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Genetic Algorithm based Clustering for Intrusion Detection
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Clustering algorithms have recently gained attention in the related literature since
they can help current intrusion detection systems in several aspects. This paper
proposes genetic algorithm (GA) based clustering, serving to distinguish patterns
incoming from network traffic packets into normal and attack. Two GA based
clustering models for solving intrusion detection problem are introduced. The first
model coined as handles numeric features of the network packet, whereas
the second one coined as concerns all features of the network packet.
Moreover, a new mutation operator directed for binary and symbolic features is
proposed. The basic concept of proposed mutation operator depends on the most
frequent value of the features using mode operator. The proposed GA-based
clustering models are evaluated using Network Security Laboratory-Knowledge
Discovery and Data mining (NSL-KDD) benchmark dataset. Also, it is compared
with two baseline methods namely k-means and k-prototype to judge their
performance and to confirm the value of the obtained clustering structures. The
experiments demonstrate the effectiveness of the proposed models for intrusion
detection problem in which and models outperform the two baseline
methods in accuracy ( ), detection rate ( ) and true negative rate ( ).
Moreover, the results prove the positive impact of the proposed mutation operator to
enhance the strength of model in all evaluation metrics. It successfully attains
6.4, 5.463 and 3.279 percentage of relative improvement in over and
baseline models respectively.

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Publication Date
Mon Dec 31 2018
Journal Name
Iraqi Journal Of Market Research And Consumer Protection
STUDYING THE EFFECT OF Proteinase K AND α-Amylase ON INHIBITION OF Staphylococcus aureus AND Klebsiella pneumoniae BIOFILM ISOLATE FROM URINARY TRACT INFECTION.: STUDYING THE EFFECT OF Proteinase K AND α-Amylase ON INHIBITION OF Staphylococcus aureus AND Klebsiella pneumoniae BIOFILM ISOLATE FROM URINARY TRACT INFECTION.
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The current study aimed to investigate the viability of biofilm formation klebsilla pneumoniae and Staphylococcus aureus. 440 urine samples were collected from patients suffering from urinary tract infection (UTI) from those who were admitted and visitors to Al-Ramadi Teaching Hospital, Al-Yarmouk Teaching Hospital, Al-Ramadi Teaching Hospital for women and children and , Teaching Laboratories in the Medical City for both genders for a period extended from 5 July, 2017 to 10 October, 2017. Samples were diagnosed by culturing them on a selective media and by biochemical testes , also, diagnosis was ensured by using VITEK-2 compact system. Results showed that K.pneumoniae isolation ratio was 17.1%(68) and S.aureus ratio was 13.1%(52). Thei

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Publication Date
Wed Feb 02 2022
Journal Name
Iraqi Journal Of Science
The influence of some amino acids,vitamins and anti-inflammatory drugs on activity of chondroitinase produced by Proteus vulgaris caused urinary tract infection
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Two hundred and ten specimens include urine, blood and ear swab were collected from different hospitals in Baghdad city; 85 (40%) isolates were diagnosed as Proteus spp. with (82%), (11.7%) and (5.8%) represented in urine, blood and ear swab specimens respectively. PCR technique was shown 30 (35.3%) isolates were positive for specific Urease C gene that used in rapid detection of Proteus vulgaris. The ability for chondritinase production was checked invetro and invevo, 24 (80%) isolates of P. vulgaris were showed ablity to chondritinase production and the isolate (p17) has higher enzyme activity value to (175.2U/ml). The Chondroitinase was purified by three short steps only included precipitate with 60% saturated of ammonium sulfate, dia

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Publication Date
Sun Jun 25 2023
Journal Name
Iraqi Journal Of Agricultural Sciences
BREEDING POTENTIAL OF RICE GENOTYPES IN TWO AGROCLIMATIC CONDITIONS OF SULAIMANI - KURDISTAN REGION - IRAQ
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This study was aimed to investigate the genetic variability of 26 rice genotypes and evaluation at two locations in Sulaimani governorate, Gaba and Chawtan which were completely different in their environmental condition during the season of 2019. The performances of the genotypes were analyzed at both locations as well as the average of both. Simple coefficients of correlation were used to assess the grain yield components and their relationships. Path analysis was used to determine the direct and indirect effects of such components on grain yield plant-1. The genotypes were grouped based on the agro-morphological features using cluster analysis. Almost all of the traits at both locat

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Publication Date
Sat Jan 30 2021
Journal Name
Iraqi Journal Of Science
A Metaheuristic Approach to the C1S Problem
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Given a binary matrix, finding the maximum set of columns such that the resulting submatrix has the Consecutive Ones Property (C1P) is called the Consecutive Ones Submatrix (C1S) problem. There are solution approaches for it, but there is also a room for improvement. Moreover, most of the studies of the problem use exact solution methods. We propose an evolutionary approach to solve the problem. We also suggest a related problem to C1S, which is the Consecutive Blocks Minimization (CBM). The algorithm is then performed on real-world and randomly generated matrices of the set covering type.  

