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Found 6374 publications
Coping strategies for financial problems: Based on Hungarian data from the OECD 2022 annual report
Publication Name: International Journal of Innovative Research and Scientific Studies
Publication Date: 2025-01-01
Volume: 8
Issue: 4
Page Range: 407-418
Description:
The aim of this study is to explore the role of demographic factors in strategies to address financial problems, based on data from the OECD Financial Literacy Survey 2022 in Hungary. The analysis focused on differences in age, gender, type of residence, income, and region. The research used multivariate statistical methods, such as canonical correlation analysis and Ridge regression, to identify associations between demographic factors and financial behavior. The results showed that region and age are the most significant determinants of financial strategy choice, while education and income have a smaller impact. Residents in Budapest showed higher financial awareness and more diversified strategies compared to a more traditional approach for rural residents. The results suggest the development of targeted financial education programs that take demographic and regional differences into account, thus supporting the enhancement of financial stability.
Open Access: Yes
Analysis Of The Relation Between Vehicle And Physiological Data
Publication Name: Transportation Research Procedia
Publication Date: 2025-01-01
Volume: 91
Issue: Unknown
Page Range: 369-376
Description:
Understanding driver behavior and state is crucial for enhancing road safety, yet traditional assessment methods often lack the granularity of real-world dynamics. This paper introduces the Automated Driving Data Analyzer II (ADDA II), an onboard system evolving from a simulator-based tool to a comprehensive platform for real-world driving data acquisition and analysis. Interfacing via the OBD-II port and offering ECU (Engine Control Unit) compatibility (initially validated with Volkswagen Group vehicles), ADDA II is designed for both scientific research and as an accessible end-user product. The system integrates multimodal data streams, including detailed vehicle dynamics, driver physiological responses (e.g., heart rate), and eye-tracking metrics (blinks, fixations), all synchronized to provide a holistic view of the driving task. This paper demonstrates ADDA II’s architecture and analytical capabilities using a representative real-world dataset from a multi-stage driving task. The analysis showcases the system’s ability to characterize driving styles (identifying, for instance, a ‘Conservative’ profile based on smooth control and adaptive behaviors) and reveal patterns indicative of driver state. Key insights are derived from correlating vehicle speed with heart rate to infer variations in physiological arousal and cognitive load across different environments, and by linking heart rate with ocular fixation patterns to understand visual attention strategies under varying demands. Furthermore, ADDA II incorporates functionalities for real-time feedback and warnings, aiming to promote safer, more sustainable driving practices and enhance driver self-awareness. The presented findings underscore ADDA II’s significant potential as a tool for advancing research in driver state monitoring and developing effective driver support applications.
Open Access: Yes
Eco-friendly strategic goals and the performance of innovative green processes: The impact of green intellectual capital
Publication Name: International Journal of Innovative Research and Scientific Studies
Publication Date: 2025-01-01
Volume: 8
Issue: 1
Page Range: 191-201
Description:
The purpose of this study is to check the intellectual capital's role in shaping green process innovation. This article contends the company's capacity to create, possess, incorporate, and implement environmentally friendly intellectual assets in its activities will result in a higher degree of performance in terms of innovative green processes. This performance serves as an indicator of the company's enduring dedication to an environmentally conscious strategy. The industries chosen for this study comprised textile, chemical, pharmaceutical, and steel based in Mexico. The random sampling technique was used to gather data. Upon analyzing the gathered data, we used only 253 questionnaires for analysis, representing a response rate of 42.7%. Findings indicate green strategic intent significantly influences three components of intellectual capital: human, relational, and organizational capital. Three components of intellectual capital significantly influence green process innovation. A green strategy can be successfully implemented by the implementation of intangible resources. Mere tangible resources are insufficient to gain superior green innovation performance; the interaction of these two resources (tangible and intangible) is complementary. Companies are adopting environmental strategies to mitigate the environment's harmful impact and meet stakeholders' demands. The study’s practical implications aim to improve companies’ environmental performance, specifically their green performance, through the implementation of green innovation.
