Research ArticleOpen accessPhrase in the titleEstimation Methods for Multicollinearity Proplem Combined with High Leverage Data PointsMoawad El-Fallah, Abd El-SallamProblem statement: Least Squares (LS) method has been the most popular method for estimating the parameters of a model due to its optimal properties and ease of computation. LS estimated regression may be seriously affected by multicollinearity which is a near linear dependency between two or more explanatory variables in the regression models. Although LS estimates are unbiased in the … …Journal of Mathematics and Statistics, Vol. 7, Issue 2 · 18 May 2011 · 7,617 accessesView PDFCite
Research ArticleOpen accessPhrase in the titleRobust Estimations as a Remedy for Multicollinearity Caused by Multiple High Leverage PointsArezoo Bagheri, Habshah MidiProblem statement: The Least Squares (LS) method has been the most popular technique for estimating the parameters of a model due to its optimal properties and ease of computation. LS estimated regression may be seriously disturbed by multicollinearity which is a near linear dependency between two or more explanatory variables in the regression models. Even though LS estimates are unbiased … …Journal of Mathematics and Statistics, Vol. 5, Issue 4 · 31 Dec 2009 · 8,247 accessesView PDFCite
Research ArticleOpen accessPhrase in the titleTwo-Step Robust Diagnostic Method for Identification of Multiple High Leverage PointsArezoo Bagheri, Habshah Midi, A.H.M. Rahmatullah ImonProblem statement: High leverage points are extreme outliers in the X-direction. In regression analysis, the detection of these leverage points becomes important due to their arbitrary large effects on the estimations as well as multicollinearity problems. Mahalanobis Distance (MD) has been used as a diagnostic tool for identification of outliers in multivariate analysis where it finds the distance between normal … …Journal of Mathematics and Statistics, Vol. 5, Issue 2 · 30 Jun 2009 · 8,306 accessesView PDFCite
Research ArticleOpen accessIn the abstractArtificial Intelligence in Quality Control: Transforming Manufacturing ProcessesGopinath KathiresanThe integration of Artificial Intelligence (AI) into Quality Control (QC) is transforming manufacturing by enhancing accuracy, efficiency, and productivity. Traditional QC methods, reliant on manual inspection and basic automation, often fall short in addressing the complexities of modern production environments. This paper presents a review on the application of AI, particularly machine learning, deep learning, and reinforcement learning, in manufacturing … …Journal of Computer Science, Vol. 22, Issue 1 · 12 Feb 2026 · 6,492 accessesView PDFCite
Research ArticleOpen accessIn the abstractModelling the Error Term of Australia Gross Domestic ProductAyodele Abraham Agboluaje, Suzilah Ismail, Chee Yin YipThe main aim of this study is to model the Gross Domestic Product (GDP) with the new Combine White Noise (CWN) Model and compare the results with the Vector Autoregressive (VAR) Model and Exponential Generalized Autoregressive Conditional Heteroscedasticity (EGARCH) Model which are the existing models. The CWN model estimation yields best results with least information criteria and high log likelihood … …Journal of Mathematics and Statistics, Vol. 12, Issue 4 · 2 Nov 2016 · 6,930 accessesView PDFCite
Research ArticleOpen accessIn the abstractModeling the Error Term by Moving Average and Generalized Autoregressive Conditional Heteroscedasticity ProcessesAyodele Abraham Agboluaje, Suzilah bt Ismail, Chee Yin YipThis study has been able to reveal that the Combine White Noise model outperforms the existing Generalized Autoregressive Conditional Heteroscedasticity (GARCH) and Moving Average (MA) models in modeling the errors, that exhibits conditional heteroscedasticity and leverage effect. MA process cannot model the data that reveals conditional heteroscedasticity and GARCH cannot model the leverage effect also. The standardized residuals of GARCH … …American Journal of Applied Sciences, Vol. 12, Issue 11 · 20 Nov 2015 · 6,721 accessesView PDFCite
Research ArticleOpen accessIn the abstractActive Reset and Scheduling in Fault-Tolerant Quantum-Classical Cloud ComputingMohamed El-DosukyQuantum-classical cloud computing refers to a hybrid computing model that integrates quantum computing with classical computing resources, typically hosted on the cloud. The objective of this paper is threefold: First, to scrutinize the computing paradigm of quantum-classical cloud computing; second, to study the three pillars of the underpinning techniques: Active reset, scheduling, and fault tolerance; third, to demonstrate the realization … …Journal of Computer Science, Vol. 22, Issue 7 · 1 Sep 2026 · 767 accessesView PDFCite
Research ArticleOpen accessIn the abstractCascaded MNetV3UNet: A Lightweight Two-Stage Architecture for High-Precision Brain Tumor Segmentation in MRIMayuri Popat, Sanskruti PatelPrecise brain tumor segmentation is an essential but quite challenging process in MRI images because of their irregular shapes, heterogeneous appearance, and low contrast with surrounding tissues. While U-Net-based architectures have achieved significant success, their high computational complexity limits deployment on resource-constrained systems. In this study, a Novel two-stage cascaded architecture, MNetV3UNet, is introduced, which employs the light-weight MobileNetV3-Large as … …Journal of Computer Science, Vol. 22, Issue 2 · 23 Feb 2026 · 1,788 accessesView PDFCite
Technical ReportOpen accessIn the abstractCritical Evaluation of Thermal Efficiency in Aerogel Glazing Systems for Energy-Saving ApplicationsErdem CuceAerogels as a thermal superinsulation material possess a unique combination of properties, most notably low densities, and exceptionally low thermal conductivities, stemming from the high-volume fraction of air incorporated within their structure. Aerogel glazing systems have emerged as a promising solution to enhance the thermal performance of building envelopes while maintaining daylighting. With the notable reductions in production cost in … …Energy Research Journal, Vol. 15, Issue 1 · 22 Jan 2026 · 2,932 accessesView PDFCite
Research ArticleOpen accessIn the abstractFine-Tuned and Optimized Transformer-Based Model for EEG Seizure DetectionPuspanjali Mallik, Ajit Kumar Nayak, Kumar Janardan Patra et al.Epilepsy, a widely recognized neurological disorder, results from irregularities in the transmission of electrical impulses among neurons in the brain. Over the last two decades, significant efforts have been made by researchers and clinicians to develop effective methods for its early detection and management. The electroencephalogram (EEG), a non-invasive tool used to monitor brainwave activity, has become a central device … …Journal of Computer Science, Vol. 21, Issue 11 · 11 Feb 2026 · 1,412 accessesView PDFCite