• Title/Summary/Keyword: Polynomial-based Study

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Using Support Vector Machine to Predict Political Affiliations on Twitter: Machine Learning approach

  • Muhammad Javed;Kiran Hanif;Arslan Ali Raza;Syeda Maryum Batool;Syed Muhammad Ali Haider
    • International Journal of Computer Science & Network Security
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    • v.24 no.5
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    • pp.217-223
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    • 2024
  • The current study aimed to evaluate the effectiveness of using Support Vector Machine (SVM) for political affiliation classification. The system was designed to analyze the political tweets collected from Twitter and classify them as positive, negative, and neutral. The performance analysis of the SVM classifier was based on the calculation of metrics such as accuracy, precision, recall, and f1-score. The results showed that the classifier had high accuracy and f1-score, indicating its effectiveness in classifying the political tweets. The implementation of SVM in this study is based on the principle of Structural Risk Minimization (SRM), which endeavors to identify the maximum margin hyperplane between two classes of data. The results indicate that SVM can be a reliable classification approach for the analysis of political affiliations, possessing the capability to accurately categorize both linear and non-linear information using linear, polynomial or radial basis kernels. This paper provides a comprehensive overview of using SVM for political affiliation analysis and highlights the importance of using accurate classification methods in the field of political analysis.

A Design on Face Recognition System Based on pRBFNNs by Obtaining Real Time Image (실시간 이미지 획득을 통한 pRBFNNs 기반 얼굴인식 시스템 설계)

  • Oh, Sung-Kwun;Seok, Jin-Wook;Kim, Ki-Sang;Kim, Hyun-Ki
    • Journal of Institute of Control, Robotics and Systems
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    • v.16 no.12
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    • pp.1150-1158
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    • 2010
  • In this study, the Polynomial-based Radial Basis Function Neural Networks is proposed as one of the recognition part of overall face recognition system that consists of two parts such as the preprocessing part and recognition part. The design methodology and procedure of the proposed pRBFNNs are presented to obtain the solution to high-dimensional pattern recognition problem. First, in preprocessing part, we use a CCD camera to obtain a picture frame in real-time. By using histogram equalization method, we can partially enhance the distorted image influenced by natural as well as artificial illumination. We use an AdaBoost algorithm proposed by Viola and Jones, which is exploited for the detection of facial image area between face and non-facial image area. As the feature extraction algorithm, PCA method is used. In this study, the PCA method, which is a feature extraction algorithm, is used to carry out the dimension reduction of facial image area formed by high-dimensional information. Secondly, we use pRBFNNs to identify the ID by recognizing unique pattern of each person. The proposed pRBFNNs architecture consists of three functional modules such as the condition part, the conclusion part, and the inference part as fuzzy rules formed in 'If-then' format. In the condition part of fuzzy rules, input space is partitioned with Fuzzy C-Means clustering. In the conclusion part of rules, the connection weight of pRBFNNs is represented as three kinds of polynomials such as constant, linear, and quadratic. Coefficients of connection weight identified with back-propagation using gradient descent method. The output of pRBFNNs model is obtained by fuzzy inference method in the inference part of fuzzy rules. The essential design parameters (including learning rate, momentum coefficient and fuzzification coefficient) of the networks are optimized by means of the Particle Swarm Optimization. The proposed pRBFNNs are applied to real-time face recognition system and then demonstrated from the viewpoint of output performance and recognition rate.

Statistical significance test of polynomial regression equation for Huff's quartile method of design rainfall (설계강우량의 Huff 4분위 방법 다항회귀식에 대한 유의성 검정)

  • Park, Jinhee;Lee, Jaejoon;Lee, Sungho
    • Journal of Korea Water Resources Association
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    • v.51 no.3
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    • pp.263-272
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    • 2018
  • For the design of hydraulic structures, the design flood discharge corresponding to a specific frequency is generally used by using the design storm calculated according to the rainfall-runoff relationship. In the past, empirical equations such as rational equations were used to calculate the peak flow rate. However, as the duration of rainfall is prolonged, the outflow patterns are different from the actual events, so the accuracy of the temporal distribution of the probability rainfall becomes important. In the present work, Huff's quartile method is used for the temporal distribution of rainfall, and the third quartile is generally used. The regression equation for Huff's quadratic curve applies a sixth order polynomial equation because of its high accuracy throughout the duration of rainfall. However, in statistical modeling, the regression equation needs to be concise in accordance with the principle of simplicity, and it is necessary to determine the regression coefficient based on the statistical significance level. Therefore, in this study, the statistical significance test for regression equation for temporal distribution of the Huff's quartile method, which is used as the temporal distribution method of design rainfall, is conducted for 69 rainfall observation stations under the jurisdiction of the Korea Meteorological Administration. It is statistically significant that the regression equation of the Huff's quartile method can be considered only up to the 4th order polynomial equation, as the regression coefficient is significant in most of the 69 rainfall observation stations.

