Scopus İndeksli Yayınlar Koleksiyonu

Permanent URI for this collectionhttps://hdl.handle.net/20.500.12416/8651

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Introduction
(Springer, 2008) Aydogan, N.
Intelligent and Energy-Aware Task Scheduling in Cloud Systems
(Springer Science and Business Media Deutschland GmbH, 2025) Böke, K.N.; Qadri, S.S.S.M.; Kabarcik, A.
The rapid advancement of information technologies has significantly reshaped industrial operations and daily life, leading to a growing demand for responsive and scalable digital services. Among the technologies addressing this growing need, cloud computing has emerged as a foundational infrastructure for delivering on-demand computing resources over the internet. However, its increasing adoption presents complex challenges such as managing dynamic workloads and minimizing virtual machine (VM) usage costs. Therefore, cloud service providers aim to optimize performance and reduce the operational costs of VMs by integrating intelligent scheduling algorithms. In response to this need, the present study explores the use of algorithms, particularly focusing on machine learning driven approaches, to enhance the sustainability and efficiency of cloud systems. Specifically, the study investigates the effectiveness of reinforcement learning through Q-learning for optimizing task scheduling against the traditional Round Robin (RR) scheduling algorithm. The primary objective is to evaluate their performance in minimizing VM usage costs within dynamic and continuously evolving cloud environments. Experimental results indicate that in reducing costs, Q-learning outperforms RR with a 33.14% improvement, demonstrating its superior adaptability and cost efficiency under varying conditions. These insights highlight the potential of reinforcement learning to enable intelligent and cost-aware scheduling strategies in modern cloud computing systems. © 2025 Elsevier B.V., All rights reserved.
Design and Implementation of a Custom ERP Framework for a Drilling Equipment Manufacturer
(Springer Science and Business Media Deutschland GmbH, 2025) Torunoğlu, D.; Erkoç, E.C.; Abay, Z.E.; Qadri, S.S.S.M.; Gök, E.C.; Karataş, D.; Güçlüer, G.
This study presents the design and implementation of a web-based Enterprise Resource Planning (ERP) system tailored for a small-to-medium-sized enterprise (SME) operating in the manufacturing sector. With a focus on GEO Sondaj Makine İmalat LTD. ŞTİ, the system was developed to digitize and streamline core operational workflows, including sales order processing, production scheduling, inventory management, procurement, and coordination between customers and suppliers. Built using the Django web framework, the ERP platform provides modular functionality with real-time data integration across departments. Unlike generic ERP packages, this custom-built solution mirrors the company’s actual business processes and addresses typical challenges faced by SMEs, such as limited IT infrastructure, absence of digital records, and resistance to organizational change. The internally developed modules led to enhanced traceability, operational efficiency, and data-driven decision-making. The system also includes a simulation module to support production visualization and planning, although advanced features like bottleneck identification and dynamic queue tracking remain under development. The findings demonstrate that a cost-effective, scalable ERP system can be successfully deployed in resource-constrained environments when grounded in business-specific needs. The system was evaluated based on internal testing, interdepartmental workflow validation, and observed improvements in operational efficiency and traceability. This project offers a practical reference for other SMEs seeking to modernize their operations through digital integration. © 2025 Elsevier B.V., All rights reserved.
The Impact of Technology on Economic Growth in Turkey
(Inderscience Publishers, 2025) Ercan, M.; Temiz, D.; Gökmen, A.
The Turkish economy has been suffering from trade imbalance for a long time. Exporting high value-added products will diminish Turkey’s dependence on foreign resources for capital and imported products. At the same time, it may be possible to divert more resources from gross domestic product (GDP) to R&D funds. Appropriate and efficient usage of technology will help companies innovate and find new areas of employment. As a result, the Turkish economy may have a better chance of obtaining a sustainable economic growth for the longer term. This study concludes that increased R&D expenditures leads to a rise in technology and this in turn contributes positively to economic growth. The results obtained from the study show that technology affects Turkey’s economic growth. Therefore, Turkey needs to work harder in the field of technology in order to achieve sustainable growth. Improving the situation and quality of research and development activities in Turkey, encouraging research and development investments by both the government and the business sector should be priority reform movements for Turkey. Policy makers should support science and technology, make institutional arrangements for intellectual property rights and raise the level of education, and make arrangements to increase R&D spending. © 2025 Elsevier B.V., All rights reserved.
