Hibridni događaj

Program događaja

petak, 26.5.2023 9:00 - 13:00, Camelia 2, Grand hotel Adriatic, Opatija 9:00 - 13:00 Radovi  1. A. Krivičić, S. Martinčić-Ipšić (Faculty of Informatics and Digital Technologies, Rijeka, Croatia) Analyzing Sentiment of Reddit Posts for the Russia-Ukraine War  Currently, we are witnessing a major global crisis caused by the ongoing war in Ukraine. In this paper, we deepen the insights into people's opinions about the Russia-Ukraine war by analyzing the posts on the Reddit subreddit UkrainianConflict. The extracted posts are preprocessed and the sentiment polarity (neutral, positive or negative) is determined using the Valence Aware Dictionary and sEntiment Reasoner" (VADER). We analyze the frequency of the most representative keywords in two longer periods in May and October 2022. Finally, the trend of Google searches on the war is compared with the number of daily subreddit posts. 2. M. Trpchevska, A. Dedinec (Faculty of Computer Science and Engineering, Skopje, Macedonia) Classification of Crimes Using Machine Learning Techniques for National Crime Data  The paper aims to assist in a more accurate classification of crimes provided by North Macedonia’s Ministry of Internal Affairs using machine learning techniques. By means of natural language processing, data is transformed into a format suitable for term frequency-inverse document frequency (TF-IDF) vectorization. Bayesian and Support Vector Machine models are utilized and evaluated. The results show non-negligible improvement toward a successful classification of crimes, confirming the beneficial nature of machine learning techniques towards such tasks. 3. E. Ibrahimović (Druga gimnazija Sarajevo, Sarajevo, Bosnia and Herzegovina) Optimizing Vision Transformer Performance with Customizable Parameters  This paper experimentally examined the effects of changing the size of image patches and the number of transformer layers on the training time and accuracy of a vision transformer used for image classification. The transformer architecture was first introduced in 2017 as a new way of processing natural language and has since found applications in computer vision as well. In this experiment, we trained and tested fourteen versions of a vision transformer on the CIFAR-100 dataset using graphical processing units provided by Google Colaboratory. The results showed that increasing the number of transformer layers and decreasing the patch size both increased test accuracy and training time. However, learning curves generated by the models showed overfitting for very small patch sizes. Overall, changing patch size had a greater impact on accuracy than changing the number of transformer layers. The results also suggested that transformers are more resource-intensive to train than other models. We showed that including a classification token could lead to shorter training times, but another experiment is needed to examine its influence on accuracy. 4. A. Ilić, M. Čarapina, V. Uglješić (Zagreb University of Applied Sciences, Zagreb, Croatia) Istraživanje izazova i problema suradnje dizajnera i razvojnih programera tijekom procesa razvoja digitalnog proizvoda  Radom se istražuje problematika procesa razvoja aplikacija od skica ekrana (engl. wireframe) do proizvoda, s fokusom na prijenos informacija između dizajnera i programera. U praksi čest je slučaj da se razvijena programska podrška u prvim fazama razlikuje od skice koju je osmislio dizajner ili dizajnerski tim. Istraživanje detektira uzroke zbog kojih dolazi do spomenutih odstupanja osvrćući se na iskustva dizajnera i programera. 5. S. Barac, I. Botički, G. Perković, V. Radošević, I. Terzić (Faculty of Electrical Engineering and Computing, Zagreb, Croatia) Cardano - What Is It and How to Start Working with It  Cardano je cijenjena blockchain platforma koja je stekla široku popularnost zbog svog fokusa na balansiranje sigurnosti i decentralizacije uz upotrebu pametnih ugovora i znanstvenog pristupa. Naše istraživanje bilo je usmjereno na Cardano mrežu, gdje smo analizirali njenu arhitekturu i razne mogućnosti poput transakcija, metapodataka i novčanika. Cilj našeg istraživanja bio je istražiti potencijalne primjene Cardano mreže u razvoju suvremenih informacijskih sustava. Kako bismo to postigli, detaljno smo proučili karakteristike i mogućnosti mreže i ustanovili da mreža ima puno potencijala za stvaranje inovativnih informacijskih sustava s visokim stupnjem sigurnosti. Rezultat našeg istraživanja je izrada javno dostupnog API-ja odnosno npm paketa koji omogućuje prijenos podataka na Cardano mrežu, a koji se lako može implementirati u druge programe. Zaključno, naše istraživanje pružilo je dragocjene uvide u mogućnosti i mehanizme korištenja Cardano blockchaina za razvoj modernih informacijskih sustava. To može koristiti širokom rasponu dionika, uključujući programere, tvrtke i krajnje korisnike koji traže sigurna i inovativna blockchain rješenja. 