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The Antimicrobial Activity of Melanin-Mediated Synthesis of Silver Nanoparticles
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Background: Nowadays, the environmentally friendly procedures must be developed to avoid using harmful compounds in synthesis methods. Their increase interest in creating and researching silver nanoparticles (AgNPs) because of their numerous applications in many fields especially medical fields such as burn, wound healing, dental and bone implants, antibacterial, viral, fungal, and arthropodal activities. Biosynthesis of nanoparticles mediated pigments have been widely used as antimicrobial agent against microorganisms. Silver nanoparticles had synthesized by using melanin from locally isolate Pseudomonas aeruginosa, and used as antimicrobial activity against pathogenic microorganisms. Aim of the study: Isolation of Pseudomonas aeruginosa that produce melanin and extraction of melanin. Synthesis and characterization silver nanoparticle and study of the antimicrobial activity of silver nanoparticles in the presence of melanin against UTI pathogens. Materials and methods: The samples swab inoculated on cetrimide agar as selective media and incubated aerobically for 24 hours at 37 °C. Used nutrient agar with nutrient broth supplement with 1% tyrosine for screening for melanin production by P. aeruginosa isolates,silver nanoparticles synthesis from P. aeruginosa was done according to biological method and was characterized with AFM, UV-Visible, XRD, FTIR and FE-SEM. Agar well diffusion method was used to examine the effect of combination against UTI pathogens. Results: The synergistic effects of AgNPs and melanin were evaluated to compare between the two treatments (silver nanoparticles alone and combination of silver nanoparticles and melanin). The results revealed that the combination showed the highest antimicrobial activity in compare with silver nanoparticles alone.

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Publication Date
Fri Sep 23 2022
Journal Name
Specialusis Ugdymas
Intrusion Detection System Techniques A Review
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With the high usage of computers and networks in the current time, the amount of security threats is increased. The study of intrusion detection systems (IDS) has received much attention throughout the computer science field. The main objective of this study is to examine the existing literature on various approaches for Intrusion Detection. This paper presents an overview of different intrusion detection systems and a detailed analysis of multiple techniques for these systems, including their advantages and disadvantages. These techniques include artificial neural networks, bio-inspired computing, evolutionary techniques, machine learning, and pattern recognition.

Publication Date
Thu Jul 01 2021
Journal Name
Iraqi Journal Of Science
Vehicles Detection System at Different Weather Conditions
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The importance of efficient vehicle detection (VD) is increased with the expansion of road networks and the number of vehicles in the Intelligent Transportation Systems (ITS). This paper proposes a system for detecting vehicles at different weather conditions such as sunny, rainy, cloudy and foggy days. The first step to the proposed system implementation is to determine whether the video’s weather condition is normal or abnormal. The Random Forest (RF) weather condition classification was performed in the video while the features were extracted for the first two frames by using the Gray Level Co-occurrence Matrix (GLCM). In this system, the background subtraction was applied by the mixture of Gaussian 2 (MOG 2) then applying a number

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Publication Date
Wed Dec 30 2020
Journal Name
Iraqi Journal Of Science
DNA Encoding for Misuse Intrusion Detection System based on UNSW-NB15 Data Set
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Recent researches showed that DNA encoding and pattern matching can be used for the intrusion-detection system (IDS), with results of high rate of attack detection. The evaluation of these intrusion detection systems is based on datasets that are generated decades ago. However, numerous studies outlined that these datasets neither inclusively reflect the network traffic, nor the modern low footprint attacks, and do not cover the current network threat environment. In this paper, a new DNA encoding for misuse IDS based on UNSW-NB15 dataset is proposed. The proposed system is performed by building a DNA encoding for all values of 49 attributes. Then attack keys (based on attack signatures) are extracted and, finally, Raita algorithm is app

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Publication Date
Thu Jan 20 2022
Journal Name
Webology
Hybrid Intrusion Detection System based on DNA Encoding, Teiresias Algorithm and Clustering Method
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Until recently, researchers have utilized and applied various techniques for intrusion detection system (IDS), including DNA encoding and clustering that are widely used for this purpose. In addition to the other two major techniques for detection are anomaly and misuse detection, where anomaly detection is done based on user behavior, while misuse detection is done based on known attacks signatures. However, both techniques have some drawbacks, such as a high false alarm rate. Therefore, hybrid IDS takes advantage of combining the strength of both techniques to overcome their limitations. In this paper, a hybrid IDS is proposed based on the DNA encoding and clustering method. The proposed DNA encoding is done based on the UNSW-NB15

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Publication Date
Fri Dec 30 2022
Journal Name
Iraqi Journal Of Science
An Improved Outlier Detection Model for Detecting Intrinsic Plagiarism
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     In the task of detecting intrinsic plagiarism, the cases where reference corpus is absent are to be dealt with. This task is entirely based on inconsistencies within a given document. Detection of internal plagiarism has been considered as a classification problem. It can be estimated through taking into consideration self-based information from a given document.

