Research ArticleOpen accessIn the keywordsA New Block Method for Special Third Order Ordinary Differential EquationsB. T. Olabode, Y. YusuphA linear multistep method for the direct solution of initial value problems of ordinary differential equations was presented in this article. Collocation approximation method was adopted in the derivation of the scheme and then the scheme was applied as simultaneous integrator to special third order initial value problem of ordinary differential equations. The new block method possessed the desirable feature … …Journal of Mathematics and Statistics, Vol. 5, Issue 3 · 30 Sep 2009 · 7,711 accessesView PDFCite
Research ArticleOpen accessIn the keywordsInverse Correlations for Multiple Time Series and Gaussian Random Fields and Measures of Their Linear DeterminismR.J. Bhansali, L. IppolitiFor a discrete-time vector linear stationary process, {X(t)}, admitting forward and backward autoregressive representations, the variance matrix of an optimal linear interpolator of X(t), based on a knowledge of {X(t-j), j≠0}, is known to be given by Ri(0)-1 where Ri(0) denotes the inverse variance of the process. Let A=Is-1Ri(0)ˉ1R(0)ˉ1, where R(0) denotes the variance matrix of {X(t)} and Is an … …Journal of Mathematics and Statistics, Vol. 1, Issue 4 · 31 Dec 2005 · 6,428 accessesView PDFCite
Research ArticleOpen accessIn the abstractExploring University Students' Perceptions of AI Tools in Programming Education: An Extended TAM ApproachAreej Abdullah AlfuhaidGenerative Artificial Intelligence (AI) is commonly used in programming education. Tools such as ChatGPT and GitHub Copilot aid in code generation, debugging, and explanation. The benefits are clear, though concerns about learning quality and academic integrity persist.We tested an extended Technology Acceptance Model (TAM) for university programming courses. The model included perceived usefulness and perceived ease of use. It added … …Journal of Computer Science, Vol. 22, Issue 3 · 11 Mar 2026 · 2,072 accessesView PDFCite
Research ArticleOpen accessIn the abstractMachine Learning Oceanographic Data for Prediction of the Potential of Marine ResourcesDenny Arbahri, Oky Dwi Nurhayati, Imam MuditaMarine data and information are very important for human survival, therefore this data and information is attractive to investors because of the potential economic value. This data and information has been difficult to obtain, the solution to overcome this is by analyzing oceanographic data for 2009-2019 collected from the marine database belonging to the Agency for the Study and Application … …Journal of Computer Science, Vol. 20, Issue 2 · 8 Jan 2024 · 5,975 accessesView PDFCite
Research ArticleOpen accessIn the abstractUnivariate Generalized Additive Models for Simulated Stationary and Non-Stationary Generalized Pareto DistributionMostafa Behzadi, Mohd Bakri Adam, Anwar FitriantoGeneralized additive models as a predictor in regression approaches, are made up over cubic spline basis and penalized regression splines. Despite of linear predictor in GLM, generalized additive models use a sum of smooth functions of covariates as a predictor. The data which are used in this study have generalized Pareto distribution and have been simulated by inversion method. The … …Journal of Mathematics and Statistics, Vol. 13, Issue 2 · 3 Jun 2017 · 7,434 accessesView PDFCite
Research ArticleOpen accessIn the abstractMultilevel Mixed Analysis and Mapping on Divorce Problem in UAEFaisal G. KhamisDespite the wealth of research investigating the divorce problem in the developed countries, few and inconsistent studies investigated this problem at emirate-level in developing countries, such as United Arab Emirates (UAE). The Questions are raised whether divorce is changed over time and whether clustering in divorce exists within emirates in UAE. The objectives are to investigate the change in divorce … …Journal of Mathematics and Statistics, Vol. 12, Issue 4 · 31 Oct 2016 · 7,302 accessesView PDFCite
Research ArticleOpen accessIn the abstractCorrelation Based ADALINE Neural Network for Commodity TradingJ. Chandra, M. Nachamai, Anitha S. PillaiCommodity trading is one of the most popular resources owning to its eminent predictable return on investment to earn money through trading. The trading includes all kinds of commodities like agricultural goods such as wheat, coffee, cocoa etc. and hard products like gold, rubber, crude oils etc.,. The investment decision can be made very easily with the help of the … …Journal of Computer Science, Vol. 11, Issue 7 · 29 Oct 2015 · 7,828 accessesView PDFCite
Research ArticleOpen accessIn the abstractGAUSSIAN COPULA MARGINAL REGRESSION FOR MODELING EXTREME DATA WITH APPLICATIONSutikno, Heri Kuswanto, Iis Dewi RatihRegression is commonly used to determine the relationship between the response variable and the predictor variable, where the parameters are estimated by Ordinary Least Square (OLS). This method can be used with an assumption that residuals are normally distributed (0, σ2). However, the assumption of normality of the data is often violated due to extreme observations, which are often found … …Journal of Mathematics and Statistics, Vol. 10, Issue 2 · 4 Apr 2014 · 7,625 accessesView PDFCite
Research ArticleOpen accessIn the abstractPartial Least Squares Regression Based Variables Selection for Water Level PredictionsNoraini Ibrahim, Antoni WibowoFloods are common phenomenon in the state of Kuala Krai, specifically in Kelantan-Malaysia. Every year, floods affecting biodiversity on this region and also causing property loss of this residential area. The residents in Kelantan always suffered from floods since the water overflows to the areas adjoining to the rivers, lakes or dams. Months, average monthly rainfall, temperature, relative humidity and … …American Journal of Applied Sciences, Vol. 10, Issue 4 · 7 Apr 2013 · 6,624 accessesView PDFCite