1. Modeling of tensile test results for low alloy steels by linear regression and genetic programming taking into account the non-metallic inclusionsMiha Kovačič, Uroš Župerl, 2022, original scientific article Abstract: Štore Steel Ltd. is one of the biggest flat spring steel producers in Europe. The main
motive for this study was to study the influences of non-metallic inclusions on mechanical properties
obtained by tensile testing. From January 2016 to December 2021, all available tensile strength data
(472 cases–472 test pieces) of 17 low alloy steel grades, which were ordered and used by the final
user in rolled condition, were gathered. Based on the geometry of rolled bars, selected chemical
composition, and average size of worst fields non-metallic inclusions (sulfur, silicate, aluminium
and globular oxides), determined based on ASTM E45, several models for tensile strength, yield
strength, percentage elongation, and percentage reduction area were obtained using linear regression
and genetic programming. Based on modeling results in the period from January 2022 to April 2022,
five successively cast batches of 30MnVS6 were produced with a statistically significant reduction
of content of silicon (t-test, p < 0.05). The content of silicate type of inclusions, yield, and tensile
strength also changed statistically significantly (t-test, p < 0.05). The average yield and tensile strength
increased from 458.5 MPa to 525.4 MPa and from 672.7 MPa to 754.0 MPa, respectively. It is necessary
to emphasize that there were no statistically significant changes in other monitored parameters.
Keywords: mechanical properties, tensile test, tensile strength, yield strength, percentage elongation, percentage reduction area, low alloy steel, modeling, linear regression, genetic programming, industrial study, steel making, optimization
Published in DKUM: 24.03.2025; Views: 0; Downloads: 2
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2. International energy security risk index - analysis of the methodological settingsIztok Podbregar, Goran Šimić, Mirjana Radovanović, Sanja Filipović, Polona Šprajc, 2020, original scientific article Abstract: The main objective of this paper is to analyze model settings of the International Energy Security Risk Index developed by the U.S. Chamber of Commerce. The study was performed using stepwise regression, principal component analysis, and Promax oblique rotation. The conclusion of the regression analysis shows that Crude Oil Price and Global Coal Reserves are sufficient to explain 90% of the variance of the Index. However, if a model that explains 100% of the variance of the Index is chosen and other variables are added, Global Coal Reserves loses importance due to the presence of other parameters in which it is contained. Regardless of the chosen model of analysis, it is evident that there is room for revising the Index and removing variables that do not contribute to its precision. The research showed that the main disadvantage of the variables that make up the Index rests with the fact that the variables are of different degrees of generality, that is, one parameter is contained in other parameters (unclear which other). The research covers data for 25 countries over a 26-year period, with the first year of the research being 1980 and the last 2016 (the latest available report).
Keywords: international energy security risk index, analysis, stepwise regression, principal component analysis, Promax oblique rotation
Published in DKUM: 04.02.2025; Views: 0; Downloads: 16
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3. The international energy security risk index in sustainable energy and economy transition decision making - a reliability analysisIztok Podbregar, Goran Šimić, Mirjana Radovanović, Sanja Filipović, Damjan Maletič, Polona Šprajc, 2020, original scientific article Abstract: The world economy and society are in a complex process of transition characterized by a high degree of uncertainty. Therefore, further development and management of the transition will largely depend on the quality of the decisions made and, accordingly, on the decision-making process itself. The main goal of this study is to analyze the reliability of International Energy Security Risk Index as a tool to support the process of energy and economy transition decision making, as closely related and highly interdependent phenomena. The index is composed of 29 aggregated variables (grouped into eight categories), and the research is conducted on a research sample of 25 countries over a period of 36 years. The reliability assessment is performed by using Multiple Regression Analysis. Multicollinearity test, plus Multicollinearity test with Variance Inflation Factors, is used for methodological verification. The test results indicate a high degree of unreliability of the Index, as is concluded based on the observed errors in its methodological settings. These errors primarily relate to a high degree of multicollinearity in all 29 variables, whereby independent variables lose their independence and thus jeopardize reliability of the total Index. Out of the eight groups of variables, the fuel imports group is the only one that does not show big methodological errors. The paper presents a recommendation for the improvement of the observed Index (review of the role of individual variables found to be particularly methodologically indicative), as well as a recommendation for different distribution of weighting coefficients.
