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Fruit classification by assessing slice hardness based on RGB imaging. Case study: apple slices
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Correct grading of apple slices can help ensure quality and improve the marketability of the final product, which can impact the overall development of the apple slice industry post-harvest. The study intends to employ the convolutional neural network (CNN) architectures of ResNet-18 and DenseNet-201 and classical machine learning (ML) classifiers such as Wide Neural Networks (WNN), Naïve Bayes (NB), and two kernels of support vector machines (SVM) to classify apple slices into different hardness classes based on their RGB values. Our research data showed that the DenseNet-201 features classified by the SVM-Cubic kernel had the highest accuracy and lowest standard deviation (SD) among all the methods we tested, at 89.51 %  1.66 %. This classifier has proved to be the best compared to the others with two features, DenseNet-201 and ResNet-18, along with WNN, NB, and SVM (cubic and linear) kernels. MSC 2010: 68T45, 68U10, 65G20

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Publication Date
Fri Jan 01 2021
Journal Name
Brazilian Dental Science
Assessing the level and diagnostic accuracy of osteopontin and oral health status in periodontitis patients with/without Type-2 Diabetes Mellitus
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Publication Date
Thu Dec 24 2020
Journal Name
Psychology And Education
A Proposed Programme Based On Sensory Integration Theory For Remediating Some Development Learning Disabilities Among Children
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The current research aims to prepare a proposed Programmebased sensory integration theory for remediating some developmental learning disabilities among children, researchers prepared a Programme based on sensory integration through reviewing studies related to the research topic that can be practicedby some active teaching strategies (cooperative learning, peer learning, Role-playing, and educational stories). The Finalformat consists of(39) training sessions.

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Publication Date
Sun Jun 20 2021
Journal Name
Baghdad Science Journal
Multifactor Algorithm for Test Case Selection and Ordering
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Regression testing being expensive, requires optimization notion. Typically, the optimization of test cases results in selecting a reduced set or subset of test cases or prioritizing the test cases to detect potential faults at an earlier phase. Many former studies revealed the heuristic-dependent mechanism to attain optimality while reducing or prioritizing test cases. Nevertheless, those studies were deprived of systematic procedures to manage tied test cases issue. Moreover, evolutionary algorithms such as the genetic process often help in depleting test cases, together with a concurrent decrease in computational runtime. However, when examining the fault detection capacity along with other parameters, is required, the method falls sh

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Publication Date
Tue Dec 30 2008
Journal Name
Al-kindy College Medical Journal
Bilateral Giant Fibro Adenoma of Breast (Case Report)
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Fibro-adenoma is the most common lesion of the breast, it occurs in25%of asymptomatic women (1,2 )
It is usually a disease of early reproductive life, the peak incidence is between the ages15 and 35 years.(3,4) It presents as firm highly mobile, non tender mass .(5)
Less than 5% of fibro-adenomas grow rapidly and display the clinical and histologic characteristics of giant fibro-adenoma which is defined as a-tumour either having a diameter greater than 5 cm. And /or amass weighing more than 500 grams, and are conventionally a benign tumor of breast.(6)
Giant fibro-adenomas appear as well-circumscribed but not encapsulated masses on mammography and solid and the texture is homogenous and hypoechoic with low level echoes on U/S. (

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Publication Date
Sun Apr 30 2023
Journal Name
Al-kindy College Medical Journal
Comparison between Reference Infliximab (Remicade) and its Biosimilar (Remsima) in Patients with Ankylosing Spondylitis: A Field-based Pharmacoeconomic Study
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Background: Ankylosing spondylitis is a chronic inflammatory disease that mostly involves the spine and sacroiliac joints. It is associated with a decreased quality of life. Biological medicines such as infliximab and its biosimilar are the mainstay treatments for active ankylosing spondylitis.

Objective: The study objective was to conduct a pharmacoeconomic study comparing the cost-effectiveness of the reference infliximab with its biosimilar in ankylosing spondylitis patients visiting public hospitals.

Subjects and Method: This is a two-center pharmacoeconomic study performed at two large teaching governmental hospitals in Baghdad, Iraq, which s

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Publication Date
Wed Dec 01 2021
Journal Name
Computers & Electrical Engineering
Utilizing different types of deep learning models for classification of series arc in photovoltaics systems
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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
Fri Mar 29 2024
Journal Name
Iraqi Journal Of Science
Evaluating the Performance and Behavior of CNN, LSTM, and GRU for Classification and Prediction Tasks
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     Deep learning (DL) plays a significant role in several tasks, especially classification and prediction. Classification tasks can be efficiently achieved via convolutional neural networks (CNN) with a huge dataset, while recurrent neural networks (RNN) can perform prediction tasks due to their ability to remember time series data. In this paper, three models have been proposed to certify the evaluation track for classification and prediction tasks associated with four datasets (two for each task). These models are CNN and RNN, which include two models (Long Short Term Memory (LSTM)) and GRU (Gated Recurrent Unit). Each model is employed to work consequently over the two mentioned tasks to draw a road map of deep learning mod

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Publication Date
Sat Jul 01 2017
Journal Name
Journal Of Construction Engineering And Management
Identification, Quantification, and Classification of Potential Safety Risk for Sustainable Construction in the United States
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Publication Date
Fri Jan 31 2025
Journal Name
Aip Conference Proceedings
Classification of oral cavity cancer using linear discriminant analysis (LDA) and principal component analysis (PCA)
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