International Conference on Software Engineering, May 18, 2013
This paper proposes an extension of the Earned Value Management - EVM technique through the integ... more This paper proposes an extension of the Earned Value Management - EVM technique through the integration of historical cost performance data of processes under statistical control as a means to improve the predictability of the cost of projects. The proposed technique was evaluated through a case-study in industry, which evaluated the implementation of the proposed technique in 22 software development projects Hypotheses tests with 95% significance level were performed, and the proposed technique was more accurate and more precise than the traditional technique for calculating the Cost Performance Index - CPI and Estimates at Completion - EAC.
The social media exerts an important role in publishing information and newspaper online. The qua... more The social media exerts an important role in publishing information and newspaper online. The quality of this information and the sentiment analysis might help predict the price of diverse market asset and cause great gains and losses. In this scenario, many researchers have been studying the diverse aspects that influence this area. Recently, cryptocurrencies have gained a spotlight between financial assets and, one of its characteristics is the fact that its market is strongly influenced by opinions and speculation being a proper area for sentiment analysis and data mining techniques. However, there is not any complete theoretical and technical framework about this subject. Due to its interdisciplinary characteristics involving topics in economics, human behavior, and artificial intelligence, there is a lack of clarity about the techniques and tools used in sentiment analysis in the cryptocurrencies scenario. The goal of this paper is to analyze related research in market prediction based on text mining and other artificial intelligence techniques and generate a systematic mapping about the main research, identifing the possible gaps in this field. This work might help the research community to better structure this emerging area and identify more exactly aspects that require research and are of essential importance.
Autism Spectrum Disorder (ASD) diagnosis is still based on behavioral criteria through a lengthy ... more Autism Spectrum Disorder (ASD) diagnosis is still based on behavioral criteria through a lengthy and time-consuming process. Much effort is being made to identify brain imaging biomarkers and develop tools that could facilitate its diagnosis. In particular, using Machine Learning classifiers based on resting-state fMRI (rs-fMRI) data is promising, but there is an ongoing need for further research on their accuracy and reliability. Therefore, we conducted a systematic review and meta-analysis to summarize the available evidence in the literature so far. A bivariate random-effects meta-analytic model was implemented to investigate the sensitivity and specificity across the 55 studies that offered sufficient information for quantitative analysis. Our results indicated overall summary sensitivity and specificity estimates of 73.8% and 74.8%, respectively. SVM stood out as the most used classifier, presenting summary estimates above 76%. Studies with bigger samples tended to obtain worse...
IAES International Journal of Robotics and Automation (IJRA), 2020
Power transmission lines are of great importance for the operation of all sectors of society, suc... more Power transmission lines are of great importance for the operation of all sectors of society, such as commerce, industry and public agencies. To ensure reliability and availability of power supply, regular and occasional inspections are conducted, mostly using patrol with binoculars, helicopters or truck cranes. Research is being developed using unmanned aerial vehicle (UAV) to make this activity autonomous, faster, safer, and less costly. The present work aims to analyze research related to the autonomous control of the UAV along the transmission lines through a systematic review of the literature (SRL), apply a viable solution and to verify the possible lacuna in this state of the art. Improvements in safety, computational process and energy efficiency with low-cost were identified. The results presented can help the research community to perform the working this state of art, from the suggestions of autonomous tracking of transmission lines.
O presente trabalho propõe a seleção de dados históricos de Índices de Desempenho de Custos (IDC)... more O presente trabalho propõe a seleção de dados históricos de Índices de Desempenho de Custos (IDC) através do classificador Naive Bayes para a aplicação do cálculo proposto por [5], para melhorar a previsibilidade de custo de projetos de software. A técnica proposta foi avaliada através de um estudo empírico, que avaliou a implementação da técnica proposta em 23 projetos de desenvolvimento de software. A técnica proposta foi aplicada em projetos reais com o objetivo de avaliar a precisão e a variação do IDCAcum e consequentemente da Estimativa no Término (ENT). Então, foi comparado com a técnica tradicional de Gerenciamento de Valor Agregado (GVA). Foram realizados testes de hipóteses com nível de significância de 95% e a técnica proposta foi mais exata e mais precisa (menor variação) do que a técnica tradicional para o cálculo do IDC.
Communications in computer and information science, 2014
The present study proposes an extension of the Earned Value Management (EVM) technique, through t... more The present study proposes an extension of the Earned Value Management (EVM) technique, through the integration of the quality historic data as a mean of improving the technique’s cost predictability. The proposed technique was evaluated and compared to the traditional technique in different hypothesis tests utilizing real data of 20 projects. The proposed technique was more accurate than the traditional technique for the Cost Performance Index (CPI) and the Estimate At Completion (EAC).
