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joe-2119
Enhancement of the Detection of the TCP SYN Flooding (DDoS) Attack
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The major of DDoS attacks use TCP protocol and the TCP SYN flooding attack is the most common one among them. The SYN Cookie mechanism is used to defend against the TCP SYN flooding attack. It is an effective defense, but it has a disadvantage of high calculations and it doesn’t differentiate spoofed packets from legitimate packets. Therefore, filtering the spoofed packet can effectively enhance the SYN Cookie activity. Hop Count Filtering (HCF) is another mechanism used at the server side to filter spoofed packets. This mechanism has a drawback of being not a perfect and final solution in defending against the TCP SYN flooding attack. An enhanced mechanism of Integrating and combining the SYN Cookie with Hop Count Filtering (HCF) mechanism is proposed to protect the server from TCP SYN flooding. The results show that the defense against SYN flood DDoS attack is enhanced, since the availability of legitimate packets is increased and the time of SYN Cookie activity is delayed.

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Publication Date
Mon Sep 30 2024
Journal Name
Iraqi Journal Of Science
Overlapping Structure Detection in Protein-Protein Interaction Networks Using a Modified Version of Particle Swarm Optimization
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In today's world, the science of bioinformatics is developing rapidly, especially with regard to the analysis and study of biological networks. Scientists have used various nature-inspired algorithms to find protein complexes in protein-protein interaction (PPI) networks. These networks help scientists guess the molecular function of unknown proteins and show how cells work regularly. It is very common in PPI networks for a protein to participate in multiple functions and belong to many complexes, and as a result, complexes may overlap in the PPI networks. However, developing an efficient and reliable method to address the problem of detecting overlapping protein complexes remains a challenge since it is considered a complex and har

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Publication Date
Tue Sep 30 2014
Journal Name
J Clin Biomed Sci
Detection of EGFR Mutations in Bronchial Wash from Iraqi patients with nonsmall Cell Lung Cancer (NSCLC)
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Background: Non-small cell lung cancer (NSCLC) is caused of 85% of all lung cancers. Among the most important factors for lung tumor growth and proliferation are the tyrosine kinase receptors that coded by the epidermal growth factor recep-tor (EGFR) gene. Activation of EGFR ultimately leads to developing of lung cancer. The present study was undertaken with an objective to detect EGFR mutations in bronchial wash from Iraqi patients with NSCLC before treatment. Methods: DNA was extracted from bronchial wash samples collected from 50 patients with NSCLC by using a Qiamp DNA Mini Kit (Qiagen, Hilden, Germany). Then, EGFR mutations were determined by using real-time RCR combined with two technologies, Amplification Refractory Mutation System (

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Publication Date
Sun Jan 01 2023
Journal Name
Iraqi Journal Of Biotechnology
Molecular Detection of Candida spp. Isolated from Female Patients Infected with COVID-19 in Baghdad City
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Abstract: Coronavirus disease 2019 (COVID-19) is an infectious disease with severe acute respiratory syndrome and first recognized in Wuhan, China, and it has since spread to the world, resulting in the coronavirus pandemic to 2020. The present study aimed to evaluate Molecular study of some types of vaginal fungi isolated from recovered women from Covid-19 in Baghdad governorate. The study was conducted on 213 samples collected between December 2021 and March 2022, where the number of positive samples reached 188 with percentage 88.26%, while the number of negative samples reached 25 with percentage 11.73% by taking vaginal swabs from various female patients in Al- Kadhimiya Teaching Hospital. Three of Candida spp. were isolated: Candida a

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Publication Date
Mon Sep 15 2014
Journal Name
Journal Of Clinical And Biomedical Sciences
Detection of EGFR Mutations in Bronchial Wash from Iraqi patients with nonsmall Cell Lung Cancer (NSCLC)
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Background: Non-small cell lung cancer (NSCLC) is caused of 85% of all lung cancers. Among the most important factors for lung tumor growth and proliferation are the tyrosine kinase receptors that coded by the epidermal growth factor recep-tor (EGFR) gene. Activation of EGFR ultimately leads to developing of lung cancer. The present study was undertaken with an objective to detect EGFR mutations in bronchial wash from Iraqi patients with NSCLC before treatment. Methods: DNA was extracted from bronchial wash samples collected from 50 patients with NSCLC by using a Qiamp DNA Mini Kit (Qiagen, Hilden, Germany). Then, EGFR mutations were determined by using real-time RCR combined with two technologies, Amplification Refractory Mutation System (

