In this research the results of applying Artificial Neural Networks with modified activation function to perform the online and offline identification of four Degrees of Freedom (4-DOF) Selective Compliance Assembly Robot Arm (SCARA) manipulator robot will be described. The proposed model of identification strategy consists of a feed-forward neural network with a modified activation function that operates in parallel with the SCARA robot model. Feed-Forward Neural Networks (FFNN) which have been trained online and offline have been used, without requiring any previous knowledge about the system to be identified. The activation function that is used in the hidden layer in FFNN is a modified version of the wavelet function. This approach ha

In this research, we dealt with the study of the Non-Homogeneous Poisson process, which is one of the most important statistical issues that have a role in scientific development as it is related to accidents that occur in reality, which are modeled according to Poisson’s operations, because the occurrence of this accident is related to time, whether with the change of time or its stability. In our research, this clarifies the Non-Homogeneous hemispheric process and the use of one of these models of processes, which is an exponentiated - Weibull model that contains three parameters (α, β, σ) as a function to estimate the time rate of occurrence of earthquakes in Erbil Governorate, as the governorate is adjacent to two countr

15 local isolates of Pseudomonas were obtained from 35 samples from several sources such as soil, water and some high-fat foods. The ability of isolates to produce lipase was measured by the size of the clarification zone formed around the colonies on the lipase production medium and by measuring the enzymatic activity and specific enzymatic activity, the isolate M3 was found to be the most efficient for production of the enzyme, This isolate was identified by microscopic, morphological, some biochemical tests and genetic diagnosis of 16S gene sequences by using the (PCR) technique, and then comparing the results obtained with the National Center for Biotechnology Inform

Background: Most primary Health Care Centers (PHCCs) in Iraq have a referral system records; however, this mechanism does not function well because of the lack of other requirements for an efficient referral system.

Objective: To assess the practice & opinion of doctors in PHCs toward the referral system, and to determine the doctors in PHC's commitment to referral system instructions and guidelines.

Subjects and methods: A cross-sectional study with analytic elements was conducted in nine health directorates in Iraq, from the 1st October 2018 – 30th June 2019.One PHC was selected randomly form each sector in every governorate, A questionnaire was used to collect the required information.

Social networking sites represent one of the modern communication technologies that have contributed to the expression of public opinion trends towards various events and crises of which security crisis is most important being characterized by its ability to influence the community life of the public. In order to recognize its role in shaping opinions of the educated class of the public that is characterized by a high level of knowledge, culture and having experience in dealing with the media. Its advantage is that they have an active audience by expressing their views on the situations, events, and news published on them as well as expressing their attitudes and sympathy with the events. So a number of questions are included in the ques

Diabetic retinopathy is an eye disease in diabetic patients due to damage to the small blood vessels in the retina due to high and low blood sugar levels. Accurate detection and classification of Diabetic Retinopathy is an important task in computer-aided diagnosis, especially when planning for diabetic retinopathy surgery. Therefore, this study aims to design an automated model based on deep learning, which helps ophthalmologists detect and classify diabetic retinopathy severity through fundus images. In this work, a deep convolutional neural network (CNN) with transfer learning and fine tunes has been proposed by using pre-trained networks known as Residual Network-50 (ResNet-50). The overall framework of the proposed