Scopus İndeksli Yayınlar Koleksiyonu

Permanent URI for this collectionhttps://gcris.khas.edu.tr/handle/20.500.12469/1248

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Citation Count: 1
Investigation Procedure for the Diagnosis of Historical Minarets: Inclined Minaret of Sivas Ulu Cami (Mosque)
(Springer Science and Business Media Deutschland GmbH, 2024) Inci,P.; Halici,O.F.; Demir,C.; Comert,M.; Aldirmaz,B.; Coban,S.; Ilki,A.
The inclined minaret of Sivas Ulu Cami (Mosque) from the 13th century Danishmend Period is one of the most invaluable architectural heritages in Turkey. The extent of inclination of the minaret towards the North-West direction, the seismicity of the region, and structural damages that occurred in time have emphasized the need for comprehensive structural and geotechnical investigations. Accordingly, a rehabilitation project is currently going on under the coordination of the General Directorate of Foundations of Turkey. Within the scope of the project, first, a series of field surveys have been conducted to obtain the current features of the minaret including the characteristics of the structural system, damages, deviation from the vertical axis, ground conditions and foundation details. In addition to that, a monitoring system including inclinometers, linear potentiometers and accelerometers has been mounted for tracking the evolution of deformations and damages in time under environmental influences and extracting the dynamic properties of the minaret. Findings from the field survey and monitoring system were used for constructing an analytical model of the structural system of the minaret. Then nonlinear time history analyses were conducted under various strong ground motion records to estimate the seismic performance of the minaret when subjected to earthquakes of different characteristics. The results showed that the tensile stresses that occurred due to seismic actions exceeded the tensile strength of the brick masonry at the region of the transition segment and the cylindrical body (top level of the boot). © Tongji University Press 2024.
Citation Count: 0
Social Media and Tax Law
(Taylor and Francis, 2024) Yazıcıoğlu, Alara Efsun
The tax implications of social media are numerous and highly debated, spanning such issues as the taxation of influencers, digital barter, and digital services taxes. This book offers a detailed overall analysis of the tax implications of social media, taking into consideration the unique characteristics of social media platforms and companies. Offering a comprehensive overview of tax law as it relates to the specificities of social media, the book examines taxation of influencers, taxation of social media companies, value added tax implications of the digital barter, the role that can be played by Pigouvian taxes in the field of social media, as well as the employment of social media as a tool for tax compliance.Widespread use of social media along with the proliferation of new social media platforms demonstrate the importance of social media tax law, and this book will be an important resource for tax administrations, lawyers, and researchers. © 2024 Alara Efsun Yazıcıoğlu.All rights reserved.
Citation Count: 0
Multi-Criteria Decision Making in Optimal Operation Problem of Unbalanced Distribution Networks Integrated with Photovoltaic Units
(Institute of Electrical and Electronics Engineers Inc., 2024) Ceylan, Oğuzhan; Aboshady,F.M.; Ceylan,O.; Pisica,I.; Ozdemir,A.
The use of renewable energy sources is increasing day by day due to their economic and environmental benefits. However, improper penetration of renewable energy into power grids can lead to problems such as over-voltages and higher active power losses. Therefore, the voltage regulation problem in distribution networks is critical due to the increasing integration of renewable energy sources. On the other hand, an increase in renewable energy penetration leads to lower operational costs due to decreased energy purchases from the overhead grid. Therefore, it can be challenging for distribution system operators (DSOs) to decide the trade-off between more Photovoltaic (PV) integration for cost minimization or less penetration to minimize voltage deviation from a rated value. In this study, we formulated this trade-off as a novel multi-objective optimization framework, aiming to minimize operating costs and voltage deviations from a rated value in an unbalanced distribution grid. The proposed formulation is applied to the modified IEEE 34-bus unbalanced distribution network, where the ε-constraint method is utilized for solving the resulting multi-objective optimization problem along with the Exterior Penalty Functions (EPF) method. The simulation results show that the proposed approach provides the DSO with a better view of decision-making in the optimal operation of the distribution networks. Authors
Citation Count: 1
DewIDS: Dew Computing for Intrusion Detection System in Edge of Things
(Springer Science and Business Media Deutschland GmbH, 2024) Das,S.; Naskar,A.; Majumder,R.; De,D.; Ahmadpour,S.-S.