Open Access: Yes
Opportunities for Pulse-Based Diagnostics in Electric and Hybrid Vehicle Batteries
Publication Name: 2025 19th International Conference on Electrical Machines Drives and Power Systems Elma 2025 Proceedings
Publication Date: 2025-01-01
Volume: Unknown
Issue: Unknown
Page Range: Unknown
Description:
This study investigates pulse-based diagnostic methods for identifying faulty cells within lithium-ion battery packs in electric and hybrid vehicles. Diagnostic measurements were conducted using a fully electric Volkswagen e-Golf under both dynamic driving (WLTP) and laboratory-based Hybrid Pulse Power Characterization (HPPC) test conditions. Voltage deviations among individual battery cells were analyzed to evaluate system reliability under constant load, peak load, and regenerative braking scenarios. Results revealed that peak load conditions provided the most informative insights for fault detection due to fewer but more significant voltage deviations. In contrast, constant load and regenerative braking conditions frequently exhibited minor deviations. These findings suggest that transient, high-current events are particularly valuable for early identification of cell degradation and faults. Future studies should further investigate the long-term relationships between detected deviations and overall battery health to enhance predictive diagnostics and optimize battery management strategies.
Open Access: Yes
Effect of Printing Parameters on the Tensile Mechanical Properties of 3D-Printed Thermoplastic Polyurethane †
Publication Name: Engineering Proceedings
Publication Date: 2025-01-01
Volume: 113
Issue: 1
Page Range: Unknown
Description:
Thermoplastic polyurethane (TPU) filament was used to fabricate specimens through material extrusion (MEX)-based 3D printing technique with varying printing parameters. Nozzle diameters of 0.4 mm and 0.8 mm were used, while the printing infill orientation (also denoted as raster angle) was either parallel (0°) to the length of the specimens, perpendicular to it (90°), or at a 45° angle with alternating direction in each layer (±45°). Tensile tests were conducted to determine tensile strength, Young’s modulus, and elongation at break of the samples. The highest tensile strength was achieved using a 0.8 mm nozzle diameter and 0° raster angle, reaching 32.5 MPa, with a corresponding Young’s modulus of 145.8 MPa. Meanwhile, the sample with the lowest modulus (100.4 MPa) and tensile strength (17.8 MPa) was the one 3D-printed with a 0.4 mm nozzle and 90° raster angle.
Open Access: Yes
Extended Measurement Methods for Onboard Detection of Brake Disc Deformation †
Publication Name: Engineering Proceedings
Publication Date: 2025-01-01
Volume: 113
Issue: 1
Page Range: Unknown
Description:
Runout is a common failure of brake discs. The detection of this fault usually depends on the driver, as there is a vibration in the car and on the brake pedal. As Advanced Driver Assistant Systems are implemented and autonomous driving modes are available, braking is carried out by the car instead. Brake disc runout can cause longer braking distance, so it is essential to recognize and repair it. NVH measurements have been validated to be one of the solutions to detect the fault immediately without disassembling the brake unit. In this article, the previous vibration measurements are extended with other methods that can also be used for fault detection. Brake fluid pressure measurement and integration of the disc rotation angle sensor enable the detection of faults without additional sensors. The aim of the research is to design a measurement method that can be compared with previously validated measurements.
Open Access: Yes
Where Do Pedestrians Look, When Crossing Suburban Railway Lines with Right- and Left-Hand Traffic?
Publication Name: Lecture Notes in Networks and Systems
Publication Date: 2025-01-01
Volume: 1258 LNNS
Issue: Unknown
Page Range: 107-119
Description:
We have learned from childhood on, that before crossing a street, first we must look left, then to right. This is related with the right-hand traffic system of cars. The research question in this paper is: how we behave in an unfamiliar situation, when crossing left-hand traffic. In Budapest, four of the five suburban railway lines operate with right-hand traffic, but one of them works in the left-hand system. The aim of this article is to investigate the behavior of pedestrians in level crossings with right- and left-hand railway traffic and to reveal any differences between their behavior, as well as the safety of these lines. The main findings are that pedestrians look at the “built-in” left-right order, even it is not the safest option. Parallelly, accident data show worse safety situation of the line with left-hand traffic. As conclusion, some low-cost infrastructure measures are recommended.
