A5056758186- Software Testing and Debugging Techniques
- Metaheuristic Optimization Algorithms Research
- Software Engineering Research
- Software System Performance and Reliability
- Network Security and Intrusion Detection
- Spam and Phishing Detection
- Software Reliability and Analysis Research
- Energy Efficient Wireless Sensor Networks
- Advanced Malware Detection Techniques
- Anomaly Detection Techniques and Applications
- Machine Learning in Healthcare
- Machine Learning and ELM
- IoT and Edge/Fog Computing
- AI in cancer detection
- Generative Adversarial Networks and Image Synthesis
- Software Engineering Techniques and Practices
- IoT-based Smart Home Systems
- Reinforcement Learning in Robotics
- Teaching and Learning Programming
- Online Learning and Analytics
- Blind Source Separation Techniques
- Cloud Computing and Resource Management
- Engineering Education and Pedagogy
- Data Stream Mining Techniques
- Neural Networks and Applications
University of Belgrade
2013-2024
Wireless sensor networks have entered a period of rapid development, due to several novel technologies which emerged in the past few years, such as Internet Things and cloud computing. Miniature nodes are integral components numerous complex systems. The biggest problem for any wireless network, possible application domain, is maximize overall network lifetime by improving total energy consumption network. A large number clustering algorithms been implemented decade, with main goal balance...
Parkinson's disease belongs to the group of health problems that are incurable but can be mitigated if treated properly. While there is no way curing damage caused by disease, patient's life quality improved diagnosed and properly on time. The role artificial intelligence (AI) in medicine increasing. Deep learning algorithms may utilized automatically detect freezing gait episodes. This study focused diagnosis based disturbances which affected this disease. A hybrid deep machine AI solution...
The problem of fake news on the Internet is not new. However, in case a global pandemic, this kind misinformation can be dangerous, confusing, and costly terms loss human lives. ongoing COVID-19 pandemic has unfortunately shown significant remarkable spread news, concerning disease itself, vaccination, number deaths, so on. It necessary to develop an effective algorithm that will able detect help scientists easily separate from true news. research presented paper proposes arithmetic...
Cardiovascular disorders, a leading cause of death, demand urgent research attention. Early detection systems hold the potential to improve patient outcomes by enabling timely interventions and lifestyle adjustments. Recent advancements in artificial intelligence algorithms show promise addressing complex challenges. This study investigates application Recurrent Neural Networks (RNNs) optimized with metaheuristic for anomaly electrocardiogram (ECG) signals. We conducted comparative analysis...
This study examines the formidable and complex challenge of insider threats to organizational security, addressing risks such as ransomware incidents, data breaches, extortion attempts. The research involves six experiments utilizing email, HTTP, file content data. To combat threats, emerging Natural Language Processing techniques are employed in conjunction with powerful Machine Learning classifiers, specifically XGBoost AdaBoost. focus is on recognizing sentiment context malicious actions,...
Proper artificial intelligence (AI) and machine learning (ML) model implementation training are highly reliant on quality input data. However, the high costs of clinical studies increasing privacy concerns limit availability medical data to researchers. This work explores potential applying generative adversarial networks (GAN) for generating synthetic based publicly available real-world datasets. Synthetic is generated observations used train several contemporary ML AI models. These models...
Abstract Nowadays, we heavily depend on software, as utilize it daily. Bugs in the software can cause significant damage, loss of private data and money, even human lives. Software testing quality assurance discipline, which belongs to engineering domain, aims ensure that is good enough before its release market. Therefore, vital engineers are highly trained this domain. Unfortunately, discipline frequently neglected throughout courses. Students mostly taught just theoretical principles gain...
Software testing is one of the most important activities in software development lifecycle. White box assumes access to source code program. One main problems when selecting a approach try minimize number tests while guaranteeing 100% test coverage.The object-oriented programs more complex than procedural programs. All traditional techniques can be applied, however, it required consider special characteristics programs, such as abstraction. Several applied - this paper we have selected and...
Software development is one of the fastest growing industries today. The defects in software can be very costly, either terms losing money, reputation, or even lives case some critical applications. Consequently, there a high and always increasing demand for engineers specialized branch testing. However, traditional engineering courses pay little attention to testing, students are entering market with practical testing experience. One way address this problem integrate into studies through...