Abstract. In this paper, a high order extended state observer (HOESO) based a sliding mode control (SMC) is proposed for a flexible joint robot (FJR) system in the presence of time varying external disturbance. A composite controller is integrated the merits of both HOESO and SMC to enhance the tracking performance of FJR system under the time varying and fast lumped disturbance. First, the HOESO estimator is constructed based on only one measured state to precisely estimate unknown system states and lumped disturbance with its high order derivatives in the FJR system. Second, the SMC scheme is designed based on such accurate estimations to govern the nominal FJR system by well compensating the estimation errors in the states and the lumped

A three-stage learning algorithm for deep multilayer perceptron (DMLP) with effective weight initialisation based on sparse auto-encoder is proposed in this paper, which aims to overcome difficulties in training deep neural networks with limited training data in high-dimensional feature space. At the first stage, unsupervised learning is adopted using sparse auto-encoder to obtain the initial weights of the feature extraction layers of the DMLP. At the second stage, error back-propagation is used to train the DMLP by fixing the weights obtained at the first stage for its feature extraction layers. At the third stage, all the weights of the DMLP obtained at the second stage are refined by error back-propagation. Network structures an

Due to the urgent need to develop technologies for continuous glucose monitoring in diabetes individuals, poten tial research has been applied by invoking the microwave tech niques. Therefore, this work presents a novel technique based on a single port microwave circuit, antenna structure, based on Metamaterial (MTM) transmission line defected patch for sensing the blood glucose level in noninvasive process. For that, the proposed antenna is invoked to measure the blood glu cose through the field leakages penetrated to the human blood through the skin. The proposed sensor is constructed from a closed loop connected to an interdigital capacitor to magnify the electric field fringing at the patch center. The proposed an tenna sensor i

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

Background: Klebsiella pneumoniae were considered as normal flora of skin, and intestine. It can cause damage to human lungs; the danger of this bacterium is related to exposure to the hospital surroundings. materials and methods: the detection of Klebsiella pneumoniae on morphological and biochemical tests and then assured with VITEK 2 system. Resistance to antibiotics was determined by Kirby-Baeur method. And genotyping of IMP-1 in isolates was done by PCR technique, then biofilm formation was identified by Micro titer plate method. Results: The present study included a collecting of 50 specimens from different clinical specimens, (blood 40%, urine 30%, sputum 20%, wound infection 10%); 10 isolates were identified as K

The estimation of the parameters of linear regression is based on the usual Least Square method, as this method is based on the estimation of several basic assumptions. Therefore, the accuracy of estimating the parameters of the model depends on the validity of these hypotheses. The most successful technique was the robust estimation method which is minimizing maximum likelihood estimator (MM-estimator) that proved its efficiency in this purpose. However, the use of the model becomes unrealistic and one of these assumptions is the uniformity of the variance and the normal distribution of the error. These assumptions are not achievable in the case of studying a specific problem that may include complex data of more than one model. To

The polycystic ovary syndrome is an endocrine condition. One of the leading causes of female infertility and the most common disorder among women. The work was being carried out on 100 Iraqi women (50 cases confirmed with PCOS and 50 controls). Between October 2019 and March 2020, blood samples were collected from the Advanced Institute of Infertility Diagnosis and Assisted Reproductive Technology at AL-Nahrain University and a private laboratory. ELISA was used to evaluate the biochemical parameters of preptin, FSH, insulin, LH, and CCL 18 in serum samples from the AFIAS-6 (AFIAS Automated Immunoassay System). The findings of the analysis indicate that, as opposed to the control group, values of prolactin (ng/ml), LH (mIU/ml), Preptin (

Glutathione S-transferases (GSTs) are enzymes that included, in a more range of detoxifying reactions by conjugation of glutathione, to electrophilic material. Polymorphisms n the genes that responsible of GSTs affect, the function of the GSTs. GSTs play an active role in protection of cell against oxidative stress mechanism. Polymorphisms of GSTP1 at codon 105 amino acids forms GSTP1 important site for bind of hydrophobic electrophiles and the substitution of Ile/Val affect substrate specially catalytic activity of the enzyme and may correlate with reach to different diseases in human like diabetes mellitus type2 disease. Correlation between these polymorphisms and changes in the parameters file of diabetic patients has also bee