Mohamed A. Ismail

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—Most of the techniques used in the literature in clustering symbolic data are based on the hierarchical methodology, which utilizes the concept of agglomerative or divisive methods as the core of the algorithm. The main contribution of this paper is to show how to apply the concept of fuzziness on a data set of symbolic objects and how to use this concept(More)
Direct modulation of gene expression by targeting oncogenic transcription factors is a new area of research for cancer treatment. ERG, an ETS-family transcription factor, is commonly over-expressed or translocated in leukaemia and prostate carcinoma. In this work, we selected the di-(thiophene-phenyl-amidine) compound DB1255 as an ERG/DNA binding inhibitor(More)
In this paper, we present VSCAN, a novel approach for generating static video summaries. This approach is based on a modified DBSCAN clustering algorithm to summarize the video content utilizing both color and texture features of the video frames. The paper also introduces an enhanced evaluation method that depends on color and texture features. Video(More)
This paper presents WhatAreYouLOOKing4 (WAY-LOOK4) system, a novel framework for content-based image retrieval (CBIR). Local descriptors are used to describe the visual contents of an image. Image signatures and similarity retrieval are based on the images' color and texture features. The main motivation of the system design is to use simple and efficient(More)
Because of the different characteristics of Arabic language and Romance and Anglo Saxon languages, recognition of documents written in hybrid of these languages requires that the language of the text to be identified priori to the recognition phase. In this paper, three efficient techniques that can be used to discriminate between text written in Arabic(More)