Sample records for traditional regression methods

1. Alternative Methods of Regression

CERN Document Server

Birkes, David

2011-01-01

Of related interest. Nonlinear Regression Analysis and its Applications Douglas M. Bates and Donald G. Watts ".an extraordinary presentation of concepts and methods concerning the use and analysis of nonlinear regression models.highly recommend[ed].for anyone needing to use and/or understand issues concerning the analysis of nonlinear regression models." --Technometrics This book provides a balance between theory and practice supported by extensive displays of instructive geometrical constructs. Numerous in-depth case studies illustrate the use of nonlinear regression analysis--with all data s

2. Quantile Regression Methods

DEFF Research Database (Denmark)

Fitzenberger, Bernd; Wilke, Ralf Andreas

2015-01-01

if the mean regression model does not. We provide a short informal introduction into the principle of quantile regression which includes an illustrative application from empirical labor market research. This is followed by briefly sketching the underlying statistical model for linear quantile regression based......Quantile regression is emerging as a popular statistical approach, which complements the estimation of conditional mean models. While the latter only focuses on one aspect of the conditional distribution of the dependent variable, the mean, quantile regression provides more detailed insights...... by modeling conditional quantiles. Quantile regression can therefore detect whether the partial effect of a regressor on the conditional quantiles is the same for all quantiles or differs across quantiles. Quantile regression can provide evidence for a statistical relationship between two variables even...

3. The Multivariate Regression Statistics Strategy to Investigate Content-Effect Correlation of Multiple Components in Traditional Chinese Medicine Based on a Partial Least Squares Method.

Science.gov (United States)

Peng, Ying; Li, Su-Ning; Pei, Xuexue; Hao, Kun

2018-03-01

Amultivariate regression statisticstrategy was developed to clarify multi-components content-effect correlation ofpanaxginseng saponins extract and predict the pharmacological effect by components content. In example 1, firstly, we compared pharmacological effects between panax ginseng saponins extract and individual saponin combinations. Secondly, we examined the anti-platelet aggregation effect in seven different saponin combinations of ginsenoside Rb1, Rg1, Rh, Rd, Ra3 and notoginsenoside R1. Finally, the correlation between anti-platelet aggregation and the content of multiple components was analyzed by a partial least squares algorithm. In example 2, firstly, 18 common peaks were identified in ten different batches of panax ginseng saponins extracts from different origins. Then, we investigated the anti-myocardial ischemia reperfusion injury effects of the ten different panax ginseng saponins extracts. Finally, the correlation between the fingerprints and the cardioprotective effects was analyzed by a partial least squares algorithm. Both in example 1 and 2, the relationship between the components content and pharmacological effect was modeled well by the partial least squares regression equations. Importantly, the predicted effect curve was close to the observed data of dot marked on the partial least squares regression model. This study has given evidences that themulti-component content is a promising information for predicting the pharmacological effects of traditional Chinese medicine.

4. The Multivariate Regression Statistics Strategy to Investigate Content-Effect Correlation of Multiple Components in Traditional Chinese Medicine Based on a Partial Least Squares Method

Directory of Open Access Journals (Sweden)

Ying Peng

2018-03-01

Full Text Available Amultivariate regression statisticstrategy was developed to clarify multi-components content-effect correlation ofpanaxginseng saponins extract and predict the pharmacological effect by components content. In example 1, firstly, we compared pharmacological effects between panax ginseng saponins extract and individual saponin combinations. Secondly, we examined the anti-platelet aggregation effect in seven different saponin combinations of ginsenoside Rb1, Rg1, Rh, Rd, Ra3 and notoginsenoside R1. Finally, the correlation between anti-platelet aggregation and the content of multiple components was analyzed by a partial least squares algorithm. In example 2, firstly, 18 common peaks were identified in ten different batches of panax ginseng saponins extracts from different origins. Then, we investigated the anti-myocardial ischemia reperfusion injury effects of the ten different panax ginseng saponins extracts. Finally, the correlation between the fingerprints and the cardioprotective effects was analyzed by a partial least squares algorithm. Both in example 1 and 2, the relationship between the components content and pharmacological effect was modeled well by the partial least squares regression equations. Importantly, the predicted effect curve was close to the observed data of dot marked on the partial least squares regression model. This study has given evidences that themulti-component content is a promising information for predicting the pharmacological effects of traditional Chinese medicine.