Keywords: energy and economy transition, decision making, international energy security risk index, multiple regression analysis, multicollinearity test, multicollinearity test with variance inflation factors
Published in DKUM: 04.02.2025; Views: 0; Downloads: 7
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4. Global projections of plastic use, end-of-life fate and potential changes in consumption, reduction, recycling and replacement with bioplastics to 2050Monika Dokl, Anja Copot, Damjan Krajnc, Yee Van Fan, Annamaria Vujanović, Kathleen B. Aviso, Raymond R. Tan, Zdravko Kravanja, Lidija Čuček, 2024, original scientific article Abstract: Excessive production, indiscriminate consumption, and improper disposal of plastics have led to plastic pollution and its hazardous environmental effects. Various approaches to tackle the challenges of reducing the plastic footprint have been developed and applied, such as the production of alternative materials (design for recycling), the production and use of biodegradable plastic and plastics from power-to-X, and the development of recycling approaches. This study proposes an optimisation strategy based on regression to evaluate and predict plastic use and end-of-life fate in the future based on historical trends. The mathematical model is formulated and correlations based on functions of time are developed and optimised by minimising the sum of squared residuals. The plastic quantities up to the year 2050 are projected based on historical trends analysis, and for improved sustainability, projections are additionally based on intervention analyses. The results show that the global use of plastics is expected to increase from 464 Mt in 2020 up to 884 Mt in 2050, with up to 4725 Mt of plastics accumulated in stock in 2050 (from the year 2000). Compared to other available forecasts, a slightly lower level of plastic use and stock are obtained. The intervention analysis estimates a range of global plastics' consumption between 594 Mt and 1018 Mt in 2050 by taking into account its different increment rates (between −1 % and 2.65 %). In the packaging sector, the implementation of reduction targets (15 % reduction in 2040 compared to 2018) could lead to a 27.3 % decrease in plastic use in 2050 as compared to 2018, while achieving recycling targets (55 % in 2030) would recycle >75 % of plastic packaging in 2050. The partial substitution of fossil-based plastics with bioplastics (polyethylene) will require significant land area, between 0.2 × 106 km2 for obtaining switchgrass and up to around 1.0 × 106 km2 for obtaining forest residue (annual yields of 58.15 t/ha and 3.5 t/ha) in 2050. The intervention analysis shows that proactive policies can mitigate sustainability challenges, however achieving broader sustainability goals also requires reduction of footprints related to energy production and virgin plastic production, the production of bio-based plastics, and the full implementation of recycling initiatives.
Keywords: plastic use, plastic waste, end-of-life fate, forecasting, hostorical trends, regression analysis, least square method, intervention analysis
Published in DKUM: 31.01.2025; Views: 0; Downloads: 2
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5. Developing a framework for closed-loop supply chain and its impact on sustainability in the petrochemicals industryLobna Tag el Sheikh, Rebeka Kovačič Lukman, 2022, original scientific article Abstract: Companies rely on formulating, implementing, and monitoring strategies in social, environmental and economic aspects to ensure that they achieve their goals and keep abreast of developments related to sustainability requirements. Therefore, our study develops a system to integrate the closed-loop supply chain approach in the petrochemical sector. The research follows the quantitative-based approach by collecting data through a questionnaire directed to employees in the supply chain departments, including 230 questionnaires that were collected. Correlation and structural equation models (SEM) were used. This technique consists of multiple regression analysis and factor analysis and analyses the structural relationship between the underlying structures and the measured variables. The results indicated a significant relationship between the supply chains that have a loop from the following perspectives: economic motivations, customer awareness, environmental legislation, and sustainability. By increasing financial reasons, customer awareness and environmental legislation, sustainability will increase as they all move in the same direction. Therefore, the overall effect of a closed-loop supply chain is positive and significant.
Keywords: closed-loop supply chain, petrochemicals, cost effectivity, product stewardship, multiple regression analysis, factor analysis, sustainability
Published in DKUM: 12.12.2024; Views: 0; Downloads: 4
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6. Optimization of billet cooling after continuous casting using genetic programming—industrial studyMiha Kovačič, Aljaž Zupanc, Robert Vertnik, Uroš Župerl, 2024, original scientific article Abstract: ŠTORE STEEL Ltd. is one of the three steel plants in Slovenia. Continuous cast 180 mm × 180 mm billets can undergo cooling to room temperature using a turnover cooling bed. They can also be cooled down under hoods or heat treated to reduce residual stresses. Additional operations of heat treatment from 36 h up to 72 h and cooling of the billets for 24 h, with limited capacities (with only two heat treatment furnaces and only six hoods), drastically influence productivity. Accordingly, the casting must be carefully planned (i.e., the main thing is casting in sequences), while the internal quality of the billets (i.e., the occurrence of inner defects) may be compromised. Also, the stock of billets can increase dramatically. As a result, it was necessary to consider the abandoning of cooling under hoods and heat treatment of billets. Based on the collected scrap data after ultrasonic examination of rolled bars, linear regression and genetic programming were used for prediction of the occurrence of inner defects. Based on modeling results, cooling under hoods and heat treatment of billets were abandoned at the casting of several steel grades. Accordingly, the casting sequences increased, and the stock of billets decreased drastically while the internal quality of the rolled bars remained the same.
