Track Description

Software development has begun to benefit more and more in recent years from the benefits of using artificial intelligence (AI). On the one hand, the software application development process can benefit from the experience gained previously in the realization of the applications, experience that is fully found in the code repositories either private or public on the Internet. On the other hand, many software applications have components that use artificial intelligence to cluster, classify, or predict. We refer here primarily to components that use computer vision techniques or techniques from natural language processing, but we do not exclude similar techniques from other fields. Also, new technologies such as mixed reality benefit fully from AI help when we need to interact with these applications or when we create smart components in games or eLearning applications.

Track Chairs

Adrian Iftene, Alexandru Ioan Cuza University of Iași, Romania
Ioan Petri, Cardiff University, UK

Papers

A Hybrid Method Based on Quantum-enhanced RNN and Data Integration for the Prediction of COVID-19 Outbreak

Ahmed Nasri, University of Manouba
Nesrine Ben Yahia, University of Manouba
Narjès Bellamine Ben Saoud, University of Manouba
Slimane Ben Miled, Universiy of Tunis El Manar

Applications of AI Alignment and Anticipatory Networks to Designing Industrial Risk Management Decision Support Systems

Andrzej M. J. Skulimowski, AGH University of Science and Technology Krakow
Paweł Łydek, AGH University of Science and Technology Krakow

Epidemic Risk Models on Graphs with Fuzzy Edges

Sándor Darida, OTP Bank Hungary

Graph Databases and E-commerce Cybersecurity - a Match Made in Heaven? The Innovative Technology to Enhance Cyberthreat Mitigation

Marek Pawlicki, Bydgoszcz University of Science and Technology
Aleksandra Pawlicka, University of Warsaw
Rafał Kozik, Bydgoszcz University of Science and Technology
Michał Choraś, Bydgoszcz University of Science and Technology

On What Kind of Applications Can Clustering Be Used for Inferring MVC Architectural Layers?

Dragoș Dobrean, Babeș-Bolyai University
Laura Dioșan, Babeș-Bolyai University

Python Library for Consumer Decision Support System with Automatic Identification of Preferences

Jarosław Watróbski, University of Szczecin
Aleksandra Baczkiewicz, University of Szczecin
Iga Rudawska, University of Szczecin

The IoT Threat Landscape vs. Machine Learning, a.k.a. Who Attacks IoT, Why Do They Do It, and How to Prevent It?

Marek Pawlicki, Bydgoszcz University of Science and Technology
Aleksandra Pawlicka, University of Warsaw
Mikołaj Komisarek, Bydgoszcz University of Science and Technology
Rafał Kozik, Bydgoszcz University of Science and Technology
Michał Choraś, Bydgoszcz University of Science and Technology

Topic Classification for Short Texts

Dan Claudiu Neagu, Babeș-Bolyai University
Andrei Bogdan Rus, Cicada Technologies
Mihai Grec, Cicada Technologies
Mihai Augustin Boroianu, Cicada Technologies
Gheorghe Cosmin Silaghi, Babeș-Bolyai University