Scopus İndeksli Yayınlar Koleksiyonu
Permanent URI for this collectionhttps://hdl.handle.net/20.500.12573/395
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Article Non-Contact Acoustic Screening for Sleep Apnea: A Subject-Aware Deep Learning Approach(Springer Science and Business Media Deutschland GmbH, 2026-02-11) Aygün Çakıroğlu, M.; Kizilkaya Aydoǧan, E.; Bolatturk, Ö.F.; Aydoğan, S.; Ismailoǧullari, S.; Delice, Y.Purpose: To explore the feasibility of using camera-derived, non-contact audio synchronized with PSG for clinically relevant sleep-apnea classification, and to benchmark compact deep models under a subject-aware design using a previously unstudied, real-world dataset. Methods: Thirty-two adults underwent simultaneous polysomnography (PSG) and camera-based non-contact audio recording. The synchronized audio segments were used to train and compare three compact deep-learning architectures (convolutional, attention-augmented, and transformer-based) under a subject-aware evaluation design that prevented identity leakage. Model performance and calibration were assessed at both segment and subject levels using standard statistical tests. Results: Subject-level evaluation was based on a very small, imbalanced test set of six subjects (one positive). Within this limited yet previously unstudied local dataset, the CNN_trans model achieved an apparent perfect ranking performance (AUC = 1.00; 95% CI 0.00–1.00), though this likely reflects the small, imbalanced test cohort, with recall = 1.00 and precision = 0.55. The wide confidence interval reflects substantial statistical uncertainty, and DeLong comparisons showed no significant AUC difference between CNN_trans and CNN_att (ΔAUC = − 0.042; p = 0.43). Conclusion: PSG-synchronized, non-contact audio supports accurate and well-calibrated sleep-apnea classification with compact deep models. This subject-aware evaluation suggests that contactless acoustic monitoring may have potential clinical relevance, motivating larger, multi-site validation. © The Author(s), under exclusive licence to Springer Nature Switzerland AG 2026.Article Process Optimization of Buckwheat Starch Myristic Acid Complex Film(John Wiley and Sons Inc, 2026-02) Koca, E.; Oskaybaş-Emlek, B.; Kahraman, K.; Özbey, A.; Aydemir, L.Y.; Oskaybas Emlek, BetulIn this study, it was aimed to develop an edible film from an amylose-lipid complex with better mechanical properties and water vapor barrier. For this purpose, the buckwheat starch (BS) is modified with myristic acid (MA) and the edible film production process was optimized by using central composite design with 4 center points where film forming solution's glycerol concentration, pH, and the temperature of as dependent variable and tensile strength (TS), elongation at break (EAB) value and Young's modulus (YM) as response. The models were significant for TS and YM, and the glycerol concentration and temperature had a significant effect on the TS of the films. The edible film produced in validated optimized conditions had better EAB (149%) and TS (1.064 MPa), and lower water solubility (44.7%) and water vapor permeability (0.39 g × mm/m2 × h × kPa) than control film (p < 0.05). There was no significant change in color values, but an increase in opacity (2.14). With the formation of the BS-MA complex, increased surface roughness and more hydrophilic (contact angle = 92.4°) films were obtained. These findings demonstrate that the BS-MA complex film has significant potential for practical applications as an edible film. © 2026 Wiley-VCH GmbH.Article Noninvasive Condition Monitoring for Eccentricity Fault Detection in Large Hydro Generators(TÜBİTAK Scientific & Technological Research Council Turkey, 2026-01-16) Lemeski, Atena Tazikeh; Tekgun, Didem; Keysan, Ozan; Leblebicioglu, Kemal; Gol, Murat; Leblebicioglu, Mehmet KemalEccentricity faults in electric machines remain a critical concern, as they generate uneven magnetic forces that increase vibration and noise, ultimately raising the risk of premature motor failure. This study proposes a method for the early detection of dynamic eccentricity (DE) faults in hydropower plants through an advanced optimization-based parameter identification technique integrated with finite element analysis (FEA). Finite element modeling (FEM) is first used to analyze an existing salient-pole synchronous generator (SPSG) from a hydroelectric power plant in T & uuml;rkiye. The effects of DE faults on the SPSG's magnetic equivalent circuit parameters are then examined under various fault severities. A comprehensive hydropower plant model-including the synchronous generator, governor, and excitation system-is developed in MATLAB/Simulink, with all input parameters obtained from real plant data and equivalent circuit variations extracted from FEA. After completing the modeling stage, including fault scenarios, MATLAB and Simulink are employed together to estimate key magnetic equivalent circuit parameters using a modified particle swarm optimization (MPSO) algorithm, achieving highly accurate parameter estimation. Since the hydropower system allows measurement of the three-phase output currents, parameter estimation is performed based on current variations under different fault conditions. The