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Artificial intelligence (AI) is rapidly penetrating all forms of digitised systems and services, including organisational, social, economic, and governmental, revolutionising the way information is processed, and decisions are made. The integration of AI in socially relevant areas is increasingly essential due to the growing use of digital services and the extensive, fragmented information spread across platforms. The lack of a unified approach to processing this data creates challenges in accessibility, reliabili...

This article focuses on the effectiveness and robustness of facial classification systems in the field of biometric identification. Artificial intelligence is increasingly becoming a part of everyday life, with more and more users employing it across various domains. In the field of security, AI is used, for instance, in cybersecurity and risk analysis. It is also integrated into surveillance systems, particularly for facial recognition. A comparative analysis of three convolutional neural networks-GoogLeNet, ResN...

Data collection and storage are crucial in the development of artificial intelligence (AI) within the socially relevant areas. Despite the increasing volume of information, it is often scattered across various sources, formats, and platforms, making effective analysis and application challenging. The lack of a unified framework for data integration further complicates efforts to leverage AI for informed decision-making, policy formulation, and public service optimisation. This article proposes a structured methodo...

The recent advances in machine learning led to exponential improvement in the field of artificial intelligence and large language models (LLMs). For university study and university students, LLMs can offer opportunities in several areas. But on the other hand, output from LLMs should be handled using critical thinking. In our research, we wanted to investigate the level of awareness of publicly available LLMs among the bachelor and master students (n=22) of Landscape Engineering program at the Slovak University of...

Accurate solar power forecasting is essential for grid stability and efficiency. Precise generation forecasts help balance electricity supply and demand, prevent overloads, and support renewable energy integration. It enables to optimize bidding strategies and reduce penalties for imbalanced production. This study presents a solar power forecasting approach that integrates deterministic models with machine learning. The system utilizes the pvlip Python library for deterministic calculations. XGBoost-based machine ...

Wind and solar energy have become increasingly viable sources of clean, sustainable power, enabling more infrastructure to operate independently of traditional energy grids. To assess the reliability of these energy sources, it is essential to evaluate how regional climate conditions influence the generation potential of renewable energy. Since wind and solar power generation is inherently irregular, analyzing both fluctuations and regional variations is crucial for making optimal decisions that ensure the continu...

Agroecology, which merges ecological principles with agricultural practices, offers a pathway to food security while ensuring environmental sustainability. However, its implementation faces challenges stemming from ineffective ecological resource monitoring, predetermined climate conditions, and insufficient real-time data for precision farming and well-informed decision-making. The aimed first, to develop models that monitor soil health and predict crop yields under different agroecological conditions powered by ...

Ultrasound diagnostics is a key tool in the investigation of renal diseases in pediatric patients due to its non-invasiveness and accessibility. Although it offers many advantages. Its accuracy in detecting functional pathological changes is investigated in this article. This pilot study included 17 children aged 1 to 18 years who underwent renal ultrasound examination followed by scintigraphy examination in a nuclear medicine clinic. Renal ultrasound images were analyzed using the digital B-MODE Assist system. wh...

This paper presents a multidisciplinary approach to analyzing data from Telegram for early warning information regarding cyber threats. With the proliferation of hacktivist groups utilizing Telegram to disseminate information regarding future cyberattacks or to boast about successful ones, the need for effective data analysis methods is paramount. The primary challenge lies in the vast number of channels and the overwhelming volume of data, necessitating advanced techniques for discerning pertinent risks amidst th...

Hydrogen is gaining popularity as a fuel source for more and more fields around the globe. The use of hydrogen for transport represents one of the important applications of this chemical substance, in this sense the development of infrastructures, but especially the safety of hydrogen filling stations representing an important element. Using hydrogen to power transportation can reduce harmful ozone-depleting emissions while improving air quality. Hydrogen fuel cell vehicles can help improve air quality and solve c...