This paper proposes improving the structure of the neural controller based on the identification model for nonlinear systems. The goal of this work is to employ the structure of the Modified Elman Neural Network (MENN) model into the NARMA-L2 structure instead of Multi-Layer Perceptron (MLP) model in order to construct a new hybrid neural structure that can be used as an identifier model and a nonlinear controller for the SISO linear or nonlinear systems. Two learning algorithms are used to adjust the parameters weight of the hybrid neural structure with its serial-parallel configuration; the first one is supervised learning algorithm based Back Propagation Algorithm (BPA) and the second one is an intelligent algorithm n

This studay was performd on 30 serum specimens of patients having type II diabetes with cardiac disease, and 40 normal specimens were investigated as control group.The activity rate of AAP in patients (125.31± 3.28)I.U/L and activity rate of AAP in normals (6.76±2.21) I.U/L, in addition purification of AAP from serum patients having type II diabetes with cardiac diaease by using dialysis bag and gel filtration (Sephadex G-50). The results of the study reveal that Alanine aminopeptidase (AAP) activity of type II diabetes with cardiac disease patients' serum show a high signifiacant increase (p<0.001) compare to normal subject .

          Five sites were chosen to the north of Babil Governorate in   order to identify the limnological features and the impact of the Hindiya Dam during 2019. Site2 was located near the dam to reflect the ecological features of this site, whereas other sites, S1 was located at the upstream of the dam as a control site. Moreover, the two other sites S3 and S4 were located down the dam. The results of  the  study  showed  a  close  correlation  between air and water temperature at all sites. Also there were significant differences in average of thirteen out of eighteen water parameters.Water temperature, total alkalinity, bicarbonate, DO, POS, TH and Mg⁺²  ions  decreased from 22.76˚C, 203.33 mg/L,

Background: Pharmacists are essential in treating MS. Pharmacists' involvement and patient consultation may improve patient adherence and satisfaction. Aim: To evaluate the influence of pharmacist-led interventions (PLI) on medication adherence and satisfaction in patients with multiple sclerosis receiving disease-modifying therapies (DMTs). Methods: This study was conducted on patients with relapsing-remitting multiple sclerosis who were receiving DMTs and attended a neurological consultant clinic in the medical city of Baghdad. It was a pre-post-intervention study. Each patient underwent two educational sessions: the first session took place at the beginning of the study, after completing the Arabic version of the treatment satisfaction q

Background: A role for vitamin D deficiency in Parkinson disease (PD) has recently been suggested.

Objective:: To estimate the state of vitamin D in PD with an age-matched healthy control.

Type of the study: A case control study.

Method: The study randomly comparison of plasma 25-hydroxyvitamin D (25[OH] D) concentrations of collected samples in a clinical neurology department ward / Baghdad teaching hospital / Medical City and Parkinson disease movement disorder clinic. Participants were registered into the study from October 2015 to October 2016. We was study   serum vitamin D level in 40 consecutive patients with

Researchers employ behavior based malware detection models that depend on API tracking and analyzing features to identify suspected PE applications. Those malware behavior models become more efficient than the signature based malware detection systems for detecting unknown malwares. This is because a simple polymorphic or metamorphic malware can defeat signature based detection systems easily. The growing number of computer malwares and the detection of malware have been the concern for security researchers for a large period of time. The use of logic formulae to model the malware behaviors is one of the most encouraging recent developments in malware research, which provides alternatives to classic virus detection methods. To address the l

In networking communication systems like vehicular ad hoc networks, the high vehicular mobility leads to rapid shifts in vehicle densities, incoherence in inter-vehicle communications, and challenges for routing algorithms. It is necessary that the routing algorithm avoids transmitting the pockets via segments where the network density is low and the scale of network disconnections is high as this could lead to packet loss, interruptions and increased communication overhead in route recovery. Hence, attention needs to be paid to both segment status and traffic. The aim of this paper is to present an intersection-based segment aware algorithm for geographic routing in vehicular ad hoc networks. This algorithm makes available the best route f

An aircraft's landing stage involves inherent hazards and problems associated with many factors, such as weather, runway conditions, pilot experiences, etc. The pilot is responsible for selecting the proper landing procedure based on information provided by the landing console operator (LCO). Given the likelihood of human decisions due to errors and biases, creating an intelligent system becomes important to predict accurate decisions. This paper proposes the fuzzy logic method, which intends to handle the uncertainty and ambiguity inherent in the landing phase, providing intelligent decision support to the pilot while reducing the workload of the LCO. The fuzzy system, built using the Mamdani approach in MATLAB software, considers critical