On the 29th of February there was a meeting on which the presentation entitled “The use of artificial intelligence and sensors to monitor and classify objects” was presented.
It was a pleasure to talk about the AI application in modern world.
Here you can find the presentation ( link to presentation) and pictures from a meeting.
On the 15th of February there was a meeting on which the presentation entitled “AI application not only in sport” was presented.
It was a pleasure to talk about the AI application in modern world.
Here you can find the presentation ( link_to_presentation ) and pictures from a meeting.
The 16th Edition of the International Conference on Advanced Technologies, Systems, and Services in Telecommunications (TELSIKS’2023) unfolded at the distinguished Faculty of Electronic Engineering (FEE), University of Nis, Serbia, from October 25-26, 2023. This conference marked a significant milestone in the exploration of cutting-edge technologies and services in the field of telecommunications.
The FAAI project consortium was represented by delegations from University of Bielsko-Biala (UBB), University of Library Studies and IT (ULSIT), University of Nis (UNI), University of Ss. Cyril and Methodius in Trnava (UCMT), and University of Montenegro (UoM), collectively showcasing the collaborative efforts and expertise of these esteemed institutions.
Opening Ceremony and Plenary Session: A Glimpse of Our Delegation’s Engagements
Before delving into the special session on Applied Artificial Intelligence, our delegations had the privilege of participating in the distinguished Opening Ceremony and Plenary Session of TELSIKS’2023.
The Opening Ceremony, held in Room 457, FEE, was a momentous occasion marked by an atmosphere of camaraderie and shared purpose. It provided a fitting commencement to the conference, setting the stage for the intellectually stimulating interactions that followed.
Following this, the Plenary Session, also convened in Room 457, FEE, showcased a lineup of eminent speakers who expounded upon the latest trends and advancements in telecommunications. Our delegations actively engaged in these enriching discussions, contributing to the collective discourse on the future of the field.
Special Session: Setting up the Applied Artificial Intelligence Learning Requirements (SS3)
A significant highlight of the conference was the special session on Applied Artificial Intelligence (AI) and learning environments. This session delved into the development of a competency framework for Applied AI, encapsulating technical, business, and ethical perspectives, in alignment with the Erasmus+ project FAAI No. 2022-1-PL01-KA220-HED-000088359.
Chaired by Vasyl Martsenyuk and Olivera Pronić-Rancic, the session played a pivotal role in fostering dynamic discussions and facilitating the exchange of innovative ideas on Applied AI.
Noteworthy Talks
1. “On Emerging Methodology for Collection of Good Practices in Applied Artificial Intelligence”
• Vasyl Martsenyuk, George Dimitrov, Dejan Rancic, Iveta Dirgova Luptakova, Igor Jovancevic, Aleksandra Klos-Witkowska, Marcin Bernas, and Tomasz Gancarczyk.
2. “Research and Analysis of IT Specifications of Good Practices in Artificial Intelligence”
• Paulina Tsvetkova, George Dimitrov, Vasyl Martsenyuk, Iveta Dirgová-Luptáková, Dejan Rancic, Igor Jovancevic, Iva Kostadinova, Katia Rasheva-Yordanova, Pepa Petrova, and Pavel Petrov.
3. “Research and Analysis of Different Real Cases, with use of AAI”
• Iva Kostadinova, George Dimitrov, Vasyl Martsenyuk, Dejan Rancic, Iveta Dirgova-Luptakova, Igor Jovancevic, Ivan Trenchev, Stefka Toleva-Stoimenova, and Pavel Petrov.
4. “Employer Requirements for Graduate Competencies in Applied Artificial Intelligence”
• Dragan Stojanovic, Olivera Pronić-Rancic, Natalija Stojanovic, Dejan Rancic, and Marko Milojkovic.
5. “Research and Analysis on the Labor Market in the Field of Applied AI”
• Aleksandar Plamenac, Igor Jovancevic, Georgi Dimitrov, Vasyl Martsenyuk, Dejan Rancic, and Iveta Dirgova-Luptakova.
