Scopus İndeksli Yayınlar Koleksiyonu
Permanent URI for this collectionhttps://hdl.handle.net/20.500.12573/395
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Article Citation - WoS: 3Citation - Scopus: 3Pericardial Fluid and Vascular Tissue Engineering: A Preliminary Study(Ios Press, 2021-03-23) Sonmezer, Dilek; Latifoglu, Fatma; Toprak, Guler; Duzler, Ayhan; Isoglu, Ismail AlperBACKGROUND: The heart is surrounded by a membrane called pericardium or pericardial cavity. OBJECTIVE: In this study, we investigated the pericardial fluid (PF) for coating polycaprolactone (PCL) scaffolds. PFS, which is a PF component, was used for the coating material. In addition to using PFS for surface coating, MED and fetal bovine serum (FBS) were also used for comparison. METHODS: Pericardial fluid cells (PFSc) isolated from PF were cultured on coated PCL scaffolds for 1, 3, and 5 days. Cell viability was determined using 3-(4, 5-di-methylthiazol- 2-yl)-2, 5-diphenyltetrazolium bromide (MTT) assay. RESULTS: The MTT assay results showed that the viability of cells on PCL scaffold coated with PFS increased over time (P < 0.005), and cell viability was significantly different between PCL scaffolds coated with PFS and non-coated PCL scaffolds. However, cell viability was significantly higher in the PCL scaffolds coated with PFS than non-coated and coated with FBS, MED, and PCL scaffolds. Scanning electron microscopy (SEM) microscopy images and MTT assay indicated that PFSc are attached, proliferated, and spread on PCL scaffolds, especially on PCL scaffolds coated with PFS. CONCLUSIONS: These results suggest that PFS is a biocompatible material for surface modification of PCL scaffolds, which can be used as a suitable material for tissue engineering applications.Article Handling Incomplete Data Classification Using Imputed Feature Selected Bagging (IFBAG) Method(Ios Press, 2021-07-09) Khan, Ahmad Jaffar; Raza, Basit; Shahid, Ahmad Raza; Kumar, Yogan Jaya; Faheem, Muhammad; Alquhayz, HaniAlmost all real-world datasets contain missing values. Classification of data with missing values can adversely affect the performance of a classifier if not handled correctly. A common approach used for classification with incomplete data is imputation. Imputation transforms incomplete data with missing values to complete data. Single imputation methods are mostly less accurate than multiple imputation methods which are often computationally much more expensive. This study proposes an imputed feature selected bagging (IFBag) method which uses multiple imputation, feature selection and bagging ensemble learning approach to construct a number of base classifiers to classify new incomplete instances without any need for imputation in testing phase. In bagging ensemble learning approach, data is resampled multiple times with substitution, which can lead to diversity in data thus resulting in more accurate classifiers. The experimental results show the proposed IFBag method is considerably fast and gives 97.26% accuracy for classification with incomplete data as compared to common methods used.Article Citation - WoS: 4Citation - Scopus: 4A New Oval Shaft, High Performance, 2 Pole Line Start Synchronous Reluctance Machine for Submersible Pump Applications(Ios Press, 2022-02-01) Tekgun, Didem; Alan, IrfanIn this paper, a 2 pole, 4 kW, 6 inches diameter line start synchronous reluctance machine (LS-SynRM) as a submersible water pump motor is designed and optimized with a new oval shaft structure. The aim is to improve the machine performance by widening the flux path on the rotor via narrowing down the shaft on the q-axis. This way a wider d-axis flux path is obtained, and accordingly, the d-axis inductance, the saliency ratio L-d/L-q, and the inductance difference L-d-L-q are increased. First, a set of structural analyses is carried out on a 7-flux barrier rotor in 3 stages: modal, harmonic, and static structural analyses. According to analysis results, the safe limit for the shaft size reduction is determined as 8 mm to avoid excessive deformations and undesired vibrations due to resonance. Later, the machine is optimized using Multi-Objective Differential Evolution (MODE) algorithm with a narrower shaft. The quality of the Pareto front solutions shows that the oval shaft machine is superior to the circular shaft machine in terms of efficiency, motor mass, and torque ripple. The maximum recorded efficiency improvement for the same size LS-SynRM is 4 points and the same size commercial induction machine is around 20 points.