1. Efficient encoding and decoding of voxelized models for machine learning-based applicationsDamjan Strnad, Štefan Kohek, Borut Žalik, Libor Váša, Andrej Nerat, 2025, original scientific article Abstract: Point clouds have become a popular training data for many practical applications of machine learning in the fields of environmental modeling and precision agriculture. In order to reduce high space requirements and the effect of noise in the data, point clouds are often transformed to a structured representation such as a voxel grid. Storing, transmitting and consuming voxelized geometry, however, remains a challenging problem for machine learning pipelines running on devices with limited amount of on-chip memory with low access latency. A viable solution is to store the data in a compact encoded format, and perform on-the-fly decoding when it is needed for processing. Such on-demand expansion must be fast in order to avoid introducing substantial additional delay to the pipeline. This can be achieved by parallel decoding, which is particularly suitable for massively parallel architecture of GPUs on which the majority of machine learning is currently executed. In this paper, we present such method for efficient and parallelizable encoding/decoding of voxelized geometry. The method employs multi-level context-aware prediction of voxel occupancy based on the extracted binary feature prediction table, and encodes the residual grid with a pointerless sparse voxel octree (PSVO). We particularly focused on encoding the datasets of voxelized trees, obtained from both synthetic tree models and LiDAR point clouds of real trees. The method achieved 15.6% and 12.8% reduction of storage size with respect to plain PSVO on synthetic and real dataset, respectively. We also tested the method on a general set of diverse voxelized objects, where an average 11% improvement of storage space was achieved.
Keywords: voxel grid, feature prediction, tree models, prediction-based encoding, key voxels, residuals, sparse voxel octree
Published in DKUM: 09.01.2025; Views: 0; Downloads: 0
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2. Kratek pregled platform za ADME testiranjeTina Maver, Boštjan Vihar, Uroš Maver, 2024, original scientific article Abstract: V zadnjem času je bil dosežen pomemben napredek pri razvoju ADME (absorpcija, distribucija, metabolizem, ekskrecija) modelov, vendar izziv ostaja vzpostaviti platforme, ki bi zmanjšale testiranje na živalih in stroške raziskav. Naraščajoča pomembnost farmakokinetičnih interakcij poudarja potrebo po zanesljivih in
ponovljivih ADME modelih, ki so vse bolj ključni za razvoj zdravil in zagotavljanje varnosti z željo po preprečevanju
resnih kliničnih zapletov in hospitalizacije.
Keywords: ADME, drug interaction studies, in vitro models, pharmacokinetics, multi-organ models
Published in DKUM: 07.01.2025; Views: 0; Downloads: 3
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3. In vitro disease models of the endocrine pancreasMarko Milojević, Jan Rožanc, Jernej Vajda, Laura Činč Ćurić, Eva Paradiž, Andraž Stožer, Uroš Maver, Boštjan Vihar, 2021, review article Abstract: The ethical constraints and shortcomings of animal models, combined with the demand to study disease pathogenesis under controlled conditions, are giving rise to a new field at the interface of tissue engineering and pathophysiology, which focuses on the development of in vitro models of disease. In vitro models are defined as synthetic experimental systems that contain living human cells and mimic tissue- and organ-level physiology in vitro by taking advantage of recent advances in tissue engineering and microfabrication. This review provides an overview of in vitro models and focuses specifically on in vitro disease models of the endocrine pancreas and diabetes. First, we briefly review the anatomy, physiology, and pathophysiology of the human pancreas, with an emphasis on islets of Langerhans and beta cell dysfunction. We then discuss different types of in vitro models and fundamental elements that should be considered when developing an in vitro disease model. Finally, we review the current state and breakthroughs in the field of pancreatic in vitro models and conclude with some challenges that need to be addressed in the future development of in vitro models.
Keywords: in vitro disease models, pancreas, islet of Langerhans, 3D cell culture, scaffolds, acute tissue slices
Published in DKUM: 01.10.2024; Views: 0; Downloads: 7
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4. Understanding cognitive transport mode choice structures : means-ends chains as a type of second-order cyberneticsTomaž Kolar, Iztok Kolar, 2022, original scientific article Abstract: Purpose: This paper aims to inform the promotion of sustainable modes of transport. For this purpose, it deploys a means-ends framework as a type of second-order cybernetics and uses it to explore cognitive transport mode choice structures.
Design/methodology/approach: The empirical study relies on a purposive sample and a qualitative research methodology known as laddering. It is aimed at the identification and comparative analysis of the cognitive means-ends structures of transport users.
