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A robust optimization approach for measuring efficiency in stochastic DEA

AIP Conference Proceedings 2023年第1期2714卷

作者： Hengki Tamando Sihotang Syahril Efendi Muhammad Zarlis Herman Mawengkang Doctoral Program Faculty of Computer Science and Information Technology Universitas Sumatera Utara. FEBO Indonesia Faculty of Computer Science and Information Technology Universitas Sumatera Utara. FEBO Indonesia Faculty of Mathematics and Natural Sciences Universitas Sumatera Utara. FEBO Indonesia

The classic data envelopment analysis (DEA) concept assumes that decision making unit (DMU) inputs and outputs can be clearly measured because they have definite values. However, there are times when there is uncertainty in a situation. This study looks at how to build a DEA model with input and output uncertainty. In the DEA model, the uncertainty situation is approached using a stochastic concept. Furthermore, the robust optimization method, which can solve the uncertainty problem, is introduced. As a result, at the conclusion of this study, a robust optimization model based on the Stochastic DEA concept is introduced.

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Framework for tackling stochastic DEA based on data-driven approach

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AIP Conference Proceedings 2023年第1期2714卷

作者： Hengki Tamando Sihotang Syahril Efendi Muhammad Zarlis Herman Mawengkang Doctoral Program Faculty of Computer Science and Information Technology Universitas Sumatera Utara Medan Indonesia Faculty of Computer Science and Information Technology Universitas Sumatera Utara Medan Indonesia Faculty of Mathematics and Natural Sciences Universitas Sumatera Utara Medan Indonesia

Data Envelopment Analysis (DEA) is a linear programming-based technique used to evaluate the relative efficiency of multi-input and multi-output decision-making units based on observed data by comparing one decision-making unit (DMU) with another DMU. The efficacy assessment process sometimes involves a stochastic approach due to the uncertainty inherent in many real life problems, so the DEA model discussed in this paper is the stochastic DEA (SDEA) model. Data-driven decision-making is based entirely on the data involved. This paper proposes a framework for the completion of SDEA based on a data-driven approach.

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A Platform for Monitoring Student Commuting in the Use of School Transport in Smart Cities - A Facial Recognition Based Approach

A Platform for Monitoring Student Commuting in the Use of Sc...

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International Conference on Smart Communications and Networking (SmartNets)

作者： Jessé Da Costa Rocha Marcela Alves de Souza Evelin Helena Silva Cardoso Nandamudi Vijaykumar Jasmine Priscyla Leite de Araújo Renato Lisboa Francês Graduate Program in Electrical Engineering Institute of Technology Federal University of Pará (UFPA) Belém Pará Brazil Information and Communication Technology Center Federal University of the South and Southeast of Para (Unifesspa) Marabá Pará Brazil Department of Computer Science Federal Rural University of the Amazon (UFRA) Capitão Poço Pará Brazil Coordination of Applied Research and Technological Development National Institute for Space Research (INPE) São Paulo Brazil

This article proposes an intelligent platform for monitoring students' steps on their way to school until they leave the school to their homes. This platform can identify students and notify those responsible and competent authorities in various situations of school life, such as: entering and leaving the school bus, entering and leaving school, entering the school cafeteria, etc. The first application aims to control access to the school bus through facial recognition. In the tests carried out, the recognition system achieved excellent results in all metrics.

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Design of Mobile Application for a Smart Home Nutrition System (SmartNS) 1st

Design of Mobile Application for a Smart Home Nutrition Syst...

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1st International Conference on Advanced Research in Technologies, information, Innovation and Sustainability, ARTIIS 2021

作者： Carrisosa, Carlos Alanis, Arnulfo Sotelo, Javier Student of the Master’s Program in Information Technology Department of Systems and Computing National Technology of Mexico Campus Tijuana Calzada del Tecnológico S/N Fraccionamiento Tomas Aquino Tijuana B.C.22414 Mexico Systems and Computer Department National Technology of México Campus Tijuana Calzada del Tecnológico S/N Fraccionamiento Tomas Aquino Tijuana B.C.22414 Mexico Computer Systems Student Department of Systems and Computing National Technology of Mexico Campus Tijuana Calzada del Tecnológico S/N Fraccionamiento Tomas Aquino Tijuana B.C.22414 Mexico

ISBN: (纸本)9783030902407

Every day there are more devices or objects that connect to the internet, these devices are found in different areas in the home, health, industry and others, this project is implemented in the internet of things for homes, it is a module called "nutrition", the which allows you to have a record of diets provided by a nutritionist, this allows reducing costs and food waste because with the mobile application called: Mobile application for smart appliances (EInt), you can obtain the products directly from a preferred provider. Given the situation current due to the COVID-19 pandemic, exits to non-essential situations have been reduced, this prototype pretends to be a support for users when making errand purchases and avoid going out as little as possible. The analysis and design of the device contains several agents, this article describes the nutrition agent, the food ontology, its semantic network. © 2021, Springer Nature Switzerland AG.

