Chemical pollution is a very important issue that people suffer from and it often affects the nature of health of society and the future of the health of future generations. Consequently, it must be considered in order to discover suitable models and find descriptions to predict the performance of it in the forthcoming years. Chemical pollution data in Iraq take a great scope and manifold sources and kinds, which brands it as Big Data that need to be studied using novel statistical methods. The research object on using Proposed Nonparametric Procedure NP Method to develop an (OCMT) test procedure to estimate parameters of linear regression model with large size of data (Big Data) which comprises many indicators associated with chemi

This study seeks to address the impact of marketing knowledge dimensions (product, price, promotion, distribution) on the organizational performance in relation to a number of variables which are (efficiency, effectiveness, market share, customer satisfaction), and seeks to reveal the role of marketing knowledge in organizational performance.

In order to achieve the objective of the study the researcher has adopted a hypothetical model that reflects the logical relationships between the variables of the study. In order to reveal the nature of these relationships, several hypotheses have been presented as tentative solutions and this study seeks to verify the validity of these hypotheses.

     The research problem revolves around the failure of Maysan Oil Company to have a strategy that enables it to keep up with work in a mysterious and highly dynamic environment. Therefore, the research aims to present a proposed strategy that is comprehensive and realistic to the Maysan Oil Company for the next five years (2020-2024) based on the position and conditions of the company Current and future by adopting the scientific foundations for formulating the strategy, and the importance of research lies in the company's situational analysis to know its internal capabilities from strengths or weaknesses and diagnosing the surrounding elements of opportunities or threats so that this analysis represents a s

The world faced many communication challenges in 2020 after the Covid-19 pandemic, the most important of which was the continuation of schooling. Therefore, the research aimed to analyze the current reality of the studied universities in terms of strengths and weaknesses and measure the implementing level of quality requirements of e-learning. This research studies the impact of knowledge sharing in its dimensions (behavior, organizational culture, work teams, and technology) on the e-learning quality and its dimensions (e-learning management, educational content, evaluation ,and evaluation). After conducting the survey, there was a difference in the universities’ application of the quality requirements of e-learning, as the study

The proposal of nonlinear models is one of the most important methods in time series analysis, which has a wide potential for predicting various phenomena, including physical, engineering and economic, by studying the characteristics of random disturbances in order to arrive at accurate predictions.

In this, the autoregressive model with exogenous variable was built using a threshold as the first method, using two proposed approaches that were used to determine the best cutting point of [the predictability forward (forecasting) and the predictability in the time series (prediction), through the threshold point indicator]. B-J seasonal models are used as a second method based on the principle of the two proposed approaches in dete

Abstract

     Travel Time estimation and reliability measurement is an important issues for improving operation efficiency and safety of traffic roads networks. The aim of this research is the estimation of total travel time and distribution analysis for three selected links in Palestine Arterial Street in Baghdad city. Buffer time index results in worse reliability conditions. Link (2) from Bab Al Mutham intersection to Al-Sakara intersection produced a buffer index of about 36%  and 26 % for Link (1) Al-Mawall intersection to Bab Al- Mutham intersection and finally for link (3) which presented a 24% buffer index. These illustrated that the reliability get worst for link

Monaural source separation is a challenging issue due to the fact that there is only a single channel available; however, there is an unlimited range of possible solutions. In this paper, a monaural source separation model based hybrid deep learning model, which consists of convolution neural network (CNN), dense neural network (DNN) and recurrent neural network (RNN), will be presented. A trial and error method will be used to optimize the number of layers in the proposed model. Moreover, the effects of the learning rate, optimization algorithms, and the number of epochs on the separation performance will be explored. Our model was evaluated using the MIR-1K dataset for singing voice separation. Moreover, the proposed approach achi