Modeling health outcomes of air pollution in the Middle East by using support vector machines and neural networks.

This study investigates the impact of air pollution on health outcomes in Middle Eastern countries, a region facing severe environmental challenges. As such, these are important in an effort to add up to policy-level as well as interventional changes that can be put in practice in the area of public health. Numeration analysis and association with health parameters was carried out by using Analytical tools such as, AIR Data, ARIMA,ANN, SVM and Exponential smoothing.

New adaptive EWMA CV control chart with application to the sintering process.

This research presents a new adaptive exponentially weighted moving average control chart, known as the coefficient of variation (CV) EWMA statistic to study the relative process variability. The production process CV monitoring is a long-term process observation with an unstable mean. Therefore, a new modified adaptive exponentially weighted moving average (AAEWMA) CV monitoring chart using a novel function hereafter referred to as the "AAEWMA CV" monitoring control chart.

A support vector machine based drought index for regional drought analysis.

The increased global warming has increased the likelihood of recurrent drought hazards. Potential links between the frequency of extreme weather events and global warming have been suggested by earlier research. The spatial variability of meteorological factors over short distances can cause distortions in conclusions or limit the scope of drought analysis in a particular region when extreme values predominate.

A novel Bayesian Max-EWMA control chart for jointly monitoring the process mean and variance: an application to hard bake process.

In this article, we introduce a novel Bayesian Max-EWMA control chart under various loss functions to concurrently monitor the mean and variance of a normally distributed process. The Bayesian Max-EWMA control chart exhibit strong overall performance in detecting shifts in both mean and dispersion across various magnitudes. To evaluate the performance of the proposed control chart, we employ Monte Carlo simulation methods to compute their run length characteristics.

Monitoring the process mean under the Bayesian approach with application to hard bake process.

This study introduces the Bayesian adaptive exponentially weighted moving average (AEWMA) control chart within the framework of measurement error, examining two separate loss functions: the squared error loss function and the linex loss function. We conduct an analysis of the posterior and posterior predictive distributions utilizing a conjugate prior. In the presence of measurement error (ME), we employ a linear covariate model to assess the control chart's effectiveness.

Bayesian AEWMA control chart under ranked set sampling with application to reliability engineering.

The article introduces a novel Bayesian AEWMA Control Chart that integrates different loss functions (LFs) like the square error loss function and Linex loss function under an informative prior for posterior and posterior predictive distributions, implemented across diverse ranked set sampling (RSS) designs. The main objective is to detect small to moderate shifts in the process mean, with the average run length and standard deviation of run length serving as performance measures. The study employs a hard bake process in semiconductor production to demonstrate the effectiveness of the proposed chart, comparing it with existing control charts through Monte Carlo simulations.

Adaptive multivariate dispersion control chart with application to bimetal thermostat data.

Adaptive EWMA (AEWMA) control charts have gained remarkable recognition by monitoring productions over a wide range of shifts. The adaptation of computational statistic as per system shift is the main aspect behind the proficiency of these charts. In this paper, a function-based AEWMA multivariate control chart is suggested to monitor the stability of the variance-covariance matrix for normally distributed process control.

Adaptive EWMA control chart for monitoring the coefficient of variation under ranked set sampling schemes.

In this study, we introduce an Adaptive Exponentially Weighted Moving based Coefficient of Variation (AEWMCV) control chart, designed to address situations where the process mean fluctuates over time and the standard deviation of the process changes linearly with the process mean. To enhance the efficiency and effectiveness of the control chart, we integrate the ranked set sampling method and its modified schemes, such as Simple Random Sampling, Quartile RSS, Median RSS, and Extreme RSS. The performance of the proposed AEWMCV control chart and the studied CV control charts are evaluated using the Average Run Length and Standard Deviation of Run Length metrics.

A simulation study: Using dual ancillary variable to estimate population mean under stratified random sampling.

In this paper, we propose an improved ratio-in-regression type estimator for the finite population mean under stratified random sampling, by using the ancillary varaible as well as rank of the ancillary varaible. Expressions of the bias and mean square error of the estimators are derived up to the first order of approximation. The present work focused on proper use of the ancillary variable, and it was discussed how ancillary variable can improve the precision of the estimates.

Synthesis of Starch-Grafted Polymethyl Methacrylate via Free Radical Polymerization Reaction and Its Application for the Uptake of Methylene Blue.

In this research, a new biodegradable and eco-friendly adsorbent, starch-grafted polymethyl methacrylate (St-g-PMMA) was synthesized. The St-g-PMMA was synthesized by a free radical polymerization reaction in which methyl methacrylate (MMA) was grafted onto a starch polymer chain. The reaction was performed in water in the presence of a potassium persulfate (KPS) initiator.

Outcomes of Ublituximab compared to Teriflunomide for relapsing multiple sclerosis: A meta-analysis.

Ublituximab is an anti-CD20 antibody that immunomodulates B-cells for relapsing multiple sclerosis (MS). With limited therapeutics available, this original meta-analysis seeks to determine the effect size (using RevMan 5.4.

Estimation of finite population distribution function with dual use of auxiliary information under non-response.

In this paper, we propose two new families of estimators for estimating the finite population distribution function in the presence of non-response under simple random sampling. The proposed estimators require information on the sample distribution functions of the study and auxiliary variables, and additional information on either sample mean or ranks of the auxiliary variable. We considered two situations of non-response (i) non-response on both study and auxiliary variables, (ii) non-response occurs only on the study variable.