The economy is exceptionally reliant on agricultural productivity. Therefore, in domain of agriculture, plant infection discovery is a vital job because it gives promising advance towards the development of agricultural production. In this work, a framework for potato diseases classification based on feed foreword neural network is proposed. The objective of this work  is presenting a system that can detect and classify four kinds of potato tubers diseases; black dot, common scab, potato virus Y and early blight based on their images. The presented PDCNN framework comprises three levels: the pre-processing is first level, which is based on K-means clustering algorithm to detect the infected area from potato image. The s

One of the most important features of the Amazon Web Services (AWS) cloud is that the program can be run and accessed from any location. You can access and monitor the result of the program from any location, saving many images and allowing for faster computation. This work proposes a face detection classification model based on AWS cloud aiming to classify the faces into two classes: a non-permission class, and a permission class, by training the real data set collected from our cameras. The proposed Convolutional Neural Network (CNN) cloud-based system was used to share computational resources for Artificial Neural Networks (ANN) to reduce redundant computation. The test system uses Internet of Things (IoT) services th

Deep learning convolution neural network has been widely used to recognize or classify voice. Various techniques have been used together with convolution neural network to prepare voice data before the training process in developing the classification model. However, not all model can produce good classification accuracy as there are many types of voice or speech. Classification of Arabic alphabet pronunciation is a one of the types of voice and accurate pronunciation is required in the learning of the Qur’an reading. Thus, the technique to process the pronunciation and training of the processed data requires specific approach. To overcome this issue, a method based on padding and deep learning convolution neural network is proposed to

The support vector machine, also known as SVM, is a type of supervised learning model that can be used for classification or regression depending on the datasets. SVM is used to classify data points by determining the best hyperplane between two or more groups. Working with enormous datasets, on the other hand, might result in a variety of issues, including inefficient accuracy and time-consuming. SVM was updated in this research by applying some non-linear kernel transformations, which are: linear, polynomial, radial basis, and multi-layer kernels. The non-linear SVM classification model was illustrated and summarized in an algorithm using kernel tricks. The proposed method was examined using three simulation datasets with different sample

The topic area of that’s research dealing with values which adopted by Iraqi people since 1980, many changes and variables which make many situations and skills which the life is suitable in war and conflicts times. That’s values like traditional and ordering, traditionalism mean the conservation about values s and tradition which society adopted its. The Iraqi society suffering from many changes since 1980-2003, the consequently of that’s changes make Iraqi citizen more interested about luxury needs like clothes, while decreasing the interested about liberty of thought, beauty, show evidence of identity, and openness of mind. The processing of values changes associated with political behavior of Iraqi people which lead to weaken o

Background: Many structural or functional abnormalities can impair the production of thyroid hormones and cause hypothyroidism.Objectives: to identify the main etiological causes of hypothyroidism among patients visiting Specialized Center for Diabetes and Endocrinology.Methods: This study was conducted in the Specialized Center for Diabetes and Endocrinology on 217 patients with proved hypothyroidism, from 2006 to 2008. Every patient was tested with thyroid function tests, Ultrasound examination, thyroid autoantibodies, fine needle aspiration, radiology of skull, isotopes scan, also checking adrenal and gonadal function. Results: Out of these 217 patients 120 patients have thyroiditis 33 patients had been undergone thyroidectomy. 39 pat

Heat treatment by solid solution method in the ?+? phase region was used at 970°C for Ti-5Al-2.5Fe alloy. The specimens cooled under different cooling media [water quenched (WQ), air cooled (AC) and furnace cooled (FC)], and subsequently aged at 550°C for 4 hours. Five specimens from each treatment were immersed in simulated body fluid SBF for a period of time (3 months). The dependence of corrosion rate on compositional variation in the phases resulted from various type of cooling rates are discussed based on immersion tests. The EDXA results show the precipitation of phosphate and calcium compounds on the alloy after 3 months of immersion in blood plasma solution forming a bone-like apatite, which enhanced the alloy biocompatibility ma