Video steganography has become a popular option for protecting secret data from hacking attempts and common attacks on the internet. However, when the whole video frame(s) are used to embed secret data, this may lead to visual distortion. This work is an attempt to hide sensitive secret image inside the moving objects in a video based on separating the object from the background of the frame, selecting and arranging them according to object's size for embedding secret image. The XOR technique is used with reverse bits between the secret image bits and the detected moving object bits for embedding. The proposed method provides more security and imperceptibility as the moving objects are used for embedding, so it is difficult to notice the

 Abstract 

The vegetative filter strips (VFS) are a useful tool used for reducing the movement of sediment and pesticide in therivers. The filter strip’s soil can help in reducing the runoff volume by infiltration. However, the characteristics of VFS (i.e., length) are not recently identified depending on the estimation of VFS modeling performance. The aim of this research is to study these characteristics and determine acorrelation between filter strip length and percent reduction (trapping efficiency) for sediment, water, and pesticide. Two proposed pesticides(one has organic carbon sorption coefficient, K_oc, of 147 L/kg which is more moveable than XXXX, and another one

This research aims to predict the value of the maximum daily loss that the fixed-return securities portfolio may suffer in Qatar National Bank - Syria, and for this purpose data were collected for risk factors that affect the value of the portfolio represented by the time structure of interest rates in the United States of America over the extended period Between 2017 and 2018, in addition to data related to the composition of the bonds portfolio of Qatar National Bank of Syria in 2017, And then employing Monte Carlo simulation models to predict the maximum loss that may be exposed to this portfolio in the future. The results of the Monte Carlo simulation showed the possibility of decreasing the value at risk in the future due to the dec

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

Abstract

In this research provide theoretical aspects of one of the most important statistical distributions which it is Lomax, which has many applications in several areas, set of estimation methods was used(MLE,LSE,GWPM) and compare with (RRE) estimation method ,in order to find out best estimation method set of simulation experiment (36) with many replications  in order  to get mean square error and used it to make compare , simulation experiment  contrast with (estimation method, sample size ,value of location and shape parameter) results show that estimation method effected by simulation experiment factors and ability of using other estimation methods such as(Shrinkage, jackknif

This research aims to study the methods of reduction of dimensions that overcome the problem curse of dimensionality when traditional methods fail to provide a good estimation of the parameters So this problem must be dealt with directly . Two methods were used to solve the problem of high dimensional data, The first method is the non-classical method Slice inverse regression ( SIR ) method and the proposed weight standard Sir (WSIR) method and principal components (PCA) which is the general method used in reducing dimensions,    (SIR ) and (PCA) is based on the work of linear combinations of a subset of the original explanatory variables, which may suffer from the problem of heterogeneity and the problem of linear

The organizational culture is an effective control mechanism that dictates the behavior of employees and according to their intellectual and social orientations, so it is considered a more powerful way to control employee orientations and determine their management according to organizational rules and regulations, as it was one of the most important factors determining the performance of organizations, while organizational performance is a measure of what the organization has achieved from the objectives of the scheme To ensure that it faces various changes and remains within the global competition, and to reach that it was necessary to identify the most prominent and most important research problems in knowing the extent of com

Bacteriocins were partially purified by ammonium sulphate 50% concentraction, bacteriocin activity of Pediococcus acidilactici-FMAC278 was 25600 U/ml with 5.8 folds and 7.6% yeild, the activity decrease to 12800 U/ml after dialysis with 6.3 folds and 3% yield, On the other hand the bacteriocin activity of Weissella paramesenteroides-DFR6 was 12800 U/ml with 2.7 folds and 8.8% yeild, after dialysis the activity became 6400 U/ml with 5.1 fold and 3.4% yield, Chicken Sausage were made by adding 0.25, 0.5 and 1% particaly purified bacteriocin to study its effect on microorganisms and increasing shelf life of Sausage. It is found that bacterial numbers were decreased after 3 days of storage at refrigerator at 0.5% conc. While the molds decrea

       In recent years, the attention of researchers has increased of semi-parametric regression models, because it is possible to integrate the parametric and non-parametric regression models in one and then form a regression model has the potential to deal with the cruse of dimensionality in non-parametric models that occurs through the increasing of explanatory variables. Involved in the analysis and then decreasing the accuracy of the estimation. As well as the privilege of this type of model with flexibility in the application field compared to the parametric models which comply with certain conditions such as knowledge of the distribution of errors or the parametric models may

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 da