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IEEE Symposium on Computers and Communications

作者： Priscylla da S. Tavares Emanuel B. Rodrigues Group of Computer Networks Software Engineering and Systems (GREat) Graduate Program in Computer Science (MDCC) Federal University of Ceará (UFC) Fortaleza Brazil

With the progress of sensor technologies, there has been an increase in the number of connected computing devices capable of collecting information and interacting with the environment in which they are inserted, forming the basis of the Internet of Things (IoT). Such devices enable the development of new applications capable of making cities more intelligent, providing improvements to society and urban infrastructure. As a result of the interaction between different applications, there is a large set of data, from which useful knowledge can be extracted. An important problem to be faced is the recurrent occurrence of arbovirus outbreaks in big cities with tropical climate. This research proposes an architecture capable of aggregating data from different types of IoT devices, and manipulating them using data analytics techniques to assist the surveillance of arbovirus outbreaks. As an example of case study, we present an exploratory analysis of climatology data and cases of arbovirus diseases in the city of Fortaleza, Ceara, Brazil, between the years of 2011 and 2017.

关键词： Internet of Things Data analytics Health care Smart city

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Refining the E+A Galaxy: A spatially resolved spectrophotometric sample of nearby post-starburst systems in SDSS-IV MaNGA (MPL-5)

arXiv

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arXiv 2021年

作者： Greene, Olivia A. Anderson, Miguel R. Marinelli, Mariarosa Holley-Bockelmann, Kelly Campbell, Lauren E.P. Liu, Charles T. Department of Physics & Astronomy Vanderbilt University PMB 401807 2301 Vanderbilt Place NashvilleTN37206 United States Department of Software Engineering Bloomberg LP 731 Lexington Avenue New YorkNY10022 United States Department of Planetarium Education Science Museum of Virginia 2500 West Broad Street RichmondVA23220 United States Department of Life & Physical Sciences Fisk University 1000 17th Avenue North NashvilleTN37208 United States Department of Physics & Astronomy City University of New York College of Staten Island 2800 Victory Blvd Staten IslandNY10314 United States Department of Astrophysics & Hayden Planetarium American Museum of Natural History Central Park West at 79th Street New YorkNY10024-5192 United States Physics Program The Graduate Center CUNY New YorkNY10016 United States

Post-starburst galaxies are crucial to disentangling the effect of star formation and quenching on galaxy demographics. They comprise, however, a heterogeneous population of objects, described in numerous ways. To obtain a well-defined and uncontaminated sample, we take advantage of spatially-resolved spectroscopy to construct an unambiguous sample of E+A galaxies - post-starburst systems with no observed ongoing star formation. Using data from the Mapping Nearby Galaxies at Apache Point Observatory (MaNGA) Survey, in the fourth generation of the Sloan Digital Sky Survey (SDSS-IV), we have identified 30 E+A galaxies that lie within the green valley of color–stellar mass space. We first identified E+A candidates by their central, single-fiber spectra and (u-r) color from SDSS DR15, and then further required each galaxy to exhibit E+A properties throughout the entirety of the system to 3 effective radii. We describe our selection criteria in detail, note common pitfalls in E+A identification, and introduce the basic characteristics of the sample. We will use this E+A sample, which has been assembled with stringent criteria and thus re-establishes a well-defined sub-population within the broader category of post-starburst galaxies, to study the evolution of galaxies and their stellar populations in the time just after star formation within them is fully quenched. Copyright © 2021, The Authors. All rights reserved.

