Scopus İndeksli Yayınlar Koleksiyonu
Permanent URI for this collectionhttps://hdl.handle.net/20.500.12416/8651
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Article Beam Shaping on a Fluorescent On-Chip Imaging System(IOP Publishing Ltd, 2026) Arpali, Caglar; Arpali, Serap AltayThe fluorescent on-chip imaging system differs from a conventional fluorescent microscope in terms of the imaging method because the sample is directly placed on the imaging sensor (i.e., charge-coupled device (CCD)). While this imaging modality presents several advantages, including a wide field of view and rapid scanning speed, it can be difficult to detect certain particles in dense and scattering environments, such as whole blood and tissue. These difficulties lead to a decreased signal-to-noise ratio (SNR) in the captured images, influenced by both the medium's light-transmitting capability and the excitation techniques used. In this paper, we quantitatively examine the effect of beam shaping techniques on a fluorescent on-chip imaging system from the SNR perspective. An experimental comparison is conducted between a Gaussian beam and plane-wave illumination generated by a novel phase modulation schema using our developed imaging platform. The results indicate that the Gaussian beam produces higher SNR images than plane waves when detecting fluorescent particles in a microchannel. Gaussian beam's higher energy confinement ability enhances the image quality of on-chip fluorescent imaging systems, particularly involving scattering-like medium limitations.Article An ALNS-Based Decision Support System for Scheduling and Routing in Home Healthcare With Lunch Break Constraints(Growing Science, 2025) Ozsakalli, Gokberk; Ozturkoglu, Omer; Qadri, Syed Shah Sultan Mohiuddin; Mohiuddin Qadri, Syed Shah SultanThis study addresses the daily scheduling and routing problem for home healthcare workers while incorporating lunch break requirements. The Home Healthcare Scheduling and Routing Problem is analysed alongside its common constraints, including patient and caregiver time windows, caregiver qualifications, and mandated breaks. To address this, four different variants of an effective Adaptive Large Neighbourhood Search (ALNS) algorithm were developed to provide high-quality solutions. The algorithms demonstrate significant efficiency, solving 30-patient instances optimally within an average of 12 seconds. For scenarios involving 100 patients, they maintained robust performance with a slight increase in computational time of about 54 seconds. Results indicate operational efficiency improvements of up to 36% through optimized travel routes and patient visitation schedules. To translate these findings into practice, a decision support system, the Home Healthcare Decision Support System (HHDSS), was designed to assist administrators by automating the complex task of scheduling and routing of caregivers. Tested using realistic patient data generated from Turkey, the system effectively allocates healthcare resources and improves responsiveness. Overall, the proposed framework shows strong potential as a valuable practical tool for improving the responsiveness and efficiency of home healthcare logistics. (c) 2026 by the authors; licensee Growing Science, CanadaArticle Perspectives on Audit Opinions and Key Audit Matters in the Global Airline Industry and the COVID-19 Pandemic(Multidisciplinary Digital Publishing Institute (MDPI), 2025) Dansık, Umutcan; Öztürk, C.The present study investigates whether the COVID-19 pandemic had a negative effect on audit opinion and led to differences in the composition of key audit matters (KAMs) observed in the airline industry. This study uses a sample of 55 airlines whose financial statements are based on International Financial Reporting Standards (IFRSs) and whose financial statement audit follows National or International Standards on Auditing (ISAs) for audit opinion, as well as a sample of 42 airlines whose financial statements are based on IFRSs and whose financial statement audit follows ISAs for the composition of KAMs. A textual analysis, a content analysis, a frequency distribution, and a chi-square test were conducted for the periods before, during, and after the COVID-19 pandemic. The findings reveal that the COVID-19 pandemic had no significant effect on audit opinion, except for one airline whose audit report declared a disclaimer of opinion. In contrast, the impairment of goodwill and intangible assets (as an industry-specific KAM) and going concern (as a KAM specific to the COVID-19 pandemic) were the two KAMs that were typically observed during the COVID-19 pandemic due to increased uncertainty. This was found to be the case, even though the main KAMs in the airline industry are usually revenue recognition; lease accounting; property, plant, and equipment (PPE); and hedge accounting. This study contributes to the debate on the effect of the COVID-19 pandemic on audit opinions and KAMs by offering evidence from the underexplored airline industry. © 2025 by the authors.Article An Investigation of Discontinuities in Time-Dependent 2D and 3D Parabolic Partial Differential Equations Utilizing Collocation Methods: A Comparative Analysis of Complex Interface Problems(Springer Heidelberg, 2025) Faheem, Muhammad; Asif, Muhammad; Amin, Rohul; Haider, Nadeem; Jarad, FahdParabolic double interface problems have many