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A Novel DNA Sequence Approach for Network Intrusion Detection System Based on Cryptography Encoding Method
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A novel method for Network Intrusion Detection System (NIDS) has been proposed, based on the concept of how DNA sequence detects disease as both domains have similar conceptual method of detection. Three important steps have been proposed to apply DNA sequence for NIDS: convert the network traffic data into a form of DNA sequence using Cryptography encoding method; discover patterns of Short Tandem Repeats (STR) sequence for each network traffic attack using Teiresias algorithm; and conduct classification process depends upon STR sequence based on Horspool algorithm. 10% KDD Cup 1999 data set is used for training phase. Correct KDD Cup 1999 data set is used for testing phase to evaluate the proposed method. The current experiment results show that the proposed system has obtained good results and these results are equal to 86.36%, 49.69%, and 77.65% for detection rate, false alarm rate and accuracy respectively. These results are considered as a better result when it is compared with the other previous basic algorithms. It is possible to conclude that DNA sequence has potential for NIDS solution and it has potential improvement using a better encoding method.

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Publication Date
Sat Oct 01 2022
Journal Name
Baghdad Science Journal
Offline Signature Biometric Verification with Length Normalization using Convolution Neural Network
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Offline handwritten signature is a type of behavioral biometric-based on an image. Its problem is the accuracy of the verification because once an individual signs, he/she seldom signs the same signature. This is referred to as intra-user variability. This research aims to improve the recognition accuracy of the offline signature. The proposed method is presented by using both signature length normalization and histogram orientation gradient (HOG) for the reason of accuracy improving. In terms of verification, a deep-learning technique using a convolution neural network (CNN) is exploited for building the reference model for a future prediction. Experiments are conducted by utilizing 4,000 genuine as well as 2,000 skilled forged signatu

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Publication Date
Mon Dec 02 2024
Journal Name
Engineering, Technology & Applied Science Research
An Artificial Neural Network Prediction Model of GFRP Residual Tensile Strength
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This study uses an Artificial Neural Network (ANN) to examine the constitutive relationships of the Glass Fiber Reinforced Polymer (GFRP) residual tensile strength at elevated temperatures. The objective is to develop an effective model and establish fire performance criteria for concrete structures in fire scenarios. Multilayer networks that employ reactive error distribution approaches can determine the residual tensile strength of GFRP using six input parameters, in contrast to previous mathematical models that utilized one or two inputs while disregarding the others. Multilayered networks employing reactive error distribution technology assign weights to each variable influencing the residual tensile strength of GFRP. Temperatur

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Publication Date
Tue Sep 06 2022
Journal Name
Methods And Objects Of Chemical Analysis
Spectrophotometric Analysis of Quaternary Drug Mixtures using Artificial Neural network model
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A Novel artificial neural network (ANN) model was constructed for calibration of a multivariate model for simultaneously quantitative analysis of the quaternary mixture composed of carbamazepine, carvedilol, diazepam, and furosemide. An eighty-four mixing formula where prepared and analyzed spectrophotometrically. Each analyte was formulated in six samples at different concentrations thus twenty four samples for the four analytes were tested. A neural network of 10 hidden neurons was capable to fit data 100%. The suggested model can be applied for the quantitative chemical analysis for the proposed quaternary mixture.

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Publication Date
Wed Feb 01 2023
Journal Name
Baghdad Science Journal
Retrieving Encrypted Images Using Convolution Neural Network and Fully Homomorphic Encryption
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A content-based image retrieval (CBIR) is a technique used to retrieve images from an image database. However, the CBIR process suffers from less accuracy to retrieve images from an extensive image database and ensure the privacy of images. This paper aims to address the issues of accuracy utilizing deep learning techniques as the CNN method. Also, it provides the necessary privacy for images using fully homomorphic encryption methods by Cheon, Kim, Kim, and Song (CKKS). To achieve these aims, a system has been proposed, namely RCNN_CKKS, that includes two parts. The first part (offline processing) extracts automated high-level features based on a flatting layer in a convolutional neural network (CNN) and then stores these features in a