Findings: The results reveal more positive and complex associations for the car than for public transport. Two main positive means-ends structures are identified for public transport, one related with the relaxation and the other with doing useful things while travelling. Dominant positive structures for the car are related with self-confidence, satisfaction and personal freedom. Negative means-ends structures in addition reveal important justifications and rationalizations for car use.
Practical implications: Based on the identified distinct means-ends elements and structures, this study holds important implications for developing a communications strategy and policy interventions seeking to promote public transport.
Originality/value: Means-ends theory is proposed as an integrative cybernetic framework for the study of stakeholders' (customers') mental models. The empirical study is the first to concurrently and comparatively examine positive and negative means-ends chains for the car and for the public transport modes.
Keywords: public transport, second-order cybernetics, laddering methodology, means-ends theory, private car, mental models, personal values, marketing, consumer
Published in DKUM: 27.08.2024; Views: 93; Downloads: 11
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5. Methods and models for electric load forecasting : a comprehensive reviewMahmoud A. Hammad, Borut Jereb, Bojan Rosi, Dejan Dragan, 2020, original scientific article Abstract: Electric load forecasting (ELF) is a vital process in the planning of the electricity industry and plays a crucial role in electric capacity scheduling and power systems management and, therefore, it has attracted increasing academic interest. Hence, the accuracy of electric load forecasting has great importance for energy generating capacity scheduling and power system management. This paper presents a review of forecasting methods and models for electricity load. About 45 academic papers have been used for the comparison based on specified criteria such as time frame, inputs, outputs, the scale of the project, and value. The review reveals that despite the relative simplicity of all reviewed models, the regression analysis is still widely used and efficient for long-term forecasting. As for short-term predictions, machine learning or artificial intelligence-based models such as Artificial Neural Networks (ANN), Support Vector Machines (SVM), and Fuzzy logic are favored.
Keywords: methods, models, electric load forecasting, modeling electricity loads, electricity industry, power management, logistics
Published in DKUM: 22.08.2024; Views: 95; Downloads: 8
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6. 7th International Conference on Technologies & Business Models for Circular Economy : book of abstracts2024 Abstract: The 7th International Conference on Technologies & Business Models for Circular Economy (TBMCE) was organized by the Faculty of Chemistry and Chemical Engineering, University of Maribor in collaboration with the Strategic Research and Innovation Partnership - Networks for the Transition into Circular Economy (SRIP- Circular Economy), managed by the Chamber of Commerce and Industry of Štajerska. The conference was held in Portorož, Slovenia, at the Grand Hotel Bernardin from September 4th to September 6th, 2024. EIT RawMaterials RIS Hub Adria, SPIRIT Slovenia Business Development Agency and Pomurje Technology Park (as part of the GREENE 4.0 and CI-Hub projects) have joined us as co-organizers. TBMCE 2024 was devoted to presentations of circular economy concepts, technologies and methodologies that contribute to the shift of business entities and society as a whole to a more responsible, circular management of resources. The conference program included panel discussions, plenary and keynote sessions, oral and poster presentations on the following topics: Sustainable Energy, Biomass and Alternative Raw Materials, Circular Business Models, Secondary Raw Materials and Functional Materials, ICT in Circular Economy, Processes and Technologies. Panel discussions addressed following topics: Circular Economy Transition in South East Europe, The transition to carbon neutrality in energy intensive industry, Valorization of used and contaminated wood, Circular economy trends in construction, Critical raw materials and circular economy transition, Industrial Symbiosis and its opportunities for industry, AI and circular economy. The event was under the patronage of Ministry of the Economy, Tourism and Sport and Ministry of Cohesion and Regional Development.
Keywords: circular economy, sustainable development, processes and technologies, circular business models, research and development
Published in DKUM: 22.08.2024; Views: 93; Downloads: 20
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7. Computer science education in ChatGPT Era: experiences from an experiment in a programming course for novice programmersTomaž Kosar, Dragana Ostojić, Yu David Liu, Marjan Mernik, 2024, original scientific article Abstract: The use of large language models with chatbots like ChatGPT has become increasingly popular among students, especially in Computer Science education. However, significant debates exist in the education community on the role of ChatGPT in learning. Therefore, it is critical to understand the potential impact of ChatGPT on the learning, engagement, and overall success of students in classrooms. In this empirical study, we report on a controlled experiment with 182 participants in a first-year undergraduate course on object-oriented programming. Our differential study divided students into two groups, one using ChatGPT and the other not using it for practical programming assignments. The study results showed that the students’ performance is not influenced by ChatGPT usage (no statistical significance between groups with a p-value of 0.730), nor are the grading results of practical assignments (p-value 0.760) and midterm exams (p-value 0.856). Our findings from the controlled experiment suggest that it is safe for novice programmers to use ChatGPT if specific measures and adjustments are adopted in the education process.
