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Exploring Fuzzy Signatures in Sensor Fusion: A Comparative Study with the Complementary Filter

Áron Ballagi Ahmet Mehmet Karadeniz Ĺaszĺo T. Ḱoczy

Publication Name: Cinti 2024 IEEE 24th International Symposium on Computational Intelligence and Informatics Proceedings

Publication Date: 2024-01-01

Volume: Unknown

Issue: Unknown

Page Range: 69-74

Description:

Sensing has become a pivotal element in the development of autonomous systems with the advancement of the technology. These systems operate on a sense-think-act cycle to execute tasks, necessitating the integration of multiple sensors. The challenge of synthesizing meaningful information from diverse data sources escalates with the complexity of the data. This study tackles the issue of sensor data complexity by investigating the potential of Fuzzy Signatures, which are promising in handling complex data due to their hierarchical structures. The main goal is to present a concept for sensor fusion based on Fuzzy Signatures, which may facilitate their use in autonomous system tasks. To demonstrate this concept, accelerometer and gyroscope data are utilized, with results compared to those from a Complementary Filter providing insight into the sensor fusion capabilities of Fuzzy Signatures. The study also underscores the importance of aggregation operators in Fuzzy Signatures, focusing on the Max and WRAO (weighted relevance aggregation operator) aggregation operators. The potential to employ various aggregation operators or to develop new ones for specific applications is highlighted. The findings indicate that Fuzzy Signatures could be an effective solution for sensor fusion challenges, offering prospects for enhancement and broader application in autonomous systems.

Open Access: Yes

DOI: 10.1109/CINTI63048.2024.10830837

Assessing the impact of artificial intelligence on project efficiency enhancement

Almas Mamyrbayev Aknur Zhidebekkyzy Assel Kozhakhmetova Svitlana Bilan

Publication Name: Knowledge and Performance Management

Publication Date: 2024-01-01

Volume: 8

Issue: 2

Page Range: 109-126

Description:

The study explores the impact of artificial intelligence (AI) technologies on project management (PM) across different industries. It aims to assess how AI adoption in PM affects project efficiency. The study surveyed 159 project supervisors and specific project managers implementing projects from 7 industries in the Republic of Kazakhstan: software, green energy, engineering, construction, science, transport, and tourism. The research used variance and linear regression analyses to evaluate the relationship between AI adoption and project efficiency level measured by the Likert scale from 1 to 5 and test the associated hypotheses. The results show that AI adoption varies among industries, with software, construction, and scientific projects being the most active users. The study also found that the use of AI differed across eight project performance domains, with the stakeholder domain using voice technologies and process automation and the uncertainty domain using fewer tools. Projects with higher AI adoption rates showed higher efficiency scores (for example, in Software projects, the AI adoption rate is 3.2; the efficiency rate is 3.3), while those with lower efficiency levels (for example, in the Tourism industry, the AI adoption rate is 1.9; the efficiency rate is 2.2) showed the worst results. Decision-making systems, process automation, and voice technologies are the three most critical AI technologies PM professionals use to improve project efficiency.

Open Access: Yes

DOI: 10.21511/kpm.08(2).2024.09

Economic and environmental drivers of renewable energy transition in the EU

Laszlo Vasa Galyna Trypolska Iryna Sotnyk Oleksandra Kubatko Ulyana Pysmenna Vladyslav Piven

Publication Name: Environmental Economics

Publication Date: 2024-01-01

Volume: 15

Issue: 2

Page Range: 232-245

Description:

The current green agenda, the climate change, and sustainability frameworks are closely linked to the successful transition to renewable energy. The study purpose is to estimate the influence of economic and environmental drivers of renewable energy promotion in the EU-27, using the 2013–2021 data for member states. Breusch and Pagan Lagrangian multiplier test and Hausman specification test were performed to determine the proper model specification. Using random-effects GLS regression for selected data, the study found that the rise in the magnitude of the Land-Ocean Temperature Index by one unit contributes to an increase in renewable energy sources by 10-16 percentage points. The rise in natural gas prices in the EU by USD 10 per MMBtu is associated with an average growth of renewable energy sources by 2.1-2.6 percentage points and three percentage points for growth in renewable electricity. An increase in GDP per capita of USD 1,000 led to an average increase in renewable electricity by 0.2 percentage points. An increase in CO2 per capita by one ton is associated with an average decrease in renewable electricity by 0.85 percentage points. This study proves that the critical point of GDP per capita within the “economic growth/renewable energy” nexus when economic stimulus starts to decline was estimated at USD 121,227-148,623. Thus, for countries that have reached the break-even point in GDP per capita, the incentives for introducing renewable energy sources are reduced when the effect of wealth prevails over the impact of environmental awareness and responsibility.

Open Access: Yes

DOI: 10.21511/ee.15(2).2024.16

Psychometric Properties of the Hungarian UCLA Loneliness Scale Among Adolescents: A Search for the Meaning of Loneliness in the Young Population

Ferenc Ihász Johanna Takács Zsolt Bálint Katona

Publication Name: European Journal of Mental Health

Publication Date: 2024-01-01

Volume: 19

Issue: Unknown

Page Range: Unknown

Description:

Introduction: Loneliness has been considered a major public health and policy concern, with substantial physical and mental health impacts.The University of California and Los Angeles Loneliness Scale (UCLA-LS) is one of the most widely used scales for measuring loneliness but it does not have robust psychometric properties among adolescents.Aims: To evaluate the psychometric properties of the Hungarian UCLA-LS among adolescents.Methods: The sample includes a total of 2508 students, 57.3% females, aged between 14 and 21 years.Studying psychometric properties, internal reliability and criterion-related validity were measured.The sample was randomly divided into two parts to examine the factorial structure: one part was used for exploratory factor analysis (EFA) and the other was used for confirmatory factor analysis (CFA).Results: The UCLA-LS showed good internal consistency.Its total score and the single-item measure showed a small correlation, and also indicated a significant moderate association with hopelessness and self-reported well-being.Based on the EFA, we identified two factors with 51.7% of the total variance explained.In the CFA, the two-factor model demonstrated a good fit.Conclusions: The findings suggested that the Hungarian UCLA-LS can be a reliable and valid tool for adolescents to measure some dimensions of loneliness.We confirmed the non-normal, relatively skewed distribution of the scale.We can conclude that the UCLA-LS measures a trait characteristic of loneliness.In the adolescent population, it is recommended to use further measures of loneliness to gain more information about the frequency and nature of the multi-faceted mental representation of loneliness.

Open Access: Yes

DOI: 10.5708/EJMH.19.2024.0034

Optimizing Video Resolution for Machine Learning-Based Traffic Monitoring Systems: A Performance Analysis

Ferenc Erdos Enas Elshebli

Publication Name: International Conference on Engineering and Emerging Technologies Iceet

Publication Date: 2024-01-01

Volume: Unknown

Issue: 2024

Page Range: Unknown

Description:

This study explores the impact of video resolution on the performance of machine learning-based traffic monitoring systems. Using a combination of empirical analysis and theoretical modeling, we assess how different resolutions affect detection accuracy, resource consumption, and computational efficiency. While other factors such as noise level, or compression artifacts also influence performance, resolution was chosen as a primary variable due to its critical role in balancing detail capture and computational cost. Higher resolutions can enhance object detection accuracy but also significantly increase data processing demands, making resolution a key trade-off in designing efficient surveillance systems. Findings of this study show significant insights into these trade-offs, guiding transportation authorities and system developers in making informed decisions to design scalable traffic monitoring solutions that meet the demands of modern urban environments.

