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A Ranked-Aware GA with HoG Features for Infant Cry Classification
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Publication Date
Fri Mar 15 2024
Journal Name
Journal Of Baghdad College Of Dentistry
A clinicopathological analysis of 151 odontogenic tumors based on new WHO classification 2022: A retrospective cross-sectional study
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Background: Odontogenic tumors are a diverse group of lesions with a variety of clinical behavior and histopathologic subtypes, from hamartomatous and benign to malignant. The study aimed to examine the clinical and pathological features of odontogenic tumors in Baghdad over the last 11 years (2011–2021). Materials and Methods: The present retrospective study analyzed all formalin-fixed, paraffin-embedded tissue blocks of patients diagnosed with an odontogenic tumor that were retrieved from archives at a teaching hospital/College of Dentistry in Baghdad University, Iraq, between 2011 and 2021. The diagnosis of each case was confirmed by examining the hematoxylin and eosin stained sections by two expert pathologists. Data from pati

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Publication Date
Sat Jun 01 2024
Journal Name
Al-nahrain Journal Of Science
The Association Between Immune-Histochemical Expressions of Program Death Ligand with some Aggressive Features of Prostate Cancer
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Prostate cancer (PC), accounts for more than one-fourth of all cancer diagnoses, and the most frequently diagnosed cancer among men in 2022. The immunoglobulin (IG) Program death ligand-1(PD-1) cell surface receptor is predominantly expressed on the surface of many cells. The purpose of this study was to demonstrate the relationship between Program death ligand expression and some aggressive features of prostate cancer including perineural invasion, vascular invasion and necrosis. Thirty cases of prostate cancer with age range from 60 to 80 year old and 30 cases of normal prostate tissue with age under 25 year old were separated into two groups in a retrospective case-control

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Publication Date
Wed Sep 23 2020
Journal Name
Artificial Intelligence Research
Hybrid approaches to feature subset selection for data classification in high-dimensional feature space
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This paper proposes two hybrid feature subset selection approaches based on the combination (union or intersection) of both supervised and unsupervised filter approaches before using a wrapper, aiming to obtain low-dimensional features with high accuracy and interpretability and low time consumption. Experiments with the proposed hybrid approaches have been conducted on seven high-dimensional feature datasets. The classifiers adopted are support vector machine (SVM), linear discriminant analysis (LDA), and K-nearest neighbour (KNN). Experimental results have demonstrated the advantages and usefulness of the proposed methods in feature subset selection in high-dimensional space in terms of the number of selected features and time spe

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Publication Date
Tue Feb 14 2023
Journal Name
Journal Of Educational And Psychological Researches
Analyzing the Literary Criticism Book Questions for High School Stage According to Bloom's Classification
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Abstract

 The current research aims to identify the analysis of the questions for the book of literary criticism for the preparatory stage according to Bloom's classification. The research community consists of (34) exercises and (45) questions. The researcher used the method of analyzing questions and prepared a preliminary list that includes criteria that are supposed to measure exercises, which were selected based on Bloom's classification and the extant literature related to the topic. The scales were exposed to a jury of experts and specialists in curricula and methods of teaching the Arabic language. The scales obtained a complete agreement. Thus, it was adapted to become a reliable instrument in this

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Publication Date
Sun Nov 01 2015
Journal Name
Engineering And Technology Journal
Synthesized Cu (In, Ga) Se2 (CIGS) thin films and implementation as the active light absorbing material in photovoltaic devices (PVs)
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This review article summarizes our research focused on Cu(In, Ga)Se2 (CIGS) nanocrystals, including their synthesis and implementation as the active light absorbing material in photovoltaic devices (PVs). CIGS thin films were prepared by arrested precipitation from molecular precursors consisting of CuCl, InCl3, GaCl3 and Se metal onto Mo/soda-lime glass (SLG) substrates. We have sought to use CIGS nanocrystals synthesized with the desired stoichiometry to deposit PV device layers without high temperature processing. This approach, using spray deposition of the CIGS light absorber layers, without high temperature selenization, has enabled up to 1.5 % power conversion efficiency under AM 1.5 solar illumination. The composition and morphology

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Publication Date
Sun Dec 16 2018
Journal Name
Al-academy
Scenography Features in the Iraqi Contemporary Theatre Show (Macbeth Play, by Salah Al-Qasab- A Model)
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Societies developed throughout history with the development of life technology, that ideas presented by the contemporary art have been crystallized. The development included all the artistic fields such as the dramatic arts which depend on many effects and elements that led to the completion of the structure of the theater show. Scenography is considered one of the most important elements that the theatre show depends on such as the decoration, lighting, sound effects, costumes and accessories. The research addressed the following question: what are the characteristics and traits of scenography in the theatre show?
The research importance has become clear because it sheds lights on the characteristics of scenography in the Iraqi thea

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Publication Date
Wed Jan 01 2020
Journal Name
Ieee Access
A Novel Approach to Improving Brain Image Classification Using Mutual Information-Accelerated Singular Value Decomposition
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Publication Date
Sat Jan 01 2022
Journal Name
Indonesian Journal Of Electrical Engineering And Computer Science
Increasing validation accuracy of a face mask detection by new deep learning model-based classification
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During COVID-19, wearing a mask was globally mandated in various workplaces, departments, and offices. New deep learning convolutional neural network (CNN) based classifications were proposed to increase the validation accuracy of face mask detection. This work introduces a face mask model that is able to recognize whether a person is wearing mask or not. The proposed model has two stages to detect and recognize the face mask; at the first stage, the Haar cascade detector is used to detect the face, while at the second stage, the proposed CNN model is used as a classification model that is built from scratch. The experiment was applied on masked faces (MAFA) dataset with images of 160x160 pixels size and RGB color. The model achieve

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Publication Date
Sat Jan 01 2022
Journal Name
Indonesian Journal Of Electrical Engineering And Computer Science (ijeecs)
Increasing validation accuracy of a face mask detection by new deep learning model-based classification
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During COVID-19, wearing a mask was globally mandated in various workplaces, departments, and offices. New deep learning convolutional neural network (CNN) based classifications were proposed to increase the validation accuracy of face mask detection. This work introduces a face mask model that is able to recognize whether a person is wearing mask or not. The proposed model has two stages to detect and recognize the face mask; at the first stage, the Haar cascade detector is used to detect the face, while at the second stage, the proposed CNN model is used as a classification model that is built from scratch. The experiment was applied on masked faces (MAFA) dataset with images of 160x160 pixels size and RGB color. The model achieve

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Publication Date
Thu Nov 01 2018
Journal Name
2018 1st Annual International Conference On Information And Sciences (aicis)
Speech Emotion Recognition Using Minimum Extracted Features
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Recognizing speech emotions is an important subject in pattern recognition. This work is about studying the effect of extracting the minimum possible number of features on the speech emotion recognition (SER) system. In this paper, three experiments performed to reach the best way that gives good accuracy. The first one extracting only three features: zero crossing rate (ZCR), mean, and standard deviation (SD) from emotional speech samples, the second one extracting only the first 12 Mel frequency cepstral coefficient (MFCC) features, and the last experiment applying feature fusion between the mentioned features. In all experiments, the features are classified using five types of classification techniques, which are the Random Forest (RF),

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