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Publication Date
Mon May 01 2017
Journal Name
Journal Of Stored Products Research
Detection and prediction of Sitophilus oryzae infestations in triticale via visible and near-infrared spectral signatures
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Triticale is a hybrid of wheat and rye grown for use as animal feed. In Florida, due to its soft coat, triticale is highly vulnerable to Sitophilus oryzae L. (rice weevil) and there is interest in development of methods to detect early-instar larvae so that infestations can be targeted before they become economically damaging. The objective of this study was to develop prediction models of the infestation degree for triticale seed infested with rice weevils of different growth stages. Spectral signatures were tested as a method to detect rice weevils in triticale seed. Groups of seeds at 11 different levels (degrees) of infestation, 0–62%, were obtained by combining different ratios of infested and uninfested seeds. A spectrophotometer wa

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Publication Date
Fri May 03 2024
Journal Name
Optical And Quantum Electronics
Design and analysis of a dual-core PCF biosensor based on SPR for cancerous cells detection
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Publication Date
Mon Jun 19 2023
Journal Name
Journal Of Engineering
Detection and Removal of Polycyclic Aromatic Hydrocarbon from Selected Areas in Tigris River in Baghdad City
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Aromatic hydrocarbons present in Iraqi national surface water were believed to be raised principally from combustion of various petroleum products, industrial processes and transport output and their precipitation on surface water.
Polycyclic aromatic hydrocarbons (PAHs) were included in the priority pollutant list due to their toxic and carcinogenic nature. The concern about water contamination and the consequent human exposure have encouraged the development of new methods for
PAHs detection and removal.
PAHs, the real contaminants of petroleum matter, were detected in selected sites along Tigris River within Baghdad City in summer and winter time, using Shimadzu high performance liquid chromatography (HPLC) system.
Analysi

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Publication Date
Sun Oct 01 2017
Journal Name
Agriculture (pol'nohospodárstvo)
Molecular detection of ‘<i>Candidatus</i> Phytoplasma australasia’ and ‘<i>Ca.</i> P. cynodontis’ in Iraq
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Abstract<p>The association of phytoplasma was investigated in symptomatic tomato (<italic>Solanum lycopersicum</italic> L.), eggplant (<italic>Solanum melongen</italic> L.), mallow (<italic>Malva</italic> spp.) and Bermuda grass (<italic>Cynodon dactylon</italic> L.) plants exhibiting witches’ broom and white leaf diseases, respectively. Total DNA was extracted from tomato (n=3), eggplant (n=2), mallow (n=2) and Bermuda grass (n=8) samples. Direct polymerase chain reaction (PCR) was performed using P1/P7 primer set, then PCR products were sequenced. Sequences obtained from tomato, eggplant and mallow shared 99% maximum nucleotide identity with phytoplasm</p> ... Show More
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Publication Date
Sun Jul 01 2018
Journal Name
Computers And Electronics In Agriculture
Detection of charcoal rot (Macrophomina phaseolina) toxin effects in soybean (Glycine max) seedlings using hyperspectral spectroscopy
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Publication Date
Wed Nov 30 2022
Journal Name
Iraqi Journal Of Science
Breast Cancer Detection using Decision Tree and K-Nearest Neighbour Classifiers
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      Data mining has the most important role in healthcare for discovering hidden relationships in big datasets, especially in breast cancer diagnostics, which is the most popular cause of death in the world. In this paper two algorithms are applied that are decision tree and K-Nearest Neighbour for diagnosing Breast Cancer Grad in order to reduce its risk on patients. In decision tree with feature selection, the Gini index gives an accuracy of %87.83, while with entropy, the feature selection gives an accuracy of %86.77. In both cases, Age appeared as the  most effective parameter, particularly when Age<49.5. Whereas  Ki67  appeared as a second effective parameter. Furthermore, K- Nearest Neighbor is based on the minimu

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