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Physical Sciences and Mathematics Commons™
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- Human factors in software engineering (4)
- Software engineering (2)
- Software testing (2)
- Adaptive neural fuzzy inference system (1)
- Automated Driving System (1)
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- Behavioral assessment (1)
- Collision (1)
- Cross-cultural study (1)
- Cyber-attacks; cyber-attacks detection; cyber-attacks identification; cybersecurity; False Data Injection (FDI) attacks; cyber resilience; smart grid (1)
- Deep Q-Network (1)
- Developing and Testing (1)
- Disengagement (1)
- Empirical software engineering (1)
- Ethics in software (1)
- Feed-forward neural network (1)
- Fundamental analysis (1)
- High-impedance fault; power system protection; unsupervised learning; deep learning; convolutional autoencoder; convolutional neural network (1)
- Machine learning (1)
- Mileage (1)
- Personality traits (1)
- Random forest (1)
- Reinforcement Learning (1)
- Responsible Software Engineering (1)
- Social aspects of software development (1)
- Social aspects of software engineering (1)
- Software careers (1)
- Stock prediction (1)
- Sustainable software engineering (1)
- Testers (1)
- Testing professionals (1)
Articles 1 - 9 of 9
Full-Text Articles in Physical Sciences and Mathematics
Machine Learning For Stock Prediction Based On Fundamental Analysis, Yuxuan Huang, Luiz Fernando Capretz, Danny Ho
Machine Learning For Stock Prediction Based On Fundamental Analysis, Yuxuan Huang, Luiz Fernando Capretz, Danny Ho
Electrical and Computer Engineering Publications
Application of machine learning for stock prediction is attracting a lot of attention in recent years. A large amount of research has been conducted in this area and multiple existing results have shown that machine learning methods could be successfully used toward stock predicting using stocks’ historical data. Most of these existing approaches have focused on short term prediction using stocks’ historical price and technical indicators. In this paper, we prepared 22 years’ worth of stock quarterly financial data and investigated three machine learning algorithms: Feed-forward Neural Network (FNN), Random Forest (RF) and Adaptive Neural Fuzzy Inference System (ANFIS) for …
Comparing The Popularity Of Testing Careers Among Canadian, Indian, Chinese, And Malaysian Students, Luiz Fernando Capretz, Pradeep Waychal, Jingdong Jia, Shuib Basri
Comparing The Popularity Of Testing Careers Among Canadian, Indian, Chinese, And Malaysian Students, Luiz Fernando Capretz, Pradeep Waychal, Jingdong Jia, Shuib Basri
Electrical and Computer Engineering Publications
This study attempts to understand motivators and de-motivators that influence the decisions of software students to take up and sustain software testing careers across four different countries, Canada, India, China, and Malaysia. Towards that end, we have developed a cross-sectional, but simple, survey-based instrument. In this study we investigated how software engineering and computer science students perceive and value what they do and their environmental settings. This study found that very few students are keen to take up software testing careers - why is this happening with such an important task in the software life cycle? The common advantages of …
Eveloping A Suitability Assessment Criteria For Software Developers: Behavioral Assessment Using Psychometric Test, Jayati Gulati, Bharti Suri, Luiz Fernando Capretz, Bimlesh Wadhwa, Anu Singh Lather
Eveloping A Suitability Assessment Criteria For Software Developers: Behavioral Assessment Using Psychometric Test, Jayati Gulati, Bharti Suri, Luiz Fernando Capretz, Bimlesh Wadhwa, Anu Singh Lather
Electrical and Computer Engineering Publications
A suitability assessment instrument for software developers was created using a psychometric criteria that identify the impact of behavior on the performance of software engineers. The instrument uses a questionnaire to help both individuals and IT recruiters to identify the psychological factors that affect the working performance of software engineers. Our study identifies the relationship between the behavioral drivers and the programming abilities of the subjects. In order to evaluate the instrument, a total of 100 respondents were compared on the basis of their programming skills and nine behavioral drivers. It was concluded that there is a direct relationship between …
Reinforcement Learning Algorithms: An Overview And Classification, Fadi Almahamid, Katarina Grolinger
Reinforcement Learning Algorithms: An Overview And Classification, Fadi Almahamid, Katarina Grolinger
Electrical and Computer Engineering Publications