Edge of Things (EoT) is a network of edge devices in which sensors, networks, electronics, and software are included. EoT enables uninterrupted data transfer from the cloud layer to edge devices through the Internet. In this transmission, there need strong privacy and security concerns. Although day by day throughout the universe the number of devices is increasing with new features, shapes, sizes, usage, protocol, etc., the conventional method of security and privacy systems are not sufficient to control the ubiquitous EoT. The conventional IDS system does not work on unstable Internet so to overcome this issue we will use Dew computing in the IDS system. With the assistance of the dew server, an individual has more control and adaptability to access data in the absence of an unstable Internet connection. IDS is used to detect different kinds of attacks in the edge layer. But sometimes it fails to detect the false alarm, which may create a severe problem. Various types of network attacks like Malware, MITM, Remote Code Execution, etc. in different networks are detected by Intrusion Detection System (IDS) and prevented by Intrusion Prevention System (IPS). At the time of the detection procedure, several alarms are generated, which decreases the effectiveness of IDS. Using an alarm filter can be a better solution to overcome this type of problem. An intelligent alarm filtration mechanism can be designed by a selective machine-learning-based classifier in DewIDS then DewIPS can block the attempted intrusion or remediate the incident after SOC investigation. This work aims to present a comprehensive survey of existing Dew Computing for Intrusion Detection Systems (IDS) and Intrusion Prevention Systems (IPS) in Edge of Things. © 2023 The Author(s),. All rights reserved.
Citation Count: 0
Merging Grid Technology with Oil Fields Power Distribution: A Smart Grid Approach
(Springer Science and Business Media Deutschland GmbH, 2024) Bektaş, Zeynep; Kayakutlu,G.; Bektas,Z.; Kayalica,M.Ö.
This study explores how grid technology can help improve oil fields’ power distribution using a fuzzy multi-criteria decision-making approach. The study compares different grid technologies based on multiple criteria, such as technical feasibility, economic viability, environmental impact, social acceptance, and regulatory compliance. The fuzzy TOPSIS method is used because it can effectively handle both crisp and fuzzy data, as well as linguistic and numerical values. After obtaining a ranking of alternatives, the study also conducts a sensitivity analysis and a robustness check to validate the results. The results show that the hybrid grid is the most preferred option for oil fields’ power distribution, followed by the smart grid, the microgrid, the nano grid, and the conventional grid. This implies that integrating different grid technologies can provide more benefits and advantages than using a single grid technology. The study provides some implications and recommendations for oil fields to adopt or integrate different grid technologies to enhance their power systems and operations. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2024.
Citation Count: 0
Evaluating Voxel-Based Graphical Passwords for Virtual Reality
(Institute of Electrical and Electronics Engineers Inc., 2024) Rawat,P.; Turkmen,R.; Nwagu,C.; Sunday,K.; Barrera MacHuca,M.D.
Previous work has proposed using voxel-based graphical passwords (VGPs) for Virtual Reality (VR) as a secure, easy-to-remember way to authenticate users. Moreover, eye-tracking technology adds another level of security, as it avoids observational threats when entering the password. However, previous work has yet to evaluate the user performance, usability, and memorability of different combinations of VGPs. In two user studies, we first identified the best combination of shape and volume for VGPs. Then, we compare 3D versus 2D VGPs. Our results show that a cube is the best shape regarding usability and user preference. We also identified that 2D VGPs are easier to remember than 3D VGPs, as shown by a higher password accuracy and lower error rate. Our results inform the implementation of VGPs and other graphical passwords in VR. © 2024 IEEE.
Citation Count: 0
EyeGuide & EyeConGuide: Gaze-based Visual Guides to Improve 3D Sketching Systems
(Association for Computing Machinery, 2024) Turkmen,R.; Gelmez,Z.E.; Batmaz,A.U.; Stuerzlinger,W.; Asente,P.; Sarac,M.; Machuca,M.D.B.
