The paper presents a spectrophotometric study of the binary system Rh(III)-2-thioxo-4-thiazolidinone. The formation conditions and the analytical application of the formed complex for spectrophotometric determination of Rh(III) were studied. The composition of the Rh(III) chelate with this particular ligand was determined by the continuous variation method, its instability constant being Kinst = 1,61·10-8 mol2L-2.

The synthesis and the properties of square-planar [Au-S 4]Z and [Au-O2S2] Z – type complex compounds, involved in electron-transfer reactions, are presented. The complexes obtained are characterized by elemental analysis, IR, visible, UV, ESR spectroscopy, conductivity, and polarographic data.

Logistics automation has been the subject of many developments linking robotic hardware with improved quality and safety of work for warehouse employees. It is also a field where robotic navigation, route optimization and precise maneuvering are crucial to the competitiveness of the engineering product on the market. This research demonstrates a mathematical modeling method through which robots can navigate warehouse floors efficiently, using indoor positioning of high accuracy. Moreover, the paper also describes the hardware considerations taken into account when measuring the accuracy of the robot from achieving its destination on the floor plan. A prototype is creating, showing the sensor fusion interlinks for obstacle avoidance and distance mapping. Finally, the prototype and the algorithm are tested against eight static, as well as dynamic performance tests, in order to validate the performance of the system in static and dynamic interference environments. The goal of this paper is to present the engineering perspectives of optimizing a self-driving warehouse robot through utilization of the emerging technologies related to indoor positioning. This is presented through a prototype development of an Automated Guided Vehicle which will perform indoor positioning of itself across a warehouse floor plan and be able to avoid obstacles while driving towards its destination. Both the hardware description and the algorithmic modeling will be presented, accompanied by an extensive set of testing experiments, presented to determine the feasibility of our proposed developments in this field.

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The great necessity of realizing appropriate monitoring of cooling and heating systems seems to be essential in the current context, as we approach the reality of interconnected smart cities and vehicles, which can regulate their energy consumption and, at the same time, maintain high standards on the equilibrium that they provide. This work outlines the essential technical considerations when modeling a working device prototype designed for monitoring of temperature inside vehicles and other areas. The main focus of this paper is to present and explain the algorithm that has been developed throughout three months of intensive prototyping of such a system. The scope of our final prototype includes an automatic alarm function for extreme cases, along with visual feedback in the form of messages on an LCD screen and color-coded LED signals. There is a specific focus regarding the collection and processing of accurate data for vehicles, with the consequence of releasing appropriate warnings to drivers or system owners. The main research focus is on explainability and reproducibility of our decisions behind the programming approach. Finally, we have demonstrated the means through which the mentioned solution is adaptable and cost-efficient, together with short considerations that would take the prototype into mass production.