scholarly journals Regressional Estimation of Cotton Sirospun Yarn Properties from Fibre Properties

2014 ◽  
Vol 14 (3) ◽  
pp. 161-167 ◽  
Author(s):  
Tuba Bedez Üte ◽  
Hüseyin Kadoğlu

Abstract In this paper, it is aimed at determining the equations and models for estimating the sirospun yarn quality characteristics from the yarn production parameters and cotton fibre properties, which are focused on fibre bundle measurements represented by HVI (high volume instrument). For this purpose, a total of 270 sirospun yarn samples were produced on the same ring spinning machine under the same conditions at Ege University, by using 11 different cotton blends and three different strand spacing settings, in four different yarn counts and in three different twist coefficients. The sirospun yarn and cotton fibre property interactions were investigated by correlation analysis. For the prediction of yarn quality characteristics, multivariate linear regression methods were performed. As a result of the study, equations were generated for the prediction of yarn tenacity, breaking elongation, unevenness and hairiness by using fibre and yarn properties. After the goodness of fit statistics, very large determination coefficients (R2 and adjusted R2) were observed.

Author(s):  
Khalid AA Abakar ◽  
Chongwen Yu

This work demonstrated the possibility of using the data mining techniques such as artificial neural networks (ANN) and support vector machine (SVM) based model to predict the quality of the spinning yarn parameters. Three different kernel functions were used as SVM kernel functions which are Polynomial and Radial Basis Function (RBF) and Pearson VII Function-based Universal Kernel (PUK) and ANN model were used as data mining techniques to predict yarn properties. In this paper, it was found that the SVM model based on Person VII kernel function (PUK) have the same performance in prediction of spinning yarn quality in comparison with SVM based RBF kernel. The comparison with the ANN model showed that the two SVM models give a better prediction performance than an ANN model.


2021 ◽  
pp. 37-43
Author(s):  
Hediyeh Baradaran ◽  
Alen Delic ◽  
Ka-Ho Wong ◽  
Nazanin Sheibani ◽  
Matthew Alexander ◽  
...  

Introduction: Current ischemic stroke risk prediction is primarily based on clinical factors, rather than imaging or laboratory markers. We examined the relationship between baseline ultrasound and inflammation measurements and subsequent primary ischemic stroke risk. Methods: In this secondary analysis of the Multi-Ethnic Study of Atherosclerosis (MESA), the primary outcome is the incident ischemic stroke during follow-up. The predictor variables are 9 carotid ultrasound-derived measurements and 6 serum inflammation measurements from the baseline study visit. We fit Cox regression models to the outcome of ischemic stroke. The baseline model included patient age, hypertension, diabetes, total cholesterol, smoking, and systolic blood pressure. Goodness-of-fit statistics were assessed to compare the baseline model to a model with ultrasound and inflammation predictor variables that remained significant when added to the baseline model. Results: We included 5,918 participants. The primary outcome of ischemic stroke was seen in 105 patients with a mean follow-up time of 7.7 years. In the Cox models, we found that carotid distensibility (CD), carotid stenosis (CS), and serum interleukin-6 (IL-6) were associated with incident stroke. Adding tertiles of CD, IL-6, and categories of CS to a baseline model that included traditional clinical vascular risk factors resulted in a better model fit than traditional risk factors alone as indicated by goodness-of-fit statistics. Conclusions: In a multiethnic cohort of patients without cerebrovascular disease at baseline, we found that CD, CS, and IL-6 helped predict the occurrence of primary ischemic stroke. Future research could evaluate if these basic ultrasound and serum measurements have implications for primary prevention efforts or clinical trial inclusion criteria.


