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Object Detection and Distance Measurement Using AI

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Publication Date
Tue Sep 01 2020
Journal Name
Baghdad Science Journal
Developing Arabic License Plate Recognition System Using Artificial Neural Network and Canny Edge Detection

In recent years, there has been expanding development in the vehicular part and the number of vehicles moving on the roads in all the sections of the country. Arabic vehicle number plate identification based on image processing is a dynamic area of this work; this technique is used for security purposes such as tracking of stolen cars and access control to restricted areas. The License Plate Recognition System (LPRS) exploits a digital camera to capture vehicle plate numbers is used as input to the proposed recognition system. Basically, the proposed system consists of three phases, vehicle license plate localization, character segmentation, and character recognition, the License Plate (LP) detection is presented using canny edge detection

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Publication Date
Sun Oct 30 2022
Journal Name
Iraqi Journal Of Science
An Internet of Things Botnet Detection Model Using Regression Analysis and Linear Discrimination Analysis

The Internet of Things (IoT) has become a hot area of research in recent years due to the significant advancements in the semiconductor industry, wireless communication technologies, and the realization of its ability in numerous applications such as smart homes, health care, control systems, and military. Furthermore, IoT devices inefficient security has led to an increase cybersecurity risks such as IoT botnets, which have become a serious threat. To counter this threat there is a need to develop a model for detecting IoT botnets.

This paper's contribution is to formulate the IoT botnet detection problem and introduce multiple linear regression (MLR) for modelling IoT botnet features with discriminating capability and alleviatin

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Publication Date
Sun Dec 09 2018
Journal Name
Baghdad Science Journal
Detection of Pseudomonas aeruginosa in Clinical Samples Using PCR Targeting ETA and gyrB Genes

Pseudomonas aeruginosa has variety of virulence factors that contribute to its pathogenicity. Therefore, rapid detection with high accuracy and specificity is very important in the control of this pathogenic bacterium. To evaluate the accuracy and specificity of Polymerase Chain Reaction (PCR) assay, ETA and gyrB genes were targeted to detect pathogenic strains of P. aeruginosa. Seventy swab samples were taken from patients with infected wounds and burns in two hospitals in Erbil and Koya cities in Iraq. The isolates were traditionally identified using phenotypic methods, and DNA was extracted from the positive samples, to apply PCR using the species specific primers targeting ETA, the gene encoding for exotoxin A, and gyrB gene. The res

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Publication Date
Tue Oct 08 2002
Journal Name
Iraqi Journal Of Laser
Laser Detection and Tracking System Using an Array of Photodiodes with Fuzzy Logic controller

In this work laser detection and tracking system (LDTS) is designed and implemented using a fuzzy logic controller (FLC). A 5 mW He-Ne laser system and an array of nine PN photodiodes are used in the detection system. The FLC is simulated using MATLAB package and the result is stored in a lock up table to use it in the real time operation of the system. The results give a good system response in the target detection and tracking in the real time operation.

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Publication Date
Mon Dec 06 2021
Journal Name
Iraqi Journal Of Science
Detecting and Monitoring the Vegetal Cover of Karbala Province (Iraq) Using Change Detection Methods

Karbala province was one of the most important areas in Iraq and considered an
economic resource of vegetation such as trees of fruits, sieve and other vegetation.
This research aimed to utilize change detection for investigating the current
vegetation cover at last three decay. The main objectives of this research are collect
a group of studied area (Karbala province) satellite images in sequence time for
the same area, these image captured by Landsat (TM 1995, ETM+ 2005 and
Landsat 8 OLI (Operational Land Imager) 2015. Preprocessing such as atmosphere
correction and rectification has been done. Mosaic model between the parts of
studied area was performing. Gap filling consider being very important step has
be

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Publication Date
Wed Oct 28 2020
Journal Name
Iraqi Journal Of Science
Epileptic Seizures Detection Using DCT-II and KNN Classifier in Long-Term EEG Signals

     Epilepsy is one of the most common diseases of the nervous system around the world, affecting all age groups and causing seizures leading to loss of control for a period of time. This study presents a seizure detection algorithm that uses Discrete Cosine Transformation (DCT) type II to transform the signal into frequency-domain and extracts energy features from 16 sub-bands. Also, an automatic channel selection method is proposed to select the best subset among 23 channels based on the maximum variance. Data are segmented into frames of  one Second length without overlapping between successive frames. K-Nearest Neighbour (KNN) model is used to detect those frames either to ictal (seizure) or interictal (non-

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Publication Date
Tue Sep 01 2020
Journal Name
Baghdad Science Journal
Developing Arabic License Plate Recognition System Using Artificial Neural Network and Canny Edge Detection

            In recent years, there has been expanding development in the vehicular part and the number of vehicles moving on the roads in all the sections of the country. Arabic vehicle number plate identification based on image processing is a dynamic area of this work; this technique is used for security purposes such as tracking of stolen cars and access control to restricted areas. The License Plate Recognition System (LPRS) exploits a digital camera to capture vehicle plate numbers is used as input to the proposed recognition system. Basically, the proposed system consists of three phases, vehicle license plate localization, character segmentation, and character recognition, the

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Publication Date
Fri Dec 24 2021
Journal Name
Iraqi Journal Of Science
Morphology Detection in Archaeological Ancient Sites by Using UAVs/Drones Data and GIS techniques

    Today, Unmanned Aerial Vehicles (UAVs) or Drones are a valuable source of data on inspection, surveillance, mapping and 3D modelling matters. Drones can be considered as the new alternative of classic manned aerial photography due to their low cost and high spatial resolution. In this study, drones were used to study archaeological sites. The archaeological Nineveh site, which is a very famous site located in heart of the city of Mosul, in northern Iraq, was chosen. This site was the largest capital of the Assyrian Empire 3000 years ago. The site contains an external wall that includes many gates, most of which were destroyed when Daesh occupied the city in 2014. The local population of the city of Mosul has also large

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Publication Date
Sun Mar 01 2015
Journal Name
International Journal Of Computer Science And Mobile Computing
Publication Date
Tue Jun 07 2022
Journal Name
Journal Of Nuclear Engineering And Radiation Science
Radon and Exhalation Rate Measurement of Soil Samples in Al-Amiriya Area in Baghdad Governorate Using a Nuclear Track Detector
Abstract<p>Radon is the most dangerous natural radioactive component affecting the human population, since it is a radioactive gas that results from the decomposition process of uranium deposits in soil, rocks, and water, and it is damaging both humans and the ecosystem. The radon concentrations and exhalation rate in soil samples from various locations were determined using a passive approach with a CR-39 (CR-39 is Columbia Resin #39; it is allyl diglycol carbonate C12H18O7) detector in Amiriya region in Baghdad Governorate. The average values of radon concentrations are ranged from 47.3 to 54.2 Bq·m−3. From the obtained results, we can conclude that the values of all studied locations are</p> ... Show More
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