6. R. Jutreša, P. Peer, Ž. Emeršič (Faculty of Computer and Information Science, Ljubljana, Slovenia), J. Kim (Kyungpook National University, Daegu, South Korea) Keeping Drivers Alert: A Solution for Monitoring Driver Attention in Assisted-Driving Vehicles  The advent of the new industrial revolution has led to a surge in the number of self-driving and assisted-driving vehicles on the roads. Although this development enhances the overall quality of life, it also poses new challenges and risks. One such difficulty is the need for driver attention in the event of system errors. To overcome this issue, a driver monitoring system is necessary to ensure that the driver remains focused and can take control if necessary, while also sending alerts in case of driver distraction. To address this challenge, we propose a method that employs a convolutional neural network based on the ResNet architecture. This system can recognize selected types of driver distractions in captured infrared images. We experimented with different depths of the ResNet architecture to determine the most optimal results. The best model achieved an accuracy rate of 94% in detecting various forms of driver distraction. 7. A. Bukovac, E. Pleše, P. Petrović, U. Maravić, T. Jagušt (Faculty of Electrical Engineering and Computing, Zagreb, Croatia) Teaching Programming and Microcontrollers with an Arduino Remote Laboratory Application  This paper presents our work on an educational web system that teaches programming and microcontroller basics using the Arduino board in remote laboratory settings. In response to the shift towards remote and distance learning brought by the COVID-19 pandemic, and in an effort to alleviate the issue of continuous equipment shortage in many Croatian schools, we developed and tested a client-server architecture-based interactive remote laboratory system called RemoLab. The system consists of a web-based frontend application, a backend server with an accompanying database, and additional tools for connectivity with an Arduino microcontroller and a webcam. The system allows students to remotely write code for real hardware and instantly observer the results of their actions through a connected web camera. The developed system was tested by a group of primary school students, and some preliminary usage and user satisfaction data was collected. The RemoLab system has the potential to enable teachers in enriching their online courses or homework assignments, but also back up students in independent learning and experimentation with Arduino or microcontrollers. We believe that this application has the potential to improve the way students learn microcontroller programming and can be used as an effective tool for distance learning. 8. P. Petrošanec, S. Čelan, R. Nikolić, M. Milenković (Faculty of Transport and Traffic Sciences, Zagreb, Croatia) Awareness of Croatian Citizens about the Advantages and Disadvantages of Iot Devices and their Safety  How knowledgeable are we about the Internet of Things? What do IoT devices mean to us in everyday life? For the purpose of the paper, a survey has been conducted among the population between the ages of 19 and older on issues of familiarity with IoT devices, and an analysis of the responses was made on the awareness of the citizens of the Republic of Croatia. This paper aims to show how knowledgeable the citizens of the Republic of Croatia are about IoT devices, their capabilities, their security, and the possibility of omissions, data leaks, and violations of the GDPR, i.e., omissions with the sharing of their personal data. Considering that the global pandemic in the last two and a half years has stimulated computerization and the sudden expansion and ever-faster spread of IoT devices, the acquaintance of EU citizens and knowledge about IoT capabilities has been called into question. There is also a viable need for educating and familiarizing the citizens of the Republic of Croatia with the capabilities of IoT devices and their advantages and disadvantages. The paper discusses the theoretical and practical implications of the research and gives recommendations for further research. 9. M. Lonić, V. Zuppa Bakša, G. Vujisić (Zagreb University of Applied Sciences, Zagreb, Croatia) Device for Testing the Windings of Electrical Machines  The topic of the paper is the digitization of the process of testing the windings of electrical machines. Windings of electrical machines create an electric field in their vicinity. This field should have specific strength allocation in the surrounding area to ensure regular electrical machine operation. By mapping the field strength, it is possible to create a graph of the field strength, which should follow the specified distribution. By checking for deviation, it is possible to detect winding defects. The field is mapped with induction coils, which generate voltage when inserted in the changing electric field. This voltage is then used as an indication of the magnetic field strength. The problem is that the mapping of the field by hand requires many measurements to be made, which is both a time-consuming and an error-prone process. The paper describes the device for testing the windings of electric fields. This device makes the process overall faster and more accurate. Both software and hardware workings are explained in the paper. 