1. Automated text similarities approach : GDPR and privacy by design principlesBoštjan Brumen, 2021, samostojni znanstveni sestavek ali poglavje v monografski publikaciji Opis: Respect for privacy is not a modern phenomenon as it has been around for centuries. Recent advances in technologies led to the rise of awareness of the importance of privacy, and to the development of principles for privacy protection to guide the engineering of information systems on one side, and on using the principles to draft legal texts protecting privacy on the other side. In this paper, we analyze how respect for privacy has been implemented in GDPR by automated comparison of the similarity of GDPR's articles and the text of seven principles of Privacy by Design. We have compared the specific text of GDPR's first 50 core privacy-protecting articles and the GDPR's remaining provisions to establish independent supervisory authorities. The first half is observing the privacy by design principles, each of them considerably more than the second half. Our findings show that automated similarity comparison can highlight portions of legal texts where principles were observed. The results can support drafting legal texts to check whether important legal (or other) principles were adequately addressed.
Ključne besede: privacy, information system, GDPR, privaci by design, similarity, semantics
Objavljeno v DKUM: 20.01.2026; Ogledov: 0; Prenosov: 0
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2. Measuring the coordinated development of the advanced manufacturing cluster based on patent data: A composite system approachH. K. Zhang, J.N. Yang, Borut Buchmeister, Robert Ojsteršek, 2025, izvirni znanstveni članek Opis: The advanced manufacturing industry serves as a key driver of high-quality economic development, with patent data widely used to assess regional technological innovation and synergy. Evaluating coordination within advanced industrial clusters offers practical insights into industrial upgrading. Focusing on the Beijing–Tianjin–Hebei advanced manufacturing cluster in China, the composite system is divided into four subsystems: quantity, quality, efficiency, and value. Using patent data from 2013 to 2023, a composite system synergy model was built to measure the degree of synergy. A coupling coordination degree model and an obstacle degree model were applied together to examine coordination states and limiting factors. The findings show a generally rising synergy degree in the cluster, indicating increased organizational coherence over time. Coupling coordination displayed short-term fluctuations but exhibited a positive long-term trend, achieving high-quality coupling by 2023. Collaborative development is dynamically influenced by multidimensional obstacles, calling for timely and tailored measures to improve synergy efficiency. This study offers an empirical basis for optimizing collaboration in the Beijing–Tianjin–Hebei cluster and provides a theoretical reference for understanding synergy mechanisms in similar industrial clusters.
Ključne besede: advanced manufacturing cluster, patent data, composite system synergy, coupling coordination degree, obstacle degree, regional industrial coordination, innovation synergy
Objavljeno v DKUM: 19.01.2026; Ogledov: 0; Prenosov: 2
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3. Integrated management systems based on risk assessment : methodology development and case studiesS. Vulanović, Milan Delić, Bato Kamberović, Ivan Beker, Bojan Lalić, 2020, izvirni znanstveni članek Opis: The implementation of management systems in organizations is often based on a "blind" meeting of requirements set by the selected standard, while these requirements are not in direct relation to the risks of the organizations. Therefore, it often happens that the established management system is not operational or is not aligned with the context and real needs of the organization. This paper presents general model for the design of an integrated management system based on risk assessment of organization's processes. The model was based on the primary hypothesis that a process that has a higher risk should be described in more detail in order to be adequately realized. The presented Model was tested on three diverse companies which had already implemented management systems according to international standards. Comparing the existing with the projected documentation in three companies, it was concluded that the number, scope and structure of documented information were optimized for successful risk management, which lowers the overall costs and enables efficient management of the company. The paper provides scientific approach and methodology for designing the integrated management system in any organization, using existing risks as universal integrating factor.