The core contribution of the work proposed in this paper is associated with the document representation. Wherein, the document, also, the disjoint segments generated from it, have been represented as weight vectors demonstrating their main content. Where, for each element in these vectors, its average weight has been considered instead of its frequency.

Th

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Publication Date
Sun Jan 16 2022
Journal Name
Iraqi Journal Of Science
A Multi-Objective Evolutionary Algorithm based Feature Selection for Intrusion Detection
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Nowad ays, with the development of internet communication that provides many facilities to the user leads in turn to growing unauthorized access. As a result, intrusion detection system (IDS) becomes necessary to provide a high level of security for huge amount of information transferred in the network to protect them from threats. One of the main challenges for IDS is the high dimensionality of the feature space and how the relevant features to distinguish the normal network traffic from attack network are selected. In this paper, multi-objective evolutionary algorithm with decomposition (MOEA/D) and MOEA/D with the injection of a proposed local search operator are adopted to solve the Multi-objective optimization (MOO) followed by Naï

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Publication Date
Fri Dec 08 2023
Journal Name
Iraqi Journal Of Science
Intrusion Detection Approach Based on DNA Signature
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Intrusion-detection systems (IDSs) aim at detecting attacks against computer systems and networks or, in general, against information systems. Most of the diseases in human body are discovered through Deoxyribonucleic Acid (DNA) investigations. In this paper, the DNA sequence is utilized for intrusion detection by proposing an approach to detect attacks in network. The proposed approach is a misuse intrusion detection that consists of three stages. First, a DNA sequence for a network traffic taken from Knowledge Discovery and Data mining (KDD Cup 99) is generated. Then, Teiresias algorithm, which is used to detect sequences in human DNA and assist researchers in decoding the human genome, is used to discover the Shortest Tandem Repeat (S

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Publication Date
Sun Sep 03 2017
Journal Name
Baghdad Science Journal
Gravity Field Interpretation for Major Fault Depth Detection in a Region Located SW- Qa’im / Iraq
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This research deals with the qualitative and quantitative interpretation of Bouguer gravity anomaly data for a region located to the SW of Qa’im City within Anbar province by using 2D- mapping methods. The gravity residual field obtained graphically by subtracting the Regional Gravity values from the values of the total Bouguer anomaly. The residual gravity field processed in order to reduce noise by applying the gradient operator and 1st directional derivatives filtering. This was helpful in assigning the locations of sudden variation in Gravity values. Such variations may be produced by subsurface faults, fractures, cavities or subsurface facies lateral variations limits. A major fault was predicted to extend with the direction NE-

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Publication Date
Sun Feb 10 2019
Journal Name
Iraqi Journal Of Physics
A nonlinear edge –preserving smoothing filter for edge detection on color and gray satellite images
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A nonlinear filter for smoothing color and gray images
corrupted by Gaussian noise is presented in this paper. The proposed
filter designed to reduce the noise in the R,G, and B bands of the
color images and preserving the edges. This filter applied in order to
prepare images for further processing such as edge detection and
image segmentation.
The results of computer simulations show that the proposed
filter gave satisfactory results when compared with the results of
conventional filters such as Gaussian low pass filter and median filter
by using Cross Correlation Coefficient (ccc) criteria.

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Publication Date
Mon Oct 30 2023
Journal Name
Iraqi Journal Of Science
An Evolutionary-Based Mutation With Functional Annotation to Identify Protein Complexes Within PPI Networks
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     The research deals with an evolutionary-based mutation with functional annotation to identify protein complexes within PPI networks. An important field of research in computational biology is the difficult and fundamental challenge of revealing complexes in protein interaction networks. The complex detection models that have been developed to tackle challenges are mostly dependent on topological properties and rarely use the biological  properties of PPI networks. This research aims to push the evolutionary algorithm to its maximum by employing gene ontology (GO) to communicate across proteins based on biological information similarity for direct genes. The outcomes show that the suggested method can be utilized to improve the

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