L86 - Information and Internet Services; Computer SoftwareReturn

The use of Virtual Reality (VR) to visualize data is increasingly common in various fields, from medical science to education. However, visualization of geospatial data in VR is still not handled well. GIS data comes in various formats and converting them to 3D can be challenging. The choice of a format capable of streaming large amounts of spatial data in the VR scene is crucial. However, the challenge lies in ensuring the reusability of the presented scenes with different GIS data. Most applications (including the 3D scene models) are created for a single use case and do not allow for simple interchangeability of presented data. This article proposes a reusable architecture of a general-purpose web service for processing and visualizing spatial data in VR using 3D Tiles as the chosen format. The goal of the architecture is to allow fast VR scene generation from GIS data. The critical aspect is the conversion of standard GIS format to 3D Tiles. Several conversion tools were tested and compared using publicly available point and polygon feature layers in order to choose which can be used in the proposed architecture.

In this paper, we focus on the categorization of tickets in service desk systems. We employ modern neural network-based artificial intelligence methods to improve the performance of current systems and address typical problems in the domain. Special attention is paid to balancing the ticket categories, selecting a suitable representation of text data, and choosing a classification model. Based on experiments with two real-world datasets, we conclude that text preprocessing, balancing the ticket categories, and using the representations of texts based on fine-tuned transformers are crucial for building successful classifiers in this domain. Although we could not directly compare our work to other research the results demonstrate superior performance to similar works.

Technostress as an academic domain has evolved significantly since year 1984. Based on the systematic literature review (SLR), eight determinants of technostress were identified which were classified into individual and organizational categories. Individual determinants were further divided into demographic, psychographic and cognitive categories. Outcome of the SLR was the development of a comprehensive framework of technostress. This study can facilitate the top management and the HR managers of organizations to adopt appropriate change management interventions while implementing and augmenting new technologies.

Web anonymization tools have been used for a long time, primarily by the users afraid of possible undesirable consequences of their on-line activity on the web. The paper analyzes both historically proven anonymization tools like TOR and newer tools, namely JAP/JonDo and CyberGhost VPN that are based on slightly modified technological principles. The primary focus is given to the measurement and evaluation of the latency increase and the transmission speed decrease in comparison to normal (non-anonymized) web browser operation. Results show that all anonymization tools being subject of the analysis provide relatively moderate latency increase. On the opposite, the transmission speed decrease was more significant, especially for JonDo. This confirms the conclusions of previous studies resulting that no anonymization tool is suitable for daily web browsing. On the other hand, in the case when higher anonymity is required, their use can be reasonably comfortable from the point of view of latency increase. However, their usefulness for downloading larger files is always disputable.

This contribution is focused on the use of the stereoscopic image for the purpose of depth map creation. Further, methods for calibration of the camera(s) are discussed. A stereoscopic head was constructed for the purpose of creating a stereoscopic image. Two Basler acA1600-20uc industrial cameras with Computar M2514-MP2 lenses were used for constructing this head. Furthermore, the algorithm for obtaining the depth map is described. The programming language C# and EmguCV library were used for the implementation of the algorithm. The algorithm consists of 4 parts. The calibration of the camera(s) and image acquisition is solved as first. Calibration of the camera(s) is solved by detection of intersections on the chessboard. Further, methods for the purpose of obtaining the depth map are described. Finally the implemented algorithm is tested.