Ključne besede: integrated management system, risk management, process approach, failure mode effect analysis, FMEA
Objavljeno v DKUM: 13.01.2026; Ogledov: 0; Prenosov: 0
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4. A hybrid AI-driven knowledge-based expert system for optimizing gear design : a case study for educationBoris Aberšek, Samo Kralj, Andrej Flogie, 2026, izvirni znanstveni članek Opis: This paper presents a hybrid knowledge-based expert system (KBES) designed to predict crack incubation and fatigue life in gear design, serving as both a research tool and an educational resource. While crack growth and initiation are well understood, crack incubation remains a challenging area. The presented expert system (KBES) integrates a novel mathematical model for crack incubation based on analogy and defect analysis principles with an optimization algorithm for gear design. The system uses genetic algorithms to optimize gear parameters, demonstrating a 5-10% deviation from experimental values in a specific gear design problem case study. Based on this KBES and a hybrid approach, we developed a learning environment based on an intelligent tutoring system (ITS) which serves older students (MSc and PhD) as a learning environment for the acquisition of knowledge and, above all, for the development of an in-depth understanding of the phenomena that occur both during incubation and initialization and during the further propagation of cracks in the root of the gear tooth, which is the basis for determining the lifespan of gear transmissions.
Ključne besede: fracture mechanics, principle of universality, crack incubation, gear assemblies, expert system, inteligent tuturing system, engineering education
Objavljeno v DKUM: 13.01.2026; Ogledov: 0; Prenosov: 0
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5. Practical approaches to the control of milk fermentation with kefir grainsJožef Ritonja, Andreja Goršek, Darja Pečar, Darius Andriukaitis, Boštjan Polajžer, 2024, samostojni znanstveni sestavek ali poglavje v monografski publikaciji Opis: In the chapter, milk fermentation for kefir production is studied. The traditional
kefir production process based on inoculating kefir grains into milk is considered. The
quality and quantity of the produced kefir also depend on the dynamics of the fermentation process. The chapter presents the design and synthesis of the closed-loop
control system in which changing the bioreactor’s temperature is used to control the
time course of the concentration of dissolved CO2. In the chapter: (1) a nonlinear
dynamic mathematical model of the fermentation process, which allows evaluating
the influence of the bioreactor’s temperature on the dynamics of the fermentation
process, is presented; (2) the design and synthesis of a conventional linear control
system with constant parameters are carried out; (3) an adaptive control system that
enables the tracking of the courses of the quantities of the fermentation process to the
desired reference trajectories without the time-consuming preliminary identification
of the parameters of the fermentation process model is developed. The numerical,
experimental, and analytic outcomes of the study are presented.
Ključne besede: milk fermentation, batch biorector, mathematical modeling, control system design and synthesis, linear control, model reference adaptive control
Objavljeno v DKUM: 08.01.2026; Ogledov: 0; Prenosov: 3
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6. A multi-task deep learning approach for landslide displacement prediction with applications in early warning systemsDamjan Strnad, Domen Mongus, Štefan Horvat, Ela Šegina, 2025, izvirni znanstveni članek Opis: Accurate landslide displacement prediction is important for the construction of reliable landslide early warning systems (LEWS). Recently, deep neural networks have become the dominant approach for landslide displacement modeling. However, we show that focusing solely on low prediction residuals is not perfectly aligned with the goals of LEWS, where the emphasis is on precise forecasts near the warning threshold. This can result in poor efficiency of threshold-based warning prediction. We propose a multi-task approach to model training, where auxiliary targets are used to optimize the model towards the performance relevant for LEWS. The methodology is validated using the data from the deep-seated Urbas landslide in north-western Slovenia, which has been monitored by GNSS since 2019. Developing a displacement prediction model for Urbas is a step towards extending the existing wire-based mechanical alarm system. We employ a convolutional neural network for day-ahead displacement prediction using recent landslide activity, hydrometeorological measurements and seismological data. The proposed multi-task model retains a competitive score for warning prediction while achieving a significantly lower mean absolute error compared to the reference models. The proposed methodology is generally applicable and has the potential to improve the efficiency of landslide modeling in the context of LEWS.
