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 chemical pollution and profoundly have an effect on the life of the Iraqi people. The SICA estimator were chosen to analyze data and the MSE were used to make a comparison between the two methods and we determine that NP estimator is more effective than the other estimators under Big Data circumstances.
Linear programming currently occupies a prominent position in various fields and has wide applications, as its importance lies in being a means of studying the behavior of a large number of systems as well. It is also the simplest and easiest type of models that can be created to address industrial, commercial, military and other dilemmas. Through which to obtain the optimal quantitative value. In this research, we dealt with the post optimality solution, or what is known as sensitivity analysis, using the principle of shadow prices. The scientific solution to any problem is not a complete solution once the optimal solution is reached. Any change in the values of the model constants or what is known as the inputs of the model that will chan
... Show MoreIn this study water quality was indicated in terms of Water Quality Index that was determined through summarizing multiple parameters of water test results. This index offers a useful representation of the overall quality of water for public or any intended use as well as indicating pollution, water quality management and decision making. The application of Water Quality Index (WQI) with sixteen physicochemical water quality parameters was performed to evaluate the quality of Tigris River water for drinking usage. This was done by subjecting the water samples collected from eight stations in Baghdad city during the period 2004-2010 to comprehensive physicochemical analysis. The sixteen physicochemical parameters included: Turbidity,
... Show MoreIn this study water quality was indicated in terms of Water Quality Index that was determined through summarizing multiple parameters of water test results. This index offers a useful representation of the overall quality of water for public or any intended use as well as indicating pollution, water quality management and decision making. The application of Water Quality Index
(WQI) with sixteen physicochemical water quality parameters was performed to evaluate the quality of Tigris River water for drinking usage. This was done by subjecting the water samples collected from eight stations in Baghdad city during the period 2004-2010 to comprehensive physicochemical analysis. The sixteen physicochemical parameters included: Turbidity, A
Abstract
People are supposed to use language harmoniously and compatibly. However, aggression may characterize much of human communication. Aggression has long been recognized as a negative anti-social issue that prevails in most personal interactions. If it abounds in familial communications, it is more dangerous due to its harmful effects on individuals, and consequently on societies. Aggression refers to all the instances in which we try to get our way without any consideration for others. Moriarty’s novel (2014), Big Little Lies, is argued to represent the patterns of aggressive communications. This study aims to find out the motivations behind aggressive language in familial communication in this
... Show MoreIn this paper, we will discuss the performance of Bayesian computational approaches for estimating the parameters of a Logistic Regression model. Markov Chain Monte Carlo (MCMC) algorithms was the base estimation procedure. We present two algorithms: Random Walk Metropolis (RWM) and Hamiltonian Monte Carlo (HMC). We also applied these approaches to a real data set.
Unconfined compressive strength (UCS) of rock is the most critical geomechanical property widely used as input parameters for designing fractures, analyzing wellbore stability, drilling programming and carrying out various petroleum engineering projects. The USC regulates rock deformation by measuring its strength and load-bearing capacity. The determination of UCS in the laboratory is a time-consuming and costly process. The current study aims to develop empirical equations to predict UCS using regression analysis by JMP software for the Khasib Formation in the Buzurgan oil fields, in southeastern Iraq using well-log data. The proposed equation accuracy was tested using the coefficient of determination (R²), the average absolute
... Show MoreThe present study conducted to study epipelic algae in the Tigris River within Baghdad city for one year from September 2011 to August 2012 due to the importance role of benthic algae in lotic ecosystems. Five sites have been chosen along the river. A total of 154 species of epipelic algae was recorded belongs to 45 genera, where Bacillariophyceae (Diatoms) was the dominant groups followed by Cyanophyceae and Chlorophyceae. The numbers of common types in three sites were 47 species. Bacillariophyceae accounted 88.31% of the total number of epipelic algae, followed by Cyanophyceae 7.14 % and Chlorophyceae 4.55%. A 85 species (29 genera) recorded in site 1, 103 species (34 genera) in site2, 112 species (35 genera) in site3, 96 species
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The grey system model GM(1,1) is the model of the prediction of the time series and the basis of the grey theory. This research presents the methods for estimating parameters of the grey model GM(1,1) is the accumulative method (ACC), the exponential method (EXP), modified exponential method (Mod EXP) and the Particle Swarm Optimization method (PSO). These methods were compared based on the Mean square error (MSE) and the Mean Absolute percentage error (MAPE) as a basis comparator and the simulation method was adopted for the best of the four methods, The best method was obtained and then applied to real data. This data represents the consumption rate of two types of oils a he
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