The usage of remote sensing techniques in managing and monitoring the environmental areas is increasing due to the improvement of the sensors used in the observation satellites around the earth. Resolution merge process is used to combine high resolution one band image with another one that have low resolution multi bands image to produce one image that is high in both spatial and spectral resolution. In this work different merging methods were tested to evaluate their enhancement capabilities to extract different environmental areas; Principle component analysis (PCA), Brovey, modified (Intensity, Hue ,Saturation) method and High Pass Filter methods were tested and subjected to visual and statistical comparison for evaluation. Both visual and statistical comparison showed that High Pass Filter method have highest visual enhancement and highly maintained the quantitative information of the original image, Modified (Intensity, Hue, Saturation) method showed good visual and statistical results in comparison with PCA and Brovey method which had the lower results respectively.
Advertisement is one of the Media most efficient persuasive communicative activities designed to marketing different ideas and products with the aim of influencing consumers' perception of goods and services. The present study sheds light on the most prominent rhetorical devices that constitute the persuasive structure of the Hebrew advertisements published in various media outlet. The study is conducted by means of analyzing the linguistic structure of the advertising texts and according to the analytic and descriptive approach to know the characteristics and the functions of the oratorical devices used in the advertising industry. The research elucidates that most of the advertisements are written in slang language, and this is due to th
... Show MoreSimplification of new fashion design methods
The aim of the research is to estimate the hidden population. Here، the number of drug users in Baghdad was calculated for the male age group (15-60) years old ، based on the Bayesian models. These models are used to treat some of the bias in the Killworth method Accredited in many countries of the world.
Four models were used: random degree، Barrier effects، Transmission bias، the first model being random، an extension of the Killworth model، adding random effects such as variance and uncertainty Through the size of the personal network، and when expanded by adding the fact that the respondents have different tendencies، the mixture of non-random variables with random to produce
... Show MoreIn this paper, we used maximum likelihood method and the Bayesian method to estimate the shape parameter (θ), and reliability function (R(t)) of the Kumaraswamy distribution with two parameters l , θ (under assuming the exponential distribution, Chi-squared distribution and Erlang-2 type distribution as prior distributions), in addition to that we used method of moments for estimating the parameters of the prior distributions. Bayes
The study aimed to measure the concentration of some heavy metal elements and represented by (Pb, Cd,Cu) through the use of atomic absorption spectrometer Flame AAS-7000 type SHIMADZU underwent a process modeling to twelve samples from the soil of electricity Dezlat al Jadiriyah station in the Baghdad University compound at a depth of 30-60 cm from the surface and divided the samples into two groups first included six samples from inside the station while the second included six samples from outside the station. For the element of Pb was higher concentration reached by 29.32ppm and less concentration 17.56ppm. were elements Cd and Cu are growing and less and proportions of certain while the highest concentration of copper 9.69 ppm and le
... Show MoreThe logistic regression model regarded as the important regression Models ,where of the most interesting subjects in recent studies due to taking character more advanced in the process of statistical analysis .
The ordinary estimating methods is failed in dealing with data that consist of the presence of outlier values and hence on the absence of such that have undesirable effect on the result. &nbs
... Show MoreIn order to obtain a mixed model with high significance and accurate alertness, it is necessary to search for the method that performs the task of selecting the most important variables to be included in the model, especially when the data under study suffers from the problem of multicollinearity as well as the problem of high dimensions. The research aims to compare some methods of choosing the explanatory variables and the estimation of the parameters of the regression model, which are Bayesian Ridge Regression (unbiased) and the adaptive Lasso regression model, using simulation. MSE was used to compare the methods.
Abstract
The problem of missing data represents a major obstacle before researchers in the process of data analysis in different fields since , this problem is a recurrent one in all fields of study including social , medical , astronomical and clinical experiments .
The presence of such a problem within the data to be studied may influence negatively on the analysis and it may lead to misleading conclusions , together with the fact that these conclusions that result from a great bias caused by that problem in spite of the efficiency of wavelet methods but they are also affected by the missing of data , in addition to the impact of the problem of miss of accuracy estimation
... Show MoreThe question of estimation took a great interest in some engineering, statistical applications, various applied, human sciences, the methods provided by it helped to identify and accurately the many random processes.
In this paper, methods were used through which the reliability function, risk function, and estimation of the distribution parameters were used, and the methods are (Moment Method, Maximum Likelihood Method), where an experimental study was conducted using a simulation method for the purpose of comparing the methods to show which of these methods are competent in practical application This is based on the observations generated from the Rayleigh logarithmic distribution (RL) with sample sizes
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