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 through our ca

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

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

Background: Prevention against nosocomial infection is an important issue of health care field and considered a challenge of patients’ since it reflects its effect on their quality of life. This due to that it will lead in most cases to prolonged hospitalization and also more cost.Objective: To determine the prevalence of different types of nosocomial infection and to demonstrate the association of different risk factors (hospital environment, workers, visitors) with nosocomial infection.Patients: this study was carried out in eleven months at Ba’quba general Hospital; Iraq. A total of 81 clinical specimens (urine, pus from abscess , burn swab, nasal swab, ear swab and wound swab) taken from surgical patients,102 specimens from

Abstract Sweden is today one of the most active European countries in the regional and international environment despite the adoption of neutrality as a guiding principle in its foreign policy. For more than two centuries, the length of time for Swedish neutrality has made it a global standard, an agreed foreign policy at home and a political culture rooted in institutions and society. Swedish. Although discussions are still underway on Swedish security and foreign policies after the end of the Cold War, especially cooperation with NATO through the Partnership for Peaceprogram, EU accession and its impact on the principle of neutrality in foreign policy. Sweden, however, insists that it still maintains neutrality, but more adequately, in