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11th and 12th EAI International Conference on Big Data Technologies and Applications, BDTA 2021 and BDTA 2022

作者： Santos, Cibele Góes, Fabrício Martins, Carlos da Cunha, Felipe Post-Graduation Program in Electrical Engineering Pontifícia Universidade Católica de Minas Gerais MG Belo Horizonte30535-901 Brazil Informatics Department University of Leicester Leicester United Kingdom Post-Graduation Program in Informatics Pontifícia Universidade Católica de Minas Gerais MG Belo Horizonte30535-901 Brazil Department of Computer Science Pontifícia Universidade Católica de Minas Gerais MG Belo Horizonte30535-901 Brazil

ISBN: (纸本)9783031336133

Candidate selection platforms have been widely used in companies that seek agility in the process of hiring. Candidates who do not meet the requirements of a job vacancy are disqualified in the first step, called screening. This stage has been automated due to the large volume of curriculum vitae (CV) of candidates per vacancy, particularly for internship vacancies. As a consequence, candidates receive little to none feedback and do not know how to improve/optimize their CVs for new applications. The goal of this paper is to realize the curriculum vitae optimization (CVO) process for internship vacancies by implementing a recommendation system that given an undergraduate student CV, it suggests the addition of relevant keywords, taking into account the student’s undergraduate course. This system is implemented based on the clustering of CVs keywords, from an internship recruitment private company database, into profile groups which are linked to internship vacancies. The experimental results showed that recommendations improved students CVs similarity (competitiveness within a specific field) from 18.83%, with 3 keywords recommendation, up to 50.67%, with 10 words. © 2023, ICST Institute for Computer Sciences, Social informatics and Telecommunications Engineering.

关键词： Students

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Analyses of Photovoltaic Systems Performance with Fuzzy Inference Systems and Bayesian Networks

Analyses of Photovoltaic Systems Performance with Fuzzy Infe...

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Power Electronics and Control (SEPOC), Seminar on

作者： Nicole Polityto Cremasco Myriam Regattieri De Biase da Silva Delgado Jair Urbanetz Junior Luiz Ledo Mota Melo Jorge Assade Leludak Keiko Verônica Ono Fonseca Program of Post-Graduation of Electrical Engineering and Industrial Informatics(CPGEI) of Federal University of Technology of Paraná(UTFPR) Program of Post-Graduation of Electrical Engineering and Industrial Informatics(CPGEI) of the Federal University of Technology of Paraná(UTFPR) Program of Post-Graduation in Energy Systems of Federal University of Technology of Paraná(UTFPR Department of Electrical Engineering (DAELT)) Federal University of Technology of Paraná(UTFPR) Curitiba Brazil

Renewable energy sources have been increasingly targeted as an alternative for reducing fossil fuel emissions. This scenario requires a better understanding of energy systems' performance and limitations, notably using photovoltaic setups under diverse meteorological conditions and determining device measurement uncertainties. Accordingly, this study conducts a performance evaluation of a photovoltaic system of copper, indium, and gallium (di)selenide technology. It compares the results provided by a reference normalized equation with two interpretable artificial intelligence techniques, Fuzzy Inference System and Bayesian Networks, when temperature is also considered. In the experiments, the study found significant percentage differences between the normalization procedure and the fuzzy system on days with lower irradiation values. On the other hand, the results provided by Bayesian networks presented lower difference percentages in relation to the normalization equation values.

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Symptom mapping and personalized care for depression, anxiety and stress: A data-driven AI approach

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Computers in Biology and Medicine 2024年 182卷 109146-109146页

作者： Delgado, Sabrinna Vignola, Rose Claudia Batistelli Sassi, Renato José Belan, Peterson Adriano Araújo, Sidnei Alves de Nove de Julho University − UNINOVE Informatics and Knowledge Management Post-Graduation Program Vergueiro Street 235/249 SP São Paulo01504-001 Brazil Federal University of São Paulo − UNIFESP Department of Health Education and Society Ana Costa Avenue 95 Vl. Mathias SP Santos11060-001 Brazil