simulation results verify the method's ability to detect faults with high accuracy; thus, this integrated and noninvasive approach provides a robust framework for ensuring the operational reliability and longevity of large hydro generators.Article Comparative Analysis of Modulation Shapes on Laser Diode Performance with a High-Efficiency LLC Resonant Converter Driver(Wiley, 2026-02-06) Yigit, Hayri; Rifat boynuegri, Ali; Tekgun, Burak; Rifat Boynuegri, AliHigh-power laser diodes (LDs) are key components in laser-based wireless power transfer (WPT) systems, where end-to-end efficiency is one of the most critical performance metrics. This study investigates the driving performance of an LD powered by a high-efficiency LLC resonant converter under three distinct excitation waveforms-sinusoidal, triangular, and rectified-sine-using a MATLAB/SIMULINK model and an experimental setup designed to reproduce real-world operating conditions. Each waveform is synthesized through frequency modulation of a full-bridge inverter stage and filtered at the output. The analysis examines the impact of modulation shape on output current ripple, converter efficiency, and overall LD efficiency. Experimental validation confirms the simulation trends, underscoring the trade-offs between waveform smoothness, implementation complexity, and efficiency. Beyond confirming that constant-current operation yields the highest LD efficiency, this study explicitly quantifies how low-frequency current ripple induced by different modulation waveforms propagates through the LLC resonant converter, alters RMS current stress, and translates into measurable efficiency degradation at both the driver and LD levels. By experimentally correlating waveform symmetry, ripple magnitude, and loss mechanisms, the work establishes practical design boundaries for waveform-modulated laser drivers in WPT systems.Article Spatial Dimension of the Local Phenomenon in Kayseri(Gazi University, Faculty of Engineering Architecture, 2025-12-31) Ozmen, Nihan Mus; Asiliskender, BurakKayseri is in the centre of Anatolia, at the intersection of trade and military routes, and possesses a rich cultural heritage. Throughout its history, the city has hosted various civilizations, developing around a central castle and continuing to expand, particularly after the 19th century. Kayseri has long served as a meeting point for diverse cultures. Within this diversity, families known as locals, whose origins date back to the oldest neighbourhoods within the city walls, have held significant mercantile power. These local families regard themselves as the actual owners of Kayseri and have influenced the city's developmental trajectory. Over time, they have moved outward from the centre to newly developed neighbourhoods, first to the north and then to the east. This study examines the urban development of Kayseri in the 20th century and the spatial mobility of these local families. It employs qualitative methods such as ethnographic observation, oral history interviews, and GIS-based thematic mapping to analyse these movements in a multi-layered way. The study also aims to understand Kayseri's socio-cultural dynamics and historical texture by investigating the role of local families in the city's physical and functional transformations. In this context, it addresses the physical and functional changes in neighbourhoods vacated by these relocations.Article Deep-Learning Detection of Open-Apex Teeth on Panoramic Radiographs Using YOLO Models(Springer, 2025-12-23) Edik, Merve; Celebi, Fatma; Cukurluoglu, AykaganObjectivesThe use of deep learning in detecting teeth with open apices can prevent the need for additional radiographs for patients. The presented study aims to detect open-apex teeth using You Only Look Once (YOLO)-based deep learning models and compare these models.MethodsA total of 966 panoramic radiographs were included in the study. Open-apex teeth in panoramic radiographs were labeled. During the labeling process, they were divided into 6 classes in the maxilla and mandible, namely incisors, premolars, and molars. AI models YOLOv3, YOLOv4, and YOLOv5 were used. To evaluate the performance of the three detection models, both overall and separately for each class in the test dataset, precision, recall, average precision (mAP), and F1 score were calculated.ResultsYOLOv4 achieved the highest overall performance with a mean average precision (mAP) of 87.84% at IoU (Intersection over Union) 0.5 (mAP@0.5), followed by YOLOv5 with 85.6%, and YOLOv3 with 84.46%. Regarding recall, YOLOv4 also led with 90%, while both YOLOv3 and YOLOv5 reached 89%. Moreover, the F1 score was the highest for YOLOv4 (0.87), followed by YOLOv3 (0.86) and YOLOv5 (0.85).ConclusionsIn this study, YOLOv3, YOLOv4, and YOLOv5 were evaluated for the detection of open-apex teeth, and their mAP, recall, and F1 scores exceeded 84%. Deep learning-based systems can provide faster and more accurate results in the detection of open-apex teeth. This may help reduce the need for additional radiographs from patients and aid dentists by saving time.Article Toward the Design of New Α-Carboline Derivatives Against Anaplastic Lymphoma Kinase (Alk): A Comprehensive in Silico Approach(Wiley-VCH Verlag GmbH, 