Background :The cotton factories have difference steps, spinning and weaving are van important parts of the factories. Cotton industry workers are exposed to various hazards in the different departments of textile factories. The major health problems associated with cotton dust are respiratory problems. Cotton workers display an excess of lung function abnormalities when compared to a community control population.
Aim of Study: This study assessed the effect of exposure to cotton dust in spinning and weaving workers on the lung function in Iraq, by measuring Forced Vital Capacity (FVC),Forced Expiratory Volume in the first second(FEV1), FEV1 ∕ FVC Ratio, and Forced Expiratory Flow 50%(FEF50%),with varying degree of reduction in lung

In light of the rapid changes in the business environment and the entry of administrative leaders in the challenges of the atheist and twenty- increasing competition between sectors and the desire to acquire the skills, the traditional methods are no longer viable, which requires doing evaluates performance according to a more holistic, rather than limiting the performance evaluation on the financial hub that has not longer enough alone, as well as benchmarking method that has proven successful in developed countries as a way to develop and improve products and services.

I've touched your search to the development of indicators evaluating the performance and preparation of a mechanism for making comparisons of reference between o

This research aims to identify the impact of the selective model in acquiring the concepts of Kurdish grammar among female students in the eighth grade, and to achieve the goal of research, the researcher selected the experimental design with partial control  and dimensional testing; the sample includes basic schools in the Chim district of Chamal/ Sulaymaniyah and randomly selected the basic school (Maha Bad) to be the field of application of the experiment and the random drawing method was chosen: two out of three sections and the number of students of the two sections is (75) students; section (C) represents the experimental group that studied the rules according to the selective model and its number is (37) students, while secti

Thyroid disease is a common disease affecting millions worldwide. Early diagnosis and treatment of thyroid disease can help prevent more serious complications and improve long-term health outcomes. However, thyroid disease diagnosis can be challenging due to its variable symptoms and limited diagnostic tests. By processing enormous amounts of data and seeing trends that may not be immediately evident to human doctors, Machine Learning (ML) algorithms may be capable of increasing the accuracy with which thyroid disease is diagnosed. This study seeks to discover the most recent ML-based and data-driven developments and strategies for diagnosing thyroid disease while considering the challenges associated with imbalanced data in thyroid dise

Today many people suffering from health problems like dysfunction in lungs and cardiac. These problems often require surveillance and follow up to save a patient's health, besides control diseases before progression. For that, this work has been proposed to design and developed a remote patient surveillance system, which deals with 4 medical signs (temperature, SPO2, heart rate, and Electrocardiogram ECG. An adaptive filter has been used to remove any noise from the signal, also, a simple and fast search algorithm has been designed to find the features of  ECG signal such as Q,R,S, and T waves.  The system performs analysis for medical signs that are used to detected abnormal values. Besides, it sends data to the Base-Stati

Abstract

Coronavirus has affected many people around the world and caused an increase in the number of hospitalized patients and deaths. The prediction factor may help the physician to classify whether the patient needs more medical attention to decrease mortality and worsening of symptoms. We aimed to study the possible relationship between C reactive protein level and the severity of symptoms and its effect on the prognosis of the disease. And determine patients who require closer respiratory monitoring and more aggressive supportive therapies to avoid poor prognosis. The data was gathered using medical record data, the patient's medical history, and the onset of symptoms, as well as a blood sample to test the