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Features Selection for Intrusion Detection System Based on DNA Encoding
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Intrusion detection systems detect attacks inside computers and networks, where the detection of the attacks must be in fast time and high rate. Various methods proposed achieved high detection rate, this was done either by improving the algorithm or hybridizing with another algorithm. However, they are suffering from the time, especially after the improvement of the algorithm and dealing with large traffic data. On the other hand, past researches have been successfully applied to the DNA sequences detection approaches for intrusion detection system; the achieved detection rate results were very low, on other hand, the processing time was fast. Also, feature selection used to reduce the computation and complexity lead to speed up the system. A new features selection method is proposed based on DNA encoding and on DNA keys positions. The current system has three phases, the first phase, is called pre-processing phase, which is used to extract the keys and their positions, the second phase is training phase; the main goal of this phase is to select features based on the key positions that gained from pre-processing phase, and the third phase is the testing phase, which classified the network traffic records as either normal or attack by using specific features. The performance is calculated based on the detection rate, false alarm rate, accuracy, and also on the time that include both encoding time and matching time. All these results are based on using two or three keys, and it is evaluated by using two datasets, namely, KDD Cup 99, and NSL-KDD. The achieved detection rate, false alarm rate, accuracy, encoding time, and matching time for all corrected KDD Cup records (311,029 records) by using two and three keys are equal to 96.97, 33.67, 91%, 325, 13 s, and 92.74, 7.41, 92.71%, 325 and 20 s, respectively. The results for detection rate, false alarm rate, accuracy, encoding time, and matching time for all NSL-KDD records (22,544 records) by using two and three keys are equal to 89.34, 28.94, 81.46%, 20, 1 s and 82.93, 11.40, 85.37%, 20 and 1 s, respectively. The proposed system is evaluated and compared with previous systems and these comparisons are done based on encoding time and matching time. The outcomes showed that the detection results of the present system are faster than the previous ones.

Scopus
Publication Date
Sun Jan 01 2017
Journal Name
Spe
SPE-188966-MS: Drilling problems detection in Basrah oil fields using smartphones
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Scopus
Publication Date
Mon Apr 19 2010
Journal Name
Computer And Information Science
Quantitative Detection of Left Ventricular Wall Motion Abnormality by Two-Dimensional Echocardiography
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Echocardiography is a widely used imaging technique to examine various cardiac functions, especially to detect the left ventricular wall motion abnormality. Unfortunately the quality of echocardiograph images and complexities of underlying motion captured, makes it difficult for an in-experienced physicians/ radiologist to describe the motion abnormalities in a crisp way, leading to possible errors in diagnosis. In this study, we present a method to analyze left ventricular wall motion, by using optical flow to estimate velocities of the left ventricular wall segments and find relation between these segments motion. The proposed method will be able to present real clinical help to verify the left ventricular wall motion diagnosis.

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Crossref
Publication Date
Tue Jun 30 2020
Journal Name
Iraq Journal Of Market Research And Consumer Protection
DETECTION OF HEAVY METALS POLLUTION INTYPES OF MILK SAMPLES IN BAGHDAD MARKETS
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Publication Date
Wed May 01 2019
Journal Name
Iraqi Journal Of Science
Detection of Sabin Poliovirus Serotypes among Vaccinated Iraqi Children with AFP Syndrom
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Poliomyelitis is a viral disease caused by an enterovirus known as poliovirus and is well known for its role in causing paralysis in children, the virus is only infectious in humans and does pass into the central nervous system and cause various degrees of paralysis, poliovirus passes newcomer disabuse of suppliant to alms-man thumb the fecal-oral route infected persons still shed the virus in their stool allowing the virus to infect others. The main aim of this study was isolating and differentiation of poliovirus strains (Sabin virus) from the stool samples of children received polio vaccine TOPV and suffering from acute flaccid paralysis.