Cognitive and Social Antecedents of Brand Loyalty in Over-The Streaming Services
(Science Publishing Corporation Inc., 2025) Ôzsaçmaci, B.
This study examines cognitive (brand image, perceived quality, brand identity) and social (eWOM) antecedents of brand loyalty in Over-the-Top (OTT) streaming using a cross-sectional survey (N=418) and covariance-based SEM. All four antecedents significantly predict loyalty, with brand image exerting the strongest effect, followed by eWOM, then perceived quality and brand identity. Group comparisons show that evaluations of perceived quality, but not eWOM, identity, image, or loyalty, differ by usage frequency and subscription breadth. The findings substantiate a dual cognitive–social route to loyalty, and suggest that, in content-rich, multi-homing markets, quality functions as a hygiene factor while brand image carries the differentiating signal. We discuss managerial implications for sequencing investments (image, eWOM, quality thresholds) and outline finance-relevant links to CLV, LTV: CAC, and revenue stability. © 2025 Elsevier B.V., All rights reserved.
Stylometric Analysis of Sustainable Central Bank Communications: Revealing Authorial Signatures in Monetary Policy Statements
(Multidisciplinary Digital Publishing Institute (MDPI), 2025) Emekci, H.; Özkan, İ.
Sustainable economic development requires transparent and consistent institutional communication from monetary authorities to maintain long-term financial stability and public trust. This study investigates the latent authorial structure and stylistic heterogeneity of central bank communications by applying stylometric analysis and unsupervised machine learning to official announcements of the Central Bank of the Republic of Turkey (CBRT). Using a dataset of 557 press releases from 2006 to 2017, we extract a range of linguistic features at both sentence and document levels—including sentence length, punctuation density, word length, and type–token ratios. These features are reduced using Principal Component Analysis (PCA) and clustered via Hierarchical Clustering on Principal Components (HCPC), revealing three distinct authorial groups within the CBRT’s communications. The robustness of these clusters is validated using multidimensional scaling (MDS) on character-level and word-level n-gram distances. The analysis finds consistent stylistic differences between clusters, with implications for authorship attribution, tone variation, and communication strategy. Notably, sentiment analysis indicates that one authorial cluster tends to exhibit more negative tonal features, suggesting potential bias or divergence in internal communication style. These findings challenge the conventional assumption of institutional homogeneity and highlight the presence of distinct communicative voices within the central bank. Furthermore, the results suggest that stylistic variation—though often subtle—may convey unintended policy signals to markets, especially in contexts where linguistic shifts are closely scrutinized. This research contributes to the emerging intersection of natural language processing, monetary economics, and institutional transparency. It demonstrates the efficacy of stylometric techniques in revealing the hidden structure of policy discourse and suggests that linguistic analytics can offer valuable insights into the internal dynamics, credibility, and effectiveness of monetary authorities. These findings contribute to sustainable financial governance by demonstrating how AI-driven analysis can enhance institutional transparency, promote consistent policy communication, and support long-term economic stability—key pillars of sustainable development. © 2025 Elsevier B.V., All rights reserved.
An Investigation of the Performance of Equal Channel Angular Pressed Copper Electrodes in Electric Discharge Machining
(Multidisciplinary Digital Publishing Institute (MDPI), 2025) Simşek, Ü.; Çoǧun, C.
