The topic of research (women and ideology in the feature film) is a series of researches addressed by the researcher on the subject of women in the feature film through studying the ideology as a thought and political system not only limited to the world of men, but women had a significant contribution in this area.  The research identified the problem and its need as well as the objectives of the research and clarified its limits and importance. The research also identified the theoretical framework, which included the following axes: personality and ideology, film and ideology, then women and ideology in the film.

After the completion of the theoretical framework, the research concluded a set of indicators of the theoretic

Perhaps going to watch movies in cinemas today has become different from what it was before. The cinematic film, the clarity of the image and the luster of its colors pulled the rug out from under the most important change that occurred in the structure of the contemporary cinematography, which is the sound. The surround sound environment that immerses viewers in the realism of sound that reaches them from all directions, and for this the researcher found it necessary to shed light on this topic because of its importance, so the research problem was represented in the following question: (How are modern sound systems used in the structure of contemporary feature films?) The theoretical framework included two topics: the first: the dialec

There is a great deal of systems dealing with image processing that are being used and developed on a daily basis. Those systems need the deployment of some basic operations such as detecting the Regions of Interest and matching those regions, in addition to the description of their properties. Those operations play a significant role in decision making which is necessary for the next operations depending on the assigned task. In order to accomplish those tasks, various algorithms have been introduced throughout years. One of the most popular algorithms is the Scale Invariant Feature Transform (SIFT). The efficiency of this algorithm is its performance in the process of detection and property description, and that is due to the fact that

The speech recognition system has been widely used by many researchers using different
methods to fulfill a fast and accurate system. Speech signal recognition is a typical
classification problem, which generally includes two main parts: feature extraction and
classification. In this paper, a new approach to achieve speech recognition task is proposed by
using transformation techniques for feature extraction methods; namely, slantlet transform
(SLT), discrete wavelet transforms (DWT) type Daubechies Db1 and Db4. Furthermore, a
modified artificial neural network (ANN) with dynamic time warping (DTW) algorithm is
developed to train a speech recognition system to be used for classification and recognition
purposes. T

This paper suggest two method of recognition, these methods depend on the extraction of the feature of the principle component analysis when applied on the wavelet domain(multi-wavelet). First method, an idea of increasing the space of recognition, through calculating the eigenstructure of the diagonal sub-image details at five depths of wavelet transform is introduced. The effective eigen range selected here represent the base for image recognition. In second method, an idea of obtaining invariant wavelet space at all projections is presented. A new recursive from that represents invariant space of representing any image resolutions obtained from wavelet transform is adopted. In this way, all the major problems that effect the image and

This paper  deals  to how to estimate points non measured spatial data when the number of its terms (sample spatial) a few, that are not preferred for the estimation process, because we also know that whenever if the data is large, the estimation results of the points non measured to be better and thus the variance estimate less, so the idea of this paper is how to take advantage of the data other secondary (auxiliary), which have a strong correlation with the primary data (basic) to be estimated single points of non-measured, as well as measuring the variance estimate, has been the use of technique Co-kriging in this field to build predictions spatial estimation process, and then we applied this idea to real data in th

The current research deals with the subject of spatial transformations and visual construction in contemporary theater. How the visual system works to create spatial diversity in the contemporary Iraqi theater performance and how visual construction contributes to a spatial development process capable of building a tourism system that creates an architectural architecture that leaves the topography of the scriptural architecture. And the production of various indications and patterns in the scene of theatrical presentation in order to produce the new foundational meaning by creating a new structure that leads to diversity and diversity in the visual system and the beginning of visual constructions and their applications. Knowledge and te

The density-based spatial clustering for applications with noise (DBSCAN) is one of the most popular applications of clustering in data mining, and it is used to identify useful patterns and interesting distributions in the underlying data. Aggregation methods for classifying nonlinear aggregated data. In particular, DNA methylations, gene expression. That show the differentially skewed by distance sites and grouped nonlinearly by cancer daisies and the change Situations for gene excretion on it. Under these conditions, DBSCAN is expected to have a desirable clustering feature i that can be used to show the results of the changes. This research reviews the DBSCAN and compares its performance with other algorithms, such as the tradit