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Software Fault Estimation Tool Based on Object-Oriented Metrics
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A fault is an error that has effects on system behaviour. A software metric is a value that represents the degree to which software processes work properly and where faults are more probable to occur. In this research, we study the effects of removing redundancy and log transformation based on threshold values for identifying faults-prone classes of software. The study also contains a comparison of the metric values of an original dataset with those after removing redundancy and log transformation. E-learning and system dataset were taken as case studies. The fault ratio ranged from 1%-31% and 0%-10% for the original dataset and 1%-10% and 0%-4% after removing redundancy and log transformation, respectively. These results impacted directly the number of classes detected, which ranged between 1-20 and 1-7 for the original dataset and 1-7 and 0-3) after removing redundancy and log transformation. The Skewness of the dataset was deceased after applying the proposed model. The classified faulty classes need more attention in the next versions in order to reduce the ratio of faults or to do refactoring to increase the quality and performance of the current version of the software.

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Publication Date
Fri May 17 2019
Journal Name
Lecture Notes In Networks And Systems
Features Selection for Intrusion Detection System Based on DNA Encoding
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Intrusion detection systems detect attacks inside computers and networks, where the detection of the attacks must be in fast time and high rate. Various methods proposed achieved high detection rate, this was done either by improving the algorithm or hybridizing with another algorithm. However, they are suffering from the time, especially after the improvement of the algorithm and dealing with large traffic data. On the other hand, past researches have been successfully applied to the DNA sequences detection approaches for intrusion detection system; the achieved detection rate results were very low, on other hand, the processing time was fast. Also, feature selection used to reduce the computation and complexity lead to speed up the system

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Publication Date
Thu Nov 29 2018
Journal Name
Iraqi Journal Of Science
A new Color image Encryption based on multi Chaotic Maps
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     This paper presents a new RGB image encryption scheme using multi chaotic maps. Encrypting an image is performed via chaotic maps to confirm the properties of secure cipher namely confusion and diffusion are satisfied. Also, the key sequence for encrypting an image is generated using a combination of   1D logistic and Sine chaotic maps. Experimental results and the compassion results indicate that the suggested scheme provides high security against several types of attack, large secret keyspace and highly sensitive.   

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Publication Date
Sun Jan 30 2022
Journal Name
Iraqi Journal Of Science
A New Image Encryption Algorithm Based on Multi Chaotic System
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       In recent years, encryption technology has been developed rapidly and many image encryption methods have been put forward. The chaos-based image encryption technique is a modern encryption system for images. To encrypt images, it uses random sequence chaos, which is an efficient way to solve the intractable problem of simple and highly protected image encryption. There are, however, some shortcomings in the technique of chaos-based image encryption, such limited accuracy issue. The approach focused on the chaotic system in this paper is to construct a dynamic IP permutation and S-Box substitution by following steps. First of all, use of a new IP table for more diffusion of al

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Publication Date
Sun Jan 26 2020
Journal Name
Iraqi Journal Of Science
New Updated Classification of Shallow Earthquakes Based on Faulting Style
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Earthquakes occur on faults and create new faults. They also occur on  normal, reverse and strike-slip faults. The aim of this work is to suggest a new unified classification of Shallow depth earthquakes based on the faulting styles, and to characterize each class. The characterization criteria include the maximum magnitude, focal depth, b-constant value, return period and relations between magnitude, focal depth and dip of fault plane. Global Centroid Moment Tensor (GCMT) catalog is the source of the used data. This catalog covers the period from Jan.1976 to Dec. 2017. We selected only the shallow (depth less than 70kms) pure, normal, strike-slip and reverse earthquakes (magnitude ≥ 5) and excluded the oblique earthquakes. Th