Keywords: large language models, ChatGPT, artificial intelligence, controlled experiment, object-oriented programming, software engineering education
Published in DKUM: 12.08.2024; Views: 59; Downloads: 6
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8. Glucose-stimulated calcium dynamics in beta cells from male C57BL/6J, C57BL/6N, and NMRI mice : a comparison of activation, activity, and deactivation properties in tissue slicesViljem Pohorec, Lidija Križančić Bombek, Maša Skelin, Jurij Dolenšek, Andraž Stožer, 2022, original scientific article Abstract: Although mice are a very instrumental model in islet beta cell research, possible phenotypic differences between strains and substrains are largely neglected in the scientific community. In this study, we show important phenotypic differences in beta cell responses to glucose between C57BL/6J, C57BL/6N, and NMRI mice, i.e., the three most commonly used strains. High-resolution multicellular confocal imaging of beta cells in acute pancreas tissue slices was used to measure and quantitatively compare the calcium dynamics in response to a wide range of glucose concentrations. Strain- and substrain-specific features were found in all three phases of beta cell responses to glucose: a shift in the dose-response curve characterizing the delay to activation and deactivation in response to stimulus onset and termination, respectively, and distinct concentration-encoding principles during the plateau phase in terms of frequency, duration, and active time changes with increasing glucose concentrations. Our results underline the significance of carefully choosing and reporting the strain to enable comparison and increase reproducibility, emphasize the importance of analyzing a number of different beta cell physiological parameters characterizing the response to glucose, and provide a valuable standard for future studies on beta cell calcium dynamics in health and disease in tissue slices.
Keywords: beta cell, mouse models, calcium imaging, glucose-dependence, tissue slice
Published in DKUM: 15.07.2024; Views: 148; Downloads: 22
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9. Unmasking the structure of a chiral cubic thermotropic liquid crystal phase by a combination of soft and tender resonant X-ray scatteringTimon Grabovac, Ewa Górecka, Chenhui Zhu, Damian Pociecha, Nataša Vaupotič, 2022, original scientific article Abstract: A resonant X-ray scattering response for two structural models of a chiral cubic phase with a giant unit cell, one composed of a continuous grid and micelles and the other with three continuous grids, is studied theoretically and compared to experimental measurements. For both structural models resonant enhancement of all the symmetry-allowed diffraction peaks is predicted, as well as the existance of several symmetry forbidden peaks (pure resonant peaks). Experimental measurements were performed at the carbon and sulphur absorption edge. Only one pure resonant peak was observed, which is predicted by both models. Two low-angle symmetry allowed peaks, not observed in non-resonant scattering, were resonantly enhanced and their intensity angular dependence can distinguish between the two structural models.
Keywords: resonant X-ray scattering, chiral cubic thermotropic liquid crystal phase, structural models, carbon absorption edge, sulphur absorption edge
Published in DKUM: 13.06.2024; Views: 140; Downloads: 14
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10. Road freight transport forecasting : a fuzzy Monte-Carlo simulation-based model selection approachDejan Dragan, Simona Šinko, Abolfazl Keshavarzsaleh, Maja Rosi, 2022, original scientific article Abstract: As important as the classical approaches such as Akaike's AIC information and Bayesian BIC criterion in model-selection mechanism are, they have limitations. As an alternative, a novel modeling design encompasses a two-stage approach that integrates Fuzzy logic and Monte Carlo simulations (MCSs). In the first stage, an entire family of ARIMA model candidates with the corresponding information-based, residual-based, and statistical criteria is identified. In the second stage, the Mamdani fuzzy model (MFM) is used to uncover interrelationships hidden among previously obtained models criteria. To access the best forecasting model, the MCSs are also used for different settings of weights loaded on the fuzzy rules. The obtained model is developed to predict the road freight transport in Slovenia in the context of choosing the most appropriate electronic toll system. Results show that the mechanism works well when searching for the best model that provides a well-fit to the real data.
Keywords: forecasting road transport, electronic toll system, Monte Carlo simulation, ARIMA models, logistics
Published in DKUM: 11.06.2024; Views: 135; Downloads: 11
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