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Article Citation - WoS: 24Citation - Scopus: 28Development of Amoxicillin-Loaded Electrospun Polyurethane/Chitosan Β-Tricalcium Phosphate Scaffold for Bone Tissue Regeneration(Ieee-inst Electrical Electronics Engineers inc, 2018) Topsakal, Aysenur; Uzun, Muhammet; Ugar, Gaye; Ozcan, Aslihan; Altun, Esra; Oktar, Faik Nuzhet; Gunduz, OguzhanBiocompatible nanocomposite electrospun fibers containing Polyurethane/Chitosan/beta-Tri calcium phosphate with diverse concentrations were designed and produced through the electrospinning process for bone tissue engineering applications. After the production process, density measurement, viscosity, electrical conductivity, and tensile strength measurement tests were carried out as physical analyses of blended solutions. The chemical structural characterization was scrutinized using Fourier transform infrared spectrometer (FTIR), and scanning electron microscopy (SEM) was used to observe the morphological details of developed electrospun scaffolds. Cell viability, attachment, and proliferation were performed using a L929 fibroblast cell line. Based on the physical, SEM, FTIR analysis, and cell culture studies, preferable nanofiber composition was selected for further studies. Amoxicillin (AMX) was loaded to that selected nanofiber composition for examination of the drug release. In comparison with other studies on similar AMX controlled products, higher drug loading and encapsulation efficiencies were obtained. It has been clearly found that the developed nanofiber composites have potential for bone tissue engineering applications.Article Citation - WoS: 5Citation - Scopus: 5A Study on the Performance of Magnetic Material Identification System by Sift-Brisk and Neural Network Methods(Ieee-inst Electrical Electronics Engineers inc, 2015) Ege, Yavuz; Nazlibilek, Sedat; Kakilli, Adnan; Citak, Hakan; Kalender, Osman; Karacor, Deniz; Sengul, GokhanIndustry requires low-cost, low-power consumption, and autonomous remote sensing systems for detecting and identifying magnetic materials. Magnetic anomaly detection is one of the methods that meet these requirements. This paper aims to detect and identify magnetic materials by the use of magnetic anomalies of the Earth's magnetic field created by some buried materials. A new measurement system that can determine the images of the upper surfaces of buried magnetic materials is developed. The system consists of a platform whose position is automatically controlled in x-axis and y-axis and a KMZ51 anisotropic magneto-resistive sensor assembly with 24 sensors mounted on the platform. A new identification system based on scale-invariant feature transform (SIFT)-binary robust invariant scalable keypoints (BRISKs) as keypoint and descriptor, respectively, is developed for identification by matching the similar images of magnetic anomalies. The results are compared by the conventional principal component analysis and neural net algorithms. On the six selected samples and the combinations of these samples, 100% correct classification rates were obtained.