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Publication Date
Mon Oct 01 2018
Journal Name
Iraqi Journal Of Physics
Classification of brain tumors using the multilayer perceptron artificial neural network
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Information from 54 Magnetic Resonance Imaging (MRI) brain tumor images (27 benign and 27 malignant) were collected and subjected to multilayer perceptron artificial neural network available on the well know software of IBM SPSS 17 (Statistical Package for the Social Sciences). After many attempts, automatic architecture was decided to be adopted in this research work. Thirteen shape and statistical characteristics of images were considered. The neural network revealed an 89.1 % of correct classification for the training sample and 100 % of correct classification for the test sample. The normalized importance of the considered characteristics showed that kurtosis accounted for 100 % which means that this variable has a substantial effect

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Publication Date
Thu Jun 24 2021
Journal Name
Frontiers In Medicine
The Characterisation of the Craniofacial Morphology of Infants Born With Zika Virus; Innovative Approach for Public Health Surveillance and Broad Clinical Applications
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Background: This study was carried out in response to the Zika virus epidemic, which constituted a public health emergency, and to the 2019 WHO calling for strengthened surveillance for the early detection of related microcephaly. The main aim of the study was to phenotype the craniofacial morphology of microcephaly using a novel approach and new measurements, and relate the characteristics to brain abnormalities in Zika-infected infants in Brazil to improve clinical surveillance.

Methods: 3D images of the face and the cranial vault of 44 Zika-infected infants and matched healthy controls were captured using a 3D stereophotogrammetry system. The CT scans of the brain of t

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Publication Date
Tue Aug 06 2019
Journal Name
Journal Of Physical Organic Chemistry
Synthesis and bioactivity studies of novel Schiff bases and their complexes
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Abstract<p>The new Schiff base (L) “4‐[(2,4‐dimethoxy‐benzylidene)‐amino]‐1,5‐dimethyl‐2‐phenyl‐1,2‐dihydro‐pyrazol‐3‐one” was synthesized from 2,4‐dimethoxy‐benzaldehyde and 4‐amino‐1,5‐dimethyl‐2‐phenyl‐1,2‐dihydropyrazol‐3‐one, and the geometry of Schiff base was characterized and determined by proton nuclear magnetic resonance (<sup>1</sup>H‐NMR), mass, Fourier transform infrared (FT‐IR), and ultraviolet‐visible (UV‐vis) spectroscopy. Schiff complexes of Ni(II), Pd(II), Pt(IV), Zn(II), Cd(II), and Mg(II) have been prepared by reaction of ion metals with as‐prepared Schiff base. The results showed that synthesized complexes offered 1:2 m</p> ... Show More
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Publication Date
Fri Jun 29 2018
Journal Name
Journal Of The College Of Education For Women
Stream of Consciousness Technique: Psychological Perspectives and Use in Modern Novel
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Stream of Consciousness technique has a great impact on writing literary texts in the modern age. This technique was broadly used in the late of nineteen century as a result of thedecay of plot, especially in novel writing. Novelists began to use stream of consciousness technique as a new phenomenon, because it goes deeper into the human mind and soul through involving it in writing. Modern novel has changed after Victorian age from the traditional novel that considers themes of religion, culture, social matters, etc.  to be a group of irregular events and thoughts interrogate or reveal the inner feeling of  readers.

This study simplifies stream of consciousness technique through clarifying the three levels of conscious

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Publication Date
Sun Jun 05 2016
Journal Name
Baghdad Science Journal
Synthesis and Characterization of Some Novel Oxazine, Thiazine and Pyrazol Derivatives
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In this paper, some chalcone derivatives (C1, C2) were synthesized based on the reaction of equal amount of substituted acetophenone and substituted banzaldehyde in basic medium. Oxazine and thiazine derivatives were prepared from the reaction of chalcones (C1-C2) with urea and thiourea respectively in a basic medium. Pyrazole derivatives were prepared based on the reaction of chalcones with hydrazine mono hydrate or phenyl hydrazine in the presence of glacial acetic acid as a catalyst. The new synthesized compounds were identified using various physical techniques like1 H-NMR and FT-IR spectra.

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Publication Date
Fri Dec 15 2023
Journal Name
Al-adab Journal
The Portrayal of Serial Killers in Thomas Harris’ Novel Read Dragon
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This study aims to deeply analyze the character of serial killers in Thomas Harris’ novels and focuses on his novel Red Dragon. The Study searches in these complex and deep characters through the use of Erich Fromm's concepts about the destructive nature of the human psyche and what are the factors affecting serial killers in all social psychological, and biological aspects. This study Concluded: Thomas Harris portrayed the characters of serial killers in a professional and complex and made the reader go on a contemplative journey in the mind and soul of the serial killer, thus reaching the climax of artistic perfection.

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