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Semi-analytical finite element method applied for characterizing micropolar fibrous composites

Applied Mathematics and Mechanics(English Edition) 2024年第12期45卷 2147-2164页

作者： J.A.OTERO Y.ESPINOSA-ALMEYDA R.RODRIGUEZ-RAMOS J.MERODIO School of Engineering and Sciences Monterrey Institute of TechnologyEstado de Mexico 52926Mexico Institute of Engineering and Technology Autonomous University of Ciudad JuarezCiudad JuarezChihuahua 32310Mexico Postgraduate Program in Computational Modeling in Science and Technology Federal Fluminense UniversityRıo de Janeiro 27255-125Brazil Faculty of Mathematics and Computer Science University of HavanaLa Habana 10400Cuba Department of Mathematics Applied to ICT School of Informatics Systems EngineeringTechnical University of MadridMadrid 28031Spain

A semi-analytical finite element method(SAFEM),based on the two-scale asymptotic homogenization method(AHM)and the finite element method(FEM),is implemented to obtain the effective properties of two-phase fiber-reinforced composites(FRCs).The fibers are periodically distributed and unidirectionally aligned in a homogeneous *** framework addresses the static linear elastic micropolar problem through partial differential equations,subject to boundary conditions and perfect interface contact *** mathematical formulation of the local problems and the effective coefficients are presented by the *** local problems obtained from the AHM are solved by the FEM,which is denoted as the *** numerical results are provided,and the accuracy of the solutions is analyzed,indicating that the formulas and results obtained with the SAFEM may serve as the reference points for validating the outcomes of experimental and numerical computations.

关键词： semi-analytical approach fiber-reinforced composite(FRC) effective property finite element method(FEM) asymptotic homogenization method(AHM) micropolar elasticity

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Permissioned Blockchain-Based Monitoring Framework for DER-Integrated Distribution Networks 14

Permissioned Blockchain-Based Monitoring Framework for DER-I...

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14th Mediterranean Conference on Power Generation Transmission, Distribution and Energy Conversion, MEDPOWER 2024

作者： Angın, Pelin Zehir, Alparslan Ceylan, Oguzhan Eissa, Mohamed Aly Amin Selim Yüksel, Murat Can Deveci, Umur Yılmaz, Seyit Cem Göl, Murat Department of Computer Engineering Middle East Technical University Ankara Turkey Department of Electrical and Electronics Engineering Marmara University Turkey Department of Management Information Systems Kadir Has University Turkey Istanbul Turkey Department of Electrical and Electronics Engineering Middle East Technical University Ankara Turkey

ISBN: (纸本)9781837242689

SCADA systems are used for real-time monitoring of key systems and the status of critical assets in both transmission and distribution networks. The trend towards different types of"new" loads and sources such as photovoltaic (PV), electric vehicle (EV) charging stations and battery storage systems is changing the operational approach of distribution grids. Well-known fit-and-forget philosophy is being replaced and requires more operational activities and more thorough monitoring of end devices in new active distribution networks (ADNs). In this paper, a permissioned blockchain-based monitoring framework for distribution networks hosting different types of distributed energy resources (DERs) is presented. The proposed tool operates independently of the SCADA system while it can utilise SCADA measurements for anomaly and fraud detection. In addition, seamless integration and visibility is facilitated by the flow of information between DERs and the distribution system operator through adapters between the blockchain network and the main protocols used for smart metering, inverter management and EV charging stations. The coordinated use of SCADA and the proposed framework will provide a redundant set of observations that will contribute to unbiased state estimation and successful anomaly detection. © The Institution of engineering & Technology 2024.

关键词： Charging stations

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Status of Industrial Complex Activity Explained by Air Quality: Central Thailand 3

Status of Industrial Complex Activity Explained by Air Quali...

