In this paper, we will illustrate a gamma regression model assuming that the dependent variable (Y) is a gamma distribution and that it's mean ( ) is related through a linear predictor with link function which is identity link function g(μ) = μ. It also contains the shape parameter which is not constant and depends on the linear predictor and with link function which is the log link and we will estimate the parameters of gamma regression by using two estimation methods which are The Maximum Likelihood and the Bayesian and a comparison between these methods by using the standard comparison of average squares of error (MSE), where the two methods were applied to real data on the disease of jaundice of children newborns(Infant Jaundice) and it was the best method of estimation It is the Maximum Likelihood because it gave less (MSE).
The species of Cr (III), Cr (VI) in biological samples and V(IV), V(V) in foods & plants samples were determined by spectrophotometric methods. Integrated spectral studies of complexes [Cr (III, VI)-DPC], [Cr (VI)-bipy], [VO-SH], [V (V)-8-HQ] which included a study of the optimum conditions for the complexes formation by the investigation of the chemical and physical variables affecting each complex formation, the nature of complexes, the preparation of calibration curves of the complexes and treated the resulted data by modern statistical methods and study the interfering species. Interferences were removed to explain the reactions thermodynamically by determining Ecell, Keq. and ∆G values and includes a study of
... Show MoreIn real situations all observations and measurements are not exact numbers but more or less non-exact, also called fuzzy. So, in this paper, we use approximate non-Bayesian computational methods to estimate inverse Weibull parameters and reliability function with fuzzy data. The maximum likelihood and moment estimations are obtained as non-Bayesian estimation. The maximum likelihood estimators have been derived numerically based on two iterative techniques namely “Newton-Raphson†and the “Expectation-Maximization†techniques. In addition, we provide compared numerically through Monte-Carlo simulation study to obtained estimates of the parameters and reliability function i
... Show MoreIn data mining, classification is a form of data analysis that can be used to extract models describing important data classes. Two of the well known algorithms used in data mining classification are Backpropagation Neural Network (BNN) and Naïve Bayesian (NB). This paper investigates the performance of these two classification methods using the Car Evaluation dataset. Two models were built for both algorithms and the results were compared. Our experimental results indicated that the BNN classifier yield higher accuracy as compared to the NB classifier but it is less efficient because it is time-consuming and difficult to analyze due to its black-box implementation.
The research aims to identify the possibility of applying environmental fines to commercial shops and restaurants to reduce the environmental pollution represented by the wastes generated from them. The research sample was divided into two groups, including the first (20) commercial shops (meat shops and slaughter it, fruits & vegetables, legumes and accessories) and second (30) Restaurant in the city of Baghdad on both sides of Karkh and Rusafa. The quality of the waste was classified into carton, plastic, aluminum, glass, paper, cork and food waste. The study revealed the possibility of applying environmental fines to restaurants and shops to reduce the waste generated from them throughout the year and to apply continuous monitorin
... Show MoreThe research aims to shed light on the amount of proceeds annual tax for each of the way the contract total and percentage of completion method - see which is better - as well as the current problems arising from the application method of the contract in full in settling accounts tax - to identify problems - related to postpone settling accounts tax in accordance with the way the contract fully and determine the advantages and disadvantages of each of the methods through practical application , and then use the results as inputs to help in the decision to confirm the continuation of the GCT using a full decade in settling accounts tax for long-term construction contracts or forgo them.
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... Show MoreThe study aims to achieve several objectives, including follow-up scientific developments and transformations in the modern concepts of the Holistic Manufacturing System for the purpose of identifying the methods of switching to the entrances of artificial intelligence, and clarifying the mechanism of operation of the genetic algorithm under the Holonic Manufacturing System, to benefit from the advantages of systems and to achieve the maximum savings in time and cost of machines Using the Holistic Manufacturing System method and the Genetic algorithm, which allows for optimal maintenance time and minimizing the total cost, which in turn enables the workers of these machines to control the vacations in th
... Show MoreThere is no doubt that the advertisement picture and the written text play a key role in the formation of the language of the communicative discourse as the main pillars of the design of commercial advertising and the main entrance for the advertising message awareness... Hence the researcher chose the title of her research (Integrative Relationship between the Picture and the Written Text in the Printed Commercial Advertisement) starting from following questions: What is the relationship between the picture and the written text in the printed commercial declaration? Is there functional, aesthetic and interactive integration between them?
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... Show MoreThis research aims to removes dyes from waste water by adsorption using banana peels. The conduct experiment done by banana powder and banana gel to compare between them and find out which one is the most efficient in adsorption. Studying the effects different factors on adsorption material and calculate the best removal efficiency to get rid of the methylene blue dye (MB).
In this research, Artificial Neural Networks (ANNs) technique was applied in an attempt to predict the water levels and some of the water quality parameters at Tigris River in Wasit Government for five different sites. These predictions are useful in the planning, management, evaluation of the water resources in the area. Spatial data along a river system or area at different locations in a catchment area usually have missing measurements, hence an accurate prediction. model to fill these missing values is essential.
The selected sites for water quality data prediction were Sewera, Numania , Kut u/s, Kut d/s, Garaf observation sites. In these five sites models were built for prediction of the water level and water quality parameters.