (GLN-PSO) algorithm to solve CSP. The basic idea of GLN-PSO is emphasize on the particle movement that considers multiple social learning structures. GLN-PSO algorithm is a development of the PSO algorithm that has been used in previous studies and is proven to outperform Bee Swarm algorithm. In this study, GLN-PSO is used to solve two types of data, namely small instances (consist of 5-27 containers) and medium instances (consist of 100-140 containers). The result showed that for small instances, GLN-PSO can outperform the PSO algorithm in terms of objective function value by 0.72% and in terms of computational time by 0,172 seconds. For medium instances, GLN-PSO has not been able to outperform the PSO algorithm by producing a gap of 27% for the objective function and 8,2 seconds for computational time © 2021 ACM.

关键词： International trade

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A Survey on Recent Applications of Artificial Intelligence and Optimization for Smart Grids in Smart Manufacturing

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Energies 2023年第22期16卷 7660-7660页

作者： Hsu, Chao-Chung Jiang, Bi-Hai Lin, Chun-Cheng Department of Industrial Engineering and Management National Yang Ming Chiao Tung University Hsinchu300 Taiwan International Master Program in Smart Manufacturing and Applied Information Science National Chin-Yi University of Technology Taichung411 Taiwan

To enable highly automated manufacturing and net-zero carbon emissions, manufacturers have invested heavily in smart manufacturing. Sustainable and smart manufacturing involves improving the efficiency and environmental sustainability of various manufacturing operations such as resource allocation, data collecting and monitoring, and process control. Recently, a lot of artificial intelligence and optimization applications based on smart grid systems have improved the energy usage efficiency in various manufacturing operations. Therefore, this survey collects recent works on applications of artificial intelligence and optimization for smart grids in smart manufacturing and analyzes their features, requirements, and challenges. In addition, potential trends and further challenges for the integration of smart grids with renewable energies for smart manufacturing, applications of 5G and B5G (beyond 5G) technologies in the SG system, and next-generation smart manufacturing systems are discussed to provide references for further research. © 2023 by the authors.

关键词： Smart power grids

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A Survey on the Impact of Data Analytics and Machine Learning Techniques in E-commerce 5

A Survey on the Impact of Data Analytics and Machine Learnin...

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5th International Conference on Contemporary Computing and Informatics, IC3I 2022

作者： Dheva Rajan, S. Vavilapalli, Sivajee Hasan, Shahriar Kumar, Ritesh Rafa, Nafisa Muda, Iskandar University of Technology and Applied Sciences Almusannah Information Technology Oman Duvvada Department of Management Studies Visakhapatnam India University of Dhaka Department of Finance Bangladesh Maharishi School of Engineering and Technology Uttar Pradesh Lucknow India BBA in Marketing Institute of Business Administration University of Dhaka Dhaka Bangladesh Universitas Sumatera Utara Faculty Economic and Business Department of Doctoral Program Medan20222 Indonesia

ISBN: (纸本)9798350398267

Current article has been developed for understanding the impact of data analytics and machine learning technique in e-commerce. If the observation has been developed for the current market of this technology it can be detected that real-life industry increases their investment which showed the interest in getting advantages. Identification of the problem of costing and different algorithm suitability objectives has been set for understanding the real impact of e-commerce. Secondary data collection has been used for understanding the different usability of machine learning and data analytics for e-commerce. It has been detected that using machine learning brings the benefits of automation and improves continuous growth. Data analytics provide the scope of accuracy build-up. Apart from this different area of application and the different techniques has been analyzed. Understanding become easier and the scope of future benefits can be identified. © 2022 IEEE.

关键词： Data Analytics

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