applications in the fields such as materials science, fluid dynamics, and heat transfer. This paper presents a comparison of the Haar wavelet-based collocation method and two variants of radial basis function (RBF) method for solving 2D and 3D, linear as well as nonlinear, parabolic double interface problems. The two variants of RBF methods are the multiquadric RBF method and the integrated RBF method. For linear problems, the system of equations obtained from the integrated RBF method is solved using Moore-Penrose pseudoinverse. Error analysis is performed using L infinity\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$L_\infty $$\end{document} norm error and root mean square error, and the findings are discussed in detail. The methods are compared based on their accuracy and efficiency in solving different benchmark problems. The results show that both the Haar wavelet collocation method and the integrated RBF method perform better than the conventional RBF method in terms of accuracy.Article Numerical and Experimental Investigation of Effects of Porous Layer on Cooling of Electronic Components(American Society of Mechanical Engineers (ASME), 2026) Kocak, E.; Türkoǧlu, H.In this study, heat transfer and temperature distribution characteristics of an electronic component covered with a porous medium were investigated both experimentally and numerically. An experimental setup was designed and constructed to conduct the experiments. For the numerical analysis, a computational fluid dynamics (CFD) software was developed on the OPENFOAM platform. The experimental results were used to validate the mathematical model and the computer program developed. The validated computer program was used to investigate the effects of Reynolds number, porosity, Darcy number, porous layer sizes, and the channel height on the heat transfer rate from the heat dissipating elements (electronic component) to the flow in wider ranges of the parameters. Using the Nusselt number values obtained both experimentally and numerically, a correlation equation was developed, and an artificial neural network architecture was trained for the Nusselt number. Results show that the Nusselt number increases with increasing Reynolds number, porosity, and the ratio of the height of the porous layer to the channel height. It was observed that the width of the porous medium has no noticeable effect on the Nusselt number. The correlation equation developed with four independent parameters predicts the Nusselt number with an average error of 7.59%. The artificial neural network architecture developed prevails as a more accurate tool, with a maximum error of 1%, for the prediction of the Nusselt number in the range of the parameters considered. © © 2026 by ASME.Article Propagation Characteristics of Higher-Order Annular Gaussian Beams in Oceanic Turbulence(Institute of Physics, 2025) Arpali, S.A.; Arpali, Ç.; Baykal, Y.This study aims to explore the propagation characteristics of higher-order annular Gaussian (HOAG) beams in oceanic turbulence. We provide an analytical derivation of the average intensity at the receiver plane based on excitation from a HOAG source field. Additionally, we conduct a detailed analyses of various beam intensity moments including kurtosis parameter, power-in-the-bucket (PIB) and the beam size variation. As oceanic turbulence strength increases, the HOAG beam gradually transforms into a pure Gaussian beam. As the strength of turbulence increases, PIB values for all modes of HOAG beams gradually decrease in an exponential manner until they stabilize, exhibiting behavior similar to that of Gaussian beams. It is also observed that modes of HOAG beams having larger mode numbers carry less energy to the receiver compared to lower-order modes as turbulence strength increases. Analyses of the kurtosis parameter for HOAG beams indicate that during propagation over intermediate distances, there is a tendency for more beam energy to be distributed toward the wings rather than to the center. In contrast, at longer distances, the beam redistributes its energy, resulting in a lower energy concentration in the wings compared to the center. This research can enhance our understanding of the effects of higher-order laser beams, thereby potentially facilitating longer communication distances in underwater wireless optical communication technologies. © 2025 IOP Publishing Ltd.Article Citation - WoS: 2Citation - Scopus: 2An Investigation of the Performance of Equal Channel Angular Pressed Copper Electrodes in Electric Discharge Machining(MDPI, 2025) Simsek, Ulke; Cogun, CanThis 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.Article Stylometric Analysis of Sustainable Central Bank Communications: Revealing Authorial Signatures in Monetary Policy Statements(MDPI, 2025) Emekci, Hakan; Ozkan, IbrahimSustainable 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.Article Indoor Soundscape Intervention (ISI) Criteria for Architectural Practice: A Systematic Review With Grounded Theory Analysis(MDPI, 2025) Ercakmak Osma, Ugur Beyza; Dokmeci Yorukoglu, Papatya NurIndoor 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.Article Self-Supervised Learning With BYOL for Non-Alcoholic Fatty Liver Disease Diagnosis Using Ultrasound Imaging(Springer London Ltd, 2025) Buktash, Ali; Gorur, Abdul KadirPurpose: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.