The present paper discusses morphological and syntactic structures of time in Russian language. The morphological and syntactic structures are considered part component of time category in Russian language.

The morphological categories of time are formed through a various types of expressions .Tenses generally express time relative to the moment of speaking. In some contexts, however, their meaning may be relativized to a point in the past ,present or future which is established in the discourse .Some languages have different verb forms or constructions and that are opposed in meaning not in syntactic category. Hence, the present study traces and compares the syntacti

Research deals the crises of the global recession of the facets of different and calls for the need to think out of the ordinary theory and find the arguments of the theory to accommodate the evolution of life, globalization and technological change and the standard of living of individuals and the size of the disparity in income distribution is not on the national level, but also at the global level as well, without paying attention to the potential resistance for thought the usual classical, Where the greater the returns of factors of production, the consumption will increase, and that the marginal propensity to consume may rise and the rise at rates greater with slices of low-income (the mouths of the poor) wi

Abstract Software-Defined Networking (commonly referred to as SDN) is a newer paradigm that develops the concept of a software-driven network by separating data and control planes. It can handle the traditional network problems. However, this excellent architecture is subjected to various security threats. One of these issues is the distributed denial of service (DDoS) attack, which is difficult to contain in this kind of software-based network. Several security solutions have been proposed recently to secure SDN against DDoS attacks. This paper aims to analyze and discuss machine learning-based systems for SDN security networks from DDoS attack. The results have indicated that the algorithms for machine learning can be used to detect DDoS

Diyala river is the most important tributaries in Iraq, this river suffering from pollution, therefore, this research aimed to predict organic pollutants that represented by biological oxygen demand BOD, and inorganic pollutants that represented by total dissolved solids TDS for Diyala river in Iraq, the data used in this research were collected for the period from 2011-2016 for the last station in the river known as D17, before the river meeting Tigris river in Baghdad city. Analysis Neural Network ANN was used in order to find the mathematical models, the parameters used to predict BOD were seven parameters EC, Alk, Cl, K, TH, NO3, DO, after removing the less importance parameters. While the parameters that used to predict TDS were fourte

The present study has three objectives: 1) to investigate the prevalence of complex nominals in economic discourse represented via the selected business news texts, 2) to shed some light on the most common translation errors made by second year students in the Department of Translation in rendering complex nominals into Arabic, and 3) to detect the possible causes behind such translation errors and suggest some translation tips which might sound helpful to the students of translation to find the most suitable translation equivalent. The present study is based on an empirical survey in which a selective analysis of someeconomic texts represented in business news texts is made. A corpus of 159 complex nominals was selected from seven busin

This study aims to identify the level of application of blue ocean leadership activities in public organizations and to build a conceptual and cognitive framework around this concept. The study adopted a descriptive-analytical approach, and the research sample consisted of (95) individuals from the senior management working at the center of the Iraqi Ministry of Communications (director general, department manager, section head). The data analysis technique used is structural equation modeling (SEM) and the Statistical Package for the Social Sciences (SPSS). The results indicate that the senior management in the Ministry of Communications is working to adopt the blue ocean leadership style through its activities, but not to the leve

Different frequency distributions models were fitted to the monthly data of raw water Turbidity at water treatment plants (WTPs) along Tigris River in Baghdad. Eight water treatment plants in Baghdad were selected, with raw water turbidity data for the period (2008-2014). The frequency distribution models used in this study are the Normal, Log-normal, Weibull, Exponential and two parameters Gamma type. The Kolmogorov-Smirnov test was used to evaluate the goodness of fit. The data for years (2008-2011) were used for building the models. The best fitted distributions were Log-Normal (LN) for Al-Karkh, Al-Wathbah, Al-Qadisiya, Al- Dawrah and, Al-Rashid WTPs. Gamma distribution fitted well for East Tigris and Al-Karamah WTPs. As for Al-

According to the prevalence of multidrug resistance bacteria, especially Pseudomonas aeruginosa, in which the essential mechanism of drug resistance is the ability to possess an efflux pump by which extrusion of antimicrobial agents usually occurs, this study aims to detect the presence of mexB multidrug efflux gene in some local isolates of this bacteria that show resistance towards three antibiotics, out of five. Sensitivity test to antibiotics was performed on all isolates by using meropenem (10μg/disc), imipenem (10μg/disc), amikacin (30 μg/disc), ciprofloxacin (5μg/disc) and ceftazidime (30 μg/disc). Conventional PCR results showed the presence of mexB gene (244bp) in four isolates out of ten (40%). In addition,25, 50μg/ml of cur