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Publications - 6374

Comparing the aggregation capability of the MPT communications library and multipath TCP

Akos Kovacs

Publication Name: 7th IEEE International Conference on Cognitive Infocommunications Coginfocom 2016 Proceedings

Publication Date: 2017-01-03

Volume: Unknown

Issue: Unknown

Page Range: 157-161

Description:

The MPT network layer multipath communication library-which was proposed to be a possible new basis for the future cognitive info-communication-is capable to use multiple communication channels to create an UDP tunnel which uses GRE tunnel protocol. On the other hand, Multipath TCP uses a special kernel module which creates multiple TCP sub-flows to aggregate network throughput. In this paper we used twelve 100Mbps speed channels to compare the aggregation capabilities of these two multipath communication techniques. Different scenarios were used: we measured both IPv4 and IPv6 as underlying and encapsulation protocols. In all cases, we used one to twelve channels to measure the aggregation capabilities with the iperf network measurement tool and also with HTTP download.

Open Access: Yes

DOI: 10.1109/CogInfoCom.2016.7804542

Dynamic Connectedness Between a Corporate Bond Market With WTI, Geopolitical and Financial Volatility: Spillover From Post-COVID-19 and Russian-Ukrainian Clash

Mohammad Sharif Karimi Kamel Si Mohammed Umer Shahzad

Publication Name: International Journal of Finance and Economics

Publication Date: 2026-04-01

Volume: 31

Issue: 2

Page Range: 2194-2207

Description:

This study investigates the dynamic connectedness between the USA's corporate bond market (CB) and various factors, including WTI, financial uncertainty, and geopolitical risks. We employ two advanced techniques to analyse these relationships: TVP-Vector autoregressive (TVP-VAR) and VAR connectedness. Specifically, we focus on two significant events, the Russian-Ukrainian conflict (RUC) and the COVID-19 pandemic (C19P), to provide insights into the behaviour of the CB during these critical periods against the oil prices and uncertainties. The empirical analysis reveals compelling findings, particularly concerning the extreme events and the magnitude of effects observed. We find a significant increase in interconnections over the time impacts during these two events, lending support to using an asymmetric and heterogeneous product over the time-varying. Furthermore, we observe that the influence of the GPR and the VIX factors is more robust when uncertainty rises rather than decreases, indicating temporary events. Policymakers and macroprudential authorities can benefit from these findings, as they emphasise the need to adapt to a changing monetary policy and reduce reliance on energy volatility to make informed decisions in a rapidly evolving financial landscape.

Open Access: Yes

DOI: 10.1002/ijfe.70037

Telerehabilitation After Brain Injuries: Its Efficacy and Role in Reducing Healthcare Burdens

Tamás Haidegger József Tollár Péter Prukner Istvan Drotar Nándor Prontvai Blanka Törő Szilvia Kóra Petra Kós Gyorgy Wersenyi

Publication Name: Acta Polytechnica Hungarica

Publication Date: 2023-01-01

Volume: 20

Issue: 8

Page Range: 305-320

Description:

Rehabilitation following brain injuries, such as stroke and other traumatic injuries, presents significant challenges for both patients and healthcare systems. Traditional in-person rehabilitation often requires regular visits to specialized facilities, which can be difficult for patients in remote areas or those with mobility and financial constraints. Telerehabilitation offers a promising solution by enabling patients to continue essential therapy at home, ensuring continuity of care while reducing the burden on healthcare providers. It can be effectively applied across various patient groups, including children, adults, the elderly, amputees, individuals with traumatic neurological injuries, and those with neurocognitive impairments such as dementia. Our telemedicine platform integrates advanced technologies, i.e., 3D motion analysis and Virtual Reality (VR) to enhance home-based physiotherapy. These tools enable precise monitoring, real-time feedback, and immersive therapy sessions, in order to improve coordination, fine motor skills, hand-eye coordination, and the vestibular system, which is crucial for balance. This platform also performs detailed offline data analysis, allowing healthcare professionals to adjust therapy plans based on individual needs. As the demand for rehabilitation services continues to grow, adopting these technologies will be crucial for sustainable, effective healthcare, ultimately improving patient outcomes and shaping a more efficient and equitable future for healthcare systems.

Open Access: Yes

DOI: 10.12700/APH.20.8.2023.8.16

Analysis of the application of different production and material flow mechanisms on construction sites

Csaba Tápler

Publication Name: Proceedings 2014 International Conference on Computational Science and Computational Intelligence Csci 2014

Publication Date: 2014-01-01

Volume: 1

Issue: Unknown

Page Range: 241-246

Description:

This paper presents an analysis of the application of material flow control mechanisms at construction sites. Such control mechanisms are widely used in assembly plants to ensure the correct quantity of materials at the correct destination, to maximize the WIP and for various other essential purposes. However the advantages of material flow control mechanisms can be questionable among certain circumstances. I determined the key parameters which influence the success of a certain control mechanism - like kanban - at a construction site. I have built up a general case in which a given control mechanism is applicable. The tool of this analysis was a logistic simulation software. © 2014 IEEE.

