Aim: This study aims to determine both the level  of knowledge, attitude, and practice  in clinical breast examination in women and the relationship between knowledge and practice.Data collection was performed within a three-month period starting from February 2019 on.  Subjects and Method: A cross-sectional analytical study included 657 non-randomly selected women visiting primary health care centers in Baghdad city with an average of age between (20-59) years old.  Results: Only 51.8% ever heard of clinical breast examination. The mean knowledge score for clinical breast examination was (51.2±44). Only 5.5% of women performed regular clinical breast examinations. Participants who adequately practice clinical breast examinatio

Realizing robust interconnectivity in a rapidly changing network topology is a challenging issue. This problem is escalating with the existence of constrained devices in a vehicular environment. Several standards have been developed to support reliable communication between vehicular nodes as the IEEE 1609 WAVE stack. Mitigating the impact of security/mobility protocols on limited capability nodes is a crucial aspect. This paper examines the burden of maintaining authenticity service that associated with each handover process in a vehicular network. Accordingly, a network virtualization-based infrastructure is proposed which tackles the overhead of IEEE 1906 WAVE standard on constrained devices existed in vehicular network. The virtualized

     Systemic Lupus Erythematosus (SLE) is a multifactorial chronic systemic autoimmune disease. It is characterized by a lack of immune tolerance to autoantigens such as nuclear antigens. The aim of the study is to assess the interferon-alpha (IFN-α) serum level in Iraqi patients with SLE and determine its potential relation to different clinical and laboratory parameters and disease activity. 100 SLE patients were all females and with a mean of age 31.3 ± 10 years (16-63years) and disease duration of 5.8 ± 3.7years (1 month to 15 years). The average of SLEDAI score ranged from 2 to 22 with a mean of (8.53 ±3.42). Proteinuria, ESR, creatinine and AST were significantly higher (65% vs. 10% and 0.62±0.11 vs. 0.70±0.14 mg/dl resp

Feature selection (FS) constitutes a series of processes used to decide which relevant features/attributes to include and which irrelevant features to exclude for predictive modeling. It is a crucial task that aids machine learning classifiers in reducing error rates, computation time, overfitting, and improving classification accuracy. It has demonstrated its efficacy in myriads of domains, ranging from its use for text classification (TC), text mining, and image recognition. While there are many traditional FS methods, recent research efforts have been devoted to applying metaheuristic algorithms as FS techniques for the TC task. However, there are few literature reviews concerning TC. Therefore, a comprehensive overview was systematicall