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3rd International Symposium on Instrumentation, Control, Artificial Intelligence, and Robotics, ICA-SYMP 2023

作者： Kodaka, Akira Leelawat, Natt Tang, Jing Onda, Yasushi Kohtake, Naohiko Graduate School of System Design and Management Keio University Kanagawa Japan Disaster and Risk Management Information Systems Research Unit Thailand Chulalongkorn University Department of Industrial Engineering Bangkok Thailand International School of Engineering Faculty of Engineering Disaster and Risk Management Information Systems Research Unit Chulalongkorn University Bangkok Thailand

ISBN: (纸本)9781665473538

Resilience in business continuity of an entire industrial complex has direct local socioeconomic impact;however, there are few methods available for objective assessment of its status. This study investigated whether change in air quality could explain the state of economic activity in an industrial complex. Concentrations of PM2.5 and NO2 above several industrial complexes in central Thailand were extracted using the Google Earth Engine™ and analyzed to examine their temporal characteristics in relation to decline in business activity caused by the COVID-19 pandemic. Results confirmed that industrial complexes whose activities were diminished by the pandemic showed concurrent trends of reduction in each pollutant, proving that the concentration of airborne substances has potential to reveal the level of activity of industrial complexes. To enhance the application potential of the proposed method, further study should investigate specific causal inferences by extracting the characteristics of other airborne substances, and consider industrial complexes that include a greater number of companies and major industries. © 2023 IEEE.

关键词： COVID-19

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Initial Exploration and Understanding of Parameters for Successful Enterprise Architecture Implementation 11

Initial Exploration and Understanding of Parameters for Succ...

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11th International Conference on ICT for Smart Society, ICISS 2024

作者： Khairina, Dyna Marisa Purwanto, Purwanto Nugraheni, Dinar Mutiara Kusumo School of Postgraduate Studies Universitas Diponegoro Program in Information Systems Semarang Indonesia Universitas Diponegoro Faculty of Engineering Department of Chemical Engineering Semarang Indonesia Universitas Diponegoro Faculty of Science and Mathematics Department of Informatics Semarang Indonesia

ISBN: (纸本)9798350389654

This study provides an initial exploration and further understanding of the factors that are parameters in evaluating the success of Enterprise Architecture (EA) implementation. An evaluation process is needed to ensure that the EA project implementation provides effectiveness, efficiency, and feasibility of the EA information system as well as assessing previous project experience to avoid future EA project risks. The research aims to present a Systematic Literature Review based on the stages of identification, screening, eligibility, and inclusion so that 14 main articles are selected for review with strong actual relevance. The study results provide insights and references that can be used to further explore key factors in evaluating the success of EA implementation in the future. It was found that there were ten factors that most influenced the evaluation of the success of EA implementation and it was concluded that two potential factors were the most influential and required further exploration in evaluating the success of EA implementation which could be applied in various sectors/dimensions. This study contributes as an initial reference for overcoming problems in investigating and exploring the factors that influence the success of EA implementation as an effort to assess the success of achieving future organizational goals. © 2024 IEEE.

关键词： Enterprise Architecture Parameters Success Factors Systematic Literature Review

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Adaptive Fault Detection Based on Neural Networks and Multiple Sampling Points for Distribution Networks and Microgrids

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Journal of Modern Power systems and Clean Energy 2022年第6期10卷 1648-1657页

作者： J.Marín-Quintero C.Orozco-Henao A.S.Bretas J.C.Velez A.Herrada A.Barranco-Carlos W.S.Percybrooks Electric and Electronic Engineering Program Universidad Tecnológica de BolívarCartagenaColombia Electrical and Electronic Engineering Department Universidad del NorteBarranquillaColombia Distributed Systems Group Pacific Northwest National LaboratoryGainesvilleUSA

Smart networks such as active distribution network(ADN)and microgrid(MG)play an important role in power system *** design and implementation of appropriate protection systems for MG and ADN must be addressed,which imposes new technical *** paper presents the implementation and validation aspects of an adaptive fault detection strategy based on neural networks(NNs)and multiple sampling points for ADN and *** solution is implemented on an edge *** are used to derive a data-driven model that uses only local measurements to detect fault states of the network without the need for communication *** sampling points are used to derive a data-driven model,which allows the generalization considering the implementation in physical *** adaptive fault detector model is implemented on a Jetson Nano system,which is a single-board computer(SBC)with a small graphic processing unit(GPU)intended to run machine learning loads at the *** proposed method is tested in a physical,real-life,low-voltage network located at Universidad del Norte,*** testing network is based on the IEEE 13-node test feeder scaled down to 220 *** validation in a simulation environment shows the accuracy and dependability above 99.6%,while the real-time tests show the accuracy and dependability of 95.5%and 100%,*** hard-to-derive parameters,the easy-to-implement embedded model highlights the potential for real-life applications.

