The meniscus has a crucial function in human anatomy, and Magnetic Resonance Imaging (M.R.I.) plays an essential role in meniscus assessment. It is difficult to identify cartilage lesions using typical image processing approaches because the M.R.I. data is so diverse. An M.R.I. data sequence comprises numerous images, and the attributes area we are searching for may differ from each image in the series. Therefore, feature extraction gets more complicated, hence specifically, traditional image processing becomes very complex. In traditional image processing, a human tells a computer what should be there, but a deep learning (D.L.) algorithm extracts the features of what is already there automatically. The surface changes become valuable when

Background: The diagnosis of prostatic pathology may be of challenging , as some  difficult and suspected, atypical  cases may lack basal cell layer by routine H&E sections . Antibodies against 34BE12(HMW-CK) and p63 aid the diagnosis of such cases , to distinguish benign from  malignant prostatic lesions.

Objective: to identify basal cells in atypical prostatic lesions ,and distinguish benign from malignant prostatic lesions.

Type of the study:  A retro-spective  study.

Methods:  115cases of  paraffin embedded prostatic tissue blocks ,diagnosed as : 76 cases were benign prostatic hy

<span>Distributed denial-of-service (DDoS) attack is bluster to network security that purpose at exhausted the networks with malicious traffic. Although several techniques have been designed for DDoS attack detection, intrusion detection system (IDS) It has a great role in protecting the network system and has the ability to collect and analyze data from various network sources to discover any unauthorized access. The goal of IDS is to detect malicious traffic and defend the system against any fraudulent activity or illegal traffic. Therefore, IDS monitors outgoing and incoming network traffic. This paper contains a based intrusion detection system for DDoS attack, and has the ability to detect the attack intelligently, dynami

During COVID-19, wearing a mask was globally mandated in various workplaces, departments, and offices. New deep learning convolutional neural network (CNN) based classifications were proposed to increase the validation accuracy of face mask detection. This work introduces a face mask model that is able to recognize whether a person is wearing mask or not. The proposed model has two stages to detect and recognize the face mask; at the first stage, the Haar cascade detector is used to detect the face, while at the second stage, the proposed CNN model is used as a classification model that is built from scratch. The experiment was applied on masked faces (MAFA) dataset with images of 160x160 pixels size and RGB color. The model achieve

Abstract
        This research aims to identify the relationship and the impact of the behavior of organizational citizenship in the performance of employees, as practiced behaviors organizational citizenship substantial role in achieving the objectives of both the organization and its staff at the same time, so it affects a large extent on the characteristics and performance of individuals employees and thus influence the success of the organization as a whole, problem of the research has indicated that there is a clear failure in the study of the impact of the behavior of organizational citizenship in the performance of employees, was chosen

Background: C-reactive protein (CRP) is an acute phase protein that its plasma levels increase after trauma or surgery so it is used as an indicator for the level of inflammation after surgery. The objective of this study is to investigate pre- and post-operative levels of CRP in three types of oral surgical interventions (Apicoectomy, Impaction, and Impacted teeth exposure). Materials and Methods: A total number of (48) healthy individuals aged (20-60) years who needed oral surgical intervention for either (removal of impacted third molars, exposure of an impacted canine, or Apicoectomy). A 4ml venous blood was obtained from each patient at two occasions (pre-operatively at the day of operation and post-operatively after 48 hours), then ce

Urinary tract infection is a bacterial infection that often affects the bladder and thus the urinary system. E. coli is one of the leading uropathogenic bacteria that cause urinary tract infections. Uropathogenic E. coli is highly effective and successful in causing urinary tract infections through biofilm formation and urothelial cell invasion mechanisms. Other organisms that cause urinary tract infections include members of the Enterobacteriaceae family, streptococci and staphylococci species and perch. In addition, K.penumoniae is another important gram-negative bacterium that causes urinary tract infections. With the PCR technique, unseen bacterial species can be detected using standard clinical microbiology methods. In this study, the

Objectives: To assess the premenstrual syndrome among the working women in Baghdad City.
Methodology: A cross-sectional analytic study, using probability sampling cluster (multi-stage) sampling of
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designed and consisted of (4) parts, including demographic, reproductive, menstrual cycle characteristics, and
premeustmual syndrome symptoms. Content validity and reliability of the questionnaire were detemined by
conducting a pilot study. Descriptive and inferential statistical procedures were used to analyze the data.
Results: The results of the study revealed that the age of women ranged betwee