Modified Regression Model Research Articles

A numerical model to predict surge and swab pressures for yield power law fluid in concentric annuli with open-ended pipe

Excessive surge pressure can cause many downhole problems such as loss circulation, leakage, fracture formation, and blowout. Accurately predicting surge and swab pressures can provide a guarantee of safety in a downhole. Multiple research endeavors have been conducted based on close-ended pipes (CEP); however, no exact or approximate models to predict surge and swab pressures have been reported for yield power law (YPL) fluid in an open-ended pipe (OEP). In this paper, an exact numerical model was established to predict surge and swab pressures for YPL fluid in concentric annuli with OEP. Additionally, existing regression models for Bingham plastic (BP) and power law (PL) fluids were modified based on the exact numerical solutions in concentric annuli with OEP. The accuracy of the modified regression model is ±5% and ±15% for BP and PL fluids, respectively. In addition, an accurate (to within 5% error) new regression model was developed to predict surge and swab pressures for YPL fluid in a concentric annulus with OEP on the basis of exact numerical solutions. The effects of fluid properties, annular geometries and drilling parameters on surge and swab pressures in OEP were investigated using an exact numerical model.

Using the Modified Regression Analysis to Estimate Industrial Competitiveness – The Case of Banks in Tanzania

The study aims at examining the competition trend in Tanzania using modified regression model; in general the competition was satisfactory as it depicted monopolistic competition although the large share of assets still being dominated by large banks. The study adopted panzer and Rosse model where the sum of H statistics was 0.8 greater than zero but less than one. Therefore the study recommends the banks supervision to increase the reforms to increase competition level.

Targeting IPOs from the Central European emerging stock markets (CEESM) of Poland during the global financial crisis

PurposeThe purpose of this paper is to focus on Initial Public Offering (IPO) investments, performance and activity in times of the global financial crisis.Design/methodology/approachThe paper utilizes, in a pioneering attempt, a modified regression model that is widely used in medical research (i.e. measuring the effectiveness of painkillers, aspects of breastfeeding, cancer research) but proved efficient and informative for the studied area. Embarking on Cox's Hazard Model perfectly mirrored investors' approach to IPO investments. Henceforth, the empirical findings reported in the paper became practical for IPO investors. The quantitative findings are then discussed with high‐profile practitioners, in order to inject more realism into the study. The qualitative research framework expands the empirical analysis to cover significant issues related to IPO activities and proves invaluable in the process of constructing practical implications.FindingsSince the main purpose of the paper is to test the profitability of targeting IPOs from the Polish stock market, the main research question attempted in the paper refers to finding out whether IPO investments constitute an attractive alternative for direct equity investments, especially during the global financial turmoil. On this occasion, the current paper advises on trading strategies that involve targeting IPOs and shield investors from experiencing crisis‐induced losses. These findings remain topical as they contribute to the current debate on tailoring investment approaches to the global financial crises. Furthermore, focusing on the issues related to the overblown deficit reported by the transition economy delivers novel and important implications for policymakers striving to stabilize budget in the aftermath of the nascent financial crisis.Originality/valueWhat distinguishes the paper from previous studies is the original methodology, three‐dimensional approach to IPO activities (adopting a company's, investor's and policymaker's perspectives) and focusing on the systemically important European market that somehow was overlooked by previous studies in this area but recently vaulted into prominence among international investors who regard the Polish stock market as a regional leading bourse.

Prediction of Oxygen Consumption of BF in Iron & Steel Factories Based on Least Squares Support Vector Machine

In this paper, we presented a prediction model of oxygen consumption of blast furnace (BF) based on least squares support vector machine (LSSVM) with the production data of an iron and steel factory. This method utilizes data pre-processing and parameters optimization to improve the fitting precision and operation speed of the model. By comparing the prediction results using different models with actual production data, we found out that the modified regression model of LSSVM is more suitable to predict the trend of oxygen consumption than others. The prediction accuracy is satisfactory and is helpful for oxygen system dispatch and production practice.

