Ivan Lorencin
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Memetic Algorithm for Energy Optimization in Point-to-Point Robotized Operations Open
This paper presents a memetic algorithm (MA) for energy cost estimation of a robot path. The developed algorithm uses a random recombination genetic algorithm (GA) as the basis for the first stage of the algorithm and performs a local sear…
Context-Aware Tourism Recommendations Using Retrieval-Augmented Large Language Models and Semantic Re-Ranking Open
This study evaluates the performance of seven large language models (LLMs) in generating context-aware recommendations. The system is built on a collection of PDF documents (brochures) describing local events and activities, which are embe…
Robust Clinical Querying with Local LLMs: Lexical Challenges in NL2SQL and Retrieval-Augmented QA on EHRs Open
Electronic health records (EHRs) are typically stored in relational databases, making them difficult to query for nontechnical users, especially under privacy constraints. We evaluate two practical clinical NLP workflows, natural language …
Large Language Models for Structured and Semi-Structured Data, Recommender Systems and Knowledge Base Engineering: A Survey of Recent Techniques and Architectures Open
Large Language Models (LLMs) are reshaping recommendation systems through enhanced language understanding, reasoning, and integration with structured data. This systematic review analyzes 88 studies published between 2023 and 2025, categor…
Data Augmentation-Driven Improvements in Malignant Lymphoma Image Classification Open
Artificial intelligence (AI)-based techniques have become increasingly prevalent in the classification of medical images. However, the effectiveness of such methods is often constrained by the limited availability of annotated medical data…
Transforming Medical Data Access: The Role and Challenges of Recent Language Models in SQL Query Automation Open
Generating accurate SQL queries from natural language is critical for enabling non-experts to interact with complex databases, particularly in high-stakes domains like healthcare. This paper presents an extensive evaluation of state-of-the…
Zero-Shot Learning in Maritime Domain Open
Maritime security and monitoring are essential for global trade, environmental protection,and national defense. Traditional machine learning models have been effective in recognizing andclassifying maritime objects, but their reliance on l…
K-means Clustering of Intracellular Calcium Signal Transients Open
Neurological diseases pose a significant public health challenge, leading to disability and mortality globally.Current diagnostics for neuroinflammatory diseases are complex and lack efficacy, necessitating invasive procedures.Calcium sign…
Military Decision-Making Process Enhanced by Image Detection Open
This study delves into the vital missions of the armed forces, encompassing the defense of territorial integrity, sovereignty, and support for civil institutions. Commanders grapple with crucial decisions, where accountability underscores …
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Table of Contents Open
Clustering-based parameter estimation of a tumor model
Classification of Faults Operation of a Robotic Manipulator Using Symbolic Classifier Open
In autonomous manufacturing lines, it is very important to detect the faulty operation of robot manipulators to prevent potential damage. In this paper, the application of a genetic programming algorithm (symbolic classifier) with a random…
Detection and Classification of Printed Circuit Boards Using YOLO Algorithm Open
Printed circuit boards (PCBs) are an indispensable part of every electronic device used today. With its computing power, it performs tasks in much smaller dimensions, but the process of making and sorting PCBs can be a challenge in PCB fac…
Drive System Inverter Modeling Using Symbolic Regression Open
For accurate and efficient control performance of electrical drives, precise values of phase voltages are required. In order to achieve control of the electric drive, the development of mathematical models of the system and its parts is of…
On the Use of a Genetic Algorithm for Determining Ho–Cook Coefficients in Continuous Path Planning of Industrial Robotic Manipulators Open
Path planning is one of the key steps in the application of industrial robotic manipulators. The process of determining trajectories can be time-intensive and mathematically complex, which raises the complexity and error proneness of this …
Localization and Classification of Venusian Volcanoes Using Image Detection Algorithms Open
Imaging is one of the main tools of modern astronomy—many images are collected each day, and they must be processed. Processing such a large amount of images can be complex, time-consuming, and may require advanced tools. One of the techni…