关键词： Internet of things

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Export- and import-based economic models for predicting global trade using deep learning

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Expert Systems with Applications 2023年 218卷

作者： Yang, Cheng-Hong Lee, Cheng-Feng Chang, Po-Yin Department of Information Management Tainan University of Technology Tainan City710302 Taiwan Department of Electronic Engineering National Kaohsiung University of Science and Technology Kaohsiung80778 Taiwan Drug Development and Value Creation Research Center Kaohsiung Medical University Kaohsiung80708 Taiwan Ph. D. Program in Biomedical Engineering Kaohsiung Medical University Kaohsiung80708 Taiwan School of Dentistry Kaohsiung Medical University Kaohsiung80708 Taiwan Department of Business Administration National Kaohsiung University of Science and Technology Kaohsiung80778 Taiwan Department of Computer Science and Information Engineering National Quemoy University Kinmen County 892 Taiwan

Forecasting global foreign trade is essential for developing government trade policies and management strategies for multinational corporations. However, achieving an accurate trade forecast is challenging because of the complex structural relationships between exports, imports and other economic variables. Many traditional forecasting models, such as time series, econometric, and machine learning, provide less accurate forecasts for trade data. This paper proposes an ensemble learning approach to improve forecasting performance by hybridizing the structural relationships between trade and deep learning models to predict foreign trade for ten major countries. The proposed method first establishes a cointegration relationship between exports and imports and their structural variables. The cointegrated models are then used to predict the future of trade, which is used as a benchmark model for comparison. A hybrid deep learning algorithm uses the cointegrated variables as input variables to predict trade data, and then are compared with time-series forecasts and economic structural models. The experimental results reveal that the ensemble learning method can achieve excellent forecasting performance for the tested periods of trade data. In most cases, the root means square error and mean absolute percentage error values are smaller than the time series and economic structural models. © 2023 Elsevier Ltd

关键词： Forecasting

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Parameter Optimization of Support Vector Regression Using Harris Hawks Optimization

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Procedia computer Science 2021年 179卷 17-24页

作者： I Nyoman Setiawan Robert Kurniawan Budi Yuniarto Rezzy Eko Caraka Bens Pardamean Computational Statistics Department Polytechnic of Statistics - STIS Jakarta 13330 Indonesia Department of Information Management College of Informatics Chaoyang University of Technology Taiwan (ROC) Bioinformatics and Data Science Research Center Bina Nusantara University Indonesia 11530 Computer Science Department BINUS Graduate Program - Master of Computer Science Program Bina Nusantara University Jakarta Indonesia. 11530.

Support Vector Regression (SVR) is often used in forecasting. Adjustment of parameters in the SVR affects the results of forecasting. This study aims to analyze the SVR method that is optimized using Harris Hawks Optimization (HHO), hereinafter referred to as HHO-SVR. The HHO-SVR was evaluated using five benchmark datasets to determine the performance of this method. The HHO process is also compared based on the type of kernel and other metaheuristic algorithms. The results showed that the HHO-SVR has almost the same performance as other methods but is less efficient in terms of time. In addition, the type of kernel also affects the process and results.

关键词： SVR harris hawks optimization parameter optimization kernel forecasting

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Accelerating Medical Knowledge Discovery through Automated Knowledge Graph Generation and Enrichment

arXiv

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arXiv 2024年

作者： Khalid, Mutahira Rahman, Raihana Abbas, Asim Kumari, Sushama Wajahat, Iram Bukhari, Syed Ahmad Chan TIB - Leibniz Information Centre for Science and Technology Lower Saxony Hannover Germany Department of Statistics Harvard University CambridgeMA United States School of Computer Science University of Birmingham Edgbaston BirminghamB15 2TT United Kingdom Sr Technical Program Manager Routing and Planning Amazon BellevueWA United States Institute for Biotechnology St. John's University New YorkNY United States Division of Computer Science Mathematics and Science St. John's University New YorkNY United States

Knowledge graphs (KGs) serve as powerful tools for organizing and representing structured knowledge. While their utility is widely recognized, challenges persist in their automation and completeness. Despite efforts in automation and the utilization of expert-created ontologies, gaps in connectivity remain prevalent within KGs. In response to these challenges, we propose an innovative approach termed "Medical Knowledge Graph Automation (M-KGA)". M-KGA leverages user-provided medical concepts and enriches them semantically using BioPortal ontologies, thereby enhancing the completeness of knowledge graphs through the integration of pre-trained embeddings. Our approach introduces two distinct methodologies for uncovering hidden connections within the knowledge graph: a cluster-based approach and a node-based approach. Through rigorous testing involving 100 frequently occurring medical concepts in Electronic Health Records (EHRs), our M-KGA framework demonstrates promising results, indicating its potential to address the limitations of existing knowledge graph automation techniques. © 2024, CC BY-NC-ND.

关键词： Knowledge graph

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Fast Measurement of Impedance Calculation for Electrochemical Impedance Spectroscopy

Fast Measurement of Impedance Calculation for Electrochemica...

