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Federal University of Rio de Janeiro, Brazil

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50 Papers

Development of HIV-1 Coreceptor Tropism Classifiers: An Approach to Improve X4 and R5X4 Viruses Prediction

Topics: Genomics and Proteomics; Sequence Analysis; Pattern Recognition, Clustering and Classification; Model Design and Evaluation

Authors: José Rodrigues ¹ , Letícia Raposo ^{2

;

1} and Flavio Nobre ¹

Affiliations: ¹ Programa de Engenharia Biomédica, Universidade Federal do Rio de Janeiro, Av. Horácio Macedo, 2030, Rio de Janeiro, Brazil , ² Departamento de Métodos Quantitativos, Universidade Federal do Estado do Rio de Janeiro, Av. Pasteur, 458, Rio de Janeiro, Brazil

Digital Object Identifier: 10.5220/0009096101830187

Proceedings of BIOINFORMATICS 2020, ISBN: 978-989-758-398-8

Quick Abstract

The pathway of human immunodeficiency virus (HIV) infection depends on the composition of a 35-amino acid variable region in its envelope, known as the V3 loop. Since this discovery, many tools have been developed to diagnose and predict viral tropism, from biochemical tests to various computational algorithms. To date, the biggest developmental difficulty is the correct prediction of X4 or R5X4-tropism virions. In this study, we evaluated some of these recommended criteria and proposed a random forest-based approach for better prediction of X4-capable (i.e., either X4-only, or R5X4-dual/mixed capability). All methods achieved a specificity higher than 87%, with geno2pheno 2.5% showing the best performance (98.2%). Nevertheless, the sensitivity (73.3%) was lower compared to the other approaches. The highest sensitivity was attained by our Complete Model with an undersampling strategy (90.1%). The accuracy of all approaches ranged from 87.4% to 93.0%. Complete Model with oversampling and Reduced Model with no balancing showed the highest MCC value (both with 0.796 score). Considering error rates and the number of explanatory variables, our main objective of increasing the ability to predict viral specimens with X4-tropism was achieved.

Mobile Devices and Systems in ADHD Treatment

Topics: Human Computer Interaction; Social and Mobile Information Systems

Authors: Renato Alves , Mônica Ferreira da Silva , Eber Schmitz and Antonio Alencar

Affiliation: Federal University of Rio de Janeiro (UFRJ), Rio de Janeiro, Brazil

Digital Object Identifier: 10.5220/0010148201410146

Proceedings of WEBIST 2020, ISBN: 978-989-758-478-7

Quick Abstract

Attention Deficit Hyperactivity Disorder (ADHD) is a neurobiological condition that appears during an individual’s childhood and may follow her/him for life. Even though it is not a new disorder, ADHD treatment is limited to the use of drugs and behavioral therapy, even for children. The objective of this research was to investigate the technological possibilities of mobile devices and web-based information systems, as well as other computer technologies, to support the ADHD treatment phase. Results show the potential of these approaches as alternatives for long-term treatment, as well as the difficulties and limitations that persist today. Besides, the research also highlighted that the use of computer technology could provide persistent long-term results.

Enhancing Spatial Keyframe Animations with Motion Capture

Topics: Animation from Motion Capture; Human Figure Animation

Authors: Bernardo Costa and Claudio Esperança

Affiliation: LCG/PESC, UFRJ, Av. Horácio Macedo 2030, CT, H-319 21941-590, Rio de Janeiro/RJ and Brazil

Digital Object Identifier: 10.5220/0007296800310040

Proceedings of GRAPP 2019, ISBN: 978-989-758-354-4

Quick Abstract

While motion capture (mocap) achieves realistic character animation at great cost, keyframing is capable of producing less realistic but more controllable animations. In this paper we show how to combine the Spatial Keyframing Framework (SKF) of Igarashi et al.(Igarashi et al., 2005) and multidimensional projection techniques to reuse mocap data in several ways. For instance, by extracting meaningful poses and projecting them on a plane, it is possible to sketch new animations using the SKF. Additionally, we show that multidimensional projection also can be used for visualization and motion analysis. We also propose a method for mocap compaction with the help of SK’s pose reconstruction (backprojection) algorithm. This compaction scheme was implemented for several known projection schemes and empirically tested alongside traditional temporal decimation schemes. Finally, we present a novel multidimensional projection optimization technique that significantly enhances SK-based compaction and can also be applied to other contexts where a back-projection algorithm is available.

