Mühendislik Fakültesi / Faculty of Engineering

Permanent URI for this collectionhttps://hdl.handle.net/11727/1401

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Author: search.filters.author.Yorulmaz, Muhammetsearch.filters.applied.f.language: search.filters.language.tur

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    Gaze-Controlled Turkish Virtual Keyboard Application with Webcam
    (2019) Yildiz, Metin; Yorulmaz, Muhammet; C-7863-2018
    In this study, an easy-to-use and inexpensive system aimed at solving the communication needs of people with disabilities such as ALS by writing with their eyes was introduced. The performance of the system are measured by writing speed (word per minutes) and error rate. The system consists of a webcam that fixed in front of the eye with a plastic eyeglass, and a computer. On the keyboard proposed in this study, the characters to be typed are placed at 22 discrete points which can be detected without error. 16 characters which are most used in Turkish (total %85 usage rate), can be selected with a single gaze. Other characters can be selected with gazing these points with a dwell time. The iris circle on the image recorded by the camera is found according to the Hough transform and the position of the center coordinates of the eye is classified by using the k-nearest neighbor algorithm from the machine learning methods and the character to be written is determined. In order to select the letters at the gaze points, the letter that is highlighted by the software in voice and color is moved to the writing area in the middle of the screen by eye. As a result of the first experiments, it has been observed that the system developed allows the average of 6.63 words per minute (approximately 33 letters) to be written with an error rate of 0.86%.
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    Eye Gaze Location Detection Based On Iris Tracking with Web Camera
    (2018) Yildiz, Metin; Yorulmaz, Muhammet; C-7863-2018
    In recent years, there has been an increased interest in human computer interaction systems where web cameras are used as input devices. In this study, a system developed to distinguish eye gaze locations on the screen by referring to the position of the iris part of the eye is introduced. It is aimed to distinguish more eye gaze location compared to the previous works by web cam. K-nearest neighbors classifier was used to detect eye gaze location by the feature vector of the iris center coordinates. As a result of the first experiments with 10 subjects, the 17 different eye gaze locations on the screen have classified with an average of 97.64% accuracy. It has been observed that only the two adjacent points near the center of the screen in the vertical direction are detected incorrectly. It is expected to increase the classification performance ratio by not using these two incorrectly detected points in future studies.
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    Evaluation of performance levels of students for moodle learning management system in terms of usability Criteria with PSI-Entropy-Marcos integration
    (2022) Yorulmaz, Muhammet; Can, Gulin Feryal
    The study, it is aimed to determine and compare the end-user performances within the scope of achieving the determined objectives while using the Moodle Learning Management System (LMS). Accordingly, considering multiple usability criteria, 18 users were prioritized in terms of their performances in using Moodie LMS. In this direction, Preference Selection Index (PSI) and Entropy integration was used to determine the importance weights of usability criteria, and the Measurement of Alternatives and Ranking according to Compromise Solution (MARCOS) method was used to prioritize the end-users. A new hybrid weighting method has been proposed by integrating the PSI method with the Entropy method, taking into account both the uncertainty in the performance values of the end-users according to the criteria and the preference change values of the criteria. This proposed method is applied for a three-dimensional initial decision matrix Thus, the traditional two-dimensional initial decision matrix which consists of the alternatives and the values that the alternatives take according to the criteria, has been developed and made more flexible. The objective criteria taken into account in the analysis were measured by the Morae V3 program, with the tasks defined as predetermined goals being performed by the users on the Moodie LMS. In addition, the criteria weights obtained from the proposed PSI-Entropy integration were used in the MARCOS method to rank the end-users according to their performance levels.