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Sobre

Vitor Rocio é doutorado em Informática pela Faculdade de Ciências e Tecnologia da Universidade Nova de Lisboa, Portugal (2002), e Licenciado em Engenharia Informática pela FCT-UNL, Portugal (1993). É professor associado da Universidade Aberta, e desde 2012, pró-reitor para o Campus Virtual.

Os seus principais interesses de investigação são as tecnologias das linguagens humanas, o processamento automático de línguas naturais, os sistemas de análise sintáctica evolutivos, a programação em lógica, e as tecnologias de elearning. http://scholar.google.pt/citations?hl=en&user=i6ilsfYAAAAJ

Tópicos
de interesse
Detalhes

Detalhes

  • Nome

    Vitor Rocio
  • Cluster

    Informática
  • Cargo

    Investigador Afiliado
  • Desde

    01 maio 2014
Publicações

2021

Using BPMN to Identify Indicators for Teacher Intervention in Support of Self-regulation and Co-regulation of Learning in Asynchronous e-learning

Autores
Morais, C; Pedrosa, D; Rocio, V; Cravino, J; Morgado, L;

Publicação
Communications in Computer and Information Science - Technology and Innovation in Learning, Teaching and Education

Abstract

2020

Context-Aware mobile applications in fog infrastructure: A literature review

Autores
Barros, C; Rocio, V; Sousa, A; Paredes, H;

Publicação
Advances in Intelligent Systems and Computing

Abstract
Today’s cloud computing techniques are becoming unsustainable for real time applications as very low latency is required with billions of connected devices. New paradigms are arising; the one that offers an integrated solution for extending cloud resources to the edge of the network and addresses current cloud issues is Fog Computing. Performing Fog Computing brings a set of challenges such as: provisioning edge nodes to perform task volumes downloaded from the Cloud; placing task volumes on edge nodes; resource management on edge nodes; need for a new programming model; programming, resource management, data consistency service discovery challenges; privacy and security and improving the quality of service (QoS) and user experience (QoE). This paper aims at introducing the Fog Computing concept and it presents a literature review on the way it is applied: context-sensitive applications and context-sensitive mobile service platforms. The result of the study is presented as the current research challenges for context aware mobile applications in Fog Computing infrastructure. © The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG 2020.

2020

Survey on Job Scheduling in Cloud-Fog Architecture

Autores
Barros, C; Rocio, V; Sousa, A; Paredes, H;

Publicação
2020 15TH IBERIAN CONFERENCE ON INFORMATION SYSTEMS AND TECHNOLOGIES (CISTI'2020)

Abstract
Application execution required in cloud and fog architectures are generally heterogeneous in terms of device and application contexts. Scaling these requirements on these architectures is an optimization problem with multiple restrictions. Despite countless efforts, task scheduling in these architectures continue to present some enticing challenges that lead us to question how tasks are routed between different physical devices, fog nodes and cloud. In fog, due to its density and heterogeneity of devices, the scheduling is very complex and, in the literature, there are still few studies that have been conducted. However, scheduling in the cloud has been widely studied. Nonetheless, many surveys address this issue from the perspective of service providers or optimize application quality of service (QoS) levels. Also, they ignore contextual information at the level of the device and end users and their user experiences. In this paper, we conducted a review of the literature on the main task scheduling algorithms in cloud and fog architecture; we studied and discussed their limitations, and we also explored and suggested some perspectives for improvement.

2020

Job Scheduling in Fog Paradigm - A Proposal of Context-aware Task Scheduling Algorithms

Autores
Barros, C; Rocio, V; Sousa, A; Paredes, H;

Publicação
2020 INTERNATIONAL CONFERENCE ON INFORMATION TECHNOLOGY SYSTEMS AND INNOVATION (ICITSI)

Abstract
According to the author's knowledge task scheduling in fog paradigm is highly complex and in the literature there are still few studies on it. In the cloud architecture, it is widely studied and in many researches, it is approached from the perspective of service providers. Trying to bring innovative contributions in these areas, in this paper, we propose a solution to the context-aware task-scheduling problem for fog paradigm. In our proposal, different context parameters are normalized through Min Max normalization, requisition priorities are defined through the application of the Multiple Linear Regression (MLR) technique and scheduling is performed using Multi-Objective Non-Linear Programming Optimization (MONLIP) technique.

2019

Combining sentiment analysis scores to improve accuracy of polarity classification in MOOC posts

Autores
Pinto, HL; Rocio, V;

Publicação
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Abstract
Sentiment analysis is a set of techniques that deal with the verification of sentiment and emotions in written texts. This introductory work aims to explore the combination of scores and polarities of sentiments (positive, neutral and negative) provided by different sentiment analysis tools. The goal is to generate a final score and its respective polarity from the normalization and arithmetic average scores given by those tools that provide a minimum of reliability. The texts analyzed to test our hypotheses were obtained from forum posts from participants in a massive open online course (MOOC) offered by Universidade Aberta de Portugal, and were submitted to four online service APIs offering sentiment analysis: Amazon Comprehend, Google Natural Language, IBM Watson Natural Language Understanding, and Microsoft Text Analytics. The initial results are encouraging, suggesting that the average score is a valid way to increase the accuracy of the predictions from different sentiment analyzers. © Springer Nature Switzerland AG 2019.

Teses
supervisionadas

2019

Estudo da utilização da arquitetura Fog Computing para a criação de soluções sensíveis ao contexto

Autor
Celestino Lopes de Barros

Instituição
UAB

2019

Wizard user: um agente inteligente na otimização de processos de ensino-aprendizagem online

Autor
Carlos Eduardo Ferrão de Azevedo

Instituição
UAB

2018

Aplicação móvel para o modelo pedagógico virtual da Universidade Aberta

Autor
Nuno Miguel Bizarro Carvalho

Instituição
UAb

2018

Estudo da utilização da arquitetura Fog Computing para a criação de soluções sensíveis ao contexto

Autor
Celestino Lopes de Barros

Instituição
UTAD