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Öğe The design and implementation of a PIC-based ultrasonic distance measurement system with PC user interface [PC kullanici arayüzlü PIC-tabanli ultrasonik mesafe ölçüm sisteminin tasarimi ve gerçekleştirilmesi](2005) Yaldiz E.; Yilmaz N.; Sa?lam H.This paper presents a distance measuring system implemented by using PIC-based ultrasonic transmitter-receiver. Microcontroller PIC 16F877 is used to calculate the propagation time of sound and to direct ultrasonic transducers to the desired angles. The resultant data is transferred from microcontroller into PC via serial port. A Delphi-based user interface fulfills data acquisition and visualization. Thus, the system becomes user-friendly. © 2005 IEEE.Öğe General aimed web based mobile robot: Sunar [Genel amaçli web tabanli mobi?l robot: Sunar](2006) Yilmaz N.; Sa?iro?lu Ş.; Bayrak M.In this paper, a web based mobile robot platform was developed for scientific and engineering education purposes and its achievement was presented on various applications. The platform based on wireless communication was especially designed for monitoring, controlling and reprogramming tasks. A real-time support library based on robot platform was also developed to support various real-time applications. Testing mobile robot platform for semi-autonomous and autonomous applications showed that the designed platform can be used for multi-purpose real-time applications and especially could support web-based applications in engineering education.Öğe A mineral classification system with multiple artificial neural network using k-fold cross validation(2011) Baykan N.A.; Yilmaz N.The aim of this study is to show the artificial neural network (ANN) on classification of mineral based on color values of pixels. Twenty two images were taken from the thin sections using a digital camera mounted on the microscope and transmitted to a computer. Images, under both plane-polarized and cross-polarized light, contain maximum intensity. To select training and test data, 5-fold-cross validation method was involved and multi layer perceptron neural network (MLPNN) with one hidden layer was employed for classification. The classification of mineral using ANN proved %93.86 accuracy for 400 data. In second study, for each of the 5 different mineral considered, 5 different network models were implemented. Size of data set was same with previous data. Each network model was differed from each other. Also 5-fold-cross validation method was involved to select data and MLPNN with one hidden layer was used. The classification accuracy of mineral using different ANN is %90.67; %96.16; %93.91; %92; %97.62 for quartz, muscovite, biotite, chlorite and opaque respectively. © Association for Scientific Research.Öğe Modelling of SO2 concentrations using artificial neural networks(2006) Dursun S.; Guclu D.; Celebi F.; Yilmaz N.Modelling of air pollution parameters, according to the meteorological data is a necessary for preventing the repetition of same problems. During recent years, neural network-based models have been shown to be powerful tools in the simulation of variations in air quality and provide better alternative to statistical models because of their computational efficiency and generalization ability. In this study, prediction of future daily SO2 concentrations in Konya (Turkey) using MLP (Multilayer Perceptron) artificial neural networks trained with the back-propagation algorithm, which uses gradient descent optimization for error reduction was employed by taking into account meteorological parameters and SO2 (sulphur dioxide) concentrations obtained for two years period from 2003 to 2004. The appropriate architecture of the neural network models was determined through several steps of trainings and testing of the models. The results illustrated that artificial neural networks offer a valuable method for air pollution management. © 2006. International Scientific Conference SGEM.Öğe A new hybrid feature selection method based on association rules and pca for detection of breast cancer(2013) Inan O.; Uzer M.S.; Yilmaz N.In this study, a new hybrid feature selection method named as AP has been formed to detect breast cancer, using association rules (Apriori algorithm) and Principal Component Analysis (PCA) together with artificial neural network classifier. Thanks to this hybrid system, both the decrease in the size of data and the successful and fast training of classifiers have been achieved. In order to detect the accuracy of the suggested system, Wisconsin breast cancer data have been used. 10-fold cross-validation has been used on the classification phase. The average classification accuracy of the developed AP + NN system is 98.29%. Among the studies performed through cross-validation method for breast cancer, our study result appears to be very promising. As the results suggest, this system, which is performed through size reduction, is a feasible system for faster and more accurate diagnosis of diseases. © 2013 ICIC International.Öğe A real-ti?me tracking application of different coloured objects with a vision based mobile robot [Görme tabanli mobi?l robot i?le farkli renklerde nesneleri?n gerçek zamanli taki?bi?](2010) Uzer M.S.; Yilmaz N.; Bayrak M.In this study, a real-time tracking application of different colored objects with a vision based mobile robot has been implemented. The developed robot has some features that can be used in the fields of exploration, security and observation. This vision based mobile robot is autonomously operated by using image processing and robot vision techniques. The response time of the robot that can track different color (red, blue and green) objects is between 96 ms and 106 ms as suitable for real time processing. By two different developed algorithms, for blue and red color objects a %100, and for green objects a %60 recognition success is seen with experiments. In colorful object tracking experiments in linear and circular orbitals, for an average value of 5.7 cm/s speed, a 4.5 cm deviation as maximum is confirmed.Öğe A real-time object tracking by using fuzzy controller for vision-based mobile robot(2011) Uzer M.S.; Yilmaz N.In this study, a real-time object tracking application based on robot vision is presented. The developed robot has features that enable it to be utilized also in expedition, security, object-based indoor navigation and observational activities. Enabling the autonomous motion of this vision-based mobile robot, by just using robot vision methods and fuzzy logic control was the aim of the study. A vision-based object tracking algorithm, conventional PD control algorithm and fuzzy control are used and compared in study. The robot system focused on fuzzy control and image based control which is useful as a test bench tool for graduate and undergraduate students who are interested in robot control and image processing. © 2011 Academic Journals.Öğe Tribonacci and tribonacci-lucas numbers via the determinants of special matrices(Hikari Ltd., 2014) Yilmaz N.; Taskara N.In this paper, by using determinants of special matrices, it has been mainly obtained Tribonacci and Tribonacci-Lucas numbers. © 2014 Nazmiye Yilmaz and Necati Taskara.
