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jih-3467
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
Mon Jan 01 2024
Journal Name
Bio Web Of Conferences
An overview of machine learning classification techniques
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Machine learning (ML) is a key component within the broader field of artificial intelligence (AI) that employs statistical methods to empower computers with the ability to learn and make decisions autonomously, without the need for explicit programming. It is founded on the concept that computers can acquire knowledge from data, identify patterns, and draw conclusions with minimal human intervention. The main categories of ML include supervised learning, unsupervised learning, semisupervised learning, and reinforcement learning. Supervised learning involves training models using labelled datasets and comprises two primary forms: classification and regression. Regression is used for continuous output, while classification is employed

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Publication Date
Wed Aug 30 2023
Journal Name
Iraqi Journal Of Science
Review of Smishing Detection Via Machine Learning
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     Smishing is a cybercriminal attack targeting mobile Short Message Service (SMS) devices that contains a malicious link, phone number, or email. The attacker intends to use this message to steal the victim's sensitive information, such as passwords, bank account details, and credit cards. One method of combating smishing is to raise awareness and educate users about the various tactics used by SMS phishers. But even so, this method has been criticized for becoming inefficient because smishing tactics are continually evolving. A more promising anti-smishing method is to use machine learning. This paper introduces a number of machine learning algorithms that can be used for detecting smishing. Furthermore, the differences and simil

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Publication Date
Mon Nov 30 2020
Journal Name
Journal Of Economics And Administrative Sciences
Evaluating Quality of Control Policies and Procedures for Banking Transactions Using the Non-application Gap Model to Enhance Financial Reporting Requirements Applied Study in an Iraqi Private Bank
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The research aims to enhance the level of evaluation of the performance of banking transactions control policies and procedures. The research is based on the following hypothesis: efficient transactions control policies and procedures contribute enhancing financial reporting, by assessing non-application gap of those policies and procedures in a manner that helps to prevent, discover, and correct material misstatementsThe researchers designed an examination list that includes the control policies and procedures related to the transactions, as a guide to the bank audit program prepared by the Federal Financial Supervision Bureau. The research methodology is

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Publication Date
Fri Feb 01 2019
Journal Name
Journal Of Economics And Administrative Sciences
Work pressure of the administrative and academic members of Biskra University, its sources and its relation to some personal and functional variables
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  The study aimed to highlight the reality of the functional pressures with its dimensions (role ambiguity, role conflict, role burden, glass ceiling, and discrimination in composition). The researchers also relied on the questionnaire as a essential tool for data collection. The field study was conducted at the University of Mohammed Khiedr - Biskra -, the study was conducted on the basis of the total survey, which included all the workers of the 6 faculties of Biskra University (523 female employees).

     After the analyzing of the data using the version 21 of the statistical program Spss, The study reached a number of results, the most of them is the low level of the functiona

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Publication Date
Fri Jan 01 2021
Journal Name
International Journal Of Agricultural And Statistical Sciences
EFFECT OF IRRIGATION UNIFORMITY AND EFFICIENCY ON WATER CONSUMPTION, YIELD OF MAIZE USING DIFFERENT IRRIGATION AND CULTIVATION METHODS
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Two field experiments were carried out for cultivating yellow maize crop Zea mays L. during the autumn planting season 2019 in two sites with soils of different textures. The first site is a loamy texture in one of the fields of the Medhatia Agriculture Division, Babylon Governorate. The second was silty loam by an alluvial mixture in one of the fields of Al-Nouriah Research Station, Ministry of Agriculture located in Al-Nouriah sub-district, Al-Qadisiyah governorate. It was found through the results that the uniformity, efficiency, and adequacy of the irrigation efficiency of the sprinkler irrigation method is better than that of the sprinkler irrigation method, and it ranged between (88.6-88.7) for uniformity and (84-86)% of the irrigatio

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Publication Date
Fri Jul 01 2016
Journal Name
Journal Of Engineering
Determination of Mono-crystalline Silicon Photovoltaic Module Parameters Using Three Different Methods
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For modeling a photovoltaic module, it is necessary to calculate the basic parameters which control the current-voltage characteristic curves, that is not provided by the manufacturer. Generally, for mono crystalline silicon module, the shunt resistance is generally high, and it is neglected in this model. In this study, three methods are presented for four parameters model. Explicit simplified method based on an analytical solution, slope method based on manufacturer data, and iterative method based on a numerical resolution. The results obtained for these methods were compared with experimental measured data. The iterative method was more accurate than the other two methods but more complexity. The average deviation of

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Publication Date
Sun Jul 04 2021
Journal Name
Journal Of Interdisciplinary Mathematics
Comparison the solutions for some kinds of differential equations using iterative methods
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This manuscript presents several applications for solving special kinds of ordinary and partial differential equations using iteration methods such as Adomian decomposition method (ADM), Variation iterative method (VIM) and Taylor series method. These methods can be applied as well as to solve nonperturbed problems and 3rd order parabolic PDEs with variable coefficient. Moreover, we compare the results using ADM, VIM and Taylor series method. These methods are a commination of the two initial conditions.

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Publication Date
Wed Dec 30 2020
Journal Name
Iraqi Journal Of Science
A Comparison of Different Estimation Methods to Handle Missing Data in Explanatory Variables
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Missing data is one of the problems that may occur in regression models. This problem is usually handled by deletion mechanism available in statistical software. This method reduces statistical inference values because deletion affects sample size. In this paper, Expectation Maximization algorithm (EM), Multicycle-Expectation-Conditional Maximization algorithm (MC-ECM), Expectation-Conditional Maximization Either (ECME), and Recurrent Neural Networks (RNN) are used to estimate multiple regression models when explanatory variables have some missing values. Experimental dataset were generated using Visual Basic programming language with missing values of explanatory variables according to a missing mechanism at random general pattern and s

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Publication Date
Sun Apr 16 2023
Journal Name
Iraqi Journal For Computer Science And Mathematics
Some Methods to Estimate the Parameters of Generalized Exponential Rayleigh Model by Simulation
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This paper shews how to estimate the parameter of generalized exponential Rayleigh (GER) distribution by three estimation methods. The first one is maximum likelihood estimator method the second one is moment employing estimation method (MEM), the third one is rank set sampling estimator method (RSSEM)The simulation technique is used for all these estimation methods to find the parameters for generalized exponential Rayleigh distribution. Finally using the mean squares error criterion to compare between these estimation methods to find which of these methods are best to the others

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Publication Date
Fri Dec 01 2017
Journal Name
Journal Of Economics And Administrative Sciences
Compare Linear Progamming With Other Methods to Finding Optimal Solution for Transportation Problem
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The researcher studied transportation problem because it's great importance in the country's economy. This paper which ware studied several ways to find a solution closely to the optimization, has applied these methods to the practical reality by taking one oil derivatives which is benzene product, where the first purpose of this study is, how we can reduce the total costs of transportation for product of petrol from warehouses in the province of Baghdad, to some stations in the Karsh district and Rusafa in the same province. Secondly, how can we address the Domandes of each station by required quantity which is depending on absorptive capacity of the warehouses (quantities supply), And through r

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