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

Churning of employees from organizations is a serious problem. Turnover or churn of employees within an organization needs to be solved since it has negative impact on the organization. Manual detection of employee churn is quite difficult, so machine learning (ML) algorithms have been frequently used for employee churn detection as well as employee categorization according to turnover. Using Machine learning, only one study looks into the categorization of employees up to date.  A novel multi-criterion decision-making approach (MCDM) coupled with DE-PARETO principle has been proposed to categorize employees. This is referred to as SNEC scheme. An AHP-TOPSIS DE-PARETO PRINCIPLE model (AHPTOPDE) has been designed that uses 2-stage MCDM s

EFFECT OF SPRAYING IRON AND ZINC CONCENTRATIONS IN GRAIN AND LEAF CONTENT FOR TWO VARIETIES OF WHEAT CROP

The new liganed Schiff base named [(E)-3-hydroxy-4-((3,4,5- trimethoxybenzylidene)amino) naphthalene-1- sulfonic acid] was synthesized from 3,4,5-trimethoxybenzyldehyde and 1-amino-2-aphthol-4- sulfonic acid in equal molar ratio. A series of new metal complexes' of the common molecular formulation [M(L)2(H2O)2].H2O are synthesized and characterized by IR, UV–Vis spectra, mass spectra, atomic absorption, elemental analyses, chloride content, magnetic susceptibility and conductivity measurements as well as thermo gravimetric analysis (TGA, DSC). Consistent with results of the magnetic and spectral studies, the advised geometrical structures for all of the prepared complexes have been octahedral formula

content Analysis for Some Type of Pillows used in Iraqi houses

Composting is one of the solid waste management (SWM) methods where the organic component decomposed biologically under controlled conditions. In this study, a 0.166 m³ bioreactor tank was designed to compose 59.2Kg of simulated common municipal solid food waste having a bulk density, organic matter, organic carbon, pH, nitrogen content, C/N and nitrification index (NH₄-N/ NO₃-N) of 536.62 kg/m³, 62.34%, 34.76%, 6.53, 1.86%, 23 and 0.34 respectively. The bioreactor operated aerobically for 30 days, and anaerobically for 70 days, until the end of the composting process. Results proved that the composting process could reduce the mass of the waste by 69%.  Nitrogen content,