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Publication Date
Tue Oct 01 2019
Journal Name
2019 Ieee 9th International Conference On System Engineering And Technology (icset)
A Digital Signature System Based on Real Time Face Recognition
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This study proposed a biometric-based digital signature scheme proposed for facial recognition. The scheme is designed and built to verify the person’s identity during a registration process and retrieve their public and private keys stored in the database. The RSA algorithm has been used as asymmetric encryption method to encrypt hashes generated for digital documents. It uses the hash function (SHA-256) to generate digital signatures. In this study, local binary patterns histograms (LBPH) were used for facial recognition. The facial recognition method was evaluated on ORL faces retrieved from the database of Cambridge University. From the analysis, the LBPH algorithm achieved 97.5% accuracy; the real-time testing was done on thirty subj

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Publication Date
Tue Feb 28 2023
Journal Name
Iraqi Journal Of Science
Photonic Crystal Fiber Pollution Sensor based on Surface Plasmon Resonance
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       In this work, a pollution-sensitive Photonic Crystal Fiber (PCF) based on Surface Plasmon Resonance (SPR) technology is designed and implemented for sensing refractive indices and concentrations of polluted  water . The overall construction of the sensor is achieved by splicing short lengths of PCF (ESM-12) solid core on one side with traditional multimode fiber (MMF) and depositing a gold nanofilm of 50nm thickness on the end of the PCF sensor. The PCF- SPR experiment was carried out with various samples of polluted water including(distilled water, draining water, dirty pond water, chemical water, salty  water and oiled water). The location of the resonant wavelength peaks is seen to move to longer wavelengths (red shift)

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Publication Date
Tue Jul 13 2021
Journal Name
Journal Of The Faculty Of Medicine Baghdad
A Comparative Study of Colorectal Cancer Based on Patient’s Age
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Abstract:

Background: The alteration of bowel habits, bleeding per-rectum and anemia were common features in both groups in this study, but in young patients there was a delay of 6 months between the presenting symptoms and the definitive diagnosis because the disease was not suspected and investigated in them. The most common site for the tumors in young patients was the rectum and in patients above the age of 40 years was the Sigmoid.

The pathological finding showed that classification of the colorectal tumors in young patients appear moderately to poorly differentiated adenocarcinoma , this indicate a more malignant course of the disease in young patients.

This study sen

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Publication Date
Tue Jun 04 2024
Journal Name
Computation
High-Performance Krawtchouk Polynomials of High Order Based on Multithreading
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Orthogonal polynomials and their moments serve as pivotal elements across various fields. Discrete Krawtchouk polynomials (DKraPs) are considered a versatile family of orthogonal polynomials and are widely used in different fields such as probability theory, signal processing, digital communications, and image processing. Various recurrence algorithms have been proposed so far to address the challenge of numerical instability for large values of orders and signal sizes. The computation of DKraP coefficients was typically computed using sequential algorithms, which are computationally extensive for large order values and polynomial sizes. To this end, this paper introduces a computationally efficient solution that utilizes the parall

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Publication Date
Sat Oct 01 2022
Journal Name
Baghdad Science Journal
A Crime Data Analysis of Prediction Based on Classification Approaches
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Crime is considered as an unlawful activity of all kinds and it is punished by law. Crimes have an impact on a society's quality of life and economic development. With a large rise in crime globally, there is a necessity to analyze crime data to bring down the rate of crime. This encourages the police and people to occupy the required measures and more effectively restricting the crimes. The purpose of this research is to develop predictive models that can aid in crime pattern analysis and thus support the Boston department's crime prevention efforts. The geographical location factor has been adopted in our model, and this is due to its being an influential factor in several situations, whether it is traveling to a specific area or livin

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Publication Date
Sat Apr 15 2023
Journal Name
Iraqi Journal Of Science
Hand Written Signature Verification based on Geometric and Grid Features
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The fact that the signature is widely used as a means of personal verification
emphasizes the need for an automatic verification system. Verification can be
performed either Offline or Online based on the application. Offline systems work on
the scanned image of a signature. In this paper an Offline Verification of handwritten
signatures which use set of simple shape based geometric features. The features used
are Mean, Occupancy Ratio, Normalized Area, Center of Gravity, Pixel density,
Standard Deviation and the Density Ratio. Before extracting the features,
preprocessing of a scanned image is necessary to isolate the signature part and to
remove any spurious noise present. Features Extracted for whole signature

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