Browsing by Author "Yorulmaz, Muhammet"

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Development of a decision support system to determine engineering student achievement levels based on individual program output during the accreditation process
(2021) Yorulmaz, Muhammet; Ic, Yusuf Tansel; 0000-0001-9274-7467; AGE-3003-2022; C-7863-2018
Accreditation studies and the number of programs that are accredited in engineering education are increasing day by day. In the auditing process, under the criteria of program outcomes, the level of individual students' achieving program outcomes is also considered as a sub-criterion. Failure to present a systematic approach to measuring the level of achievement of the program outcomes of the students who have reached the graduation stage in the evaluations or the use of questionnaires to measure them is considered insufficient evidence. In this study, a decision support system based on a multi-criteria decision-making model has been developed to determine the achievement levels of individual program outcomes (PO) of students who have reached the graduation stage of any engineering program. The MOORA (Multi- Objective Optimization on the basis of Ratio Analysis) method was used as a multi-criteria decision-making model, and the provision levels of POs were graded. In this way, the required evidence is created automatically by calculating the PO provision levels according to the compulsory and elective courses taken by the students at the graduation stage throughout their education life. We aimed to prevent the observed deficiencies and to set an example for the programs that will work the process. We developed a decision support system that can be used by engineering programs to determine whether their program satisfies accreditation requirements.
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.
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.
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%.
A Novel Gaze Input System Based on Iris Tracking With Webcam Mounted Eyeglasses
(2021) Yorulmaz, Muhammet; C-7863-2018
Due to the high cost of eye-tracking systems based on pupillary corneal reflections, efforts to develop a webcam-based eye-tracking system have increased to provide an affordable alternative to disabled people in recent years. However, due to the camera specification and location, ambient light changes and positional changes of the users, the gazing point of the eyes has not yet been determined precisely by such a system. Therefore, only 8 different gaze directions or up to 10 gaze regions could be detected in the previous webcam-based human-computer interaction studies. In this study, a novel gaze input system has been proposed to make the best use of the limited performance of webcam-based eye tracking and offer an economical alternative for disabled people. To reduce the impact of head movements, the webcam has been mounted to an ordinary glasses frame and positioned in front of the eye. For estimation of the gaze regions, a feature-based method (Hough transformation) was used by considering the circular shape of the iris and the contrast between the iris and sclera. The central coordinates of the iris image captured by the webcam were given to the k-nearest neighbor classifier. We performed a series of experiments with 20 subjects to determine the performance of the system and to investigate the effect of ambient light on the system's accuracy. The 23 regions that were gazed at by subjects were determined with an average accuracy of 99.54%. When the ambient light level was reduced by half, the accuracy decreased to 94.74%. As a result, it has been found that the proposed prototype allows more accurate recognition of a larger number of regions on the screen than previous webcam-based systems. It has been observed that system performance decreases if the ambient light is reduced by half.
Task and user-based Entropy-Rank Sum-TPOP integration proposal for usability evaluation of web applications
(2022) Yorulmaz, Muhammet; Bas, Gilin Feryal Can
The present study aims to determine the importance weights of the subjective and objective usability cri-teria based on task and user by considering these criteria simultaneously in the usability analysis of web applications. In this context, by proposing a Multi-criteria Decision Making approach including Entropy -Rank Sum (RS) - Technique of Precise Order Preference (TPOP) integration, the Multi-Dimensional Usability Analysis (MDUA) approach was advanced. The proposed analysis approach was applied on MOODLE software selected as a sample web application. The objective criteria in the sample application were measured using the Morae V3 program as a result of users performing their predefined tasks, and the subjective criteria were evaluated by determining the importance orders of the criteria for each user that affect the users' satisfaction. Subsequently, objective criteria weights were calculated by the Entropy method on task basis, and subjective criteria weights were computed by the RS method on user basis. In the last stage, the weights of the objective criteria and the weights of the subjective criteria that change according to the user are combined separately using the TPOP method. Thus, the most important subjec-tive and objective criteria for improving the usability of MOODLE LMS were determined. (c) 2022 The Authors. Published by Elsevier B.V. on behalf of King Saud University. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).