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An Improvement to Face Detection Algorithm for Non-Frontal Faces
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Publication Date
Mon Jun 17 2019
Journal Name
Ibn Al-haitham Journal For Pure And Applied Sciences
Determination of Manganese (II) using Flow Injection Analysis with Chemiluminescence detection
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The determination of manganese (II) using flow injection analysis with chemiluminescence detection was investigated. Mn2+ in sample solutions injected into a carrier stream of sodium bismuthate (NaBiO3) were oxidised to form MnO4- ions which were capable of producing luminescence after reaction with luminol/KOH in a flow cell. The linear range of the system is from 20 to 80 mg/L with a detection limit 8 mg/L. The proposed system is suitable for determination of Mn2+ in steel alloys after dissolution, filtration and dilution at a rate of approximately 60 samples per hour with a relative standard deviation (RSD)1.2%. Statistical comparison between the proposed system and standard spectrophotometric method revealed that there is no signific

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Publication Date
Sun Apr 30 2023
Journal Name
Iraqi Journal Of Science
Detection of some heavy metals and bacterial contamination in canned vegetables
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In this paper, thirty six samples of canned vegetables were collected randomly from
different markets in Baghdad city from October 2013 till March 2014. The study
includes identifying the concentration of some heavy metals (lead, nickel, zinc and iron)
by flameless atomic absorption spectrophotometery. It was found that the higher
concentrations of heavy metals in canned vegetables, was lead 1.179 ppm in olive,
nickel 0.9078 ppm in olive, while zinc 10.143 ppm green peas and iron 90.601ppm in
white asparagus; but the lower concentrations represents with lead 0.0021 ppm in green
asparagus, nickel 0.0202 ppm in mushroom, while zinc 0.528 ppm in white asparagus
and iron 4.061 ppm in green peas. Canned food has been r

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Publication Date
Tue May 23 2023
Journal Name
Journal Of Engineering
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) mech

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Publication Date
Sat Jun 03 2023
Journal Name
Iraqi Journal Of Science
Detection of antibiotics resistance genes in clinical isolates of Klebsiella pneumonia
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Total of 46 isolates of Klebsiella pneumoniae were collected from patients attending (Al-Yarmook Hospital and Education Labs / medical city), and isolates were re-identified, depending on morphology and biochemical tests . Disk diffusion method was employed to determine antibiotic susceptibility of forty six isolates by using eleven antibiotics .The results revealed the sensitivity of six isolates (9.3%) to Imipenem and Meropenem . On the other hand the isolates were showed 23.9% resistant against Ciprofloxacin, while some isolates shown higher resistant against several antimicrobial agents such as 65.2%, 69.0% for Amikacin and Cefepime consequently , 71.1%, 71.7 % for Amoxicillin -Clauvulanic acid and Gentamicin and 82.6% against Pipera

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Publication Date
Tue Dec 11 2018
Journal Name
Iraqi National Journal Of Nursing Specialties
Detection of Hypertension among Cardiac Diseases Inpatients at Kirkuk City Hospitals
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Objectives of the study: The main objective of the study is to assess the prevalence of hypertension among
cardiac diseases patients and to fiend out relation ship between hypertension and cardiovascular diseases.
Methodology: A descriptive study, using interviewer and questionnaire technique was conducted on cardiac
diseases inpatients of clinic unite at Kirkuk and Azady hospitals from 17th ,June ,2012 to 1st, March , 2013.
Non – probability (purposive) sample of (148) adult patients, (81) females and (67) males with heart disease are
selected from inpatients of clinic unite at Kirkuk and Azady hospitals at kirkuk city. Questionnaire was
developed to assess the items which are related to heart disease patient's (Dise

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Publication Date
Fri Jun 24 2022
Journal Name
Iraqi Journal Of Science
Detection of Genetic Polymorphism in Iraqi Barley using SSR-PCR Analysis
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Nine Iraqi varieties of barley (Hordeum vulgare L.) has been differentiated and diagnosed using simple sequence repeat markers to detect their genetic polymorphism. Six SSR primers were used for genetic screening of barley samples (IPA 265, IPA 99, Tuwaitha, Hitra, Rayhan, Shuaa, Bawadi, Samir and Al_khair). These primers generated total PCR product (11) bands divided to 8 polymorphic bands 3 monomorphic bands. the percentage of polymorphism 80% ranged between (50-100%). a mean value of polymorphic band per primer was 1.6 . these primers produced amplification fragment at Molecular weight between 75-900 bp. One unique band was generated at size 200bp, this band can be used as a DNA profiling of all studied genotypes. These results appear

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Publication Date
Mon Dec 14 2020
Journal Name
2020 13th International Conference On Developments In Esystems Engineering (dese)
Anomaly Based Intrusion Detection System Using Hierarchical Classification and Clustering Techniques
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With the rapid development of computers and network technologies, the security of information in the internet becomes compromise and many threats may affect the integrity of such information. Many researches are focused theirs works on providing solution to this threat. Machine learning and data mining are widely used in anomaly-detection schemes to decide whether or not a malicious activity is taking place on a network. In this paper a hierarchical classification for anomaly based intrusion detection system is proposed. Two levels of features selection and classification are used. In the first level, the global feature vector for detection the basic attacks (DoS, U2R, R2L and Probe) is selected. In the second level, four local feature vect

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Scopus (2)
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Publication Date
Fri Jan 20 2023
Journal Name
Ibn Al-haitham Journal For Pure And Applied Sciences
Automatic Detection and Recognition of Car Plates Based on Cascade Classifier
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The study consists of video clips of all cars parked in the selected area. The studied camera height is1.5 m, and the video clips are 18video clips. Images are extracted from the video clip to be used for training data for the cascade method. Cascade classification is used to detect license plates after the training step. Viola-jones algorithm was applied to the output of the cascade data for camera height (1.5m). The accuracy was calculated for all data with different weather conditions and local time recoding in two ways. The first used the detection of the car plate based on the video clip, and the accuracy was 100%. The second is using the clipped images stored in the positive file, based on the training file (XML file), where the ac

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Publication Date
Tue Mar 01 2022
Journal Name
Malaysian Journal Of Medicine & Health Sciences
Detection of Iron and Ferritin in Diabetes Mellitus Type 2 Patients
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Scopus (1)
Scopus
Publication Date
Sun Apr 30 2023
Journal Name
Iraqi Journal Of Science
Detection of COVID-19 in X-Rays by Convolutional Neural Networks
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      Coronavirus is considered the first virus to sweep the world in the twenty-first century, it appeared by the end of 2019. It started in the Chinese city of Wuhan and began to spread in different regions around the world too quickly and uncontrollable due to the lack of medical examinations and their inefficiency. So, the process of detecting the disease needs an accurate and quickly detection techniques and tools. The X-Ray images are good and quick in diagnosing the disease, but an automatic and accurate diagnosis is needed. Therefore, this paper presents an automated methodology based on deep learning in diagnosing COVID-19. In this paper, the proposed system is using a convolutional neural network, which is considered one o

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