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A new modified differential evolution algorithm scheme-based linear frequency modulation radar signal de-noising
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The main intention of this study was to investigate the development of a new optimization technique based on the differential evolution (DE) algorithm, for the purpose of linear frequency modulation radar signal de-noising. As the standard DE algorithm is a fixed length optimizer, it is not suitable for solving signal de-noising problems that call for variability. A modified crossover scheme called rand-length crossover was designed to fit the proposed variable-length DE, and the new DE algorithm is referred to as the random variable-length crossover differential evolution (rvlx-DE) algorithm. The measurement results demonstrate a highly efficient capability for target detection in terms of frequency response and peak forming that was isolated from noise distortion. The modified method showed significant improvements in performance over traditional de-noising techniques.

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Publication Date
Tue Jun 30 2015
Journal Name
International Journal Of Computer Techniques
Multifractal-Based Features for Medical Images Classification
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This paper presents a method to classify colored textural images of skin tissues. Since medical images havehighly heterogeneity, the development of reliable skin-cancer detection process is difficult, and a mono fractaldimension is not sufficient to classify images of this nature. A multifractal-based feature vectors are suggested hereas an alternative and more effective tool. At the same time multiple color channels are used to get more descriptivefeatures.Two multifractal based set of features are suggested here. The first set measures the local roughness property, whilethe second set measure the local contrast property.A combination of all the extracted features from the three colormodels gives a highest classification accuracy with 99.4

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Publication Date
Fri Jan 01 2016
Journal Name
Ibn Al-haitham Journal For Pure And Applied Science
Genetic--Based Face Retrieval Using Statistical Features
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Publication Date
Sun Jun 20 2021
Journal Name
Baghdad Science Journal
Reinforcement Learning-Based Television White Space Database
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Television white spaces (TVWSs) refer to the unused part of the spectrum under the very high frequency (VHF) and ultra-high frequency (UHF) bands. TVWS are frequencies under licenced primary users (PUs) that are not being used and are available for secondary users (SUs). There are several ways of implementing TVWS in communications, one of which is the use of TVWS database (TVWSDB). The primary purpose of TVWSDB is to protect PUs from interference with SUs. There are several geolocation databases available for this purpose. However, it is unclear if those databases have the prediction feature that gives TVWSDB the capability of decreasing the number of inquiries from SUs. With this in mind, the authors present a reinforcement learning-ba

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Publication Date
Sat Aug 03 2024
Journal Name
Proceedings Of Ninth International Congress On Information And Communication Technology
Offline Signature Verification Based on Neural Network
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The investigation of signature validation is crucial to the field of personal authenticity. The biometrics-based system has been developed to support some information security features.Aperson’s signature, an essential biometric trait of a human being, can be used to verify their identification. In this study, a mechanism for automatically verifying signatures has been suggested. The offline properties of handwritten signatures are highlighted in this study which aims to verify the authenticity of handwritten signatures whether they are real or forged using computer-based machine learning techniques. The main goal of developing such systems is to verify people through the validity of their signatures. In this research, images of a group o

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Publication Date
Fri Jan 30 2026
Journal Name
Iraqi Journal Of Science
Intrusion Detection Approach Based on DNA Signature
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Publication Date
Thu Aug 01 2019
Journal Name
International Journal Of Machine Learning And Computing
Emotion Recognition System Based on Hybrid Techniques
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Emotion recognition has important applications in human-computer interaction. Various sources such as facial expressions and speech have been considered for interpreting human emotions. The aim of this paper is to develop an emotion recognition system from facial expressions and speech using a hybrid of machine-learning algorithms in order to enhance the overall performance of human computer communication. For facial emotion recognition, a deep convolutional neural network is used for feature extraction and classification, whereas for speech emotion recognition, the zero-crossing rate, mean, standard deviation and mel frequency cepstral coefficient features are extracted. The extracted features are then fed to a random forest classifier. In

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Publication Date
Wed Oct 17 2018
Journal Name
Journal Of Economics And Administrative Sciences
The Use Of the Bayesian Method and Restricted Maximum Likelihood in estimating of mixed Linear Components with random effects model with practical application.
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In this research we study a variance component model, Which is the one of the most important models widely used in the analysis of the data, this model is one type of a multilevel models, and it is considered as linear models , there are three types of linear variance component models ,Fixed effect of linear variance component model, Random effect of linear variance component model and Mixed effect of linear variance component model . In this paper we will examine the model of mixed effect of linear variance component model with one –way random effect ,and the mixed model is a mixture of fixed effect and random effect in the same model, where it contains the parameter (μ) and treatment effect (τi ) which  has

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Publication Date
Sun Mar 08 2020
Journal Name
Biochem. Cell. Arch
SYNTHESIS AND SPECTROSCOPIC CHARACTERIZATION OF NEW HETEROCYCLIC COMPOUNDS DERIVATIED FROM 1-(4-AMINOPHENYL) ETHAN-1-ONEOXIME AS A STARTING MATERIAL WITH EVALUATE THEIR BIOLOGICAL ACTIVITY
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ABSTRACT : This research involves the synthesis of five to seven heterocyclic compounds starting with Schiff’s bases which derived from oxime as a starting material. 1.3-oxazepine derivatives were prepared from adding different anhydrides to the Schiff bases, tetrazole and thiazolidinone derivatives synthesized from add sodium azide and thioglycolic acid to the same Schiff’s bases as a five members ring. Pyrimidine derivatives were prepared after the reaction of the azomethine group with acetyl chloride and then urea and thiourea to synthesis on derivatives contain the six members ring. Another step included identified and confirmed these compounds by FT- IR, 1HNMR, TLC and 13CNMR finally, step included the assay of biological activity

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Publication Date
Wed Jun 19 2019
Journal Name
Biochemical And Cellular Archives
SYNTHESIS, CHARACTERIZATION, STRUCTURAL, THERMAL, POM STUDIES, ANTIMICROBIAL AND DNA CLEAVAGE ACTIVITY OF A NEW SCHIFF BASE-AZO LIGAND AND ITS COMPLEXATION WITH SELECTED METAL IONS
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SYNTHESIS, CHARACTERIZATION, STRUCTURAL, THERMAL, POM STUDIES, ANTIMICROBIAL AND DNA CLEAVAGE ACTIVITY OF A NEW SCHIFF BASE-AZO LIGAND AND ITS COMPLEXATION WITH SELECTED METAL IONS

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Scopus
Publication Date
Tue Nov 13 2018
Journal Name
Biochemical And Cellular Archives
Synthesis, characterization, structural, thermal, POM, studies, antimicrobial, and DNA cleavage activity of a new schiff base-azo lighand and its complexation with selected metal ions
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RKRAS L. K. Abdul Karem, F. H. Ganim, Biochemical and Cellular Archives, 2018 - Cited by 2

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