Latest Communications of International Proceedings articles

The fast rise of digital data brings both chances and problems for law enforcement and forensic investigators. The large amount of digital evidence can give useful information about crimes, but the high volume and complexity of this data make manual analysis hard. Machine learning (ML)…

The increasing frequency of extreme weather events caused by climate change highlights the urgent need for reliable tools to support flood risk management. Traditional inspection methods for levees, polders, and related hydraulic structures are limited in terms of coverage, cost, and timeliness. In this paper,…

Machine learning (ML) is increasingly recognized as a powerful tool for scientific discovery, yet practical guidance for working with small to medium-sized datasets is limited. This article fills that gap by presenting lessons drawn directly from the author’s hands-on experience across natural and social sciences,…

Machine learning (ML) is increasingly recognized as a powerful tool for scientific discovery, yet practical guidance for working with small to medium-sized datasets is limited. This article fills that gap by presenting lessons drawn directly from the author’s hands-on experience across natural and social sciences,…

The article presents the structure, organisation and examples of operation of the university employee activity administrator panel, which is the main element of the employee evaluation system (EES) at Czestochowa University of Technology (CUT). EES consists of a database server based on PostgreSQL and LibreOffice…

In medium-sized organizations, frequent turnover of first-level support agents can lead to challenges for new agents, who struggle to discover existing and relevant documentation that would help solve user issues due to inexperience. Consequently, these agents escalate tickets to second-level support professionals, increasing their workload.…

Forecasting financial time series with deep neural networks requires models that are both expressive and well regularized. Regularized Self-Attention Regression (RSAR) is a hybrid architecture that combines LSTM, self-attention and convolutional components with explicit regularization, and has shown promising results in financial price prediction. However,…

This article presents the current capabilities for measuring the accuracy of selected IBM Q-class quantum architectures for specific stages and tasks of the recommendation process in hybrid classical-quantum recommendation systems. The main motivations for this research undoubtedly include the increased use of quantum technologies to…

This paper presents a conceptual multilayer model designed for the analysis and simulation of spatial conflicts, incorporating the interdependencies between infrastructural layers and socio -spatial dynamics. The model employs a cellular automata (CA) approach, enabling the exploration of local interactions within complex spatial systems. Each…

The global decline of natural pollinators poses a critical risk to agricultural productivity, particularly for crops such as Hass avocado that depend heavily on cross-pollination. This study is motivated by the need to develop alternative and scalable pollination methods capable of sustaining yields amid declining…