Analysis of Efficiency of Bacillus subtilis To Treat Bagasse Based Paper and Pulp Industry Wastewater-A Novel Approach

  • Karichappan, Thirugnanasambandham;Venkatachalam, Sivakumar;Jeganathan, Prakash Maran
    • Journal of the Korean Chemical Society
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    • v.58 no.2
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    • pp.198-204
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    • 2014
  • In this present study, bagasse based pulp and paper industry wastewater was treated under different operating conditions such as initial pH (6-8), temperature ($25-35^{\circ}C$) and contact time (3-7 days) by using Bacillus subtilis. Response surface methodology (RSM) coupled with Box-Behnken response surface design (BBD) was employed to investigate the effect of process variables on the responses such as turbidity, biological oxygen demand (BOD) and chemical oxygen demand (COD) removal. The experimental data were analyzed by Pareto analysis of variance (ANOVA) and the second order polynomial models were developed. Interactive effects of the process variables on the responses were studied using plotting 3D response surface contour graph and the optimum process conditions were found to be: initial pH of 7, temperature of $30^{\circ}C$ and contact time of 5 days. Under these conditions, removal efficiencies of turbidity, BOD and COD were found to be 85%, 93% and 80% respectively which are close agreement with real experiments. These results indicate that the treatment of bagasse based pulp and paper industry wastewater using Bacillus subtilis is an effective and novel technique.

Prediction of Remaining Useful Life of Lithium-ion Battery based on Multi-kernel Support Vector Machine with Particle Swarm Optimization

  • Gao, Dong;Huang, Miaohua
    • Journal of Power Electronics
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    • v.17 no.5
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    • pp.1288-1297
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    • 2017
  • The estimation of the remaining useful life (RUL) of lithium-ion (Li-ion) batteries is important for intelligent battery management system (BMS). Data mining technology is becoming increasingly mature, and the RUL estimation of Li-ion batteries based on data-driven prognostics is more accurate with the arrival of the era of big data. However, the support vector machine (SVM), which is applied to predict the RUL of Li-ion batteries, uses the traditional single-radial basis kernel function. This type of classifier has weak generalization ability, and it easily shows the problem of data migration, which results in inaccurate prediction of the RUL of Li-ion batteries. In this study, a novel multi-kernel SVM (MSVM) based on polynomial kernel and radial basis kernel function is proposed. Moreover, the particle swarm optimization algorithm is used to search the kernel parameters, penalty factor, and weight coefficient of the MSVM model. Finally, this paper utilizes the NASA battery dataset to form the observed data sequence for regression prediction. Results show that the improved algorithm not only has better prediction accuracy and stronger generalization ability but also decreases training time and computational complexity.

Conjugate Point Extraction for High-Resolution Stereo Satellite Images Orientation

  • Oh, Jae Hong;Lee, Chang No
    • Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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    • v.37 no.2
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    • pp.55-62
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    • 2019
  • The stereo geometry establishment based on the precise sensor modeling is prerequisite for accurate stereo data processing. Ground control points are generally required for the accurate sensor modeling though it is not possible over the area where the accessibility is limited or reference data is not available. For the areas, the relative orientation should be carried out to improve the geometric consistency between the stereo data though it does not improve the absolute positional accuracy. The relative orientation requires conjugate points that are well distributed over the entire image region. Therefore the automatic conjugate point extraction is required because the manual operation is labor-intensive. In this study, we applied the method consisting of the key point extraction, the search space minimization based on the epipolar line, and the rigorous outlier detection based on the RPCs (Rational Polynomial Coefficients) bias compensation modeling. We tested different parameters of window sizes for Kompsat-2 across track stereo data and analyzed the RPCs precision after the bias compensation for the cases whether the epipolar line information is used or not. The experimental results showed that matching outliers were inevitable for the different matching parameterization but they were successfully detected and removed with the rigorous method for sub-pixel level of stereo RPCs precision.

