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

There is a great risk of cardiovascular disease (CVD) and vascular thrombosis in patients with End-Stage Renal Disease (ESRD). These patients exhibit numerous abnormalities in coagulation, fibrinolytic, inhibitory protein abnormalities in multiple levels. The study aimed to assess hypercoagulable changes by measuring the levels of antithrombin, plasma fibrinogen and FXII activity in patients with ESRD, and to find their correlation with Hemoglobin (Hb) level, WBC count, reticulocyte percentage and platelet count. This study was conducted at Al-Hayat center, Al Karama Teaching Hospital on 50 ESRD patients aged < 60 years of both genders. In addition, 20 apparently healthy individuals were included as a control group. The mean Hb level, total

protein oxidation through oxidative stress, which represents the overall status of the protein in the cell/tissue. Due to their increased levels of AOPPs were reported during T2DM. The aim of this study was to assess AOPP level in T2DM subjects with foot ulcer (DFU) and explore its correlation with infection. Type 2 diabetic patients (n=108) and healthy subjects (n=25) were enrolled in this study. The T2DM group was subdivided to diabetic patients without complications (n=25) and eighty-three (83) of them have diabetic foot. They were sub- grouped into two groups according to presence Osteomyelitis and abscess, and in reliance on medical analysis of WBC count and CRP. Group of diabetic without superficial or deep ulcer and no osteomyelitis

MH Hamzah, AF Abbas, International Journal of Early Childhood Special Education, 2022

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 func

The importance of evaluation depends on many institutions, whether governmental or private, including media institutions, rely on the list to evaluate the weight of things and appreciation, as well as judging things, achievements, and everything related to the institution is concerned. Because through evaluation, institutions can recognize weaknesses and strengths. It is also an effective tool for management review, through which the institution can review everything related to planning and decision-making, leadership, incentives and other administrative matters.

Therefore, this study attempts to shed light on the evaluation process, its basics and its importance in general and in the Kurdish media institutions as a model in part

The need to create the optimal water quality management process has motivated researchers to pursue prediction modeling development. One of the widely important forecasting models is the sessional autoregressive integrated moving average (SARIMA) model. In the present study, a SARIMA model was developed in R software to fit a time series data of monthly fluoride content collected from six stations on Tigris River for the period from 2004 to 2014. The adequate SARIMA model that has the least Akaike's information criterion (AIC) and mean squared error (MSE) was found to be SARIMA (2,0,0) (0,1,1). The model parameters were identified and diagnosed to derive the forecasting equations at each selected location. The correlation coefficien

This research consists of two parts, the first part concern with analyzing the collected data of BOD and COD values in discharge waste water from Al-Dora refinery during 2010 to find the relationship between these two variables The results indicates that there is a high correlation between BOD and COD when using a natural logarithm model (0.86 ln(COD)) with correlation coefficient of 0.98. This relationship is useful in predicting the BOD value using the COD value. The second part includes analyzing collected data from the same site in order to find a relationsip between BOD and other parameters COD, Phenol(phe), Temperature(T), Oil, Sulphat(SO4),pH and Total dissolved solids( TDS) discharged from the refinery. The results indicated that th