We are happy to report that 4 BSc theses were defended on 18.07.2023. that were relevant to AI applications. These theses were done under mentorship of HPC4S3ME and EUROCC team. This is all part of building scientific and innovation potential to utilize HPC and AI in different domains of S3 Smart Specialisation Strategy in Montenegro. This is a great exampe of NCC support and cross-project collaboration. More about HPC4S3ME project can be found at: link.
Ms Tamara Lasica: “Development of Generative AI (GenAI)” (link)
Ms Elda Kalac: “Artificial intelligence and big data analytics” (link)
Mr Nikola Kavaric: “Explainable Artificial Intelligence” (link)
Mr Elvis Taruh: “Artificial intelligence and video games” (link)
Mr Dejan Babic, a young researcher from UDG, just defended his Master thesis on the use of computer vision and artificial intelligence in medicine. This is a great example of using ICT for vertical priority domains of Monteengrin S3. This research was supported in part by HPC4S3ME project and EUROCC. Mr Babic intends to continue his research in this domain and to enroll PhD program at the UDG. Mr Babic explored the use of different tools for ML and he also experimened with the use of HPC for training prediction models that can be used in medicine. He was one of the first MSc theses defended from the Artificial Intelligence Master program created under the EuroCC project.
ABSTRACT – Artificial Intelligence is transforming the way we live, work, and communicate with the world. The proliferation of data has been the biggest driver of AI in recent years. AI in medicine is rapidly developing and holds great potential in revolutionizing healthcare systems. Its application is already producing promising results in disease detection, diagnosis and drug discovery. AI is widely used in medical facilities worldwide as a decision support tool for patient diagnosis. It is expected to bring significant benefits to healthcare sector. In this thesis, the focus is on the application of artificial intelligence and computer vision in solving real medical problems. The research is both theoretical and empirical and focuses on the application of artificial intelligence and computer vision in the detection of pneumonia, segmentation of blood vessels in the retina, and estimation of cardiovascular risk. The main goal of the research is to achieve the highest possible accuracy in specific cases and approaches, in order for these approaches to be considered applicable in medicine. Throughout the study, some of the ethical issues related to the use of this technology were also raised. At the end of the study, the results, potential challenges, and future directions of this research were discussed.
Computer vision and artificial intelligence in medicineSegmentation of blood vessels in images of retina
Mr Ivan Jovovic, a young researcher from UDG, just defended his Master thesis on the use of artificial intelligence and machine learining on edge devices. This research was supported in part by HPC4S3ME project and EUROCC. Mr Jovovic intends to continue his research in this domain and to enroll PhD program at the UDG. Mr Jovovic explored the use of different tools for ML and he also experimened with the use of HPC for training prediction models that can be ported onto edge devices. He was one of the first MSc theses defended from the Artificial Intelligence Master program created under EuroCC project.
ABSTRACT – This thesis explores the combination of artificial intelligence, machine learning, deep learning, and edge computing in modern applications, with a special focus on medicine and agriculture. The paper first introduces the reader to the basic terms and definitions of machine learning, deep learning, computer vision, the Internet of Things and Edge computing. After the theoretical basis, the work provides an insight into the practical applications of these technologies in medicine and agriculture, highlighting the benefits and drawbacks of their applications. In the following, the paper offers a detailed study of practical examples of edge artificial intelligence in agriculture and healthcare, as well as artificial intelligence in the field of medicine, with focus on disease classification. Through the realization and implementation of these projects, the interpretation of the results and the discussion, the paper emphasizes the importance of the integration of artificial intelligence and edge computing in various industries.
Master thesis: The use of Artificial Intelligence on Edge (Edge AI)
Thanks to EuroCC2 team from Montenegro, EuroCC and 27th International Scientific and Professional Conference – Information technology IT2023 were featured in the June issue of IEEE Region 8 News magazine (Vol 4 No 2). You can access the full issue at the following link. The News bulletin is published quartterly and distributed to over 80000 IEEE members in Region 8.
EuroCC has published their first booklet edition of Success Stories for 2023! The booklet contains a summary of successful experiments that have been conducted within the EuroCC projects with some of them using EuroHPC Joint Undertaking supercomputers Each success story includes its challenges, solutions, business impacts and benefits. Discover more on the newly published booklet! Project AIMHiGH, a HPC/AI use case for computer vision solutions in agri-food sector, was featured in this first bulletin. The booklet is available at the following link.
Project AIMHIGH featured in the Success Story bulletin
Researchers from UDG and NCC Montenegro published a paper “Machine Learning Models for Statistical Analysis” by M. Grebovic et al. in The International Arab Journal of Information Technology, Vol. 20, No. 3A, Special Issue 2023. This was a follow up effort on the paper previously presented at the ACIT2023 conference.
Click on image to open
ABSTRACT – Compared to traditional statistical models, Machine Learning (ML) algorithms provide the ability to interpret, understand and summarize patterns and regularities in observed data for making predictions in an advanced and more sophisticated way. The main reasons for the advantage of ML methods in making predictions are a small number of significant predictors of the statistical models, which means limited informative capability, and pseudo-correct regular statistical patterns, used without previous understanding of the used data causality. Also, some ML methods, like Artificial Neural Networks, use non-linear algorithms, considering links and associations between parameters. On the other hand, statistical models use one-step-ahead linear processes to improve only short-term prediction accuracy by minimizing a cost function. Although designing an optimal ML model can be a very complex process, it can be used as a potential solution for making improved prediction models compared to statistical ones. However, ML models will not automatically improve prediction accuracy, so it is necessary to evaluate and analyze several statistical and ML methods, including some artificial neural networks, through accuracy measures for prediction purposes in various fields of applications. A couple of techniques for improving suggested ML methods and artificial neural networks are proposed to get better accuracy results.
FF4EuroHPC experiment AIMHIGH featured in national magazine Glasnik published by Montenegrin Chamber of Economy (Feb-Mar 2023 issue). The article provides summary and results of the FF4EuroHPC experiment called AIMHiGH that focuses on the use of HPC and AI for developing computer vision solutions for smart farming solutions in poultry sector. The focus of the article is to provide an insight on how HPC can be utilized by SMEs, in this case focused on digital innovation, to provide smart solutions for agri-food sector. The full version of the magazine can be accessed here.