5. Regression methods for medical research

CERN Document Server

Tai, Bee Choo

2013-01-01

Regression Methods for Medical Research provides medical researchers with the skills they need to critically read and interpret research using more advanced statistical methods. The statistical requirements of interpreting and publishing in medical journals, together with rapid changes in science and technology, increasingly demands an understanding of more complex and sophisticated analytic procedures.The text explains the application of statistical models to a wide variety of practical medical investigative studies and clinical trials. Regression methods are used to appropriately answer the

6. Regression modeling methods, theory, and computation with SAS

CERN Document Server

Panik, Michael

2009-01-01

Regression Modeling: Methods, Theory, and Computation with SAS provides an introduction to a diverse assortment of regression techniques using SAS to solve a wide variety of regression problems. The author fully documents the SAS programs and thoroughly explains the output produced by the programs.The text presents the popular ordinary least squares (OLS) approach before introducing many alternative regression methods. It covers nonparametric regression, logistic regression (including Poisson regression), Bayesian regression, robust regression, fuzzy regression, random coefficients regression,

7. Stochastic development regression using method of moments

DEFF Research Database (Denmark)

Kühnel, Line; Sommer, Stefan Horst

2017-01-01

This paper considers the estimation problem arising when inferring parameters in the stochastic development regression model for manifold valued non-linear data. Stochastic development regression captures the relation between manifold-valued response and Euclidean covariate variables using...... the stochastic development construction. It is thereby able to incorporate several covariate variables and random effects. The model is intrinsically defined using the connection of the manifold, and the use of stochastic development avoids linearizing the geometry. We propose to infer parameters using...... the Method of Moments procedure that matches known constraints on moments of the observations conditional on the latent variables. The performance of the model is investigated in a simulation example using data on finite dimensional landmark manifolds....

8. Method for nonlinear exponential regression analysis

Science.gov (United States)

Junkin, B. G.

1972-01-01

Two computer programs developed according to two general types of exponential models for conducting nonlinear exponential regression analysis are described. Least squares procedure is used in which the nonlinear problem is linearized by expanding in a Taylor series. Program is written in FORTRAN 5 for the Univac 1108 computer.

9. A method for nonlinear exponential regression analysis

Science.gov (United States)

Junkin, B. G.

1971-01-01

A computer-oriented technique is presented for performing a nonlinear exponential regression analysis on decay-type experimental data. The technique involves the least squares procedure wherein the nonlinear problem is linearized by expansion in a Taylor series. A linear curve fitting procedure for determining the initial nominal estimates for the unknown exponential model parameters is included as an integral part of the technique. A correction matrix was derived and then applied to the nominal estimate to produce an improved set of model parameters. The solution cycle is repeated until some predetermined criterion is satisfied.

10. Analyzing Big Data with the Hybrid Interval Regression Methods

Directory of Open Access Journals (Sweden)

Chia-Hui Huang

2014-01-01

Full Text Available Big data is a new trend at present, forcing the significant impacts on information technologies. In big data applications, one of the most concerned issues is dealing with large-scale data sets that often require computation resources provided by public cloud services. How to analyze big data efficiently becomes a big challenge. In this paper, we collaborate interval regression with the smooth support vector machine (SSVM to analyze big data. Recently, the smooth support vector machine (SSVM was proposed as an alternative of the standard SVM that has been proved more efficient than the traditional SVM in processing large-scale data. In addition the soft margin method is proposed to modify the excursion of separation margin and to be effective in the gray zone that the distribution of data becomes hard to be described and the separation margin between classes.

11. Moving beyond Traditional Methods of Survey Validation

Science.gov (United States)

Maul, Andrew

2017-01-01

In his focus article, "Rethinking Traditional Methods of Survey Validation," published in this issue of "Measurement: Interdisciplinary Research and Perspectives," Andrew Maul wrote that it is commonly believed that self-report, survey-based instruments can be used to measure a wide range of psychological attributes, such as…

12. Finding-equal regression method and its application in predication of U resources

International Nuclear Information System (INIS)

