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Intrusion Detection System Using Data Stream Classification
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Secure data communication across networks is always threatened with intrusion and abuse. Network Intrusion Detection System (IDS) is a valuable tool for in-depth defense of computer networks. Most research and applications in the field of intrusion detection systems was built based on analysing the several datasets that contain the attacks types using the classification of batch learning machine. The present study presents the intrusion detection system based on Data Stream Classification. Several data stream algorithms were applied on CICIDS2017 datasets which contain several new types of attacks. The results were evaluated to choose the best algorithm that satisfies high accuracy and low computation time.

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Publication Date
Sat Jan 01 2022
Journal Name
Journal Of Al-farabi For Engineering Sciences Vol
Prototyping of Multi-Factors Based Vehicle Accident Detection and Reporting System Relying on GPS and GSM
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Publication Date
Thu Apr 28 2022
Journal Name
Iraqi Journal Of Science
Hybrid Images Compression and Transmitted Using MC-CDMA System
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In this paper, the combined source coding with Multi Carrier Code Division Multiple Access (MC-CDMA) system is proposed, where the transmission of the compressed image produced from source coding through Additive White Gaussian Noise (AWGN) channel for a single user and multi users. In which the (MC-CDMA) system removes Inter Symbol Interference (ISI) and Inter Carrier Interference (ICI). The hybrid compression system of Discrete Cosine Transform (DCT) and predictive coding (PC) technique are integrated as a source coding. The simulation results indicates that the transmission system of a single user was much better than the transmission system of multi users. When the number of users increased, the Bit Error Rate (BER) increased. For a

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Publication Date
Sun Apr 30 2023
Journal Name
Iraqi Journal Of Science
Automatic Numeral Recognition System Using Local Statistical and Geometrical Features
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     Optical Character Recognition (OCR) research includes computer vision, artificial intelligence, and pattern recognition. Character recognition has garnered a lot of attention in the last decade due to its broad variety of uses and applications, including multiple-choice test data, business documents (e.g., ID cards, bank notes, passports, etc.), and automatic number plate recognition. This paper introduces an automatic recognition system for printed numerals. The automatic reading system is based on extracting local statistical and geometrical features from the text image. Those features are represented by eight vectors extracted from each digit. Two of these features are local statistical (A, A th), and six are local

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Publication Date
Thu Feb 28 2019
Journal Name
Iraqi Journal Of Science
Stratigraphic and Structural Study of Khlesia Region Using 2D Seismic Data - North Western Iraq
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     This study deals with interpretation of stratigraphic and structural of Khlesia area north-west Iraq in Nineveh province, near the Iraq- Syria border, by using 2D seismic data. Synthetic trace are prepared by using available data of the well (Kh-1) using Geoframe program to define and picking the reflectors on seismic section. These reflectors are: (Within Fatha and Kurra Chine reflectors) representing  Middle Miocene and Late Triassic ages respectively. A listric growth normal fault is affecting the stratigraphic succession, and normal fault as a result of collision of Arabian plate with Eurasian plate. In addition, minor normal faults (Dendritic and Tension) are developed on the listric normal growth fault

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Publication Date
Wed Aug 31 2022
Journal Name
Iraqi Journal Of Science
Structural study Using 2D Seismic Reflection Data of East lake Razzazah Area, Central Iraq
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     This research is focused on an interpretive of 2D seismic data to study is reinterpreting seismic data by applying sufficient software (Petrel 2017) of the area between Al-Razzazah Lake and the Euphrates river belonging to Karbala'a and Al-Anbar Governorates, central Iraq. The delineation of the sub-surface structural features and evaluation of the structure of Najmah and Zubair Formations was done. The structure interpretation showed that the studied area was affected by normal fault bearing (NW-SE) direction with a small displacement. In contrast, time and depth maps showed monocline structures (nose structures) located in the western part of the studied area.

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Publication Date
Mon May 01 2017
Journal Name
Australian Journal Of Basic And Applied Sciences
Sprite Region Allocation Using Fast Static Sprite Area Detection Algorithm
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Background: Sprite coding is a very effective technique for clarifying the background video object. The sprite generation is an open issue because of the foreground objects which prevent the precision of camera motion estimation and blurs the created sprite. Objective: In this paper, a quick and basic static method for sprite area detection in video data is presented. Two statistical methods are applied; the mean and standard deviation of every pixel (over all group of video frame) to determine whether the pixel is a piece of the selected static sprite range or not. A binary map array is built for demonstrating the allocated sprite (as 1) while the non-sprite (as 0) pixels valued. Likewise, holes and gaps filling strategy was utilized to re

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Publication Date
Tue Feb 01 2022
Journal Name
Svu-international Journal Of Engineering Sciences And Applications
Water Quality Detection using cost-effective sensors based on IoT
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Publication Date
Tue Dec 28 2021
Journal Name
2021 2nd Information Technology To Enhance E-learning And Other Application (it-ela)
Pedestrian and Objects Detection by Using Learning Complexity-Aware Cascades
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Publication Date
Wed Nov 24 2021
Journal Name
Iraqi Journal Of Science
Molecular Detection of Suspected Leishmania Isolates Using Polymerase Chain Reaction
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Leishmaniasis is a widespread parasitic disease that occurs as a result of infection with a unicellular parasite belonging to the genus Leishmania. Diagnosis by conventional methods is inaccurate and is not sensitive to confirm the genus infection. Here, we have investigated a methods for Leishmania genus diagnosis, which includes the technique of polymerase chain reaction to detect the presence of the parasite at in vitro for promastigote cultures using three genus-specific primer pairs to amplify HSP70, ITS, and ITS2. The results showed single band of ~1422, ~1020, and ~550 respectively. This study has proved the ability of these primer pairs to detect Leishmania infection and recommend them to be used for detection of leishmaniasis in

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Publication Date
Fri Sep 30 2022
Journal Name
Iraqi Journal Of Science
Sequential feature selection for heart disease detection using random forest
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Heart disease identification is one of the most challenging task that requires highly experienced cardiologists. However, in developing nations such as Ethiopia, there are a few cardiologists and heart disease detection is more challenging. As an alternative solution to cardiologist, this study proposed a more effective model for heart disease detection by employing random forest and sequential feature selection (SFS). SFS is an effective approach to improve the performance of random forest model on heart disease detection. SFS removes unrelated features in heart disease dataset that tends to mislead random forest model on heart disease detection. Thus, removing inappropriate and duplicate features from the training set with sequential f

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