Cutting forces are important factors for determining machine serviceability and product quality. Factors such as speed feed, depth of cut and tool noise radius affect on surface roughness and cutting forces in turning operation. The artificial neural network model was used to predict cutting forces with related to inputs including cutting speed (m/min), feed rate (mm/rev), depth of cut (mm) and work piece hardness (Map). The outputs of the ANN model are the machined cutting force parameters, the neural network showed that all (outputs) of all components of the processing force cutting force FT (N), feed force FA (N) and radial force FR (N) perfect accordance with the experimental data. Twenty-five samp

With its rapid spread, the coronavirus infection shocked the world and had a huge effect on billions of peoples' lives. The problem is to find a safe method to diagnose the infections with fewer casualties. It has been shown that X-Ray images are an important method for the identification, quantification, and monitoring of diseases. Deep learning algorithms can be utilized to help analyze potentially huge numbers of X-Ray examinations. This research conducted a retrospective multi-test analysis system to detect suspicious COVID-19 performance, and use of chest X-Ray features to assess the progress of the illness in each patient, resulting in a "corona score." where the results were satisfactory compared to the benchmarked techniques.  T

The present study is concerned with Biostratigraphy of the Early-Middle Miocene outcrops of Jeribe Formation in the Zurbatiyah area, Wasit Governorate, Eastern Iraq. Forty-two Samples collected from Shur Sharin and AL-Hashima outcrop sections. The fossil content is rich in large and small benthic foraminifera; Twenty-one species and genus are identified in this study, in addition to coral, gastropoda, pelecypoda, ostracoda, alge, echinoid and shell fragments. According to the presence of benthic foraminifera, two Biozone have been identified in the Jeribe: Austrotrillina asmariensis-Dendritina rangi Concurrent Zone and Borelis melo curdica range zone.The age of the Formation determined as Early-Middle Miocene depending on these Bioz

Addressed the problem of the research is marked (technical openness in the formation of post-modernism - Pop Art an Example) the nature of the technical expansion of the output artifacts postmodern, and the nature of the raw materials taken as components of its sensual. The search came in four sections: general framework for research and identified the research problem and the need for him. With an indication of the importance of his presence. From then select the search goal (revealed openness to hire technical material in the art of Pop Art), followed by the establishment of the three search limits (objectivity, the temporal and spatial) were then determine the terms related to the title. Then provide the theoretical framework and indi

Adverse drug reactions (ADR) are important information for verifying the view of the patient on a particular drug. Regular user comments and reviews have been considered during the data collection process to extract ADR mentions, when the user reported a side effect after taking a specific medication. In the literature, most researchers focused on machine learning techniques to detect ADR. These methods train the classification model using annotated medical review data. Yet, there are still many challenging issues that face ADR extraction, especially the accuracy of detection. The main aim of this study is to propose LSA with ANN classifiers for ADR detection. The findings show the effectiveness of utilizing LSA with ANN in extracting AD

Abstract

This research aim to overcome the problem of dimensionality by using the methods of non-linear regression, which reduces the root of the average square error (RMSE), and is called the method of projection pursuit regression (PPR), which is one of the methods for reducing dimensions that work to overcome the problem of dimensionality (curse of dimensionality), The (PPR) method is a statistical technique that deals with finding the most important projections in multi-dimensional data , and With each finding projection , the data is reduced by linear compounds overall the projection. The process repeated to produce good projections until the best projections are obtained. The main idea of the PPR is to model

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