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

The investigation of machine learning techniques for addressing missing well-log data has garnered considerable interest recently, especially as the oil and gas sector pursues novel approaches to improve data interpretation and reservoir characterization. Conversely, for wells that have been in operation for several years, conventional measurement techniques frequently encounter challenges related to availability, including the lack of well-log data, cost considerations, and precision issues. This study's objective is to enhance reservoir characterization by automating well-log creation using machine-learning techniques. Among the methods are multi-resolution graph-based clustering and the similarity threshold method. By using cutti

The research included studying a group of eight cuneiform texts dating back to the Old Babylonian era, specifically to the reign of King Larsa Rim-Sin, which were identified through studying the historical versions of these texts. These texts are confiscated, i.e. texts of unknown location, because they did not come through excavations, but rather came to the Iraqi Museum either by people who obtained them through digging, or stolen and smuggled texts that are retrieved by the General Authority for Antiquities; as is the case with our texts that were found smuggled to Jordan and were retrieved by the General Authority for Antiquities.

In this work we experimentally investigated SWCNTs and MWCNTs to increase their thermal conductivity and electrically functionalization process using different reagents ((nitric acid, HNO3 followed by acid treatment with H2SO4), then washed with deionized water (DW) and then treated with H2O2 via ultrasonic technique. Then repeated the steps with MWCNTs and compare their results in an effort to improve experimental conditions that efficiently differentiate the surface of the single walled carbon nanotubes (SWCNTs) and multi walled carbon nanotubesi(MWCNTs) that less nanotubes destroy and to enhance the properties of them and also to reduce aggregation in liquid. the results were prove by XRD, and infrared spectroscopy (FTIR). The FTIR sp

The aim of this essay is to use a single-index model in developing and adjusting Fama-MacBeth.  Penalized smoothing spline regression technique (SIMPLS) foresaw this adjustment.  Two generalized cross-validation techniques, Generalized Cross Validation Grid (GGCV) and Generalized Cross Validation Fast (FGCV), anticipated the regular value of smoothing covered under this technique. Due to the two-steps nature of the Fama-MacBeth model, this estimation generated four estimates: SIMPLS(FGCV) - SIMPLS(FGCV), SIMPLS(FGCV) - SIM PLS(GGCV), SIMPLS(GGCV) - SIMPLS(FGCV), SIM PLS(GGCV) - SIM PLS(GGCV). Three-factor Fama-French model—market risk premium, size factor, value factor, and their implication for excess stock returns and portfolio return

ECG is an important tool for the primary diagnosis of heart diseases, which shows the electrophysiology of the heart. In our method, a single maternal abdominal ECG signal is taken as an input signal and the maternal P-QRS-T complexes of original signal is averaged and repeated and taken as a reference signal. LMS and RLS adaptive filters algorithms are applied. The results showed that the fetal ECGs have been successfully detected. The accuracy of Daisy database was up to 84% of LMS and 88% of RLS while PhysioNet was up to 98% and 96% for LMS and RLS respectively.

In this work preparation of antireflection coating with single layer of MgO using pulsed laser deposition (PLD) method which deposit on glass substrate with different thicknesses (90 and 100) nm annealed at temperature 500 K was done.
The optical and structural properties (X-ray diffraction) have been determined. The optical reflectance was computed with the aid of MATLAB over the visible and near infrared region. Results shows that the best result obtained for optical performance of AR'Cs at 700 shots with thickness 90 nm nanostructure single layer AR'Cs and low reflection at wavelength 550 nm.