In this paper, an intelligent tracking control system of both single- and double-axis Piezoelectric Micropositioner stage is designed using Genetic Algorithms (GAs) method for the optimal Proportional-Integral-Derivative (PID) controller tuning parameters. The (GA)-based PID control design approach is a methodology to tune a (PID) controller in an optimal control sense with respect to specified objective function. By using the (GA)-based PID control approach, the high-performance trajectory tracking responses of the Piezoelectric Micropositioner stage can be obtained. The (GA) code was built and the simulation results were obtained using MATLAB environment. The Piezoelectric Micropositioner simulation model with th

Breast cancer is the most repeatedly detected cancer category and the second reason cause of cancer-linked deaths among women worldwide. Tumor bio-indictor is a term utilized to describe possible indicators for carcinoma diagnosis, development and progression. The goal of this study is to evaluate part of some cytokines and biomarkers for both serum and saliva samples in breast cancer then estimate their potential value in the early diagnosis of breast cancer by doing more researches in saliva, and utilizing saliva instead of blood (serum and plasma) in sample collection from patients. Serum and salivary samples were taken from 72 patients with breast cancer and 45 healthy controls, in order to investigate the following

The current study was conducted in the period extending from November 2018 to October 2019 and designed as a case-control study and aimed to assess the seroprevalence of HCMV. However, a total number of 91serum specimens were collected to fulfill this purpose from females (71 breast cancer patients, and control group of 20 females) attending Al-Amal hospital for cancer management and Baghdad teaching hospital and the practical part was performed in College of Science, University of Baghdad. The study protocol was approved by the Ethics Committee at the Department of Biology (Reference: BEC/0220/0011). The immunological part for evaluation of seroprevalence of HCMV was accomplished by ELISA technique which revealed that anti-HCMV IgG was sco

Determining the face of wearing a mask from not wearing a mask from visual data such as video and still, images have been a fascinating research topic in recent decades due to the spread of the Corona pandemic, which has changed the features of the entire world and forced people to wear a mask as a way to prevent the pandemic that has calmed the entire world, and it has played an important role. Intelligent development based on artificial intelligence and computers has a very important role in the issue of safety from the pandemic, as the Topic of face recognition and identifying people who wear the mask or not in the introduction and deep education was the most prominent in this topic. Using deep learning techniques and the YOLO (”You on

The paper present design of a control structure that enables integration of a Kinematic neural controller for trajectory tracking of a nonholonomic differential two wheeled mobile robot, then  proposes a Kinematic neural controller to direct a National Instrument mobile robot (NI Mobile Robot). The controller is to make the actual velocity of the wheeled mobile robot close the required velocity by guarantees that the trajectory tracking mean squire error converges at minimum tracking error. The proposed tracking control system consists of two layers; The first layer is a multi-layer perceptron neural network system that controls the mobile robot to track the required path , The second layer is an optimization layer ,which is impleme

Objective(s): The study aims to assess the early detection of early detection of first degree relatives to type-II
diabetes mellitus throughout the diagnostic tests of Glycated Hemoglobin A1C. (HgbA1C), Oral Glucose Tolerance
Test (OGTT) and to find out the relationship between demographic data and early detection of first degree
relatives to type-II diabetes mellitus.
Methodology: A purposive "non-probability" sample of (200) subjects first degree relatives to type-II diabetes
mellitus was selected from National Center for Diabetes Mellitus/Al-Mustansria University and Specialist Center
for Diabetes Mellitus and Endocrine Diseases/Al-kindy. These related persons have presented the age of (40-70)
years old. A questio

     This research develops a new method based on spectral indices and random forest classifier to detect paddy rice areas and then assess their distributions regarding to urban areas. The classification will be conducted on Landsat OLI images and Landsat OLI/Sentinel 1 SAR data. Consequently, developing a new spectral index by analyzing the relative importance of Landsat bands will be calculated by the random forest. The new spectral index has improved depending on the most three important bands, then two additional indices including the normalized difference vegetation index (NDVI), and standardized difference built-up index (NDBI) have been used to extract paddy rice fields from the data. Several experiments being