Keywords: billet cooling, continuous casting, ultrasonic testing, logistic regression, genetic programming, industrial study, steel making, optimization
Published in DKUM: 25.11.2024; Views: 0; Downloads: 9
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7. Factors affecting attitudes towards COVID-19 vaccination : an online survey in SloveniaLuka Petravić, Rok Arh, Tina Gabrovec, Lucija Jazbec, Nika Rupčić, Nina Starešinič, Lea Zorman, Ajda Pretnar Žagar, Andrej Srakar, Matjaž Zwitter, Ana Slavec, 2021, original scientific article Abstract: While the problem of vaccine hesitancy is not new, it has become more pronounced with the new COVID-19 vaccines and represents an obstacle to resolving the crisis. Even people who would usually trust vaccines and experts now prefer to wait for more information. A cross-sectional online survey was conducted in Slovenia in December 2020 to find out the attitudes of the population regarding COVID-19 vaccination and the factors that affect these attitudes. Based on 12,042 fully completed questionnaires, we find that higher intention to get vaccinated is associated with men, older respondents, physicians and medical students, respondents who got the influenza vaccination, those who knew someone who had gotten hospitalised or died from COVID-19 and those who have more trust in experts, institutions and vaccines. Nurses and technicians were less likely to get vaccinated. In answers to an open question, sceptics were split into those doubting the quality due to the rapid development of the vaccine and those that reported personal experiences with side effects of prior vaccinations. Although the Slovenian population is diverse in its attitudes towards vaccination, the results are comparable to those found in other countries. However, there are potential limitations to the generalizability of the findings that should be addressed in future studies.
Keywords: cross-sectional studies, intention, public opinion, trust, ordinal regression, COVID-19, vaccination, surveys and questionnaires, Europe, immune system, SARS-CoV-2
Published in DKUM: 10.10.2024; Views: 0; Downloads: 10
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8. Associations between physical activity and academic competence : a cross-sectional study among Slovenian primary school studentsJoca Zurc, Jurij Planinšec, 2022, original scientific article Abstract: Physical activity has beneficial effects on overall academic performance in children. However, there is a lack of evidence regarding how the individual characteristics of physical activity interact with other confounding variables of academic competence. Leisure-time physical activity with potential confounders—such as developmental, behavioral, family, and school factors, predicting overall, mathematical, and reading academic competence—was studied in a random sample of 1520 Slovenian primary school students in grades 4–6 (51.9% female; mean age = 10.4 years; SD = 0.93). A structured self-reported questionnaire was used to gather data on the children’s leisuretime physical activity and social-demographic variables, while academic competence was measured by teachers using the SSRS Academic Competence Evaluation Scale. The findings showed that children engage in physical activity most days a week, with moderate-intensity and unorganized activities. It was predicted that engaging in physical activity would lead to an increase in academic performance by 4.2% in males (p = 0.002) and 3.2% in females (p = 0.024), but after fully adjusting the model for controlling confounding variables, the prediction increased to 81.1% in females and 84.1% in males (p < 0.001). The frequency and intensity of physical activity, the absence of digital games, and attending sports clubs seem to have the most beneficial effects in terms of academic competence in school children, among other relevant confounders mediating in this complex relationship.
Keywords: physical activity, leisure time, sports, academic competences, late childhood, multiple regression analyses
Published in DKUM: 12.07.2024; Views: 94; Downloads: 15
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9. Materials for HybridNeuro webinar titled "Validation of results: statistical models and MU identification accuracy"Aleš Holobar, Nina Murks, 2024, complete scientific database of research data Abstract: This dataset contains a collection of teaching materials that were used in the HybridNeuro project webinar titled "Validation of results: statistical models and MU identification accuracy". The webinar was presented by Aleš Holobar and covered the complexities of motor unit (MU) identification accuracy, regression analysis and Bayesian models. The primary aim of the webinar was to spark a robust discussion within the scientific community, particularly focusing on the application and implications of linear mixed models and Bayesian regression in the realm of MU identification. The teaching materials include Matlab and R source code for statistical analysis of the included data, as well as three examples of MU identification results in CSV format (from both synthetic and experimental HDEMG signals). The presentation slides in PDF format are also included. The dataset is approximately 9 MB in size.
Keywords: HybridNeuro, webinar, teaching materials, statistical models, regression analysis, motor unit identification, matlab, rstudio, statistics, surface high density electromyogram (HDEMG), tibialis anterior, dataset
Published in DKUM: 30.05.2024; Views: 221; Downloads: 25
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10. Elderly pedestrians and road safety: Findings from the Slovenian accident database and measures for improving their safetyStanko Laković, Tomaž Tollazzi, Chiara Gruden, 2023, original scientific article Keywords: elderly pedestrians, road safety, regression model, human abilities, crash data, countermeasures, sustainable transportation
Published in DKUM: 15.04.2024; Views: 258; Downloads: 50
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