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A proposal to detect computer worms (malicious codes) using data mining classification algorithms
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Malicious software (malware) performs a malicious function that compromising a computer system’s security. Many methods have been developed to improve the security of the computer system resources, among them the use of firewall, encryption, and Intrusion Detection System (IDS). IDS can detect newly unrecognized attack attempt and raising an early alarm to inform the system about this suspicious intrusion attempt. This paper proposed a hybrid IDS for detection intrusion, especially malware, with considering network packet and host features. The hybrid IDS designed using Data Mining (DM) classification methods that for its ability to detect new, previously unseen intrusions accurately and automatically. It uses both anomaly and misuse detection techniques using two DM classifiers (Interactive Dichotomizer 3 (ID3) classifier and Naïve Bayesian (NB) Classifier) to verify the validity of the proposed system in term of accuracy rate. A proposed HybD dataset used in training and testing the hybrid IDS. Feature selection is used to consider the intrinsic features in classification decision, this accomplished by using three different measures: Association rules (AR) method, ReliefF measure, and Gain Ratio (GR) measure. NB classifier with AR method given the most accurate classification results (99%) with false positive (FP) rate (0%) and false negative (FN) rate (1%).

Publication Date
Thu Jan 01 2015
Journal Name
Applied And Computational Mathematics
Texture Classification Using Spline, Wavelet Decomposition and Fractal Dimension
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Publication Date
Wed Nov 25 2015
Journal Name
Research Journal Of Applied Sciences, Engineering And Technology
Subject Independent Facial Emotion Classification Using Geometric Based Features
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Accurate emotion categorization is an important and challenging task in computer vision and image processing fields. Facial emotion recognition system implies three important stages: Prep-processing and face area allocation, feature extraction and classification. In this study a new system based on geometric features (distances and angles) set derived from the basic facial components such as eyes, eyebrows and mouth using analytical geometry calculations. For classification stage feed forward neural network classifier is used. For evaluation purpose the Standard database "JAFFE" have been used as test material; it holds face samples for seven basic emotions. The results of conducted tests indicate that the use of suggested distances, angles

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Publication Date
Fri Dec 29 2017
Journal Name
Ibn Al-haitham Journal For Pure And Applied Sciences
Effect of Using the Computer in Teaching Physics to the Fifth Secondary Grade on the Achievement of Students and Their Retention of Information
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The aims of research is to know the effect of using the computer in

teaching physics to the fifth secondary grade on the achievement of the students and their retention of  information .

The sample consists of ( 50 ) students in the fillh secondary grade (scicnti fie  branch  )   in  Nassiriyah   secondary  school   in  Thi-qar governorate in ( 200 I - 2002 ) that chooses as random Iy and divided

to t>vo equivalent groups:control and experimental .

The researcher built the teaching plans of each group . The five lessons choice from curriculum , and desi b'Tl  five computer teaching programs , and final achievement test from multip

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Publication Date
Sat Apr 01 2017
Journal Name
Journal Of Economics And Administrative Sciences
Proposal framework to activate the international accounting procedures for disasters and wars effects in the local environment
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natural and non-natural disasters, is an environmental challenges the society and the economy as well as a direct and indirect economic affect, and the units are part of the system overlapping among themselves and thus affected by external indicators, directly or indirectly, these direct effects appear in the destruction or damage inflicted by disasters in property , infrastructure , superstructure , accounting information systems and indirectly in the outcome of future business, comes research problem through access to accounting treatments issued by the Federal Office of financial supervision to address the damage caused by the disasters and prepare the missing financial accounts it turns out us that there is negligence of a nu

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Publication Date
Wed Apr 25 2018
Journal Name
Ibn Al-haitham Journal For Pure And Applied Sciences
Using Approximation Non-Bayesian Computation with Fuzzy Data to Estimation Inverse Weibull Parameters and Reliability Function
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        In real situations all observations and measurements are not exact numbers but more or less non-exact, also called fuzzy. So, in this paper, we use approximate non-Bayesian computational methods to estimate inverse Weibull parameters and reliability function with fuzzy data. The maximum likelihood and moment estimations are obtained as non-Bayesian estimation. The maximum likelihood estimators have been derived numerically based on two iterative techniques namely “Newton-Raphson” and the “Expectation-Maximization” techniques. In addition, we provide compared numerically through Monte-Carlo simulation study to obtained estimates of the parameters and reliability function i