This study examines the mechanical, thermal, and electrical properties of copper tool electrodes processed via Equal Channel Angular Pressing (ECAP), with a specific focus on their performance in Electrical Discharge Machining (EDM) applications. A novel Crystal Plasticity Finite Element Method (CPFEM) framework is employed to model anisotropic slip behavior and microscale deformation mechanisms. The primary objective is to elucidate how initial crystallographic orientation influences hardness, thermal conductivity, and electrical conductivity. Simulations are performed on single-crystal copper for three representative Face Centered Cubic (FCC) orientations. Using an explicit CPFEM model, the study examines texture evolution and deformation heterogeneity during the ECAP process of single-crystal copper. The results indicate that the <100> single-crystal orientation exhibits the highest Taylor factor and the most homogeneous distribution of plastic equivalent strain (PEEQ), suggesting enhanced resistance to plastic flow. In contrast, the <111> single-crystal orientation displays localized deformation and reduced hardening. A decreasing Taylor factor correlates with more uniform slip, which improves both electrical and thermal conductivity, as well as machinability, by minimizing dislocation-related resistance. These findings make a novel contribution to the field by highlighting the critical role of crystallographic orientation in governing slip activity and deformation pathways, which directly impact thermal wear resistance and the fabrication efficiency of ECAP-processed copper electrodes in EDM. © 2025 Elsevier B.V., All rights reserved.
The Implementation of a Successive Cancellation Polar Decoder on Xilinx System Generator
(Institute of Electrical and Electronics Engineers Inc., 2017) Arli, A.Ç.; Colak, A.; Gazi, O.
Polar coding is the first kind of the capacity achieving codes which are defined for binary-input discrete memoryless channels initially. Parallel processing property of the FPGA allows to decode faster with a margin of complexity. Xilinx System Generator as a practical tool to construct decoding designs in shorter time is a fact. In this study, FPGA implementation of decoding polar codes through Xilinx System Generator is shown. © 2023 Elsevier B.V., All rights reserved.
Covariance Features for Trajectory Analysis
(Institute of Electrical and Electronics Engineers Inc., 2016) Karadeniz, T.; Maras, H.H.
In this work, we aimed to demonstrate that covariance estimation methods can be used for trajectory classification. We have shown that, features obtained via shrunk covariance estimation are suitable for describing trajectories. We have arrived to the conclusion that, when compared to Dynamic Time Warping, the explained technique is faster and may yield more accurate results. © 2017 Elsevier B.V., All rights reserved.
Citation - Scopus: 4
Parallel Data Reduction Techniques for Big Datasets
(IGI Global, 2016) Yıldırım, A.A.; Özdoǧan, C.; Watson, D.
Data reduction is perhaps the most critical component in retrieving information from big data (i.e., petascale-sized data) in many data-mining processes. The central issue of these data reduction techniques is to save time and bandwidth in enabling the user to deal with larger datasets even in minimal resource environments, such as in desktop or small cluster systems. In this chapter, the authors examine the motivations behind why these reduction techniques are important in the analysis of big datasets. Then they present several basic reduction techniques in detail, stressing the advantages and disadvantages of each. The authors also consider signal processing techniques for mining big data by the use of discrete wavelet transformation and server-side data reduction techniques. Lastly, they include a general discussion on parallel algorithms for data reduction, with special emphasis given to parallel waveletbased multi-resolution data reduction techniques on distributed memory systems using MPI and shared memory architectures on GPUs along with a demonstration of the improvement of performance and scalability for one case study. © 2025 Elsevier B.V., All rights reserved.
Citation - Scopus: 12
Computation of Supervisors for Fault-Recovery and Repair for Discrete Event Systems
(IFAC Secretariat, 2014) Sülek, A.N.; Schmidt, K.W.
In this paper, we study the fault-recovery and repair of discrete event systems (DES). To this end, we first develop a new method for the fault-recovery of DES. In particular, we compute a fault-recovery supervisor that follows the specified nominal system behavior until a fault-occurrence, that continues its operation according to a degraded specification after a fault and that finally converges to a desired behavior after fault. We next show that our method is also applicable to system repair and we propose an iterative procedure that determines a supervisor for an arbitrary number of fault occurrences and system repairs. We demonstrate our method with a manufacturing system example. © 2021 Elsevier B.V., All rights reserved.
Citation - Scopus: 1
Enterprise Architecture for Personalization of E-Government Services: Reflections From Turkey
(IGI Global, 2012) Erdem, A.; Medeni, İ.T.; Medeni, T.D.
