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Article Citation - WoS: 8Citation - Scopus: 8Berinde Mappings in Ordered Metric Spaces(Springer-verlag Italia Srl, 2015) Karapinar, Erdal; Sadarangani, KishinRecently, Samet and Vetro proved a fixed point theorem for mappings satisfying a general contractive condition of integral type in orbitally complete metric spaces (Samet and Vetro, Chaos Solitons Fractals 44:1075-1079, 2011). Our aim in this paper is to present a version of the results obtained in the above mentioned paper in the context of ordered metric spaces. Some examples are presented to distinguish our results from the existing ones.Article ISAR Imaging of Drone Swarms at 77 GHz(Tubitak Scientific & Technological Research Council Turkey, 2025) Coruk, Remziye Busra; Kara, Ali; Aydin, ElifThe proliferation of easily available, internet-purchased drones, coupled with the emergence of coordinated drone swarms, poses a significant security threat for airspace. Detecting these swarms is crucial to prevent potential accidents, criminal misuse, and airspace disruptions. This paper proposes a novel inverse synthetic aperture radar (ISAR) imaging technique for high-resolution reconstruction of drone swarms at 77 GHz millimeter wave (mmWave) frequency, offering a valuable tool for military and defense antidrone systems. The key parameters affecting down-range and cross-range resolution (0.05 m), ultimately enabling the generation of detailed ISAR images are discussed. Here, we create diverse scenarios encompassing various swarm formations, sizes, and payload configurations by employing ANSYS simulations. To enhance image quality, different window functions are evaluated, and the Hamming window is selected due to its highest peak signal-to-noise ratio (PSNR) (16.3645) and structural similarity (SSIM) (0.9067) values, ensuring superior noise reduction and structural preservation. The results demonstrate that the effectiveness of high-resolution ISAR imaging in accurately detecting and characterizing drone swarms pave the way for enhanced airspace security measures.Letter The Psychosocial Interventions for the Marmara Earthquake Children Survivors: The Lessons Learned(Taylor & Francis inc, 2021) Cihanoglu, Mine; Vatansever, Merve; Erden, Gulsen[No Abstract Available]Article Citation - WoS: 1Citation - Scopus: 1Principal and Nonprincipal Solutions of Impulsive Dynamic Equations: Leighton and Wong Type Oscillation Theorems(Springer, 2023) Zafer, A.; Akgol, S. Dogru; Doğru Akgöl, S.Principal and nonprincipal solutions of differential equations play a critical role in studying the qualitative behavior of solutions in numerous related differential equations. The existence of such solutions and their applications are already documented in the literature for differential equations, difference equations, dynamic equations, and impulsive differential equations. In this paper, we make a contribution to this field by examining impulsive dynamic equations and proving the existence of such solutions for second-order impulsive dynamic equations. As an illustration, we prove the famous Leighton and Wong oscillation theorems for impulsive dynamic equations. Furthermore, we provide supporting examples to demonstrate the relevance and effectiveness of the results.Review Citation - WoS: 3Citation - Scopus: 8Machine Learning for Sustainable Reutilization of Waste Materials as Energy Sources - a Comprehensive Review(Taylor & Francis inc, 2024) Peng, Wei; Sadaghiani, Omid Karimi; Karimi Sadaghiani, OmidThis work reviews Machine Learning applications in the sustainable utilization of waste materials as energy source so that analysis of the past works exposed the lack of reviewing study. To solve it, the origin of waste biomass raw materials is explained, and the application of Machine Learning in this section is scrutinized. After analysis of numerous papers, it is concluded that Machine Learning and Deep Learning are widely utilized in waste biomass production areas to enhance the quality and quantity of production, improve the predictions, diminish the losses, as well as increase storage and transformation conditions. The positive effects and application with the utilized algorithms and other effective information are collected in this work for the first time. According to the statistical analysis, in 20% out of the studies conducted about the application of Machine Learning and Deep Learning in waste biomass raw materials, Artificial Neural Network (ANN) algorithm has been applied. Afterward, the Super Vector Machine (SVM) and Random Forest (RF) are the second and third most-utilized algorithms applied in 15% and 14% of studies. Meanwhile, 27% of studies focused on the applications of Machine Learning and Deep Learning in the Forest wastes.Article Citation - Scopus: 13A Note on Ćirić Type Nonunique Fixed Point Theorems(Springer International Publishing, 2017) Karapınar,E.; Agarwal,R.P.In this paper, we suggest some nonunique fixed results in the setting of various abstract spaces. The proposed results extend, generalize and unify many existing results in the corresponding literature. © 2017, The Author(s).Conference Object Citation - WoS: 7Citation - Scopus: 7Effect of Hardening Models on Different Ductile Fracture Criteria in Sheet Metal Forming(Springer France, 2016) Dizaji, Shahram Abbasnejad; Darendeliler, Haluk; Kaftanoglu, Bilgin; Abbasnejad Dizaji, ShahramPrediction of the fracture is one of the challenging issues which gains attention in sheet metal forming as