• Transfer Learning in Heterogeneous Drug-Target Interaction Predictions Using Federated Boosting 

  Sándor, Dániel; Antal, Péter (2023)

  In multitask federated learning, when small amounts of data are available, it can be harder to achieve proper predictive performance, especially if the clients’ tasks are different. However, task heterogeneity is common ...

• N-Version Programming as a Mitigation for Smart Contract Faults in Execute-Order-Validate Blockchain Systems 

  Péter, Bertalan Zoltán; Kocsis, Imre (2023)

  In this paper, we propose the application of a well-known runtime fault-tolerance technique, N-Version Program-ming (NVP), as a new tool of smart contract software fault mitigation, especially for execute-order-validate ...

• Knowledge-driven Exploratory Performance Data Analysis for Execute-Order-Validate Blockchains 

  Al-Gburi, Noor; Kocsis, Imre (2023)

  Exploratory data analysis (EDA) of the performance characteristics of complex IT systems, such as enterprise blockchain solutions, would significantly benefit from explicit representations of, and inference on knowledge ...

• Handling Uncertainity in Error Propagation Analysis 

  Földvári, András; Pataricza, András (2023)

  Error propagation analysis (EPA) is a systematic model-based approach to assess the impact of incidental or malicious faults in the dependability and security analysis of complex systems. Its main purpose is to estimate ...

• Analyzing the Discriminative Power of EEG Microstates Over Mental Tasks 

  Vetró, Mihály; Hullám, Gábor (2023)

  Microstate analysis of EEG recordings has long been an instrumental tool for studying the temporal dynamics of whole-brain neuronal networks. The characteristics of EEG microstate sequences have been used mostly for ...

• Thoratic Spine Segmentation Based on CT Images 

  Révy, Gábor; Hadházi, Dániel; Hullám, Gábor (2023)

  Automatic vertebrae localization and segmentation in computed tomography (CT) are fundamental for computer-aided detection (CADe) and computer-aided diagnosis (CADx) systems. However, they remain challenging due to the ...

• Behavior of Observer Performing Discrete Gabor Transform 

  Ország, Bence; Sujbert, László (2023)

  The theory of discrete Gabor transforms provides a constructive and interpretable way of creating biorthogonal transforms. These transforms can achieve a non-uniform frequency resolution and they can be implemented recursively ...

• Improving the Convergence Speed of the Resonator-Based Observer by Significant Component Selection 

  Palkó, András; Sujbert, László (2023)

  The resonator-based observer has been developed for measuring the harmonic components of a periodic signal with known fundamental frequency. In certain applications, the signal to be processed is sparse in the frequency ...

• Lazy Abstraction for Probabilistic Systems 

  Szekeres, Dániel; Majzik, István (2023)

  Reliability analysis of complex safety-critical systems by probabilistic model checking is often hindered by state space explosion. Abstraction is one way to counteract this problem. In this paper, we adapt an existing ...

• Towards Automated Worst-Case Analysis of Circuits: Selecting Initial Values for Global Optimization 

  Horváth, Kristóf; Bank, Balázs; Orosz, György (2023)

  Worst-case circuit analysis is a mandatory practice in hardware verification and validation. To this end, several methods, including extreme value analysis (EVA) and Monte Carlo analysis are commonly used, however, each ...

• Integration Test Generation and Formal Verification for Distributed Controllers 

  Graics, Bence; Majzik, István (2023)

  Software-intensive distributed controllers are becoming increasingly prevalent, among others, also in railway interlocking systems (RIS). As such systems carry out critical tasks, their systematic verification and testing ...

• Matchmaking optimisation for car sharing services 

  Sardouk, Firas; Vida, Rolland; Cinkler, Tibor (2023)

  With the continuous growth of our cities it became obvious that personal car ownership is not sustainable on the long run. Personal cars are only used a couple of hours per day, the rest of the time occupying a parking ...

• Utilization of AI in 5G Edge Networks 

  Horváth, Márton Áron (2023)

  As society advances toward the information era, the telecommunications network, a major aspect of this transformation, is undergoing rapid and profound change. Innovative methods, such as Artificial Intelligence (AI), are ...

• Performance simulation of Power over Ethernet on spacecraft buses 

  Skriba, Dániel; Nagy, Lajos (2023)

  This paper presents a waveform level simulation for 100Base-TX Ethernet for performance evaluation on spacecraft power buses. The article starts by explaining the motives behind using Ethernet technology on spacecrafts. ...

• Power Optimization of Massive MIMO Using Quantum Genetic Algorithm 

  Almasaoodi, Mohammed; Sabaawi, Abdulbasit; El Gaily, Sara; Imre, Sándor (2023)

  The massive Multiple-Input Multiple-Output (MIMO) is key enabling technology for the 5G and 6G cellular technologies, which allows dramatically improving the energy efficiency of the network, as well as increasing the ...

• Implementing a Text-to-Speech synthesis model on a Raspberry Pi for Industrial Applications 

  Mandeel, Ali Raheem; Aggar, Ammar Abdullah; Al-Radhi, Mohammed Salah; Csapó, Tamás Gábor (2023)

  Text-to-Speech (TTS) produces human-like speech from input text. It has recently acquired prominence by applying deep neural networks. Nowadays, end-to-end TTS models produce highly natural synthesized speech but require ...

• The development of a soil-movement measurement system to create more precise numeric soil models 

  Wágner, Árpád; Szabó, Bence; Kovács, László; Tamás, Kornél; Grad-Gyenge, László (2023)

  A well developed and industrialized agriculture system is one of the bases of our modern society, but it introduces a problem, as it also is a large contributor to climate change. Even only the use of unoptimized tools in ...

• Is Dynamic Time Warping of speech signals suitable for articulatory signal comparison using ultrasound tongue images? 

  Csapó, Tamás Gábor (2023)

  In speech technology, the examination of speaker dependency is vital - that is, whether methods developed for one speaker can be adapted to another speaker or not. In the case of text-to-speech synthesis, well-usable speaker ...

• Improving Naturalness of Neural-based TTS System Trained with Arabic Limited Data 

  Sawalha, Layan; Alradhi, Mohammad (2023)

  In this paper, we investigated different approaches, a neural network speech synthesis system and a non-autoregressive text-to-speech (TTS) model. In the neural network speech synthesis, we showed how a baseline system ...

• A Comparison of Data Augmentation Methods on Ultrasound Tongue Images for Articulatory- to-Acoustic Mapping towards Silent Speech Interfaces 

  Ibrahimov, Ibrahim; Gosztolya, Gábor; Csapó, Tamás Gábor (2023)

  Silent Speech Interfaces (SSI), being a subfield of speech technology, break the limitations of automatic speech recognition when acoustic signals cannot be produced or clearly captured. SSI focuses on the articulation ...

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