2025-11) Sari, Ceyhun; Akcok, IsmailAfter the first description of anaplastic lymphoma kinase (ALK) in an anaplastic large cell lymphoma cell line as a nucleophosmin (NPM) fusion partner, ALK and its various fusion partners have been implicated in numerous cancers such as non-small cell lung cancer (NSCLC), anaplastic large cell lymphoma (ALCL), neuroblastoma, and rhabdomyosarcoma. In the last decade, several compounds targeting ALK have been developed and approved by the Food and Drug Administration (FDA). Despite the advances of generations of ALK inhibitors, a recent study highlighted that around half of the ALK-positive NSCLC patients will go through disease progression in response to first-line alectinib, which is a second-generation ALK inhibitor. In this study, we aimed to propose a novel alpha-carboline compound targeting the ALK tyrosine kinase domain to be used against various types of cancer in which ALK fusion proteins may be involved. In this regard, we designed more than 200 alpha-carboline derivatives and investigated their binding properties against ALK tyrosine kinase by using in silico protocols consisting of molecular docking studies, molecular dynamics simulations, MM/PBSA binding free energy calculation, and essential dynamics analysis. Considering the obtained results, we developed two promising candidates, compounds 208 & 209 with -9.05 and -9.80 binding energies, respectively, which demonstrated improved binding profiles over the course of a 300 ns simulation.Article Modeling and Simulation of Dynamic Energy Management Systems for Smart Buildings(TÜBİTAK, 2025-11-25) Ozel, O.; Rıfat Boynueğrİ, A.; Yigit, H.; Tekgun, B.; Boynuegri, Ali RifatThis study presents a dynamic energy management system tailored for smart residential buildings, integrating thermal and electrical models to achieve both natural gas and electricity bill cost reduction. By harnessing wind and solar energy sources, the system aims to meet the diverse energy needs of modern homes. Through load shifting and thermal storage strategies, known as power-to-heat (P2H) approaches, the system ensures efficient renewable energy utilization while maintaining resident comfort. Validation of the proposed system was conducted using real-world data from the Yıldız Technical University Smart Home Laboratory, demonstrating its practical applicability and effectiveness. Results indicate significant reductions in both natural gas and electricity consumption, leading to substantial cost savings. Specifically, the proposed system reduced natural gas consumption by 3.79% and electricity consumption by 35.62%, highlighting its potential to enhance energy efficiency and sustainability in residential settings. © This work is licensed under a Creative Commons Attribution 4.0 International License.Article Developing a Label Propagation Approach for Cancer Subtype Classification Problem(TUBITAK, 2021) Güner, P.; Bakir-Güngör, B.; Coşkun, M.; Şahan, Pınar GünerCancer is a disease in which abnormal cells grow uncontrollably and invade other tissues. Several types of cancer have various subtypes with different clinical and biological implications. Based on these differences, treatment methods need to be customized. The identification of distinct cancer subtypes is an important problem in bioinformatics, since it can guide future precision medicine applications. In order to design targeted treatments, bioinformatics methods attempt to discover common molecular pathology of different cancer subtypes. Along this line, several computational methods have been proposed to discover cancer subtypes or to stratify cancer into informative subtypes. However, existing works do not consider the sparseness of data (genes having low degrees) and result in an ill-conditioned solution. To address this shortcoming, in this paper, we propose an alternative unsupervised method to stratify cancer patients into subtypes using applied numerical algebra techniques. More specifically, we applied a label propagation-based approach to stratify somatic mutation profiles of colon, head and neck, uterine, bladder, and breast tumors. We evaluated the performance of our method by comparing it to the baseline methods. Extensive experiments demonstrate that our approach highly renders tumor classification tasks by largely outperforming the state-of-the-art unsupervised and supervised approaches. © 2022 Elsevier B.V., All rights reserved.Article Citation - Scopus: 3Chaos in PID Controlled Nonlinear Systems(Korean Institute of Electrical Engineers, 2015) Ablay, G.Controlling nonlinear systems with linear feedback control methods can lead to chaotic behaviors. Order increase in system dynamics due to integral control and control parameter variations in PID controlled nonlinear systems are studied for possible chaos regions in the closed-loop system dynamics. The Lur’e form of the feedback systems are analyzed with Routh’s stability criterion and describing function analysis for chaos prediction. Several novel chaotic systems are generated from second-order nonlinear systems including the simplest continuous-time chaotic system. Analytical and numerical results are provided to verify the existence of the chaotic dynamics. © 2021 Elsevier B.V., All rights reserved.