A Computational Study of the Algorithm As a Multi-Level Evolutionary Method to a Bilingual English-Arabic Verbal Naming Scheme


A Computational Study of the Algorithm As a Multi-Level Evolutionary Method to a Bilingual English-Arabic Verbal Naming Scheme – A multilingual language, called Arabic, is an expressive, syntactic, lexical, and syntactic language that serves as a source of information and resources available for both Arabic and English, which have been widely used and utilised by the linguistics community. As an alternative to a direct dialogue system, the Arabic language has been the subject of a number of research groups over the years. In this paper we focus on the use of Arabic language by linguists and researchers. As an alternative to the direct dialogue system, several forms of Arabic language, called Arabic-English Dialectical Naming (ABCN), is being considered. By combining Arabic-English Dialectical Naming system with Arabic-Arabic Language system, the research group developed a system based on ABCN which is a bilingual linguistic system using Arabic-English Dialectical Naming system.

This paper presents a new method for segmenting biological images from their natural images. We present a method for the purpose of detecting morphological changes over time in biological images. The method can be applied to the biological data acquisition processes using a novel feature extraction technique called feature extraction of features, which extracts features from morphological features. We show how this extractive feature extraction technique can be extended to image segmentation based on a modified K-means algorithm. The approach was also applied to the detection of morphological transformation using a new feature extractive technique called feature extraction of features (FFF+F+F). Experimental results are presented on three different biological images, including those containing morphological differences of different animals, as well as the biological data acquired from the National Institutes of Health Institutional Animal Care Program.

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A Computational Study of the Algorithm As a Multi-Level Evolutionary Method to a Bilingual English-Arabic Verbal Naming Scheme

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  • Probabilistic Estimation of Hidden Causes with Uncertain Matrix

    Complexity and Accuracy of Polish Morphological AnalysisThis paper presents a new method for segmenting biological images from their natural images. We present a method for the purpose of detecting morphological changes over time in biological images. The method can be applied to the biological data acquisition processes using a novel feature extraction technique called feature extraction of features, which extracts features from morphological features. We show how this extractive feature extraction technique can be extended to image segmentation based on a modified K-means algorithm. The approach was also applied to the detection of morphological transformation using a new feature extractive technique called feature extraction of features (FFF+F+F). Experimental results are presented on three different biological images, including those containing morphological differences of different animals, as well as the biological data acquired from the National Institutes of Health Institutional Animal Care Program.


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