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Publications - 6674

Comparison of Auditory and Visual Short-Term Memory Capabilities using a Serious Game Application

Adam B. Csapo György Wersényi

Publication Name: Infocommunications Journal

Publication Date: 2024-06-01

Volume: 16

Issue: 2

Page Range: 51-60

Description:

A comprehensive serious game application has been designed and implemented to examine the capacity and effective- ness of short-term auditory and visual memory, otherwise known as working memory in human subjects. Participants engaged in an adaptation of the well-known paired association game that entails turning over cards and recalling their placement within a 2D matrix structure of various resolutions. Each trial introduced either visual icons (vision-only condition) or auditory objects (audio-only condition). User performance was evaluated through a detailed statistical analysis focusing only on the highest 6x8 resolution condition in the application. Findings suggest that visual memory did not conclusively outperform auditory memory in the context of this game. However, within the scope of auditory stimuli, familiar iconic sounds, such as excerpts of speech and commonplace sounds, were recalled more effectively than unfamiliar, synthetic sounds like parametric waveforms. Furthermore, performance appeared to be influenced by demographic factors, with male and younger subjects yielding superior results.

Open Access: Yes

DOI: 10.36244/ICJ.2024.2.7

Blockchain and Smart Cities: Co-Word Analysis and BERTopic Modeling

Abderahman Rejeb Karim Rejeb Heba F. Zaher Steve Simske

Publication Name: Smart Cities

Publication Date: 2025-08-01

Volume: 8

Issue: 4

Page Range: Unknown

Description:

Highlights: What are the main findings? Blockchain plays a foundational role in supporting secure, interoperable infrastructure for key urban services, particularly through integration with IoT, edge computing, and smart contracts. Research has shifted from general blockchain exploration to sector-specific applications, including decentralized healthcare, energy trading, smart mobility, and drone coordination. What is the implication of the main finding? Blockchain enables cross-sectoral innovation in smart cities by enhancing transparency, data integrity, and trust across complex urban systems. As both a technological and ethical infrastructure, blockchain supports the development of secure, resilient, and sustainable smart city ecosystems aligned with Industry 5.0 values. This paper explores the intersection of blockchain technology and smart cities to support the transition toward decentralized, secure, and sustainable urban systems. Drawing on co-word analysis and BERTopic modeling applied to the literature published between 2016 and 2025, this study maps the thematic and technological evolution of blockchain in urban environments. The co-word analysis reveals blockchain’s foundational role in enabling secure and interoperable infrastructures, particularly through its integration with IoT, edge computing, and smart contracts. These systems underpin critical urban services such as transportation, healthcare, energy trading, and waste management by enhancing data privacy, authentication, and system resilience. The application of BERTopic modeling further uncovers a shift from general technological exploration to more specialized and sector-specific applications. These include real-time mobility systems, decentralized healthcare platforms, peer-to-peer energy exchanges, and blockchain-enabled drone coordination. The results demonstrate that blockchain increasingly supports cross-sectoral innovation, enabling transparency, trust, and circular flows in urban systems. Overall, the current study identifies blockchain as both a technological backbone and an ethical infrastructure for smart cities that supports secure, adaptive, and sustainable urban development.

Open Access: Yes

DOI: 10.3390/smartcities8040111

Human factor of multi attribute decision aid making system for supply chains

Edit Süle Tamás Bódis Gergely Hodosi

Publication Name: 2024 IEEE 15th International Colloquium of Logistics and Supply Chain Management Logistiqua 2024

Publication Date: 2024-01-01

Volume: Unknown

Issue: Unknown

Page Range: Unknown

Description:

Achieving optimal operation is a fundamental objective in most production and service systems. The core of this pursuit involves seeking the minimum or maximum values of one or more target functions within specific constraints. For instance, it is common to strive for the minimization of operating costs, lead times, and resource utilization, or the maximization of revenue and coverage. These objectives must be balanced against a range of factors, including market constraints, resource capacities, budgets, and technological conditions. A significant challenge in the quest for optimal operation is the quality and documentation of data. Often, data are neither clean nor well-documented, which complicates the process of finding and implementing optimal operational strategies. This paper focuses on the human element in decision-making processes, acknowledging the limitations inherent in human capabilities when making decisions. The primary aim of this paper is to present a case study that highlights the constraints of human decision-making processes. Through this case study, we examine the impact of human factors on achieving optimal operation in production and service systems. The study provides insights into how human limitations can affect the decision-making process, particularly in the context of imperfect data and the complex interplay of various operational constraints.