Ključne besede: landslide displacement prediction, neural network, multitask learning, landslide early warning system, remote sensing, GNSS
Objavljeno v DKUM: 12.12.2025; Ogledov: 0; Prenosov: 2
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7. An integrated PLS-SEM-TOPSIS-Sort approach for assessing ERP solutions acceptance across various industriesAleksandra Radić, Samo Bobek, Sanela Arsić, Đorđe Nikolić, Simona Sternad Zabukovšek, 2025, izvirni znanstveni članek Opis: In the context of accelerated digitalization, enterprises are increasingly adopting information-driven solutions to support managerial decision-making, with Enterprise Resource Planning (ERP) systems playing a crucial role in organizational development. Despite its importance, ERP adoption varies significantly across industries, particularly between developed and developing economies, where technological and structural differences persist. This paper proposes and validates a classification framework for assessing industry readiness for ERP adoption, based on an integrated PLS-SEM-MCDA methodological approach. PLS-SEM identified statistically significant factors and transformed them into weights to compare ERP user attitudes across eleven industries in Serbia and Slovenia. In addition, the TOPSIS-Sort method classified industries into high, moderate, and low readiness as predefined order classes. Finally, sensitivity analysis and comparative analysis are performed with AHP expert weights and the PROMETHEE-FlowSort method to determine the robustness of the PLS-SEM-TOPSIS-Sort results. The results show that the IT industry is the most consistent in adopting ERP systems. In contrast, other industries exhibit varying levels of readiness, depending on their degree of digital maturity and organizational preparedness. The proposed framework’s methodological flexibility allows it to be adapted to various contexts, making it suitable for future academic research and comparative studies. Additionally, the practical implications of the research are twofold. For ERP suppliers, the findings provide guidance on how to approach market segmentation and strategic positioning tailored to the specific needs of individual industries. For ERP users, their success in ERP adoption can be amplified by using the research insights as a benchmarking model.
Ključne besede: ERP system, industries, PLS-SEM, TOPSIS-Sort, PROMETHEE-FlowSort
Objavljeno v DKUM: 02.12.2025; Ogledov: 0; Prenosov: 1
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8. Improving AGV path planning efficiency using Genetic Algorithms with Hamming distance-based initializationŽiga Breznikar, Janez Gotlih, Ž. Artič, Miran Brezočnik, 2025, izvirni znanstveni članek Opis: This paper presents a Genetic Algorithm (GA) framework for warehouse navigation as a Travelling Salesman Problem (TSP) variant for Automated Guided Vehicles (AGVs). The warehouse layout is represented as a graph, where pick-up locations serve as terminal nodes. A distance matrix, computed via Breadth-First Search (BFS) enables efficient route evaluation. To promote diversity in the initial population, a Hamming distance-based vectorized initialization strategy is employed, ensuring that the chromosomes are maximally distinct. The GA balances exploration and exploitation by dynamically adjusting the fitness function. Early generations emphasize diversity, while later ones focus on solution refinement, improving convergence and avoiding premature stagnation. Our key contribution demonstrates that the Hamming distance-based approach achieves comparable or better results with significantly fewer chromosomes. This reduces computational cost and runtime, making the method well-suited for real-time AGV routing in warehouses. The framework is adaptable to structured environments and shows strong potential for integration into real-world logistics and robotics applications. Future work will focus on optimizing the algorithm and integrating it into the ROS 2 environment.