6. “On Predicting Financial Time Series of Various Granularity as an Applied AI Problem”
• Vasyl Martsenyuk and Jacek Kafel-Kania.
7. “On Manufacturing Network Design as an Applied AI Problem”
• Vasyl Martsenyuk and Nataliia Kit.
Engaging Discourse and Valuable Insights
The ensuing discussions were characterized by a palpable enthusiasm and a profound appreciation for the depth of knowledge shared. The questions posed were astute, and the insights imparted were instrumental in augmenting our collective understanding.
Looking Ahead
The conference culminated as a resounding success, serving as an exemplary platform for the dissemination of the FAAI project’s findings. The strides made in the domain of Applied AI are nothing short of commendable, and we remain sanguine about the transformative potential of our collaborative endeavors.
We extend our gratitude to all participants for their invaluable contributions, and we eagerly anticipate the continued discourse on these vital topics.
The A4.1 transnational meeting took place at the Faculty of Electronic Engineering in Nis, and Science Technology Park Nis, Serbia, with the participation of partners from five universities: University of Bielsko-Biala (UBB), University of Library Studies and IT (ULSIT), University of Nis (UNI), University of Ss. Cyril and Methodius in Trnava (UCMT), and University of Montenegro (UoM). The meeting’s main objective was to facilitate collaboration, assess the project’s current status, and explore future perspectives.
Science Technology Park Nis (STPN) gave the venue for the meeting conductance.
Photo. The meeting participants before the STPN building
Photo. The meeting participants studied the experience of IT companies located in STPN, focusing on applied AI
Photo. The meeting participants investigating AI hardware solutions for virtual platforms
Day 1 – October 25, 2023:
1. Introduction and Project Overview (14:30 – 15:00)
• Vasyl Martsenyuk and Georgi Dimitrov provided an overview of the project’s current state, highlighting the progress made in developing the Artificial Intelligence Competency Framework, Learning Requirements, and the curriculum’s main content and topics.
2. Current State of WP4 and Task Distribution (15:00 – 15:30)
• Igor Jovancevic and Dejan Rancic discussed the current state of Work Package 4 (WP4) and allocated tasks and responsibilities among the partners.
3. Methodology of AAI Design (15:30 – 16:00)
• Igor Jovancevic and Vasyl Martsenyuk presented the methodology for designing Artificial Intelligence in Education (AAI) components.
4. Translations of Project Results (16:30 – 17:00)
• All partners engaged in discussions regarding the translation of project results into their respective native languages.
Day 2 – October 26, 2023:
5. AAI Job Hub and Openness of Project Results (08:30 – 09:00)
• Vasyl Martsenyuk introduced the AAI Job Hub as a platform to enhance the accessibility and openness of project results.
6. Enhancing Project Evaluation (09:30 – 09:45)
• All partners collaborated to explore ways to enhance the evaluation of project results.
7. Education Materials Development Report (09:45 – 10:30)
• Partners reported on the progress made in developing education materials for the training course on AAI.
8. Dissemination of Project Results (10:30 – 11:00)
• Vasyl Martsenyuk discussed strategies for disseminating project results through events and publications.
9. Preparing Trainings in Trnava (15:00 – 15:30)
• Iveta Dirgova Luptakova provided insights into the preparation of training sessions in Trnava.
10. Financial and Managerial Activities (15:30 – 16:00)
• Institutional coordinators from all partners addressed financial and managerial aspects of the project (AdminProject).
The meeting concluded successfully, achieving its objectives of fostering collaboration, assessing project progress, and outlining future actions. The partners left with a clear understanding of their roles and responsibilities moving forward in the FAAI Erasmus+ project.
Project FAAI:2022-1-PL01-KA220-HED-000088359 “Future is in Applied Artificial Intelligence” (FAAI) under the Erasmus+ program started in September 2022. This project aims to bring together universities and business, and provide innovative solutions to develop artificial intelligence experts.
