Latest Communications of International Proceedings articles

This study explores the application of machine learning methods to predict football (soccer) match outcomes. Football, as a highly dynamic and data-rich sport, provides a valuable source of information for predictive modeling. The research focuses on evaluating and comparing the performance of several machine learning…

This study investigates the use of machine learning methods to assess and predict the level of athletes’ preparation for e-cycling competitions based on their training data. A three-month dataset of activities collected from selected competitors of the Polish Open E-cycling Championships was processed to extract…

One of the primary problems in our society is skin diseases, due to their severe effects on both the body and the mental health of individuals. Early detection and diagnosis of these diseases can have a significant impact on the success of treatments. The skills…

The rise of Artificial Intelligence (AI) in information systems offers a host of new opportunities but also substantial challenges. In 2019 the EU commission released the “Ethical Guidelines for Trustworthy AI”. So far, these guidelines are only recommendations and not enforced by law. Six years…

This study investigates interpretable photometric and geometric features for deepfake detection under realistic conditions. The dedicated DeepFake RealWorld (DFRW) dataset, comprising 46 371 clips generated by diffusion, reenactment, and face-swap models, was used to evaluate lighting and shape consistency. Key descriptors, including light direction mismatch…

This study evaluates interpretable textural and edge descriptors for deepfake detection under real-world conditions. Using the new DFRW dataset with 46 371 clips from diffusion and face-swap models, classical features showed strong robustness to compression and re-encoding. The best-performing descriptors: CLBP, LBP, BSIF, HOG, structure…

This paper presents the concept of an agent-based, distributed web application utilizing artificial intelligence (AI) for forecasting startup profitability. The proposed system integrates key success factors (KSFs) to evaluate financial and operational performance across different stages of a startup’s life cycle. The application employs autonomous…

The increasing complexity of distributed and cloud-based systems has revealed the limitations of traditional access control mechanisms and highlighted the need for adaptive models capable of operating in dynamic environments. This study analyzes the progression of access control from classical models, such as Discretionary Access…

This paper presents a comparative analysis of energy consumption and security performance in IoT systems using LoRa, BLE, and Wi-Fi technologies. Current measurements were performed with an INA219 module under both unsecured and secured (encrypted/authenticated) transmission conditions. Results indicate that BLE offers the lowest energy…

This study addresses the critical need for advanced quantitative approaches in cybersecurity risk management, motivated by the limitations of traditional qualitative methods in today's dynamic threat landscape. The research identifies a significant void in literature concerning the integration of sophisticated stochastic modeling techniques with practical…