Category: FAAI

UBB students gain knowledge using FAAI

UBB students gain knowledge using FAAI

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We are delighted to inform you that our students are using FAAI work both in their Master’s theses and future progress. On the 2nd of July, the students defended their theses during the bachelor exam. The work was inspired by the FAAI project. The results of the students’ projects considered using applied AI in game development. Thanks to the project, the theses were defended successfully with the highest grade possible.

Now, we are proud to inform you that, based on their research, the scientific papers were accepted for the Engineer of the XXI Century Conference, which will take place in Bielsko-Biała, Poland.

 

Report on dissemination activities

Report on dissemination activities

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Below you can analyze the summary of the dissemination actions per project partners.

The summary was prepared in AdminProject platform.

In total, there are 93 actions engaging 6826 participants.

UBB (docx) – The Future is in Applied Artificial Intelligence_DISSEMINATION_P1_(UBB) (1)

UBB (xlsx) – The Future is in Applied Artificial Intelligence_DISSEMINATION_P1_(UBB)

ULSIT (docx) – The Future is in Applied Artificial Intelligence_DISSEMINATION_P2_(ULSIT)

 

A4.6: Publication “Designing a Competency-Focused Course on Applied AI Based on Advanced System Research on Business Requirements”

A4.6: Publication “Designing a Competency-Focused Course on Applied AI Based on Advanced System Research on Business Requirements”

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The publication disseminating WP4 has been published in Applied Sciences.

Below is the link

https://www.mdpi.com/2076-3417/14/10/4107

Abstract

The consortium of “The Future is in Applied Artificial Intelligence” Project designed the first competency-based applied artificial intelligence curriculum at the higher-education institution level. The development was based on advanced system research on existing artificial intelligence-related resources and surveying target groups of teachers, information technology students, and employers, which should enhance the performance of implementing artificial intelligence education. A review of applied artificial intelligence was prepared in the form of keyword clustering. The initial data were collected with the help of surveying by identifying job offers, existing artificial intelligence training courses, scientific projects, and real cases. A synthetic analysis of the textual information from the studies was conducted using the word clouds technique. A tensor-based approach was used for the presentation of the competency-based course. The specific numerical requirements for the course in the form of priorities followed from the solution to decision-making problems using the analytic hierarchy process technique. Based on a comprehensive study of surveys, educational experience, scientific projects, and business requirements, and a meta-analysis of the recent references, we specified the criteria for a training course in the form of a tensor-based representation of competencies in relation to content and educational modules.

 

A5.6: Publication on advanced neural network models

A5.6: Publication on advanced neural network models

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The work has been published in a top-ranked journal “IEEE Transactions on Neural Networks and Learning Systems”

The link is below

https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10479223

 

The title: On Model of Recurrent Neural Network on a Time Scale: Exponential Convergence and Stability Research

Abstract:

The majority of the results on modeling recurrent neural networks (RNNs) are obtained using delayed differential equations, which imply continuous time representation. On the other hand, these models must be discrete in time, given their practical implementation in computer systems, requiring their versatile utilization across arbitrary time scales. Hence, the goal of this research is to model and investigate the architecture design of a delayed RNN using delayed differential equations on a time scale. Internal memory can be utilized to describe the calculation of the future states using discrete and distributed delays, which is a representation of the deep learning architecture for artificial RNNs. We focus on qualitative behavior and stability study of the system. Special attention is paid to taking into account the effect of the time-scale parameters on neural network dynamics. Here, we delve into the exploration of exponential stability in RNN models on a time scale that incorporates multiple discrete and distributed delays. Two approaches for constructing exponential estimates, including the Hilger and the usual exponential functions, are considered and compared. The Lyapunov–Krasovskii (L–K) functional method is employed to study stability on a time scale in both cases. The established stability criteria, resulting in an exponential-like estimate, utilizes a tuple of positive definite matrices, decay rate, and graininess of the time scale. The models of RNNs for the two-neuron network with four discrete and distributed delays, as well as the ring lattice delayed network of seven identical neurons, are numerically investigated. The results indicate how the time scale (graininess) and model characteristics (weights) influence the qualitative behavior, leading to a transition from stable focus to quasiperiodic limit cycles.

