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Publications - 6374

Relevance of Industry 4.0 Technologies to Advancing SDG 14: Life Below Water

John G. Keogh Abderahman Rejeb Karim Rejeb

Publication Name: Sustainable Development Goals Series

Publication Date: 2025-01-01

Volume: Part F1068

Issue: Unknown

Page Range: 197-218

Description:

This chapter explores the critical role of Industry 4.0 technologies in fostering Sustainable Development Goal 14 (SDG 14): Life Below Water. It investigates how digital innovations, such as remote sensing, artificial intelligence (AI), big data analytics, drones, robotics, and autonomous underwater vehicles, reshape marine ecosystems’ monitoring, management, and conservation. The chapter details key applications, including smart aquaculture farms, AI-driven pollution monitoring, early warning systems for harmful algal blooms, and real-time data platforms for marine governance. It outlines the contributions of these technologies to specific SDG 14 targets, particularly in reducing marine pollution, regulating harvesting to end overfishing, and increasing economic benefits for small island and coastal communities. In addition to exploring the significant benefits, the chapter critically discusses challenges such as high implementation costs, data interoperability issues, digital skill gaps, and ethical concerns related to Industry 4.0 adoption. It concludes by calling for greater investment, cross-sector collaboration, and inclusive policy frameworks to ensure that the digital transformation of marine conservation is both practical and equitable. Finally, the chapter envisions a “digital oceans” future where real-time and data-informed management ushers in resilient and sustainable marine ecosystems.

Open Access: Yes

DOI: 10.1007/978-3-032-06527-8_10

Evaluation of Questionnaires by Combining Fuzzy Signatures, Factor Analysis and Least Squares Method

Dalia Susniene Márta Konczos Szombathelyi Szabolcs Ramhap Ojaras Purvinis Ĺaszĺo T. Ḱoczy

Publication Name: Ines 2020 IEEE 24th International Conference on Intelligent Engineering Systems Proceedings

Publication Date: 2020-07-01

Volume: Unknown

Issue: Unknown

Page Range: 215-218

Description:

A survey based on a standard questionnaire on employee satisfaction was carried out in Hungary. The questionnaire was developed by international university research consortium. The qualitative data were collected from 1159 respondents. The subjective and therefore inexact answers represented in the Likert scale were mapped into fuzzy membership degrees. The article presents a method that consists of the combination of factor analysis and the least square method, applied for developing the fuzzy signature characterizing the employees' behavioural engagement.

Open Access: Yes

DOI: 10.1109/INES49302.2020.9147125

Bridging Diagnostic Condition Monitoring and NVH Tonal Excitation Through Frequency–Domain Structural Mapping

Krisztian Horvath Krisztián Horváth

Publication Name: Applied Sciences Switzerland

Publication Date: 2026-04-01

Volume: 16

Issue: 8

Page Range: Unknown

Description:

Featured Application: The mapping methodology presented in this manuscript can aid in the vibration-based assessment of tonal excitation-related response in powertrain systems, providing a structural link between diagnostic monitoring and NVH assessment practices. In general, condition monitoring (CM) and noise, vibration and harshness (NVH) are often treated as separate disciplines, despite the fact that both rely on vibration measurements. CM relies on broadband statistical metrics such as RMS, kurtosis, and envelope analysis to detect faults. Meanwhile, NVH investigates tonal excitation mechanisms related to gear mesh frequency (GMF) and its modulation components. In this study, we investigate whether a numerical relationship can be established between classical CM indicators and physically based tonal excitation indicators derived from frequency–domain analysis. Using healthy and damaged benchmark gearbox recordings, Spearman correlation analysis was performed between broadband metrics and GMF-related tonal features, including GMF-band energy and absolute sideband energy. Results show moderate but statistically significant correlations between RMS, envelope peak amplitude, and tonal indicators, whereas kurtosis exhibits no meaningful association. Additionally, tonal response amplification in the damaged gearbox is shown to be non-uniformly distributed across sensor locations, indicating sensor-dependent structural sensitivity rather than uniform response growth. These findings demonstrate that broadband CM indicators partially encode changes in tonal excitation-related response, establishing a reproducible data-driven bridge between diagnostic condition monitoring and NVH excitation analysis.