Patterns of medicinal plant use: An examination of the Ecuadorian Shuar medicinal flora using contingency table and binomial analyses

Ethnopharmacological relevance Botanical pharmacopoeias are non-random subsets of floras, with some taxonomic groups over- or under-represented. Moerman [Moerman, D.E., 1979. Symbols and selectivity: a statistical analysis of Native American medical ethnobotany, Journal of Ethnopharmacology 1, 111–119] introduced linear regression/residual analysis to examine these patterns. However, regression, the commonly-employed analysis, suffers from several statistical flaws. Aim of the study We use contingency table and binomial analyses to examine patterns of Shuar medicinal plant use (from Amazonian Ecuador). Materials and methods We first analyzed the Shuar data using Moerman's approach, modified to better meet requirements of linear regression analysis. Second, we assessed the exact randomization contingency table test for goodness of fit. Third, we developed a binomial model to test for non-random selection of plants in individual families. Results Modified regression models (which accommodated assumptions of linear regression) reduced R 2 to from 0.59 to 0.38, but did not eliminate all problems associated with regression analyses. Contingency table analyses revealed that the entire flora departs from the null model of equal proportions of medicinal plants in all families. In the binomial analysis, only 10 angiosperm families (of 115) differed significantly from the null model. These 10 families are largely responsible for patterns seen at higher taxonomic levels. Conclusions Contingency table and binomial analyses offer an easy and statistically valid alternative to the regression approach.

Effect of interaction of operation parameters on elutriation behavior in a vortexing fluidized bed

A systematic investigation on elutriation behavior conducted in a vortexing fluidized bed (VFB) cold model is studied. The effects of various parameters on the elutriation are investigated from the data obtained by using 'response surface methodology' (RSM) to determine the relationship between elutriation rate and operating conditions. The results show that all the interactions among primary air flow rate, secondary air flow rate, fine particle size, secondary air inlet diameter, and imaginary circle diameter had significant influences on elutriation behavior in the VFB. The modified regression models of the 'specific elutriation rate constant' (K*) were also submitted in this study.

A modified regression model for forecasting the volumes of Taiwan’s import containers

The available empirical evidence on the relationship between international trade container volume and the economic growth in Taiwan is not conclusive. The purpose of this paper is to propose a modified regression model for forecasting the volumes of Taiwan’s import containers. This article first identifies the contributions and shortcomings of previous empirical works. Then, a new modified regression model is proposed and built using data for the period 1989–2001. Finally, this paper compares the accuracy of the traditional regression model and this modified regression model for forecasting the volumes of Taiwan’s import containers. The results show that this modified regression model proposed in this paper exhibits higher prediction accuracy.

Contribution of the cytochrome and alternative pathways to growth respiration and maintenance respiration in Arabidopsis thaliana

The activities of the cytochrome and alternative respiratory pathways were measured during the growth cycle in Arabidopsis thaliana using a newly developed Isotope Ratio Mass Spectrometer (IRMS) dual‐inlet system that allows very precise measurements of oxygen‐isotope fractionation under low oxygen consumption rates. Under optimum growth conditions, the relative growth rate was highly dependent on the activity of the cytochrome pathway. The activity of the alternative pathway was almost constant irrespective of the growth rate and appeared mostly involved in the maintenance respiration component, although the alternative pathway also played a role under optimum growth conditions. This is the first time that the contribution of the two respiratory pathways to the two main respiratory components (growth and maintenance) has been analyzed with the use of the oxygen‐isotope fractionation technique. The respiration efficiency of the specific costs for growth and maintenance (adenosine triphosphate/O2 ratio) was determined by a modified regression model. The ability to measure oxygen‐isotope fractionation during respiration in A. thaliana opens the door to a wider set of studies that are discussed.

A modified regression model to adjust for intraindividual variation in serum biomarker concentrations

A modified regression model to adjust for intraindividual variation in serum biomarker concentrations

EMPIRICAL MODELS FOR ESTIMATING NET RADIATIVE FLUX: A CASE STUDY FOR THREE MID-LATITUDE SITES WITH OROGRAPHIC VARIABILITY

Based on a 4-year REKLIP data-set of global solar radiationG, shortwave surface albedo a, air temperature Ta and net radiative flux Rn, four types of regression models for the estimation of net radiative flux for three sites at different altitudes, located in the southern Upper Rhine valley have been proposed. In order to make for the limitation associated with the basic regression model (BRM) which relates net radiative flux over a surface to only incoming shortwave radiation, a longwave exchange coefficient has been introduced thus giving rise to the modified regression model (MRM). During daytime, the longwave exchange coefficient is observed to be negative for all three sites averaging about -0.20. The suitability of MRM over BRM becomes particularly obvious with respect to the mountainous site of Feldberg where the mean absolute error between measured and simulated Rn using MRM amounts to just half of that observed using BRM. Furthermore the role of clearness index and air temperature in the estimation of the net radiative flux have each been examined. The incorporation of the former is to make up for the effect of cloudiness on the net radiative flux budget, while the latter is an independent variable arising from the effective terrestrial radiation which thus allow for the estimation of the net radiative flux during all hours of the day. The regression models been proposed here have each been validated and their efficiency in reproducing actual measurements have been reported.