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Found 6374 publications

Dynamic Vehicle Dashboard Design for Reduced Driver Distraction

Viktor Nagy Ágoston Pál Sándor

Publication Name: Mechanisms and Machine Science

Publication Date: 2025-01-01

Volume: 174 MMS

Issue: Unknown

Page Range: 645-654

Description:

In the context of contemporary vehicle dashboard systems, advanced In-Vehicle Information Systems (IVIS) often employ touchscreen functionalities, and multi-layered menu structures. However, these solutions have been identified as more distracting for drivers compared to traditional tactile switches and buttons with single, dedicated functions. Our primary focus is on exploring the design capabilities of dynamic vehicle center console interfaces, leading to the inception of the Dynamic Human-Computer Interface System (DHCIS). DHCIS employs a context-aware, adaptive functional framework structure, which, rather than relying on deep menu layers, enhances the safety level in varied traffic situations by simplifying controls to one-touch features. The design concept has been compared with a generic user interface in terms of the handling method, operational steps and layout design.

Open Access: Yes

DOI: 10.1007/978-3-031-80512-7_63

Migration Models Based on Diffusion and Determinants Gradients: Beyond the Gravity Theory

Laszlo Vasa Petro Martyniuk Halyna Mishchuk Slavka Silberg Petro Martyniuk

Publication Name: European Journal of Interdisciplinary Studies

Publication Date: 2025-01-01

Volume: 17

Issue: 2

Page Range: 33-43

Description:

The article proposes an alternative approach to study migration flows based on gravity models. This approach does not reject gravity theory; on the contrary, it expands it to some extent. The relevant models are suggested to be described using diffusion-convection approaches. The intensity of human flows is proposed to identify on the basis of determinant gradients, and the very structure of the domain for studying these processes can be represented as a graph with nodes in the form of continuous areas of social space. The proposed approach is suitable for different dimensions of mobility studying, i.e. permanent migration decisions, touristic flows, academic mobility, transportation etc. The developed conceptual approach and mathematical formalization allow for understanding the patterns of migration applying fundamental principles of mathematic physics for economic processes.

Open Access: Yes

DOI: 10.24818/ejis.2025.12

Possibilities for Further Development of the Airbags in the Case of Non-conventional Seating Positions

I. Lakatos Laszlo Porkolab

Publication Name: Periodica Polytechnica Transportation Engineering

Publication Date: 2025-01-01

Volume: 53

Issue: 2

Page Range: 146-157

Description:

The first ideas and experiments aimed at protecting passengers from the vehicle’s internal components with airbags date back to the 1960s. Twenty years later, the airbag appeared in series production, in December 1980, the Mercedes-Benz S-Class (W126) was the first serial production car to be equipped with a driver airbag, and since its introduction, the use of airbag technology has been uninterrupted. Airbag systems are currently regarded as almost mandatory protection systems in a vehicle. The article generally presents the development of airbags used in cars, followed by the currently used airbag folding types. After that, the article presents the simulation of the airbag deployment, its types and theoretical background, as well as the most important stages of the deployment of the airbag. In the following, the article presents the results of the research so far in the case of frontal and side crashes. The next section of the article introduces the materials capable of absorbing energy, then details the simulation model built and the airbag concept created. The last part of the article contains an evaluation of the results and the summary. The modified seat examined in the earlier phase of the research and the airbag concept that is the subject of this research also fulfill the set goals, but the latter has a great advantage.

Open Access: Yes

DOI: 10.3311/PPtr.38633

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

Mindful eating under pressure in combat sport: a single-case study of an adolescent athlete

Zekihan Hazar Kürşat Hazar Merve Alpay Réka Erika Kovács Szilvia Boros

Publication Name: Frontiers in Psychology

Publication Date: 2025-01-01

Volume: 16

Issue: Unknown

Page Range: Unknown

Description:

Objectives: The purpose of this study was to examine closely how mindful eating intervention influences the eating behavior of a kickboxer 10 days before the competition. Methods: A mindful intervention was conducted. A mixed method was used, in which data was collected from two semi-structured interviews and four scales [Eating Attitudes Test (EAT-26), Eating Disorder Examination Questionnaire (EDE-Q), Dutch Eating Behavior Questionnaire (DEBQ), and Mindful Eating Scale (MEQ-30)]. The first semi-structured interview and four scales were administered before the intervention process, and the last interview was conducted after the competition. 10 days before the competition, 10 sessions of “mindful raisin eating” exercise, each lasting 10 min, were performed. The scores obtained from the scales were calculated manually. The data collected from semi-structured interviews were analyzed using the descriptive analysis method. Results: According to the administered 4 scales initially, the athlete’s average scores were (X̄=16) on the Eating Attitude Test (EAT-26), (X̄=3.125) on the “shape concern” sub-dimension of the Eating Disorder Examination Questionnaire (EDE-Q), (X̄=4) on the Emotional Eating sub-dimension of the Dutch Eating Behavior Questionnaire (DEBQ), and (X̄=2.5) on both the “awareness” and “eating control” sub-dimensions of the Mindful Eating Questionnaire (MEQ-30). Qualitative data showed, positive improvements were detected in eating attitudes and behaviors, stress management, perceived performance, and body image, respectively. During the mindful eating exercises, she lost approximately 2.4 kg (~3.9% of her body weight) without experiencing stress on weigh-in day. She also reported that focusing on mindful eating helped her avoid unhealthy foods and made her feel safe and calm. Conclusion: It was stated by the athlete that there were positive improvements in eating attitudes and behaviors, level of coping with stress, perceived performance and body perception.

Open Access: Yes

DOI: 10.3389/fpsyg.2025.1624709

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

Investigating the Impact of Environmental Factors on Autonomous Vehicle Sensors †

Janos Hollosi Dániel Csikor Ferenc Szauter

Publication Name: Engineering Proceedings

Publication Date: 2025-01-01

Volume: 113

Issue: 1

Page Range: Unknown

Description:

The operation of autonomous vehicles requires the coordinated operation of a number of sensors to improve road safety. Data from the sensors are processed by vehicle control algorithms, which then make decisions. If there is a degradation in the efficiency of these sensors, the reliability of the whole system is affected. Different weather conditions affect the efficiency of the system. The research has identified the weather factors that affect the performance of the sensors based on a literature search. Following the literature analysis, a simulation test was carried out to investigate the extent to which the detection performance of a stereo video camera installed in an experimental autonomous vehicle is affected when part of the sensor is covered by a contaminant. The measurement was followed by a comparison of the vehicle and obstacle detection efficiency when the camera is completely clean and when part of the camera is covered.

Open Access: Yes

DOI: 10.3390/engproc2025113015

Different Breeding Values Under Uniform Environmental Condition for Milk Production Yield Traits in Holstein-Friesian Cows

Szabolcs Bene László Bognár Zsolt J. Kőrösi Ferenc Szabó István Anton

Publication Name: Animals

Publication Date: 2025-01-01

Volume: 15

Issue: 1

Page Range: Unknown

Description:

In this study, 1,616,549 Holstein-Friesian females were genotyped for genomic evaluation of genetic merit (BVGenomic). Genotyping was performed using the EuroGenomics MD v3.0 chipset on the Illumina microarray scanner platform operated by an accredited Illumina laboratory. In addition, international and national reference populations were used for traditional BLUP breeding value (BV) estimation for both individuals (BVBLUP) and parents (BVPedigree). A single-step BLUP animal model was used for this estimation. A sample of 190 first lactation progeny cows from a single herd, reared and kept under consistent environmental conditions, was used to validate the three types of BV estimation methods. Correlation and regression analysis were used to study the association between the phenotypic performance and the results of three different estimation models. The average production of the 305-day standard lactation was 10,910.5 kg milk, 397.86 kg butterfat and 365.33 kg protein. Comparative analyses showed that BVBLUP had the highest accuracy, followed by BVGenomic, while BVPedigree was the least reliable, R2 = 0.37 to 0.48; 0.09 to 0.23; 0.02 to 0.06, respectively.

Open Access: Yes

DOI: 10.3390/ani15010051

Beyond Lithium: Evaluating Sodium-Ion Batteries for the Next Generation of Electric Vehicles †

Peter Gulyas

Publication Name: Engineering Proceedings

Publication Date: 2025-01-01

Volume: 113

Issue: 1

Page Range: Unknown

Description:

Sodium-ion batteries (SIB) are gaining attention as a sustainable, cost-effective alternative to lithium-ion technology in electric vehicles (EVs), driven by concerns over lithium’s scarcity, high costs, and environmental impact. This study explores the feasibility of SIBs through a theoretical analysis of recent advancements in chemistry, materials, and electrochemical performance. It compares key factors such as energy density, charge cycles, safety, cost-effectiveness, and supply chain sustainability. While sodium-ion batteries currently offer lower energy density and shorter cycle life, they benefit from abundant raw materials and more sustainable production. Recent breakthroughs in electrode and electrolyte design show promise for improved efficiency and longevity. Sodium-ion technology is not yet a full replacement for Li-ion batteries but presents a viable option for low-cost EVs and stationary storage.

Open Access: Yes

DOI: 10.3390/engproc2025113041