As there has not yet been enough work on enterprise architectures for fully integrated knowledge-based, highly-sophisticated (citizen-oriented) personalized services, this chapter aims to articulate a perspective to design architectures for the development and provision of sophisticated, personalized services. Doing so, the authors benefit from their knowledge and experience in the Turkish e-Government Gateway (eGG) and general e-Government services development and provision. First providing an introduction and background information, the chapter discusses the development of eGG services in Turkey, and then provides a visionary suggestion for knowledge-based personalized, citizen-centric e-Government. Among the suggested perspectives, an E-Citizen Decision Support System, and Entity-Utility and Information Flow Model could be useful for eGG development in Turkey and elsewhere. © 2025 Elsevier B.V., All rights reserved.
Influencers in Luxury Brand Communication: An Evaluation of the Relationship Between Source Credibility, Persuasive Message, and Parasocial Engagement
(Sage Publications Inc, 2025) Alkan, Zeynep; Dolunay, Ayhan; Ulas, Sevilay
This study examines persuasive messages and source credibility in luxury brand influencers' content within their brand collaborations. It also explores how influencers establish parasocial engagement with followers through their posts. Conducted as an online survey between February and July 2023, the study targeted 400 individuals in Northern Cyprus who follow influencers. Findings indicate that increased parasocial engagement enhances the perceived persuasiveness of messages. A positive relationship between parasocial engagement and source credibility was observed, demonstrating that as influencers' credibility rises, so does the persuasiveness of their messages. Additionally, the study analyzed relationships between parasocial engagement, persuasive messages, source credibility and demographic factors. While no significant differences were found between parasocial engagement and most demographic characteristics, education level stood out. Individuals with a primary education level showed a greater tendency toward parasocial engagement. A significant difference was noted between source credibility and monthly income, with the highest perceived credibility reported in the 7,000 to 8,999 TL income group. Similarly, persuasive messages were most effective among individuals in this income range. In conclusion, this study highlights the importance of considering demographic differences and parasocial engagement in influencer brand collaborations. It underscores that source credibility and persuasive messages play a crucial role in influencer communication, influencing how audiences perceive and engage with branded content. It has been concluded that strong parasocial bonds in influencer and brand collaborations play a strategic role in establishing effective interaction with the target audience.
Indoor Soundscape Intervention (ISI) Criteria for Architectural Practice: A Systematic Review With Grounded Theory Analysis
(MDPI, 2025) Ercakmak Osma, Ugur Beyza; Dokmeci Yorukoglu, Papatya Nur
Indoor soundscape is a relatively new and developing field compared to urban soundscape in practice. To address this gap, this study aims to identify the key influencing factors as a first step of the indoor soundscape intervention approach. The study employed a two-phase methodology. Phase one involved a Systematic Review (SR) of the literature, conducted through the PRISMA 2020 guidelines, to collate data on the influencing factors and intervention criteria of the indoor soundscape approach. Searching was conducted using two databases, Web of Science and Scopus. As a result of the search, a total of 29 studies were included in the review. The review included studies addressing the soundscape influencing factors and theoretical frameworks. Studies that did not address these criteria were excluded. Phase two comprised the application of the Grounded Theory (GT) coding process to organize, categorize, and merge the data collected in phase one. As a result of the coding process, three levels of categories were achieved; L1: key concept, L2: overarching category, L3: core category. Four core categories were identified as 'Sound', 'People', 'Building', and 'Environment' by proposing the Indoor Soundscape Intervention (ISI) criteria. The repeatable and updatable nature of the proposed method allows it to be adapted to further studies and different contexts/cases.
