http://hdl.handle.net/20.500.14044/33806 2026-07-26T15:35:41Z 2026-07-26T15:35:41Z Guzsvinecz, Tibor http://hdl.handle.net/20.500.14044/31993 2025-09-17T14:32:13Z 2025-01-01T00:00:00Z

The Effects of Display Devices on Locating Sound Sources in Virtual Environments Guzsvinecz, Tibor Sound localization plays a crucial role in both real and virtual environments, particularly for effective navigation. Naturally, this ability can be affected by various factors. To understand how it is influenced, the sound localization skills of 110 students were measured within a virtual environment. Two versions of this virtual space were created, and all students used both. The desktop display version was used first, then the Gear VR version was used afterward. A Sony PlayStationTM Platinum Wireless headset was used on both versions. The results were grouped and examined by various human characteristics and display devices. According to the results, the following conclusions can be made: gender influenced sound localization, since males outperformed females using the desktop display, but not with the Gear VR. This was due to significant accuracy improvements for females with the mentioned head-mounted display. Previous virtual reality experience improved accuracy and speed with the Gear VR. The proportions of incorrect localizations differed significantly between the two versions, indicating that the immersion level affects them. These results can affect the design and implementation processes of future virtual reality experiences, in several fields of research and entertainment.

2025-01-01T00:00:00Z Abbas, Sayyed Khawar Szabó, Zoltán Kő, Andrea http://hdl.handle.net/20.500.14044/31990 2025-09-17T14:32:00Z 2025-01-01T00:00:00Z

Robo-Advisors in Fintech-Challenges and Solutions Abbas, Sayyed Khawar; Szabó, Zoltán; Kő, Andrea The banking sector has experienced substantial transformations as a result of the proliferation of financial technology, commonly known as FinTech. The introduction of these breakthroughs has caused a transition from conventional banking to digital services, bringing forth a range of developments like AI platforms, Blockchain technology, virtual currencies, Robo-advisors, and chatbots. Despite the speedy and easy services offered by FinTech, there are still difficulties regarding trust, security, and data privacy, particularly in nations such as Pakistan. This study explores the integration of Robo-advisors within Pakistan's FinTech sector, focusing on the challenges of trust, security, and data privacy. Chatbots, playing a crucial role in the banking and telecom industries, encounter challenges such as customer skepticism and the potential for cybersecurity threats. Using Grounded Theory and Social Representation Theory (SRT), the study comprehensively examines how chatbots and Robo-advisors in the Pakistani FinTech industry address these challenges. The findings indicate that establishing trust, guaranteeing data security, and enhancing user experience are of utmost importance. Transparent communication, robust security measures, and user-centric design have been identified as critical for building trust and driving adoption. Collaboration with financial professionals, continuous innovation, and user education emerge as crucial answers. The study highlights the significance of transparency and adherence to regulations, while proposing future research avenues to investigate the psychological aspects influencing the adoption of FinTech and the effects of developing technologies. These insights contribute to the growing discourse on FinTech innovation and its potential to enhance financial inclusion in developing economies.

2025-01-01T00:00:00Z Szabó, Mihály Fodor, Szabina http://hdl.handle.net/20.500.14044/31989 2025-09-17T14:31:43Z 2025-01-01T00:00:00Z

Assessing the Limits of Simple Quantum Hardware Szabó, Mihály; Fodor, Szabina Although quantum computing is advancing rapidly, ensuring the accuracy and reliability of the computations available to quantum computer researchers is still a challenge today. This paper reviews the main directions of quantum error correction (QEC) techniques that can potentially be applied in superconducting qubit computers. We present the Mermin- Peres magic square game, where the quantum strategy has theoretical advantages over classical and can provide a benchmark solution for testing the accuracy of quantum computation. In the experimental part of our work, we run the algorithm of the Mermin-Peres magic square game on IBMQ quantum computers accessible via the cloud. Our experimental results failed to demonstrate a proven quantum advantage of the game on the noisy intermediate-scale quantum (NISQ) hardware tested, confirming the inevitable need to implement error correction techniques on physical qubits. By aligning with the Digital and Cognitive Corporate Reality (DCR) theme, this research seeks to inform business strategies incorporating emerging quantum technologies

2025-01-01T00:00:00Z Füstös, Gergely Forstner, Bertalan http://hdl.handle.net/20.500.14044/31985 2025-09-17T14:31:29Z 2025-01-01T00:00:00Z

Data Synthesis and Simulation for Modeling Cognitive Abilities Füstös, Gergely; Forstner, Bertalan Recent advancements in the methodology of cognitive assessment and development rely on various cognitive models. Determining the underlying abilities tapped by individual tasks involves different procedures, which presuppose dependencies on specific subskills, considerations of statistical distributions, and a substantial amount of measurement data for accurate estimation of latent factors. Addressing these bottlenecks, various deep learning (DL) models show promising performance. Despite their initial success, it is evident that DL models are hindered by the requirement for significant quantities of annotated and labeled data to experiment and refine these models. Synthetic data offer a solution to this challenge by being easily generated, error-free, inexhaustible, pre-annotated, and circumventing various ethical and practical concerns. The past decade has witnessed remarkable progress in data synthesis and domain adaptation techniques, narrowing the statistical gap between synthetic and real data. Beyond sustaining the DL revolution, synthetic data will pave the way for the next generation of DL models, capable of understanding the physical composition of the world and learning continually, multimodally, and interactively. This paper clarifies the models emerging from prevalent cognitive models, statistical methodologies, and psychometric research regarding the subjects and their subskills, as well as how to model the parameter and subskill dependencies of individual tasks independent of the limitations posed by current solutions. Building upon these insights, an environment for data synthesis and simulation is developed, suitable for validating various analysis solutions.

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