Abstract Web technology advances faster than humans can adapt to it and develop the proper online skills. Most users are not experienced enough to have a good online knowledge on how to protect their data. Thus, many people can become vulnerable to threats. The most common online attacks are through malicious web links, which…
Abstract This paper introduces the UICVD Dataset, a novel resource fostering advancements in Robotic Process Au-tomation (RPA) and Computer Vision. The paper focuses on recognizing UI (User Interface) components of a web application which is not as well known as recognizing real objects in images in the field of computer vision. This dataset derives…
Abstract Technology offers transformative potential for educational innovation. This paper introduces a novel approach by harnessing virtual assistants, specifically through an Alexa quiz skill tailored for university students, to enhance learning experiences. Supported by a preliminary evaluation, our solution demonstrates significant user satisfaction, indicating its effectiveness and areas for further refinement. Our tailored skill…
Abstract Proper treatment of breast cancer is essential to increase survival rates. Mammography is a widely used, non-invasive screening method for breast cancer. A challenging task in mammogram analysis is to distinguish between tumors. In the current study, we address this problem using different feature extraction and classification methods. In the literature, numerous feature…
Abstract Over the last years, the Internet has monopolized most businesses and industries. These outstanding advancements lead to the dangerous development of specialized threats employed to outsmart everyday users, collect personal data and financial benefits. One of the most relevant attacks is malicious web links, which can be inserted into private messages, emails, social…
Abstract We model cooperative-competitive social group dynamics with multi-agent environments, specialized in cases with a large number of agents from only a few distinct types. The multi-agent optimization problems are addressed in turn with multi-agent reinforcement learning algorithms to obtain flexible and robust solutions. We analyze the effectiveness of centralized and decentralized algorithms using…
Abstract Today, robots can be found in almost any field. Examples include robots for transporting materials in hospitals and warehouses, surveillance, intelligent laboratories and space exploration. Whatever the reason for moving the robot and whatever its location, all robot applications anywhere require path calculation. In this paper, we address the problem of collision-free path…
Abstract This paper presents a method for detecting a crack in simply supported beams by identifying its location and severity (depth). The method is based on the measured natural frequencies for several bending vibration modes of an intact and cracked beam and the Particle Swarm Optimization (PSO). To explain the approach, we calculate the…
Abstract The Influence Maximization Problem is a challenging computational task with multiple real-world applications. A new approach to this problem based on cooperative game theory and optimization called the Shapley Influence Maximization Extremal Optimization approach is proposed. The influence maximization problem for the independent cascade model is considered as a cooperative game, where players seek to…
Abstract The feature selection problem has become a key undertaking within machine learning. For classification problems, it is known to reduce the computational complexity of parameter estimation, but it also adds an important contribution to the explainability aspects of the results. An evolution strategy for feature selection is proposed in this paper. Feature weights…