In this paper a dynamic behavior and control of  a jacketed continuous stirred tank reactor (CSTR)  is developed using different control strategies, conventional feedback control (PI and PID), and neural network (NARMA-L2, and NN Predictive) control. The dynamic model for CSTR process is described by a first order lag system with dead time.

The optimum tuning of control parameters are found by two different methods; Frequency Analysis Curve method (Bode diagram) and Process Reaction Curve using the mean of Square Error (MSE) method. It is found that the Process Reaction Curve method is better than the Frequency Analysis Curve method and PID feedback controller is better than PI feedback controller.

The results s

The research focuses on determination of best location of high elevated tank using the required head of pump as a measure for this purpose. Five types of network were used to find the effect of the variation in the discharge and the node elevation on the best location. The most weakness point was determined for each network. Preliminary tank locations were chosen for test along the primary pipe with same interval distance. For each location, the water elevation in tank and pump head was calculated at each hour depending on the pump head that required to achieve the minimum pressure at the most weakness point. Then, the sum of pump heads through the day was determined. The results proved that there is a most economical lo

Background: Urinary incontinence (UI) is a common disorder that affects women of various ages and impacts all aspects of life. This condition negatively influences quality of life. Fractional CO₂ laser (10600nm) is the recent method for treatment of stress urinary incontinence in women. Objectives: The purpose of the study was to evaluate the efficacy and safety of fractional CO₂ laser (10600nm) in the treatment of female stress urinary incontinence. Materials & Methods: This study was done from July 2020 to February 2021conducted at the laser institute for postgraduate studies university of Baghdad, patients collected from a private clinic and the Department of

Before the start of delivery, any membranes rupture could be named as a premature rupture of membranes (PROM), which may need special obstetrical interactions to minimize perinatal complications, it is important topromptly diagnose PROM, the method used should be accurate, cheap, simple, and widely available. This was exactly the idea behind this study to use an ordinary pregnancy test kit aiming to confirm presence of PROM.Over a 6 months’ period, 60 pregnant women with a history of leaking liquor and a positive speculum examination for amniotic fluid pooling were collected prospectively and compared with other 60 women (control group) with uneventful pregnancy. Majority of patients with positive leaking liquor signs and symptoms had a p

Al Machraya River was considered as one of the water feeders of Hawizeh Marsh. In 1986, the outlet of this river into the marsh was blocked and the river was used as a main channel for the East Tigris Irrigation Project near Kalat Salih. This causes significant decrease in the available water supply sources, deterioration in the water quality distribution patterns and increasing the stagnation areas within the marsh. This research aims to study the possibility of reusing this river for feeding Hawizeh Marsh. A frequency analysis study was carried out to study the maximum and minimum probable water level (MMPWL) of Tigris River at the upstream of Kalat Salih Barrage. Six statistical models; Normal distribution, Log-Normal type II, Lo

Objective: Breast cancer is regarded as a deadly disease in women causing lots of mortalities. Early diagnosis of breast cancer with appropriate tumor biomarkers may facilitate early treatment of the disease, thus reducing the mortality rate. The purpose of the current study is to improve early diagnosis of breast by proposing a two-stage classification of breast tumor biomarkers fora sample of Iraqi women.

Methods: In this study, a two-stage classification system is proposed and tested with four machine learning classifiers. In the first stage, breast features (demographic, blood and salivary-based attributes) are classified into normal or abnormal cases, while in the second stage the abnormal breast cases are