Volume 17 - 2025
Comparative Analysis of Different Noise Colors
The objective of this paper is to systematically identify and analyze the most prominent types of noise categorized by color, with particular emphasis on white noise as the foundational reference from which all other types are derived. The study focuses on the spectral and statistical properties of white, pink, brown, blue, purple, and grey noise. Additionally, the paper provides an overview of the fundamental characteristics of the acoustic spectra. It finds applications in fields such as acoustics, audio engineering, and digital signal processing, as it includes spectral analysis of various noise types and demonstrates their critical role in understanding their behavior and practical applications. The paper contains code created in Octave that generates the spectral densities of the noises of interest, and it represents a contribution of the paper.
Design and implementation of a software solution for the distribution of teaching activities
The distribution of teaching activities is a key process in the organization of educational institutions, requiring a clear and systematic method for assigning subjects to teachers. This master’s thesis presents the design and implementation of a web-based software solution that supports and automates the distribution process in schools. The application is developed using Angular for the frontend and Spring Boot for the backend, providing a scalable and maintainable architecture.
The system allows users to manage teachers and subjects, create distributions, export data in JSON format, and generate PDF documents for administrative and payroll purposes. The backend is based on RESTful API principles and uses DTO objects for structured and efficient data transfer, while the frontend offers a user-friendly interface for managing distributions.
Prototype of a Large Language Model-Based Interviewer: Design, Implementation, and Evaluation
The development of artificial intelligence agents based on Large Language Models (LLMs) represents a major milestone in the automation of technical interview processes. Modern LLMs enable the simulation of realistic communication between a candidate and an interviewer, during which the candidate’s responses are analyzed, technical skills evaluated, and feedback formulated according to predefined criteria.
This paper presents the implementation and analysis of an AI agent that uses LLMs to conduct interviews with candidates applying for software engineering positions. A well-designed system of this kind enables reliable assessment of candidate performance through the analysis of guided conversation and interaction within a programming work environment.
System for Processing, Storing, and Searching Single-Cell RNA Sequencing Data
Single-Cell RNA Sequencing (scRNA-seq) technology enables gene expression analysis at individual cell resolution, revealing cellular heterogeneity and developmental pathways, but generates massive, complex datasets that pose significant bioinformatics challenges for processing, storage, and analysis. This master's thesis presents an integrated platform that addresses these challenges by combining automated data processing through Nextflow workflows with advanced search and analysis systems, including centralized metadata storage in optimized relational databases and intelligent data searching using both traditional indexing and artificial intelligence approaches.
The system's key innovation is a RAG (Retrieval-Augmented Generation) architecture that enables natural language-based contextual searching and semantic analysis of scientific studies, integrated with both a Python API and an intuitive web interface for researchers. Designed for scalability, high performance, and data security with support for distributed computing, the platform significantly improves accessibility and usability of single-cell RNA sequencing data, accelerating research in functional genomics, developmental biology, biomedicine, and personalized medicine while providing practical value to the bioinformatics community.
An Approach to the Development of a Receivables Collection System Based on SAP Technologies
The aim of this paper is to provide insight into how SAP's specific module, RMCA, is implemented within the context of a company. The focus is on a theoretical analysis of the system architecture, based on concrete examples. In addition, strategies and recommendations that we have acquired and applied in practice are also presented. This paper may help in understanding and future implementations of the entire receivables collection process using this and other similar technologies.