Student IT/EE Workshop 2024

Session

Session B (Poster)

18 Apr 2024, 10:45

SK 04 / SK 05 (Warsaw University of Technology)

Conveners

Session B (Poster)

• Marcin Iwanowski

8. Analysis of Application Handling System Process in the Internet Dean's Office Support System Using Process Mining

Ms Natalia Bernardelli

This paper investigates the process discovery conducted using process mining on anonymized logs extracted from the university's departmental application handling system (ISOD) in CSV file format. The study focuses on analyzing the process occurring within the application handling system. Activities and analyses are based on logs from this system. The proper data processing was needed to allow...

21. Application of machine learning in epileptic seizure detection

Kamil Grzegorzewski

The presented work utilizes machine learning methods to solve the problem of detecting epileptic seizures using EEG signals. Epilepsy is one of the most common neurological diseases, affecting millions of people worldwide. This disease has always been of great importance in the field of biomedicine due to the health risks it poses. It is characterized by recurring, unprovoked epileptic...

10. Automated Identification of Malignant Breast Lesions: A Convolutional Neural Network Perspective

Mateusz Kozicki

Accurate diagnosis and prognosis are crucial for the effective treatment of breast cancer. To improve diagnostic accuracy and reduce human error, this study presents a novel approach using deep neural networks (DNNs) to detect cancerous lesions in microscopic specimens from the breast. In this paper, I examine the performance of convolutional neural network (CNN) model as well as CNN-based...

12. Comparison of cardiovascular diseases' classification models based on ECG signal

Kajetan Jeznach

Deep neural networks (DNNs) are becoming a handy tool in the healthcare field. Research work in recent years has led to the creation of solutions that can effectively support the work of medical staff. This paper presents a comparison of deep learning architectures used for the classification of cardiovascular diseases. Models were trained and tested on the PTB-XL dataset, a large publicly...

17. Deciphering AI Black Boxes: A Comparative Review of Python XAI Packages

Bartosz Obstawski, Wojciech Nowicki

As artificial intelligence (AI) systems increasingly penetrate various domains, the need to understand their decision-making processes becomes paramount. This study presents a comprehensive review of Python-based eXplainable AI (XAI) packages aimed at deciphering the black box nature of AI models. By analyzing and comparing prominent XAI techniques and tools, this review sheds light on their...

6. Deepfake Detection: A Comprehensive Analysis of Convolutional Neural Networks

Kamil Kowieski, Kinga Kocoł

In the era of rapidly advancing technology, the spread of deepfake content has become an escalating challenge, making detecting synthetically created materials crucial in softening the potential harms. This paper focuses on a comparative analysis of Convolutional Neural Networks (CNNs) designed explicitly for deepfake detection (MesoNet and MesoNet Inception) with a custom architecture...

13. Exploitation of prototyping network in shelf product recognition

Karolina Gałczyńska

This paper uses a prototyping network to address the problem of recognizing products on store shelves. The problem of identifying store products is similar to the problem of facial recognition. The number of facings is practically unlimited, and new products are introduced every week, current labels are changed, and new product variants are added. Collecting appropriate training patterns is...

19. Eye disease multiclassification based on fundus images

Maciej Dragun

Sense of sight is fundamental in one's life and one can hardly imagine living without it yet in modern times eye diseases can develop relatively early and without timely reaction can lead to severe eyesight degradation or even loss. A means widely used in ophthalmology is fundus photography which can be obtained with relativaly low effort. Their analysis can reveal symptoms of various...

31. Optimization and parallelization of an electromagnetic field FDTD-based solver on asymmetrical 2D grid

Ms Agata Lachowiecka, Mr Maxymilian Kowalski, Patryk Guba

Finite-Difference Time-Domain method of electromagnetic field computation often requires significant amount of time and memory resources, which emphasizes the necessity for the development of high-performance programs. In this paper, we present enhancements to the performance of an electromagnetic field solver using the FDTD method on an asymmetric grid. The improvement in efficiency was...

2. Pathfinding algorithms in dynamic gaming enviroments

Mohamad Al-Tabich

Since the development of advanced gaming engines, pathfinding has evolved into a crucial role in enhancing the complexity and realism of non-player characters (NPCs). This article explores the implementation of the D* algorithm in Unity, a leading solution in game development. It features a comparison of various notable pathfinding algorithms, tested in a generated labyrinth with interactable...

24. Prediction of photovoltaic energy generation using Recurrent and Transformer Neural Networks

Stanisław Świder

Precise prediction of photovoltaic (PV) energy generation is essential for optimal, profitable and ecological management of electric energy resources all over the world. As a result, one attempts to develop more accurate prediction algorithms. This paper compares the application of Long Short-Term Memory (LSTM), a subtype of Recurrent Neural Networks, with Transformer Neural Network for...

30. Pulmonary Hypertension Diagnosis: A Comprehensive Review of AI and Machine Learning Approaches

Agata Biernacka, Mr Kacper Kilianek

Pulmonary hypertension (PH) refers to a group of diseases characterized by elevated blood pressure in the pulmonary arteries supplying the lungs. Accurate diagnosis of PH and determining its underlying causes is crucial but often challenging for physicians. The development of artificial intelligence (AI) techniques may help address this challenge by enhancing the diagnostic process. This paper...

34. Quantum Enhancement of Cryptography

Barbara Gałczyńska, Michał Wyrostkiewicz (Warsaw University of Technology)

Quantum computers promise to revolutionize several fields, including cryptography. In recent years, researchers have made significant progress in developing quantum algorithms that can solve computational problems much faster than classical computers. These advances have led to concerns about the security of traditional cryptography algorithms, as they may be vulnerable to quantum attacks. In...

1. Using Small Language Models For Local Email Categorization Into Variable Number Of User-Defined Labels

Mr Jakub Matłacz (Warsaw University Of Technology, Faculty Of Electrical Engineering)

This paper presents a novel approach, Analyze-Select-Match (ASM), for local email categorization using small language models. The objective is to enable users to organize emails on their local machines by categorizing them into user-defined labels with flexibility in both quantity and quality. A dataset of email samples was curated, and five models, sized for widespread graphics card...

27. Virtualisation of the JetRacer ROS AI KIT platform using a simulation environment

Mr Bartosz Sieracki

Simulation environments perform an important function in modern technical processes. Skillful utilization of such environments reduces testing costs and time associated with implementing solutions, thereby expediting development efforts. This paper focuses on reviewing the application of selected simulation environments for integration with the JetRacer ROS AI KIT mobile platform. This study...