Visual guides help to align strokes and raise accuracy in Virtual Reality (VR) sketching tools. Automatic guides that appear at relevant sketching areas are convenient to have for a seamless sketching with a guide. We explore guides that exploit eye-tracking to render them adaptive to the user's visual attention. EyeGuide and EyeConGuide cause visual grid fragments to appear spatially close to the user's intended sketches, based on the information of the user's eye-gaze direction and the 3D position of the hand. Here we evaluated the techniques in two user studies across simple and complex sketching objectives in VR. The results show that gaze-based guides have a positive effect on sketching accuracy, perceived usability and preference over manual activation in the tested tasks. Our research contributes to integrating gaze-contingent techniques for assistive guides and presents important insights into multimodal design applications in VR. © 2024 Copyright held by the owner/author(s)
Citation Count: 0
Energy Performance Optimisation of a Single Dwelling Archetype Targeted to ZEB in the Earthquake Zone
(Springer Science and Business Media Deutschland GmbH, 2024) Yılmaz, Burcu Çiğdem; Yılmaz,B.Ç.
A single dwelling archetype design subjected to be constructed in Gaziantep City to provide accommodation for the earthquake victims was researched in this paper. It is aimed to find out the optimum building orientation, window-to-wall ratio, and aspect ratio as design variables to achieve Zero Emission Building target. In this regard, the GenOpt Optimisation tool was coupled with the EnergyPlus simulation tool to run the simulations and optimise proposed design scenarios. A threshold value for primary energy use based on the EPBD recommendation document as a guide was improved to determine ZEB design scenarios. It is evident from the 56.43% primary energy use difference between the lowest and highest energy performance among design scenarios that optimum design variables are highly effective in terms of energy efficiency. Besides, 82 design scenarios achieving the ZEB threshold were elaborated from the design variables’ point of view that rectangular forms and low WWRs are optimal for the selected region. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2024.
Citation Count: 0
Towards Atomic Scale Quantum Dots in Silicon: An Ultra-Efficient and Robust Subtractor using Proposed P-shaped Pattern
(Institute of Electrical and Electronics Engineers Inc., 2024) Rasmi,H.; Mosleh,M.; Navimipour,N.J.; Kheyrandish,M.
Today, Complementary Metal-OxideSemiconductor (CMOS) technology faces critical challenges, such as power consumption and current leakage at the nanoscale. Therefore, Atomic Silicon Dangling Bond (ASDB) technology has been proposed as one of the best candidates to replace CMOS technology; due to its high-speed switching and low power consumption. Among the most important issues in ASDB nanotechnology, output stability and robustness against possible faults may be focused. This paper first introduces a novel P-shaped pattern in ASDB, for designing stable and robust primitive logic gates, including AND, NAND, OR, NOR and XOR. Then, two combinational circuits, half-subtractor and full-subtractor, are proposed by the proposed ASDB gates. The simulation results show high output stability as well as adequate robustness, against various defects obtained by the proposed designs; on average, they have improvements of more than 56% and 62%, against DB omission defects and extra cell deposition defects; respectively. Also, the results of the investigations show that the proposed circuits have been improved by 65%, 21% and 2%, in terms of occupied area, energy and occurrence, respectively; compared to the previous works. IEEE
Citation Count: 0
Eye-Hand Coordination Training: A Systematic Comparison of 2D, VR, and AR Display Technologies and Task Instructions
(Institute of Electrical and Electronics Engineers Inc., 2024) Aliza,A.; Zaugg,I.; Celik,E.; Stuerzlinger,W.; Ortega,F.R.; Batmaz,A.U.; Sarac,M.
Previous studies on Eye-Hand Coordination Training (EHCT) focused on the comparison of user motor performance across different hardware with cross-sectional studies. In this paper, we compare user motor performance with an EHCT setup in Augmented Reality (AR), Virtual Reality (VR), and on a 2D touchscreen display in a longitudinal study. Through a ten-day user study, we thoroughly analyzed the motor performance of twenty participants with five task instructions focusing on speed, error rate, accuracy, precision, and none. As a novel evaluation criterion, we also analyzed the participants' performance in terms of effective throughput. The results showed that each task instruction has a different effect on one or more psychomotor characteristics of the trainee, which highlights the importance of personalized training programs. Regarding different display technologies, the majority of participants could see more improvement in VR than in 2D or AR. We also identified that effective throughput is a good candidate for monitoring overall motor performance progress in EHCT systems. © 2024 IEEE.
Citation Count: 0
INTERNATIONAL CASE STUDIES IN EVENT MANAGEMENT
(Taylor and Francis, 2024) Kozak, Metin; Aktaş,G.; Kozak,M.