Open Access: Yes

DOI: 10.1109/ICEET65156.2024.10913642

VR supported outer space education

Istvan Gulyas Laszlo Kadocsa Gyorgy Molnar

Publication Name: 2024 IEEE 22nd World Symposium on Applied Machine Intelligence and Informatics Sami 2024 Proceedings

Publication Date: 2024-01-01

Volume: Unknown

Issue: Unknown

Page Range: 229-236

Description:

The basic aim of the research presented in this paper was a complex evaluation of a practical space exercise supported by virtual tools, with a special focus on the role of VR technology and the software used. The research also examined technological and methodological aspects such as the effectiveness of VR lab exercises, the quality of online learning materials and software, and the role of instructors. The methodology of our research was based on attitudinal analysis and descriptive statistical analysis, an important part of which was an evaluation of the VR software used, which not only characterises the current situation but also determines future development directions. As a result of our research, we can conclude that VR technology, especially 3D visualisation and interactive exercises, have proven to be particularly important in the learning process, but the future of VT technology in education is still perceived by students as somewhat uncertain due to infrastructural and resource constraints. Furthermore, our research results show that there is a need to improve the IT infrastructure and further optimize VR software, as well as a need for future research on resource allocation and technology integration beyond the pedagogical effectiveness of VR technology.

Open Access: Yes

DOI: 10.1109/SAMI60510.2024.10432907

Preface

Ĺaszĺo T. Ḱoczy

Publication Name: Studies in Fuzziness and Soft Computing

Publication Date: 2024-01-01

Volume: 427

Issue: Unknown

Page Range: vii-xiii

Description:

No description provided

Open Access: Yes

DOI: DOI not available

Non-Linear Time History and Pushover analysis of a Steel Silo Behavior

Oveys Ghodousian Farhood Shahidi Farhad Shahidi Majid Movahedi Rad Vahid Shafaie

Publication Name: Advances in Transdisciplinary Engineering

Publication Date: 2024-01-01

Volume: 59

Issue: Unknown

Page Range: 334-341

Description:

Earthquakes, among the most destructive natural hazards, result in substantial economic and demographic losses. An effective strategy to mitigate future structural damage involves investigating past collapses. Numerical modeling proves instrumental in analyzing and identifying deficiencies in collapsed structures. This study numerically evaluates a steel silo damaged during the 2011 Van earthquake. Employing non-linear time history and pushover analyses, the research assesses the silo's performance. Findings highlight inadequate welding dimensions and incomplete fusion with the base metal in fillet welds between columns and the silo tank as primary causes of collapse. Numerical simulations with varied column removal scenarios underscore the importance of robust silo tank-column connections in reducing earthquake-induced damage.

Open Access: Yes

DOI: 10.3233/ATDE240564

Forecasting of macroeconomic stability post-pandemic recovery: The case of European countries

Aleksandra Kuzior Wojciech Augustyniak Alina Vysochyna Sándor Remsei

Publication Name: Journal of International Studies

Publication Date: 2024-01-01

Volume: 17

Issue: 4

Page Range: 56-79

Description:

The unfolding of the COVID-19 pandemic has revealed "bottlenecks" not only in the healthcare system, which was unable to cope with a significant influx of patients and quickly eliminate the spread of coronavirus infection, but also the vulnerability of the socioeconomic systems of countries all over the world. The research aims to determine country-specific trend patterns of volatility of the integral level of macroeconomic stability and its components and forecast their values for the medium term to determine the dynamics of post-pandemic recovery. The implementation of the research objectives involves the implementation of the following steps: 1) determining outliers in data series that characterise the dynamics of the components of macroeconomic stability in the context of each of the 10 studied countries; 2) eliminating outliers; 3) determining the highest-quality functional form of the dependence of the change in the corresponding individual macroeconomic indicator over time; 4) forecasting the change in individual indicators and the integral level of macroeconomic stability for the medium term (2023-2025); 5) determining the deviations of the forecast values of the above indicators from their pre-pandemic level (2019) and end-of-pandemic level (2022); 6) qualitative interpretation of the forecasting results.

Open Access: Yes

DOI: 10.14254/2071-8330.2024/17-4/4