Self-Supervised Learning With BYOL for Non-Alcoholic Fatty Liver Disease Diagnosis Using Ultrasound Imaging
(Springer London Ltd, 2025) Buktash, Ali; Gorur, Abdul Kadir
Purpose:The study aims to evaluate the effectiveness of Bootstrap Your Own Latent (BYOL), a self-supervised learning method for diagnosing NAFLD from ultrasound images using limited labeled data, which represents a novel approach in this domain. Self-supervised learning provides an alternative approach to traditional supervised learning by learning useful representations from unlabeled data, thereby reducing the time and cost required by radiologists to annotate images.Methods:The pre-trained ResNet-50 and ResNet-101 on the labeled ImageNet dataset were used for BYOL pre-training on ultrasound images without relying on labels. The training was conducted using default and custom augmentation, as well as balanced and imbalanced class distribution protocols. The model was then evaluated using linear and fine-tuning protocols with varying percentages of labeled data. The model was trained using three shuffled subsets, each trained 10 times. The custom augmentation set was derived by testing various augmentation settings using 100% and 1% of the labels to enhance feature learning.Results:BYOL with ResNet-101 and using the proposed custom augmentation set achieved average accuracies of 93.44%, 92.29%, and 88.49% using 100%, 10%, and 1% of the training labels across three shuffled datasets. In addition, our proposed method attained an average accuracy of 96.9% using patient-specific leave-one-out cross-validation (LOOCV).Conclusion:BYOL, with the proposed custom augmentation set, can learn effective image representations without relying on a large amount of labeled data, thereby enhancing scalability since unlabeled images are easier to acquire. It surpasses BYOL with default augmentation and training under supervised learning, especially with a low-labeled data regime.
Comparative Analysis of Four Usability Assessment Techniques for Electronic Record Management Systems
(Wiley, 2025) Tunc, Sevgi Koyuncu
Effective electronic record management systems (ERMSs) are crucial for modern organizations, offering benefits such as streamlined document management, enhanced security, and improved institutional memory. However, poor usability often hinders ERMS adoption and effectiveness. While various usability evaluation methods exist, a comprehensive approach integrating multiple techniques is often lacking, particularly in the context of ERMS, where factors like data security and regulatory compliance are paramount. This paper presents a novel hybrid usability assessment model that combines heuristic walkthrough, statistical log analysis, server log path analysis, and user testing to provide a holistic evaluation of ERMS usability. This integrated approach, suitable for continuous evaluation throughout the software lifecycle, addresses limitations inherent in individual methods, capturing both expert insights and real-world user behavior at scale, and generating complementary insights for diverse stakeholders (executives, developers, procurement, UX researchers). Furthermore, this study offers specific heuristics for evaluating ERMS, such as "standardized terminology" and "automatic suggestions for the standard file plan." Applied to Hacettepe University's ERMS, the model revealed usability challenges such as poor search functionality, inefficient workflows, and nonintuitive design. The study demonstrates how the combined insights from these methods provide a more nuanced understanding of ERMS usability than single-method approaches, generating actionable and cost-effective recommendations for system improvement. This research contributes a practical framework for enhancing ERMS usability and highlights the importance of multimethod evaluations for complex web applications.
Dielectric and Thermal Properties of the Ferroelectric NH4HSO4 Close to Phase Transitions
(Elsevier, 2025) Kiraci, A.; Yurtseven, H.
This work gives the analysis of the dielectric and thermal properties close to the second order and first order types of ferroelectric-paraelectric phase transitions in ferroelectrics, in particular, NH4HSO4. The power-law formula is used by adapting the Kouvel-Fisher (KF) method describing the magnetization (M) and magnetic susceptibility (chi M) in the case of the spontaneous polarization (PS) and the dielectric constant (& varepsilon;), respectively, in ferroelectric systems. Similar treatment is performed to describe the heat capacity (CP) and the thermal expansivity (proportional to P) close to the phase transitions in NH4HSO4. We show that the variations of PS and & varepsilon; with the temperature near the upper Curie point (TC1 = 270 K) exhibit linearity for the second order transition in NH4HSO4. A linear variation is also obtained between the CP and proportional to P with the temperature close to the lower Curie point (TC2 = 160 K) for the first order transition in this crystal. Experimental data are used from the literature for our analysis. Our approach given here to describe dielectric and thermal properties of NH4HSO4 close to the Curie points, can be applied to some other ferroelectric materials.
On the Determination of the Quadratic Pencil of the Sturm-Liouville Operator With an Impulse
(Pleiades Publishing Ltd, 2025) Khalili, Y.; Baleanu, D.
