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    An application for fundamental computer programming learning
    (Elsevier Science Bv, 2015) Aki, Ozan; Gullu, Aydin; Kaplanoglu, Erkan
    Applied computer laboratory lessons could be unproductive because of many students in there. Correcting students' mistakes one by one is wasting lesson time. Especially for beginners, most of these mistakes caused by complex integrated development environments. In this study, we develop a client server application for computer laboratories. Developed application is able to compile programming language source code remotely. Thus, students don't need to make something out of the writing source code. Furthermore, instructors don't need to install compiler to the each computer in laboratory. For start lesson, it is enough that server has just been configured. (C) 2015 The Authors. Published by Elsevier Ltd.
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    DETECTION OF DRIVER SLEEPINESS AND WARNING THE DRIVER IN REALTIME USING IMAGE PROCESSING AND MACHINE LEARNING TECHNIQUES
    (Lublin Univ Technology, Poland, 2017) Umut, Ilhan; Aki, Ozan; Ucar, Erdem; Ozturk, Levent
    The aim of this study is to design and implement a system that detect driver sleepiness and warn driver in real-time using image processing and machine learning techniques. Viola-Jones detector was used for segmenting face and eye images from the cameraacquired driver video. Left and right eye images were combined into a single image. Thus, an image was obtained in minimum dimensions containing both eyes. Features of these images were extracted by using Gabor filters. These features were used to classifying images for open and closed eyes. Five machine learning algorithms were evaluated with four volunteer's eye image data set obtained from driving simulator. Nearest neighbor IBk algorithm has highest accuracy by 94.76% while J48 decision tree algorithm has fastest classification speed with 91.98% accuracy. J48 decision tree algorithm was recommended for real time running. PERCLOS the ratio of number of closed eyes in one minute period and CLOSDUR the duration of closed eyes were calculated. The driver is warned with the first level alarm when the PERCLOS value is 0.15 or above, and with second level alarm when it is 0.3 or above. In addition, when it is detected that the eyes remain closed for two seconds, the driver is also warned by the second level alarm regardless of the PERCLOS value. Designed and developed real-time application can able to detect driver sleepiness with 24 FPS image processing speed and 90% real time classification accuracy. Driver sleepiness were able to detect and driver was warned successfully in real time when sleepiness level of driver is achieved the defined threshold values.
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    Remote access for education and control of mechatronics systems
    (Elsevier Science Bv, 2015) Gullu, Aydin; Aki, Ozan; Kuscu, Hilmi
    Applied training is important in mechatronics engineering, a multidisciplinary science. Laboratory practice should be done theoretical training to be efficient. Expert trainers are required for mechatronics education which is a complex science. In this study, a network infrastructure is made for education and control of modular production system which is a mechatronics system. The structure was applied to mechatronics laboratory where is Trakya University Ipsala Vocational School. In this way, an educator will provide the education of trainees, from any location with internet. Also, a modular production system can be controlled remotely. (C) 2015 The Authors. Published by Elsevier Ltd.