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Öğe Comparison of Artificial Neural Network and Extreme Learning Machine in Benign Liver Lesions Classification(IEEE, 2015) Akin, Mustafa; Ceylan, MuratIn this study, the classification of the most common benign lesions, cysts and hemangiomas in liver was achieved using magnetic resonance (MR) images. T1 venous phase of 68 liver MR images were used for the classification, including 28 cysts and 40 hemangiomas MR images. Liver segmentation was done by expert radiologists using MR images. Then automatic windowing was applied to images to reduce the negative impact on the process of image-free areas of tissue information. The obtained images were normalized and thresholded using histogram equalization. The average, standard deviation and distortion values of the image feature matrix obtained by applying wavelet transform (WT) and complex valued wavelet transform (CVWT) onto the thresholded images were calculated. Artificial neural network (ANN), extreme learning machine (ELM), cyst and hemangiomas classification were achieved using these features as inputs. As a result of this study, 50% accuracy at the data applied CVWT, 70,5% accuracy at the data applied WT were obtained in ANN. Average processing time is 4.61 seconds. When examined the ELM application results, it can be seen that there are 55, 8% accuracy at the data applied CVWT and 62, 5% accuracy at the data applied WT. Also, the average processing time is 0,016 seconds this time. Although the classification results seem low, classification accuracy rates will increase with the development studies considering advantage of ELM processing time.Öğe MEASURING THE IMPACT OF AGRICULTURAL RESEARCH: THE CASE OF NEW WHEAT VARIETIES IN TURKEY(CAMBRIDGE UNIV PRESS, 2015) Mazid, Ahmed; Keser, Mesut; Amegbeto, Koffi N.; Morgounov, Alexey; Bagci, Ahmet; Peker, Kenan; Akin, MustafaThis paper summarizes a study initiated by the Turkish General Directorate of Agricultural Research and ICARDA/CIMMYT Wheat Improvement Program on the adoption of five new winter and spring wheat varieties developed and released by the Turkish national breeding program and through international collaboration in the past 10 years. The study results are based on a survey of 781 households selected randomly in the Adana, Ankara, Diyarbakir, Edirne, and Konya provinces of Turkey. The five new wheat varieties are compared to old improved varieties released prior to 1995 that are also still grown by farmers. Technical and biological indicators of impacts including crop productivity are measured to determine the impact of these varieties. Yield stability is assessed by comparing average yields in normal, good and dry years and by comparing the coefficients of variation of yields by variety. Profitability is measured by the gross margin generated per unit of land. Household income from wheat and for all economic activities are estimated and compared between adopters and non-adopters. Adopters of the new varieties have higher per-capita income than non-adopters as compared to the same group using old varieties. However, the overall impact of the improved varieties is generally low, mainly due to their low adoption levels. Farmers' knowledge and perception of certain variety characteristics and unavailability of adequate and timely seed are the main reasons. Increasing adoption has the potential to improve household income and this requires revising wheat impact pathway to achieve the expected impact.