Open Access: Yes

DOI: 10.1109/LOGISTIQUA61063.2024.10571459

A hybrid physics-informed neural and explainable AI approach for scalable and interpretable AQI predictions

Dragan Pamucar Rajesh Kumar Dhanaraj Malathy Sathyamoorthy Firoz Khan C. Sai Varun Balamurugan Balusamy Sunaina Sridhar Rajesh Kumar Dhanaraj Sai Varun Chandrashekar

Publication Name: Methodsx

Publication Date: 2025-12-01

Volume: 15

Issue: Unknown

Page Range: Unknown

Description:

Air Pollution is a critical environmental issue affecting public health, climate, and ecosystems. However, accurately predicting and classifying Air Quality Index (AQI) levels across different regions remains a challenging task due to the complex nature of air pollution patterns. Conventional and ensemble ML and DL models often fail to capture the physical laws goverming the air pollution, which leads to inaccurate predictions. This study addresses these issues by introducing an approach that employs Physics-Informed Neural Networks (PINN) with Explainable AI (XAI) techniques for AQI classification (AirSense-X). The proposed approach utilizes PINN for regression, along with mapping for classification and XAI for interpretation. PINN ensures that the model learns from physical laws governing air quality rather than relying solely on data. The dataset utilized in this study is a publicly available dataset containing the AQI data at daily levels from various stations across multiple cities in India. The proposed AirSense-X approach achieves an accuracy of 98 %, with 97 % precision, 95 % recall, and an F1 score of 0.96, ensuring reliability. Similarly, the confusion matrix for the proposed approach indicated that the model correctly classified 21,306 and misclassified 268 instances. The key focuses of this study include: • Introducing a novel approach, AirSense-X, which employs PINN for accurate AQI prediction and XAI for enhanced interpretability. Additionally, the study also involves comparative analysis with conventional and ensemble ML and DL models. • Employing structure mapping technique for classification based on the predicted AQI values. • Integrating physical laws governing air pollution using a PINN model enhances prediction accuracy and ensures that the model learns beyond relying on data-driven insights.

Open Access: Yes

DOI: 10.1016/j.mex.2025.103597

Dynamic and quasi static stiffness characterization of a lamination stack of an electric motor

Balázs Vehovszky Zoltán Gazdagh Viktor Szabó

Publication Name: Heliyon

Publication Date: 2024-11-15

Volume: 10

Issue: 21

Page Range: Unknown

Description:

The development of electric motors for automotive applications requires precise material models to simulate structural strength and NVH (Noise, Vibration, and Harshness) properties. Modeling the behavior of lamination stacks, composed of stacked steel plates, presents significant challenges. This study conducted dynamic and quasi-static experiments at various preload levels on an unmodified automotive lamination stack. Significant discrepancies were identified between stiffness values obtained from static and dynamic measurements. Consequently, using dynamically obtained stiffness values in static models, and vice versa, leads to inaccuracies and should be avoided. These results enhance the precision and efficiency of simulations used in the design and optimization of electric motors.

Open Access: Yes

DOI: 10.1016/j.heliyon.2024.e39693

Macrogeometric Measurement of Camshafts of Internal Combustion Engines

Levente Solecki Szilvia Nagy

Publication Name: Strojnicky Casopis Journal of Mechanical Engineering

Publication Date: 2024-11-01

Volume: 74

Issue: 2

Page Range: 71-82

Description:

In this work, cam profiles of a camshaft are measured by a roundness measurement machine. First, the measured cam profiles are transformed into their actual sizes, based on the measurement of the bearing locations. The 8 cams of the camshaft are of two types. From the 4-4 cam profiles of each type an approximate profile is created by fitting them to one another using their base circles as reference, and calculating the center of gravity of the cumulative points of these fitted profiles corresponding to an arc segment.

