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Studying the Classification of Texture Images by K-Means of Co-Occurrence Matrix and Confusion Matrix
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In this research, a group of gray texture images of the Brodatz database was studied by building the features database of the images using the gray level co-occurrence matrix (GLCM), where the distance between the pixels was one unit and for four angles (0, 45, 90, 135). The k-means classifier was used to classify the images into a group of classes, starting from two to eight classes, and for all angles used in the co-occurrence matrix. The distribution of the images on the classes was compared by comparing every two methods (projection of one class onto another where the distribution of images was uneven, with one category being the dominant one. The classification results were studied for all cases using the confusion matrix between every Two cases or two steps (two different angles and for the same number of classes). The agreement percentage between the classification results and the various methods was calculated.

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Publication Date
Mon Dec 05 2022
Journal Name
Baghdad Science Journal
K-Nearest Neighbor Method with Principal Component Analysis for Functional Nonparametric Regression
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This paper proposed a new  method to study functional non-parametric regression data analysis with conditional expectation in the case that the covariates  are functional and the Principal Component Analysis was utilized to de-correlate the multivariate response variables. It  utilized the formula of the Nadaraya Watson estimator (K-Nearest Neighbour (KNN)) for prediction with different types of the semi-metrics, (which are based on Second Derivative and Functional Principal Component Analysis (FPCA))  for measureing the closeness between curves.  Root Mean Square Errors is used for the  implementation of this model which is then compared to the independent response method. R program is used for analysing data. Then, when  the cov

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Publication Date
Sat Jan 01 2022
Journal Name
Turkish Journal Of Physiotherapy And Rehabilitation
classification coco dataset using machine learning algorithms
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In this paper, we used four classification methods to classify objects and compareamong these methods, these are K Nearest Neighbor's (KNN), Stochastic Gradient Descentlearning (SGD), Logistic Regression Algorithm(LR), and Multi-Layer Perceptron (MLP). Weused MCOCO dataset for classification and detection the objects, these dataset image wererandomly divided into training and testing datasets at a ratio of 7:3, respectively. In randomlyselect training and testing dataset images, converted the color images to the gray level, thenenhancement these gray images using the histogram equalization method, resize (20 x 20) fordataset image. Principal component analysis (PCA) was used for feature extraction, andfinally apply four classification metho

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Publication Date
Mon Feb 04 2019
Journal Name
Journal Of The College Of Education For Women
Classification of Rural Road Network in Al-Najaf Governorate
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This study has dealt with, the issue of classification of rural road network , in addition to prepare a suggested for the classification for this network in Iraq , this classification account , the specifications and characteristics of rural roads, population, and the range taking of settlements , then this classification was applied on the rural road network in the Najaf province there are four categories of classification ,the first is major arterial rural roads divided into two major arterial and minor arterial roads , while the second category collected roads which was divided into minor arterial roads and main collected roads. The third category was represented by Local Roads , it has been divided into paved roads and unpaved, the f

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Publication Date
Mon Mar 14 2022
Journal Name
Periodicals Of Engineering And Natural Sciences (pen)
Mathematical simulation of memristive for classification in machine learning
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Publication Date
Thu Mar 01 2018
Journal Name
Journal Of Engineering
Anaerobic Co-digestion of Giant Reed for Biogas Recovery
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This study investigated the feasibility of anaerobic co-digestion of giant reed (GR) inoculated with waste manure as a co-substrate for biogas production. The performance of co-digestion was evaluated in 4 anaerobic digesters operated in batch mode at different conditions. The effects of alkali pretreatment with NaOH (4% w/v) solution, inoculum type, and thermal condition were studied. The results demonstrated that the alkali-pretreatment of GR enhanced the biogas generation by about 15% at mesophilic conditions. Thermophilic conditions enhanced the biogas recovery from both alkali-free and alkali pretreated GR by 15% and 127%, respectively. The kinetic study of the co-digestion process of GR for biogas recovery suggeste

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Publication Date
Sun Jun 23 2019
Journal Name
Journal Of The College Of Basic Education
Viscometric and Activation energy study of PEG 6000 in water, and solution of DMSO with water at 298.15 k, 308.15, 318.‏
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Publication Date
Sat May 01 2021
Journal Name
Journal Of Physics: Conference Series
The effect of the Doping with Cobalt Transition Metal on the Dielectric and Structural Properties of Fe<sub>0.5</sub>Co<sub>x</sub>Mg<sub>0.95-x</sub>O Nanoparticles Synthesized by Sol-Gel Assisted Auto-Combustion
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Abstract<p>The compound Fe<sub>0.5</sub>Co<sub>x</sub>Mg<sub>0.95-x</sub>O where (x= 0.025, 0.05, 0.075, 0.1) was prepared via the sol-gel technique. The crystalline nature of magnesium oxide was studied by X-ray powder diffraction (XRD) analysis, and the size of the sample crystals, ranging between (16.91-19.62nm), increased, while the lattice constant within the band (0.5337-0.4738 nm) decreased with increasing the cobalt concentration. The morphology of the specimens was studied by scanning electron microscopy (SEM) which shows images forming spherical granules in addition to the presence of interconnected chips. The presence of the elements involved in the super</p> ... Show More
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Publication Date
Mon Jul 11 2022
Journal Name
International Journal Of Online And Biomedical Engineering (ijoe)
Dynamic Background Subtraction in Video Surveillance Using Color-Histogram and Fuzzy C-Means Algorithm with Cosine Similarity
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The background subtraction is a leading technique adopted for detecting the moving objects in video surveillance systems. Various background subtraction models have been applied to tackle different challenges in many surveillance environments. In this paper, we propose a model of pixel-based color-histogram and Fuzzy C-means (FCM) to obtain the background model using cosine similarity (CS) to measure the closeness between the current pixel and the background model and eventually determine the background and foreground pixel according to a tuned threshold. The performance of this model is benchmarked on CDnet2014 dynamic scenes dataset using statistical metrics. The results show a better performance against the state-of the art

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Publication Date
Wed May 16 2018
Journal Name
Asian Journal Of Chemistery
Study of Physical and Spectral Properties of Quaternary System of 2,5-Hexadione+Cyclopentanol+Cyclohexanol+3-Heptanol Mixture at 298 K
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Publication Date
Mon Sep 30 2024
Journal Name
Iraqi Journal Of Science
Effect of Atmospheric Mixing on Spectral Reflectivity in Sentinel Images of Baghdad Province
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The lowest layer of the atmosphere is called the atmospheric mixed layer, characterized by small-scale, irregular air motions defined by winds that change in speed and direction. Aerosol radiative effects impact the atmospheric boundary layer (ABL), which holds most aerosols in the lower atmosphere. Aerosol absorption and scattering both lower the quantity of solar energy that reaches the ground, which has an impact on the spectral signature of the land coverings. In this study, 51 locations in downtown Baghdad were chosen for four different types of land cover (water bodies, farms, open areas, and residential areas) for Sentinel 2 satellite imagery, and the time the pictures were taken was 8:00 am ( 22 March, 22 June, 20 September,

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