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jih-3102
Applying Ensemble Classifier, K-Nearest Neighbor and Decision Tree for Predicting Oral Reading Rate Levels
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For many years, reading rate as word correct per minute (WCPM) has been investigated by many researchers as an indicator of learners’ level of oral reading speed, accuracy, and comprehension. The aim of the study is to predict the levels of WCPM using three machine learning algorithms which are Ensemble Classifier (EC), Decision Tree (DT), and K- Nearest Neighbor (KNN). The data of this study were collected from 100 Kurdish EFL students in the 2nd-year, English language department, at the University of Duhok in 2021. The outcomes showed that the ensemble classifier (EC) obtained the highest accuracy of testing results with a value of 94%. Also, EC recorded the highest precision, recall, and F1 scores with values of 0.92 for the three performance measures. The Receiver Operating Character curve (ROC curve) also got the highest results than other classification algorithms. Accordingly, it can be concluded that the ensemble classifier is the best and most accurate model for predicting reading rate (accuracy) WCPM.    

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Publication Date
Sun Oct 03 2010
Journal Name
Journal Of Educational And Psychological Researches
The Effect of Applying K-W-L Technique on Teaching ESP Students
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         Over the last few decades, many instructors have been trying all kinds of teaching methods, but without benefit. Nevertheless, in the 1986, a new technique is appeared which called K-W-L technique, it  is specified for reading comprehension passages because reading  skill is not easy matter for students for specific purposes (ESP).therefore, the K-W-L technique is a good one for thinking and experiences. To fulfill the aims and verify the hypothesis which reads as follows" it is hypothesized that there are no significant differences between the achievements of students who are taught according to K-W-L technique and those who are taught according to the traditional method

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Publication Date
Tue Aug 01 2017
Journal Name
International Journal Of Scientific & Engineering Research
Integrated System of Information hiding by Applying Three levels
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MB Mahmood, BN Dhannoon

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Publication Date
Thu Apr 27 2017
Journal Name
Ibn Al-haitham Journal For Pure And Applied Sciences
Applying Nuclear Slidell Model To Calculate Energy Levels Ti42-44
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   In this work , we applied the nuclear shell model by using Modified Surface Delta Interaction ( MSDI ) to study the nuclear structure for Ti42-44 nuclei from the calculation of the energy level values and its total angular momentum .      After comperation with the experiment values which found to be rather in good agreement and determined the total angular momentum values of energy levels which are not assigned experimently , as soon as , we certify some values that were not certained experimently .  

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Publication Date
Tue Dec 26 2017
Journal Name
Al-khwarizmi Engineering Journal
Fuzzy Wavenet (FWN) classifier for medical images
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    The combination of wavelet theory and neural networks has lead to the development of wavelet networks. Wavelet networks are feed-forward neural networks using wavelets as activation function. Wavelets networks have been used in classification and identification problems with some success.

  In this work we proposed a fuzzy wavenet network (FWN), which learns by common back-propagation algorithm to classify medical images. The library of medical image has been analyzed, first. Second, Two experimental tables’ rules provide an excellent opportunity to test the ability of fuzzy wavenet network due to the high level of information variability often experienced with this type of images.

&n

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Publication Date
Fri Jun 30 2006
Journal Name
Al-kindy College Medical Journal
Oral Carriage Rate of Candida Species in Diabetic Patients
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Background: It is well known that oral carriage
of Candida species increase in many situations, like
obesity, debility, leukemia, viral infection, use of
certain drugs in addition to diabetes mellitus.
Objective: find the relation between diabetes and
its control on oral carriage of Candida.
Methods: Thirty four hundred oral swabs from
diabetic patients 67% are females and 33% are
males, 41.7% are type 1 diabetes and 58.3% are type
2.different culture media are used.
Results: we found that 37.9% of diabetics had oral
carriage, older age group had more but the
difference is not significant statistically P>0.05, in
addition females carry more Candida than males
P<0.05, while type of diabetes

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Publication Date
Thu Jun 30 2022
Journal Name
Journal Of Economics And Administrative Sciences
Examining the Asymmetric Impacts of Interest and Exchange Rate on Investment in Egypt for the Period 1976-2020: Applying NARDL Model
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Most of the studies conducted in the past decades focused on the effect of interest rates and exchange rates on domestic investment under the assumption that the independent variables have the same effect on the dependent variable, but there were limited studies that investigated the unequal effects of changes in interest rates and exchange rates, both positive and negative, on domestic investment.  This study used a nonlinear autoregressive distributed lag (NARDL) model to assess the unequal effects of the real interest rate and real exchange rate variables on domestic investment in Egypt for the period 1976 - 2020.  The results revealed that positive and negative shocks for both exchange rates have unequal effects on

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Publication Date
Mon Nov 27 2023
Journal Name
Journal Of Periodontal Research
Ability of gingival crevicular fluid volume, E‐cadherin, and total antioxidant capacity levels for predicting outcomes of nonsurgical periodontal therapy for periodontitis patients
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Abstract<sec><title>Objectives

To determine the potential of gingival crevicular fluid (GCF) volume, E‐cadherin and total antioxidant capacity (TAC) levels to predict the outcomes of nonsurgical periodontal therapy (NSPT) for periodontitis patients.

Background

NSPT is the gold‐standard treatment for periodontal pockets < 6 mm in depth, however, successful outcomes are not always guaranteed due to several factors. Periodontitis‐associated tissue destruction is evidenced by the increased level of soluble E‐cadherin and reduced antioxidants in oral fluids which could be used as predictors for success/failure of N

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Publication Date
Mon Jan 01 2018
Journal Name
Proceedings Of The 10th International Joint Conference On Computational Intelligence
Deep Classifier Structures with Autoencoder for Higher-level Feature Extraction
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Publication Date
Mon Apr 11 2011
Journal Name
Icgst
Employing Neural Network and Naive Bayesian Classifier in Mining Data for Car Evaluation
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In data mining, classification is a form of data analysis that can be used to extract models describing important data classes. Two of the well known algorithms used in data mining classification are Backpropagation Neural Network (BNN) and Naïve Bayesian (NB). This paper investigates the performance of these two classification methods using the Car Evaluation dataset. Two models were built for both algorithms and the results were compared. Our experimental results indicated that the BNN classifier yield higher accuracy as compared to the NB classifier but it is less efficient because it is time-consuming and difficult to analyze due to its black-box implementation.

Publication Date
Thu Aug 01 2024
Journal Name
Iop Conference Series: Earth And Environmental Science
Combining Bourgoyne and Young Equations by Bagging Tree Regression to Predict Rate of Penetration in a Southern Iraqi Field, Case Study
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Abstract<p>Achieving an accurate and optimal rate of penetration (ROP) is critical for a cost-effective and safe drilling operation. While different techniques have been used to achieve this goal, each approach has limitations, prompting researchers to seek solutions. This study’s objective is to conduct the strategy of combining the Bourgoyne and Young (BYM) ROP equations with Bagging Tree regression in a southern Iraqi field. Although BYM equations are commonly used and widespread to estimate drilling rates, they need more specific drilling parameters to capture different ROP complexities. The Bagging Tree algorithm, a random forest variant, addresses these limitations by blending domain kno</p> ... Show More
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