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Found 6407 publications

Reliability Assessment of Reinforced Concrete Beams under Elevated Temperatures: A Probabilistic Approach Using Finite Element and Physical Models

János Szép János Lógó Majid Movahedi Rad Muayad Habashneh

Publication Name: Sustainability Switzerland

Publication Date: 2023-04-01

Volume: 15

Issue: 7

Page Range: Unknown

Description:

A novel computational model is proposed in this paper considering reliability analysis in the modelling of reinforced concrete beams at elevated temperatures, by assuming that concrete and steel materials have random mechanical properties in which those properties are treated as random variables following a normal distribution. Accordingly, the reliability index is successfully used as a constraint to restrain the modelling process. A concrete damage plasticity constitutive model is utilized in this paper for the numerical models, and it was validated according to those data which were gained from laboratory tests. Detailed comparisons between the models according to different temperatures in the case of deterministic designs are proposed to show the effect of increasing the temperature on the models. Other comparisons are proposed in the case of probabilistic designs to distinguish the difference between deterministic and reliability-based designs. The procedure of introducing the reliability analysis of the nonlinear problems is proposed by a nonlinear code considering different reliability index values for each temperature case. The results of the proposed work have efficiently shown how considering uncertainties and their related parameters plays a critical role in the modelling of reinforced concrete beams at elevated temperatures, especially in the case of high temperatures.

Open Access: Yes

DOI: 10.3390/su15076077

A Risk Assessment Technique for Energy-Efficient Drones to Support Pilots and Ensure Safe Flying

Péter Földesi Szabolcs Fischer Mykola Sysyn Dmytro Kurhan Szabolcs Kocsis Szurke Norbert Perness

Publication Name: Infrastructures

Publication Date: 2023-04-01

Volume: 8

Issue: 4

Page Range: Unknown

Description:

Unmanned Aerial Vehicles, also known as UAVs, play an increasingly important part in daily life. However, the ever-increasing number of UAVs pose an ever-increasing threat to the transportation infrastructure. Despite their precision and general efficiency, infrastructural-scale Unmanned Aerial Systems (UASs) have a disadvantage regarding their capability of being implanted in the ecosystem. There are several reasons for this, but the primary bottleneck is that their systems are not transparent to society and have very complicated processes. As a result, the authors decided to investigate the functional properties of UASs and make improvements to those properties. Throughout the study, the authors’ primary focus was on analysis, which boosts productivity and ensures a significant level of safety for routine flights. The amount of power that a UAV uses depends on several variables, including the amount of power that its individual components require, the temperature of its surroundings, and the condition of the battery that it is powered by. Therefore, critical parameters and interdependencies are taken into account in the risk assessment strategy for energy-efficient Unmanned Aerial Vehicles (UAVs). In the case of UAVs, the algorithm performs a risk calculation before take-off to estimate the amount of risk that can be associated with the given flight time when using the provided battery. On the one hand, several instances of the pre-take-off state and how its parameters interact are investigated. On the other hand, they demonstrate the calculation of the risk while in flight, which is based on actual flight data.

Open Access: Yes

DOI: 10.3390/infrastructures8040067

Flower Pollination Algorithm on optimal design of space trusses

Edina Koch Majid Movahedi Rad Shaymaa Alsamia

Publication Name: International Review of Applied Sciences and Engineering

Publication Date: 2025-10-13

Volume: 16

Issue: 3

Page Range: 418-427

Description:

Abstract: This study assesses the performance of four nature-inspired optimization algorithms—Dynamic Differential Annealed Optimization (DDAO), Flower Pollination Algorithm (FPA), Firefly Algorithm (FF), and Particle Swarm Optimization (PSO) for achieving optimal space truss design. The aim is to minimize the structural weight of three benchmark trusses (10-bar, 25-bar, and 72-bar) while meeting stress and displacement constraints. The key contribution of this work is the first systematic evaluation of FPA in space truss optimization, demonstrating its greater effectiveness in obtaining optimal or near-optimal solutions with faster convergence and higher stability compared to PSO and FF. The results also highlight the limitations of DDAO in handling constrained engineering problems. Findings confirm that FPA and FF are highly effective for structural optimization, offering robust solutions with minimal computational cost. These insights contribute to advancing metaheuristic-based structural design, supporting the adoption of FPA in large-scale optimization problems.

