In light of the development in computer science and modern technologies, the impersonation crime rate has increased. Consequently, face recognition technology and biometric systems have been employed for security purposes in a variety of applications including human-computer interaction, surveillance systems, etc. Building an advanced sophisticated model to tackle impersonation-related crimes is essential. This study proposes classification Machine Learning (ML) and Deep Learning (DL) models, utilizing Viola-Jones, Linear Discriminant Analysis (LDA), Mutual Information (MI), and Analysis of Variance (ANOVA) techniques. The two proposed facial classification systems are J48 with LDA feature extraction method as input, and a one-dimen

AshShinnafiyah and AsSamawa cities suffer from significant increase in salinity of Euphrates River water compared with their counterpart's north AshShinnafiyah city which is reflected adversely on the quality of water within the study area. The study aims to find possible solutions to avoid the deterioration of Euphrates River northern AshShinnafiyah city until AsSamawa city that were
presented by total dissolved solid TDS. Twelve main hydrological and fifteen salinity measurement stations were selected to cover 117 km of the river reach within the study area during July-2011. Additional twenty three hydrological and salinity stations were adopted during March-2012, winter season to the river within the study area. After conducting t

Cyber-attacks keep growing. Because of that, we need stronger ways to protect pictures. This paper talks about DGEN, a Dynamic Generative Encryption Network. It mixes Generative Adversarial Networks with a key system that can change with context. The method may potentially mean it can adjust itself when new threats appear, instead of a fixed lock like AES. It tries to block brute‑force, statistical tricks, or quantum attacks. The design adds randomness, uses learning, and makes keys that depend on each image. That should give very good security, some flexibility, and keep compute cost low. Tests still ran on several public image sets. Results show DGEN beats AES, chaos tricks, and other GAN ideas. Entropy reached 7.99 bits per pix

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

Developing an efficient algorithm for automated Magnetic Resonance Imaging (MRI) segmentation to characterize tumor abnormalities in an accurate and reproducible manner is ever demanding. This paper presents an overview of the recent development and challenges of the energy minimizing active contour segmentation model called snake for the MRI. This model is successfully used in contour detection for object recognition, computer vision and graphics as well as biomedical image processing including X-ray, MRI and Ultrasound images. Snakes being deformable well-defined curves in the image domain can move under the influence of internal forces and external forces are subsequently derived from the image data. We underscore a critical appraisal

  The research aims to measure  the efficiency of health services Quality  in the province of Karbala, using the Data Envelopment analysis Models in ( 2006). According to these models the degree of efficiency ranging between zero and unity. We estimate Scale efficiency  for two types of orientation direction, which are input and output oriented direction.

  The results showed, according Input-oriented efficiency that the levels of Scale efficiency on average is ( 0.975), in the province of Karbala. While the index of Output-oriented efficiency on average is (o.946).

Atrial fibrillation is associates with elevated risk of stroke. The simplest stroke risk assessment schemes are CHADS₂ and CHA₂DS₂-VASc score. Aspirin and oral anticoagulants are recommended for stroke prevention in such patients.

The aim of this study was to  assess status of CHADS₂ and CHA₂DS₂-VASc scores in Iraqi atrial fibrillation patients and to report current status of stroke prevention in these patients with either warfarin or aspirin in relation to these scores.

This prospective cross-sectional study was carried out at Tikrit, Samarra, Sharqat, Baquba, and AL-Numaan hospitals from July 2017 to October 2017. CHADS₂

Studied the environment and fish life Qattan in the Euphrates River in central Iraq for the period from September 2002 until 2003 recorded the lowest temperature of the water during the month of January during the month of August ranged salinity ranges between 068

The research aims to test the correlation relationships between wise leadership, and the business model, and to demonstrate its influence (wise leadership) on the business model. Therefore, two main hypotheses were put forward. The research was applied to a sample consisting of (87) managers and deputy managers, some of them are members on the board of directors of the researched company. The questionnaire was adopted as a basic tool for collecting data, in addition to personal interviews. A number of statistical methods were used to analyze the data and obtain results. The researcher showed a set of results, including: There is a significant correlation between wise leadership and business model. There is an influence of wise leadership on