In this paper, first and second order sliding mode controllers are designed for a single link robotic arm actuated by two Pneumatic Artificial Muscles (PAMs). A new mathematical model for the arm has been developed based on the model of large scale pneumatic muscle actuator model. Uncertainty in parameters has been presented and tested for the two controllers. The simulation results of the second-order sliding mode controller proves to have a low tracking error and chattering effect as compared to the first order one. The verification has been done by using MATLAB and Simulink software.

In this paper, a self-tuning adaptive neural controller strategy for unknown nonlinear system is presented. The system considered is described by an unknown NARMA-L2 model and a feedforward neural network is used to learn the model with two stages. The first stage is learned off-line with two configuration serial-parallel model & parallel model to ensure that model output is equal to actual output of the system & to find the jacobain of the system. Which appears to be of critical importance parameter as it is used for the feedback controller and the second stage is learned on-line to modify the weights of the model in order to control the variable parameters that will occur to the system. A back propagation neural network is appl

A cross-sectional study was conducted on 80 type 2 diabetic patients aged 20-60 years in Baghdad and 20 non diabetic persons as controls. Laboratory assessment of glucose related parameters; Fasting blood sugar (FBS), Glycated hemoglobin (HbA1c), Insulin and Insulin resistance (IR), renal function test; Blood urea, serum creatinine, Calcium (Ca) and Phosphorus (P), Calcium regulating hormones; Parathyroid hormone (PTH), calcitonin and vitamin D, cytokines, Adiponectin and Tumor necrosis factor (TNF-α) and comparison these parameters between patients and controls. The results: a high significant (p˂0.01) increase in FBG level in the patients (211.34 ± 11.20 mg/dl) as compared with control (85.89 ± 3.07 mg/dl). A high significant (p˂0.01

Type 2 diabetes mellitus (T2DM) is a chronic disorder that is a serious health concern all over the globe, it is linked to Interleukin-10 (IL-10) single nucleotide polymorphisms (SNPs) at the promoter region. On the other hand, diabetes influences the cellular and humoral immunity predisposing the patient to a variety of opportunistic parasites one of them is Toxoplasma gondii (T. gondii), which may infect any nucleated cell, including pancreatic cells. The purpose of this research was to explore the association of IL-10 genetic polymorphisms with T2DM and latent toxoplasmosis among Iraqi patients with T2DM. Fifty-five and fifty-eight venous blood samples were taken from T2DM patients and age-matched non-diabetic person

Generalized multivariate transmuted Bessel distribution belongs to the family of probability distributions with a symmetric heavy tail. It is considered a mixed continuous probability distribution. It is the result of mixing the multivariate Gaussian mixture distribution with the generalized inverse normal distribution. On this basis, the paper will study a multiple compact regression model when the random error follows a generalized multivariate transmuted Bessel distribution. Assuming that the shape parameters are known, the parameters of the multiple compact regression model will be estimated using the maximum likelihood method and Bayesian approach depending on non-informative prior information. In addition, the Bayes factor was used

The main purpose of this work is to introduce some types of fuzzy convergence sequences of operators defined on a standard fuzzy normed space (SFN-spaces) and investigate some properties and relationships between these concepts. Firstly, the definition of weak fuzzy convergence sequence in terms of fuzzy bounded linear functional is given. Then the notions of weakly and strongly fuzzy convergence sequences of operators  are introduced and essential theorems related to these concepts are proved. In particular, if ( ) is a strongly fuzzy convergent sequence with a limit  where linear operator from complete standard fuzzy normed space  into a standard fuzzy normed space  then  belongs to the set of all fuzzy bounded linear operators

This paper presents a new design of a nonlinear multi-input multi-output PID neural controller of the active brake steering force and the active front steering angle for a 2-DOF vehicle model based on modified Elman recurrent neural. The goal of this work is to achieve the stability and to improve the vehicle dynamic’s performance through achieving the desired yaw rate and reducing the lateral velocity of the vehicle in a minimum time period for preventing the vehicle from slipping out the road curvature by using two active control actions: the front steering angle and the brake steering force. Bacterial forging optimization algorithm is used to adjust the parameters weights of the proposed controller. Simulation resul

        Artificial Neural networks (ANN) are powerful and effective tools in time-series applications. The first aim of this paper is to diagnose better and more efficient ANN models (Back Propagation, Radial Basis Function Neural networks (RBF), and Recurrent neural networks) in solving the linear and nonlinear time-series behavior. The second aim is dealing with finding accurate estimators as the convergence sometimes is stack in the local minima. It is one of the problems that can bias the test of the robustness of the ANN in time series forecasting. To determine the best or the optimal ANN models, forecast Skill (SS) employed to measure the efficiency of the performance of ANN models. The mean square error and

Combination therapy with a dipeptidyl peptidase–4 inhibitor and metformin or metformin+ glibenclamide results in substantial and additive glucose- lowering effects in Iraqis patients with type 2 diabetes mellitus . This study evaluated the glycemic control by using two groups of  combinations of drugs metformin + glibenclamide and metformin + sitagliptin in Baghdad teaching hospital / medical city. 68 T2DM patients and 34 normal healthy individuals as control group were enrolled in this study and categorized in to two treatment groups. The group 1 (34 patients ) received ( metformin 500 mg three times daily + glibenclamide 5 mg twice daily ) and the group 2 (34 patients) received (metformin 500 mg three times daily + sitaglip