The project unites 5 partners from Central European and Eastern European universities: Poland, Slovakia, Serbia, Bulgaria and Montenegro.
In fulfillment of the goals set in the project, a case study with real application of AAI was conducted at stage WP2. The survey was conducted by the participants of this project.
Full paper can be found here: Research 8_EN_StateOfTheArt
The work presents the study of specifications of good practices in applied artificial intelligence (AAI). The analysis of 25 questionnaires from five partner institutions revealed key insights into the current state of artificial intelligence (AI) and machine learning (ML) projects. Training conducted in Serbia and Bulgaria, was signaling a need for expanded opportunities in EU countries. As a result of the study, we obtained that Deep ML prevails, particularly in Convolutional Neural Networks, while Gated Recurrent Unit is less common. Data volumes between 1 GB and 1 TB are typical, reflecting practical constraints. AI applications span diverse fields, with TensorFlow leading in libraries. Permissive licenses are most prevalent, databases are primary data sources, and texts/pictures dominate data characteristics. NoSQL databases are favored for storage. Security features and data processing tools vary. Dedicated servers and clusters are widely used, recommender systems are prominent, Python is the preferred language, and Apache Hadoop dominates ecosystems. Free datasets foster accessibility. Overall, the findings emphasize the dynamic nature of AI/ML projects, providing a foundation for future research in the rapidly advancing field.
Full paper can be found here: Research 7 StateOfTheArt_V3
FAAI is an ERASMUS+ project that aims to evaluate existing AI systems and tools and develop common EU competencies for skill-building systems that use AI capabilities in the SME sector. The project aims to increase the quality and relevance of students’ and graduates’ knowledge and skills in AI/ML-specific topics based on skills needed in the labor market. This survey was conducted in the context of the FAAI project to assess the needs of employers in graduate competencies in Artificial Intelligence, Machine Learning, and Data Science in general. The survey aimed to research the needs and expectations of employers and companies for the purpose of training specialists in the field of Applied AI. A total of 38 companies filled in the survey representing a good starting point for examination and analysis of their needs related to applied AI. The survey consisted of 31 questions, including questions on general competencies needed, the type of machine learning problems solved, and the AI libraries used in companies. The survey also included questions on soft skills required, additional competencies needed, employer satisfaction with the level of preparation of Master’s studies’ graduates in the area of AI, and views towards raising the qualification of current employees of organizations by letting them study AI at а master’s level.
Full paper can be found here: Research 6
This study is based on extensive survey conducted as a part of activities during the realization of the Erasmus+ project “Future is in Applied Artificial Intelligence”. Survey aimed to research the needs and expectations of IT graduates Masters and IT Alumni in Information Systems and Technologies regarding various Applied Artificial Intelligence topics with the goal to examine knowledge and attitude of students toward AI contents, current state of AI education and future directions of the transformation of education system toward competency-based education.
Full paper can be found here: Research 5
The questionnaires of 80 teachers from 5 countries were collected and analyzed, concerning artificial intelligence teaching. Among the more interesting results belongs the finding, that most of the teachers are self-educated regarding artificial intelligence, the majority of them never participated in a commercial project regarding artificial intelligence, but most of the teachers would welcome extended participation of experts from industry in teaching of students. From their recommendations can be selected e.g. advices:
Focus more on the free versions.
Most of the answers were analyzed and visualized in a form of graphs.
Full paper can ce found here: Research 4 StateOfTheArt_teachers_Dirgova
The questionnaires about 63 projects collected by partner organizations from the 5 countries were collected and analyzed, concerning artificial intelligence teaching. The project coordinators were from 19 countries. Among the more interesting results belongs the finding, that more than half of the projects concerned deep neural networks learning modules, and most machine learning tasks which were solved, were image processing, classification, regression, clusterization and natural language processing. Among the used AI libraries dominated TensorFlow, Keras, scikit-learn and CUDA. The programming languages were Python and C++.
Most of the answers were analyzed and visualized in a form of graphs.
Full document can be found here: Research 3 StateOfTheArt_scientificprojects_Dirgova