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Regression shrinkage and selection variables via an adaptive elastic net model
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Abstract<p>In this paper, a new method of selection variables is presented to select some essential variables from large datasets. The new model is a modified version of the Elastic Net model. The modified Elastic Net variable selection model has been summarized in an algorithm. It is applied for Leukemia dataset that has 3051 variables (genes) and 72 samples. In reality, working with this kind of dataset is not accessible due to its large size. The modified model is compared to some standard variable selection methods. Perfect classification is achieved by applying the modified Elastic Net model because it has the best performance. All the calculations that have been done for this paper are in R program by using some existing packages.</p>
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Publication Date
Fri Dec 09 2016
Journal Name
Éditions Universitaires EuropÉennes Est Gestionée Par Omniscriptum Management Gmbh
Adaptive Modeling of Urban Dynamics With Mobile Phone Database
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The communication networks (mobile phone networks, social media platforms) produce digital traces from their usages. This type of information help to understand and analyze the human mobility in very accurate way. By these analyzes over cities, it can give powerful data on daily citizen activities, urban planners have in that way, relevant indications for decision making on design and development. As well as, the Call detail Records (CDRs) provides valuable spatiotemporal data at the level of citywide or even nationwide. The CDRs could be analyzed to extract the life patterns and individuals mobility in an observed urban area and during ephemeral events. Whereas, their analysis gives conceptual views about human density and mobility pattern

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Publication Date
Sun Dec 01 2002
Journal Name
Iraqi Journal Of Physics
A Hyperbolic Potential Field Model for Designing an Einzel Lens of Low Aberrations
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An analytical model in the form of a hyperbolic function has been suggested for the axial potential distribution of an electrostatic einzel lens. With the aid of this hyperbolic model the relative optical parameters have been computed and investigated in detail as a function of the electrodes voltage ratio for various trajectories of an accelerated charged-particles beam. The electrodes voltage ratio covered a wide range where the lens may be operated at accelerating and decelerating modes. The results have shown that the proposed hyperbolic field has the advantages of producing low aberrations under various magnification conditions and operational modes. The electrodes profile and their three-dimensional diagram have been determined whi

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Publication Date
Thu Jun 29 2023
Journal Name
International Journal Of Nonlinear Analysis And Applications (ijnaa)
Applying a suitable approximate-simulation technique of an epidemic model with random parameters
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Because the Coronavirus epidemic spread in Iraq, the COVID-19 epidemic of people quarantined due to infection is our application in this work. The numerical simulation methods used in this research are more suitable than other analytical and numerical methods because they solve random systems. Since the Covid-19 epidemic system has random variables coefficients, these methods are used. Suitable numerical simulation methods have been applied to solve the COVID-19 epidemic model in Iraq. The analytical results of the Variation iteration method (VIM) are executed to compare the results. One numerical method which is the Finite difference method (FD) has been used to solve the Coronavirus model and for comparison purposes. The numerical simulat

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Publication Date
Sat Dec 14 2019
Journal Name
International Journal On Emerging Technologies
Utilizing an Artificial Neural Network Model to Predict Bearing Capacity of Stone Columns
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ABSTRACT: Ultimate bearing capacity of soft ground reinforced with stone column was recently predicted using various artificial intelligence technologies such as artificial neural network because of all the advantages that they can offer in minimizing time, effort and cost. As well as, most of applied theories or predicted formulas deduced analytically from previous studies were feasible only for a particular testing environment and do not match other field or laboratory datasets. However, the performance of such techniques depends largely on input parameters that really affect the target output and missing of any parameter can lead to inaccurate results and give a false indicator. In the current study, data were collected from previous rel

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Publication Date
Wed Jun 15 2022
Journal Name
Journal Of Sensors
A Modern Approach towards an Industry 4.0 Model: From Driving Technologies to Management
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Every so often, a confluence of novel technologies emerges that radically transforms every aspect of the industry, the global economy, and finally, the way we live. These sharp leaps of human ingenuity are known as industrial revolutions, and we are currently in the midst of the fourth such revolution, coined Industry 4.0 by the World Economic Forum. Building on their guideline set of technologies that encompass Industry 4.0, we present a full set of pillar technologies on which Industry 4.0 project portfolio management rests as well as the foundation technologies that support these pillars. A complete model of an Industry 4.0 factory which relies on these pillar technologies is presented. The full set of pillars encompasses cyberph

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Publication Date
Tue Aug 27 2024
Journal Name
Tem Journal
Preparing the Electrical Signal Data of the Heart by Performing Segmentation Based on the Neural Network U-Net
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Research on the automated extraction of essential data from an electrocardiography (ECG) recording has been a significant topic for a long time. The main focus of digital processing processes is to measure fiducial points that determine the beginning and end of the P, QRS, and T waves based on their waveform properties. The presence of unavoidable noise during ECG data collection and inherent physiological differences among individuals make it challenging to accurately identify these reference points, resulting in suboptimal performance. This is done through several primary stages that rely on the idea of preliminary processing of the ECG electrical signal through a set of steps (preparing raw data and converting them into files tha

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Publication Date
Sat May 01 2021
Journal Name
Materials Today: Proceedings
WITHDRAWN: Application of net pay for reservoir characterization in carbonate reservoir rock – Case study: South-eastern of Iraq
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Publication Date
Mon Nov 11 2019
Journal Name
Spe
Modeling Rate of Penetration using Artificial Intelligent System and Multiple Regression Analysis
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Abstract<p>Over the years, the prediction of penetration rate (ROP) has played a key rule for drilling engineers due it is effect on the optimization of various parameters that related to substantial cost saving. Many researchers have continually worked to optimize penetration rate. A major issue with most published studies is that there is no simple model currently available to guarantee the ROP prediction.</p><p>The main objective of this study is to further improve ROP prediction using two predictive methods, multiple regression analysis (MRA) and artificial neural networks (ANNs). A field case in SE Iraq was conducted to predict the ROP from a large number of parame</p> ... Show More
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Publication Date
Tue Oct 23 2018
Journal Name
Journal Of Economics And Administrative Sciences
Use projection pursuit regression and neural network to overcome curse of dimensionality
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Abstract

This research aim to overcome the problem of dimensionality by using the methods of non-linear regression, which reduces the root of the average square error (RMSE), and is called the method of projection pursuit regression (PPR), which is one of the methods for reducing dimensions that work to overcome the problem of dimensionality (curse of dimensionality), The (PPR) method is a statistical technique that deals with finding the most important projections in multi-dimensional data , and With each finding projection , the data is reduced by linear compounds overall the projection. The process repeated to produce good projections until the best projections are obtained. The main idea of the PPR is to model

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Publication Date
Sun Feb 25 2024
Journal Name
Baghdad Science Journal
Hybrid Framework To Exclude Similar and Faulty Test Cases In Regression Testing
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Regression testing is a crucial phase in the software development lifecycle that makes sure that new changes/updates in the software system don’t introduce defects or don’t affect adversely the existing functionalities. However, as the software systems grow in complexity, the number of test cases in regression suite can become large which results into more testing time and resource consumption. In addition, the presence of redundant and faulty test cases may affect the efficiency of the regression testing process. Therefore, this paper presents a new Hybrid Framework to Exclude Similar & Faulty Test Cases in Regression Testing (ETCPM) that utilizes automated code analysis techniques and historical test execution data to

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