10. M. Putak, V. Zuppa Bakša, A. Bednjanec (Zagreb University of Applied Sciences, Zagreb, Croatia) Electrical Scheme Digitization Using Deep Learning Methods  The use of software tools and applications progressively became a standard in both education and industry. A solution for hand-drawn electrical scheme digitization has been proposed to match the fast-paced dynamic of the modern world in the field of electrical engineering. The aim is to notably reduce time-consuming and error-prone electrical scheme tracing from hand-drawn to simulating software. The means have been achieved through the usage of state-of-the-art deep learning model YOLOv5 for electrical elements detection along with Python and OpenCV library for data processing. The user's input is an image of a hand-drawn circuit and the end result is an LTSpice digitized electrical scheme ready for simulation. 11. M. Vasilj (Faculty of Electrical Engineering and Computing, Zagreb, Croatia), V. Vučetić (Faculty of Kinesiology, Zagreb, Croatia), M. Sukreški (Ultrax technologies, Zagreb, Croatia), D. Bojanjac (Faculty of Electrical Engineering and Computing, Zagreb, Croatia) Body Fat Percentage Calculation: A Linear Regression Model on Croatian Tennis Players Morphology  Body composition is an important aspect of the fitness and performance of tennis players. Measuring body composition accurately can be a challenging task due to its complex nature and various factors that can affect the results. This study aims to examine the relationship between tennis player morphology and body fat through mathematical models, reducing the reliance on costly measurement equipment. Morphology of Croatian tennis players dataset was used, and the results of statistical analysis showed a strong correlation between player morphology, age, sex and body fat percentage. Furthermore, a PCA analysis was carried out which revealed that male and female populations become distinct when they hit puberty and allows us to explain the differences in body composition between the sexes. Using these results, a set of linear regression models were developed that can be used to predict body fat percentage. This research adds to the existing literature by highlights the significance of factors affecting body fat percentage in tennis players, which are skin fold thickness, age, and sex. The newly developed models offer a cost-effective solution for coaches to assess and monitor body composition in tennis players with skin fold measurements instead of more expensive equipment. 12. H. Hrženjak, Ž. Mihajlović (Faculty of Electrical Engineering and Computing, Zagreb, Croatia) Visualization of Three-Dimensional Ultrasound Data  This paper presents visualization of an ultrasonic probe beam from a series of cross-section images. The goal was to simulate scanning with an ultrasonic probe as it would be done in real-life. Cross-section slices that represent the detection sensitivity of the probe were obtained by simulating a sound pressure field in the metal sample and were provided by INETEC. Different techniques for rendering the three-dimensional model of a sequence of images used for beam visualization in the making of the software are presented. The beam and its inner structure were rendered with the Volumetric Ray Marching algorithm while the polygonal mesh approximation was constructed with the Marching cubes algorithm. The final software was developed using the Unity engine. The results and visualization possibilities were presented and analyzed along with the possible improvements for the future work. The developed simulation software can be used as a helping tool in minimizing the number of redundant scans in search of defects inside an object structure during the quality control phase.

Osnovni podaci:

Lovro Božičević (Croatia), Dubravko Sabolić (Croatia), Pavle Ergović (Croatia)

Prijava/Kotizacija:

Popust se ne odnosi na studente doktorskog studija.

Lovro Božičević
KSET
Fakultet elektrotehnike i računarstva
Unska 3
10000 Zagreb, Hrvatska

GSM: +385 99 788 1134
E-mail: lovro.bozicevic@fer.hr

Najbolji radovi bit će nagrađeni.
Prihvaćeni radovi bit će objavljeni u zborniku radova s ISSN brojem. Prezentirani radovi na engleskom jeziku bit će poslani za uključenje u digitalnu bazu IEEE Xplore.
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Postoji mogućnost da se odabrani znanstveni radovi uz određenu doradu objave u sljedećim časopisima: Journal of Computing and Information Technology (CIT), MDPI Applied Science, MDPI Information Journal, Frontiers i EAI Endorsed Transaction on Scalable Information Systems.

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