In this paper, a cognitive system based on a nonlinear neural controller and intelligent algorithm that will guide an autonomous mobile robot during continuous path-tracking and navigate over solid obstacles with avoidance was proposed. The goal of the proposed structure is to plan and track the reference path equation for the autonomous mobile robot in the mining environment to avoid the obstacles and reach to the target position by using intelligent optimization algorithms. Particle Swarm Optimization (PSO) and Artificial Bee Colony (ABC) Algorithms are used to finding the solutions of the mobile robot navigation problems in the mine by searching the optimal paths and finding the reference path equation of the optimal

KE Sharquie, AA Noaimi, WK Al-Janabi, The Iraqi Postgraduate Medical Journal, 2013 - Cited by 3

Background: Osteoporosis (OP) is a systemic disease characterized by low bone mass and micro architectural deterioration of bone tissue, resulting in an increased risk of fractures and has touched rampant proportions. Osteocalcin, one of the osteoblast-specific proteins, showed that its functions as a hormone improves glucose metabolism and reduces fat mass ratio. This study is aimed to estimate the osteocalcin and glucose level in blood serum of osteoporotic postmenopausal Women with and without Type 2 Diabetes.Materials and methods: 60 postmenopausal women with osteoporosis divided into two groups depending on with or without T2DM, 30 patients for each. Serum samples of 30 healthy postmenopausal women were collected as control group. Ost

Study the role of CoQ10 and IGFBP-1 in obese male patients with diabetic mellitus type 2. ELISA method was used to assay Serum CoQ10 and IGFBP-1. Blood was taken with drawn sample from 30 obese normal patients with age range (40-60) years, 30 diabetic patients with age range (40-60) years at duration of disease (1-5) years and 30 normal healthy patients. The mean difference between T2DM according to CoQ10 (12.5±1.1) was decreased than the mean of IFG (21.8±3.2) (P 0.002) and the mean difference between T2DM according to IGFBPs (0.65±0.06) was decreased than the mean of IFG (3.2±0.3) (P 0.000). While no significant difference between mean age of DM2 patients (55.5±1.06), and IFG (55.6±0.9) (p 0.90), no significant difference bet

Background: Cardiovascular disease (CVD) is an important complication of type 2 diabetes mellitus (T2DM). Oxidative stress plays a major role in the development of CVD. Saliva has a diagnostic properties aiding in the detection of systemic diseases. This study aimed to assess the association between salivary oxidative stress markers and the risk of vascular disease (VD) in T2DM patients. Materials and Methods: One hundred T2DM patients and fifty apparently healthy males were enrolled in this study. Saliva sample was collected for assessment of oxidative stress markers including: lipid peroxidation plasma thiobarbituric acid-reactive substances (TBARS), uric acid (UA) and total antioxidant capacity (TAC) levels. Arterial stiffness index (ASI

ز

Epstein-Barr Virus (EBV) infection is associated with broad spectrum of clinical manifestationsdepending on the immune status of the host, To analyze their possible role in the complication ofautoimmune hepatitis, we investigated (30) female patients with autoimmune hepatitis type-1 of(10-40)years and 25 healthy female of same ages(control groups). Both groups were carried outto measure the levels of EBV-CA IgM, IgG Ab, EBV-EA IgM, IgG Ab, and EBV-NA IgM, IgGAb using indirect immunoflourescent assay (IFAT).The prevalence of EBV-CA IgM, IgG Ab were(10%,20%) and EBV-EA IgM, IgG Ab were (10% and20%) respectively, while the prevalence ofEBV-NA IgG Ab was( 3.33%) and there are no prevalence of EBV-NA IgM Ab. There weresignificant differences (P

The Weibull distribution is considered one of the Type-I Generalized Extreme Value (GEV) distribution, and it plays a crucial role in modeling extreme events in various fields, such as hydrology, finance, and environmental sciences. Bayesian methods play a strong, decisive role in estimating the parameters of the GEV distribution due to their ability to incorporate prior knowledge and handle small sample sizes effectively. In this research, we compare several shrinkage Bayesian estimation methods based on the squared error and the linear exponential loss functions. They were adopted and compared by the Monte Carlo simulation method. The performance of these methods is assessed based on their accuracy and computational efficiency in estimati