关键词： Galaxies

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Multiple criteria hierarchy process for sorting problems under uncertainty applied to the evaluation of the operational maturity of research institutions

arXiv

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arXiv 2019年

作者： Pelissari, Renata Abackerli, Alvaro José Amor, Sarah Ben Oliveira, Maria Célia Infante, Kleber Manoel Telfer Management School University of Ottawa Ottawa Canada Post Graduate Program of Industrial Engineering Methodist University of Piracicaba Santa Bárbara d’OesteSP Brazil Shool of Applied Sciences University of Campinas Limeira Brazil Embrapii-Brazilian Association for Industrial Research and Innovation BrasíliaDF Brazil Engineering School Mackenzie Presbyterian University São Paulo Brazil KMI Software Consulting Jundiaí Brazil

Despite the availability of qualified research personnel, up-to-date research facilities and experience in developing applied research and innovation, many worldwide research institutions face difficulties when managing contracted Research and Development (R&D) projects due to expectations from Industry (private sector), particularly regarding the applied development procedures, managerial processes and timing. Such difficulties have motivated funding agents to create evaluation processes to check whether the operational procedures of funded research institutions are sufficient to provide timely answers to demand for innovation from industry and also to identify aspects that require quality improvement in research development. For this purpose, several multiple criteria decision-making approaches can be applied. In this context, the research institutions are considered as alternatives for funding and their processes for research development as decision criteria. Among the available multiple criteria approaches, sorting methods are one prominent tool to evaluate the operational capacity. However, the first difficulty in applying multiple criteria sorting methods is the need to hierarchically structure multiple criteria in order to represent the intended decision process. Additional challenges include the elicitation of the preference information and the definition of criteria evaluation, since these are frequently affected by some imprecision. In most approaches, all these critical points are neglected, or, at best, only partially considered. In this paper, a new sorting method is proposed to deal with all of those critical points simultaneously. To consider multiple levels for the decision criteria, the FlowSort method is extended to account for hierarchical criteria. To deal with imprecise data, the FlowSort is integrated with fuzzy approaches. To yield solutions that consider fluctuations from imprecise weights, the Stochastic Multicriteria Acceptability Analysis

关键词： Decision making

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Transient Thermal Analysis of Welding Fixtures Design 2

Transient Thermal Analysis of Welding Fixtures Design

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2nd International Conference on Eco engineering Development 2018, ICEED 2018

作者： Anual, M.T. Sahroni, T.R. Akmal, S. Nasution, F.A. Faculty of Manufacturing Engineering Universiti Teknikal Malaysia Melaka Hang Tuah Jaya Durian Tunggal Melaka76100 Malaysia Industrial Engineering Department BINUS Graduate Program - Master of Industrial Engineering Bina Nusantara University Jakarta11480 Indonesia Faculty of Manufacturing Engineering Innovative Software System and Services Research Group Centre for Advanced Computing Technology Universiti Teknikal Malaysia Melaka Hang Tuah Jaya Durian Tunggal Melaka76100 Malaysia Industrial Engineering Department Faculty of Engineering Bina Nusantara University Jakarta11480 Indonesia

This paper presents the design and analysis of welding fixtures based on transient thermal analysis. Welding fixtures is designed to hold and support the workpiece securely during the welding process. The heat transformation from the workpiece could lead the temperature rises and impacts to the welding fixtures. Therefore, the study introduces the development of welding fixtures as one of a safety measure prevents the welder from injury while handling welding process. The conceptual design of welding fixtures and material were applied to conduct the simulation. Transient thermal analysis was performed on temperature and total heat flux by using computer aided engineering software. The result shows the analysis of equivalent stress, total deformation, factors of safety, fatigue life and fatigue damage. Furthermore, the equivalent stress failure theory used to predict yielding in welding fixture design. The design of welding fixtures and material selection were proposed to hold and support the workpiece securely. © 2018 Institute of Physics Publishing. All rights reserved.

关键词： Heat flux

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FUTURE-AI: International consensus guideline for trustworthy and deployable artificial intelligence in healthcare