On Approximating the pIC50 Value of COVID-19 Medicines In Silico with Artificial Neural Networks Open
In the case of pandemics such as COVID-19, the rapid development of medicines addressing the symptoms is necessary to alleviate the pressure on the medical system. One of the key steps in medicine evaluation is the determination of pIC50 f…
Cervical Cancer Diagnostics Using Machine Learning Algorithms and Class Balancing Techniques Open
Objectives: Cervical cancer is present in most cases of squamous cell carcinoma. In most cases, it is the result of an infection with human papillomavirus or adenocarcinoma. This type of cancer is the third most common cancer of the female…
Classification of Wall Following Robot Movements Using Genetic Programming Symbolic Classifier Open
The navigation of mobile robots throughout the surrounding environment without collisions is one of the mandatory behaviors in the field of mobile robotics. The movement of the robot through its surrounding environment is achieved using se…
The Development of Symbolic Expressions for the Detection of Hepatitis C Patients and the Disease Progression from Blood Parameters Using Genetic Programming-Symbolic Classification Algorithm Open
Hepatitis C is an infectious disease which is caused by the Hepatitis C virus (HCV) and the virus primarily affects the liver. Based on the publicly available dataset used in this paper the idea is to develop a mathematical equation that c…
The Development of Symbolic Expressions for Fire Detection with Symbolic Classifier Using Sensor Fusion Data Open
Fire is usually detected with fire detection systems that are used to sense one or more products resulting from the fire such as smoke, heat, infrared, ultraviolet light radiation, or gas. Smoke detectors are mostly used in residential are…
Estimation of Excitation Current of a Synchronous Machine Using Machine Learning Methods Open
A synchronous machine is an electro-mechanical converter consisting of a stator and a rotor. The stator is the stationary part of a synchronous machine that is made of phase-shifted armature windings in which voltage is generated and the r…
Detection of Malicious Websites Using Symbolic Classifier Open
Malicious websites are web locations that attempt to install malware, which is the general term for anything that will cause problems in computer operation, gather confidential information, or gain total control over the computer. In this …
Mean Phase Voltages and Duty Cycles Estimation of a Three-Phase Inverter in a Drive System Using Machine Learning Algorithms Open
To achieve an accurate, efficient, and high dynamic control performance of electric motor drives, precise phase voltage information is required. However, measuring the phase voltages of electrical motor drives online is expensive and poten…
Applying Regressive Machine Learning Techniques in Determination of COVID-19 Vaccinated Patients’ Influence on the Number of Confirmed and Deceased Patients Open
Vaccinations are one of the most important steps in combat against viral diseases such as COVID-19. Determining the influence of the number of vaccinated patients on the infected population represents a complex problem. For this reason, th…
Ship production processes air emissions analysis Open
Compliance with modern environmental norms and regulations is an increasingly important requirement in the shipbuilding process of ship design and construction. Related to the ship production process, volatile organic compounds (VOCs), nit…
Genetic Algorithm-Based Parametrization of a PI Controller for DC Motor Control Open
This paper analyses the application of a genetic algorithm (GA) for the purpose of designing the control system with separately excited DC motor controlled according to the rotor angle. The presented research is based on the utilization of…
Determining residuary resistance per unit weight of displacement with Symbolic Regression and Gradient Boosted Tree algorithms Open
Determining the residuary resistance per unit weight of displacement is one of the key factors in the design of vessels. In this paper, the authors utilize two novel methods – Symbolic Regression (SR) and Gradient Boosted Trees (GBT) to ac…
Semantic Segmentation of Urinary Bladder Cancer Masses from CT Images: A Transfer Learning Approach Open
Urinary bladder cancer is one of the most common cancers of the urinary tract. This cancer is characterized by its high metastatic potential and recurrence rate. Due to the high metastatic potential and recurrence rate, correct and timely …
Epidemiological Predictive Modeling of COVID-19 Infection: Development, Testing, and Implementation on the Population of the Benelux Union Open
Since the outbreak of coronavirus disease-2019 (COVID-19), the whole world has taken interest in the mechanisms of its spread and development. Mathematical models have been valuable instruments for the study of the spread and control of in…