numerical analyses are being extensively used to simulate the process. To have better results in predicting the sheet metal fracture, appropriate ductile fracture criterion (DFC), yield criterion and hardening rule should be chosen. In this study, the effects of different hardening models namely isotropic, kinematic and combined hardening rules on the various uncoupled ductile fracture criteria are investigated using experimental and numerical methods. Five different ductile fracture criteria are implemented to a finite element code by the user subroutines. The criterion constants of DFCs are obtained by the related experimental tests. The in-plane principle strains obtained by the finite element analyses for different DFCs are compared with the experimental results. Also, the experimental results are used to evaluate the principle strain values calculated by the finite element analysis for different combinations of DFCs and hardening rules. It is shown that some DFCs give better predictions if the appropriate hardening model is employed.Article Citation - WoS: 5Citation - Scopus: 5Development and Psychometric Analysis of a Pediatric Oncology Nurses' Educational Needs Scale(Wiley, 2023) Kudubes, Asli Akdeniz; Semerci, Remziye; Ozbay, Sevil Cinar; Ay, Ayse; Boztepe, HandanBackground/objectivesIt is important to determine the educational needs of pediatric oncology nurses in order to maximize and implement nursing care interventions. Therefore, this study aims to develop a valid and reliable measurement tool to determine pediatric oncology nurses' educational needs and examine its psychometric properties. Design/methodsThis methodological study was conducted with 215 pediatric oncology nurses in Turkey between December 2021 and July 2022. Data were collected with the "Nurse Information Form" and "Pediatric Oncology Nurses' Educational Needs Scale." IBM SPSS 21.0 and IBM AMOS 25.0 software programs were used for data analysis, and descriptive statistics were used to analyze numeric variables. Exploration and confirmatory factor analyses were performed to determine the scale's factorial structure. ResultsThe factorial analysis was used to test the structural validity of the scale. A five-factor structure consisting of 42 items was developed. The Cronbach's alpha coefficient for "Illness" was .978, "Chemotherapy and Side Effect" was .978, "Another Therapy and Side Effect" was .974, "Palliative Care" was .967, "Supportive Care" was .985, and the total score was .990. Fit indices resulting from the study were chi(2)/SD: 3.961, root mean square error of approximation (RMSEA): 0.072, goodness-of-fit index (GFI): 0.95, comparative-of-fit index (CFI): 0.96, and normed fit index (NFI): 0.95. ConclusionThe Pediatric Oncology Nurses' Educational Needs Scale is a valid and reliable scale for pediatric oncology nurses to determine their educational needs.Article Citation - WoS: 14Citation - Scopus: 15Analysis of Temperature-Dependent Forward and Leakage Conduction Mechanisms in Organic Thin Film Heterojunction Diode With Fluorine-Based Pcbm Blend(Springer, 2020) Yildiz, D. E.; Gullu, H. H.; Toppare, L.; Cirpan, A.The forward and reversed biased current-voltage behaviors of the organic diode were detailed in a wide range of temperatures. In this diode, a donor-acceptor-conjugated copolymer system was constructed with poly((9,9-dioctylfluorene)-2,7-diyl-(2-dodecyl-benzo[1,2,3]triazole)) as a partner of [6,6]-phenyl-C61-butyric acid methyl ester (PCBM). Two-order of magnitude rectification ratio was achieved, and the temperature-dependent values of saturation current, zero-bias barrier height, and ideality factor were extracted according to the thermionic emission model. The temperature responses of these diode parameters showed an existence of inhomogeneity in the barrier height formation. As a result, the observed non-ideal behavior was explained by Gaussian distribution of barrier height where low-barrier regions are effective in the forward biased conduction mechanism at low temperatures. Together with this analysis, series resistances were evaluated using Cheung's functions and also density of interface states were investigated. On the other hand, reverse biased current flow was found under the dominant effect of Poole-Frenkel effects associated with these interfacial traps. The reverse current conduction mechanism was detailed by calculating characteristic field-lowering coefficients and barrier height values in the emission process from the trapped state in the range of temperatures of interest.Article Citation - WoS: 12Citation - Scopus: 13A New Mixed Δ-Shock Model With a Change in Shock Distribution(Springer, 2023) Chadjiconstantinidis, Stathis; Tuncel, Altan; Eryilmaz, SerkanIn this paper, reliability properties of a system that is subject to a sequence of shocks are investigated under a particular new change point model. According to the model, a change in the distribution of the shock magnitudes occurs upon the occurrence of a shock that is above a certain critical level. The system fails when the time between successive shocks is less than a given threshold, or the magnitude of a single shock is above a critical threshold. The survival function of the system is studied under both cases when the times between shocks follow discrete distribution and when the times between shocks follow continuous distribution. Matrix-based expressions are obtained for matrix-geometric discrete intershock times and for matrix-exponential continuous intershock times, as well.
