Scopus İndeksli Yayınlar Koleksiyonu
Permanent URI for this collectionhttps://hdl.handle.net/20.500.12416/8651
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Article Enhanced Mapping of Rainfall Induced Landslide Susceptibility Using a Deep Feedforward Neural Network with Soft Computing(Techno-Press, 2026) Zhu, Licai; Akagic, Amila; Nanehkaran, Yaser A.; Pusatli, Tolga; Mahmud, Elkhan; Jian, DongThe presented study attempted to propose enhanced rainfall-induced landslide susceptibility mapping method by using the Deep Feedforward Neural Network (DFNN) which is developed for analysis the non-liner feature detection in landslide susceptibility analysis. To evaluate our approach, a comprehensive dataset of triggering factors was compiled, encompassing historical landslide occurrences with total of 107 records, rainfall data, geological information, seismicity, human-activities, and topographic attributes. Through rigorous training and testing procedures, the DFNN demonstratedsuperior ability for generalization and superior performance. The effectiveness of the selected method is demonstrated on the data from the Zanjan County, known for its diverse geographical, geological, and hydrological characteristics, which are pivotal factors in mapping of landslide susceptibility. Results showcased a substantial enhancement in the accuracy of mapping of rainfall-induced landslide susceptibility for the Zanjan County, which is compared with benchmark learning classifiers. According to the results of the study, it appeared that the northeastern and southwestern area of the Zanjan County can be deemed to have a high to very-high risk of landslide occurrence, which is validated via benchmark classifiers. The western part of the Zanjan County was observed to have a very low to low risk.Article Widths and Entropy of Sets of Smooth Functions on Compact Homogeneous Manifolds(Tubitak, 2021) LEVESLEY, Jeremy; KUSHPEL, Alexander; Taş, KenanWe develop a general method to calculate entropy and n-widths of sets of smooth functions on an arbitrary compact homogeneous Riemannian manifold Md . Our method is essentially based on a detailed study of geometric characteristics of norms induced by subspaces of harmonics on Md . This approach has been developed in the cycle of works [1, 2, 10–19]. The method’s possibilities are not confined to the statements proved but can be applied in studying more general problems. As an application, we establish sharp orders of entropy and n-widths of Sobolev’s classes Wγ p ( Md ) and their generalisations in Lq ( Md ) for any 1 < p, q < ∞. In the case p, q = 1, ∞ sharp in the power scale estimates are presented.Article Vessel Segmentation in MRI Using a Variational Image Subtraction Approach(Tubitak Scientific & Technological Research Council Turkey, 2014) Nar, Fatih; Saran, Ayse Nurdan; Saran, MuratVessel segmentation is important for many clinical applications, such as the diagnosis of vascular diseases, the planning of surgery, or the monitoring of the progress of disease. Although various approaches have been proposed to segment vessel structures from 3-dimensional medical images, to the best of our knowledge, there has been no known technique that uses magnetic resonance imaging (MRI) as prior information within the vessel segmentation of magnetic resonance angiography (MRA) or magnetic resonance venography (MRV) images. In this study, we propose a novel method that uses MRI images as an atlas, assuming that the patient has an MRI image in addition to MRA/MRV images. The proposed approach intends to increase vessel segmentation accuracy by using the available MRI image as prior information. We use a rigid mutual information registration of the MRA/MRV to the MRI, which provides subvoxel accurate multimodal image registration. On the other hand, vessel segmentation methods tend to mostly suffer from imaging artifacts, such as Rician noise, radio frequency (RF) inhomogeneity, or partial volume effects that are generated by imaging devices. Therefore, this proposed method aims to extract all of the vascular structures from MRA/MRI or MRV/MRI pairs at the same time, while minimizing the combined effects of noise and RF inhomogeneity. Our method is validated both quantitatively and visually using BrainWeb phantom images and clinical MRI, MRA, and MRV images. Comparison and observer studies are also realized using the BrainWeb database and clinical images. The computation time is markedly reduced by developing a parallel implementation using the Nvidia compute unified device architecture and OpenMP frameworks in order to allow the use of the method in clinical settings.Article Two-Variable Quantum Integral Inequalities of Simpson-Type Based on Higher-Order Generalized Strongly Preinvex and Quasi-Preinvex Functions(MDPI AG, 2020) Rashid, Saima; Baleanu, Dumitru; Idrees, Muhammad; Kalsoom, Humaira; Chu, Yu-MingArticle The Analytical Analysis of Time-Fractional Fornberg-Whitham Equations(MDPI AG, 2020) Baleanu, Dumitru; Shah, Rasool; Aly, Shaban; Khan, Hassan; Alderremy, A.A.Article The Lebesgue Constants on Projective Spaces(Tubitak Scientific & Technological Research Council Turkey, 2021) Kushpel, AlexanderWe give the solution of a classical problem of Approximation Theory on sharp asymptotic of the Lebesgue constants or norms of the Fourier-Laplace projections on the real projective spaces P-d (R). In particular, these results extend sharp asymptotic found by Fejer [2] in the case of S-1 in 1910 and by Gronwall [4] in 1914 in the case of S-2. The case of spheres, S-d, complex and quaternionic projective spaces, P-d(C), P-d(H) and the Cayley elliptic plane P-16 (Cay) was considered by Kushpel [8].Article Soliton Solutions of Mathematical Physics Models Using the Exponential Function Technique(MDPI AG, 2020) Javeed, Shumaila; Waheed, Asif; Suleman, Muhammad; Baleanu, Dumitru; Atif, M.; Alimgeer, Khurram Saleem; Nawaz, SidraArticle Simheuristic Framework for Optimizing Urban Mobility at Signalized Roundabouts(DAAAM International Vienna, 2026) Gokce, M. A.; Qadri, S. S. S. M.; Oner, E.Managing high traffic volumes and traffic congestion at signalized intersections remains a critical urban challenge. Appropriate traffic signal timing (TST) and phase sequencing are essential for ensuring smooth traffic flow. This study presents a microscopic simulation-based heuristic optimization (Simheuristic) framework using the Genetic Algorithm (GA) for optimizing the TST of Four-Legged Two-stops Signalized Roundabouts (FLTSR). The framework is tested using the actual traffic flow through a microscopic simulation model developed in Simulation for Urban Mobility (SUMO). Within this framework, the integrated GA searches for the green TSTs to minimize vehicular queue lengths, while SUMO is used to evaluate those timings. Additionally, four different phase sequence settings are evaluated to find the efficient configuration. The proposed approach is benchmarked against Webster's method and the existing TST plan. In the best-case scenario, the proposed framework improves vehicular flow by mitigating the average time loss, average waiting time, and the average number of vehicles in a queue at the FLTSR up to 35.83 %, 51.91 %, and 50.97 %, respectively, compared to the current setting. (Received in November 2025, accepted in January 2026. This paper was with the authors 1 month for 1 revision.)Article Singular Dirac Systems in the Sobolev Space(Tubitak Scientific & Technological Research Council Turkey, 2017) Ugurlu, EkinIn this paper we construct Weyl's theory for the singular left-definite Dirac systems. In particular, we prove that there exists at least one solution of the system of equations that lies in the Sobolev space. Moreover, we describe the behavior of the solution belonging to the Sobolev space around the singular point.Article Shape-Preserving Properties of a Relaxed Four-Point Interpolating Subdivision Scheme(MDPI AG, 2020) Baleanu, Dumitru; Nisar, Kottakkaran Sooppy; Ghaffar, Abdul; Khan, Faheem; Ashraf, Pakeeza; Sehar, Irem