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Enhanced Support Vector Machine Methods Using Stochastic Gradient Descent and Its Application to Heart Disease Dataset
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Support Vector Machines (SVMs) are supervised learning models used to examine data sets in order to classify or predict dependent variables. SVM is typically used for classification by determining the best hyperplane between two classes. However, working with huge datasets can lead to a number of problems, including time-consuming and inefficient solutions. This research updates the SVM by employing a stochastic gradient descent method. The new approach, the extended stochastic gradient descent SVM (ESGD-SVM), was tested on two simulation datasets. The proposed method was compared with other classification approaches such as logistic regression, naive model, K Nearest Neighbors and Random Forest. The results show that the ESGD-SVM has a very high accuracy and is quite robust. ESGD-SVM is used to analyze the heart disease dataset downloaded from Harvard Dataverse. The entire analysis was performed using the program R version 4.3.

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Publication Date
Fri Nov 01 2019
Journal Name
Journal Of Engineering
Analysis of Shell and Double Concentric Tube Heat Exchanger Using CFD Application
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This study focuses on CFD analysis in the field of the shell and double concentric tube heat exchanger. A commercial CFD package was used to resolve the flow and temperature fields inside the shell and tubes of the heat exchanger used. Simulations by CFD are performed for the single shell and double concentric tube.

This heat exchanger included 16 tubes and 20 baffles. The shell had a length of 1.18 m and its diameter was 220 mm. Solid Works 2014, ANSYS 15.0 software was used to analyze the fields of flow and temperature inside the shell and the tubes. The RNG k-ε model was used and it provided good results. Coarse and fine meshes were investigated, showing that aspect ratio has no significant effect. 14 million

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Publication Date
Sun Dec 12 2010
Journal Name
Alustath Journal For Human And Social Sciences
Suggested Approach to deal with Multicollinearity Problem – with Application –
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This research introduce a study with application on Principal Component Regression obtained from some of the explainatory variables to limitate Multicollinearity problem among these variables and gain staibilty in their estimations more than those which yield from Ordinary Least Squares. But the cost that we pay in the other hand losing a little power of the estimation of the predictive regression function in explaining the essential variations. A suggested numerical formula has been proposed and applied by the researchers as optimal solution, and vererifing the its efficiency by a program written by the researchers themselves for this porpuse through some creterions: Cumulative Percentage Variance, Coefficient of Determination, Variance

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Publication Date
Tue Feb 01 2022
Journal Name
Baghdad Science Journal
Application of Groebner Bases to Study a Communication System
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This paper introduces a relationship between the independence of polynomials associated with the links of the network, and the Jacobian determinant of these polynomials. Also, it presents a way to simplify a given communication network through an algorithm that splits the network into subnets and reintegrates them into a network that is a general representation or model of the studied network. This model is also represented through a combination of polynomial equations and uses Groebner bases to reach a new simplified network equivalent to the given network, which may make studying the ability to solve the problem of network coding less expensive and much easier.

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Publication Date
Wed Jan 01 2014
Journal Name
Journal Of Thi – Qar Science
Enhanced of the Two photon Absorption in Nanostructure Wide Band gap Semiconductor CdS using femtosecond Laser
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We observed strong nonlinear absorption in the CdS nanoparticles of dimension in the range 50-100 nm when irradiant with femtosecond pulsed laser at 800 nm and 120 GW/cm 2 irradiance intensity. The repetition rate and average power were 250 kHz and

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Publication Date
Thu Feb 07 2019
Journal Name
Iraqi Journal Of Laser
Laser Enhanced Photocatalyic Degradation of Methylene blue using Nanostructured ZnO Catalyst based on Interfacial Charge Transfer
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In this research, annealed nanostructured ZnO catalyst water putrefaction system was built using sun light and different wavelength lasers as stimulating light sources to enhance photocatalytic degradation activity of methylene blue (MB) dye as a model based on interfacial charges transfer. The structural, crystallite size, morphological, particle size, optical properties and degradation ability of annealed nanostructured ZnO were characterized by X-Ray Diffraction (XRD), Atomic Force Microscopy (AFM) and UV-VIS Spectrometer, respectively. XRD results demonstrated a pure crystalline hexagonal wurtzite with crystalline size equal to 23 nm. From AFM results, the average particle size was 79.25nm. All MB samples and MB with annealed nanostr

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Publication Date
Tue Dec 03 2013
Journal Name
Baghdad Science Journal
Satellite Images Unsupervised Classification Using Two Methods Fast Otsu and K-means
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Publication Date
Wed Feb 14 2024
Journal Name
2nd International Conference For Engineering Sciences And Information Technology (esit 2022): Esit2022 Conference Proceedings
Segmentation moon images using different segmentation methods and isolate the lunar craters
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Segmentation is the process of partition digital images into different parts depending on texture, color, or intensity, and can be used in different fields in order to segment and isolate the area to be partitioned. In this work images of the Moon obtained through observations in Astronomy and space dep. College of science university of Baghdad by ( Toward space telescopes and widespread used of a CCD camera) . Different segmentation methods were used to segment lunar craters. Different celestial objects cause craters when they crash into the surface of the Moon like asteroids and meteorites. Thousands of craters appears on the Moon's surface with ranges in size from meter to many kilometers, it provide insights into the age and geology

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Publication Date
Mon Jan 01 2024
Journal Name
Fusion: Practice And Applications
Optimizing Task Scheduling and Resource Allocation in Computing Environments using Metaheuristic Methods
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Optimizing system performance in dynamic and heterogeneous environments and the efficient management of computational tasks are crucial. This paper therefore looks at task scheduling and resource allocation algorithms in some depth. The work evaluates five algorithms: Genetic Algorithms (GA), Particle Swarm Optimization (PSO), Ant Colony Optimization (ACO), Firefly Algorithm (FA) and Simulated Annealing (SA) across various workloads achieved by varying the task-to-node ratio. The paper identifies Finish Time and Deadline as two key performance metrics for gauging the efficacy of an algorithm, and a comprehensive investigation of the behaviors of these algorithms across different workloads was carried out. Results from the experiment

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Publication Date
Tue Jan 17 2017
Journal Name
International Journal Of Science And Research (ijsr)
Detection System of Varicose Disease using Probabilistic Neural Network
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Publication Date
Sat Nov 01 2014
Journal Name
I-manager's Journal On Information Technology
AN ENHANCED METHOD FOR SPRITE EXTRACTING
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The extracting of personal sprite from the whole image faced many problems in separating the sprite edge from the unneeded parts, some image software try to automate this process, but usually they couldn't find the edge or have false result. In this paper, the authors have made an enhancement on the use of Canny edge detection to locate the sprite from the whole image by adding some enhancement steps by using MATLAB. Moreover, remove all the non-relevant information from the image by selecting only the sprite and place it in a transparent background. The results of comparing the Canny edge detection with the proposed method shows improvement in the edge detection.