Most of the medical datasets suffer from missing data, due to the expense of some tests or human faults while recording these tests. This issue affects the performance of the machine learning models because the values of some features will be missing. Therefore, there is a need for a specific type of methods for imputing these missing data. In this research, the salp swarm algorithm (SSA) is used for generating and imputing the missing values in the pain in my ass (also known Pima) Indian diabetes disease (PIDD) dataset, the proposed algorithm is called (ISSA). The obtained results showed that the classification performance of three different classifiers which are support vector machine (SVM), K-nearest neighbour (KNN), and Naïve B

Clerodendrum plant is believed to be very useful in many countries for treating various health disorders .“in this study was undertaken to assess antimicrobial activity of ethanol and aqueous extracts of clerodendrum plant”. Display my alcoholic extract higher inhibition of the aqueous extract all of the bacteria (Esherichia Coli , Pseudomonas aeruginosa, Bacillus subtilis). While the inhibition of the aqueous extract bacteria (Streptococcus, Shigelladysenteria) in higher alcoholic extract. However, the bacteria (Klebseillapneumoniae) did not shown any inhibition zone for both aqueous and alcoholic extracts. From the above results,“ it is concluded the antibacterial properties of Clerodendrum against life threatening pathogens”. So,

The extraction process of chlorophyll from dehydrated and pulverized alfalfa plant were studied by percolation method. Two  solvent systems were used for the extraction namely; Ethanol-water and Hexane-Toluene systems . The effect of circulation rate, solvent concentration, and solvent volume to solid weight ratio were studied. In  both ethanol water, and Hexane-Toluene systems it appears that solvent concentration is the most effective variable.

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