Extractive multi-document text summarization – a summarization with the aim of removing redundant information in a document collection while preserving its salient sentences – has recently enjoyed a large interest in proposing automatic models. This paper proposes an extractive multi-document text summarization model based on genetic algorithm (GA). First, the problem is modeled as a discrete optimization problem and a specific fitness function is designed to effectively cope with the proposed model. Then, a binary-encoded representation together with a heuristic mutation and a local repair operators are proposed to characterize the adopted GA. Experiments are applied to ten topics from Document Understanding Conference DUC2002 datas

Schizophrenia(SCZ) is oneof the most destructive and complicated chronic diseases of the human nervous system. Serotonin receptors have been involved in the pathophysiology of psychiatric disorders including schizophrenia. Fortyschizophrenia subjects (14females and 26 males) with an age range of 23– 57 years were enrolled, in addition to twenty healthy control subjects (10female and 10 male) with an age range of 19-44 years.

This study aimed to evaluate the frequency of one single nucleotide polymorphism (SNP), namelyrs643627 in HTR2Agene,inIraqi patients with schizophrenia in comparison with controls, along with the association between this SNP and the incidence of schizophrenia.

The genetic variantrs6436

       In spite of the high rate of morbidity and mortality heart failure (HF) is common, and none of the medications are now entirely available for HF treatment. In addition to many environmental influences and clinical diseases, genetic factors may also contribute to the progression and development of HF.  In the current study, samples of blood were collected from 150 heart failure patients and 130 healthy controls. We evaluated the association of four single nucleotide polymorphisms (snps) of Toll-like receptors (TLR6 and TLR5) with (HF) susceptibility in the Iraqi population. In this work, (SNP) called Toll-like receptor 5 (rs5744168, rs2072493) and Toll-like receptor 6 (rs1039559, rs5743810) were employed. (PCR-RFLP) for snps

Determining the face of wearing a mask from not wearing a mask from visual data such as video and still, images have been a fascinating research topic in recent decades due to the spread of the Corona pandemic, which has changed the features of the entire world and forced people to wear a mask as a way to prevent the pandemic that has calmed the entire world, and it has played an important role. Intelligent development based on artificial intelligence and computers has a very important role in the issue of safety from the pandemic, as the Topic of face recognition and identifying people who wear the mask or not in the introduction and deep education was the most prominent in this topic. Using deep learning techniques and the YOLO (”You on

Rivest Cipher 4 (RC4) is an efficient stream cipher that is commonly used in internet protocols. However, there are several flaws in the key scheduling algorithm (KSA) of RC4. The contribution of this paper is to overcome some of these weaknesses by proposing a new version of KSA coined as modified KSA . In the initial state of the array is suggested to contain random values instead of the identity permutation. Moreover, the permutation of the array is modified to depend on the key value itself. The proposed performance is assessed in terms of cipher secrecy, randomness test and time under a set of experiments with variable key size and different plaintext size. The results show that the RC4 with improves the randomness and secrecy with

For businesses that provide delivery services, the efficiency of the delivery process in terms of punctuality is very important. In addition to increasing customer trust, efficient route management, and selection are required to reduce vehicle fuel costs and expedite delivery. Some small and medium businesses still use conventional methods to manage delivery routes. Decisions to manage delivery schedules and routes do not use any specific methods to expedite the delivery settlement process. This process is inefficient, takes a long time, increases costs and is prone to errors. Therefore, the Dijkstra algorithm has been used to improve the delivery management process. A delivery management system was developed to help managers and drivers

Stemming is a pre-processing step in Text mining applications as well as it is very important in most of the Information Retrieval systems. The goal of stemming is to reduce different grammatical forms of a word and sometimes derivationally related forms of a word to a common base (root or stem) form like reducing noun, adjective, verb, adverb etc. to its base form. The stem needs not to be identical to the morphological root of the word; it is usually sufficient that related words map to the same stem, even if this stem is not in itself a valid root. As in other languages; there is a need for an effective stemming algorithm for the indexing and retrieval of Arabic documents while the Arabic stemming algorithms are not widely available.

The past years have seen a rapid development in the area of image compression techniques, mainly due to the need of fast and efficient techniques for storage and transmission of data among individuals. Compression is the process of representing the data in a compact form rather than in its original or incompact form. In this paper, integer implementation of Arithmetic Coding (AC) and Discreet Cosine Transform (DCT) were applied to colored images. The DCT was applied using the YCbCr color model. The transformed image was then quantized with the standard quantization tables for luminance and chrominance. The quantized coefficients were scanned by zigzag scan and the output was encoded using AC. The results showed a decent compression ratio