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

The idea of ​​carrying out research on incomplete data came from the circumstances of our dear country and the horrors of war, which resulted in the missing of many important data and in all aspects of economic, natural, health, scientific life, etc.,. The reasons for the missing are different, including what is outside the will of the concerned or be the will of the concerned, which is planned for that because of the cost or risk or because of the lack of possibilities for inspection. The missing data in this study were processed using Principal Component  Analysis and self-organizing map methods using simulation. The variables of child health and variables affecting children's health were taken into account: breastfeed

This research sought to present a concept of cross-sectional data models,  A crucial double data to take the impact of the change in time and obtained from the measured phenomenon of repeated observations in different time periods, Where the models of the panel  data were defined by different types of fixed , random and mixed, and Comparing them by studying and analyzing the mathematical relationship between the influence of time with a set of basic variables Which are the main axes on which the research is based and is represented by the monthly revenue of the working individual and the profits it generates, which represents the variable response And its relationship to a set of explanatory variables represented by the

The hydrological process has a dynamic nature characterised by randomness and complex phenomena. The application of machine learning (ML) models in forecasting river flow has grown rapidly. This is owing to their capacity to simulate the complex phenomena associated with hydrological and environmental processes. Four different ML models were developed for river flow forecasting located in semiarid region, Iraq. The effectiveness of data division influence on the ML models process was investigated. Three data division modeling scenarios were inspected including 70%–30%, 80%–20, and 90%–10%. Several statistical indicators are computed to verify the performance of the models. The results revealed the potential of the hybridized s

The study aims to investigate the degree of student teachers at Sultan Qaboos University acquired skills in teaching Arabic via a virtual micro-teaching lab, as well as to reveal the difficulties they faced and their development proposals. To do this, the researchers developed a questionnaire divided into four dimensions: planning, implementation, evaluation, and

ethical values for the teaching profession, in addition to two open-ended questions to identify difficulties and suggestions. It was administered to (30) student teachers. The results revealed that the average degree of student-teacher acquisition of skills was high in its four dimensions. It ranged between (39.2) to (82.2), while the overall average was (56.2).

The research aims at identify the role of the electronic trading system used in the Iraq stock exchange to promote trading activity for the stocks of listed companies in this market.

To prove the hypothesis of research, it was selected the main trading indicators for the market to be a main field in test the research hypothesis.it was selected as the period of time for (9)years span between the years (2005-2013) because they represent the first two articles of equal time periods represent aperiod that preceded the introduction of electronic trading system  while the second represents the period of time that followed 

The research found a number of conclusions but the mo

Tax information system is one of the most important means that help the tax administration to reach the real income of the taxpayer, and the problem of research came in the General Authority for Tax ,The next question (Does the control carried out by the Central Bank on foreign remittances to reach the real income of the taxpayer). The research is gaining importance by focusing on the Central Bank's control over foreign remittances, and how to use this control to finance the tax information system. The relationship between the Central Bank's control over foreign remittances and the tax information system.The study has reached a number of recommendations, the most important of which are the following: The work of an integrated information