Open Access: Yes
INVESTIGATING THE ROLE OF ACTIVATION FUNCTIONS IN PREDICTING THE PRICE OF CRYPTOCURRENCIES DURING CRITICAL ECONOMIC PERIODS
Publication Name: Virtual Economics
Publication Date: 2024-12-31
Volume: 7
Issue: 4
Page Range: 64-91
Description:
Accurate cryptocurrency price forecasting is crucial due to the significant financial implications of prediction errors. The volatile and non-linear nature of cryptocurrencies challenges traditional statistical methods, revealing a gap in effective predictive modelling. This study addresses this gap by examining the impact of activation functions on neural network models during critical economic periods, specifically aiming to determine how optimising activation functions enhances accuracy in neural network models, including RNN, GRU, LSTM, and hybrid architectures. Using data from January 2016 to June 2022—encompassing stable periods, the COVID-19 pandemic, and the onset of the 2022 Ukraine conflict—we analysed price trends under various market conditions. Our methodology involved testing three activation functions (ReLU, sigmoid, and Tanh) across these models. Both univariate and multivariate analyses were conducted, with the latter incorporating additional metrics such as opening, highest, and lowest prices. The results indicate that optimising activation functions enhances prediction accuracy. Among the models, GRU demonstrated the highest accuracy, whereas RNN was the least efficient. Multivariate models outperformed univariate ones, highlighting the benefits of incorporating comprehensive data. Notably, the Tanh activation function led to the greatest improvements, particularly in underperforming models such as RNN. These findings underscore the critical role of activation function selection in enhancing the predictive power of neural networks for cryptocurrency markets. Optimising activation functions can lead to more reliable forecasts, facilitating better trading decisions and risk management. This study highlights activation functions as key parameters in neural network modelling, encouraging further exploration. Future research could investigate different economic periods and cryptocurrency behaviours to assess model robustness. Additionally, examining a broader range of cryptocurrencies may reveal whether the benefits of activation function optimisation are consistent across various assets. Incorporating external factors such as macroeconomic indicators or social media sentiment could further enhance models and improve forecasting accuracy.
Open Access: Yes
Impact of green fiscal policy on the collaborative reduction of pollution and carbon emissions: Evidence from energy saving and emission reduction policy in China
Publication Name: Oeconomia Copernicana
Publication Date: 2024-12-30
Volume: 15
Issue: 4
Page Range: 1263-1302
Description:
Research background:Since China is facing the dual challenges of environmental pollution and climate change, how to effectively deal with the collaborative reduction of pollution and carbon emissions (CRPCE) has become an important problem. Energy saving and emission reduction fiscal policy (ESER), as a green fiscal policy, plays an important role in solving China's environmental problems. Purpose of the article: The aim of this study is to analyze the direct impacts, mechanisms and spatial spillover effects of the ESER policy on the CRPCE through theoretical and empirical analyses, thereby providing practical and feasible fiscal-related policy proposals for developing countries like China to achieve low-carbon development. Methods: Difference-in-differences method (DID), spatial DID. Findings & value added: Based on panel data from 274 Chinese cities, this study analyzes the impact of ESER policy on the CRPCE. The findings demonstrate that the ESER policy effectively enhances the CRPCE. The mechanism analysis demonstrates that the impact of the ESER policy is realized by promoting green technology innovation, improving energy efficiency, and increasing industrial structure upgrading. The heterogeneity analysis demonstrates that the ESER policy can be more effective in enhancing the CRPCE when it is implemented in northern, resource-based, and high fiscal self-sufficiency cities. The spatial analysis results suggest that ESER policy attenuates the CRPCE of neighboring cities. In addition, the co-implementation of the ESER policy and the innovation policy is more effective in enhancing the CRPCE, but cities are required to implement the innovation policy first. This study broadens the research perspective on the synergistic effects of green fiscal policy in reducing pollutant and carbon emissions, and offers a useful guide for other developing countries on green fiscal policy.
Open Access: Yes
DOI: 10.24136/oc.3159
