The Annals of “Dunarea de Jos“ University of Galati. Fascicle III, Electrotechnics, Electronics, Automatic Control, Informatics

ANALYSIS AND SIMULATION IN SIMULINK/MATLAB OF A THREE-PHASE ACTIVE POWER FILTER

George Marin — 2024-03-04

In this article, the authors present the analysis and simulation process in the Simulink/MATLAB environment for a three-phase active power filter. Active power filters are used in power distribution systems to compensate for voltage and current disturbances. The Simulink model reproduces the key components of the filter, and simulations allow evaluation of its performance. The aim is to optimize the parameters and the control algorithm, thus ensuring a superior quality of the supplied electricity. This approach contributes to the development of more efficient and reliable electrical power distribution systems by providing a deeper understanding of the behavior and performance of the three-phase active power filter.

GREEN HYDROGEN – THE FUEL OF THE FUTURE. OVERVIEW

Nicolae Badea — 2024-03-04

Due to the increasing demand in energy consumption a need for a new fuel has risen, a fuel that doesn’t add to the greenhouse effect. A new emerging trend in agreement with the green initiative that has begun is hydrogen. Hydrogen is primarily obtained using fossil fuel, natural gas and coal. However, there is a green method, electrolysis can produce hydrogen from water by using electricity, thus by using renewable power supplies like photovoltaic panels and/ or wind turbines, “green hydrogen” can be obtained. Storing the energy of the sun and wind in hydrogen production provides the versatility needed for the renewable power supply field. A case study on green hydrogen production and utilization like the Galati Hydrogen Valley is an example that explains the exploring of new methods for obtaining green hydrogen, focusing on water electrolysis.

ARTIFICIAL INTELLIGENCE FOR CRIME PREDICTION AND PREVENTION – A LITERATURE REVIEW

Paul Iacobescu — 2024-03-04

Crime prevention is a key concern in modern society, with significant implications for public safety and informed law enforcement decision-making. An innovative approach in this direction is the use of Artificial Intelligence (AI) to analyze statistical data on crime history. This paper explores the current state of the art of using AI in crime assessment and prevention, presenting current methods, and techniques, such as Machine Learning and Deep Learning, which are applied to identify crime patterns and trends. Throughout the analysis, the advantages, and challenges of using AI in this context are discussed and relevant case studies are highlighted where AI has had a significant impact in reducing crime. Finally, it outlines emerging research directions, including improving crime prediction algorithms and applications integrating data from various sources and developing robust mechanisms for evaluating the performance of AI models. By exploring these issues, the paper provides a broad perspective on the current state and future directions for crime prevention using Artificial Intelligence.

DYNAMIC BACKTRACKING FOR ABSTRACT ARGUMENTATION SYSTEMS

Sabina Costache — 2024-03-04

Abstract Argumentation Frameworks (AFs) are a major formalism for practical reasoning, to be used in non-monotonical reasoning of intelligent agents. The paper presents some of the latest researches in the field of efficient computation for different semantics of abstract argumentation systems. An algorithm with backtracking with look-ahead and different heuristics is taken as a basis, to be further developed and to experiment new backtracking -based optimizations in the field of AF, and an adaptation of dynamic backtracking for the same field is shaped for further experiments and improvements.