Cao Huimo

1995-03-01

The commonly adopted deposit model method in mineral resources predication has two main part: one is model data that show up geological mineralization law for deposit, the other is statistics predication method that accords with characters of the data namely pretty regression method. This kind of regression method may be called finding-equal regression, which is made of the linear regression and distribution finding-equal method. Because distribution finding-equal method is a data pretreatment which accords with advanced mathematical precondition for the linear regression namely equal distribution theory, and this kind of data pretreatment is possible of realization. Therefore finding-equal regression not only can overcome nonlinear limitations, that are commonly occurred in traditional linear regression or other regression and always have no solution, but also can distinguish outliers and eliminate its weak influence, which would usually appeared when Robust regression possesses outlier in independent variables. Thus this newly finding-equal regression stands the best status in all kind of regression methods. Finally, two good examples of U resource quantitative predication are provided

13. Survey Methods, Traditional, Public Opinion Polling

DEFF Research Database (Denmark)

Elmelund-Præstekær, Christian; Hopmann, David Nicolas; Pedersen, Rasmus Tue

2017-01-01

Traditional public opinion polls are surveys in which a random sample of a given population is asked questions about their attitudes, knowledge, or behavior. If conducted properly, the answers from such surveys are approximately representative of the entire population. Traditional public opinion...... polling is typically based on four different methods of data gathering, or combinations hereof: face-to-face, postal surveys, phone surveys, and web surveys. Given that opinion polls are based on a sample, we cannot be sure that the sample reflects public opinion perfectly, however—even if randomness...... is perfect. Moreover, responses may be highly dependent on the contextual information provided with the question. Also, it may be difficult to capture past or complex causes of attitudes or behavior. In short, surveys are a precise way of measuring public opinion, but they do not come without challenges....

14. Ridge regression estimator: combining unbiased and ordinary ridge regression methods of estimation

Directory of Open Access Journals (Sweden)

2009-10-01

Full Text Available Statistical literature has several methods for coping with multicollinearity. This paper introduces a new shrinkage estimator, called modified unbiased ridge (MUR. This estimator is obtained from unbiased ridge regression (URR in the same way that ordinary ridge regression (ORR is obtained from ordinary least squares (OLS. Properties of MUR are derived. Results on its matrix mean squared error (MMSE are obtained. MUR is compared with ORR and URR in terms of MMSE. These results are illustrated with an example based on data generated by Hoerl and Kennard (1975.

15. A multiple regression method for genomewide association studies ...

Bujun Mei

2018-06-07

Jun 7, 2018 ... Similar to the typical genomewide association tests using LD ... new approach performed validly when the multiple regression based on linkage method was employed. .... the model, two groups of scenarios were simulated.

16. BOX-COX REGRESSION METHOD IN TIME SCALING

Directory of Open Access Journals (Sweden)

ATİLLA GÖKTAŞ

2013-06-01

Full Text Available Box-Cox regression method with λj, for j = 1, 2, ..., k, power transformation can be used when dependent variable and error term of the linear regression model do not satisfy the continuity and normality assumptions. The situation obtaining the smallest mean square error  when optimum power λj, transformation for j = 1, 2, ..., k, of Y has been discussed. Box-Cox regression method is especially appropriate to adjust existence skewness or heteroscedasticity of error terms for a nonlinear functional relationship between dependent and explanatory variables. In this study, the advantage and disadvantage use of Box-Cox regression method have been discussed in differentiation and differantial analysis of time scale concept.

17. On two flexible methods of 2-dimensional regression analysis

Czech Academy of Sciences Publication Activity Database

Volf, Petr

2012-01-01

Roč. 18, č. 4 (2012), s. 154-164 ISSN 1803-9782 Grant - others:GA ČR(CZ) GAP209/10/2045 Institutional support: RVO:67985556 Keywords : regression analysis * Gordon surface * prediction error * projection pursuit Subject RIV: BB - Applied Statistics, Operational Research http://library.utia.cas.cz/separaty/2013/SI/volf-on two flexible methods of 2-dimensional regression analysis.pdf

18. Thermal Efficiency Degradation Diagnosis Method Using Regression Model

International Nuclear Information System (INIS)

Jee, Chang Hyun; Heo, Gyun Young; Jang, Seok Won; Lee, In Cheol

2011-01-01

This paper proposes an idea for thermal efficiency degradation diagnosis in turbine cycles, which is based on turbine cycle simulation under abnormal conditions and a linear regression model. The correlation between the inputs for representing degradation conditions (normally unmeasured but intrinsic states) and the simulation outputs (normally measured but superficial states) was analyzed with the linear regression model. The regression models can inversely response an associated intrinsic state for a superficial state observed from a power plant. The diagnosis method proposed herein is classified into three processes, 1) simulations for degradation conditions to get measured states (referred as what-if method), 2) development of the linear model correlating intrinsic and superficial states, and 3) determination of an intrinsic state using the superficial states of current plant and the linear regression model (referred as inverse what-if method). The what-if method is to generate the outputs for the inputs including various root causes and/or boundary conditions whereas the inverse what-if method is the process of calculating the inverse matrix with the given superficial states, that is, component degradation modes. The method suggested in this paper was validated using the turbine cycle model for an operating power plant