The desire to make applications and machines more intelligent and the aspiration to enable their operation without human interaction have been driving innovations in neural networks, deep learning, and other machine learning techniques. Although reinforcement learning has been primarily used in video games, recent advancements and the development of diverse and powerful reinforcement algorithms have enabled the reinforcement learning community to move from playing video games to solving complex real-life problems in autonomous systems such as self-driving cars, delivery drones, and automated robotics. Understanding the environment of an application and the algorithms’ limitations plays a vital role in selecting the …
International Comparative Studies On The Software Testing Profession, Luiz Fernando Capretz, Pradeep Waychal, Jingdong Jia, Daniel Varona, Yadira Lizama
International Comparative Studies On The Software Testing Profession, Luiz Fernando Capretz, Pradeep Waychal, Jingdong Jia, Daniel Varona, Yadira Lizama
Electrical and Computer Engineering Publications
This work attempts to fill a gap by exploring the human dimension in particular, by trying to understand the motivation of software professionals for taking up and sustaining their careers as software testers. Towards that goal, four surveys were conducted in four countries—India, Canada, Cuba, and China—to try to understand how professional software engineers perceive and value work-related factors that could influence their motivation to start or move into software testing careers. From our sample of 220 software professionals, we observed that very few were keen to take up testing careers. Some aspects of software testing, such as the potential …
Promoting And Teaching Responsible Leadership In Software Engineering, Devender Goyal, Luiz Fernando Capretz
Promoting And Teaching Responsible Leadership In Software Engineering, Devender Goyal, Luiz Fernando Capretz
Electrical and Computer Engineering Publications
As software and computer technology is becoming more prominent and pervasive in all spheres of life, many researchers and industry folks are realizing the importance of teaching soft skills and values to CS and SE students. Many researchers and leaders, from both academic and non-academic world, are also calling for software researchers and practitioners to seriously consider human values, like respect, integrity, compassion, justice, and honesty when building software, both for greater social good and also for financial considerations. In this paper, we propose and wish to promote teaching soft skills, values, and responsibilities to students, which we term as …
An Analysis Of Testing Scenarios For Automated Driving Systems, Luiz Fernando Capretz, Siyuan Liu
An Analysis Of Testing Scenarios For Automated Driving Systems, Luiz Fernando Capretz, Siyuan Liu
Electrical and Computer Engineering Publications
10.1109/SANER50967.2021.00078
Emerging Challenges In Smart Grid Cybersecurity Enhancement: A Review, Fazel Mohammadi
Emerging Challenges In Smart Grid Cybersecurity Enhancement: A Review, Fazel Mohammadi
Electrical and Computer Engineering Publications
In this paper, a brief survey of measurable factors affecting the adoption of cybersecurity enhancement methods in the smart grid is provided. From a practical point of view, it is a key point to determine to what degree the cyber resilience of power systems can be improved using cost-effective resilience enhancement methods. Numerous attempts have been made to the vital resilience of the smart grid against cyber-attacks. The recently proposed cybersecurity methods are considered in this paper, and their accuracies, computational time, and robustness against external factors in detecting and identifying False Data Injection (FDI) attacks are evaluated. There is …
Deep Learning For High-Impedance Fault Detection: Convolutional Autoencoders, Khushwant Rai, Firouz Badrkhani Ajaei, Farnam Hojatpanah, Katarina Grolinger
Deep Learning For High-Impedance Fault Detection: Convolutional Autoencoders, Khushwant Rai, Firouz Badrkhani Ajaei, Farnam Hojatpanah, Katarina Grolinger
Electrical and Computer Engineering Publications
High-impedance faults (HIF) are difficult to detect because of their low current amplitude and highly diverse characteristics. In recent years, machine learning (ML) has been gaining popularity in HIF detection because ML techniques learn patterns from data and successfully detect HIFs. However, as these methods are based on supervised learning, they fail to reliably detect any scenario, fault or non-fault, not present in the training data. Consequently, this paper takes advantage of unsupervised learning and proposes a convolutional autoencoder framework for HIF detection (CAE-HIFD). Contrary to the conventional autoencoders that learn from normal behavior, the convolutional autoencoder (CAE) in CAE-HIFD …