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Extending the Core Ontology on Decision Making according to Behavioral Economics 14

Extending the Core Ontology on Decision Making according to ...

14th Seminar on Ontology Research in Brazil, ONTOBRAS 2021 and 5th Doctoral and Masters Consortium on Ontologies, WTDO 2021

作者： Ramos, Eduardo C. Campos, Maria Luiza M. Baião, Fernanda Guizzardi, Renata Graduate Program in Informatics Universidade Federal do Rio de Janeiro RJ Rio de Janeiro Brazil RJ Rio de Janeiro Brazil Department of Industrial Engineering and Business Information Systems University of Twente Enschede Netherlands

Decisions are constantly made and some of them may be extremely critical. However, most decision makers are unaware that their decisions may be biased. We used Behavioral Economics as a foundation to propose an ontology that shows how decision makers’ preferences are set and the situation in which they occur in an intuitive decision under risk and uncertainty. Our aim is that this ontology be used to improve their decisions by allowing them a better understanding of how they decide. In addition, this ontology can be used as part of a strategy to reduce biases. © 2021 Copyright for this paper by its authors.

关键词： Ontology

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Permanent Magnet Synchronous Motor Drive Control for Hybrid Construction Machinery - Revisited

Permanent Magnet Synchronous Motor Drive Control for Hybrid ...

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IEEE Transportation Electrification Conference and Expo (ITEC)

作者： Thiago M. Parreiras Dener A. de L. Brandao Mariana de F. Ramos Thales A. C. Maia Tomás P. Corrêa Igor A. Pires Anderson Nascimento Braz de J. C. Filho Institute of Technological Sciences Universidade Federal de Itaiubá Itabira Brazil Graduate Program in Electrical Engineering Universidade Federal de Minas Gerais Belo Horizonte Brazil Department of Electrical Engineering Universidade Federal de Minas Gerais Belo Horizonte Brazil Department of Electronics Engineering Universidade Federal de Minas Gerais Belo Horizonte Brazil South America Tractor Backhoe Loader CNH Industrial Brasil Contagem Brazil

Hybrid Construction Machinery (HCM) differs from conventional Hybrid Electric Vehicles (HEV) by offering fuel consumption reduction not only in the traction system, but mainly in its hydraulic work implements. Regardless of the type of hybridization considered (series, parallel or series-parallel), Permanent Magnet Synchronous Machines (PMSM) are increasingly consolidating their position as the preferred option. Commercial motor drive systems usually can benefit of some revision in its control system and to take into account some of the specific needs of HCMs. This work revisit the PMSM drive control topic in face of the HCM requirements along with a method for controllers adjust, which is based in the disturbance-output relationship and makes use of feedforward and disturbance decoupling actions. Furthermore, it compares the proposed schemes with the ones used by some commercial products and shows how the they can improve the system disturbance rejection. Simulation and experimental results shows a better speed regulation with the proposed approach.

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COMPETITIVE ADVANTAGE MODEL THROUGH KNOWLEDGE MANAGEMENT systems IMPLEMENTATION TO OPTIMIZE BUSINESS SUSTAINABILITY 9

COMPETITIVE ADVANTAGE MODEL THROUGH KNOWLEDGE MANAGEMENT SYS...

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9th International Conference on Information Technology: IoT and Smart City, ICIT 2021

作者： Sardjono, Wahyu Lusia, Erma Utomo, Hargo Sukardi, Samudra Rahmasari, Aninda Regent Montororing, Yuri Delano Information Systems Management Department Binus Graduate Program Bina Nusantara University Indonesia Research Capacity Building Research & Development Bina Nusantara University Indonesia Department of Management Faculty of Economic and Business Gajah Mada University Indonesia Graduate Program Faculty of Economy and Business University of Indonesia Indonesia International Relations Department Faculty of Humanities Bina Nusantara University Indonesia Industrial Engineering Study Program Bhayangkara University Indonesia

ISBN: (纸本)9781450384971

Complaint resolution that arise due to internal and external factors in a company can be monitored through the Service Recovery Index (SRI), and SRI is developed through a number of factors that influence it. Meanwhile, the SRI model needs to be developed to see the business sustainability through implementation knowledge management system in the organization. The data collection method was carried out, starting with building a research instrument based on knowledge management theory and continued with observation and distributing questionnaires to respondents who were involved in the business process of managing SRI. The data analysis method was used to process the data from the questionnaire, factor analysis method was used and the method to build the model used was the regression analysis method. The results obtained from this study are the discovery of 4 (four) factors with a number of indicators that are grouped on each formed factor, which can then be made and built a readiness model that reflects current conditions, so that it can be used to build predictions in the future related to readiness. implementation of knowledge management system development in order to support increased understanding of the service recovery index in the organization. © 2021 ACM.