关键词： Distribution network microgrid adaptive protection intelligent electronic device machine learning

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Quantifying the Benefits of Mindful Driving Training in Safety and Sustainability

Quantifying the Benefits of Mindful Driving Training in Safe...

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2023 systems and Information engineering Design Symposium, SIEDS 2023

作者： Dollahite, Rebecca Duffy, Michael Park, B. Brian University of Virginia Department of Systems & Information Engineering United States University of Virginia Facilities Management United States University of Virginia Department of Civil & Environmental Engineering United States

ISBN: (纸本)9798350300642

While automobiles are essential for enabling the daily lives of many Americans and businesses, they have caused significant public health concerns, including over 31,785 fatalities in 2022 from traffic crashes and generating 27% of the United States' greenhouse gas emissions in 2020. It has been shown that mindful driving training reduces aggressive driving behaviors, which is expected to reduce crashes, fuel consumption, and greenhouse gas *** this research, we work with the University of Virginia (UVA)'s Facilities management (FM) group which monitors over 280 vehicles through GPS tracking software. The FM group started mindful driving training in March 2021 and has since completed training for nearly half of drivers. We started collecting and analyzing these vehicles' performance data, including harsh braking, hard acceleration, speed violation, seatbelt violation, fuel consumption, and idling time. We quantified the impacts of mindful driving using before and after analysis. The safety impact was assessed using delta changes in harsh braking, speed violation, seatbelt violation, and number of relative crashes and the sustainability impact was based on the changes in hard acceleration, fuel economy, and idling time. Our analyses showed that mindful driving training greatly improves sustainability with reduced fuel consumption and safety with reduced occurrences of safetyrelated violations. © 2023 IEEE.

关键词： Sustainable development

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Exploring Integration AI-Powered in Supply Chain management

Exploring Integration AI-Powered in Supply Chain Management

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2024 International Conference on Decision Aid Sciences and Applications, DASA 2024

作者： Fernando, Erick Ikhsan, Ridho Bramulya Winanti Universitas Multimedia Nusantara Information Systems Faculty of Engineering and Informatics Tangerang Indonesia BINUS Online Learning Management Department Bina Nusantara University Jakarta Indonesia Universitas Insan Pembangunan Department of Information Systems Indonesia

ISBN: (纸本)9798350369106

This study aims to examine the integration of AI implementation in Supply Chain management. In this era, AI has become a transformational force in all sectors, especially in SCM. With AI capabilities, it is possible to assist SCM operations in a company. However, there are still many studies that need to be reviewed in this regard. This study examines the literature study method approach. This method uses relevant studies to analyze. The results of this study indicate that the success of AI integration in Supply Chain management (SCM) depends on organizational readiness, data quality, human resource skills, and management support in investing in technology and training. The main challenges in AI integration include technical difficulties, limited expertise, and data security issues. AI provides significant advantages in increasing efficiency, decision-making accuracy, and supply chain visibility. Industries such as e-commerce, manufacturing, food, and technology implement AI to improve inventory management, accelerate response to demand, and support operational sustainability and competitiveness. © 2024 IEEE.

关键词： Supply chain management

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Minimizing UCB: a Better Local Search Strategy in Local Bayesian Optimization 38

Minimizing UCB: a Better Local Search Strategy in Local Baye...

