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- Motivation (2)
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- Anomaly detection; Ensemble learning; Autoencoder; Support vector regression; Random forest; Building energy consumption (1)
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Articles 1 - 8 of 8
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Would You Like To Motivate Software Testers? Ask Them How, Ronnie Santos, Cleyton Magalhaes, Jorge Correia-Neto, Fabio Queda Silva, Luiz Fernando Capretz, Rodrigo Souza
Would You Like To Motivate Software Testers? Ask Them How, Ronnie Santos, Cleyton Magalhaes, Jorge Correia-Neto, Fabio Queda Silva, Luiz Fernando Capretz, Rodrigo Souza
Electrical and Computer Engineering Publications
Considering the importance of software testing to the development of high quality and reliable software systems, this paper aims to investigate how can work-related factors influence the motivation of software testers. Method. We applied a questionnaire that was developed using a previous theory of motivation and satisfaction of software engineers to conduct a survey-based study to explore and understand how professional software testers perceive and value work-related factors that could influence their motivation at work. Results. With a sample of 80 software testers we observed that software testers are strongly motivated by variety of work, creative tasks, recognition for their …
Would You Like To Motivate Software Testers? Ask Them How, Ronnie Santos, Cleyton Magalhaes, Jorge S. Correia-Neto, Fabio Q. B. Silva Dr., Luiz Fernando Capretz, Rodrigo E. C. Souza
Would You Like To Motivate Software Testers? Ask Them How, Ronnie Santos, Cleyton Magalhaes, Jorge S. Correia-Neto, Fabio Q. B. Silva Dr., Luiz Fernando Capretz, Rodrigo E. C. Souza
Electrical and Computer Engineering Publications
Considering the importance of software testing to the development of high quality and reliable software systems, this paper aims to investigate how can work-related factors influence the motivation of software testers. Method. We applied a questionnaire that was developed using a previous theory of motivation and satisfaction of software engineers to conduct a survey-based study to explore and understand how professional software testers perceive and value work-related factors that could influence their motivation at work. Results. With a sample of 80 software testers we observed that software testers are strongly motivated by variety of work, creative tasks, recognition for their …
Finding An Effective Classification Technique To Develop A Software Team Composition Model, Abdul Rehman Gilal, Jafrezal Jaafar, Luiz Fernando Capretz, Mazni Omar, Shuib Basri
Finding An Effective Classification Technique To Develop A Software Team Composition Model, Abdul Rehman Gilal, Jafrezal Jaafar, Luiz Fernando Capretz, Mazni Omar, Shuib Basri
Electrical and Computer Engineering Publications
Ineffective software team composition has become recognized as a prominent aspect of software project failures. Reports from results extracted from different theoretical personality models have produced contradicting fits, validity challenges, and missing guidance during software development personnel selection. It is also believed that the technique/s used while developing a model can impact the overall results. Thus, this study aims to: 1) discover an effective classification technique to solve the problem, and 2) develop a model for composition of the software development team. The model developed was composed of three predictors: team role, personality types, and gender variables; it also contained …
Soft Sides Of Software, Luiz Fernando Capretz, Faheem Ahmed, Fabio Queda Silva
Soft Sides Of Software, Luiz Fernando Capretz, Faheem Ahmed, Fabio Queda Silva
Electrical and Computer Engineering Publications
Software is a field of rapid changes: the best technology today becomes obsolete in the near future. If we review the graduate attributes of any of the software engineering programs across the world, life-long learning is one of them. The social and psychological aspects of professional development is linked with rewards. In organizations, where people are provided with learning opportunities and there is a culture that rewards learning, people embrace changes easily. However, the software industry tends to be short-sighted and its primary focus is more on current project success; it usually ignores the capacity building of the individual or …
Direct And Mediating Influences Of User-Developer Perception Gaps In Requirements Understanding On User Participation, Jingdong Jia, Luiz Fernando Capretz
Direct And Mediating Influences Of User-Developer Perception Gaps In Requirements Understanding On User Participation, Jingdong Jia, Luiz Fernando Capretz
Electrical and Computer Engineering Publications
User participation is considered an effective way to conduct requirements engineering, but user-developer perception gaps in requirements understanding occur frequently. Since user participation in practice is not as active as we expect and the requirements perception gap has been recognized as a risk that negatively affects projects, exploring whether user-developer perception gaps in requirements understanding will hinder user participation is worthwhile. This will help develop a greater comprehension of the intertwined relationship between user participation and perception gap, a topic that has not yet been extensively examined. This study investigates the direct and mediating influences of user-developer requirements perception gaps …
An Ensemble Learning Framework For Anomaly Detection In Building Energy Consumption, Daniel B. Araya, Katarina Grolinger, Hany F. Elyamany, Miriam Am Capretz, Girma T. Bitsuamlak
An Ensemble Learning Framework For Anomaly Detection In Building Energy Consumption, Daniel B. Araya, Katarina Grolinger, Hany F. Elyamany, Miriam Am Capretz, Girma T. Bitsuamlak
Electrical and Computer Engineering Publications
During building operation, a significant amount of energy is wasted due to equipment and human-related faults. To reduce waste, today's smart buildings monitor energy usage with the aim of identifying abnormal consumption behaviour and notifying the building manager to implement appropriate energy-saving procedures. To this end, this research proposes a new pattern-based anomaly classifier, the collective contextual anomaly detection using sliding window (CCAD-SW) framework. The CCAD-SW framework identifies anomalous consumption patterns using overlapping sliding windows. To enhance the anomaly detection capacity of the CCAD-SW, this research also proposes the ensemble anomaly detection (EAD) framework. The EAD is a generic framework …
Deep Neural Networks With Confidence Sampling For Electrical Anomaly Detection, Norman L. Tasfi, Wilson A. Higashino, Katarina Grolinger, Miriam A. M. Capretz
Deep Neural Networks With Confidence Sampling For Electrical Anomaly Detection, Norman L. Tasfi, Wilson A. Higashino, Katarina Grolinger, Miriam A. M. Capretz
Electrical and Computer Engineering Publications
The increase in electrical metering has created tremendous quantities of data and, as a result, possibilities for deep insights into energy usage, better energy management, and new ways of energy conservation. As buildings are responsible for a significant portion of overall energy consumption, conservation efforts targeting buildings can provide tremendous effect on energy savings. Building energy monitoring enables identification of anomalous or unexpected behaviors which, when corrected, can lead to energy savings. Although the available data is large, the limited availability of labels makes anomaly detection difficult. This research proposes a deep semi-supervised convolutional neural network with confidence sampling for …
A Gamification Framework For Sensor Data Analytics, Alexandra L'Heureux, Katarina Grolinger, Wilson A. Higashino, Miriam A. M. Capretz
A Gamification Framework For Sensor Data Analytics, Alexandra L'Heureux, Katarina Grolinger, Wilson A. Higashino, Miriam A. M. Capretz
Electrical and Computer Engineering Publications
The Internet of Things (IoT) enables connected objects to capture, communicate, and collect information over the network through a multitude of sensors, setting the foundation for applications such as smart grids, smart cars, and smart cities. In this context, large scale analytics is needed to extract knowledge and value from the data produced by these sensors. The ability to perform analytics on these data, however, is highly limited by the difficulties of collecting labels. Indeed, the machine learning techniques used to perform analytics rely upon data labels to learn and to validate results. Historically, crowdsourcing platforms have been used to …