This work was supported in part by the Erasmus + Program for Education of the European Union through the Key Action 2 Grant (the Future Is in Applied Artificial Intelligence) under Grant 2022-1-PL01-KA220-HED000088359 (work package 5: “Piloting,” activity A5.6 “Project deliverables”)

A5.7: Final multiplier event

A5.7: Final multiplier event

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This year’s 12th edition of the Beskid Academic Day conference, organized by the RESET scientific club operating at the University of Bielsko-Bialski, was devoted to topics related to Artificial Intelligence. The event has also become an official event of  The Future Is In Applied Artificial Intelligence project, No. 2022-1-PL01-KA220-HED-000088359. The agenda, which included nine AI-related lectures, included the following topics:

1. Inaugural lecture – The Future is in Applied Artificial Intelligence: the outputs of the project FAAI.  – prof. dr hab. Vasyl Martsenyuk – UBB
2. AI, a threat or… Is it high time to change jobs? Arcadiusz Benedict – Pitney Bowes.
3. A brief history of money. Will AI change the monetary system? Roman Majewski Crypto Mines.
4. When will AI create a video game? Artur Loska – Fool’s Theory
5. Malware vs antimalware. Michał Komendera UBB
6. The role of Cryptocurrency Miners in building decentralized AI. Konrad Duszyński – Crypto Mines.
7. Does IT have a future in Podbeskidzie? Wojciech Bachta – Da Vinci Studio.
8. Artificial intelligence and game design. Marcin Bernaś – UBB
9. Copyright and artificial intelligence through the eyes of a lawyer. Marek Nowicki – law firm.

 

The conference was officially inaugurated by the Rector of the University of Bielsko-Biala, Prof. Jacek Nowakowski. He familiarized the participants with the structure of the university, individual faculties and faculties. In his speech, he drew attention to the accelerating development of artificial intelligence and its rapidly growing capabilities. Finally, he wished all participants of the conference fruitful and knowledgeable lectures.

During the inaugural lecture, Prof. Vasyl Martsenyuk presented the current state of use of artificial intelligence in various areas of life and familiarized the conference participants with the main assumptions and goals of the FAAI project.

During the lecture entitled Artificial Intelligence and Game Design, Dr. Marcin Bernaś presented the student projects related to AI implemented at UBB and talked about the practical applications of artificial intelligence in game design based on the FAAI project materials on the real applications of AI in IT companies in Europe.

During the conference – in the lobby in front of the conference room – IT companies using AI in their IT products set up their stands:

  1. SI Record
  2. Vattenfall from Poland
  3. Pitney Bowes
  4. Regional Development Agency
  5. Infonet Project
  6. NEXT!

 

 

 

 

 

 

 

One of the blocks of the conference was a discussion panel on aspects of the FAAI project in the process of teaching AI and its use in the daily work of companies. The panel was attended by: Dr. Tomasz Gancarczyk – UBB (FAAI), Filip Wątorek – Pitney Bowes, Robert Gawlak – SI Record, Przemysław Dana – Vattenfall Polska.

The conference was attended by over 300 participants, who could listen to many interesting lectures related to AI and learn about aspects of its use in the educational process and in projects carried out on a daily basis in IT companies.

 

 

 

 

In addition to the lectures, participants could also take part in 4 workshops on AI:

1. Process Automation – ChatGPT in the work of a programmer. Filip Wątorek as Pitney Bowes
2. Build AI solutions with select Azure AI Services. Krzysztof Burejza – Data Community Podbeskidzie.
3. Scrum in practice. Mikołaj Kukurba – Vattenfall Poland.
4. Introduction to the world of cyber and pentesting. Michał Kłaput – Foundation 17 53c

 

 

 

 

Lectures:

Inaugural lecture – Areas of application of artificial intelligence. FAAI Project – Prof. Vasyl Martsenyuk – UBB

 

 

 

AI, a threat or… Is it high time to change jobs? Arcadiusz Benedict – Pitney Bowes.

 

 

A brief history of money. Will AI change the monetary system? Roman Majewski Crypto Mines.

 

When will AI create a video game? Artur Loska – Fool’s Theory

 

 

 

Malware vs antimalware. Michał Komendera UBB

 

The role of Cryptocurrency Miners in building decentralized AI. Konrad Duszyński – Crypto Mines.

 

Does IT have a future in Podbeskidzie? Wojciech Bachta – Da Vinci Studio.

 

 

 

Artificial intelligence and game design. Marcin Bernaś – UBB (FAAI)

 

 

Copyright and artificial intelligence through the eyes of a lawyer. Marek Nowicki – law firm.

 

All companies whose representatives took part in the conference

 Beskid IT Academic day

 

  1. SI Record
  2. Vattenfall from Poland
  3. Pitney Bowes
  4. Regional Development Agency
  5. Infonet Project
  6. NEXT!
  7. Fool’s Theory
  8. Crypto Mining Pools
  9. DaVinci Studio
  10. FabLab Bielsko-Biała
  11. BDY PSA
  12. Selleo
  13. Iteo
  14. BlackFrog
  15. JD Sport Fashion
  16. UX community
  17. Data Community Poland
  18. Kaczmarski Group
  19. District Road Administration
  20. WeNet Group S.A.
  21. inEwi
  22. MakoLab
  23. WASKO
  24. Marek Nowicki Law Firm
  25. conTeyor
A5.4: Teacher training on AAI

A5.4: Teacher training on AAI

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Teacher Training A5.4 in Trnava, Slovakia

Dates: May 15-19, 2024
Location: University of Ss. Cyril and Methodius in Trnava, Slovakia

 

 

The A5.4 Teacher Training event, held from May 15-19, 2024, in Trnava, Slovakia, brought together educators from five partner institutions to develop comprehensive teaching materials and guidelines for Artificial Intelligence (AI) and Machine Learning (ML) education. Organized by the University of Ss. Cyril and Methodius in Trnava, this training focused on equipping teachers with practical knowledge, resources, and frameworks to support and enhance AI education within various academic environments.

