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 main goal of this in vivo study was to evaluate the effect of 532nm Q-switched Nd: YAG Laser in combination with Human Serum Albumin 20% concentration (as a welding aid) on the liver tissue repair clinically, and histologically. The animals used in this study were 21 male rabbits divided into three main groups: control group (3 rabbits), conventionally treated group (9 rabbits) and Laser treated group (9 rabbits). Each two main groups (conventional and laser treated) consist of three sub-groups depending on the response evaluation at three different periods. The Laser group was treated using 532nm Q-switched Nd: YAG laser after adding human serum albumin immediately on the incised liver’s tissue. The energy of was 460mJ, and 4Hz fr

This research is aimed at identifying the communicative habits and the impact of the content on the communicative process, especially the youth audience, which is one of the most important categories to which the advertisement is directed, as young people face life with passion and aspiration that make then responsive to all the influences used by the media in designing advertisements which use all the techniques and methocls to attract young people, such as relying on drama , artistic tricks, musical phrases and advertising slogans that respond to the desire of young people in entertainment.
The research aims to identify the reflection of television advertising and its impact on the development of the cognitive abilities of universi

Nanoparticles of humic acid and iron oxide were impregnated on the inert sand to produce sorbent for treating groundwater contained of cadmium and copper ions by technology of permeable reactive barrier (PRB). Sewage sludge was the source of the humic acid to prepare the coated sand by humic acid—iron oxide (CSHAIO) sorbent; so, this work is consistent with sustainable development. For 10 mg/L metal concentration, batch tests at speed of 200 rpm signified that the removal efficiencies are greater than 90% at sorbent dosage 0.25 g/ 50 mL, pH 6 and contact time 1 h. The kinetic data was well described by the Pseudo first-order model indicating that physicosorption is the predominant mechanism. The maximum adsorption capacities (qmax) were c

In all applications and specially in real time applications, image processing and compression plays in modern life a very important part in both storage and transmission over internet for example, but finding orthogonal matrices as a filter or transform in different sizes is very complex and importance to using in different applications like image processing and communications systems, at present, new method to find orthogonal matrices as transform filter then used for Mixed Transforms Generated by using a technique so-called Tensor Product based for Data Processing, these techniques are developed and utilized. Our aims at this paper are to evaluate and analyze this new mixed technique in Image Compression using the Discrete Wavelet Transfo

This research describes a new model inspired by Mobilenetv2 that was trained on a very diverse dataset. The goal is to enable fire detection in open areas to replace physical sensor-based fire detectors and reduce false alarms of fires, to achieve the lowest losses in open areas via deep learning. A diverse fire dataset was created that combines images and videos from several sources. In addition, another self-made data set was taken from the farms of the holy shrine of Al-Hussainiya in the city of Karbala. After that, the model was trained with the collected dataset. The test accuracy of the fire dataset that was trained with the new model reached 98.87%.