This international case study book provides 27 expertly curated case studies on the topic of events management, each with detailed implementation instructions for the instructor in order to maximise student participation and learning. Embellished with questions, diagrams and data throughout, these case studies have been developed by industry experts and practitioners with the aim of creating a more interactive teaching experience focused on ‘real world’ scenarios within the events industry. Each case study is logically structured and includes an aim and objectives, expected learning outcomes, required background knowledge, steps of implementation in class or online, as well as suggestions for further reading resources. Topics covered range from macro impacts of events on destinations to success criteria in event operations, with the aim of preparing future professionals and equipping them with the necessary skills and competencies to succeed within the events industry. Easy to use and international in scope, this volume is an ideal study resource for use in higher and vocational education, and its unique, teaching-led approach positions it as a vital study tool for instructors and students alike. © 2024 selection and editorial matter, Judith Mair, Gürhan Aktaş and Metin Kozak; individual chapters, the contributors.
Citation Count: 0
List 3-Coloring on Comb-Convex and Caterpillar-Convex Bipartite Graphs
(Springer Science and Business Media Deutschland GmbH, 2024) Yaşar Diner, Öznur; Yaşar Diner,Ö.; Erlebach,T.
Given a graph G= (V, E) and a list of available colors L(v) for each vertex v∈ V, where L(v) ⊆ { 1, 2, …, k}, List k -Coloring refers to the problem of assigning colors to the vertices of G so that each vertex receives a color from its own list and no two neighboring vertices receive the same color. The decision version of the problem List 3-Coloring is NP-complete even for bipartite graphs, and its complexity on comb-convex bipartite graphs has been an open problem. We give a polynomial-time algorithm to solve List 3-Coloring for caterpillar-convex bipartite graphs, a superclass of comb-convex bipartite graphs. We also give a polynomial-time recognition algorithm for the class of caterpillar-convex bipartite graphs. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2024.
Citation Count: 0
Physical Layer Security with DCO-OFDM-based VLC Under the Effects of Clipping Noise and Imperfect CSI
(Institute of Electrical and Electronics Engineers Inc., 2024) Panayırcı, Erdal; Bektas,E.B.; Poor,H.V.
Visible light communications (VLC) and physical-layer security (PLS) are key candidate technologies for 6G wireless communication. This paper combines these two technologies by considering an orthogonal frequency division multiplexing (OFDM) technique called DC-biased optical OFDM (DCO-OFDM) equipped with PLS as applied to indoor VLC systems. First, a novel PLS algorithm is designed to protect the DCO-OFDM transmission of the legitimate user from an eavesdropper. A closed-form expression for the achievable secrecy rate is derived and compared with the conventional DCO-OFDM without security. To analyze the security performance of the PLS algorithm under the effects of the residual clipping noise and the channel estimation errors, a closed-form expression is derived for a Bayesian estimator of the clipping noise induced naturally at the DCO-OFDM systems after estimating the optical channel impulse response (CIR), by a pilot-aided sparse channel estimation algorithm with the compressed sensing approach, in the form of the orthogonal matching pursuit (OMP), and the least-squares (LS). Finally, from the numerical and the computer simulations, it is shown that the proposed PLS algorithm with secret key exchange guarantees the eavesdropper’s BER to stay close to 0.5 and that the proposed encryption-based PLS algorithm does not affect the BER performance of the legitimate user in the system. IEEE
Citation Count: 0
Milling process monitoring based on intelligent real-time parameter identification for unmanned manufacturing
(Elsevier Inc., 2024) Tehranizadeh, Faraz; Tehranizadeh,F.; Pashmforoush,F.; Budak E., (1),
This study addresses the critical need for intelligent process monitoring in unmanned manufacturing through real-time fault detection. The proposed hybrid approach, which is focused on overcoming the limitations of existing methods, utilizes machine learning (ML) for precise parameter identification in real-time to detect deviations. The ML system is developed using extensive data obtained from simulations based on enhanced force models also achieved through ML. Demonstrating over 96 % accuracy in real-time predictions, the method proves applicable for diverse unmanned manufacturing applications, including monitoring and process optimization, emphasizing its adaptability for industrial implementation using CNC controller signals. © 2024 CIRP
Citation Count: 0
Effect of Hand and Object Visibility in Navigational Tasks Based on Rotational and Translational Movements in Virtual Reality
(Institute of Electrical and Electronics Engineers Inc., 2024) Hatira,A.; Gelmez,Z.E.; Batmaz,A.U.; Sarac,M.