arXiv

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arXiv 2023年

作者： Lekadir, Karim Feragen, Aasa Fofanah, Abdul Joseph Frangi, Alejandro F. Buyx, Alena Emelie, Anais Lara, Andrea Porras, Antonio R. Chan, An-Wen Navarro, Arcadi Glocker, Ben Botwe, Benard O. Khanal, Bishesh Beger, Brigit Wu, Carol C. Cintas, Celia Langlotz, Curtis P. Rueckert, Daniel Mzurikwao, Deogratias Fotiadis, Dimitrios I. Zhussupov, Doszhan Ferrante, Enzo Meijering, Erik Weicken, Eva González, Fabio A. Asselbergs, Folkert W. Prior, Fred Krestin, Gabriel P. Collins, Gary S. Tegenaw, Geletaw S. Kaissis, Georgios Misuraca, Gianluca Tsakou, Gianna Dwivedi, Girish Kondylakis, Haridimos Jayakody, Harsha Woodruf, Henry C. Mayer, Horst Joachim Aerts, Hugo JWL Walsh, Ian Chouvarda, Ioanna Buvat, Irène Tributsch, Isabell Rekik, Islem Duncan, James Kalpathy-Cramer, Jayashree Zahir, Jihad Park, Jinah Mongan, John Gichoya, Judy W. Schnabel, Julia A. Kushibar, Kaisar Riklund, Katrine Mori, Kensaku Marias, Kostas Amugongo, Lameck M. Fromont, Lauren A. Maier-Hein, Lena Alberich, Leonor Cerdá Rittner, Leticia Phiri, Lighton Marrakchi-Kacem, Linda Donoso-Bach, Lluís Martí-Bonmatí, Luis Cardoso, M. Jorge Bobowicz, Maciej Shabani, Mahsa Tsiknakis, Manolis Zuluaga, Maria A. Bielikova, Maria Fritzsche, Marie-Christine Camacho, Marina Linguraru, Marius George Wenzel, Markus De Bruijne, Marleen Tolsgaard, Martin G. Ghassemi, Marzyeh Ashrafuzzaman, Md Goisauf, Melanie Yaqub, Mohammad Abadía, Mónica Cano Mahmoud, Mukhtar M.E. Elattar, Mustafa Rieke, Nicola Papanikolaou, Nikolaos Lazrak, Noussair Díaz, Oliver Salvado, Olivier Pujol, Oriol Sall, Ousmane Guevara, Pamela Gordebeke, Peter Lambin, Philippe Brown, Pieta Abolmaesumi, Purang Dou, Qi Lu, Qinghua Osuala, Richard Nakasi, Rose Zhou, S. Kevin Napel, Sandy Colantonio, Sara Albarqouni, Shadi Joshi, Smriti Carter, Stacy Klein, Stefan Petersen, Steffen E. Aussó, Susanna Awate, Suyash Raviv, Tammy Riklin Cook, Tessa Mutsvangwa, Tinashe E.M. Rogers, Wendy A. Niessen, Wiro J. Puig-Bosch, Xènia Zeng, Yi Mohammed, Yunusa G. Aquino, Yves Saint James Salahuddin, Zohaib Starmans, Martijn P.A. Department de Matemàtiques i Informàtica Universitat de Barcelona Barcelona Spain Barcelona Spain DTU Compute Technical University of Denmark Kgs Lyngby Denmark Department of Mathematics and Computer Science Faculty of Science and Technology Milton Margai Technical University Freetown Sierra Leone Center for Computational Imaging & Simulation Technologies in Biomedicine Schools of Computing and Medicine University of Leeds Leeds United Kingdom Cardiovascular Science and Electronic Engineering Departments KU Leuven Leuven Belgium Institute of History and Ethics in Medicine Technical University of Munich Munich Germany Faculty of Engineering of Systems Informatics and Sciences of Computing Galileo University Guatemala City Guatemala Department of Biostatistics and Informatics Colorado School of Public Health University of Colorado Anschutz Medical Campus AuroraCO United States Department of Medicine Women’s College Research Institute University of Toronto Toronto Canada Universitat Pompeu Fabra BarcelonaBeta Brain Research Center Barcelona Spain Department of Computing Imperial College London London United Kingdom School of Biomedical & Allied Health Sciences University of Ghana Accra Ghana Department of Midwifery & Radiography School of Health & Psychological Sciences City University of London United Kingdom Kathmandu Nepal European Heart Network Brussels Belgium Department of Thoracic Imaging University of Texas MD Anderson Cancer Center Houston United States IBM Research Africa Nairobi Kenya Departments of Radiology Medicine and Biomedical Data Science Stanford University School of Medicine Stanford United States Institute for AI and Informatics in Medicine Klinikum rechts der Isar Technical University Munich Munich Germany Department of Computing Imperial College London London United Kingdom Muhimbili University of Health and Allied Sciences Dar es Salaam Tanzania United Republic of Ioannina Greece Almaty AI Lab Almaty Kazakhstan