In this work, an inverse problem for the quadratic pencil of the Sturm-Liouville operator with an impulse in the finite interval is considered. It is shown that some information on eigenfunctions at some internal point \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$b\in\left(\frac{1}{2},1\right)$$\end{document} and parts of two spectra uniquely determine the potential functions and all parameters in the boundary conditions. Moreover we prove that the potential functions on the whole interval and the parameters in the boundary conditions can be established from one spectrum and the potentials prescribed on \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\left(\frac{1}{2},1\right)$$\end{document}.
Comparative Analysis of Impedance Matching Techniques in Wireless Power Transfer Efficiency: A Focus on Resonant, Adaptive, and Hybrid Approaches
(Springer, 2025) Hatem, Sude; Kurt, Erol
Wireless power transfer (WPT) efficiency is highly dependent on impedance matching; however, comparative analyses of matching techniques under dy namic operating conditions remain limited. This study presents a systematic evaluation of three impedance matching approaches, namely resonant, adaptive, and hybrid, via theoretical modeling and numerical simulations. The results prove that adaptive impedance matching maintains stable efficiency (90.0% +/- 0.9%) in load variations (20-100 Omega ), coil misalignment (0degrees-30degrees), and transmission distances (0.1-1 cm), with minimal fluctuations. In contrast, resonant matching shows the best efficiency (i.e., 95%) under ideal conditions (10 MHz, 0degrees misalignment, 50 Omega load) but degrades rapidly to <50% under deviation conditions (e.g., 30 misalignment or 1 cm distance). The hybrid solution yields a balanced compromise that maintaining 85-92% efficiency in larger operating ranges. Quantitative metrics-the fluctuation rate (adaptive: 0.07 vs. resonant: 0.15) and stability index (adaptive: 102 vs. resonant: 20)-exhibit adaptive matching's superior dynamic performance. These find ings present practical advice on selecting impedance matching techniques in real WPTapplications, such as electric vehicle charging and medical implants, where stability under variability is paramount.
A Hybrid Approach Based on Qualitative and Quantitative Techniques for Analyzing Last-Mile Parcel Delivery
(Springer India, 2025) Kanik, Zehra B.; Eriskan, Sibel; Soysal, Mehmet; Omurgonulsen, Mine
Operational excellence in last-mile delivery is becoming increasingly challenging, highlighting the need for a strategic assessment framework to improve decision-making processes. This study aims to provide a strategic assessment tool for last-mile parcel delivery processes, which are critical in terms of service levels, cost management and sustainability. The study presents a comprehensive approach to identify and prioritise feasible strategies by combining qualitative data obtained from expert opinions with Strengths, Weaknesses, Opportunities, and Threats analysis (SWOT) and Multi-Criteria Decision-Making (MCDM) methods. As a result of semi-structured interviews conducted with nine experts, 27 strategic criteria were identified and classified under SWOT dimensions. The 10 strategies developed during the interviews were evaluated by using the Intuitionistic Fuzzy Set (IFS) approach, which considers expert reliability, the Full Consistency Method (FUCOM) for weighting, and the Complex Proportional Assessment (COPRAS) technique for final ranking. There is a clear gap in the literature regarding critical criteria and strategies for last-mile delivery in developing economies. Since it is not possible to implement all strategies simultaneously due to limited resources, the strategies proposed in this study have been prioritised according to their relative importance. While expert-based evaluations in the literature typically assume that experts have equal influence, this study differs from the literature by weighting experts based on their level of experience. This approach not only addresses the gap in strategy and criterion development in the literature but also offers a more realistic and feasible approach from an implementation perspective. The findings show that all strategies are meaningful in improving last-mile performance, but their impact levels vary. "Developing public and corporate strategies for environmental sustainability" stands out as the highest priority strategy with a performance index of 100 points, while "Incorporating parcel transportation-related topics into logistics management education" is considered as the lowest priority strategy with 91.94 points. Limitations of this study arise from the niche nature of the sector and the small sample size.

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