Mahmut Sinecen

Using and Analyzing of Distance Education Model for Adnan Menderes University 5(I) Courses

The different models have led to occurring on education because of transferring, using, accessing, and sharing of knowledge. Today, distance education model is the most important and effective use in these models. The lack of teaching staff and the limited field of education areas are the most important factor in the use of distance education model. Therefore, required courses (Ataturk’s Principles and History of Turkish Language, Foreign Language) which are Law 5(I) of 2547 under Article have been transferred to the distance education system instead of formal education in the Adnan Menderes University. In this article, requirements, using reasons and analyzing of the results of this model are given.

Artificial Neural Network System for Prediction of Dimensional Properties of Cloth in Garment Manufacturing: Case Study on a T-Shirt

The purpose of the present study was to estimate dimensional measure properties of T-shirts made up of single jersey and interlock fabrics through artificial neural networks (ANN). To that end, 72 different types of T-shirts were manufactured under 2 different fabric groups, each was consisting of 2 groups: one with elastane and the other without. Each of these groups were manufactured from six different materials in three different densities through two different knitting techniques of single jersey and interlock. For estimation of dimensional changes in these T-shirts, models including feed-forward, back-propagated, the momentum learning rule and sigmoid transfer function were utilized. As a result of the present study, the ANN system was found to be successful in estimation of pattern measures of garments. The prediction of dimensional properties produced by the neural network model proved to be highly reliable (R2> 0.99).

Automatic control system for aquarium: Aduarium

Fish feeding is a relaxing hobby, as well as being used for psychological treatment and the decorative nature of aquariums, it also holds an important place in daily life, at home and in offices of people. In this study, the data obtained from the automated aquarium system: aduarium and the tests made with this system are shared.

Performance analysis of e-Learning server

In this paper, a performance test has been performed on our ADUZEM e-Learning system to investigate performance impact of users on the systems server and network equipment, and the results are presented to readers in graphical form. The paper and results will help administrators to have a clear insight of how to setup an e-Learning system and how much provisioning is required for an e-Learning system to securely response to request of clients.

Neural network classification of aggregates by means of line laser based 3D acquisition

This study focuses on the development of a new module for a more accurate determination of geometrical properties of aggregates. A laser-based imaging system has been developed for the shape characterization of aggregates by using various digital image analysis techniques. By using this system it is possible to create a three-dimensional (3D) image form of aggregate particles. The system has been optimized to minimize the possible errors during image capturing and processing. The aggregates were classified according to their shape properties as; round, flat, elongated, angular, sphere, and irregular during test procedures. Geometrical properties of each aggregate group were analysed in 3D spatial domain. 3D shape reconstruction and characterization of the aggregates were realized by using digital image processing and analysis techniques based on the laser imaging system. MatLab® Image Processing Toolbox and Neural Network Toolbox were used to extract typical features of the aggregates and classify them according to their geometrical properties. Among the classifier types, multi-layered perceptron that has two hidden layers revealed the best performance (95.83%). The selection and production of appropriate shaped aggregate for various construction purposes seems to be possible by this developed method.

Diagnosis of Prostat Cancer using Artificial Neural Networks

Prostat cancer is a disease which is the most common and which is also the second deadly in men. When prostat cancer can be diagnosed early, medical surgery operation can be performed and the disease can be treated.