关键词： Knowledge management

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Factors for design of performance measurement systems for not-for-profit organizations

Factors for design of performance measurement systems for no...

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2016 industrial and systems engineering Research Conference, ISERC 2016

作者： Moura, Louisi Francis de Lima, Edson Pinheiro Deschamps, Fernando van Aken, Eileen Gouvea da Costa, Sergio E. Industrial and Systems Engineering Graduate Program Pontifical Catholic University of Parana Curitiba Brazil Federal University of Technology - Parana Curitiba Brazil Department of Mechanical Engineering Federal University of Parana Curitiba Brazil Grado Department of Industrial and Systems Engineering Virginia Tech Blacksburg United States

The scope of this research is delimited by the study of not-for-profit organizations performance through operations management lens. According to a systematic literature review, the performance measurement frameworks applied to not-for-profit organizations are adaptations of models developed for for-profit companies. However, the specific characteristics related to participatory governance, responsibility to declare their tangible and intangible results, and accountability of different revenue sources that combine donations, governmental aids, volunteering or public financing are usually not properly considered. In this context, this paper intends to identify factors that intervene in not-for-profit organizations' performance measurement systems, and to organize them in a conceptual framework that could assist not-for-profit organizations to better design their performance measurement systems. The paper also analyzes how enterprise engineering design principles can be applied in this context, relating the intervening factors to enterprise engineering guidelines. © 2016 Proceedings of the 2016 industrial and systems engineering Research Conference, ISERC 2016. All rights reserved.

关键词： industrial research

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Deep Learning with Greedy Layer-Wise Compound Scaling for Temperature and Humidity Prediction in Solar Dryer Dome

SSRN

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SSRN 2022年

作者： Cenggoro, Tjeng Wawan Elwirehardja, Gregorius Natanael Dominic, Nicholas Setiawan, Karli Eka Rahutomo, Reza Djuana, Endang Gunawan, Fergyanto E. Budiman, Arief S. Romeli, Sugiarto Pardamean, Bens Computer Science Department School of Computer Science Bina Nusantara University Jakarta11480 Indonesia Bioinformatics and Data Science Research Center Bina Nusantara University Jakarta11480 Indonesia Computer Science Department BINUS Graduate Program Master of Computer Science Program Bina Nusantara University Jakarta11480 Indonesia Information Systems Department School of Information Systems Bina Nusantara University Jakarta11480 Indonesia Electrical Engineering Department Faculty of Industrial Technology Universitas Trisakti Jakarta11440 Indonesia Industrial Engineering Department BINUS Graduate Program Master of Industrial Engineering Bina Nusantara University Jakarta11480 Indonesia Department of Manufacturing and Mechanical Engineering and Technology Oregon Institute of Technology Klamath FallsOR97601 United States PT. Impack Pratama Industri Jakarta Indonesia

Drying has been an eco-friendly and cost-efficient method to reduce post-harvest losses of agricultural crops. In various countries, the technique has been widely utilized in the form of Solar Dryer Dome (SDD) buildings. Accurate indoor microclimate forecasting is very important to implement smart control systems in SDDs that can maintain the ideal conditions, as the availability of solar energy is limited only at daytimes and the temperature may drop significantly during nighttimes in remote areas. The microclimate variables that play an important role in maintaining ideal environmental conditions include temperature and relative humidity. © 2022, The Authors. All rights reserved.