Design optimization of semi-rigid space steel frames with semi-rigid bases using biogeography-based optimization and genetic algorithms

  • Shallan, Osman;Maaly, Hassan M.;Sagiroglu, Merve;Hamdy, Osman
    • Structural Engineering and Mechanics
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    • v.70 no.2
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    • pp.221-231
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    • 2019
  • This paper performs for the first time a simultaneous optimization for members sections along with semi-rigid beam-to-column connections for space steel frames with fixed, semi-rigid, and hinged bases using a biogeography-based optimization algorithm (BBO) and a genetic algorithm (GA). Furthermore, a member's sections optimization for a fully fixed space frame is carried out. A real and accurate simulation of semi-rigid connection behavior is considered in this study, where the semi-rigid base connections are simulated using Kanvinde and Grilli (2012) nonlinear model, which considers deformations in different base connection components under the applied loads, while beam-to-column connections are modeled using the familiar Frye and Morris (1975) nonlinear polynomial model. Moreover, the $P-{\Delta}$ effect and geometric nonlinearity are considered. AISC-LRFD (2016) specification constraints of the stress and displacement are considered as well as section size fitting constraints. The optimization is applied to two benchmark space frame examples to inspect the effect of semi-rigidity on frame weight and drift using BBO and GA algorithms.

Small scale effect on the vibration of non-uniform nanoplates

  • Chakraverty, S.;Behera, Laxmi
    • Structural Engineering and Mechanics
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    • v.55 no.3
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    • pp.495-510
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    • 2015
  • Free vibration of non-uniform embedded nanoplates based on classical (Kirchhoff's) plate theory in conjunction with nonlocal elasticity theory has been studied. The nanoplate is assumed to be rested on two-parameter Winkler-Pasternak elastic foundation. Non-uniform material properties of nanoplates have been considered by taking linear as well as quadratic variations of Young's modulus and density along the space coordinates. Detailed analysis has been reported for all possible casesof such variations. Trial functions denoting transverse deflection of the plate are expressed in simple algebraic polynomial forms. Application of the present method converts the problem into generalised eigen value problem. The study aims to investigate the effects of non-uniform parameter, elastic foundation, nonlocal parameter, boundary condition, aspect ratio and length of nanoplates on the frequency parameters. Three-dimensional mode shapes for some of the boundary conditions have also been illustrated. One may note that present method is easier to handle any sets of boundary conditions at the edges.

Development and Calibration of a Seven-Hole Pressure Probe (7공 압력프로브의 교정 및 개발)

  • Yang, Jae-Hun;Chang, Jo-Won
    • Journal of the Korean Society for Aviation and Aeronautics
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    • v.14 no.1
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    • pp.43-48
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    • 2006
  • The present study was carried out in order to develope a seven-hole pressure probe which is able to measure high flow angles. The seven-hole pressure probe is a non-nulling, directional velocity probe used for measuring three dimensional flow that having high flow angles. A 4 mm diameter seven-hole conical pressure probe was manufactured with a cone angle of 70$^{\circ}$. The probe was comprised of seven 1 mm diameter stainless steel tubes packed close together and fitted into an outer stainless steel sleeve. The calibration procedure is based on the use of the Callington's polynomial curve-fit method. The validity of the seven-hole conical pressure probe is demonstrated by comparisons with hot-wire data.

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Eigenvalue Analysis of Circular Mindlin Plates Using the Pseudospectral Method (의사스펙트럴법을 이용한 원형 Mindlin 평판의 동적특성 해석)

  • Lee, Jin-Hee
    • Transactions of the Korean Society of Mechanical Engineers A
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    • v.26 no.6
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    • pp.1169-1177
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    • 2002
  • A study of fee vibration of circular Mindlin plates is presented. The analysis is based on the pseudospctral method, which uses Chebyshev polynomials and Fourier series as basis functions. It Is demonstrated that rapid convergence and accuracy as well as the conceptual simplicity could be achieved when the pseudospectral method was apt)lied to the solution of eigenvalue problems. Numerical examples of circular Mindlin plates with clamped and simply supported boundary conditions are provided for various thickness-to-radius ratios.