Background: Depression, anxiety, and stress disorders have significant and widespread impacts worldwide, affecting millions of individuals and their communities. According to the World Health Organization, depression impacts the daily lives of more than 300 million people, making it one of the most important diseases globally. Treatment for these mental disorders (MD) typically involves medication and psychotherapies, but also incorporates technological resources like Artificial Intelligence (AI) to indicate personalized therapies and care. While various AI approaches have been applied in the context of MD in the literature, they often focus solely on aiding diagnosis. Objective: This research proposes an AI approach for mapping symptoms and assisting in the personalized care of depression, anxiety, and stress. Methods: Symptom mapping utilizes data mining (DM) techniques to generate rules representing knowledge extracted from data of 242 patients collected using the Depression, Anxiety, and Stress Scale (DASS-21). This knowledge elucidates how symptoms impact the severity degrees of considered MDs. Subsequently, the generated rules are employed to construct a Fuzzy Inference System (FIS) for inferring the severities of MDs based on patient symptoms and personal data. Results and conclusions: The results achieved in the DM (accuracy ≥92.98 %, sensibility ≥86.02 %, specificity ≥97.32 %, and kappa statistic ≥87.98 %), indicating consistent patterns, along with the results produced by the FIS, demonstrate the potential of the proposed approach to assist health professionals in rapidly predicting symptoms of depression, anxiety, and stress, thereby facilitating outpatient screening and emergency care. Furthermore, it can improve the association of symptoms, referral to specialized care, therapeutic proposals, and even investigations of other diseases unrelated to MD. © 2024 Elsevier Ltd

关键词： Mental disorders DASS-21 Symptom mapping AI Data mining Fuzzy logic

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Turing Project: An Open Educational Game to Teach and Learn programming Logic 15

Turing Project: An Open Educational Game to Teach and Learn ...

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15th Iberian Conference on Information Systems and Technologies, CISTI 2020

作者： Silva, Josivan P. Silveira, Ismar F. Kamimura, Leonardo Barboza, Alcides T. Post-graduation Program on Electrical Eng. And Computing Mackenzie Presbyterian University São Paulo Brazil Cruzeiro Do sul University São Paulo Department of Informatics Brazil

ISBN: (纸本)9789895465903

The paper proposes an open educational game, for students who have never had contact or who present some difficulty in programming logic. The game, in a playful and fun way, tries to teach the basics of programming logic for the students, allowing the same to acquire knowledge during the gameplay. The game proposed in this paper is called 'Turing Project', a RPG game, in which the student will play the role of the game's hero. By collecting scrolls, items and performing missions, students are expected to learn the concepts related to the logic of programming. A subjective experiment was carried out via a survey with 19 users and the main conclusions points out that students had good experiences during the game, which had positive impact in their learning. © 2020 AISTI.

关键词： Students

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Supporting Collaboration with Forgetting Curves

Supporting Collaboration with Forgetting Curves

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International Conference on Computer Supported Cooperative Work in Design

作者： Hector N. Melo Jéssica P. Silvério Angélica F.S. Dias Juliana B. S. França Adriana S. Vivacqua Marcos R.S. Borges Federal University of Rio de Janeiro (UFRJ) Brazil Post-Graduation Program of Informatics (PPGI) Federal University of Rio de Janeiro (UFRJ) Brazil Federal Rural University of Rio de Janeiro (UFRRJ) Brazil

Competency Management Systems are used to facilitate individual competencies management, both in companies and academia. Most systems use the term “competency management” based only on the technical skills of individuals. This way, the manager ends up not being sure of the accuracy of the technical skills of individuals, forming low-performance and poorly collaborative groups. This paper presents an open source web tool aimed at forming highly collaborative groups. The main contribution of this research is the innovative use of the Forgotten Curve concept and modeling for collaborative based grouping to support the design of work teams.

