Support Vector Machines (SVMs) are supervised learning models used to examine data sets in order to classify or predict dependent variables. SVM is typically used for classification by determining the best hyperplane between two classes. However, working with huge datasets can lead to a number of problems, including time-consuming and inefficient solutions. This research updates the SVM by employing a stochastic gradient descent method. The new approach, the extended stochastic gradient descent SVM (ESGD-SVM), was tested on two simulation datasets. The proposed method was compared with other classification approaches such as logistic regression, naive model, K Nearest Neighbors and Random Forest. The results show that the ESGD-SVM has a

This study investigated the prevalence of quinolones resistance proteins encoding genes (qnr genes) and co-resistance for fluoroquinolones and β-lactams among clinical isolates of Klebsiella pneumoniae.  Out of 150 clinical samples, 50 isolates of K. pneumoniae were identified according to morphological and biochemical properties. These isolates were collected from different clinical samples, including 15 (30%) urine, 12 (24%) blood, 9 (18%) sputum, 9 (18%) wound, and 5 (10%) burn. The minimum inhibitory concentrations (MICs) assay revealed that 15 (30%) of isolates were resistant to ciprofloxacin (≥4µg/ml), 11 (22%) of isolates were resistant to levofloxacin (≥8 µg/ml), 21 (42%) of isolates were re

Introduction & Aim: Long-term diabetes mellitus (DM) is known to have a deleterious impact on bone health, resulting in change in bone mineral density, bone turnover, and bone quality, all of which increase the risk of fractures. The aim of. this study was to link immunological and pro-inflammatory cytokine (I.L-6, I.L-1, and TNF-alpha) markers in patients.with type 1 diabetes to Their connection to bones formation (sPINP) and bone resorption parameters (sCTX).   Materials & Methods: This study included 80 patients suffering from T1DM in the age range of 20-45 years. The patients were assayed for their biochemical (Vitamin D and HbA1c), Immunological (IL-6, IL-1 and TNF-alpha) parameters, as well as bone formation and resor

Background: Because of the disturbance in the pituitary gland, growth hormone (GH) secretion will be increased and, as a result, insulin-like growth factor 1 (IGF-1) secretion will be increase as well, leading to a chronic and rare disease called acromegaly disease. One of the most serious complications of acromycaly is diabetes. Insulin resistance, which causes diabetes, occurs in the body because of increased growth hormone secretion Objective: The aim of this work is to estimate some biochemical parameters. These parameters were not studied extensively in the literature such as BALP and LOX and the possibility of using LOX as a new biomarker for acromyalgic patients with diabetic. Patients and Methods: The study was performed on (25) mal

Background: Nutrition can affect the development and integrity of the oral cavity as well as the progression of oral diseases such as dental caries which was the most predominant and wide spread not life threatening human diseases especially in developing countries as in Iraq. This study was conducted to assess the occurrence, prevalence and severity of dental caries condition and their relations to nutritional status among intermediate schools females in Al-Najaf city in Iraq. Materials and methods: This study was conducted among intermediate schools females aged 13, 14 and15 years old and the total sample consisted of 754 students. The assessment of nutritional status was performed using body mass index (BMI) following Centers for Diseas

This research deals with unusual approach for analyzing the Simple Linear Regression via Linear Programming by Two - phase method, which is known in Operations Research: “O.R.”. The estimation here is found by solving optimization problem when adding artificial variables: Ri. Another method to analyze the Simple Linear Regression is introduced in this research, where the conditional Median of (y) was taken under consideration by minimizing the Sum of Absolute Residuals instead of finding the conditional Mean of (y) which depends on minimizing the Sum of Squared Residuals, that is called: “Median Regression”. Also, an Iterative Reweighted Least Squared based on the Absolute Residuals as weights is performed here as another method to