The popularity of railway transportation has been on the rise over the past decades, as it has been able to provide safe, reliable, and highly available service. The main challenge within this domain is to reduce the costs of preventive maintenance and improve operational efficiency. To tackle these challenges, one needs to investigate and provide new approaches to enable quick and timely data collection, transfer, and storage aiming at easier and faster analysis whenever needed. In this thesis, we aim at enabling the monitoring and analysis of collected signal data from a train propulsion system. The main idea is to monitor and analyze collected signal data gathered during the regular operation of the propulsion control unit or data recorded during the regular train tests in the real-time simulator. To do so, we have implemented a solution to enable train signal data collection and its storage into a .txt and .CSV file to be further analyzed in the edge node and in the future connected to the cloud for further analysis purposes. In our analysis, we focus on identifying signal anomalies and predicting potential failures using MathWorks tools. Two machine learning techniques, unsupervised and supervised learning, are implemented. Additionally, in this thesis, we have investigated ways of how data can be efficiently managed. We have also reviewed existing edge computing solutions and anomaly detection approaches using a survey as a suitable method to identify relevant works within the state of the art.

This paper presents the author Rhonda Byrne and her works in the context of the role of human thoughts in the daily life. Special attention is paid to her work The Secret as it represents the foundation which makes it possible to construct her teaching from. Also, this paper explores the reception of The Secret in the former Yugoslav countries.

The aim of this research was to examine physicochemical parameters of finished and semi-finished meat products: minced meat (beef, pork and mixed meat) and raw formed meat products (ćevapi, patties/burgers and sujuk sausages), and to determine quality parameters of these products on the Bosnia and Herzegovina market. Examined parameters included: protein content, fat, collagen in meat proteins and salt (NaCl). We analysed 282 samples of these products and found deviations with regard to the applicable Ordinance on minced meat and semi-finished and finished meat products of “The Law on Food of Bosnia and Herzegovina” in all parameters, except salt (NaCl). The majority of deviations referred to the content of collagen in meat proteins, with as much as 21.98 % of examined samples in violation of the applicable legislation.

Abstract Simultaneous adsorption of heavy metals in complex multi metal system is insufficiently explored. This research gives results of key process parameters optimization for simultaneous removal of Cd(II), Co(II), Cr(III), Cu(II), Mn(II), Ni(II) and Pb(II) from aqueous solution (batch system). New lemon peel-based biomaterial was prepared and characterized by infrared spectroscopy with Fourier transformation (FTIR), scanning electron microscopy (SEM), electron dispersive spectroscopy (EDS), while the quantification of metals was made by atomic absorption spectrometry (AAS). Simultaneous removal of seven metals ions was favorable at pH 5 with 300 mg/50 mL solid-liquid phase ratio, within 60 min at room temperature with total obtained adsorption capacity of 46.77 mg g−1. Kinetic modeling showed that pseudo-second order kinetic and Weber-Morris diffusion models best describe the adsorption mechanism of all seven heavy metals onto lemon peel.