关键词： Forecasting

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A New Damage Index for Structural Health Monitoring: A Comparison of Time and Frequency Domains

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Procedia Computer Science 2021年 179卷 930-935页

作者： Fergyanto E. Gunawan Tran Huu Nhan Muhammad Asrol Yasuhiro Kanto Insannul Kamil Sutikno Industrial Engineering Department BINUS Graduate Program - Master of Industrial Engineering Bina Nusantara University Jakarta Indonesia 11480 Department of Automotive Engineering Faculty of Transportation Engineering Ho Chi Minh City University of Technology Ho Chi Minh City Viet Nam Mechanical Systems Engineering College of Engineering Ibaraki University Ibaraki Japan Department of Industrial Engineering Department Faculty of Engineering Andalas University Padang Indonesia Department of Mechanical Engineering Department Faculty of Engineering Institut Teknologi Sepuluh Nopember Surabaya Indonesia

With the adoption of the damage tolerance design principle, the health monitoring system has become an integral part of the operation of engineering structures. For the system to work, a damage indicator that describes the structural integrity level should be established and monitored. The damage indicator is usually derived from structural responses. Many quantities have been proposed for damage indicator including natural frequency, mode shape, curvature, strain energy, and t-, F-, and z-statistics. In this paper, we propose a new damage indicator in the time and frequency domains derived from the Euler-Bernoulli beam theory. We evaluate the method by using data obtained from a numerical simulation of a cracked beam. The beam deformation is nonlinear due to the contact between the crack faces during vibration. The proposed damage index is estimated in the domains for various observation points on the beam. Besides, the existence of the crack is also predicted by the widely used traditional method based on the change of the natural frequency and mode shape. A comparison is made between the present method and the existing ones. We conclude the present proposal is more sensitive to detect the crack.

关键词： Euler-Bernoulli Beam Structural Health Monitoring Damage Indicator Natural Frequency Finite Element Method

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Efficient Hardware Implementation of Nonlinear Moving-horizon State Estimation with Artificial Neural Networks

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IFAC-PapersOnLine 2020年第2期53卷 7813-7818页

作者： Rafael Koji Vatanabe Brunello Renato Coral Sampaio Carlos H Llanos Leandro dos Santos Coelho Helon Vicente Hultmann Ayala Department of Mechanical Engineering UnB 70910-900 DF Brazil Industrial and Systems Engineering Graduate Program PUCPR 80215-910 PR Brazil Department of Electrical Engineering UFPR 81531-980 PR Brazil Department of Mechanical Engineering PUC-Rio 22231-180 RJ Brazil

In this contribution we investigate the application of radial basis functions artificial neural networks embedded in hardware for real-time moving-horizon state estimation. The solution of the optimal moving-horizon state estimation problem may be faced as the mapping from the inputs and outputs of the system to the state estimates according to the system model. This mapping may be solved offline with the optimal formulation and then approximated by any higher order function approximation algorithm, such as the ones from machine learning. An approximate version with radial basis functions neural networks is developed and implemented in a Field programmable Gate Array (FPGA) showing good results in terms of accuracy and computational time. We show that the state estimate using the approximate version of the moving-horizon algorithm can be run using a laboratory scale kit of approximately 500 kHz for an inverted pendulum at a clock rate of about 110 MHz. The latency to provide an estimate can be further reduced when FPGAs with higher clocks are used as the artificial neural network architecture is inherently parallel.

关键词： Estimation filtering Nonlinear observers filter design Nonlinear predictive control Neural networks Embedded computer architectures

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Big data in healthcare:Conceptual network structure,key challenges and opportunities

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Digital Communications and Networks 2023年第4期9卷 856-868页

作者： Leonardo B.Furstenaua Pedro Leivas Michele Kremer Sott Michael S.Dohan Jose Ricardo Lopez-Robles Manuel J.Cobo Nicola Luigi Bragazzi Kim-Kwang Raymond Choo Post-Graduate Program in Industrial Engineering Federal University of Rio Grande Do SulPorto Alegre90035-190Brazil University of Santa Cruz Do Sul Av.Independencia 2293Santa Cruz Do SulRSBrazil Business School Unisinos UniversityAv.Dr.Nilo Peçanha 160091330-002Porto AlegreBrazil Faculty of Business Administration Lakehead UniversityThunder BayOntarioCanada Autonomous University of Zacatecas Av.Ramon Lopez Velarde Col.CentroZacatecas98000Mexico Department of Computer Science and Artificial Intelligence Andalusian Research Institute in Data Science and Computational Intelligence(DaSCI)University of GranadaGranada 18071Spain York University ON M3J 1P3Canada Department of Information Systems and Cyber Security University of Texas at San AntonioSan AntonioTX78249USA