In this study use the cell culture system as the

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Publication Date
Sat Apr 01 2023
Journal Name
Iop Conference Series: Earth And Environmental Science
Detection of Mineral and Microbial Contaminants in some Types of Imported Meat
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Abstract<p>The main target of the current study is to investigate the microbial content and mineral contaminants of the imported meat available in the city of Baghdad and to ensure that it is free from harmful bacteria, safe and it compliances with the Iraqi standard specifications. Some trace mineral elements such as (Iron, Copper, Lead, and Cadmium) were also estimated, where 10 brands of these meats were collected. Bacteriological tests were carried out which included (total bacterial count, <italic>Staphylococcus</italic> bacteria, <italic>Salmonella</italic> bacteria). The results showed highest number of total bacterial count 13×10<sup>5</sup> CFU/g in F8 bra</p> ... Show More
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Publication Date
Tue Jan 01 2019
Journal Name
Advances In Public Health
Detection of Antibiotics in Drinking Water Treatment Plants in Baghdad City, Iraq
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Persistence of antibiotics in the aquatic environment has raised concerns regarding their potential influence on potable water quality and human health. This study analyzes the presence of antibiotics in potable water from two treatment plants in Baghdad City. The collected samples were separated using a solid-phase extraction method with hydrophilic-lipophilic balance (HLB) cartridge before being analyzed. The detected antibiotics in the raw and finished drinking water were analyzed and assessed using high-performance liquid chromatography (HPLC), with fluorometric detector and UV detector. The results confirmed that different antibiotics including fluoroquinolones andB-lactams were detected in the raw an

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Publication Date
Tue Sep 01 2009
Journal Name
Al-khwarizmi Engineering Journal
Analysis of Wave Propagation in Detection of Aorta Dieses Using Lumps Analysis
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In this paper a theoretical attempt is made to determine whether changes in the aorta diameter at different location along the aorta can be detected by brachial artery measurement.  The aorta is divided into six main parts, each part with 4 lumps of 0.018m length. It is assumed that a desired section of the aorta has a radius change of 100,200, 500%. The results show that there is a significant change for part 2 (lumps 5-8) from the other parts. This indicates that the nearest position to the artery gives the significant change in the artery wave pressure while other parts of the aorta have a small effect.

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Publication Date
Mon Dec 28 2020
Journal Name
The Iraqi Journal Of Veterinary Medicine
Serological and Molecular Phylogenetic Detection of Coxiella burnetii in Lactating Cows, Iraq
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This study is carried out to investigate the prevalence of Coxiella burnetii (C. burnetii) infections in cattle using an enzyme-linked immunosorbent assay (ELISA) and polymerase chain reaction (PCR) assay targeting IS1111A transposase gene. A total of 130 lactating cows were randomly selected from different areas in Wasit province, Iraq and subjected to blood and milk sampling during the period extended between November 2018 and May 2019. ELISA and PCR tests revealed that 16.15% and 10% of the animals studied were respectively positive. Significant correlations (P<0.05) were detected between the positive results and clinical data. Two positive PCR products were analyzed phylogenetically, named as C. burnetii IQ-No.5 and C. burnet

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Publication Date
Tue Jun 20 2023
Journal Name
Baghdad Science Journal
Detection of Autism Spectrum Disorder Using A 1-Dimensional Convolutional Neural Network
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Autism Spectrum Disorder, also known as ASD, is a neurodevelopmental disease that impairs speech, social interaction, and behavior. Machine learning is a field of artificial intelligence that focuses on creating algorithms that can learn patterns and make ASD classification based on input data. The results of using machine learning algorithms to categorize ASD have been inconsistent. More research is needed to improve the accuracy of the classification of ASD. To address this, deep learning such as 1D CNN has been proposed as an alternative for the classification of ASD detection. The proposed techniques are evaluated on publicly available three different ASD datasets (children, Adults, and adolescents). Results strongly suggest that 1D

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Scopus (19)
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Publication Date
Wed Jul 10 2024
Journal Name
The Open Neuroimaging Journal
The Efficacy of Bedside Chest Ultrasound in the Detection of Traumatic Pneumothorax
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Background

Chest X-rays have long been used to diagnose pneumothorax. In trauma patients, chest ultrasonography combined with chest CT may be a safer, faster, and more accurate approach. This could lead to better and quicker management of traumatic pneumothorax, as well as enhanced patient safety and clinical results.

Aim

The purpose of this study was to assess the efficacy and utility of bedside US chest in identifying traumatic pneumothorax and also its capacity to estimate the extent of the lesion in comparison to the gold standard modality chest computed tomography.

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