Open Access: Yes

DOI: 10.2478/scjme-2024-0028

Global Sensitivity Study of a Duffing-Type Nonlinear Vibration System

Flóra Hajdu

Publication Name: Strojnicky Casopis Journal of Mechanical Engineering

Publication Date: 2024-11-01

Volume: 74

Issue: 2

Page Range: 17-24

Description:

An interesting field of studying nonlinear systems is their sensitivity study. With sensitivity study the most influential parameters on a system can be obtained and then the simplification and improvement of the model will be possible. In this paper the global sensitivity study of a Duffing-type vibration system is carried out with Sobol's variance-based method taking the root mean square of acceleration and the maximum acceleration as output variables. With the sensitivity study it was observed that the parameters of the excitation signal like the amplitude and the angular velocity are the most influential. It was also found that a single parameter has less influence on the system than the parameter combinations. The aim of the research is to carry out the global sensitivity study of a relatively simple nonlinear system. The study is the basis for further research tasks in order to perform the sensitivity study of more complex systems.

Open Access: Yes

DOI: 10.2478/scjme-2024-0021

Structural Brain Abnormalities, Diagnostic Approaches, and Treatment Strategies in Vertigo: A Case-Control Study

Gergely Orsi József Tollár Klaudia Széphelyi Szilvia Kóra

Publication Name: Neurology International

Publication Date: 2025-09-01

Volume: 17

Issue: 9

Page Range: Unknown

Description:

Background/Objectives: Dizziness is a frequent medical complaint with neurological, otolaryngological, and psychological origins. Imaging studies such as CT (Computer Tomography), cervical X-rays, and ultrasound aid diagnosis, while MRI (Magnetic Resonance Imaging) is crucial for detecting brain abnormalities. Our purpose is to identify structural brain changes associated with vertigo, assess pre-MRI diagnostic approaches, and evaluate treatment strategies. Methods: A case-control study of 232 vertigo patients and 232 controls analyzed MRI findings, pre-MRI examinations, symptoms, and treatments. Statistical comparisons were performed using chi-square and t-tests (p < 0.05). Results: White matter lesions, lacunar infarcts, Circle of Willis variations, and sinusitis were significantly more frequent in vertigo patients (p < 0.05). Pre-MRI diagnostics frequently identified atherosclerosis (ultrasound) and spondylosis (X-ray). Common symptoms included headache, imbalance, and visual disturbances. The most frequent post-MRI diagnosis was Benign Paroxysmal Positional Vertigo (BPPV). Treatments included lifestyle modifications, physical therapy (e.g., Epley maneuver), and pharmacological therapies such as betahistine. Conclusions: MRI revealed structural brain changes linked to vertigo. Pre-MRI assessments are essential for ruling out vascular and musculoskeletal causes. A multidisciplinary treatment approach is recommended. Trial Registration: This study was registered in ClinicalTrials.gov with the trial registration number NCT06848712 on 22 February 2025.

Open Access: Yes

DOI: 10.3390/neurolint17090146

Towards the resilience quantification of (military) unmanned ground vehicles

Áron Ballagi Árpád Tóth Rudolf Krecht Alex Suta

Publication Name: Cleaner Engineering and Technology

Publication Date: 2023-06-01

Volume: 14

Issue: Unknown

Page Range: Unknown

Description:

In the case of Unmanned Ground Vehicles (UGVs), resilience can be an economical, an environmental, but most importantly, a mission-critical question as well: mission failure caused by the lack of resilience in some cases might imply the loss of the UGV, which could lead to human and financial losses and environmental damage. Thus, the aim of this article is to provide a methodology for UGV resilience analysis by introducing a generalizable method that can be applied both for complete UGV systems and subsystems, and leads to resilience quantification. After proposing a specific resilience definition for UGVs, this article proposes a method for UGV resilience assessment using process graphs, created based on the system components and the expected behavior of UGVs. To provide a context for the introduced solution, existing methods applied for UGV resilience assessment are briefly mentioned. The application of the proposed method is showcased on the perception subsystem of a UGV, finalized with the evaluation of the achieved results.

Open Access: Yes

DOI: 10.1016/j.clet.2023.100644