Astronomy image is regarded main source of information to discover outer space, therefore to know the basic contain for galaxy (Milky way), it was classified using Variable Precision Rough Sets technique to determine the different region within galaxy according different color in the image. From classified image we can determined the percentage for each class and then what is the percentage mean. In this technique a good classified image result and faster time required to done the classification process.

Two unsupervised classifiers for optimum multithreshold are presented; fast Otsu and k-means. The unparametric methods produce an efficient procedure to separate the regions (classes) by select optimum levels, either on the gray levels of image histogram (as Otsu classifier), or on the gray levels of image intensities(as k-mean classifier), which are represent threshold values of the classes. In order to compare between the experimental results of these classifiers, the computation time is recorded and the needed iterations for k-means classifier to converge with optimum classes centers. The variation in the recorded computation time for k-means classifier is discussed.

Among the issues that preoccupied ancient and modern grammarians is the phenomenon of grammatical disagreement among grammarians and their differences in many grammatical issues that many of them go back to the phenomenon of dialectical difference, so this filled our thinking with a lot of things that led us to look at the side of the reasons for this grammatical difference, and here lies the significance of research to know that it is a linguistic phenomenon dealing with the living language used among the Arabs and linguistic phenomena that reflect linguistic reality as well. Thus our chagrin determination in research and investigation in this issue is the scarcity of dialectical studies at the compositional grammar side, and the lack o

This research explains to us the role of the Islamic religion in the issue of accuracy in speech and work, and how it is closely related to human production in his life, and Islam affirms that his idea is mainly reflected in his production, and how it affects the perception of the meaning of creativity. Therefore, our Islam affirmed the accuracy in every word or work we do to build a society in which people enjoy high quality in ethics and dedication in their work so that the Islamic system depends on humanity to preserve our rights on the other hand the research discusses the deliberate default and how it reflects on our production and how it makes it less good.

Abstract

 The objective of image fusion is to merge multiple sources of images together in such a way that the final representation contains higher amount of useful information than any input one.. In this paper, a weighted average fusion method is proposed. It depends on using weights that are extracted from source images using counterlet transform. The extraction method is done by making the approximated transformed coefficients equal to zero, then taking the inverse counterlet transform to get the details of the images to be fused. The performance of the proposed algorithm has been verified on several grey scale and color test  images, and compared with some present methods.

Generally, different propositions show that culture changes because of many factors, and acculturation has emerged out of important operations which lead to cultural change as a result of contact between different societies or cultures. Since the cultural environment with its varying effects plays a major role in the formulation of architectural products, the research defined its research problem as follows: There is need for knowledge to specify the results of acculturation at  the level of plans of house architecture belong to Iraqi elites in Baghdad city during the late Ottoman rule in Iraq(1830-1917). The research depends on the comparative procedure to define the acculturation results, so the plans character of

The interests toward developing accurate automatic face emotion recognition methodologies are growing vastly, and it is still one of an ever growing research field in the region of computer vision, artificial intelligent and automation. However, there is a challenge to build an automated system which equals human ability to recognize facial emotion because of the lack of an effective facial feature descriptor and the difficulty of choosing proper classification method. In this paper, a geometric based feature vector has been proposed. For the classification purpose, three different types of classification methods are tested: statistical, artificial neural network (NN) and Support Vector Machine (SVM). A modified K-Means clustering algorithm

The research aims at identifying The Effect of Woods model in the Acquisition of Grammatical Concepts on students at the Sixth Primary. The total number of students is (49) male and female. students are distributed in two groups . The First group is the experimental group which is taught the( Woods Model) and it is (25) students . The second group is the control group which is taught according to the traditional method of teaching and it is (24) students . The researcher has matched between the two groups by the following variables : the age (in months), their intelligence, their parents, academic level of education . The research has constructed multiple choice test of (20) items . The reliability of The test has been calculated and it