Ziegler and Nichols proposed the well-known Ziegler-Nichols method to tune the coefficients of PID controller. This tuning method is simple and gives fixed values for the coefficients which make PID controller have weak adaptabilities for the model parameters variation and changing in operating conditions. In order to achieve adaptive controller, the Neural Network (NN) self-tuning PID control is proposed in this paper which combines conventional PID controller and Neural Network learning capabilities. The proportional, integral and derivative (K_P, K_I, K_D) gains are self tuned on-line by the NN output which is obtained due to the error value on the desired output of the system under control. The conventio

The research aims to evaluate the selected projects from the water Department of Baghdad, according to a standard for total quality management and to achieve this goal , adopted the case study method to get to know how close or turn away those projects in the management of Standard Malcolm Baldrige Award for Excellence in Quality Management its comprehensive one scales the world's most famous in this area , in order to draw a general framework to evaluate how project management can benefit from this approach to modern management , input from the entrances of the comprehensive management reform and development.

Be standard Malcolm Baldrige Award of several elements: - leadership , strategic planning , foc

Examining and comparing the image quality of degenerative cervical spine diseases through the application of three MRI sequences; the Two-Dimension T2 Weighed Turbo Spin Echo (2D T2W TSE), the Three-Dimension T2 Weighted Turbo Spin Echo (3D T2W TSE), and the T2 Turbo Field Echo (T2_TFE). Thirty-three patients who were diagnosed as having degenerative cervical spine diseases were involved in this study. Their age range was 40-60 years old. The images were produced via a 1.5 Tesla MRI device using (2D T2W TSE, 3D T2W TSE, and T2_TFE) sequences in the sagittal plane. The image quality was examined by objective and subjective assessments. The MRI image characteristics of the cervical spines (C4-C5, C5-C6, C6-C7) showed significant difference

The effect of mental and physical health on the feelings of subject welfare is known as health-related quality of life. The chronic obstructive pulmonary disease is a common respiratory diseases. Assessment of health-related quality of life is considered important in such chronic disease. The objective of the current study was to measure health-related quality of life in a sample of chronic obstructive pulmonary  patients in AL- Diwanyia city/Iraq. This study was carried out on 150 already diagnosed COPD patients who attended to the Center of Respiratory Diseases/AL-Diwaniyah Teaching Hospital during September  2019 to January 2020. The Arabic version of St George’s Respiratory Questionnaire was used to asses

Recently, the phenomenon of the spread of fake news or misinformation in most fields has taken on a wide resonance in societies. Combating this phenomenon and detecting misleading information manually is rather boring, takes a long time, and impractical. It is therefore necessary to rely on the fields of artificial intelligence to solve this problem. As such, this study aims to use deep learning techniques to detect Arabic fake news based on Arabic dataset called the AraNews dataset. This dataset contains news articles covering multiple fields such as politics, economy, culture, sports and others. A Hybrid Deep Neural Network has been proposed to improve accuracy. This network focuses on the properties of both the Text-Convolution Neural

The study was conducted over the period of Oct 2018 to Apr 2019 and is aimed for the detection and estimation of four hazardous Volatile Organic Compounds VOC (benzene, toluene, ethylbenzene, and xylene) so-called (BTEX) in samples collected from the produced water in the Al-Ahdab oil field in Iraq also to track their availability in the important natural water sources around the field. These compounds pose a risk to human health as well as environment. To avoid the laborious and tiresome conventional extraction methods, water samples were collected and concentrated using solid-phase extraction technique (SPE) which is a robust and cost-effective method of sample extraction with minimal exposure and handling of solvents and then to be analy

In this study, the stable isotop 18O and 2H has been used to investigate the interaction of surface water (SW), and groundwater (GW) in Al-Taji district/ Northern Baghdad for two seasons (March and August 2022). 16 Samples were collected from water resources in the Al-Taji district (Tigris channel, Tigris River, and groundwater), in each season water samples from 8 Tigris channel, 5 drilled wells, and 3 Tigris River were taken for the analysis of the isotopes 18O and 2H. The average analysis results of 18O and 2H in the Tigris channel, Tigris River, and groundwater were found to be -3.435‰ and -18.6094‰, -2.07167‰ and -17.81‰, -4.125‰ and -34.707‰ respectively. The results, generally, show a comparable range of isotope c

Biometrics represent the most practical method for swiftly and reliably verifying and identifying individuals based on their unique biological traits. This study addresses the increasing demand for dependable biometric identification systems by introducing an efficient approach to automatically recognize ear patterns using Convolutional Neural Networks (CNNs). Despite the widespread adoption of facial recognition technologies, the distinct features and consistency inherent in ear patterns provide a compelling alternative for biometric applications. Employing CNNs in our research automates the identification process, enhancing accuracy and adaptability across various ear shapes and orientations. The ear, being visible and easily captured in

Identifying breast cancer utilizing artificial intelligence technologies is valuable and has a great influence on the early detection of diseases. It also can save humanity by giving them a better chance to be treated in the earlier stages of cancer. During the last decade, deep neural networks (DNN) and machine learning (ML) systems have been widely used by almost every segment in medical centers due to their accurate identification and recognition of diseases, especially when trained using many datasets/samples. in this paper, a proposed two hidden layers DNN with a reduction in the number of additions and multiplications in each neuron. The number of bits and binary points of inputs and weights can be changed using the mask configuration