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

When soft tissue planning is important, usually, the Magnetic Resonance Imaging (MRI) is a medical imaging technique of selection. In this work, we show a modern method for automated diagnosis depending on a magnetic resonance images classification of the MRI. The presented technique has two main stages; features extraction and classification. We obtained the features corresponding to MRI images implementing Discrete Wavelet Transformation (DWT), inverse and forward, and textural properties, like rotation invariant texture features based on Gabor filtering, and evaluate the meaning of every

This work implements an Electroencephalogram (EEG) signal classifier. The implemented method uses Orthogonal Polynomials (OP) to convert the EEG signal samples to moments. A Sparse Filter (SF) reduces the number of converted moments to increase the classification accuracy. A Support Vector Machine (SVM) is used to classify the reduced moments between two classes. The proposed method’s performance is tested and compared with two methods by using two datasets. The datasets are divided into 80% for training and 20% for testing, with 5 -fold used for cross-validation. The results show that this method overcomes the accuracy of other methods. The proposed method’s best accuracy is 95.6% and 99.5%, respectively. Finally, from the results, it

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 precise classification of DNA sequences is pivotal in genomics, holding significant implications for personalized medicine. The stakes are particularly high when classifying key genetic markers such as BRAC, related to breast cancer susceptibility; BRAF, associated with various malignancies; and KRAS, a recognized oncogene. Conventional machine learning techniques often necessitate intricate feature engineering and may not capture the full spectrum of sequence dependencies. To ameliorate these limitations, this study employs an adapted UNet architecture, originally designed for biomedical image segmentation, to classify DNA sequences.The attention mechanism was also tested LONG WITH u-Net architecture to precisely classify DNA sequences

Acidizing is one of the most used stimulation techniques in the petroleum industry. Several reports have been issued on the difficulties encountered during the stimulation operation of the Ahdeb oil field, particularly in the development of the Mishrif reservoir, including the following: (1) high injection pressures make it difficult to inject acid into the reservoir formation, and (2) only a few acid jobs have been effective in Ahdeb oil wells, while the bulk of the others has been unsuccessful. The significant failure rate of oil well stimulation in this deposit necessitates more investigations. Thus, we carried out this experimental study to systematically investigate the influence of acid treatment on the geomechanical properties of Mi4

     تعد الملابس وسيلة هامة لكل مايقوم به الانسان في حياته العامة ، فهي الانطباع والكلمة الخارجية عن ذاته الداخلية فهي تعكس فكرة الفرد عن ذاته وعن شخصيته , كما تعد وسيلة تعبير جمالية وفنية , فهي تساعد على اخفاء عيوب الجسد وابراز محاسنه . ويتوقف اختيار الفرد لملابسه على مجموعة  عوامل منها احتياجه , قدراته المالية , سنه , مركزه الاجتماعي , طبيعة عمله ,الظروف الجوية التي يعيش فيها وعلى مايُؤمن به من قيم و

Abstract:

                  This research seeks to test the influence of intellectual capital as an explanatory variable and its components (human capital, structural capital, relational capital) and sustainable competitive performance as a responsive variable and its components (reducing service delivery cycle time, rapid response to market demand, increasing customer satisfaction, providing better Quality of service, increasing market share)” through a field study, and here the research problem was diagnosed in an attempt to answer the following question: Is there awareness among the senior management within the private colle