Background: Despite major advances in artificial intelligence (AI) research for healthcare, the deployment and adoption of AI technologies remain limited in clinical practice. In recent years, concerns have been raised about the clinical, technical, ethical and legal risks associated with healthcare AI. To increase adoption in the real world, it is essential that AI technologies are trusted and accepted by patients, clinicians, health organisations and authorities. This paper describes the FUTURE-AI framework as the first international consensus guideline for trustworthy AI in healthcare. Methods: The FUTURE-AI consortium was founded in 2021 and now comprises 117 interdisciplinary experts from 50 countries representing all continents, including AI scientists, clinical researchers, biomedical ethicists, and social scientists. Over a two-year period, the consortium established guiding principles and best practices for trustworthy and deployable AI through an iterative process comprising an in-depth literature review, a modified Delphi survey, and online consensus meetings. Findings: The FUTURE-AI framework was established based on six guiding principles for trustworthy AI in healthcare, i.e. Fairness, Universality, Traceability, Usability, Robustness and Explainability. Through consensus, a set of 30 best practices were defined, addressing technical, clinical, socio-ethical and legal dimensions of trustworthy AI. The recommendations cover the entire lifecycle of healthcare AI, from design, development and validation to regulation, deployment, and monitoring. Interpretation: FUTURE-AI is a structured, risk-informed framework which provides guidance for constructing healthcare AI tools that will be trusted, deployed and adopted in real-world clinical practice. Researchers are encouraged to take the recommendations into account in proof-of-concept stages to facilitate future translation towards clinical practice of healthcare AI. Copyright © 2023, The Authors. All rights

关键词： Clinical research

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software Requirement Specification for the Automotive Sector: The Case of a Post-Collision Event Control System

Software Requirement Specification for the Automotive Sector...

引用

International Conference in software engineering Research and Innovation (CONISOFT)

作者： Jorge Rafael Aguilar Cisneros Genaro de la Rosa Garcia Carlos Alberto Fernández-y-Fernnádez Graduate program in Software Engineering Puebla Pue México Graduate program in Software Engineering Puebla Pue. México Computer Science Institute Oaxaca Mexico

Safety systems in the automotive sector are very important. Among these are ABS brake systems, stability control system, and air bag systems. One group of these safety systems is oriented toward collisions and are activated at different times, having specific objectives, for example 1) systems activated before a collision have the objective of preventing impact, 2) systems activated during a collision have the objective of minimizing the physical harm to occupants, and 3) after a collision, their objective is to minimize the time between the collision and arrival of outside assistance for the vehicle's occupants. However, while type 1 systems (passive) and type 2 systems (active) are currently in many vehicles, type 3 systems have not been thoroughly researched. Therefore, this article describes a proposal of the behavioral logic of a type 3 system, which is represented through a software requirement specification document (SRS). The SRS presented satisfies some of the recommendations of the requirements of the automotive standard ISO 26262 and two of the processes used relate to the requirements of the standard ISO/IEC/IEEE 15288.

关键词： ISO Standards Safety Automobiles Automotive engineering Stakeholders IEC Standards

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Evaluation Of Adherence To The Model Six Sigma Using Paraconsistent Logic

Evaluation Of Adherence To The Model Six Sigma Using Paracon...

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IEEE International Symposium on Innovations in Intelligent Systems and Applications (INISTA)

作者： Caique Z. Kirilo Jair M. Abe Marcelo Nogueira Kazumi Nakamatsu Luiz Carlos Machi Lozano Luiz A. de Lima Software Engineering Research Group Paulista University UNIP São Paulo Brazil Graduate Program in Production Engineering Paulista University UNIP São Paulo Brazil ALGORITMI Centre School of Engineering University of Minho Guimarães Portugal School of Human Science and Environment/H.S.E University of Hyogo Hyogo Japan

This study aims to present a compliance analysis tool to Six Sigma by integrating indicative of success and Paraconsistent Method Decision. This way is contributing to a previous scenario analysis that can help the im... 详细信息

ISBN: (纸本)9781538651513

关键词： Six sigma Belts Tools Companies Decision making Sensors

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Evaluation of an Instrument to Identify Factors that Impact the Motivation and Engagement of Undergraduate Students in Computing

Evaluation of an Instrument to Identify Factors that Impact ...

