The light-based life in the universe, including the human derived concepts and meanings of the fear of darkness and evil, comfort and goodness of light, became constitute bilateral haunted man to this day in various concepts of life.Therefore reflect the light form artistic aesthetic in visual arts such arts Fine Photography and the other until the emergence of art cinema, as the use of lighting in cinema has produced high-energy in the composition of its values expressive and symbolic, where it became dark and light are the space visually moving the vehicles media kit for many within the work structure artwork. The research is divided into five chapters, the first chapter (the methodological framework) that included an introduction the

This study discussed a biased estimator of the Negative Binomial Regression model known as (Liu Estimator), This estimate was used to reduce variance and overcome the problem Multicollinearity between explanatory variables, Some estimates were used such as Ridge Regression and Maximum Likelihood Estimators, This research aims at the theoretical comparisons between the new estimator (Liu Estimator) and the estimators

The aim of this research is to identify the availability of visual thinking skills in the chemistry textbook scheduled for the third intermediate grade for the academic year (2020-2021) in the Republic of Iraq. The study sample consisted of all (85) images contained in the chemistry course for the third intermediate grade, which are (85) form using the curriculum.  Analytical descriptive A list of visual thinking skills was prepared, and the unit of form was adopted as a unit of analysis and repetition as a unit of counting, and frequencies and percentages were used for statistical treatment, and validity and reliability were calculated.  And using the Holste equation.  The following results were reached: The skill

The optimum design is characterized by structural concrete components that can sustain loads well beyond the yielding stage. This is often accomplished by a fulfilled ductility index, which is greatly influenced by the arrangement of the shear reinforcement. The current study investigates the impact of the shear reinforcement arrangement on the structural response of the deep beams using a variety of parameters, including the type of shear reinforcement, the number of lacing bars, and the lacing arrangement pattern. It was found that lacing reinforcement, as opposed to vertical stirrups, enhanced the overall structural response of deep beams, as evidenced by test results showing increases in ultimate loads, yielding, and cracking of

Dynamic Thermal Management (DTM) emerged as a solution to address the reliability challenges with thermal hotspots and unbalanced temperatures. DTM efficiency is highly affected by the accuracy of the temperature information presented to the DTM manager. This work aims to investigate the effect of inaccuracy caused by the deep sub-micron (DSM) noise during the transmission of temperature information to the manager on DTM efficiency. A simulation framework has been developed and results show up to 38% DTM performance degradation and 18% unattended cycles in emergency temperature under DSM noise. The finding highlights the importance of further research in providing reliable on-chip data transmission in DTM application.

The optimum design is characterized by structural concrete components that can sustain loads well beyond the yielding stage. This is often accomplished by a fulfilled ductility index, which is greatly influenced by the arrangement of the shear reinforcement. The current study investigates the impact of the shear reinforcement arrangement on the structural response of the deep beams using a variety of parameters, including the type of shear reinforcement, the number of lacing bars, and the lacing arrangement pattern. It was found that lacing reinforcement, as opposed to vertical stirrups, enhanced the overall structural response of deep beams, as evidenced by test results showing increases in ultimate loads, yielding, and cracking of

Support vector machines (SVMs) are supervised learning models that analyze data for classification or regression. For classification, SVM is widely used by selecting an optimal hyperplane that separates two classes. SVM has very good accuracy and extremally robust comparing with some other classification methods such as logistics linear regression, random forest, k-nearest neighbor and naïve model. However, working with large datasets can cause many problems such as time-consuming and inefficient results. In this paper, the SVM has been modified by using a stochastic Gradient descent process. The modified method, stochastic gradient descent SVM (SGD-SVM), checked by using two simulation datasets. Since the classification of different ca

There are many methods of teaching foreign language to non-native speakers now therefore the discovery of new methods - which  make students understand the language , vocabulary & saves them as soon as possible – becomes one of  the most important duties of teachers and educators .

The personal experience shows that the teaching of the Russian language through memorizing    Russian poetry is   one of the fastest ways to master the language and know its rules and also    improve the   ability of translating vocabulary and being not able to  save the Russian words only  , but to make it complete too. Poetry is an article or text which loves by people and en