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International SoC Design Conference, ISOCC

作者： En-Chi Yang Suz-Ting Wang Kusn-Lin Liu Wen-Ho Juang Ming-Hwa Sheu How-Chiun Wu Shin-Chi Lai Dept. Electronics Engineering / Dept. Doctor’s Program of Smart Industry Technology Research and Design National Yunlin University of Science and Technology / National Formosa University Douliu Taiwan / Huwei Taiwan Dept. Doctor’s Program of Smart Industry Technology Research and Design National Formosa University Huwei Taiwan Dept. Electronics Engineering National Yunlin University of Science and Technology Douliu Taiwan Dept. Computer Science and Information Engineering National Formosa University Huwei Taiwan Dept. Natural Biotechnology Nanhua University Chiayi Taiwan Dept. Automation Engineering & Smart Machinery and Intelligent Manufacturing Research Center National Formosa University Huwei Taiwan

This paper presents a design for a fast measurement electrochemical impedance spectroscopy (EIS) system, which differs from the traditional single-frequency point calculation approach. The proposed system is capable of simultaneously measuring 23 frequency points within the frequency range of 1Hz-10KHz. Additionally, it has an impedance measurement range of 100$\omega$ - 1M$\omega$. The experimental results demonstrate that the average MRE and PAE are both below 0.4% and 1°, with conditions of R=9940 $\omega$ and C=1.02uF.

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Ideation of Engineering Solutions for Sustainable Development Goals: A Collaborative Course Between Thai and Japanese Students

Ideation of Engineering Solutions for Sustainable Developmen...

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IEEE Region 10 International Conference TENCON

作者： Kodchakorn Krutphong Natt Leelawat Jing Tang Eri Ota Rie Murakami Suzuki Yuki Taoka Proadpran Punyabukkana Environmental Engineering and Disaster Management Program Mahidol University Thailand Department of Industrial Engineering Faculty of Engineering Chulalongkorn University and Disaster and Risk Management Information Systems Research Unit Chulalongkorn University Thailand International School of Engineering Chulalongkorn University Center for International Education Tokyo Institute of Technology Japan School of Environmet and Society Tokyo Institute of Technology Japan Department of Computer Engineering Faculty of Engineering Chulalongkorn University and the Learning Innovation Center Chulalongkorn University Thailand

A collaborative course called Global Awareness for technology Implementation was conducted by the Faculty of Engineering, Chulalongkorn University, Thailand, and the Tokyo Institute of technology, Japan. The objective of this course was to facilitate the exchange of knowledge, perspectives, and experiences between Thai and Japanese students through project work, using an engineering design approach and the design thinking process to create innovation relevant to the Sustainable Development Goals (SDGs). During the class, experts shared their knowledge and experiences with the students. The students then worked on their respective projects to develop solution concepts using the design thinking process. The proposed ideas include the application for English class, smart water quality checker, hydrogen-based energy system for rural area, reduced wasted fashion solution, and auto waste sorting machine. Finally, this study concluded with a summary of the results and findings on the empathy process in the chosen SDGs, and of the commonalities and differences between Thailand and Japan in terms of ideation.

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High-Order Cardiomyopathy Human Heart Model and Mesh Generation

High-Order Cardiomyopathy Human Heart Model and Mesh Generat...

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2021 Computing in Cardiology, CinC 2021

作者： Mohammadi, Fariba Shontz, Suzanne M Linte, Cristian A Department of Mechanical Engineering University of Kansas LawrenceKS United States Department of Electrical Engineering and Computer Science University of Kansas LawrenceKS United States Bioengineering Program University of Kansas LawrenceKS United States Information and Telecommunication Technology Center University of Kansas LawrenceKS United States Chester F Carlson Center for Imaging Science Rochester Institute of Technology RochesterNY United States Department of Biomedical Engineering Rochester Institute of Technology RochesterNY United States

ISBN: (纸本)9781665479165

Faithful, accurate, and successful cardiac biomechanics and electrophysiological simulations require patient-specific geometric models of the heart. Since the cardiac geometry consists of highly-curved boundaries, the use of high-order meshes with curved elements would ensure that the various curves and features present in the cardiac geometry are well-captured and preserved in the corresponding mesh. Most other existing mesh generation techniques require computer-aided design files to represent the geometric boundary, which are often not available for biomedical applications. Unlike such methods, our technique takes a high-order surface mesh, generated from patient medical images, as input and generates a high-order volume mesh directly from the curved surface mesh. In this paper, we use our direct high-order curvilinear tetrahedral mesh generation method [1] to generate several second-order cardiac meshes. Our meshes include the left ventricle myocardia of a healthy heart and hearts with dilated and hypertrophic cardiomyopathy. We show that our high-order cardiac meshes do not contain inverted elements and are of sufficiently high quality for use in cardiac finite element simulations. © 2021 Creative Commons.

关键词： Heart

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