Iskanje po katalogu digitalne knjižnice

Opis: 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).
Ključne besede: international energy security risk index, analysis, stepwise regression, principal component analysis, Promax oblique rotation
Objavljeno v DKUM: 04.02.2025; Ogledov: 0; Prenosov: 6
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Opis: 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.
Ključne besede: plastic use, plastic waste, end-of-life fate, forecasting, hostorical trends, regression analysis, least square method, intervention analysis
Objavljeno v DKUM: 31.01.2025; Ogledov: 0; Prenosov: 2
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Opis: 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.
Ključne besede: HybridNeuro, webinar, teaching materials, statistical models, regression analysis, motor unit identification, matlab, rstudio, statistics, surface high density electromyogram (HDEMG), tibialis anterior, dataset
Objavljeno v DKUM: 30.05.2024; Ogledov: 221; Prenosov: 23
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Opis: Owing to its advantages such as producing durable models and easy accessibility, 3D modeling and printing (3DMP) has become increasingly popular in educational practice and research. However, the results of many studies have shown that the adoption rate of 3DMP among teachers is still low, especially in elementary schools. Therefore, research is needed to expand current knowledge about what influences teachers' decisions to start and continue using 3DMP in elementary schools. To investigate factors that affect elementary school teachers' decisions to use 3D printing in teaching, this study uses a mixed methods research approach combining binary logistic regression with a qualitative thematic analysis approach. Both approaches assembled predictive constructs from a range of theories on (1) technology acceptance and (2) intentions to continue or abandon 3DMP use. Using a sample of 225 elementary teachers from Montenegro, this study empirically concluded that intentions to discontinue 3DMP was slightly more strongly correlated with the predictors (i.e., performance expectancy, effort expectancy, perceived pedagogical impact, personal innovativeness, management support, user interface quality, technology compatibility, social influence, student expectations) than was intentions to continue using 3DMP. Performance expectancy was a significant determinant of teachers’ continued use of a 3DMP approach. The remaining seven factors (constructs) were found to be insignificant predictors. Perceived pedagogical impact and technology compatibility were significantly associated with teachers' decisions to discontinue using 3DMP. Our results also suggest that the time required to use 3DMP during instruction, the impact of 3DMP on the implementation of curriculum activities, and the availability of 3D printers are all relevant factors that influence teachers’' decision to use or abandon 3DMP.
Ključne besede: elementary school, binary logistic regression, continuance intentions, thematic analysis approach, 3D modelling and printing
Objavljeno v DKUM: 26.03.2024; Ogledov: 268; Prenosov: 205
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Opis: The aim of this paper is to analyse the influence of the development level indicators on the e-commerce, i.e. on the online purchase by individuals, in selected European countries in 2013. In the analysis, the main variable under study and all the independent variables are included as standardised. Based on nine variables, the principal component analysis with varimax rotation was performed and the two extracted factors were used as the regressors in the multiple regression analysis. In the regression model both components, Factor 1, which includes seven variables, called Prosperity, Investing in Education and IT Infrastructure, and Awareness, and Factor 2, comprised of two variables, called IT Skills, are statistically significant at the significance level of 1%. Both factors show a positive correlation with the online purchase of individuals. Inclusion and analysis of distributions and impacts of even nine independent variables, which make up two distinct factors affecting the e-commerce, make a new contribution of this work.
Ključne besede: e-commerce, broadband access to the Internet, factor analysis, multiple regression analysis
Objavljeno v DKUM: 10.10.2018; Ogledov: 1313; Prenosov: 381
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