http://hdl.handle.net/20.500.14044/33879 Tue, 21 Jul 2026 07:04:32 GMT 2026-07-21T07:04:32Z http://hdl.handle.net/20.500.14044/32350 Big Data Deduplication in Data Lake Hlavačka, Jakub; Bobák, Martin; Hluchý, Ladislav Data lakes are the next generation of technology to process and store big data. As usual, new challenges and problems arise inevitably with new technologies. One of these problems is the occurrence of duplicate data in the storage. Our paper aims to address this challenge during the data ingestion phase that is currently overlooked or addressed insufficiently. The first part discusses the design of a suitable architecture for the data lake and deduplication workflow for processing structured and unstructured data. The proposed solution is evaluated through experiments that deal with the flexible deduplication window, the scalability of the proposed solution, the suitable hash function, and the advantages of an in-memory pointer repository. Mon, 01 Jan 2024 00:00:00 GMT http://hdl.handle.net/20.500.14044/32350 2024-01-01T00:00:00Z http://hdl.handle.net/20.500.14044/32349 Model-Free Nonsingular Fast Terminal Sliding Mode Control of a Permanent Magnet Synchronous Motor Hagras, Ashraf Abdalla; Azab, Ayman; Zaid, Sherif This paper proposes a new algorithm for Model-Free Control (MFC) combined with an improved Nonsingular Fast Terminal Sliding Mode Control (NFTSMC) technique for current control of a Permanent Magnet Synchronous Motor (PMSM). This new improved NFTSMC technique adds more advantages to the conventional terminal sliding mode control theory to enhance transient and steady state performance. The proposed new improved NFTSMC bridged over the traditional difficulties of Terminal Sliding Mode Control (TSMC) theory, like the limited values of its constraints and its state differentiation and avoids the complexity of its following versions. The MFC was based on the Radial Basis Function Neural Network (RBF NN) which doesn’t require known bounds of uncertainty. The stability of the proposed method was analyzed using Lypunov stability theory. Therefore, this technique was compared with Model Free Fractional Order Sliding Mode Control (MFFOSMC) [11] using MATLAB/SIMULINK in a vector control scheme to validate its design and show its faster torque and speed response, as well as its strong robust performance against varying parameters and external load disturbances. Mon, 01 Jan 2024 00:00:00 GMT http://hdl.handle.net/20.500.14044/32349 2024-01-01T00:00:00Z http://hdl.handle.net/20.500.14044/32348 One Aspect of Environmental Engineering – Modelling the Air Pollution Effects using Advection-Diffusion Stojičić, Snežana; Cisar, Petar; Radovanović, Radovan; Petrović, Nataša; Blagojević, Milan; Srećković, Milesa; Pamučar, Dragan This paper aims to contribute to the development of appropriate and sustainable solutions that enhance response readiness and facilitate the identification, processing, investigation and reporting of fire and explosion incidents. Additionally, it seeks to address the overall reduction and control of pollution levels. From this perspective, the elements and cases of pollutant emission factors are analysed concerning spatial distribution, mechanisms and elimination time. The concentration of air pollutants can be described by the advection- diffusion equation, a second-order partial differential equation (PDE). This approach exemplifies an interdisciplinary method, taking into account the atmospheric boundary layer, including wind limitations, daily temperature variations and the presence of eddies. To analyse the analytical and numerical solutions to the diffusion equation, a two- dimensional, time-independent case with a continuous terrestrial line source of pollutants was selected. The results, obtained using freely chosen parameters and appropriate boundary conditions determined according to literature sources, are presented in both code and graphical form. Modeling is recognized as an important complementary tool and can be applied to both short-term and long-term planning. In particular, this study investigates the potential of a numerical scheme for modeling advection, using the analytical solution as a reference within defined boundary conditions. This approach demonstrates its applicability in tracking diffusion processes caused by accidents or natural events, where air pollutants disperse from one area to another over time. Mon, 01 Jan 2024 00:00:00 GMT http://hdl.handle.net/20.500.14044/32348 2024-01-01T00:00:00Z http://hdl.handle.net/20.500.14044/32347 Time Evolution Model for Analysing Malicious Samples Leitold, Ferenc In this paper, the results of the practical examination of the Time Evolution Model ([1] [2] [3]) used to categorize malicious samples are summarized. This method provides effective assistance in anti-malware testing procedures as well as cyberattack detection. With its help, the typical properties of malicious codes can be determined more easily and quickly with automatic tools. The Time Evolution Model can help security experts better understand the behavior of malicious attacks and malware families. The Time Evolution Model works based on variables describing changes in the detection capabilities of different protection systems related to a specific malicious file. An exponential curve fitting method is used to estimate the main characteristics of the spread of the malicious code. During the curve fitting, three parameters are determined, with the help of which the properties of the spread of a malware or a malware family can be identified more precisely. In the case of malicious program families, the aggregation of these parameters can be an effective solution for estimating cyberthreat trends. The Time Evolution Model was tested on a large number (more than 1000) of malicious samples, based on which different groups can be distinguished according to when the investigation starts after the first appearance of the malicious code. Mon, 01 Jan 2024 00:00:00 GMT http://hdl.handle.net/20.500.14044/32347 2024-01-01T00:00:00Z