Open Access: Yes

DOI: 10.1556/1848.2025.00958

Generalised weighted relevance aggregation operators for hierarchical fuzzy signatures

János Botzheim B. Sumudu U. Mendis Tamás D. Gedeon Laszlo T. Koczy

Publication Name: Cimca 2006 International Conference on Computational Intelligence for Modelling Control and Automation Jointly with Iawtic 2006 International Conference on Intelligent Agents Web Technologies

Publication Date: 2006-01-01

Volume: Unknown

Issue: Unknown

Page Range: Unknown

Description:

Hierarchical Fuzzy Signatures are generalizations of the Vector Valued Fuzzy Set concept introduced in the 1970s. A crucial question in the Fuzzy Signature context is what kinds of aggregations are applicable for combining data with partly different substructures. Our earlier work introduced the Weighted Relevance Aggregation method to enhance the accuracy of the final results of calculations based on Hierarchical Fuzzy Signature Structures. In this paper, we further generalise the weights and the aggregation into a new operator called Weighted Relevance Aggregation Operator (WRAO). WRAO enhances the adaptability of the fuzzy signature model to different applications and simplifies the learning of fuzzy signature models from data. We also show the methodology of learning these aggregation operators from data. © 2006 IEEE.

Open Access: Yes

DOI: 10.1109/CIMCA.2006.110

Area of Interest Tracking Techniques for Driving Scenarios Focusing on Visual Distraction Detection

Péter Földesi György Istenes Viktor Nagy

Publication Name: Applied Sciences Switzerland

Publication Date: 2024-05-01

Volume: 14

Issue: 9

Page Range: Unknown

Description:

On-road driving studies are essential for comprehending real-world driver behavior. This study investigates the use of eye-tracking (ET) technology in research on driver behavior and attention during Controlled Driving Studies (CDS). One significant challenge in these studies is accurately detecting when drivers divert their attention from crucial driving tasks. To tackle this issue, we present an improved method for analyzing raw gaze data, using a new algorithm for identifying ID tags called Binarized Area of Interest Tracking (BAIT). This technique improves the detection of incidents where the driver’s eyes are off the road through binarizing frames under different conditions and iteratively recognizing markers. It represents a significant improvement over traditional methods. The study shows that BAIT performs better than other software in identifying a driver’s focus on the windscreen and dashboard with higher accuracy. This study highlights the potential of our method to enhance the analysis of driver attention in real-world conditions, paving the way for future developments for application in naturalistic driving studies.

Open Access: Yes

DOI: 10.3390/app14093838

Using Machine Learning Models to Predict and Reduce Noise Levels in Gear Systems

Ambrus Zelei Krisztián Horváth

Publication Name: Advances in Science and Technology

Publication Date: 2025-01-01

Volume: 165 AST

Issue: Unknown

Page Range: 215-221

Description:

Machine learning models are effective tools for predicting and reducing noise levels in industrial gear systems. In this study, we compare different machine learning methods to investigate the effects of different gear modification parameters on noise levels. Four different predictive models was used. Random Forest Regressor, XGBoost, Gradient Boosting Machines and neural network. The study concluded that Random Forest and Gradient Boosting Machines models were the most effective. Both models achieved low mean squared error values 6.10 and 6.67. Further tests with synthetic data confirmed the stability of these models. Current sustainability trends show that the integration of machine learning into industrial applications fits well with manufacturers' objectives. However, it is currently challenging to determine which machine learning methods are most effective in optimizing noise reduction. This paper seeks to address this gap by comparing the accuracy and reliability of these models. Based on the results, the use of machine learning models is recommended to reduce noise levels in geared systems.

