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Construct an efficient distributed denial of service attack detection system based on data mining techniques
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<span>Distributed denial-of-service (DDoS) attack is bluster to network security that purpose at exhausted the networks with malicious traffic. Although several techniques have been designed for DDoS attack detection, intrusion detection system (IDS) It has a great role in protecting the network system and has the ability to collect and analyze data from various network sources to discover any unauthorized access. The goal of IDS is to detect malicious traffic and defend the system against any fraudulent activity or illegal traffic. Therefore, IDS monitors outgoing and incoming network traffic. This paper contains a based intrusion detection system for DDoS attack, and has the ability to detect the attack intelligently, dynamically and periodically by evaluating the set of attackers of the current node with its neighbors. We use dataset named CICDDoS2019 that contains on binary classes benign and DDoS. Performance has evaluated by applying data mining algorithms as well as applying the best features to discover potential attack classes.</span>

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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
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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Publication Date
Sun May 01 2022
Journal Name
Journal Of Engineering
Performance Analysis of different Machine Learning Models for Intrusion Detection Systems
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In recent years, the world witnessed a rapid growth in attacks on the internet which resulted in deficiencies in networks performances. The growth was in both quantity and versatility of the attacks. To cope with this, new detection techniques are required especially the ones that use Artificial Intelligence techniques such as machine learning based intrusion detection and prevention systems. Many machine learning models are used to deal with intrusion detection and each has its own pros and cons and this is where this paper falls in, performance analysis of different Machine Learning Models for Intrusion Detection Systems based on supervised machine learning algorithms. Using Python Scikit-Learn library KNN, Support Ve

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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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Publication Date
Sat Apr 30 2022
Journal Name
Iraqi Journal Of Science
Detection of some CC Chemokine Ligands in Patients with Cutaneous Leishmaniasis
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     Cutaneous leishmaniasis (CL) is an endemic parasitic disease found in many provinces of Iraq. The immune system plays a crucial role in the development or healing of lesions through chemotactic cytokine activity. This study was aimed to detect the levels of two chemokine ligands (CCL2 and CCL5) in Iraqi patients suffering from dermal ulcers, caused by cutaneous leishmaniasis. It was measured in pre and post-treatment state of Pentostam (Pentavalent Antimony 100 mg). Blood serum concentrations of CCL2, CCL5 were measured by enzyme-linked immunosorbent assay among newly infected patients, two-trial treatment patients and three-trial treatment patients, in comparison with the control group. The result indicated a significant differ

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Publication Date
Mon Dec 06 2021
Journal Name
Iraqi Journal Of Science
Detection of Snow Cover us ing NDSI and False Color Methods
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Snowfall is one of the most important natural phenomena that can be seen in the
winter which is considered as a rare phenomenon in the Middle East. Snow is
covering parts of mountains in northern Iraq and neighboring countries in the first
months of the year. In this research, the snow cover can be detected and monitored
using pseudo color method, and the Normalized Difference Snow INDECES
(NDSI). Snow cover is difficult to detect in true color satellite images because the
white color of snow cover is the same color with the cloud cover. Modis sensors that
carried by Terra and Equa satellites images have been used in different bands and
different resolution and the case studied in 4/2/2017, 5/2/2017.

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Publication Date
Wed Jan 15 2020
Journal Name
Iraqi Journal Of Laser
Electronically Implementation and Detection of Pulse Laser from Continuous Laser Diode
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This research aims to design a high-speed laser diode driver and photodetector, the result is the
design of the high-speed laser diode driver with a short pulse of 10 ns at 30 KHz frequency and the
delivered maximum pulse voltage is 5.5 mV. Also, its optical output power of the laser diode driver is
about 2.529 mW for the centroied wavelength 1546.7 nm with FWHM of 286 pm and (1270-1610) nm.
The design of the circuit based on bipolar transistor where the input pulse signal is simply generated by
an arduino kit with 15 kHz frequency and then compensated to trigger to small signal amplifier which
was is simply NPN C3355 transistor and the output is a current driver to the laser diode. OptiSystem
software and Electronic

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Publication Date
Tue May 01 2012
Journal Name
Iraqi Journal Of Physics
Detection of line shape parameters in normal and abnormal biological tissues
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Doppler broadening technique is suggested to monitor the development of tumours. It depends on the sensitivity of positronium (Ps) annihilation parameters to the sub- microstructural changes in biological tissues. This technique uses high resolution HpGe detector to measure the lineshape parameters (S and W) in normal mice's mammary tissues and adenocarcinoma mammary tissues as a function of tumour growth. The results demonstrate that the central parameter (S) decreases and the wing parameter (W) increases as the tumour grow. It is found that the S parameter changes considerably with the distribution of voids which are affected by the tumour development. Therefore the present technique can successfully be employed to monitor the developm

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Publication Date
Sun Jan 05 2025
Journal Name
Science Journal Of University Of Zakho
DETECTION AND RECOGNITION OF IRAQI LICENSE PLATES USING CONVOLUTIONAL NEURAL NETWORKS
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Due to the large population of motorway users in the country of Iraq, various approaches have been adopted to manage queues such as implementation of traffic lights, avoidance of illegal parking, amongst others. However, defaulters are recorded daily, hence the need to develop a mean of identifying these defaulters and bring them to book. This article discusses the development of an approach of recognizing Iraqi licence plates such that defaulters of queue management systems are identified. Multiple agencies worldwide have quickly and widely adopted the recognition of a vehicle license plate technology to expand their ability in investigative and security matters. License plate helps detect the vehicle's information automatically ra

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