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Article Citation - WoS: 8Estimation of Polypropylene Concentration of Modified Bitumen Images by Using K-Nn and Svm Classifiers(Asce-amer Soc Civil Engineers, 2015) Tapkin, Serkan; Sengoz, Burak; Sengul, Gokhan; Topal, Ali; Ozcelik, ErolThe goal of this study is to design an expert system that automatically classifies the microscopic images of polypropylene fiber (PPF) modified bitumen including seven different contents of fibers. Optical microscopy was used to capture the images from thin films of polypropylene fiber modified bitumen samples at a magnification scale of 100 x. A total of 313 images were pre-processed, and features were extracted and selected by the exhaustive search method. The k-nearest neighbor (k-NN) and multiclass support vector machine (SVM) classifiers were applied to quantify the representation capacity. The k-NN and multiclass SVM classifiers reached an accuracy rate of 87% and 86%, respectively. The results suggest that the proposed expert system can successfully estimate the concentration of PPF in bitumen images with good generalization characteristics. (C) 2014 American Society of Civil Engineers.Article Citation - WoS: 11Citation - Scopus: 13Gesture-Based Interaction for Learning: Time To Make the Dream a Reality(Wiley, 2012) Ozcelik, Erol; Sengul, Gokhan[No Abstract Available]Article Citation - WoS: 15Citation - Scopus: 15Construct and Face Validity of the Educational Computer-Based Environment (ece) Assessment Scenarios for Basic Endoneurosurgery Skills(Springer, 2017) Cagiltay, Nergiz Ercil; Ozcelik, Erol; Sengul, Gokhan; Berker, MustafaBackground In neurosurgery education, there is a paradigm shift from time-based training to criterion-based model for which competency and assessment becomes very critical. Even virtual reality simulators provide alternatives to improve education and assessment in neurosurgery programs and allow for several objective assessment measures, there are not many tools for assessing the overall performance of trainees. This study aims to develop and validate a tool for assessing the overall performance of participants in a simulation-based endoneurosurgery training environment. Methods A training program was developed in two levels: endoscopy practice and beginning surgical practice based on four scenarios. Then, three experiments were conducted with three corresponding groups of participants (Experiment 1, 45 (32 beginners, 13 experienced), Experiment 2, 53 (40 beginners, 13 experienced), and Experiment 3, 26 (14 novices, 12 intermediate) participants). The results analyzed to understand the common factors among the performance measurements of these experiments. Then, a factor capable of assessing the overall skill levels of surgical residents was extracted. Afterwards, the proposed measure was tested to estimate the experience levels of the participants. Finally, the level of realism of these educational scenarios was assessed. Results The factor formed by time, distance, and accuracy on simulated tasks provided an overall performance indicator. The prediction correctness was very high for the beginners than the one for experienced surgeons in Experiments 1 and 2. When non-dominant hand is used in a surgical procedure-based scenario, skill levels of surgeons can be better predicted. The results indicate that the scenarios in Experiments 1 and 2 can be used as an assessment tool for the beginners, and scenario-2 in Experiment 3 can be used as an assessment tool for intermediate and novice levels. It can be concluded that forming the balance between perceived action capacities and skills is critical for better designing and developing skill assessment surgical simulation tools.