Big data is a concept that deals with large or complex data sets by using data analysis tools(e.g.,data mining,machine learning)to analyze information extracted from several sources *** data has attracted wide attention from academia,for example,in supporting patients and health professionals by improving the accuracy of decision-making,diagnosis and disease *** research aimed to perform a Bibliometric Performance and Network Analysis(BPNA)supported by a Scoping Review(SR)to depict the strategic themes,thematic evolution structure,main challenges and opportunities related to the concept of big data applied in the healthcare *** this goal in mind,4857 documents from the Web of Science covering the period between 2009 to June 2020 were analyzed with the support of SciMAT *** bibliometric performance showed the number of publications and citations over time,scientific productivity and the geographic distribution of publications and research *** strategic diagram yielded 20 clusters and their relative importance in terms of centrality and *** thematic evolution structure presented the most important themes and how it changes over ***,we presented the main challenges and future opportunities of big data in healthcare.

关键词： Big data Healthcare digitalization Bibliometric Strategic intelligence Co-word analysis SciMAT

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Using Online Grocery Applications during the COVID-19 Pandemic: Their Relationship with Open Innovation

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Journal of Open Innovation: Technology, Market, and Complexity 2022年第2期8卷

作者： Gumasing, Ma. Janice J. Prasetyo, Yogi Tri Persada, Satria Fadil Ong, Ardvin Kester S. Young, Michael Nayat Nadlifatin, Reny Redi, Anak Agung Ngurah Perwira School of Industrial Engineering and Engineering Management Mapúa University 658 Muralla St. Intramuros Manila 1002 Philippines School of Graduate Studies Mapúa University 658 Muralla St. Intramuros Manila 1002 Philippines Entrepreneurship Department BINUS Business School Undergraduate Program Bina Nusantara University Malang 65154 Indonesia Department of Information Systems Institut Teknologi Sepuluh Nopember Kampus ITS Sukolilo Surabaya 60111 Indonesia Industrial Engineering Department BINUS Graduate Program—Master of Industrial Engineering Bina Nusantara University Jakarta 11480 Indonesia

This present research examines the behavioral intentions of Filipinos to use online grocery applications during the novel COVID-19 pandemic. The study proposes an integration of the health belief model (HBM) and the Unified Theory of Acceptance and Use of Technology (UTAUT2) to identify the factors affecting the acceptance and usage of Filipinos of online grocery applications in terms of the impact of health risk for COVID-19. To accurately measure the factors and their relationship to behavioral intentions and usage behavior, a questionnaire was developed and distributed to 373 residents in the Philippines. Partial least squares structural equation modeling (PLS-SEM) was applied as an analytical method for this study. The results revealed that performance expectancy, perceived benefits, perceived severity, and cues to action significantly influenced the behavioral intentions and usage of online grocery apps during the COVID-19 pandemic. The study’s findings can be utilized as a theoretical framework for future researchers of consumer behavior;e-commerce developers;and grocery industry retailers, to enhance the innovation and services of online grocery applications. The results of this study may also be used and capitalized on by investors and managers to apply in strategizing when developing and marketing online grocery applications among con-sumers. Moreover, the framework of this study may be adopted and utilized by other online markets, even in different counties. Further theoretical and practical aspects are discussed in this paper. © 2022 by the authors. Licensee MDPI, Basel, Switzerland.

关键词： health belief model online grocery applications structural equation modeling UTAUT2

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Towards a Predictive Approach for Omni-channel Retailing Supply Chains

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IFAC-PapersOnLine 2019年第13期52卷 844-850页

作者： Pereira, Marina Meireles Frazzon, Enzo Morosini Graduate Program in Production Engineering Industrial and Systems Engineering Department Technology Center Federal University of Santa Catarina Florianópolis Santa Catarina Brazil

The adoption of omni-channel strategy has changed the relation between retailers and customers and brought more complexity to the retailing supply chains. To address the increasing complexity, it is necessary to adopt innovative approaches based on information technologies and intelligent decision methods. The challenges to retailers are improving the accuracy of offline and online channels demand forecasting, better managing offline and online customer's needs, thus reducing the uncertainties of the omni-channel retailing supply chain. In this context, this research paper aims to propose a predictive approach for omni-channel retailing supply chain combining clustering with artificial neural network to handle demand uncertainty. © 2019, IFAC (International Federation of Automatic Control) Hosting by Elsevier Ltd. All rights reserved.

关键词： Neural networks Complex networks Learning systems Sales Supply chain management Channel strategies Clustering Demand forecasting Demand uncertainty Innovative approaches Intelligent decisions Omni channel Retail supply chain

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