2019 ◽  
Vol 31 (1) ◽  
pp. 194-216 ◽  
Author(s):  
Ching-Chan Cheng ◽  
Ya-Yuan Chang ◽  
Ming-Chun Tsai ◽  
Cheng-Ta Chen ◽  
Yu-Chun Tseng

Purpose This study aims to develop a comprehensive LOHAS (lifestyles of health and sustainability) restaurant service quality scale by using a rigorous qualitative and quantitative research process to effectively measure the service quality of LOHAS restaurants. Moreover, this study aims to further identify the Kano quality characteristics and strategic meanings of service attributes in LOHAS restaurants. Design/methodology/approach This study designed the preliminary items of the service quality scale for LOHAS restaurants (LORSERV scale) based on relevant literatures and expert interview procedures. This study identified the goodness of fit of the questionnaire content, construct validity and validity of the LORSERV scale using exploratory factor analysis and confirmatory factor analysis. The moderated regression was conducted to identify the Kano quality characteristics and strategic meanings of each service attribute in LOHAS restaurants. Findings The results indicated that the LORSERV scale included seven dimensions (internal sense of happiness, transitiveness, environment, healthy catering, service commitment, green practicability and thoughtfulness), for a total of 33 items. According to the results of the Kano model, the seven service attributes were categorized into the attractive quality. A total of 25 service attributes were categorized into the one-dimensional quality, and one service attribute was categorized into the must-be quality. Originality/value The contribution of this study is that the scale could facilitate operators of LOHAS restaurants to effectively understand customer perceptions of service quality and serve as a reference to upgrade and improve service quality. The identification of Kano quality characteristics for each service attribute is conducive for LOHAS restaurants to understand the strategic meanings of each service attribute and can serve as a reference to make distinctive service strategies to reach sustainable operations.


Symmetry ◽  
2020 ◽  
Vol 12 (1) ◽  
pp. 80 ◽  
Author(s):  
Martynas Narmontas ◽  
Petras Rupšys ◽  
Edmundas Petrauskas

In this work, we employ stochastic differential equations (SDEs) to model tree stem taper. SDE stem taper models have some theoretical advantages over the commonly employed regression-based stem taper modeling techniques, as SDE models have both simple analytic forms and a high level of accuracy. We perform fixed- and mixed-effect parameters estimation for the stem taper models by developing an approximated maximum likelihood procedure and using a data set of longitudinal measurements from 319 mountain pine trees. The symmetric Vasicek- and asymmetric Gompertz-type diffusion processes used adequately describe stem taper evolution. The proposed SDE stem taper models are compared to four regression stem taper equations and four volume equations. Overall, the best goodness-of-fit statistics are produced by the mixed-effect parameters SDEs stem taper models. All results are obtained in the Maple computer algebra system.


Author(s):  
Davide Carino ◽  
Paolo Denti ◽  
Guido Ascione ◽  
Benedetto Del Forno ◽  
Elisabetta Lapenna ◽  
...  

Abstract OBJECTIVES The EuroSCORE II is widely used to predict 30-day mortality in patients undergoing open and transcatheter cardiac surgery. The aim of this study is to evaluate the discriminatory ability of the EuroSCORE II in predicting 30-day mortality in a large cohort of patients undergoing surgical mitral valve repair in a high-volume centre. METHODS A retrospective review of our institutional database was carried on to find all patients who underwent mitral valve repair in our department from January 2012 to December 2019. Discrimination of the EuroSCORE II was assessed using receiver operating characteristic curves. The maximum Youden’s Index was employed to define the optimal cut-point. Calibration was assessed by generating calibration plot that visually compares the predicted mortality with the observed mortality. Calibration was also tested with the Hosmer–Lemeshow goodness-of-fit test. Finally, the accuracy of the models was tested calculating the Brier score. RESULTS A total of 2645 patients were identified, and the median EuroSCORE II was 1.3% (0.6–2.0%). In patients with degenerative mitral regurgitation (MR), the EuroSCORE II showed low discrimination (area under the curve 0.68), low accuracy (Brier score 0.27) and low calibration with overestimation of the 30-day mortality. In patients with secondary MR, the EuroSCORE II showed a good overall performance estimating the 30-day mortality with good discrimination (area under the curve 0.88), good accuracy (Brier score 0.003) and good calibration. CONCLUSIONS In patients with degenerative MR operated on in a high-volume centre with a high level of expertise in mitral valve repair, the EuroSCORE II significantly overestimates the 30-day mortality.


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