Search Results - (( development linear interpolation algorithm ) OR ( java application optimisation algorithm ))
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STEP-NC Interpolator for General 2D and 3D Parametric Curve / Dzullijah Ibrahim...[et al.]
Published 2017“…In specialty domain, such as design, manufacturing, and machining, the STEP AP238 (STEP-NC) is developed. A STEP-NC interface to OAPC-NC interpolator using STEP-NC tool path data is proposed and developed. …”
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Study and Implementation of Data Mining in Urban Gardening
Published 2019“…The system is essentially a three-part development, utilising Android, Java Servlets, and Arduino platforms to create an optimised and automated urban-gardening system. …”
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Solving fractional differential equations using fractional explicit method
Published 2024“…This research is focusing in solving the fractional differential equations (FDEs) for linear and non-linear type using fractional explicit method (FEM) with constant step-size. …”
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Solving fractional differential equations using fractional explicit method
Published 2024“…This research is focusing in solving the fractional differential equations (FDEs) for linear and non-linear type using fractional explicit method (FEM) with constant step-size. …”
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Dual-thresholding based sinogram interpolation To reduce metal artefact In Computed tomography imaging
Published 2021“…It is caused bybeamhardening effects, photons starvation, non-linear partial volume, photonscatter, undersampling and inappropriate correction algorithm during reconstructionofimage. …”
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The development of spatio-temporal data model for dynamic visualization of virtual geographical information system
Published 2006“…Result shows that the proposed data model is able to perform well with a visualization algorithm using linear interpolation and an improved TIN structure. …”
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Monograph -
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Multistep block methods for solving higher order delay differential equations
Published 2016“…This thesis describes the development of numerical algorithms for solving higher order DDEs. …”
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Use of the simplex method to optimize analytical condition in structural analysis
Published 2011“…The prediction is made with help of some interpolation procedure. In this paper a simplex method of nonlinear dynamics response analysis is developed.…”
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Formulation of a new implicit method for group implicit BBDF in solving related stiff ordinary differential equations
Published 2021“…We generate the solver by manipulating the numbers of back values to achieve a higher-order possible using the interpolation procedure. The algorithm is developed and implemented in C ++ medium. …”
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Pemetaan Pm10 Dan Aot Menggunakan Teknik Penderiaan Jauh Di Semenanjung Malaysia
Published 2006“…The developed algorithms are two-band algorithm, terma linear and modified algorithm from the combination of the visible and infrared thermal bands. …”
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Web-based expert system for material selection of natural fiber- reinforced polymer composites
Published 2015“…Finally, the developed expert system was deployed over the internet with central interactive interface from the server as a web-based application. As Java is platform independent and easy to be deployed in web based application and accessible through the World Wide Web (www), this expert system can be one stop application for materials selection.…”
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Volumetric spatiotemporal data model
Published 2007“…Result shows that the data model which has been proposed can work with a visualization algorithm using linear interpolation and improvement TIN structure.…”
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Book Section -
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Direct Block Methods for Solving Special Second Order Ordinary Differential Equations and Their Parallel Implementations
Published 2008“…The parallel algorithms are written in C language and implemented on Sun Fire V1280 distributed memory system. …”
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Parallel strategies on a distributed parallel computer system
Published 2004“…There are IADEI method which is based on Richardson's formula and AGE\_BRIAN which is based on linear interpolation concept. The development of a few strategies parallel is being as a mechanism for IADE to make it implemented in parallel. …”
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Prediction of rice biomass using machine learning algorithms
Published 2022“…This study aims to: (i) compare the base and ensemble MLs’ model performance, variance, stability, and confidence for predicting rice biomass using collinear (multicollinearity context (MCC)) and non-collinear (non-multicollinearity context (NMCC)) VIs; (ii) compare the rice above ground biomass (TAGB) predictability from noised and Kalman filter’ denoised VIs using histogram gradient boosting regressor (HGBR); (iii) develop a trigonometric-Euclidean-smoother interpolator (TESI), including linear (LN-TESI), cubic (C-TESI), quadratic (Q-TESI), and logarithmic (L-TESI) interpolators, for continuous time-series and non-timeseries VIs data augmentation, and compare them to the tabular variational autoencoder (TVAE) and the conditional tabular generative adversarial network (CTGAN) for preventing DNN’s under/overfitting. …”
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