International Conference on Software Engineering, May 18, 2013
This paper proposes an extension of the Earned Value Management - EVM technique through the integ... more This paper proposes an extension of the Earned Value Management - EVM technique through the integration of historical cost performance data of processes under statistical control as a means to improve the predictability of the cost of projects. The proposed technique was evaluated through a case-study in industry, which evaluated the implementation of the proposed technique in 22 software development projects Hypotheses tests with 95% significance level were performed, and the proposed technique was more accurate and more precise than the traditional technique for calculating the Cost Performance Index - CPI and Estimates at Completion - EAC.
The social media exerts an important role in publishing information and newspaper online. The qua... more The social media exerts an important role in publishing information and newspaper online. The quality of this information and the sentiment analysis might help predict the price of diverse market asset and cause great gains and losses. In this scenario, many researchers have been studying the diverse aspects that influence this area. Recently, cryptocurrencies have gained a spotlight between financial assets and, one of its characteristics is the fact that its market is strongly influenced by opinions and speculation being a proper area for sentiment analysis and data mining techniques. However, there is not any complete theoretical and technical framework about this subject. Due to its interdisciplinary characteristics involving topics in economics, human behavior, and artificial intelligence, there is a lack of clarity about the techniques and tools used in sentiment analysis in the cryptocurrencies scenario. The goal of this paper is to analyze related research in market prediction based on text mining and other artificial intelligence techniques and generate a systematic mapping about the main research, identifing the possible gaps in this field. This work might help the research community to better structure this emerging area and identify more exactly aspects that require research and are of essential importance.
Autism Spectrum Disorder (ASD) diagnosis is still based on behavioral criteria through a lengthy ... more Autism Spectrum Disorder (ASD) diagnosis is still based on behavioral criteria through a lengthy and time-consuming process. Much effort is being made to identify brain imaging biomarkers and develop tools that could facilitate its diagnosis. In particular, using Machine Learning classifiers based on resting-state fMRI (rs-fMRI) data is promising, but there is an ongoing need for further research on their accuracy and reliability. Therefore, we conducted a systematic review and meta-analysis to summarize the available evidence in the literature so far. A bivariate random-effects meta-analytic model was implemented to investigate the sensitivity and specificity across the 55 studies that offered sufficient information for quantitative analysis. Our results indicated overall summary sensitivity and specificity estimates of 73.8% and 74.8%, respectively. SVM stood out as the most used classifier, presenting summary estimates above 76%. Studies with bigger samples tended to obtain worse...
IAES International Journal of Robotics and Automation (IJRA), 2020
Power transmission lines are of great importance for the operation of all sectors of society, suc... more Power transmission lines are of great importance for the operation of all sectors of society, such as commerce, industry and public agencies. To ensure reliability and availability of power supply, regular and occasional inspections are conducted, mostly using patrol with binoculars, helicopters or truck cranes. Research is being developed using unmanned aerial vehicle (UAV) to make this activity autonomous, faster, safer, and less costly. The present work aims to analyze research related to the autonomous control of the UAV along the transmission lines through a systematic review of the literature (SRL), apply a viable solution and to verify the possible lacuna in this state of the art. Improvements in safety, computational process and energy efficiency with low-cost were identified. The results presented can help the research community to perform the working this state of art, from the suggestions of autonomous tracking of transmission lines.
O presente trabalho propõe a seleção de dados históricos de Índices de Desempenho de Custos (IDC)... more O presente trabalho propõe a seleção de dados históricos de Índices de Desempenho de Custos (IDC) através do classificador Naive Bayes para a aplicação do cálculo proposto por [5], para melhorar a previsibilidade de custo de projetos de software. A técnica proposta foi avaliada através de um estudo empírico, que avaliou a implementação da técnica proposta em 23 projetos de desenvolvimento de software. A técnica proposta foi aplicada em projetos reais com o objetivo de avaliar a precisão e a variação do IDCAcum e consequentemente da Estimativa no Término (ENT). Então, foi comparado com a técnica tradicional de Gerenciamento de Valor Agregado (GVA). Foram realizados testes de hipóteses com nível de significância de 95% e a técnica proposta foi mais exata e mais precisa (menor variação) do que a técnica tradicional para o cálculo do IDC.
Communications in computer and information science, 2014
The present study proposes an extension of the Earned Value Management (EVM) technique, through t... more The present study proposes an extension of the Earned Value Management (EVM) technique, through the integration of the quality historic data as a mean of improving the technique’s cost predictability. The proposed technique was evaluated and compared to the traditional technique in different hypothesis tests utilizing real data of 20 projects. The proposed technique was more accurate than the traditional technique for the Cost Performance Index (CPI) and the Estimate At Completion (EAC).
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