Related Ontology Subjects/Areas/Topics (4)

Animation and Simulation		Computer Vision, Visualization and Computer Graphics		Human Figure Animation
Animation from Motion Capture

Real World Examples of Agent based Decision Support Systems for Deep Learning based on Complex Feed Forward Neural Networks

Topics: Simulation and Modeling; Deep Learning; Intelligent Multi-agent Systems and Intelligent Agents; Expert and Intelligent Services, Applications, Proofs-of-concept and Best Practices; Big Data Predictive Modeling

Authors: Harald R. Kisch and Claudia L. R. Motta

Affiliation: Universidade Federal do Rio de Janeiro, Germany

Digital Object Identifier: 10.5220/0006307000940101

Proceedings of COMPLEXIS 2017, ISBN: 978-989-758-244-8

Quick Abstract

Nature frequently shows us phenomena that in many cases are not fully understood. To research these phenomena we use approaches in computer simulations. This article presents a model based approach for the simulation of human brain functions in order to create recurrent machine learning map fractals that enable the investigation of any problem trained beforehand. On top of a neural network for which each neuron is illustrated with biological capabilities like collection, association, operation, definition and transformation, a thinking model for imagination and reasoning is exemplified in this research. This research illustrates the technical complexity of our dual thinking process in a mathematical and computational way and describes two examples, where an adaptive and self-regulating learning process was applied to real world examples. In conclusion, this research exemplifies how a previously researched conceptual model (SLA process) can be used for making progress to simulate the complex systematics of human thinking processes and gives an overview of the next major steps for making progress on how artificial intelligence can be used to simulate natural learning.

Exchanging Solutions for Information Systems Development using a Model Pattern Perspective - Diagram Templates in the Context of the Mdarte Collaborative Evolution Process

Topics: Software Factories and Software Product Lines; Generative Programming

Authors: Rodrigo Salvador Monteiro ¹ , Geraldo Zimbrão ² and Jano Moreira de Souza ²

Affiliations: ¹ Universidade Federal Fluminense, Brazil , ² COPPE / Universidade Federal do Rio de Janeiro, Brazil

Digital Object Identifier: 10.5220/0005690306400647

Proceedings of MODELSWARD 2016, ISBN: 978-989-758-168-7

Quick Abstract

Information Systems Development faces many recurrent issues that must be addressed in every project. A lot of common requirements and features repeatedly appear on different projects challenging the development team. Exchanging solutions and the expertise gained over the evaluation of such solutions among projects can prevent the development teams from reinventing the wheel. The MDArte framework has been used to develop information systems through the Model Driven Architecture approach, automating the generation from models reaching around 80% of the application code. Most important is that the MDArte framework turned out to be a common platform between the adherent projects used to share new solutions and features. This paper focus on recurrent issues present at the modeling phase. We applied the concept of Model Patterns in order to provide diagram templates. A set of diagram templates were designed, implemented and evaluated by a volunteer project. The feedback was extremely positive and the proposed approach proves to be very promising. This level of collaboration between different projects on one hand accelerates the development and on the other hand prevents from neglecting important issues on information systems development.

Related Ontology Subjects/Areas/Topics (5)

Applications and Software Development		Model-Driven Software Development		Software Factories and Software Product Lines
Generative Programming		Software Engineering

Computational Neuroscience - Challenges and Implications for Brazilian Education

Topics: Metrics and Performance Measurement; Standards and Interoperability; Teacher Evaluation; Classroom Management

Authors: Raimundo José Macário Costa ¹ , Luís Alfredo Vidal de Carvalho ² , Emilio Sánchez Miguel ³ , Renata Mousinho ² , Renato Cerceau ⁴ , Lizete Pontes Macário Costa ⁵ , Jorge Zavaleta ² , Laci Mary Barbosa Manhães ² and Sérgio Manuel Serra da Cruz ⁶