Participating Institutions:

  1. University of Bielsko-Biala, Poland (UBB)
  2. University of Library Studies and IT, Bulgaria (ULSIT)
  3. The University of Nis, Serbia (UNI)
  4. The University of Ss. Cyril and Methodius in Trnava, Slovakia (UCMT)
  5. University of Montenegro, Montenegro (UoM)

Training Overview and Agenda Highlights

Across five days, participants worked collaboratively to establish practical resources, including guidelines and educational materials for AI instruction. This training not only focused on content development but also provided a forum for discussing and refining methodologies, curriculum design, and teaching strategies for AI-related courses.

Day 1: Opening and Good Practice Guidelines

The training commenced with a welcome address by UCMT, which introduced participants to each other and set the tone for the week’s collaborative work. ULSIT led the first session on Good Practice in Developing Guidelines, sharing methods for structuring effective teaching resources. This session offered practical insights into creating comprehensive yet adaptable teaching materials, critical for AI education across diverse institutional settings.

 

Day 2: Developing the AAI Teacher Guide

UBB led a focused session on the development of the AAI Teacher Guide, which provides educators with foundational AI concepts, teaching strategies, and adaptable resources for classroom use. Following this, teachers collaborated in team sessions to expand and refine the guide with input from UCMT, ensuring that it would be accessible and relevant across different educational contexts.

Day 3: Creating the AAI Student Guide

ULSIT took the lead on Day 3 to develop the AAI Student Guide. This guide aims to provide students with clear, foundational information on AI principles and practical skills, tailored to varying levels of AI knowledge. The guide also includes interactive activities and project-based learning recommendations, supporting a hands-on approach to AI education.

Day 4: Building the AAI Business Guide

Day 4 shifted focus toward practical applications of AI in business, with UNI presenting the initial framework for the AAI Business Guide. This resource is designed to bridge the gap between academic AI education and industry applications, preparing students with the knowledge and skills they’ll need to understand and apply AI solutions in professional settings. UoM and UNI facilitated collaborative team sessions, encouraging participants to integrate business-relevant AI scenarios and case studies.

Day 5: Certification and Round Table on Future Improvements

On the final day, all participants received certificates of completion as recognition for their involvement in developing these essential AI resources. This was followed by a round-table discussion on enhancing the AAI framework, including potential revisions to methodology, curriculum, and content to align with emerging trends and requirements in AI and ML. Institutional coordinators concluded with a summary of training outcomes and an outline of future project steps to ensure continued progress and support.

Conclusion

The A5.4 Teacher Training in Trnava served as a productive and impactful event, allowing educators to collaboratively build and refine resources that will enhance AI and ML education for students, teachers, and industry professionals alike. By developing these guides, the training has contributed to a stronger foundation for AI learning across participating institutions, ensuring that both educators and students are well-prepared for the demands of the AI field. As the FAAI project progresses, these resources will play a crucial role in supporting an informed, skilled generation of AI practitioners.

 

 

       

 

A5.5: Student training on AAI

A5.5: Student training on AAI

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Student Training A5.5 in Trnava, Slovakia

Dates: May 15-19, 2024
Location: University of Ss. Cyril and Methodius in Trnava, Slovakia

 

 

The A5.5 student training, held from May 15-19, 2024, in Trnava, Slovakia, brought together students from five partner institutions for an immersive experience in the practical applications of artificial intelligence (AI) and machine learning (ML). Organized by the University of Ss. Cyril and Methodius in Trnava, the training aimed to equip students with hands-on skills in AI across multiple domains, from industry and healthcare to ecology and smart cities.

Participating Institutions:

  1. University of Bielsko-Biala, Poland (UBB)
  2. University of Library Studies and IT, Bulgaria (ULSIT)
  3. The University of Niš, Serbia (UNI)
  4. The University of Ss. Cyril and Methodius in Trnava, Slovakia (UCMT)
  5. University of Montenegro, Montenegro (UoM)

Training Overview and Agenda Highlights

Over five days, students delved into various AI modules, gaining practical skills and collaborating on projects designed to address real-world challenges through AI-driven solutions. Each session, led by expert representatives from partner institutions, introduced students to AI applications in science, industry, and business, with modules covering both foundational knowledge and specialized fields.