During object manipulation in Virtual Reality (VR) systems, realistically visualizing avatars and objects can hinder user performance and experience by complicating the task or distracting the user from the environment due to possible occlusions. Users might feel the urge to go through biomechanical changes, such as re-positioning the head to visualize the interaction area. In this paper, we investigate the effect of hand avatar and object visibility in navigational tasks using a VR headset. We performed two user studies where participants grasped a small, cylindrical object and navigated it through the virtual obstacles performing rotational or translational movements. We used three different visibility conditions for the hand avatar (opaque, transparent, and invisible) and two conditions for the object (opaque and transparent). Our results indicate that participants performed faster and with fewer collisions using the invisible and transparent hands compared to the opaque hand and fewer collisions with the opaque object compared to the transparent one. Furthermore, participants preferred to use the combination of the transparent hand avatar with the opaque object. The findings of this study might be useful to researchers and developers in deciding the visibility/transparency conditions of hand avatars and virtual objects for tasks that require precise navigational activities. © 2024 IEEE.
Citation Count: 0
Personality and conceptions of religiosity across the world's religions
(Academic Press Inc., 2024) Baranski,E.; Gardiner,G.; Shaman,N.; Shagan,J.; Lee,D.; Funder,D.; Bui,H.T.T.
Research assessing personality traits and religiosity across cultures has typically neglected variation across religious affiliations and has been limited to a small number of personality traits. This study examines the relationship between the Big Five personality traits and their facets, two theoretically distinct measures of religiosity, and twelve other personality traits across seven religious affiliations and 61 countries/regions. The proportion of participants following a religion varied substantially across countries (e.g., Indonesia = 99%; Estonia = 7%). Both measures of religiosity were related to agreeableness, conscientiousness, happiness, and fairness; however; relations with religiosity as a social axiom were stronger and less variable across religious affiliations. Additionally, personality-religiosity links were more robust in low-development, high-conflict, and collectivist nations. © 2024 Elsevier Inc.
Citation Count: 1
Media Systems and Media Capture in Turkey: A Case Study
(Cogitatio Press, 2024) Baybars, Banu; Baybars,B.
This article attempts to explain the current situation of the Turkish media system through the media systems approach as a case study with special attention to the concept of media capture. We propose that the Turkish media system’s shift is heavily influenced by media capture. We associate four of Hallin and Mancini’s media systems concepts related to the effects of media capture in the Turkish media system shift: rise of political parallelism, erosion of journalistic professionalism (ethics), controlling role of the state, and government-friendly ownership concentration. In explaining the shift from a pluralist polarised to captured media in Turkey, we acknowledge the potential for new, independent, and alternative media to emerge. The article also comments that the potential reason for this shift from a captured liberal to a captured media in Turkey is the climate of fear that has allowed successive governments in Turkey to attempt media capture. In general, this article attempts to provide insight into the current relationship between media and politics in Turkey. © 2024 by the author(s).
Citation Count: 0
Warehouse site selection for humanitarian relief organizations using an interval-valued fermatean fuzzy LOPCOW-RAFSI model
(Elsevier Ltd, 2024) Korucuk,S.; Aytekin,A.; Görçün,Ö.; Simic,V.; Faruk Görçün,Ö.
