Iskanje po katalogu digitalne knjižnice

Opis: This paper proposes a model for creating a vector profile graph in ArcGIS Pro based on AllTrails tracking. The vector profile graph is important for route’s geometric measurements and spatial analysis in GIS. The model was created in an Excel table, based on the AllTrails output Excel data, and implemented in ArcGIS Pro. A model needed to be equipped with several attributes, including the coordinates of the initial and all other points of the vector profile graph. The same Excel model was also used to create a vector profile graph based on the output of the Stack Profile tool. The two vector profile graphs were compared with each other. Comparison showed significant differences in elevation and surface distance between them. In general, the profile graph created using the Stack Profile tool shows lower elevations and shorter surface distance. This study also points out the issues of positional error that can occur when tracking routes with smartphones, and the discrepancies in creating vector profile graphs using different approaches.
Ključne besede: vector profile graph, hiking route, distance, elevation, AllTrails
Objavljeno v DKUM: 26.03.2025; Ogledov: 0; Prenosov: 3
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Opis: Data compression algorithms tend to reduce information entropy, which is crucial, especially in the case of images, as they are data intensive. In this regard, lossless image data compression is especially challenging. Many popular lossless compression methods incorporate predictions and various types of pixel transformations, in order to reduce the information entropy of an image. In this paper, a block optimisation programming framework is introduced to support various experiments on raster images, divided into blocks of pixels. Eleven methods were implemented within , including prediction methods, string transformation methods, and inverse distance weighting, as a representative of interpolation methods. Thirty-two different greyscale raster images with varying resolutions and contents were used in the experiments. It was shown that reduces information entropy better than the popular JPEG LS and CALIC predictors. The additional information associated with each block in is then evaluated. It was confirmed that, despite this additional cost, the estimated size in bytes is smaller in comparison to the sizes achieved by the JPEG LS and CALIC predictors.
Ključne besede: computer science, information entropy, prediction, inverse distance transform, string transformations
Objavljeno v DKUM: 07.01.2025; Ogledov: 0; Prenosov: 9
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Opis: The COVID-19 pandemic has led to the introduction of unprecedented safety measures, one of them being physical distancing recommendations. Here, we assessed whether the pandemic has led to long-term effects on two important physical distancing aspects, namely interpersonal distance preferences and interpersonal touch behaviors. We analyzed nearly 14,000 individual cases from two large, cross-cultural surveys – the first conducted 2 years prior to the pandemic and the second during a relatively stable period of a decreased infection rate in May-June 2021. Preferred interpersonal distances increased by 54% globally during the COVID-19 pandemic. This increase was observable across all types of relationships, all countries, and was more pronounced in individuals with higher self-reported vulnerability to diseases. Unexpectedly, participants reported a higher incidence of interpersonal touch behaviors during than before the pandemic. We discuss our results in the context of prosocial and self-protection motivations that potentially promote different social behaviors.
Ključne besede: neverbalna komunikacija, preference glede medosebne razdalje, medosebni dotiki, pandemija, kovid, COVID-19, fizična distanca, medkulturna psihologija, coronavirus, nonverbal communication, interpersonal distance preferences, interpersonal touch behaviour, cross-cultural psychology, physical distancing
Objavljeno v DKUM: 02.08.2024; Ogledov: 89; Prenosov: 7
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Opis: Because of the Coronavirus Disease 2019 (COVID-19) outbreak, most universities were forced to choose Online Distance Learning (ODL). The study aimed to examine the response of university students to the new situation. A questionnaire was sent to the entire university student population. Based on responses from 606 students, it was revealed that use of all applications in ODL increased. However, only the use of MS Teams increased significantly, while the use of the other applications (email, Moodle, e-textbooks) increased in a range of low to medium in terms of effect sizes, and even nonsignificant for applications such as Padlet and Kahoot. Based on the replies of 414 respondents, a Model of Forced Distance Online Learning Preferences (MoFDOLP) based on Structural Equation Modeling was developed. With a chosen combination of predictors, we succeeded in predicting 95% of variance for Satisfaction, more than 50% for Continuance Preferences variance in MS Teams applications, and nearly 20% in the case of e-materials. Among hypothesized constructs, only Attitudes are a strong predictor of Satisfaction, while Organizational Support, Perceived Ease of Use and Learner Attitude toward Online Learning are not. Satisfaction is a good predictor of Continuance Preferences to use Information Technology after the lockdown ended.
Ključne besede: higher education, online distance learning, continuance preferences, COVID-19
Objavljeno v DKUM: 30.05.2024; Ogledov: 111; Prenosov: 19
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Opis: Amidst the COVID-19 pandemic, university students and teachers had to adapt to distance learning during the closures. To better understand the student experience during the second closure, a study was conducted at the University of Maribor, Slovenia. The study aimed to analyze the views and experiences of 244 prospective primary and secondary teachers from three faculties. The study found that students had a higher workload during the closure, resulting in a preference for synchronous forms of online education over asynchronous ones. Despite this, students generally had positive experiences with their teachers, except for lack of spontaneous discussions. They also missed the social interactions with their classmates, which highlights the importance of the social dimension of education. Additionally, students were expected to participate in domestic activities, which could have mixed impacts on their educational outcomes. In summary, the student experiences with online distance learning were mixed, positively impacting quality of life but not necessarily on the quality of schooling. The findings can serve as a guide for organizing study programs or courses for prospective teachers in online distance education.
Ključne besede: forced online distance education, prospective teachers, teacher education, university closure
Objavljeno v DKUM: 08.05.2024; Ogledov: 185; Prenosov: 4
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