Yazar "Ceven, Suleyman" seçeneğine göre listele

Listeleniyor 1 - 2 / 2
  • Küçük Resim
    Öğe
    Design and implementation of modular test equipment for process measurements in mechatronics education
    (Wiley, 2020) Ceven, Suleyman; Albayrak, Ahmet
    In this study, an experimental setup is presented which is developed to enrich mechatronics education in terms of content and to provide a variety of applications. The experimental setup was developed to enable students to learn through more practical experiments. The main purpose of this study is to develop an experimental setup that can be used as a basic application tool for many courses that will eliminate the deficiencies in mechatronics education. In addition, the experimental setup contributes to the learning of equipment commonly used in mechatronic systems and to enable students to graduate more readily for the industry. This methodology, which was taken into consideration when designing the experimental setup, provided the students with the basic skills that enable them to acquire interdisciplinary knowledge more easily and achieve a successful career. The experimental setup was tested in process measurements course. For the mechanism which was tested with 65 students, the opinions of the students were taken with the help of a questionnaire. These opinions were analyzed with SPSS software. As a result of the analysis, Cronbach's alpha was calculated and found to be .815. In addition, descriptive statistics and chi(2) tests were conducted on the questionnaire results. As a result of all these analyzes, it was seen that the experimental setup should be made more interactive. With the integration of new technologies, the experimental setup will be available for many years in associate degree and undergraduate education.
  • Küçük Resim
    Öğe
    Modeling of migratory beekeeper behaviors with machine learning approach using meteorological and environmental variables: The case of Turkey
    (Elsevier, 2021) Albayrak, Ahmet; Ceven, Suleyman; Bayir, Raif
    In this study, migratory beekeeping behavior, which is an important form of beekeeping, has been modeled. Modeling was performed in conditions of Turkey. Modeling was made by considering food sources (nectar / pollen) and meteorological variables (temperature, humidity, number of rainy days, number of cloudy days and sunshine duration) for Turkey in which migratory beekeeping carried out in a different form than in developed countries. The main output in migratory beekeeping is honey production. Considering honey production, modeling has been made with the food sources and meteorological variables that have the greatest effect on honey production. Since the data set developed for modeling consists of relatively few samples, the ensemble learning approach was preferred from the machine learning approaches. Random Forest and Decision Tree algorithms, which are among the ensemble learning techniques, were used. As a result, the migratory beekeeping behavior was correctly classified at a rate of 92%. As a result of classification of Turkey's 81 provinces in five different categories, it was concluded that 33 provinces are suitable for migratory beekeeping at different times of the year. These 33 provinces are regions in the good and very good categories. In the next stage, thematic maps were produced for migratory beekeepers. Maps were produced for each month of the year. Thus, a guidance and information system has been obtained for migratory beekeepers.