Day 1: Opening and Foundational Modules

The training began with a welcome session by the host institution, UCMT, followed by introductions from participants. ULSIT presented an overview of the FAAI project, including its objectives and target audiences, to familiarize students with the broader context and goals of their work.

The day’s training sessions included:

  • Module 1: Basic principles of AI in scientific and business applications, presented by ULSIT
  • Module 2: An exploration of embeddable AI modules from major providers like IBM, Microsoft, Google, and AWS, led by UNI
  • Module 3: Conducting AI-related research with practical applications, also by ULSIT

Day 2: Technical Modules and Team Collaboration

Building on foundational knowledge, Day 2 introduced students to more technical aspects:

  • Module 4: Building AI-powered software applications, led by UCMT
  • Module 5: Implementation of external AI modules, presented by UBB
  • Module 6: AI-based solutions for ecology, highlighting AI’s potential to address environmental challenges, presented by ULSIT

The day ended with collaborative team-working sessions where students worked on project ideas, guided by mentors from UBB and UCMT.

Day 3: AI Applications in Key Sectors

Day 3 showcased AI applications across diverse sectors:

  • Module 7: AI for agriculture, led by UoM, explored how AI tools are used to optimize crop production, resource management, and sustainability.
  • Module 8: AI in healthcare, presented by UBB, introduced solutions for predictive diagnostics, patient monitoring, and personalized care.
  • Module 9: AI solutions for smart cities, by UCMT, which highlighted how AI is transforming urban planning, transportation, and public services.

In the afternoon, students continued with their team projects, mentored by ULSIT experts.

Day 4: Industrial and Specialized AI Applications

On Day 4, students delved into industrial and robotics applications:

  • Module 10: AI in industry, presented by UNI, which included AI-driven manufacturing, predictive maintenance, and automation.
  • Module 11: AI in robotics, by UoM, discussed the role of AI in robotics innovation, from autonomous machines to human-robot collaboration.
  • Module 12: Application of other AI modules, led by UNI, focused on lesser-known but impactful AI applications.

Afternoon team-working sessions allowed students to finalize their project concepts, with guidance from UNI and UoM.

Day 5: Project Presentations and Certificate Ceremony

The training concluded with project presentations, where student teams showcased AI solutions they had developed, applying knowledge from each module to create innovative concepts targeting specific societal or industrial challenges. Projects ranged from AI-driven environmental monitoring systems to smart city applications and personalized healthcare tools. Each presentation was followed by a brief Q&A session, allowing teams to receive feedback and suggestions from trainers and peers.

Finally, all participants received certificates of completion, celebrating their dedication, hard work, and newly acquired expertise in AI and ML.

Conclusion

The A5.5 training in Trnava provided a comprehensive introduction to AI applications for the students, equipping them with valuable skills and practical knowledge that will benefit their academic and professional pursuits. This training was not only a stepping stone in AI education but also an inspiring experience for students, allowing them to collaborate with peers across countries and apply their skills in innovative ways. The FAAI project remains committed to supporting such experiences, fostering a skilled generation of AI practitioners ready to meet the challenges of tomorrow.

 

 

Publication: Electrochemical Biosensor Design Through Data-Driven Modeling Incorporating Meta-Analysis and Big Data Workflow

Publication: Electrochemical Biosensor Design Through Data-Driven Modeling Incorporating Meta-Analysis and Big Data Workflow

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The objective of the work is to offer workflow enabling us to execute both empirical and analytical studies of enzyme kinetics. For this purpose, on the one hand, we are based on a series of experimental research involving the traditional methods and techniques used when studying biochemical reactions and designing electrochemical biosensors: conductance research, spectroscopy, and electromagnetic field study.

Full text can be found here: https://link.springer.com/chapter/10.1007/978-3-031-42508-0_22

The audio description can be found here:

Publication: The Role of Cyber-Physical Systems and Internet of Things In Development of Smart Cities for Industry 4.0

Publication: The Role of Cyber-Physical Systems and Internet of Things In Development of Smart Cities for Industry 4.0

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The pace of urbanisation is currently increasing. Modern cities are striving to become more technologically advanced and “smarter”, combining the concept of sustainable development with an improved quality of life. At the same time, digital transformation is taking place, and a variety of flexible tools will help meet the growing challenges of urbanisation over the next
few decades. One of the tools of digital transformation is cyber-physical systems.
Cyber-physical systems (CPS) are a set of infrastructure and production systems that
combine computing (cyber) technologies integrated into the physical environment with
human interaction.

The full article text can found here: https://ceur-ws.org/Vol-3468/paper7.pdf

You can listen to article here: