In April, the University of Bielsko-Biała hosted a Blended Intensive Programme event for students from Europe. The main goal of the “AI for Art” panel was to increase understanding of how AI is influencing and contributing to the field of art, including generative art and creative applications.
The presentation and link for tools are given here:
In April the University of Bielsko-Biala hosted Blended Intensive learning event. It bringed students from all Europe.
The special presentation was given that utilise the results of FAAI projects. The presentation and aditional asest are given here:
Blended Intensive Programme_fin
Additional files:
Report on Transnational Meeting A5.1 in Trnava
Date: March 14-15, 2024
Location: Trnava, Slovakia
The transnational meeting A5.1, a pivotal component of Work Package 5 (WP5) of the FAAI project, was held on March 14-15, 2024, in Trnava, Slovakia. This meeting brought together representatives from five partner institutions to discuss and coordinate the development of training materials and a thesaurus in artificial intelligence (AI) and machine learning (ML). The targeted audiences for these resources include students, teachers, mentors, and managers in the education and business sectors.
March 14, 2024
The meeting commenced with an introduction session at 11:00 AM, where participants reviewed the current state of the project and discussed the results from previous work packages (A5.3 and A5.6). Each institution presented their progress:
Following this overview, participants engaged in a detailed discussion on the current state of WP5, focusing on the distribution of responsibilities for key deliverables. This included:
After a productive morning, attendees broke for lunch at 1:00 PM, allowing for informal networking and discussion.
In the afternoon, sessions resumed at 2:00 PM with discussions on the translation of project results into native languages, ensuring that all materials are accessible to non-English speaking participants. The team then explored the AAI Job Hub, a proposed platform to enhance the visibility and openness of project results, facilitating broader engagement with the resources developed through the FAAI project.
The day concluded with a collaborative session at 3:00 PM, where participants shared good practices for implementing the FAAI initiative in their respective institutions, highlighting successes and challenges faced in the process.
March 15, 2024
The second day began with a focus on enhancing the evaluation of project results. Participants discussed various metrics and methodologies to assess the effectiveness of the training materials and their impact on the target audiences.
Following this, the agenda included a reporting session on the ongoing development of educational materials for the training course on Applied Artificial Intelligence. Participants reviewed progress and outlined next steps for ensuring comprehensive coverage of key AI concepts.
At 10:30 AM, the group shifted its attention to the dissemination of project results. Discussions centered on upcoming events and publications designed to share findings with a broader audience and prepare for multiplier events that will promote WP5 initiatives.
After a coffee break at 11:00 AM, participants reconvened to focus on the preparation of teacher and student training sessions scheduled to take place in Trnava. This session included planning for recording lectures and ensuring high-quality educational content.
The meeting concluded with a discussion on financial issues and managerial activities of the project, led by institutional coordinators from each participating university. This discussion was crucial for ensuring that all partners are aligned on budgetary matters and project administration.
The transnational meeting A5.1 proved to be a highly productive gathering, fostering collaboration among partner institutions. Participants left with clear action items, a shared vision for the development of AI education resources, and a renewed commitment to enhancing the capacity of students, teachers, and business leaders in the field of AI. The meeting not only advanced the objectives of the FAAI project but also strengthened the network of institutions working together to drive innovation in AI education across Europe.
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.
This article is a contribution within the Erasmus+ project titled “The Future Lies in Applied Artificial Intelligence” (FAAI) and examines research of collected IT specifications of good practices in Area of Artificial Intelligence (AAI). The article describes research conducted, the purpose of which is to find IT specifications of good practices in AI and describe their characteristics, like an area of implementation of the AI solution, the result of processing the data, the source of data, Data processing, and quality, what tools are used for processing data, and others. AAI application cases and the technologies used for implementation are reviewed. The specifics of the data and the applications used are described. The examination of these technologies will provide insight into which ones are favored and provide an overview of what is commonly referred to as “best practices” in this particular domain.
This article is a contribution within the Erasmus+ project titled “The Future is in Applied Artificial Intelligence” (FAAI) and examines research of collected IT specifications of good practices in Area of Artificial Intelligence (AAI). The article describes research conducted, the purpose of which is to find IT specifications of good practices in AI and describe their characteristics, like an area of implementation of the AI solution, the result of processing the data, the source of data, Data processing, and quality, what tools are used for processing data, and others. AAI application cases and the technologies used for implementation are reviewed. The specifics of the data and the applications used are described. The examination of these technologies will provide insight into which ones are favored and provide an overview of what is commonly referred to as “best practices” in this particular domain.
The use of data derived from Brain Computer Interaction (BCI) is a complex process that requires multidisciplinary skills and knowledge in computer science, signal processing, neuroscience, robotics, artificial intelligence, and other related fields. In this study, we propose the quantitative analysis method for feature selection based on descriptive statistics (maximum, minimum, mean and median).The purpose of this paper is to show that different trials of the same individual at the same symbol yield similar brain profiles regardless of their mental state, and that different individuals have different brain profiles at the same visual signals.
The obtained data are discussed in the context of studying the nature of brain signals.