Affiliations: ¹ Universidade Federal Rural do Rio de Janeiro - UFRRJ, Brazil , ² Universidade Federal do Rio de Janeiro – UFRJ, Brazil , ³ Salamanca University (U.S.A.L), Spain , ⁴ Universidade Federal do Rio de Janeiro – UFRJ and National Regulatory Agency for Private Health Insurance and Plans (ANS), Brazil , ⁵ Rio de Janeiro State University (UERJ), Brazil , ⁶ Universidade Federal Rural do Rio de Janeiro - UFRRJ, Programa de Educação Tutorial (PET-SI/UFRRJ) and Programa de Pós- Graduação em Modelagem Matemática e Computacional (PPGMMC/UFRRJ), Brazil

Digital Object Identifier: 10.5220/0005481004360441

Proceedings of CSEDU 2015, ISBN: 978-989-758-107-6

Quick Abstract

Understanding the core function of the brain is one the major challenges of our times. In the areas of neuroscience and education, several new studies try to correlate the learning difficulties faced by children and youth with behavioral and social problems. This work aims to present the challenges and opportunities of computational neuroscience research, with the aim of detecting people with learning disorders. We present a line of investigation based on the key areas: neuroscience, cognitive sciences and computer science, which considers young people between nine and eighteen years of age, with or without a learning disorder. The adoption of neural networks reveals consistency in dealing with pattern recognition problems and they are shown to be effective for early detection in patients with these disorders. We argue that computational neuroscience can be used for identifying and analyzing young Brazilian people with several cognitive disorders.

Related Ontology Subjects/Areas/Topics (9)

Classroom Management	Learning/Teaching Methodologies and Assessment	Standards and Interoperability
Computer-Supported Education	Metrics and Performance Measurement	Teacher Evaluation
Information Technologies Supporting Learning	Social Context and Learning Environments	Ubiquitous Learning

Knowing the past to Plan for the Future - An In-depth Analysis of the First 10 Editions of the WEBIST Conference

Topics: Knowledge Management; Communities of Interest; Data Mining; Meta-Knowledge Discovery and Representation

Authors: Giseli Rabello Lopes ¹ , Bernardo Pereira Nunes ² , Luiz André P. Paes Leme ³ , Terhi Nurmikko-Fuller ⁴ and Marco A. Casanova ²

Affiliations: ¹ Federal University of Rio de Janeiro, Brazil , ² Pontifical Catholic University of Rio de Janeiro, Brazil , ³ Fluminense Federal University, Brazil , ⁴ Oxford University, United Kingdom

Digital Object Identifier: 10.5220/0005447704310442

Proceedings of WEBIST 2015, ISBN: 978-989-758-106-9

Quick Abstract

Over the last ten years, members of the WEBIST community have dedicated their time and efforts to face a number of research challenges, making significant advances in Information Systems and pointing to new directions for innovation and learning. After ten successful WEBIST conferences and several scientific publications, an extensive analysis of the WEBIST conferences has been carried out (involving authors, publications, conference impact, topics coverage, community analysis and other aspects) to possibly assist us to further advance Information Systems. Thus, in this paper, we present an in-depth analysis of the last ten WEBIST conferences based on social network analysis, bibliometrics and statistical measures and describe a Web-based application built on top of triplified datasets to interactively explore the findings and possibly assist the Information Systems community to reveal new directions.

Related Ontology Subjects/Areas/Topics (16)

Artificial Intelligence	Enterprise Information Systems	Sensor Networks
Biomedical Engineering	Health Information Systems	Signal Processing
Communities of Interest	Information Systems Analysis and Specification	Society, e-Business and e-Government
Data Engineering	Knowledge Management	Soft Computing
Data Mining	Ontologies and the Semantic Web	Web Information Systems and Technologies
Databases and Information Systems Integration

Model of a Neuron Network in Human Brains for Learning Assistance in E-Learning Environments

Topic: Theoretical Bases of E-Learning Environments

Authors: Harald R. Kisch ¹ and Claudia L. R. Motta ²

Affiliations: ¹ Universidade Federal do Rio de Janeiro (UFRJ) and University of Applied Sciences, Brazil , ² Universidade Federal do Rio de Janeiro (UFRJ), Brazil

