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Improved Merging Multi Convolutional Neural Networks Framework of Image Indexing and Retrieval
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Background/Objectives: The purpose of current research aims to a modified image representation framework for Content-Based Image Retrieval (CBIR) through gray scale input image, Zernike Moments (ZMs) properties, Local Binary Pattern (LBP), Y Color Space, Slantlet Transform (SLT), and Discrete Wavelet Transform (DWT). Methods/Statistical analysis: This study surveyed and analysed three standard datasets WANG V1.0, WANG V2.0, and Caltech 101. The features an image of objects in this sets that belong to 101 classes-with approximately 40-800 images for every category. The suggested infrastructure within the study seeks to present a description and operationalization of the CBIR system through automated attribute extraction system premised on CNN infrastructure. Findings: The results acquired through the investigated CBIR system alongside the benchmarked results have clearly indicated that the suggested technique had the best performance with the overall accuracy at 88.29% as opposed to the other sets of data adopted in the experiments. The outstanding results indicate clearly that the suggested method was effective for all the sets of data. Improvements/Applications: As a result of this study, it was found the revealed that the multiple image representation was redundant for extraction accuracy, and the findings from the study indicated that automatically retrieved features are capable and reliable in generating accurate outcomes.

Publication Date
Mon Jul 31 2017
Journal Name
Journal Of Engineering
Rigid Trunk Sewer Deterioration Prediction Models using Multiple Discriminant and Neural Network Models in Baghdad City, Iraq
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Publication Date
Fri Feb 14 2020
Journal Name
Progress In Industrial Ecology, An International Journal
3D image reconstruction from its 2D projection - a simulation study
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A simulation study of using 2D tomography to reconstruction a 3D object is presented. The 2D Radon transform is used to create a 2D projection for each slice of the 3D object at different heights. The 2D back-projection and the Fourier slice theorem methods are used to reconstruction each 2D projection slice of the 3D object. The results showed the ability of the Fourier slice theorem method to reconstruct the general shape of the body with its internal structure, unlike the 2D Radon method, which was able to reconstruct the general shape of the body only because of the blurring artefact, Beside that the Fourier slice theorem could not remove all blurring artefact, therefore, this research, suggested the threshold technique to eliminate the

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Publication Date
Thu Feb 01 2018
Journal Name
Applied Mathematical Modelling
Identification of a multi-dimensional space-dependent heat source from boundary data
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Publication Date
Sun Dec 01 2024
Journal Name
Chilean Journal Of Statistics
A method of multi-dimensional variable selection for additive partial linear models.
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In high-dimensional semiparametric regression, balancing accuracy and interpretability often requires combining dimension reduction with variable selection. This study intro- duces two novel methods for dimension reduction in additive partial linear models: (i) minimum average variance estimation (MAVE) combined with the adaptive least abso- lute shrinkage and selection operator (MAVE-ALASSO) and (ii) MAVE with smoothly clipped absolute deviation (MAVE-SCAD). These methods leverage the flexibility of MAVE for sufficient dimension reduction while incorporating adaptive penalties to en- sure sparse and interpretable models. The performance of both methods is evaluated through simulations using the mean squared error and variable selection cri

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Publication Date
Fri Oct 20 2023
Journal Name
Al-ameed Journal For Medical Research And Health Sciences
Perceptions of Nursing Students about COVID-19 Transmission: A Multi University Study
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Publication Date
Fri Jan 01 2016
Journal Name
Aip Conference Proceedings
Application of simulated annealing to solve multi-objectives for aggregate production planning
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Aggregate production planning (APP) is one of the most significant and complicated problems in production planning and aim to set overall production levels for each product category to meet fluctuating or uncertain demand in future. and to set decision concerning hiring, firing, overtime, subcontract, carrying inventory level. In this paper, we present a simulated annealing (SA) for multi-objective linear programming to solve APP. SA is considered to be a good tool for imprecise optimization problems. The proposed model minimizes total production and workforce costs. In this study, the proposed SA is compared with particle swarm optimization (PSO). The results show that the proposed SA is effective in reducing total production costs and req

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Publication Date
Sun Jul 09 2023
Journal Name
Journal Of Engineering
Development a Proposed System of Organization Structure to Management Multi Construction Projects
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The purpose of this study is aimed to lay down an arranged platform suited to Iraqi constructional associations which in charge to carry out multi constructional projects, as it fulfilled management requirements and supervising, so that low - cost projects will be controlled in due term and quality. Based on primary info and observed data collected, the study thesis has been formulated in this way: Iraqi constructional sector bodies which are in charge to implement simultaneously multi constructional projects in need to reformulate its organized structure so that it will be more fitted to management and control of these projects. This thesis includes a
theoretical part contained presenting the most important resources locally and int

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Publication Date
Wed Dec 13 2017
Journal Name
Al-khwarizmi Engineering Journal
Multi-Dimensional Angle of Arrival Estimation by Circular Phased Adaptive Array Antennas
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In this paper the use of a circular array antenna with adaptive system in conjunction with modified Linearly Constrained Minimum Variance Beam forming (LCMVB) algorithm is proposed to meet the requirement of Angle of Arrival (AOA) estimation in 2-D as well as the Signal to Noise Ratio (SNR) of estimated sources (Three Dimensional 3-D estimation), rather than interference cancelation as it is used for. The proposed system was simulated, tested and compared with the modified Multiple Signal Classification (MUSIC) technique for 2-D estimation. The results show the system has exhibited astonishing results for simultaneously estimating 3-D parameters with accuracy approximately equivalent to the MUSIC technique (for estimating elevation and a

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Publication Date
Mon Nov 30 2020
Journal Name
International Journal Of Civil Engineering
Adsorption of Meropenem Antibiotics from Aqueous Solutions on Multi-Walled Carbon Nanotube
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Pharmaceutical-instigated pollution is a major concern, especially in relation to aquatic environments and drugs such as meropenem antibiotics. Adsorbents, such as multi-walled carbon nanotubes, offer potential as means of removing polluting meropenem antibiotics and other similar compounds from water. In order to evaluate the effectiveness of multi-walled carbon nanotubes in this capacity, various experimental parameters, including contact time, initial concentration, pH, temperature and the dose of adsorbent have been investigated. The Langmuir and the Freundlich isotherm models have been used. The data obtained using a modified Langmuir model have been consistent with the experimental ones; the best pH value has been obtained to have the

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Publication Date
Fri Jan 01 2016
Journal Name
Journal Of Engineering
Mobile Position Estimation using Artificial Neural Network in CDMA Cellular Systems
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Using the Neural network as a type of associative memory will be introduced in this paper through the problem of mobile position estimation where mobile estimate its location depending on the signal strength reach to it from several around base stations where the neural network can be implemented inside the mobile. Traditional methods of time of arrival (TOA) and received signal strength (RSS) are used and compared with two analytical methods, optimal positioning method and average positioning method. The data that are used for training are ideal since they can be obtained based on geometry of CDMA cell topology. The test of the two methods TOA and RSS take many cases through a nonlinear path that MS can move through tha

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