Ključne besede: automated guided vehicles (AGV), warehouse routing, combinatorial optimization, Hamming distance initialization, Robot operating system 2 (ROS 2)
Objavljeno v DKUM: 28.11.2025; Ogledov: 0; Prenosov: 6
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9. Dynamic modeling and experimental validation of the photovoltaic/thermal systemKlemen Sredenšek, Eva Simonič, Klemen Deželak, Marko Bizjak, Niko Lukač, Sebastijan Seme, 2025, izvirni znanstveni članek Opis: The aim of this paper is to present a novel and comprehensive methodology for the dynamic modeling and experimental validation of a photovoltaic/thermal system. The dynamic model is divided into thermal and electrical subsystems, encompassing the photovoltaic/ thermal module and the thermal energy storage. The thermal subsystem of both the photovoltaic/thermal module and the thermal energy storage is described by a one-dimensional dynamic model of heat transfer mechanisms and optical losses, while the electrical subsystem is presented as an electrical equivalent circuit of double diode solar cell. Model validation was conducted on a modern experimental photovoltaic/thermal system over an extended operational period at a five-minute resolution, with validation days classified as sunny, cloudy, or overcast based on weather conditions, thereby demonstrating an applied approach. The results demonstrate the lowest deviation values reported to date, confirmed using six quantitative indicators. The added value of the proposed methodology, not previously addressed in the literature, lies in the following contributions: (i) comprehensive modeling of the entire photovoltaic/thermal system, (ii) accurate consideration of optical losses in the photovoltaic/thermal module, and (iii) long-term experimental validation. Overall, the proposed methodology provides a reliable and efficient framework for PV/T system design, optimization, and long-term performance assessment.
Ključne besede: photovoltaic/thermal system, thermal energy storage, dynamic modeling, experimental validation, heat transfer mechanism, temperature, electrical power
Objavljeno v DKUM: 10.11.2025; Ogledov: 0; Prenosov: 11
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10. Performance Enhancement of Grid Connected Multilevel Inverter Based Wind Energy Conversion System with LVRT Capability Using Optimized Type 2 ANFIS Based DVRCh. Sajan, P. Satish Kumar, Peter Virtič, 2024, izvirni znanstveni članek Opis: A Permanent Magnet Synchronous Generator (PMSG) based Wind Energy Conversion System (WECS) holds significant importance in the realm of Renewable Energy Sources (RES) for several reasons. The permanent magnets in the generator eliminate the need for a separate excitation system, leading to improved efficiency in power conversion. This makes PMSG-based WECS an effective and reliable source of wind energy electricity. The motivation behind the proposed conceptual framework stems from the need to overcome the limitations related to the integration of RES into the power grid, specifically focusing on voltage stability and Low Voltage Ride Through (LVRT) capability of PMSG based WECS. A Dynamic Voltage Restorer (DVR), empowered by an energy storage device, is used to mitigate voltage fluctuations and disturbances. The input DC voltage to the DVR is intricately regulated by a Type 2 Adaptive Neuro Fuzzy Inference System (ANFIS) Controller optimized using the Seagull algorithm, exhibiting intelligent adaptability to dynamic conditions. The rectified output from the WECS transforms an Isolated Flyback converter. Subsequently, a 31-Level Cascaded H-Bridge Multilevel Inverter (CHBMLI) along with a Proportional-Integral (PI) controller aids in generating high-quality AC output. By addressing challenges related to voltage stability and the ability to ride through low-voltage conditions, the proposed work contributes to enhanced grid stability. The use of advanced control techniques, including the Type 2 ANFIS Controller optimized by the Seagull algorithm, adds a layer of intelligent adaptability to changing environmental and grid conditions. A lower Total Harmonic Distortion (THD) Value of 1.29% is shown during the validation of the created system utilizing MATLAB/Simulink, assuring significant LVRT capabilities.
Ključne besede: Permanent Magnet Synchronous Generator (PMSG), Wind Energy Conversion System (WECS), Renewable Energy Sources (RES), Low Voltage Ride Through (LVRT), Type 2 Adaptive Neuro Fuzzy Inference System, 31-Level CHBMLI, Proportional-Integral (PI)
Objavljeno v DKUM: 06.11.2025; Ogledov: 0; Prenosov: 3
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