The selection of warehouse locations for humanitarian organizations represents a critical and strategic decision-making process. It is inherently complex, influenced by uncertainties and conflicting criteria. This study presents an integrated decision-making framework tailored to address this complexity for humanitarian organizations. The framework combined two key methodologies: logarithmic percentage change-driven objective weighting (LOPCOW) and ranking of alternatives through functional mapping of criterion sub-intervals into a single interval (RAFSI). Besides, this model has strengthened by extending with the help of the interval-valued Fermatean fuzzy sets to capture and process highly complex ambiguities. A significant advantage of this proposed model is its high resilience against the rank reversal problem, which is a critical shortcoming and challenge in decision-making methodologies. Additionally, the model boasts a robust, powerful, and practical structure coupled with a straightforward and easily understandable algorithm. Based on the results obtained through the implementation of the model, population density (0.1140) emerges as the most critical factor influencing decisions regarding site selection. Humanitarian organizations aim to rescue and assist as many individuals as possible during and after a disaster, prioritizing their humanitarian needs. Therefore, enhancing logistical efficiency in disaster zones and promptly reaching affected populations becomes feasible when humanitarian aid warehouses are as close as possible to areas with the highest concentration of potential disaster victims. Moreover, according to the study's findings, the most suitable option identified for the case study was Bağcılar. The conclusions drawn from sensitivity and comparative analyses affirm the model's reliability, consistency, and resilience. © 2024 Elsevier Ltd
Citation Count: 0
Enhancing Malware Classification: A Comparative Study of Feature Selection Models with Parameter Optimization
(Institute of Electrical and Electronics Engineers Inc., 2024) Dağ, Hasan; Dag,H.
This study assesses the impact of seven feature selection algorithms (Minimum Redundancy Maximum Relevance (MRMR), Mutual Information (MI), Chi-Square (Chi), Leave One Feature Out (LOFO), Feature Relevance-based Unsupervised Feature Selection (FRUFS), A General Framework for Auto-Weighted Feature Selection via Global Redundancy Minimization (AGRM), and BoostARoota) across two malware datasets (Microsoft and API call sequences) using three machine learning models (Extreme Gradient Boosting (Xgboost), Random Forest, and Histogram-Based Gradient Boosting (Hist Gradient Boosting)). The analysis reveals that no feature selection algorithm uniformly outperforms the others as their effectiveness varies based on the dataset and model characteristics. Specifically, BoostARoota demonstrated significant compatibility with the Microsoft dataset, especially after parameter optimization, whereas its performance varied with the API call sequences dataset, suggesting the need for customized parameter selection. This study highlights the necessity of tailored feature selection approaches and parameter adjustments to optimize machine learning model performance across different datasets. © 2024 IEEE.
Citation Count: 0
Evaluating the deep learning software tools for large-scale enterprises using a novel TODIFFA-MCDM framework
(King Saud bin Abdulaziz University, 2024) Görçün, Ömer Faruk; Görçün,Ö.F.; Gligorić,M.; Pamucar,D.; Simic,V.; Küçükönder,H.
Deep learning (DL) is one of the most promising technological developments emerging in the fourth industrial revolution era for businesses to improve processes, increase efficiency, and reduce errors. Accordingly, hierarchical learning software selection is one of the most critical decision-making problems in integrating neural network applications into business models. However, selecting appropriate reinforcement learning software for integrating deep learning applications into enterprises’ business models takes much work for decision-makers. There are several reasons for this: first, practitioners’ limited knowledge and experience of DL makes it difficult for decision-makers to adapt this technology into their enterprises’ business model and significantly increases complex uncertainties. Secondly, according to the authors’ knowledge, no study in the literature addresses deep structured learning solutions with the help of MCDM approaches. Consequently, making inferences concerning criteria that should be considered in an evaluation process is impossible by considering the studies in the relevant literature. Considering these gaps, this study presents a novel decision-making approach developed by the authors. It involves the combination of two new decision-making approaches, MAXC (MAXimum of Criterion) and TODIFFA (the total differential of alternative), which were developed to solve current decision-making problems. When the most important advantages of this model are considered, it associates objective and subjective approaches and eliminates some critical limitations of these methodologies. Besides, it has an easily followable algorithm without the need for advanced mathematical knowledge for practitioners and provides highly stable and reliable results in solving complex decision-making problems. Another novelty of the study is that the criteria are determined with a long-term negotiation process that is part of comprehensive fieldwork with specialists. When the conclusions obtained using this model are briefly reviewed, the C2 “Data Availability and Quality” criterion is the most influential in selecting deep learning software. The C7 “Time Constraints” criterion follows the most influential factor. Remarkably, prior research has overlooked the correlation between the performance of Deep Learning (DL) platforms and the quality and accessibility of data. The findings of this study underscore the necessity for DL platform developers to devise solutions to enable DL platforms to operate effectively, notwithstanding the availability of clean, high-quality, and adequate data. Finally, the robustness check carried out to test the validity of the proposed model confirms the accuracy and robustness of the results obtained by implementing the suggested model. © 2024 The Author(s)

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