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All Journal International Journal of Intelligent Systems and Applications in Engineering
TASDEMIR, Sakir
Advanced Technology and Science (ATScience)
Computer Science & IT

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Stemming Implementation in Preprocessing Phase for Evaluating of Exams Using Data Mining Approach BALCI, Mehmet; TASDEMIR, Sakir; SARACOGLU, Ridvan
International Journal of Intelligent Systems and Applications in Engineering Vol 5, No 2 (2017)
Publisher : Advanced Technology and Science (ATScience)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.18201/ijisae.2017529086

Abstract

In educational activities, examinations are sometimes carried out in the form of multiple-choice tests or sometimes as open-ended long texts. When multiple-choice tests are performed, evaluating process is carried out either manual or computer-assisted. Exam questions prepared in the form of multiple choice tests are not suitable for every course. It may be necessary to use open-ended questionnaires in order for pupils to accurately measure their achievement in relation to the course. It can take a long time to evaluate examinations made with such questions. However, this process can create problems in terms of objective evaluation. Data mining, defined as the extraction of useful information from large quantities of data, can be used to process all kinds of data. The data mining method used in the processing of textual data is called text mining. In text processing studies, data is subject to preprocessing in order to obtain a high quality data set. The most important stage of preprocessing is stemming. In this study, stemming process is implemented to questions and correct answers taken from students. The results obtained in 2 different samples and 4 sentences are 71%, 69%, 86% and 78% correct. In order to be able to distinguish what the textual data written in the natural language really is, it is necessary to use the states of the words which are made up of construction and free from the suffixes. Therefore, in the pre-processing phase, stemming process is applied to the textual data in accordance with the grammar rules of the language they are written on, and stems of every word are found. Text processing is used in many areas of the natural language. Computer-aided solutions will be inevitable so that problems can be eliminated and open-ended questions can be quickly assessed. Despite the desirability of a computer aided solution for this measurement technique, studies of this solution are not included in the literature very much.
Determination of Wind Potential of a Specific Region using Artificial Neural Networks Tasdemir, Sakir; Yaniktepe, Bulent; Guher, A.Burak
International Journal of Intelligent Systems and Applications in Engineering Vol 5, No 3 (2017)
Publisher : Advanced Technology and Science (ATScience)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.18201/ijisae.2017531433

Abstract

There is a widespread trend in alternative energy sources in todays world. Achieving energy without harming the environment has been the most important target of the countries in recent years. For this reason, it is necessary to make utmost use of natural energy sources such as wind, sun and water. Among these sources, wind energy is the most utilized. Because it was cheap and quickly return to investment it is carried out many studies in this area. However, the most important problem is the continuity when the wind energy is obtained. The first thing to do before a wind power plant is installed in a region is to calculate the wind potential of the area concerned. This process is long-term under normal conditions. Artificial Neural Networks (ANN) is one of the most frequently used methods for determining a wind power potential in a short time period. In this study, it is aimed to estimate the wind potential of a certain region within the boundaries of Osmaniye province. ANN was used to estimate the wind power potential. As a result of comparing the statistical values of the forecast values with the measured actual values, the performance of the method applied is indicated. The meteorology station at Osmaniye Korkut Ata University using data has been successfully estimated wind potential.
Application of ANN Modelling of Fire Door Resistance Altin, Mustafa; Tasdemir, Sakir
International Journal of Intelligent Systems and Applications in Engineering Vol 4, No 2 (2016)
Publisher : Advanced Technology and Science (ATScience)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.18201/ijisae.90445

Abstract

Fire doors are compulsorily used in every kind of building nowadays. The determination of fire doors’ resistance in which kind of buildings is also essential. This determination is needed to be watched through the experimental works done. Computer technologies and applications are commonly used in many fields in industry. In this study, by using the data obtained as a result of experiments made in order to determine the resistance of fire doors, artificial neural network (ANN) model was developed. With this model, it is aimed to evaluate the inner temperature of fire room having an important role in resistance of the fire door. In the developed system, temperature values belonging to thermocouples on the door (Top Left, Top  Right, Middle Left, Middle Right, Bottom Left, Bottom Right (oC) and time (minute) were taken as input parameters and in-room temperature (oC) was taken as output parameters. When the results obtained from ANN and experimental data are compared, it is determined that two groups of data were coherent. It is shown that ANN can be safely used in the determination of fire door resistance. 
Co-Authors ALTIN, Mustafa BALCI, Mehmet Guher, A.Burak SARACOGLU, Ridvan Yaniktepe, Bulent