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38th Conference on Neural Information Processing systems, NeurIPS 2024

作者： Fan, Zheyi Wang, Wenyu Ng, Szu Hui Hu, Qingpei Academy of Mathematics and Systems Science Chinese Academy of Sciences China School of Mathematical Sciences University of Chinese Academy of Sciences China Department of Industrial Systems Engineering & Management National University of Singapore Singapore

Local Bayesian optimization is a promising practical approach to solve high dimensional black-box function optimization problem. Among them is the approximated gradient class of methods, which implements a strategy similar to gradient descent. These methods have achieved good experimental results and theoretical guarantees. However, given the distributional properties of the Gaussian processes applied on these methods, there may be potential to further exploit the information of the Gaussian processes to facilitate the Bayesian optimization search. In this work, we develop the relationship between the steps of the gradient descent method and one that minimizes the Upper Confidence Bound (UCB), and show that the latter can be a better strategy than direct gradient descent when a Gaussian process is applied as a surrogate. Through this insight, we propose a new local Bayesian optimization algorithm, MinUCB, which replaces the gradient descent step with minimizing UCB in GIBO [22]. We further show that MinUCB maintains a similar convergence rate with GIBO. We then improve the acquisition function of MinUCB further through a look ahead strategy, and obtain a more efficient algorithm LA-MinUCB. We apply our algorithms on different synthetic and real-world functions, and the results show the effectiveness of our method. Our algorithms also illustrate improvements on local search strategies from an upper bound perspective in Bayesian optimization, and provides a new direction for future algorithm design. © 2024 Neural information processing systems foundation. All rights reserved.

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Determining Marketing Strategy for Coffee Shops with Conjoint Analysis

Determining Marketing Strategy for Coffee Shops with Conjoin...

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2023 IEEE International Conference on Industrial engineering and engineering management, IEEM 2023

作者： Prasetyo, Yogi Tri Susanto, Krisna Chandra Asiddao, Sheree Mae A. Benito, Omar Paolo Liao, Jui-Hao Young, Michael Nayat Persada, Satria Fadil Nadlifatin, Reny Yuan Ze University International Bachelor Program in Engineering Chung-Li Taiwan Yuan Ze University Department of Industrial Engineering and Management Chung-Li Taiwan School of Industrial Engineering and Engineering Management Mapúa University Manila Philippines Binus Business School Undergraduate Program Bina Nusantara University Entrepreneurship Department Jakarta Indonesia Institut Teknologi Sepuluh Nopember Department of Information Systems Surabaya Indonesia

ISBN: (纸本)9798350323153

Coffee has become an important part of any individual nowadays. The purpose of this study is to determine the marketing strategy for the coffee shops. This study uses several coffee attributes such as coffee type, sugar level, temperature, coffee beans, and frappe were analyzed by utilizing a conjoint approach. A questionnaire was utilized for this research which collected 500 respondents. Conjoint analysis showed that sugar level was the most important coffee attribute (43.013%), followed by temperature (37.75%), coffee type (14.701%), coffee beans (2.601%), and frappe (1.936%). Interestingly, cold cappuccino with Arabica coffee bean, less sugar, and with frappe was found to be the best combination for marketing strategy. This study can be utilized for developing the marketing strategy of coffee shops. By Understanding the relationship between the factors, coffee shops can find out which factors influence customers the most. © 2023 IEEE.

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Status Quo of Hate Content Research using Bibliometric Analysis

Status Quo of Hate Content Research using Bibliometric Analy...

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2024 International Conference on Cybernation and Computation, CYBERCOM 2024

作者： Chetty, Naganna Alathur, Sreejith Pai, Vinayak NMAM Institute of Technology Nitte University Department of Information Science & Engineering Mangaluru India Indian Institute of Management Department of Information Systems Kozhikode India Manipal Institute of Technology MAHE Department of Computer Science & Engineering Manipal India

ISBN: (纸本)9798331542344

Expression of hate content through social media is prevalent and a global issue. The objective of this paper is to conduct analysis on hate content research and suggest policies to combat online hate content. The Scopus database containing published articles is queried with a set of keywords and filtering techniques to obtain relevant documents on hate content research. Different bibliometric analysis approaches such as bibliometric coupling, co-occurrence of keywords and citation analysis of documents are applied on selected dataset. Bibliometric analysis resulted with major sources of hate content research, most associated keywords with hate content and top cited articles. From the year 2015 onwards, there is a rapid increase in hate content research. Currently, different social media and its content are the most associated keywords with hate content. © 2024 IEEE.

关键词： bibliometric analysis bibliometric coupling governance hate content Social media violent

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