FSM Vakıf Üniversitesi Araştırma ve Akademik Performans Sistemi
DSpace@FSM, FSM Vakıf Üniversitesi’nin bilimsel araştırma ve akademik performansını izleme, analiz etme ve raporlama süreçlerini tek çatı altında buluşturan bütünleşik bilgi sistemidir.
Güncel Gönderiler
Öğe Türü: Öğe , Statistical Structure and Physical Interpretation of the Fillout Factor Distribution in Contact Binary Stars(EDP Sciences, 2026) Poro, A.; Li, K.; Paki, E.; Aliçavuş, F.; Alan, N.Contact binary systems exhibit complex evolutionary behavior governed by mass transfer, angular momentum loss (AML), and Roche geometry. The fillout factor (f) is widely used as a descriptor of the degree of overcontact, yet its physical and statistical role remains nonuniformly defined across the literature. We used a compiled observational sample of W UMa-type contact binaries to construct a data-driven classification framework based on f and its relation to fundamental system parameters. Unsupervised clustering applied to the one-dimensional f distribution reveals a robust three-class structure corresponding to shallow-, medium-, and deep-contact configurations. The statistically determined boundaries are located at f similar or equal to 0.257 and f similar or equal to 0.561, with a stable silhouette score of S similar or equal to 0.613. The stability of this classification is confirmed through perturbation tests in f and parameter-conditioned samples. A random forest regression model shows that 60.7% of the variance in f can be explained by the considered physical and geometric system parameters, with geometric parameters providing the largest predictive contribution. Among the considered parameters, the mass ratio emerges as the dominant predictor. The identified subclasses therefore appear to reflect a continuous geometric sequence rather than discrete physical states, governed by the progressive evolution of the Roche equipotential configuration under mass transfer and AML. Notably, the second boundary separating medium-and deep-contact systems shows lower stability than the first boundary, suggesting that the transition toward deep contact may be more sensitive to the physical composition of the analyzed sample.Öğe Türü: Öğe , Geometry-Aware Tumor Classification via Mean Curvature Flow on 3D Surface Meshes(IEEE, 2026) Arat, Mehdi Miraç; Karakaş, Bahar; Şimşek, Latif; Dal, Demet Yüksel; Demirci, Burcu Bektaş; Kuş, ZekiThis study presents a geometry-aware framework for binary tumor classification based on mean curvature flow (MCF) applied to reconstructed 3D surface meshes. Segmented medical image slices are converted into surface meshes and evolved under MCF. During the evolution, geometric descriptors, including quasi-conformal ratio, radial variance, and evolution speed, are extracted and concatenated into feature vectors. These descriptors are used with standard vector-based machine learning models for classification. Experimental results indicate that the proposed pipeline achieves competitive performance compared to a 3D CNN while providing practical advantages in terms of efficiency and structural interpretability.Öğe Türü: Öğe , Paths to Inclusive Early Childhood Education: Bridging the Reported Curriculum–Teacher Practice Gap in Türkiye and China(MDPI, 2026) Tursun, Mehliya; Akgül, Esra MacaroğluThis study examines inclusive early childhood education in China and Türkiye through a comparative qualitative analysis of policy, curriculum, and teacher perspectives. A two-stage research design was employed, combining document analysis of national early childhood education curricula with structured individual interviews involving 60 (30 from each country) early childhood teachers. Content analysis of data explored conceptualizations of inclusion, implementation practices, perceived barriers, and contextual influences. Findings reveal contrasting patterns in the relationship between policy and teacher-reported practices. Türkiye demonstrates more explicit curricular commitment to inclusion, with extensive references to diversity, participation, and individualized support. However, teachers frequently reported challenges in implementing these principles due to limitations in professional preparation, institutional support, and available resources. In contrast, Chinese curriculum documents contain fewer explicit references to inclusion; teachers described more pragmatic and contextually responsive implementation practices that facilitate the participation of children with diverse needs. Across both countries, cultural values, teacher agency, and school-level conditions emerged as significant factors influencing inclusive practice. The findings indicate that the policy–teacher-reported practice gap remains a central challenge in both contexts. The study argues that effective inclusion depends not only on policy commitments but also on the capacity of educators and institutions to translate policy into practice.Öğe Türü: Öğe , A Trade-Off Between Wear Resistance and Corrosion Protection in Sol–Gel SiO2–Al2O3 Hybrid Coatings on AISI 316L(Elsevier, 2026) Özer, Gökhan; Gecu, RıdvanIn this study, single-phase (SiO2 and Al2O3) and hybrid (SiO2–Al2O3) ceramic coatings were synthesized on 316L stainless steel via a sol–gel dip-coating route followed by thermal densification at 800°C for 1 h. Cross-sectional FE-SEM observations confirmed continuous, well-adhered coatings with uniform thicknesses ranging from 1.26 µm to 3.92 µm. Microstructural characterization revealed that incorporating alumina into the amorphous siloxane matrix induced the crystallization of hard γ-Al2O3 phase domains. Oliver–Pharr nanoindentation and Hertzian elastic contact stress analysis (1.6–2.0 GPa under 1 N) verified substantial mechanical reinforcement without macro-plastic substrate deformation. Tribological evaluations demonstrated that the 50% Al2O3–50% SiO₂ hybrid coating achieved superior wear resistance. Conversely, electrochemical evaluations via potentiodynamic polarization (Tafel) and Electrochemical Impedance Spectroscopy (EIS) revealed an opposite trend for corrosion protection. Single-phase 100% Al2O3 and 100% SiO2 coatings provided exceptional dielectric barrier protection, with ultra-low normalized corrosion current densities and high pore and charge-transfer resistances. In contrast, thermal expansion mismatch in the 50/50 hybrid induced an interconnected microcrack network, increasing apparent porosity and degrading Rc and Rct. Overall, these findings establish a fundamental microstructural trade-off in sol–gel oxide coatings between mechanical wear resistance and long-term electrochemical barrier integrity.Öğe Türü: Öğe , Enhancing the Accuracy of Low-Cost Pulse Oximetry via Edge AI: A Neural Network Approach Optimized for STM32 Microcontrollers(IEEE, 2026) Göksu, Ömer Faruk; Dal, Demet YükselAlthough pulse oximeters are widely used in clinical monitoring, low-cost sensors often exhibit reduced accuracy under altered perfusion and hypoxic conditions. This study proposes a deep learning-based Edge AI framework deployable on STM32 microcontrollers to enhance measurement reliability. Using the open-access OpenOximetry dataset, a neural network was trained with pulse-oximeter oxygen saturation (SpO2), Perfusion Index (PI), and Heart Rate (HR) as inputs, taking arterial oxygen saturation ( SaO2 ) as the reference standard. Evaluation on 3,918 independent test samples achieved a Mean Absolute Error (MAE) of 1.48% and R2 of 0.843, with a Bland-Altman mean bias of 0.16%. Post-training optimization using TensorFlow Lite reduced the model size to approximately 20 KB while maintaining inference latency below 2 ms. The results demonstrate that embedded deep learning can significantly improve low-cost pulse oximetry accuracy while enabling real-time, resource-efficient wearable monitoring.