Open Access: Yes

DOI: 10.4028/p-0GDArj

Optimal Sensor Placement for Autonomous Formula Student Vehicles: A Field-of-View Analysis of Dual LIDAR and Stereo Camera Configurations †

Zoltan Pusztai László Illés Orova Máté Kapocsi

Publication Name: Engineering Proceedings

Publication Date: 2025-01-01

Volume: 113

Issue: 1

Page Range: Unknown

Description:

The optimal configuration of perception systems in autonomous vehicles is essential for accurate environmental sensing, precise navigation, and overall operational safety. In Formula Student Driverless (FSD) vehicles, sensor placement is particularly challenging due to the compact design constraints and the highly dynamic nature of the racing environment. This study investigates the positioning and configuration of two LIDAR sensors and a stereo camera on an FSD race car, focusing on field-of-view coverage, sensing redundancy, and sensor fusion potential. To achieve a comprehensive evaluation, measurements are conducted exclusively in a simulation environment, where field-of-view maps are generated, detection ranges are analyzed, and perception reliability is assessed under various conditions. The results provide insights into the optimal sensor arrangement that minimizes blind spots, maximizes sensing accuracy, and enhances the efficiency of the autonomous vehicle’s perception architecture.

Open Access: Yes

DOI: 10.3390/engproc2025113027

How Can a Household Reduce its Ecological Footprint? - An Example from Hungary

Gabor Harangozo Zoltán Major Cecilia Szigeti Egedy Tamás

Publication Name: Acta Polytechnica Hungarica

Publication Date: 2026-01-01

Volume: 23

Issue: 6

Page Range: 67-83

Description:

Literature extensively uses ecological footprint accounts to measure the natural resource use of human consumption patterns. Beyond national-level accounts, there is a wide range of literature on calculating ecological footprints at the sub-national, regional, or even micro level. However, there seems to be surprisingly little research on how different urban neighborhoods relate to each other in terms of their ecological footprint. The study employs a literature review and the results of an ecological footprint calculation based on the input-output methodology to investigate what households can do to reduce their ecological footprint in various urban neighborhoods. Furthermore, this study builds on the gap that earlier research has uncovered that different households in different neighborhoods consume in different ways, however, complex estimates of reduction opportunities have not been carried out. The results indicate that the choice of housing is the most important intervention point. This has an impact on available transport options, heating types, and food choices. The research results indicate significant potential for reducing the ecological footprint by promoting individual motivation (e.g., the use of public transport) and developing a policy support system (e.g., incentives for energy-efficient investments). Every household has the potential to reduce its ecological footprint, but the methods to achieve this may differ. The greatest impact is expected from modernizing heating, but using public transport and switching to a plant-based diet can also be effective. The research results indicate that the ecological footprint values of different dwelling types are similar, but the potential for reduction varies. It seems encouraging that sustainability appears to be an important issue for young people, but positive scenarios may be threatened by the fact that they feel less inclined to make significant changes in their behavior that would reduce their ecological footprint.

Open Access: Yes

DOI: 10.12700/aph.23.6.2026.6.5

The Impact of Social Media Relationships on e-WOM in Syria and Hungary

Anikó Tompos Jawad Abo Khair

Publication Name: Review of Applied Socio Economic Research

Publication Date: 2023-06-29

Volume: 25

Issue: 1

Page Range: 52-65

Description:

Cultural values play a crucial role in the formation of individuals’ behaviour. With the emergence of social networking sites, which have formed a parallel world to the real world, the behaviour of individuals and their motives to engage in electronic word of mouth (eWOM) on social media platforms has become extremely important for brands. Due to a relative lack in studies focusing on the cultural differencebased impact of social relationships on eWOM in social media, the present study seeks to address this gap as its broad objective is to investigate the effect of social relationship variables on eWOM in social media by comparing two different cultures, namely Syria and Hungary in order to explore whether social relationships exert a more significant impact on eWOM in a collectivistic society than in an individualistic one. An explanatory research design was adopted and the data was collected by means of a questionnaire survey. The final sample included 113 Syrian and 90 Hungarian respondents, all of them aged 35 or below. It was found that tie strength among young adults has a more positive impact on eWOM in Syria than in Hungary, while no homophily impact was found on eWOM in either. Regarding the other social relationship variables examined in the study (trust, normative and informational influences), the results showed that they do not have a more positive impact on eWOM in Syria than in Hungary. The research is believed to have contributed to previous investigations on the impact of social relationships on eWOM via social media by providing insights into the role of a cultural value dimension in determining the extent to which individuals are affected by their cultural background, whether collectivistic or individualistic, when they interact in social media platforms. At the same time, it is acknowledged that the study has limitations thus future examinations are necessary.

Open Access: Yes

DOI: 10.54609/reaser.v25i1.335