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Publication Date
Thu Aug 31 2023
Journal Name
Iraqi Geological Journal
Mineral Inversion Approach to Improve Ahdeb Oil Field's Mineral Classification
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Knowledge of the mineralogical composition of a petroleum reservoir's formation is crucial for the petrophysical evaluation of the reservoir. The Mishrif formation, which is prevalent in the Middle East, is renowned for its mineralogical complexity. Multi-mineral inversion, which combines multiple logs and inversions for multiple minerals at once, can make it easier to figure out what minerals are in the Mishrif Formation. This method could help identify minerals better and give more information about the minerals that make up the formation. In this study, an error model is used to find a link between the measurements of the tools and the petrophysical parameters. An error minimization procedure is subsequently applied to determine

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Publication Date
Sun Jun 02 2013
Journal Name
Baghdad Science Journal
Sludge worms species (Oligochaeta: Naididae: Tubificinae) From Different Aquatic Habitat in Baghdad / Iraq
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The present investigation is concerned primarily with sorting and identification of subfamily Tubificinae from River Tigris and some water surface in Baghdad /Iraq . For this purpose six study sites were chosen, including a Al- Kadhemyia drainage canal, North Baghdad; three sites on the shore of River Tigris; in addition to site in Al-Jaish canal , East Baghdad, finally the sixth site was from pond in Al-Zawra'a park , within the center of Baghdad .These sites were characterized by sediment rang from clay, silty-clay to silty with a percentage of organic matter ranged between 0.7% - 9.9% . According to water temperature, salinity and pH values, they were nearly identical in all study sites, the water temperature was ranged through the study

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Publication Date
Wed May 17 2023
Journal Name
International Journal Of Computational Intelligence Systems
Prediction of ROP Zones Using Deep Learning Algorithms and Voting Classifier Technique
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Abstract<p>Retinopathy of prematurity (ROP) can cause blindness in premature neonates. It is diagnosed when new blood vessels form abnormally in the retina. However, people at high risk of ROP might benefit significantly from early detection and treatment. Therefore, early diagnosis of ROP is vital in averting visual impairment. However, due to a lack of medical experience in detecting this condition, many people refuse treatment; this is especially troublesome given the rising cases of ROP. To deal with this problem, we trained three transfer learning models (VGG-19, ResNet-50, and EfficientNetB5) and a convolutional neural network (CNN) to identify the zones of ROP in preterm newborns. The dataset to train th</p> ... Show More
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Publication Date
Thu Nov 22 2018
Journal Name
Ibn Al-haitham Journal For Pure And Applied Sciences
The Computer Based Tests: a digital substitution for the Iraqi postgraduate students
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The wide spread of Computer Based Test in the Iraqi universities raised an important concern for some scholars thinking about integrating computers as an academic assessment tool before making big change in the examination systems, that concern is: how the computerized test score is effected in comparison to old paper and pencil . This paper researches whether test scores of Iraqi students varies in the computer, Pencil based tests, sixty-four postgraduate graduates from Iraqi universities. Thirty five female and twenty nine male, all graduated from colleges of science in specializations other than computer science and applying for postgraduate studies in the Iraqi

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Publication Date
Sun May 01 2016
Journal Name
Journal Of Engineering
Encoding of QC-LDPC Codes of Rank Deficient Parity Matrix
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The encoding of long low density parity check (LDPC) codes presents a challenge compared to its decoding. The Quasi Cyclic (QC) LDPC codes offer the advantage for reducing the complexity for both encoding and decoding due to its QC structure. Most QC-LDPC codes have rank deficient parity matrix and this introduces extra complexity over the codes with full rank parity matrix. In this paper an encoding scheme of QC-LDPC codes is presented that is suitable for codes with full rank parity matrix and rank deficient parity matrx. The extra effort required by the codes with rank deficient parity matrix over the codes of full rank parity matrix is investigated.

 

 

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