The features of strategic thought transformation in Russia based on attempt confirm the Russian influenced on Region of Eastern Europe through series of common defense treaties and mutual security between USSR and another states this treaties emphasis size on direct Russian supervision on these states in addition, Russia in trusted to formation communism regimes in its vital space, Russia inherited the status of former USSR in political and economic levels.

           Shortly we can see that Russia witnessed large Transformation in political strategic thought as a result of change in internal strategic environment and change of nature understanding which influenced on Russia. This

Text based-image clustering (TBIC) is an insufficient approach for clustering related web images. It is a challenging task to abstract the visual features of images with the support of textual information in a database. In content-based image clustering (CBIC), image data are clustered on the foundation of specific features like texture, colors, boundaries, shapes. In this paper, an effective CBIC) technique is presented, which uses texture and statistical features of the images. The statistical features or moments of colors (mean, skewness, standard deviation, kurtosis, and variance) are extracted from the images. These features are collected in a one dimension array, and then genetic algorithm (GA) is applied for image clustering.

Some new 2,5-disubsituted-1,3,4-oxadiazole derivatives with azo group were synthesized by known reactions sequence . The structure of the synthesized compounds were confirmed by physical and spectral means .

Due to the increase in the number of the satellite channels which resulted from the satellite broadcasting, the demand for the television drama production has increased dramatically, and there has been a significant competitive market, which encouraged the producers to adopt many carrots among them the inclusion of TV series large scenes whose main purpose is to show the volume of the production in the series, let alone achieving the dramatic function. The researcher called this type of scenes (the productive scenes), a name which has not been used before. The researcher studied these scenes and determined his research subject under the title (the production scenes in the TV series) where the research problem has been determined through

Although language research has focused on blackmail in general, less attention has been paid to emotional blackmail. To date, researchers could not locate any literature that examines emotional blackmail from a linguistic standpoint. The current study is intended to fill this gap by scrutinizing emotional blackmail from a pragma-stylistic point of view by examining the style of the characters in selected episodes extracted from the American Breaking Bad series. To carry out the study, an eclectic model comprising kinds of emotional blackmailers by Forward and Frazier (1997), Searles’ speech acts (1979), Grice’s maxims (1975), Brown and Levinson’s politeness (1987), Culpeper’s impoliteness (1996), and Simpson’s stylistic le

KE Sharquie, AA Noaimi, ZM Mijthab, J Clin Exp Dermatol Res, 2012 - Cited by 5

The aim of this study to conduct the effects of fimbrial and lipopolysacchride (LPS) immunization is on the pathohistological changes in rabbits, Fifteen rabbits of both sexes (Weight 1500-2000 gm) divided into three groups (5 animals of each group). The first group was immunized by 1ml (200µg /animal) of fimbrial subcutaneously the second group gave 1 ml ( 200 µg /animal) LPS while the third group was left as negative control group that injected 1 ml phosphate buffer control subcutaneously. First and second groups recived the same dose after two weeks give as booster dose. All animals challenged after 5 weeks of immunization by5X107CFU/ml Proteus vulgaris intra peritoneally .After 7 days from challenge all the animals, sacrificed for hi

Over the past few years, ear biometrics has attracted a lot of attention. It is a trusted biometric for the identification and recognition of humans due to its consistent shape and rich texture variation. The ear presents an attractive solution since it is visible, ear images are easily captured, and the ear structure remains relatively stable over time.  In this paper, a comprehensive review of prior research was conducted to establish the efficacy of utilizing ear features for individual identification through the employment of both manually-crafted features and deep-learning approaches. The objective of this model is to present the accuracy rate of person identification systems based on either manually-crafted features such as D

The work is devoted to the study of the plastics features in modern construction use. The plastics classification in modern construction is generalized. This classification includes: the field of building products application, the features of the materials properties and products, a backup group that includes those products that are not included in the previous groups. The classification considered is the basis for choosing the basic materials properties that affect the quality and durability of products. To improve the plastics types in the construction, the Venn diagram is used. The main materials types for manufacturing a product of the "window profile" type are analyzed; the result of the studies is a comparative diagram.

This paper presents a method to classify colored textural images of skin tissues. Since medical images havehighly heterogeneity, the development of reliable skin-cancer detection process is difficult, and a mono fractaldimension is not sufficient to classify images of this nature. A multifractal-based feature vectors are suggested hereas an alternative and more effective tool. At the same time multiple color channels are used to get more descriptivefeatures.Two multifractal based set of features are suggested here. The first set measures the local roughness property, whilethe second set measure the local contrast property.A combination of all the extracted features from the three colormodels gives a highest classification accuracy with 99.4