关键词： Conferences Computational modeling Collaboration Companies Tools Collaborative work

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Corporate Venture Capital and Sustainability

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Journal of Open Innovation: Technology, Market, and Complexity 2022年第3期8卷

作者： Döll, Luciano Mathias Ulloa, Micaela Ines Castillo Zammar, Alexandre Prado, Guilherme Francisco do Piekarski, Cassiano Moro Post-Graduation Program of Production Engineering Federal University Technology (UTFPR) Ponta Grossa 84016-210 Brazil Department of Informatics Universidade Estadual de Ponta Grossa (UEPG) Ponta Grossa 84030-900 Brazil Coordination of Technology in Mechanical Manufacturing Instituto Federal de Santa Catarina (IFPR) Florianópolis 88020-300 Brazil

Corporate Venture Capital (CVC) has been receiving increasingly more attention all over the world as a special way for accessing new ideas and innovative opportunities through minor-share investing in established companies. The purpose of CVC investments may either be purely financial or to pursue strategic goals. Organisations often seek to take actions that impact positively on sustainability by assembling related knowledge and technologies. These resources may come from invested startups through the use of a CVC programme. This research aims to measure and analyse the Corporate Venture Capital programmes of companies listed in the ISE B3 Corporate Sustainability Index. To this end, a three-step methodology was conducted. First, a systematic review of the literature took place, followed by a review of companies based on secondary sources such as their websites. Finally, a survey was developed and was opted to survey companies through their Investor Relationship (IR) public channels. Results show that 27 of the companies listed in the ISE B3 Index have CVC programmes that contemplate organizational initiatives besides investment. In this sense, one can claim that at least 70% of the ISE B3 Index companies are somehow involved in CVC operations. The results contribute to the literature on corporate venture capital and sustainability by showing that companies spend from 10% to 15% of their capital in sustainable businesses in order to remain competitive. © 2022 by the authors.

关键词： corporate venture capital open innovation startups sustainability

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Universal design for learning and diversity in elementary school: Experience report 6

Universal design for learning and diversity in elementary sc...

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6th Iberoamerican Conference of Computer Human Interaction, HCI 2020

作者： Martins, Valéria Farinazzo Ribeiro, Glaucia Roxo da Costa, Mariana Revoredo Pereira de la Higuera Amato, Cibelle Albuquerque Mackenzie Presbyterian University Computing and Informatics Department Rua da Consolação 930 São PauloCEP 01302-000 Brazil Mackenzie Presbyterian University Post-graduation Program in Developmental Disorders Rua da Consolação 930 São PauloCEP 01302-000 Brazil

As the Information Technologies and Communication (ITCs) are to be seen as an important resource in classrooms at all levels of learning, it is necessary to think about how to ensure that these ITCs meet the needs of diverse learners. In this article, we are introduced to the Universal Design for Learning (UDL), which was used to develop and to refine a digital didactic material based on a printed book used in more than 100 Brazilian schools. A case study was conducted in a classroom of the first grade of elementary school to verify the benefits and the difficulties in implementing such an approach. The results of this experiment are presented in this article. Copyright © 2020 for this paper by its authors. Use permitted under Creative Commons License Attribution 4.0 International (CC BY 4.0).

关键词： E-learning

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Data Mining applied to the navigation task in autonomous robots

Data Mining applied to the navigation task in autonomous rob...

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IEEE Symposium on Computers and Communications (ISCC)

作者： Carlos Fransley Scatambulo Costa Eduardo Alexandre Franciscon UEM State University of Maringá Maringa PR Brazil Program of Post-Graduation in Informatics (PPGIA) Pontifical Catholic University of Paraná Curitiba PR Brazil

ISBN: (数字)9781728180861

ISBN: (纸本)9781728180878

This paper reports the results of the classifications algorithms used, in data mining, for the creation of a navigation model applied to an autonomous robot to perform the task of wall-following. The goal is to make the robotic vehicle capable of moving, guiding and making decisions autonomously, avoiding collisions, using the smallest resources set as possible. A simulator was used to develop a test environment, the robot vehicle and simulate the proposed navigation system. The results suggest that the J48 (C4.5) classification algorithm obtained the most satisfactory results, generating a model with high degree confidence in decision making.