19. Linear regression methods a ccording to objective functions

OpenAIRE

Yasemin Sisman; Sebahattin Bektas

2012-01-01

The aim of the study is to explain the parameter estimation methods and the regression analysis. The simple linear regressionmethods grouped according to the objective function are introduced. The numerical solution is achieved for the simple linear regressionmethods according to objective function of Least Squares and theLeast Absolute Value adjustment methods. The success of the appliedmethods is analyzed using their objective function values.

20. Comparing parametric and nonparametric regression methods for panel data

DEFF Research Database (Denmark)

Czekaj, Tomasz Gerard; Henningsen, Arne

We investigate and compare the suitability of parametric and non-parametric stochastic regression methods for analysing production technologies and the optimal firm size. Our theoretical analysis shows that the most commonly used functional forms in empirical production analysis, Cobb......-Douglas and Translog, are unsuitable for analysing the optimal firm size. We show that the Translog functional form implies an implausible linear relationship between the (logarithmic) firm size and the elasticity of scale, where the slope is artificially related to the substitutability between the inputs....... The practical applicability of the parametric and non-parametric regression methods is scrutinised and compared by an empirical example: we analyse the production technology and investigate the optimal size of Polish crop farms based on a firm-level balanced panel data set. A nonparametric specification test...

1. FATAL, General Experiment Fitting Program by Nonlinear Regression Method

International Nuclear Information System (INIS)

Salmon, L.; Budd, T.; Marshall, M.

1982-01-01

1 - Description of problem or function: A generalized fitting program with a free-format keyword interface to the user. It permits experimental data to be fitted by non-linear regression methods to any function describable by the user. The user requires the minimum of computer experience but needs to provide a subroutine to define his function. Some statistical output is included as well as 'best' estimates of the function's parameters. 2 - Method of solution: The regression method used is based on a minimization technique devised by Powell (Harwell Subroutine Library VA05A, 1972) which does not require the use of analytical derivatives. The method employs a quasi-Newton procedure balanced with a steepest descent correction. Experience shows this to be efficient for a very wide range of application. 3 - Restrictions on the complexity of the problem: The current version of the program permits functions to be defined with up to 20 parameters. The function may be fitted to a maximum of 400 points, preferably with estimated values of weight given

2. To Set Up a Logistic Regression Prediction Model for Hepatotoxicity of Chinese Herbal Medicines Based on Traditional Chinese Medicine Theory

Science.gov (United States)

Liu, Hongjie; Li, Tianhao; Zhan, Sha; Pan, Meilan; Ma, Zhiguo; Li, Chenghua

2016-01-01

Aims. To establish a logistic regression (LR) prediction model for hepatotoxicity of Chinese herbal medicines (HMs) based on traditional Chinese medicine (TCM) theory and to provide a statistical basis for predicting hepatotoxicity of HMs. Methods. The correlations of hepatotoxic and nonhepatotoxic Chinese HMs with four properties, five flavors, and channel tropism were analyzed with chi-square test for two-way unordered categorical data. LR prediction model was established and the accuracy of the prediction by this model was evaluated. Results. The hepatotoxic and nonhepatotoxic Chinese HMs were related with four properties (p 0.05). There were totally 12 variables from four properties and five flavors for the LR. Four variables, warm and neutral of the four properties and pungent and salty of five flavors, were selected to establish the LR prediction model, with the cutoff value being 0.204. Conclusions. Warm and neutral of the four properties and pungent and salty of five flavors were the variables to affect the hepatotoxicity. Based on such results, the established LR prediction model had some predictive power for hepatotoxicity of Chinese HMs. PMID:27656240

3. Mapping urban environmental noise: a land use regression method.

Science.gov (United States)