引用

Frontiers in Education (FIE) Conference

作者： Pablo Schoeffel Raul Sidnei Wazlawick Vinicius Faria Culmant Ramos Adilson Vahldick Marcelo de Souza Graduate Program in Computer Science Federal University of Santa Catarina Florianópolis Brazil Department of Informatics and Statistics Federal University of Santa Catarina Florianópolis Brazil Department of Information and Communication Technologies Federal University of Santa Catarina Araranguá Brazil Departament of Software Engineering University of Santa Catarina State Ibirama Brazil

ISBN: (纸本)9781538611753;9781538611746

This Research Paper presents the evaluation of an instrument to identify the impact of motivation and engagement factors in undergraduate students in computing. Although researches indicate a direct impact of motivation and engagement on student performance and retention, few studies have been found that address which factors are relevant in this process. The instrument is a questionnaire based on the compilation of several works of the literature containing 48 items divided into 6 groups: personal and demographic data, general perception about motivation, perception about the university, student behavior, perception about program and perception about classes/teachers. The questionnaire evaluation is based on a case study with 112 undergraduate students in software engineering. As a result, we found that the questionnaire can be considered reliable (Cronbach's alpha = .8904). Considering the validity of constructs, we found an acceptable degree of correlation between the most pair of items in each group (averaging 63%). We also found that the item-total correlation coefficient was only not adequate for one factor group, indicating satisfactory correlation for all other items. Finally, we found that the number of factors is coherent, but there are several items from different groups strongly correlated, indicating the need for a reorganization.

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Identification of Pre-University Factors that Affect the Initial Motivation of Students in Computing programs: A multi-institutional case study

Identification of Pre-University Factors that Affect the Ini...

引用

Frontiers in Education (FIE) Conference

ISBN: (纸本)9781538611753;9781538611746

This Research to Practice Paper presents the results of the evaluation of pre-university factors that impact the initial motivation of undergraduate students in computing. Although there are studies in the literature that have investigated some previous factors, this paper replicates a previous work that aims to consolidate several pre-university factors and, as the main differential, uses the AMS (Academic Motivation Scale), a scale already consolidated in the literature to measure students' initial motivation, and evaluate the relation between motivation and candidate factors. We applied a questionnaire to 159 students from different computing programs in ten universities, which evaluates 20 factors divided into 4 groups: personal and demographic data, taste and knowledge of the program and area, computing experience, and school performance. To evaluate the correlation between factors and motivation, we used Spearman's coefficient, t-student test, and ANOVA to evaluate the correlation between factors and motivation. As main results, we found significant variation in the initial motivation according to following factors: taste for programming and technology, knowledge about the undergraduate program content, correct perception about computing professionals, knowledge and experience in computer programming, and general school performance.

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Transient Thermal Analysis of Welding Fixtures Design

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IOP Conference Series: Earth and Environmental Science 2018年第1期195卷

作者： M T Anual T R Sahroni S Akmal F A Nasution Faculty of Manufacturing Engineering Universiti Teknikal Malaysia Melaka Hang Tuah Jaya 76100 Durian Tunggal Melaka Malaysia Industrial Engineering Department BINUS Graduate Program – Master of Industrial Engineering Bina Nusantara University Jakarta Indonesia 11480 Faculty of Manufacturing Engineering Innovative Software System & Services Research Group Centre for Advanced Computing Technology Universiti Teknikal Malaysia Melaka Hang Tuah Jaya 76100 Durian Tunggal Melaka Malaysia. Industrial Engineering Department Faculty of Engineering Bina Nusantara University Jakarta Indonesia 11480

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