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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 spent to achieve the best classification accuracy.

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Publication Date
Wed Aug 28 2019
Journal Name
Journal Of Engineering
Integrating of Lean Six Sigma Methodology and Ergonomics Principles for Improvement in an Assembly Industrial Workstation
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Lean Six Sigma methodologies and Ergonomics principles are the main pillars of this work given their importance in the implementation of continuous improvement in assembly workstations design. When looking at the introduction of the Ergonomics that has been affected by the integration of the Lean and Six Sigma for improvements, it is necessary to understand why these methodologies belong to each other and how they can be handled in the industrial field. The aim of the work seeks towards the impact of analyzing the integration of the basics tools of Lean and Six Sigma that enhanced Ergonomics highlighted the importance of using the priority matrix in the selection of the priority criteria. Two models of a system based on

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Publication Date
Wed Nov 17 2021
Journal Name
Periodicals Of Engineering And Natural Sciences (pen)
Pearson coefficient matrix for studying the correlation of community detection scores in multi-objective evolutionary algorithm
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Publication Date
Mon Jun 01 2020
Journal Name
Journal Of Engineering
The The Use of Copper and Aluminum Electrodes for Energy Production in a Microbial Fuel Cell
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Microbial fuel cell is a device that uses the microorganism metabolism for the production of electricity under specific operating conditions. Double chamber microbial fuel cell was tested for the use of two cheap electrode materials copper and aluminum for the production of electricity under different operating conditions. The investigated conditions were concentration of microorganism (yeast) (0.5- 2 g/l), solutions temperature (33-45 oC) and concentration of glucose as a substrate (1.5- 6 g/l). The results demonstrated that copper electrode exhibit good performance while the performance of aluminum is poor. The electricity is generated with and without the addition of substrate. Addition of glucose substrate

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Publication Date
Sun Jan 01 2023
Journal Name
Open Engineering
Optimizing and coordinating the location of raw material suitable for cement manufacturing in Wasit Governorate, Iraq
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Abstract<p>The cement industry is considered one of the strategic industries, because it is directly related to construction work and cement is used as a hydraulic binder. However, it is a simple industry compared to major industries and depends on the availability of the necessary raw materials. This study focuses on optimizing and coordinating the location of raw materials needed for the cement manufacturing in Wasit Governorate in Iraq. Field works include detailed reconnaissance, topographic work, and description and sampling of 24 lithological sections that represent the carbonate deposits, which crop out in the area. The investigated area has the following specifications: The weighted aver</p> ... Show More
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Publication Date
Wed Aug 18 2021
Journal Name
Chemical Papers
Analytical methods for the identification of micro/nano metals in e-cigarette emission samples: a review
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Publication Date
Sun Dec 31 2023
Journal Name
Azerbaijan Pharmaceutical And Pharmacotherapy J
Prevalence and Contributed Factors for Varicose Veins in Intensive Care Unit Nurses at Baghdad Teaching Hospitals
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Background: Varicose vein (VV) is a common problem that mostly occurs in legs. This medical condition can influence the quality of life and working condition of nurses. Aim of the study: To estimate the prevalence of lower limbs varicosity and its associated risk factors among nurses. Methods: This a cross-sectional descriptive study was carried out among 100 nurses working Baghdad Teaching Hospital, Surgical Specialties Hospital, and Al- Kidney Teaching Hospital, Baghdad, Iraq from January 1st to May 10th, 2022. The participants were recruited in the study using systematic random sampling. The Occupational Sitting and Physical Activity and Aberdeen Varicose Vein Questionnaires were used for data gathering. Results: The prevalence o

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Publication Date
Sat Dec 27 2025
Journal Name
International Journal Of Corrosion And Scale Inhibition
Sustainable corrosion inhibition using Aloe vera extract and its nanocomposites for carbon steel (CS1137) in seawater
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Two nanocomposite corrosion inhibitors were synthesized from Aloe vera extract: one incorporating sodium thiosulfate and the other silver nitrate. Both nanocomposites were subjected to structural characterization using atomic force microscopy (AFM), which revealed distinct morphological features. The sodium thiosulfate-based nanocomposite exhibited uniform and well-dispersed nanoparticles with an average size of 47.51 nm, suggesting a stable and homogeneous distribution. In contrast, the silver nitrate-based nanocomposite displayed slightly larger particles with an average diameter of 58.34 nm, indicating a tendency toward moderate aggregation. The corrosion inhibition performance of these nanocomposites for carbon steel (CS1137) was invest

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Publication Date
Fri Dec 01 2023
Journal Name
Baghdad Science Journal
Synthesis of Carbon Nanotubes Using Modified Hummers Method for Cathode Electrodes in Dye-Sensitized Solar Cell
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      In this research, carbon nanotubes (CNTs) is prepared  through the Hummers method with a slight change in some of the work steps, thus, a new method has been created for preparing carbon nanotubes which is similar to the original Hummers method that is used to prepare graphene oxide. Then, the suspension carbon nanotubes is transferred to a simple electrode position platform consisting of two electrodes and the cell body for the coating and reduction of the carbon nanotubes on ITO glass which represents the cathode electrode while platinum represents the anode electrode. The deposited layer of carbon nanotubes is examined through the scanning electron microscope technique (SEM), and the images throughout the research show the

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Publication Date
Wed Apr 12 2023
Journal Name
Iraqi Postgraduate Medical Journal
The Accuracy of Electrocardiographic Criteria for Predicting Left Ventricular Hypertrophy in adult Patients with Systemic Hypertension
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ABSTRACT: BACKGROUND: Left ventricular hypertrophy is a significant risk factor for cardiovascular complications such as ischemic heart disease, heart failure, sudden death, atrial fibrillation, and stroke. A proper non-expensive tool is required for detection of this pathology. Different electrocardiographic (ECG) criteria were investigated; however, the results were conflicting regarding the accuracy of these criteria. OBJECTIVE: To assess the accuracy of three electrocardiographic criteria in diagnosis of left ventricular hypertrophy in adult patients with hypertension using echocardiography as a reference test. PATIENTS AND METHODS: This is a hospital-based cross sectional observational study which included 340 adult patients with a his

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Publication Date
Fri Sep 26 2025
Journal Name
Applied Data Science And Analysis
Deep Learning in Genomic Sequencing: Advanced Algorithms for HIV/AIDS Strain Prediction and Drug Resistance Analysis
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Genome sequencing has significantly improved the understanding of HIV and AIDS through accurate data on viral transmission, evolution and anti-therapeutic processes. Deep learning algorithms, like the Fined-Tuned Gradient Descent Fused Multi-Kernal Convolutional Neural Network (FGD-MCNN), can predict strain behaviour and evaluate complex patterns. Using genotypic-phenotypic data obtained from the Stanford University HIV Drug Resistance Database, the FGD-MCNN created three files covering various antiretroviral medications for HIV predictions and drug resistance. These files include PIs, NRTIs and NNRTIs. FGD-MCNNs classify genetic sequences as vulnerable or resistant to antiretroviral drugs by analyzing chromosomal information and id

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