Xie, Dan; Liu, Yi; Chen, Jining

2011-09-01

Forecasting and preventing urban noise pollution are major challenges in urban environmental management. Most existing efforts, including experiment-based models, statistical models, and noise mapping, however, have limited capacity to explain the association between urban growth and corresponding noise change. Therefore, these conventional methods can hardly forecast urban noise at a given outlook of development layout. This paper, for the first time, introduces a land use regression method, which has been applied for simulating urban air quality for a decade, to construct an urban noise model (LUNOS) in Dalian Municipality, Northwest China. The LUNOS model describes noise as a dependent variable of surrounding various land areas via a regressive function. The results suggest that a linear model performs better in fitting monitoring data, and there is no significant difference of the LUNOS's outputs when applied to different spatial scales. As the LUNOS facilitates a better understanding of the association between land use and urban environmental noise in comparison to conventional methods, it can be regarded as a promising tool for noise prediction for planning purposes and aid smart decision-making.

4. Dimension Reduction and Discretization in Stochastic Problems by Regression Method

DEFF Research Database (Denmark)

Ditlevsen, Ove Dalager

1996-01-01

The chapter mainly deals with dimension reduction and field discretizations based directly on the concept of linear regression. Several examples of interesting applications in stochastic mechanics are also given.Keywords: Random fields discretization, Linear regression, Stochastic interpolation, ...

5. Regression and Sparse Regression Methods for Viscosity Estimation of Acid Milk From it’s Sls Features

DEFF Research Database (Denmark)

Sharifzadeh, Sara; Skytte, Jacob Lercke; Nielsen, Otto Højager Attermann

2012-01-01

Statistical solutions find wide spread use in food and medicine quality control. We investigate the effect of different regression and sparse regression methods for a viscosity estimation problem using the spectro-temporal features from new Sub-Surface Laser Scattering (SLS) vision system. From...... with sparse LAR, lasso and Elastic Net (EN) sparse regression methods. Due to the inconsistent measurement condition, Locally Weighted Scatter plot Smoothing (Loess) has been employed to alleviate the undesired variation in the estimated viscosity. The experimental results of applying different methods show...

6. Relevance of traditional methods of conflict resolution in the justice ...

African Journals Online (AJOL)

The traditional methods of African conflict resolution have long existed and are deeply rooted in the customs and traditions of the peoples of Africa. These methods are geared towards maintaining harmonious and peaceful coexistence in the community. Colonialism introduced the modern justice system, which dominated ...

7. Discussion on Regression Methods Based on Ensemble Learning and Applicability Domains of Linear Submodels.

Science.gov (United States)

Kaneko, Hiromasa

2018-02-26

To develop a new ensemble learning method and construct highly predictive regression models in chemoinformatics and chemometrics, applicability domains (ADs) are introduced into the ensemble learning process of prediction. When estimating values of an objective variable using subregression models, only the submodels with ADs that cover a query sample, i.e., the sample is inside the model's AD, are used. By constructing submodels and changing a list of selected explanatory variables, the union of the submodels' ADs, which defines the overall AD, becomes large, and the prediction performance is enhanced for diverse compounds. By analyzing a quantitative structure-activity relationship data set and a quantitative structure-property relationship data set, it is confirmed that the ADs can be enlarged and the estimation performance of regression models is improved compared with traditional methods.

8. Methods of Detecting Outliers in A Regression Analysis Model ...

African Journals Online (AJOL)

PROF. O. E. OSUAGWU

2013-06-01

Jun 1, 2013 ... especially true in observational studies .... Simple linear regression and multiple ... The simple linear ..... Grubbs,F.E (1950): Sample Criteria for Testing Outlying observations: Annals of ... In experimental design, the Relative.

9. Reliability studies of diagnostic methods in Indian traditional Ayurveda medicine

DEFF Research Database (Denmark)

Kurande, Vrinda Hitendra; Waagepetersen, Rasmus; Toft, Egon

2013-01-01

as prakriti classification), method development (pulse diagnosis), quality assurance for diagnosis and treatment and in the conduct of clinical studies. Several reliability studies are conducted in western medicine. The investigation of the reliability of traditional Chinese, Japanese and Sasang medicine...

10. Traditional methods of social control in Afikpo north local ...

African Journals Online (AJOL)

Traditional methods of social control in Afikpo north local government area, Ebonyi state south eastern Nigeria. ... Journal of Religion and Human Relations ... simple percentage was used in presenting and interpreting the quantitative data.

