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

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

Wildfire risk has globally increased during the past few years due to several factors. An efficient and fast response to wildfires is extremely important to reduce the damaging effect on humans and wildlife. This work introduces a methodology for designing an efficient machine learning system to detect wildfires using satellite imagery. A convolutional neural network (CNN) model is optimized to reduce the required computational resources. Due to the limitations of images containing fire and seasonal variations, an image augmentation process is used to develop adequate training samples for the change in the forest’s visual features and the seasonal wind direction at the study area during the fire season. The selected CNN model (Mob

The research aims to clarify the importance of adoption of International Accounting  Standard No. (12) "Income Taxes" as a tool for the measurement and disclosure of income taxes in the financial statements، and how to deal with the differences that arise as a result of difference in net profit accounting for net tax profit ،The problem of the research focused on the disparity between the income tax estimate in Iraq in accordance with the accounting standards and financial reporting and assessment of income tax in accordance with the tax laws and legislation, this discrepancy has led to the emergence of differences between accounting profit and tax profit (temporary differences and permanent differences) and these differences of w

We refer in this research into linguistic binaries, try rounding of simiaei news analysis. It is known that there are branches of Linguistics called social Linguistics, divided into communicative Linguistics and media. Perhaps the best justification for the inclusion of a new curriculum in media studies is a semiotic analysis of the news. I›ve turned the speech, language and communication studies in relation to different disciplines, many research projects, and returned only old curriculum, speed shift in thought, proportional to the revolution in information and communication technology, for reality imposed on the entire world, researchers are the first affected by this enormous humanitarian Almanza. Alsimiaaeon still shy away from an