Digital Object Identifier: 10.5220/0005439904070415

Proceedings of CSEDU 2015, ISBN: 978-989-758-108-3

Quick Abstract

It is typically known that brain neurons are responsible for a significant part of our knowledge adaption process. However, it is not yet fully understood how knowledge adaption works or what conscious intelligence is. The aim of this research is to investigate how an E-learning environment can automatically identify learning sequences to dynamically map them to specific learning types for suggesting course material, which makes learning more individual, flexible and faster. For the purpose of this research, a neural ontology is created. In this ontology, the characterization of one neural brain cell is meant to represent every neuron cell in our brain as a specific part of a neural network to get closer to the answer how a simulation of brain functions could be accomplished. This paper describes a neural network theory and how the conceptual model of a neural brain cell could be interpreted through the concept of cognitive pattern match in relation to intelligence. In conclusion, two fundamental hypotheses for effective knowledge adaption in E-learning environments are derived.

Related Ontology Subjects/Areas/Topics (4)

Computer-Supported Education		Social Context and Learning Environments		Theoretical Bases of e-Learning Environments
e-Learning

Motivational Factors and the Intention of Use of a Virtual Learning Environment - A Preliminary Study about an e-Learning Application Developed by the Brazilian Ministry of Education

Topics: e-Learning Platforms, Portals; Critical Success Factors in Distance Learning; Distance Education; e-Learning in Developing Countries

Authors: Élton Carneiro Marinho , Mônica Ferreira da Silva , Donaldo de Souza Dias , Eber Assis Schmitz and Antônio Juarez Alencar

Affiliation: Federal University of Rio de Janeiro, Brazil

Digital Object Identifier: 10.5220/0005429104770482

Proceedings of CSEDU 2015, ISBN: 978-989-758-108-3

Quick Abstract

This research aims to verify the impact of motivational factors on the intention of use of a Virtual Learning Environment. The environment studied was an e-government web application used by The Brazilian Ministry of Education offered to Brazilian high schools. In this preliminary approach, a case study was done in a private school in Rio de Janeiro followed by an experiment with 20 of its students. Qualitative and quantitative data allowed to endorse some of the results. Previous studies have indicated that teenagers tend to be motivated by playful environments, pointing to the importance of the perceived enjoyment factor. Nevertheless, in this study the perceived usefulness factor appeared as the greatest motivator for the intention of use of the adopted technology. The results of this study will be beneficial for increasing our understanding of new generation adoption of technology.

Related Ontology Subjects/Areas/Topics (10)

Computer-Supported Education	e-Learning	Simulation and Modeling
Critical Success Factors in Distance Learning	e-Learning in Developing Countries	Simulation Tools and Platforms
Distance Education	e-Learning Platforms	Ubiquitous Learning
Domain Applications and Case Studies

A Metadata Focused Crawler for Linked Data

Topic: Semantic Web Technologies and Applications

Authors: Raphael do Vale Amaral Gomes ¹ , Marco A. Casanova ¹ , Giseli Rabello Lopes ¹ and Luiz André P. Paes Leme ²

Affiliations: ¹ PUC-Rio, Brazil , ² UFF, Brazil

Digital Object Identifier: 10.5220/0004867904890500

Proceedings of ICEIS 2014, ISBN: 978-989-758-028-4

Quick Abstract

The Linked Data best practices recommend publishers of triplesets to use well-known ontologies in the triplication process and to link their triplesets with other triplesets. However, despite the fact that extensive lists of open ontologies and triplesets are available, most publishers typically do not adopt those ontologies and link their triplesets only with popular ones, such as DBpedia and Geonames. This paper presents a metadata crawler for Linked Data to assist publishers in the triplification and the linkage processes. The crawler provides publishers with a list of the most suitable ontologies and vocabulary terms for triplification, as well as a list of triplesets that the new tripleset can be most likely linked with. The crawler focuses on specific metadata properties, including subclass of, and returns only metadata, hence the classification “metadata focused crawler”.

Related Ontology Subjects/Areas/Topics (5)

Cloud Computing		Semantic Web Technologies		Software Agents and Internet Computing
Enterprise Information Systems		Services Science

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