Open Access: Yes

DOI: 10.1109/CSCI.2014.48

NREM parasomnia-related behaviors and adverse childhood experiences

Mengesha Srahbzu Biresaw Vivian M. Correa József Vitrai Anna Szűcs

Publication Name: Sleep Medicine

Publication Date: 2024-09-01

Volume: 121

Issue: Unknown

Page Range: 365-369

Description:

Purpose: To assess the prevalence, types, sociodemographic factors, and reported dangerous activities of sleep-related behaviors likely representing NREM parasomnia episodes, as well as their association with adverse childhood experiences in Hungary. Methods: Cross-sectional survey of 1000 adults (aged ≥18 years) representing the Hungarian population, using a non-probability quota sampling with a random walk method and a structured face-to-face interview. A multi-criterion weighting procedure was applied to correct bias along the main sociodemographic variables to the data available. Binary logistic regression estimated the odds of NREM parasomnia-related behaviors associated with sociodemographic factors and adverse childhood experiences. Results: The prevalence of NREM parasomnia-related behaviors was 2.7 %, and self-reported sleep-eating was 0.1 % of the population (4.6 % of parasomnia-like activities). For middle-aged adults, the odds of sleep ambulation were significantly lower than for younger adults (OR 0.3; P = 0.03). A participant's family occurrence of reported parasomnia-like activity increased their odds of having it by more than 7 times (OR 7.1; P < 0.001). Nine participants out of those 27 people reporting NREM parasomnia-related behavior episodes, reported childhood adverse experiences, increasing the odds of parasomnia-related behavior by more than six times (OR 6.2; P < 0.001) compared to those not reporting it. Conclusion: This is the first population survey in Hungary on adult sleep-related behaviors likely representing NREM parasomnia episodes and the potential association with childhood traumatic events preceding them. The related dangerous behaviors call for safety measures and prevention. The significant association between adverse childhood events and NREM parasomnia-related behaviors needs further analysis.

Open Access: Yes

DOI: 10.1016/j.sleep.2024.07.027

Eigenshape based imperfection method for beam-columns with mono-symmetric I-sections

Achim Rubert G. Hajdú

Publication Name: Stahlbau

Publication Date: 2021-08-01

Volume: 90

Issue: 8

Page Range: 600-613

Description:

Eigenshape based imperfection method for beam-columns with mono-symmetric I-sections. This paper shows for the first time the application of the Overall Imperfection Method (OIM) for columns, beams and beam-columns with mono-symmetric I cross-section. The buckling failure mode of compressed members with mono-symmetric I-section is torsional-flexural like. The second-order effect from the rotation around the longitudinal shear axis during the loss of stability is taken into account when the amplitude of the initial imperfection is calculated for the compressed members. For beams, the buckling behaviour is also different from doubly symmetric cross-section because the shear centre and the centre of gravity of the cross-section do not meet at the same position. This paper shows the extension and the usability of the OIM for steel structures with mono-symmetric I-section. The automatic determination of the equivalent amplitudes for columns, beams and beam-columns are presented for the first time. The practicality of the proposed method is demonstrated for single and multi-span members with three examples.

Open Access: Yes

DOI: 10.1002/stab.202100017

Touching reality: Bridging the user-researcher divide in upper-limb prosthetics

J. D. Brown E. Battaglia S. Engdahl G. Levay A. C. Parks M. K. O’Malley E. Skinner

Publication Name: Science Robotics

Publication Date: 2023-10-01

Volume: 8

Issue: 83

Page Range: Unknown

Description:

No description provided

Open Access: Yes

DOI: 10.1126/SCIROBOTICS.ADK9421

The applicability of on-line contextual calibration to a neural network based monocular collision avoidance system on a UAV

Bálint Daróczy Antal Hiba Koppány Pázmán Rita Aleksziev Péter Bauer András Benczúr Ákos Zarándy

Publication Name: IFAC Papersonline

Publication Date: 2019-01-01

Volume: 52

Issue: 11

Page Range: 7-12

Description:

Contextual calibration for object detection is a technique where a pretrained network collects attractive false positives during a calibration phase and use this calibration data for further training. This paper investigates the applicability of this method to a vision based onboard sense and avoid system, which requires intruder aircraft detection in camera images. Various landscape and sky backgrounds were generated by Unreal4 3D engine for calibration tests. Contextual calibration is a promising candidate for handling extreme situations which are not covered well in the training data.

Open Access: Yes

DOI: 10.1016/j.ifacol.2019.09.110

Detection of Bus Driver Mobile Phone Usage Using Kolmogorov-Arnold Networks

Áron Ballagi Szabolcs Fischer Janos Hollosi Gabor Kovacs Viktor Nagy

Publication Name: Computers

Publication Date: 2024-09-01

Volume: 13

Issue: 9

Page Range: Unknown

Description:

This research introduces a new approach for detecting mobile phone use by drivers, exploiting the capabilities of Kolmogorov-Arnold Networks (KAN) to improve road safety and comply with regulations prohibiting phone use while driving. To address the lack of available data for this specific task, a unique dataset was constructed consisting of images of bus drivers in two scenarios: driving without phone interaction and driving while on a phone call. This dataset provides the basis for the current research. Different KAN-based networks were developed for custom action recognition tailored to the nuanced task of identifying drivers holding phones. The system’s performance was evaluated against convolutional neural network-based solutions, and differences in accuracy and robustness were observed. The aim was to propose an appropriate solution for professional Driver Monitoring Systems (DMS) in research and development and to investigate the efficiency of KAN solutions for this specific sub-task. The implications of this work extend beyond enforcement, providing a foundational technology for automating monitoring and improving safety protocols in the commercial and public transport sectors. In conclusion, this study demonstrates the efficacy of KAN network layers in neural network designs for driver monitoring applications.

Open Access: Yes

DOI: 10.3390/computers13090218