The main objectives of the research thesis are the design, simulation, and analysis of a FPGA controlled GaN based 3-phase grid-tied inverters in terms of efficiency and performance. High frequency switching applications ...

When battery storage system incorporate into modern power system began a critical answer to problems such as voltage instability, energy imbalances, and the increasing use of renewable energy. This thesis investigates ...

The actual electric power structure of Azerenerji relies only on Conventional Current Transformer (CCT), and this gives a very great chance to start assessing new technologies that could improve the performance of measurement ...

Integrating renewable energy sources into the modern grid has been challenging in terms of maintaining grid stability and quality. Changes in renewable energy production and fluctuating load demands have brought innovative ...

This research endeavors to evaluate and compare High Voltage Direct Current (HVDC) implementation strategies for augmenting power transmission within Azerbaijan. The study delves into the efficacy of HVDC technology ...

In this thesis, we have investigated the challenges of building multimodal vision-language models for image retrieval tasks in a low-resource languages, particularly in Azerbaijani. Due to the multiple reasons this task ...

When mobile banks have supported mobile phone technology, the sector of the financial services has undergone revolutionary transformations that now provide alternative options to the customers for their affairs related to ...

The thesis proposes a design and practical implementation of a database system that is made for holding and managing the descriptive data derived from various repositories. The driver of this project is the goal of giving ...

In the Brain-Computer Interface (BCI) field, applying deep learning to interpret neural data for Electroencephalogram (EEG) based gaze prediction is challenging due to complexity of EEG data. This study focuses on a hybrid ...

This study was conducted with the primary focus of exploring the potential of smallscale Large Language Models (LLMs) to handle causal reasoning tasks through two primary interventions, namely, dataset augmentation and ...