The need for effective and portable parallel programming models has increased due to the complexity of high-performance computing systems, especially with the introduction of many-core processors like GPUs. Creating applications for various multi-core and many-core architectures frequently necessitates maintaining separate codebases, which increases development effort. In this paper, we evaluate Kokkos, a high-level C++ framework that allows for performance portability across architectures, by running five benchmark applications on a CPU and comparing their performance with OpenMP-based counterparts. The obtained results and corresponding observations are discussed in detail.
This work evaluatesFK-meansRA against abroader set of LEACH variants, including LEACH-C, MOD-LEACH, LEACH-B, MULTIHOP-LEACH, and I-LEACH,with a focus on metrics such as average residual energy, number of alive nodes, and throughput. The paper focuses oncomparative performance benchmarking across these popular LEACH variants, providing a rigorous validation of FK-meansRA efficiency. In this paper, we extend our prior study on the performance of the proposed algorithm, FK-meansRA, against famous protocols, such as LEACH, etc. Comparative analysis with LEACH variants ensures a fair, relevant, and focused performance assessment of clusteringhierarchical protocols in contrast to chain-based or flatrouting protocols like PEGASIS or HEED. The simulationresults demonstrate that the fuzzy logic-based modeloutperforms these protocols in terms of network stability and resource utilization.FK-meansRA has nearly 450 nodes alive after the end of 1250 rounds, 200% energy more left than multihop LEACH, and a 13.6% throughput improvementover multihop LEACH.
This paper presents a survey of Internet ofThings (IoT) applications using the Raspberry PI (RPi) SingleBoard Computer (SBC) alongside Computer Vision (CV) techniques from the field of Artificial Intelligence (AI). It presents and compares solutions across several IoTapplication areas, offering an overview of the associated hardware, software, CV methods, and algorithms. The studyexplores IoT applications in the following areas: Smart Healthcare, Face and emotion recognition, Wildlife, Smart Agriculture, Smart Homes, Security, Smart Cities, Autonomous Vehicles, Robotics, Manufacturing, and Retail. Each area is analyzed with respect to the integration of RPiand CV, showcasing their contributions to enhancingoperational efficiency and enabling innovative solutions. The presented solutions use different RPi boards, from RPi 3A+ up to the latest RPi 5.
This paper presents the engineering design and usability validation of SAVIRE (Social Anxiety-Virtual Reality-Serious Game), an immersive digital therapeutic platform for adolescents with Social Anxiety Disorder (SAD).Adopting an engineering-centered approach, SAVIRE is developed using a modular system architecture that incorporates a Behavioral Scoring Engine for real-time classification of user responses during virtual social interactions. The system is implemented using Unity 3D and the Oculus SDK and optimized for the Meta Quest 3S, leveraging inside-out tracking to enable high-fidelity immersion without reliance on external computing devices. Following the Rapid Game Development (RGD) methodology, clinically grounded therapeutic principles are translated into interactive mechanics and graded virtual exposure scenarios. Technical evaluation conducted by clinical experts using the User Experience Questionnaire (UEQ) demonstrated positive results, with mean scores exceeding 2.67 across all dimensions, including efficiency and stimulation. Usability testing involving 20 adolescents diagnosed with SAD yielded an average System Usability Scale (SUS) score of 80.38, indicating excellent usability. These findings position SAVIRE as an engineering-oriented framework for adaptive virtual simulations, contributing to the development of scalable digital therapeutic systems in mental healthcare.
The main goal of the study is to determine whether artificial intelligence can create mathematical and simulation models of the automatic room heating system, and therefore test the abilities of artificial intelligence in the field of engineering sciences. The scientific novelty of the article is the development of a simulation model of an automatic room heating system with relay temperature control using artificial intelligence. To fully and comprehensively disclose the purpose of the study, elementary physical laws are provided that describe the processes of heat transfer and thermal conductivity of the air in a confined space, such as JouleLenz's law or Ohm's law and describe the foundations of the theory of automatic control, and in particular the role of necessary links and negative feedback. Based on the operation of the built models, graphs of the resulting temperature are given, on the basis of which the operating time, the maximum achieved temperatures and the switching time of the heater are based.
