The developments accelerated in technology and rapid changes in the environment and increase numbers industrial countries and different desires and requirements of customers, lead to be produced in large quantities is not feasible due to changes listed above as well as the need to product variety and change in tastes and desires of consumers, all above led not to enable companies to discharge their products in the case of mass production and created the need to devise ways and new methods fit with the current situation, and accounting point no longer the traditional accounting systems able to meet the requirements needed by the companies to make decisions and know where waste and loss of resources resulting to invent new style away from

Total dissolved solids are at the top of the parameters list of water quality that requires investigations for planning and management, especially for irrigation and drinking purposes. If the quality of water is sufficiently predictable, then appropriate management is possible. In the current study, Multiple Linear Regression (MLR) and Artificial Neural Network (ANN) models were used as indicators of water quality and for the prediction of Total Dissolved Solids (TDS) along the Tigris River, in Baghdad city. To build these models five water parameters were selected from the intakes of four water treatment plants on the Tigris River, for the period between 2013 and 2017. The selected water parameters were Total Dissolved Solids (TDS

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 current paper proposes a new estimator for the linear regression model parameters under Big Data circumstances.  From the diversity of Big Data variables comes many challenges that  can be interesting to the  researchers who try their best to find new and novel methods to estimate the parameters of linear regression model. Data has been collected by Central Statistical Organization IRAQ, and the child labor in Iraq has been chosen as data. Child labor is the most vital phenomena that both society and education are suffering from and it affects the future of our next generation. Two methods have been selected to estimate the parameter

In this paper, the using of Non-Homogenous Poisson Processes, with one of the scientific and practical means in the Operations Research had been carried out, which is the Queuing Theory, as those operations are affected by time in their conduct by one function which has a cyclic behavior, called the (Sinusoidal Function). (M_t / M / S) The model was chosen, and it is Single Queue Length with multiple service Channels, and using the estimating scales (QL_s, HOL, HOL_r) was carried out in considering the delay occurring to the customer before his entrance to the service, with the comparison of the best of them in the cases of the overload.

Through the experiments

Objective: The approximate life span of a silicone maxillofacial prosthesis is as short as1.5–2 years of clinical service, then a new prosthesis should be fabricated. The most common reasonfor re-making the prosthesis is silicone mechanical properties degradation. The aim of this studywas to assess some mechanical properties of VST-30 silicone for maxillofacial prostheses after addi-tion of intrinsic pigments.Methods: Two types of intrinsic pigments (rayon flocking and burnt sienna); each of them wasincorporated into silicone. One hundred and twenty samples were prepared and split into 4 groupsaccording to the conducted tests (tear strength, hardness, surface roughness, and tensile strengthand elongation percentage) with 30 samples for ea

This research was conducted to measure the safety of heat stable enterotoxin a (STa) produced by enterotoxigenic Escherichia coli, through studying its toxic effect on human blood lymphocyte, since it showed a promising effect in reducing the proliferation of colorectal cancer cells. the cytogenetic effects of (STa) by using five different concentrations (100, 200, 400, 800 and 1600μg/ml) in comparison with negative (PBS, Phosphate buffer saline) and positive (MMC, Mitomycin C) at concentration of 5μg/ml, controls on human blood lymphocytes obtained from both (10) normal healthy persons and (20) colorectal cancer patients was measured by employing the following parameters: mitotic index, blast index, chromosomal aberrations and micronucle

Prediction of daily rainfall is important for flood forecasting, reservoir operation, and many other hydrological applications. The artificial intelligence (AI) algorithm is generally used for stochastic forecasting rainfall which is not capable to simulate unseen extreme rainfall events which become common due to climate change. A new model is developed in this study for prediction of daily rainfall for different lead times based on sea level pressure (SLP) which is physically related to rainfall on land and thus able to predict unseen rainfall events. Daily rainfall of east coast of Peninsular Malaysia (PM) was predicted using SLP data over the climate domain. Five advanced AI algorithms such as extreme learning machine (ELM), Bay