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A transcriptome meta-analysis of ethanol embryonic exposure: Implications in neurodevelopment and neuroinflammatory genes

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Neuroscience informatics 2022年第3期2卷 100094-100094页

作者： Lord, Vinícius Oliveira Giudicelli, Giovanna Câmara Recamonde-Mendoza, Mariana Vianna, Fernanda Sales Luiz Kowalski, Thayne Woycinck Laboratory of Genomic Medicine Center of Experimental Research Hospital de Clínicas de Porto Alegre (HCPA) Porto Alegre Brazil Centro Universitário CESUCA Cachoeirinha Brazil Post-Graduation Program in Genetics and Molecular Biology Genetics Department Universidade Federal do Rio Grande do Sul (UFRGS) Porto Alegre Brazil Institute of Informatics Universidade Federal do Rio Grande do Sul (UFRGS) Porto Alegre Brazil Bioinformatics Core Hospital de Clínicas de Porto Alegre (HCPA) Porto Alegre Brazil National Institute of Medical Population Genetics (INAGEMP) Porto Alegre Brazil Post-Graduation Program in Medical Sciences Medical College Universidade Federal do Rio Grande do Sul (UFRGS) Porto Alegre Brazil

Fetal Alcohol Spectrum Disorder (FASD) comprises the phenotypes induced by prenatal alcohol exposure. Understanding the molecular mechanisms of FASD is needed since it is a public health problem. This study aimed to evaluate the impact of ethanol in the differential gene expression (DGE) of embryonic cells and fetal tissues by performing a transcriptome meta-analysis in microarrays datasets publicly available. The datasets were obtained in the GEO database and DGE was evaluated, followed by meta-analysis. DGE was also analyzed in a RNA-Seq dataset, although it was not included in the meta-analysis. To filter the main candidate genes, a database and literature review was performed, followed by ontologies enrichment analyses. In the meta-analysis, 1,938 genes were deregulated and 487 were perturbed in the RNA-Seq. Calcium homeostasis and neuroinflammation genes were overrepresented in the meta-analysis and RNA-Seq, respectively. After the database and literature review, DOCK8, FOXG1, IL1RN, and PRKN genes were proposed as new candidates for FASD;they are associated with neurodevelopment and neuroinflammation. BDNF and SLC2A1, previously associated to FASD, were also suggested in meta-analysis as candidate genes. It is known neuroinflammation reduction might help to minimize the alcohol damage. Hence, there is an urgent need to understand FASD molecular mechanisms to help in strategies aimed at preventing ethanol-induced neurologic damage. © 2022 The Authors

关键词： Bioinformatics Differential gene expression Fetal alcohol spectrum disorder Microarray Neurophenotypes Ontology Prenatal ethanol exposure Random effect model RNA-Seq

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Turing Project: An Open Educational Game to Teach and Learn programming Logic

Turing Project: An Open Educational Game to Teach and Learn ...

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Iberian Conference on Information Systems and Technologies (CISTI)

作者： Josivan P. Silva Ismar F. Silveira Leonardo Kamimura Alcides T. Barboza Post-graduation Program on Electrical Eng. and Computing Mackenzie Presbyterian University São Paulo Brazil Department of Informatics Cruzeiro do Sul University São Paulo Brazil

ISBN: (数字)9789895465903

ISBN: (纸本)9781728167244

The paper proposes an open educational game, for students who have never had contact or who present some difficulty in programming logic. The game, in a playful and fun way, tries to teach the basics of programming logic for the students, allowing the same to acquire knowledge during the gameplay. The game proposed in this paper is called “Turing Project”, a RPG game, in which the student will play the role of the game's hero. By collecting scrolls, items and performing missions, students are expected to learn the concepts related to the logic of programming. A subjective experiment was carried out via a survey with 19 users and the main conclusions points out that students had good experiences during the game, which had positive impact in their learning.

关键词： Games programming profession Education Writing Software Mathematics

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