Branislav Madoš

The paper deals with the problematics of representation of the geometry of three-dimensional scenes in computer graphics using domain-specific hierarchical data structures based on octant trees or directed acyclic graphs as the means of space saving binary representation of this information. Several hierarchical data structures were introduced in this field in past decades. In this paper we are moving this problematic to the field of the representation of three-dimensional scenes which are rather dynamic in time, so their geometry is changing on the regular basis. We are investigating the influence of this time-variability on the size of the related hierarchical data structure on binary level. We are comparing the approach in which each time step is considered as the stand-alone static three-dimensional scene and therefore is represented by its own hierarchical data structure with the approach when this time-variable scene is considered as the four dimensional space and spatio-temporal sparse voxel octree hierarchical data structure is used for the representation of the geometry of this scene. We tested both approaches on three different scenes which were obtained by voxelization into two different resolutions of polygonal surface models represented originally as the mesh of triangles in Wavefront Object file format. Results of the tests show that spatio-temporal sparse voxel octree is better solution, when we obtained from 1.73 to 2.08 more compact binary representation, in comparison to the solution when time frames were encoded separately as the set of sparse voxel octrees.

This paper focuses on training machine learning models using the XGBoost and extremely randomized trees algorithms on two datasets obtained using static and dynamic analysis of real malicious and benign samples. We then compare their success rates—both mutually and with other algorithms, such as the random forest, the decision tree, the support vector machine, and the naïve Bayes algorithms, which we compared in our previous work on the same datasets. The best performing classification models, using the XGBoost algorithm, achieved 91.9% detection accuracy and 98.2% sensitivity, 0.853 AUC, and 0.949 F1 score on the static analysis dataset, and 96.4% accuracy and 98.5% sensitivity, 0.940 AUC, and 0.977 F1 score on the dynamic analysis dataset. Then, we exported the best performing machine learning models and used them in our proposed MLMD program, automating the process of static and dynamic analysis and allowing the trained models to be used for classification on new samples.

Steganography is considered to be the science and the art of hidden communication through an open communication channel or hiding information using innocent and harmless-looking media. It has been evolving for centuries, but as in many areas of human activity, its new possibilities and effectiveness have been brought about by the development of information and communication technologies. These have not only become a means of simplifying and speeding up the implementation of operations enabling the hiding of information in stegomedia and dynamizing the transmission of such modified media, but they have also brought with them specific types of stegomedia and information hiding algorithms. They are so closely related to information and communication technologies that without their existence the meaning of those algorithms and stegomedia will be lost. They use specific data structures, file formats, communication protocols, etc. and are even adapted to the design of the hardware and related firmware. The following paper is devoted to this area, dealing with hiding information in the domain-specific hierarchical data structure Symmetry-aware Sparse Voxel Directed Acyclic Graphs. It is designed for lossless-compressed representation of voxelized three-dimensional scenes in the field of computer graphics. The paper deals with a brief description of this data structure and proposes a new steganographic algorithm. The algorithm allows information to be hidden through specific features of this data structure using its three-dimensional voxel grids.

This paper reports on an investigation which is part of a comprehensive project aimed at investigating translators’ work-related happiness in various contexts, a subject largely under-researched in contemporary translation studies. The purpose of this pilot cohort study is to determine the perceptions of happiness in two presumably high-profile groups of translators—Slovak sworn translators and Slovak EU translators. To accomplish the aim, comparative and causal perspectives are used. The quantitative analysis, comprising descriptive and correlation analysis, involves data from questionnaires completed by a total of 115 translators belonging to the two groups (83 + 32). The respondents’ perceptions of their work-related happiness are examined and compared, based on their responses to questions revolving primarily around social status variables and parameters of occupational prestige. Based on the gained data, seven hypotheses are tested with quantitative research methods employing contingency tables. Although our findings largely do not corroborate the hypotheses and lead to the identification of crucial differences between the two groups, the analyses also allow us to identify some commonalities. The results of the quantitative analysis are discussed in detail.

The paper describes Computer Aided Software Engineering (CASE) tool, that supports programming of the experimental multi-core tile based System-on-a-Chip (SoC). SoC comprises cores, which are based on the data flow computation control principle. Proposed CASE tool allows creation of the program code in graphical form using Data Flow Graph (DFG) or in text representation using assembly language or machine code. Automatic transformations between those representations are supported. CASE tool brings sequential, mask based and global multi-mapping of the program code, which was introduced in our previous research. Another output lies in introduction of altered assembly language and machine code that allow multi-mapping of the program code on the instructions level. The aim of the solution lies in optimization of the program load phase in multi-core microprocessors that comprise tens or potentially hundreds of cores.