In this paper, several combination algorithms between Partial Update LMS (PU LMS) methods and previously proposed algorithm (New Variable Length LMS (NVLLMS)) have been developed. Then, the new sets of proposed algorithms were applied to an Acoustic Echo Cancellation system (AEC) in order to decrease the filter coefficients, decrease the convergence time, and enhance its performance in terms of Mean Square Error (MSE) and Echo Return Loss Enhancement (ERLE). These proposed algorithms will use the Echo Return Loss Enhancement (ERLE) to control the operation of filter's coefficient length variation. In addition, the time-varying step size is used.The total number of coefficients required was reduced by about 18% , 10% , 6%

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

      In this article, a numerical study of compressible and weak compressible Newtonian flows is achieved for a time marching, Galerkin algorithm. A comparison between two numerical techniques for such flows, namely the artificial compressibility method (AC–method) and the fully artificial compressibility method (FAC–method) is performed. In the first artificial compressibility parameter (  is added to the continuity equation, while this parameter is added to both continuity and momentum equations in the second technique. This strategy is implemented to treat the governing equations of Newtonian flow in cylindrical coordinates (axisymmetric). Particularly, this study concerns with the effect of the artificial compressibility p

In order to facilitate the accounting procedure and accelerate its achievement, commercial banks used to follow reversing entry style in agent’s account opened with them, to settle its debits caused by non-payment of the discounted commercial paper value. The question was raised about: the legal importance to such method for settling the discounting bank debits, particularly when the bank account of the discounted side was debtor and not creditor, as the case of discounted party under bankruptcy.

It is noted that the Jordanian trade legislations is totally silent in this regard, as well as the  other trade legislations which are frankly considering the reversing entry as an organizer for deleting the trust entry which was

A substantial matter to confidential messages' interchange through the internet is transmission of information safely. For example, digital products' consumers and producers are keen for knowing those products are genuine and must be distinguished from worthless products. Encryption's science can be defined as the technique to embed the data in an images file, audio or videos in a style which should be met the safety requirements. Steganography is a portion of data concealment science that aiming to be reached a coveted security scale in the interchange of private not clear commercial and military data. This research offers a novel technique for steganography based on hiding data inside the clusters that resulted from fuzzy clustering. T

This paper develops a fuzzy multi-objective model for solving aggregate production planning problems that contain multiple products and multiple periods in uncertain environments. We seek to minimize total production cost and total labor cost. We adopted a new method that utilizes a Zimmermans approach to determine the tolerance and aspiration levels. The actual performance of an industrial company was used to prove the feasibility of the proposed model. The proposed model shows that the method is useful, generalizable, and can be applied to APP problems with other parameters.

Background: Neonatal intensive care unit infants frequently experience acute kidney damage. Estimates of the prevalence of acute kidney vary depending on the definitions used. In Iraq, studies addressing the prevalence and risk factors of acute kidney injury in this age group are scarce, none of which has implicated the KDIGO diagnostic and staging criteria.

Objectives: To describe the prevalence, demographics, risk factors, etiology, and staging of acute kidney injury using KDIGO criteria in the Neonatal intensive care unit and correlate these findings with patient outcomes.

Methods: A retrospective study was conducted in the Neonatal Intensive Care Unit/ CWTH/ Medical Cit

Background: Changes of coagulation profile have been described in patients with B-Thalassemia major. Prolongation of prothrombin time and partial thromboplastin time and reduced levels of coagulation factors and natural anticoagulants have been variously described though the mechanisms involved in the thrombotic tendency seen in some Thalassemia patients have not been fully clarified.
Objectives: To investigate changes in the coagulation profile in patients with B-Thalassemia according to the available hemostatic parameters in Thalassemia patients in Al-Karama Teaching Hospital in Wasit governorate.
Methods: Hemostatic variables were studied in pre-transfusion blood samples from 50 transfusion-dependent children with Beta Thalassem

Imitation learning is an effective method for training an autonomous agent to accomplish a task by imitating expert behaviors in their demonstrations. However, traditional imitation learning methods require a large number of expert demonstrations in order to learn a complex behavior. Such a disadvantage has limited the potential of imitation learning in complex tasks where the expert demonstrations are not sufficient. In order to address the problem, we propose a Generative Adversarial Network-based model which is designed to learn optimal policies using only a single demonstration. The proposed model is evaluated on two simulated tasks in comparison with other methods. The results show that our proposed model is capable of completing co