Latest Communications of International Proceedings articles

Over many years of consulting practice as advisor to senior executives, the author of the present paper identified several most common errors made by financial controlling departments of international companies. These are: a. using full cost accounting for strategic decisions regarding product pricing and discontinuation;…

As the number of new and increasingly difficult to detect threats increases, the effectiveness of classification methods in intrusion detection systems (IDS) becomes particularly important. Previous research approaches mainly focus on detecting incidents in a binary approach, while issues related to multi-class classification, which includes…

In today's digital world, Open-Source Intelligence (OSINT) is of critical importance in cyber threat analysis. However, when the studies in the current literature are examined, it has been realized that there is no comprehensive and automatic framework that allows the processing of visual and textual…

One of the goals of data dispersion analysis is the determination of the empirical probability density function based on the sampled data. The paper presents a critical discussion of four methods of analysis of the dispersion of multivariate data in the sample: classical histogram, ”inverted…

The article discusses the testing of new alternative models of the biquadratic finite element of the serendipity family using the problem of torsion of a non-circular cross-section rod and compares the results obtained with the exact solution. The conversion of the Lagrange model to the…

This study evaluates the effectiveness of three popular large language models (LLMs)—GPT-3.5-Turbo, GPT-4o-Mini, and Gemini-2.0-Flash—in identifying Myers-Briggs Type Indicator (MBTI) personality traits from textual data. Using a dataset of over 8,000 personality-labeled posts, each model's capability to accurately classify individual MBTI letters (Introversion-Extraversion, Sensing-Intuition, Thinking-Feeling,…

In this investigation, we evaluate the comparative efficacy of Random Forest (RF) classifiers and Deep Q-Network (DQN) agents in the context of No-Limit Texas Hold’em poker. Within a high-fidelity simulation, RF-based agents—trained through supervised learning on labeled gameplay data—demonstrated superior and more consistent profitability relative…

Credible assessment of positioning errors of industrial robots is important for their application. The paper concerns a problem of determination of positioning errors of a manipulating robot basing on simulated experimental results. The procedure of ISO 9283 standard was the base of determination of 5…

Task scheduling in multicore systems becomes increasingly complex in the presence of inter-task dependencies, which traditional operating system schedulers are not designed to manage. As a result, tasks are often activated before their prerequisites are satisfied, leading to passive waiting and inefficient CPU utilization. Although…

Business analytics (BA) leverages data-driven techniques, statistical analysis, and predictive modeling to enhance decision-making and strategic planning across industries. With advancements in computing power, artificial intelligence, and big data, BA has become integral to optimizing operations, improving customer experiences, and gaining competitive advantages. This study…