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 can…
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 from…
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 dynamically…
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 extraction…
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 media…
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 three…
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 are…
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 also it adds an important contribution to the explainability aspects of the results. In this paper, a genetic algorithm for feature selection is proposed. The importance, as…
Railway switches represent the mechanism which slightly adjusts the rail blades at the intersection of two rail tracks in order to allow trains to exchange their routes. Ensuring that the switches are correctly set represents a critical task. If switches are not correctly set, they may cause delays in train schedules or even loss…
K-nearest neighbor is one of the simplest and most intuitive binary classification methods providing robust results on a wide range of data. However, classification results can be improved by using a decision method that is capable of assigning, if necessary, the minority label from the list of neighbors of a tested instance. In this…