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Publication Date
Sat Jul 01 2023
Journal Name
The Egyptian Journal Of Hospital Medicine
Production, Extraction, and Purification of An Extracellular Melanin Pigment from Clinically Isolated Pseudomonas aeruginosa
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Introduction: Melanin is a high-molecular weight pigment produced through the oxidative polymerization of phenolic or indolic compounds and plays a perfect role in UV-light shielding, as well as in photoprotection. Among biopolymers, melanin is unique in many aspects. This study is designed to screen Production, extraction and characterizes of an extracellular melanin pigment from clinically isolated P. aeruginosa. Objective: The aim of the current study is isolation and diagnosis of P.aeruginosa using vitek-2 compact system and screening the ability to produce melanin and characterization of extracted melanin by UV-vis, FTIR, XRD and SEM. Materials and methods: the samples swab inoculated on cetrimide agar as selective media and incubated

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Publication Date
Mon Jan 30 2023
Journal Name
Iraqi Journal Of Science
Scene Text Recognition: A Review
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      The problem of text recognition and its applicability as part of images captured in the wild has gained a significant attention from the computer vision community in recent years. In contrast to the recognition of printed documents, scene text recognition is a difficult problem. Contrary to recognition of printed documents, recognizing a scene text is a challenging problem. Many researches focus on the problem of recognizing text extracted from natural scene images. Significant attempts have been made to address this problem in recent past. However, many of these attempts work on utilizing availability of strong context, which naturally limits the dictionary. This paper presents a review of recent papers related to scene text

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Publication Date
Wed Feb 16 2022
Journal Name
Iraqi Journal Of Science
Colord Image White Cracks In-Painting Method
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The gaps and cracks in an image result from different reasons and affect the images. There are various methods concerning gaps replenishment along with serious efforts and proposed methodologies to eliminate cracks in diverse tendencies. In the current research work a color image white crack in-painting system has been introduced. The proposed inpainting system involved on two algorithms. They are Linear Gaps Filling (LGF) and the Circular Gaps Filling (CGF). The quality of output image depends on several effects such as: pixels tone, the number of pixels in the cracked area and neighborhood of cracked area and the resolution the image. The quality of the output images of two methods (linear method: average Peak Signal to Noise Ratio (PS

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Publication Date
Tue Sep 25 2018
Journal Name
Iraqi Journal Of Science
Effect of Successive Convolution Layers to Detect Gender
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Image classification can be defined as one of the most important tasks in the area of machine learning. Recently, deep neural networks, especially deep convolution networks, have participated greatly in end-to-end learning which reduce need for human designed features in the image recognition like Convolution Neural Network. It is offers the computation models which are made up of several processing layers for learning data representations with several abstraction levels. In this work, a pre-trained deep CNN is utilized according to some parameters like filter size, no of convolution, pooling, fully connected and type of activation function which includes 300 images for training and predict 100 image gender using probability measures. Re

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Publication Date
Fri Nov 24 2023
Journal Name
Iraqi Journal Of Science
Segmenting the Dermatological Diseases Images by Developing the Range Operator
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Medical image segmentation is a frequent processing step in image medical understanding and computer aided diagnosis. In this paper, development of range operator in image segmentation is proposed depending on dermatology infection. Three different block sizes have been utilized on the range operator and the developed ones to enhance the behavior of the segmentation process of medical images. To exploit the concept of range filtering, the extraction of the texture content of medical image is proposed. Experiment is conducted on different medical images and textures to prove the efficacy of our proposed filter was good results.

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Publication Date
Fri Aug 31 2012
Journal Name
Al-khwarizmi Engineering Journal
Design a Security Network System against Internet Worms
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 Active worms have posed a major security threat to the Internet, and many research efforts have focused on them. This paper is interested in internet worm that spreads via TCP, which accounts for the majority of internet traffic. It presents an approach that use a hybrid solution between two detection algorithms: behavior base detection and signature base detection to have the features of each of them. The aim of this study is to have a good solution of detecting worm and stealthy worm with the feature of the speed. This proposal was designed in distributed collaborative scheme based on the small-world network model to effectively improve the system performance.

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