Open Access: Yes

DOI: 10.3390/app16083709

Transfer Learning-Based Steering Angle Prediction and Control with Fuzzy Signatures-Enhanced Fuzzy Systems for Autonomous Vehicles

Áron Ballagi Ahmet Mehmet Karadeniz Ĺaszĺo T. Ḱoczy

Publication Name: Symmetry

Publication Date: 2024-09-01

Volume: 16

Issue: 9

Page Range: Unknown

Description:

This research introduces an innovative approach for End-to-End steering angle prediction and its control in electric power steering (EPS) systems. The methodology integrates transfer learning-based computer vision techniques for prediction and control with fuzzy signatures-enhanced fuzzy systems. Fuzzy signatures are unique multidimensional data structures that represent data symbolically. This enhancement enables the fuzzy systems to effectively manage the inherent imprecision and uncertainty in various driving scenarios. The ultimate goal of this work is to assess the efficiency and performance of this combined approach by highlighting the pivotal role of steering angle prediction and control in the field of autonomous driving systems. Specifically, within EPS systems, the control of the motor directly influences the vehicle’s path and maneuverability. A significant breakthrough of this study is the successful application of transfer learning-based computer vision techniques to extract respective visual data without the need for large datasets. This represents an advancement in reducing the extensive data collection and computational load typically required. The findings of this research reveal the potential of this approach within EPS systems, with an MSE score of 0.0386 against 0.0476, by outperforming the existing NVIDIA model. This result provides a 22.63% better Mean Squared Error (MSE) score than NVIDIA’s model. The proposed model also showed better performance compared with all other three references found in the literature. Furthermore, we identify potential areas for refinement, such as decreasing model loss and simplifying the complex decision model of fuzzy systems, which can represent the symmetry and asymmetry of human decision-making systems. This study, therefore, contributes significantly to the ongoing evolution of autonomous driving systems.

Open Access: Yes

DOI: 10.3390/sym16091180

Characterisation of Hungarian Cikta sheep based on the control region of mtDNA

Petra Zenke Ákos Maróti-Agóts Károly Tempfli Annus Kata Sáfár László Kovács Endre Harmat Levente András Gáspárdy

Publication Name: Magyar Allatorvosok Lapja

Publication Date: 2020-07-01

Volume: 142

Issue: 7

Page Range: 421-428

Description:

Background: The consideration of the high genetic diversity is indispensable on the course of preservation of endangered animal breeds. Objectives: The authors evaluate the genetic background in the Hungarian native Cikta breed by use of mitochondrial DNA (mtDNA) control region (CR) sequence firstly. Their investigation was carried out in order to serve data for the maintenance of maternal lineages. Materials and Methods: The DNA samples were taken from the descendants of the eldest families by use of founder sampling method based on pedigree (n = 69) in 2015. The primers described by Hiendleder et al. (7) were used to amplify the region of interest (AF010406). Results and Discussion: The control region of mtDNA showed polymorphisms at 32 sites. However, the herds shared 24 polymorphic sites, so the maternal background of the Cikta appears to be genetically uniform. The total number of haplotypes were 13, furthermore, most of the samples belonged to the haplog-roup B of sheep. This fact proves the decisively European maternal origin of the Hungarian Cikta. The average number of pairwise differences (k) and the average nucleotide diversity (ro) were 6.863 and 5.95 × 10-3, respectively. The values of the Cikta population were not significant (p < 0.10) neither by the Tajima D-test (0.107) and by Fu's Fs statistics (2.533), meaning that the greatly reduced population size of the breed known from the breed history did not cause genetic drift, it is in genetic equilibrium regarding its ancient families. The genetic information confirmed the origin of the families/flocks known from the breed history. A more intense focusing on the maternal side is motivated also by the fact that the females are present at greater number than the males, respectively they remain in breeding for a longer period of time, so they can at larger extent be the depositaries of realization and maintenance of genetic diversity.

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

Primitive reflexes as behavioral biomarkers of cognitive aging: associations with physical activity and resilience—a pilot study

Ferenc Ihász Johanna Takács István Barthalos Eliza Toth Anna Horváth-Pápai Zoltán Alföldi

Publication Name: Frontiers in Aging Neuroscience

Publication Date: 2025-01-01

Volume: 17

Issue: Unknown

Page Range: Unknown

Description:

Introduction: Primitive reflexes (PRs) are brainstem-mediated automatic responses that typically disappear in early life, but may reappear in older age, which may be associated with neurodegenerative processes. But the presence of PRs in cognitively healthy adults has not yet been sufficiently explored. The relationship between PRs and cognitive functioning (COG) may be influenced by modifiable factors such as physical activity (PA) and psychological resilience. This cross-sectional observational pilot study aimed to investigate the mediating and moderating role of physical activity and resilience in the association between primitive reflexes and cognitive functioning in older adults. Methods: A total of 30 older adults (mean age 73.4 ± 6.9 years; 80% female) living in residential care facilities were assessed. PRs were evaluated using standardized neurological protocols, COG was measured with the Mini-Mental State Examination, PA with the Global Physical Activity Questionnaire, and resilience with the Connor–Davidson Resilience Scale. Moderation and mediation models were tested using Hayes’ PROCESS macro, controlling for age and BMI. Results: A higher number of primitive reflexes was strongly associated with lower cognitive functioning [COG (r = −0.904, p < 0.001)]. Physical activity showed a significant mediating effect in this association, indicating that more active older adults exhibited better cognitive performance despite the presence of primitive reflexes. Resilience, although correlated with both cognition and physical activity, did not show a mediating or moderating effect. Discussion: These findings highlight primitive reflexes as potential behavioral biomarkers of cognitive aging, and underscore the importance of physical activity as a protective factor that may buffer against neurocognitive decline.

Open Access: Yes

DOI: 10.3389/fnagi.2025.1687512

A computational model for inference chains in expert systems

Jozsef Sziray

Publication Name: Proceedings 2009 International Conference on Intelligent Engineering Systems Ines 2009

Publication Date: 2009-11-02

Volume: Unknown

Issue: Unknown

Page Range: 183-188

Description:

This paper deals with the calculations performed in the reasoning process of rule-based expert systems, where inference chains are applied. It presents a logic model for representing the rules and the rule base of a given system. Also, the fact base of the same expert system is involved in the logic model. The proposed equivalent representation manifests itself in a logic network. After that, a four-valued logic algebra is introduced. This algebra is used for the calculations where forward chaining is carried out. Next, the notion of line-value justification is described. This operation is applied in the backward chaining process, also on the base of the previously introduced four-valued logic. The paper describes two exact algorithms which serve for the forward and backward chaining processes. These algorithms make it possible to be implemented by a computer program, resulting in an efficient inference engine of an expert system. The achieved result enhances the reliability and usability of the intelligent software systems which is extremely important in embedded environments. ©2009 IEEE.

Open Access: Yes

DOI: 10.1109/INES.2009.4924759

Evaluating blockchain-based waste management investments in smart cities using a multi-criteria decision support framework

Dragan Pamucar Ashit Kumar Dutta Mohd Anjum Sana Shahab Vladimir Simic

Publication Name: Scientific Reports

Publication Date: 2026-12-01

Volume: 16

Issue: 1

Page Range: Unknown

Description:

With growing urbanization, there are increasing demands on waste management systems that can be performed in an environmentally friendly way as well as efficiently. Current approaches to managing waste often have issues with efficiency, transparency, and engaging with the public. Blockchain technology has been identified as one potential solution to these problems because it offers several benefits including decentralization, security, and transparency. The selection of the best blockchain-based waste management (BBWM) system is very difficult due to the many different evaluation criteria that may conflict with each other. Therefore this research uses a multi-criteria decision making (MCDM) approach using CIMAS (Criteria Importance Assessment), for determining weights based upon subjective input, and LOPCOW (Logarithmic Percentage Change-Driven Objective Weighing), for determining weights based upon objective data within the MCDM framework. To rank alternatives effectively, an Alternative Ranking Order Method Accounting for Two-Step Normalization (AROMAN) technique is applied, ensuring a precise evaluation process. The use of T-Spherical Fuzzy Sets (T-SFS) captures all three (membership, non-membership, hesitation degree) and is used to address the variability that exists when making an expert judgment. Some of the key factors include; Technological Feasibility, Operational Costs, Scalability, Data Security, Regulatory Compliance, Environmental Impact. Based on the evaluation criteria, it appears that the Blockchain Enabled Waste Tracking System is the most appropriate alternative due to its high potential for Transparency, Regulatory Compliance and Fraud Prevention. In addition, this research will provide Policymakers, Urban Planners and Investors with a methodical way of making Data Driven Decisions on BBWM Investments.

Open Access: Yes

DOI: 10.1038/s41598-025-33085-5