11. Analysis of some methods for reduced rank Gaussian process regression

DEFF Research Database (Denmark)

Quinonero-Candela, J.; Rasmussen, Carl Edward

2005-01-01

While there is strong motivation for using Gaussian Processes (GPs) due to their excellent performance in regression and classification problems, their computational complexity makes them impractical when the size of the training set exceeds a few thousand cases. This has motivated the recent...... proliferation of a number of cost-effective approximations to GPs, both for classification and for regression. In this paper we analyze one popular approximation to GPs for regression: the reduced rank approximation. While generally GPs are equivalent to infinite linear models, we show that Reduced Rank...... Gaussian Processes (RRGPs) are equivalent to finite sparse linear models. We also introduce the concept of degenerate GPs and show that they correspond to inappropriate priors. We show how to modify the RRGP to prevent it from being degenerate at test time. Training RRGPs consists both in learning...

12. Methods for identifying SNP interactions: a review on variations of Logic Regression, Random Forest and Bayesian logistic regression.

Science.gov (United States)

Chen, Carla Chia-Ming; Schwender, Holger; Keith, Jonathan; Nunkesser, Robin; Mengersen, Kerrie; Macrossan, Paula

2011-01-01

Due to advancements in computational ability, enhanced technology and a reduction in the price of genotyping, more data are being generated for understanding genetic associations with diseases and disorders. However, with the availability of large data sets comes the inherent challenges of new methods of statistical analysis and modeling. Considering a complex phenotype may be the effect of a combination of multiple loci, various statistical methods have been developed for identifying genetic epistasis effects. Among these methods, logic regression (LR) is an intriguing approach incorporating tree-like structures. Various methods have built on the original LR to improve different aspects of the model. In this study, we review four variations of LR, namely Logic Feature Selection, Monte Carlo Logic Regression, Genetic Programming for Association Studies, and Modified Logic Regression-Gene Expression Programming, and investigate the performance of each method using simulated and real genotype data. We contrast these with another tree-like approach, namely Random Forests, and a Bayesian logistic regression with stochastic search variable selection.

13. Methods for estimating disease transmission rates: Evaluating the precision of Poisson regression and two novel methods

DEFF Research Database (Denmark)

Kirkeby, Carsten Thure; Hisham Beshara Halasa, Tariq; Gussmann, Maya Katrin

2017-01-01

the transmission rate. We use data from the two simulation models and vary the sampling intervals and the size of the population sampled. We devise two new methods to determine transmission rate, and compare these to the frequently used Poisson regression method in both epidemic and endemic situations. For most...... tested scenarios these new methods perform similar or better than Poisson regression, especially in the case of long sampling intervals. We conclude that transmission rate estimates are easily biased, which is important to take into account when using these rates in simulation models....

14. Ordinary Least Squares and Quantile Regression: An Inquiry-Based Learning Approach to a Comparison of Regression Methods

Science.gov (United States)

Helmreich, James E.; Krog, K. Peter

2018-01-01

We present a short, inquiry-based learning course on concepts and methods underlying ordinary least squares (OLS), least absolute deviation (LAD), and quantile regression (QR). Students investigate squared, absolute, and weighted absolute distance functions (metrics) as location measures. Using differential calculus and properties of convex…

15. Examining Delivery Method and Infant Feeding Intentions between Women in Traditional and Non-Traditional Prenatal Care.

Science.gov (United States)

Risisky, Deb; Chan, Ronna L; Zigmont, Victoria A; Asghar, Syed Masood; DeGennaro, Nancy

2018-02-01

Introduction The purpose of the study is to evaluate delivery method and breastfeeding initiation in women enrolled in group prenatal care (CenteringPregnancy) and in traditional prenatal care. Methods Data were obtained from medical records of a hospital-based midwifery practice in south central Connecticut that offered both types of prenatal care programs. Medical information from 307 women enrolled in this practice was included in the analysis. Out of the 307, 80 were enrolled in group prenatal care. Socio-demographic, lifestyle, and previous and current obstetrical information from medical records formed the basis of comparison. Bivariate and logistic regression analyses were carried out. Results Women in Centering had fewer planned cesarean sections (1.3 vs. 12.8%) and had a higher breastfeeding initiation (88.7 vs. 80.0%). However, Centering women were found to have a higher portion of unplanned cesarean sections (27.5 vs. 11.0%). Both the unadjusted and the adjusted odds ratios of having a cesarean planned delivery were lower in the group care. Women in Centering had 2.44 (95% CI 1.05, 5.66) times the odds of breastfeeding initiation compared to the odds for women in traditional prenatal care after adjusting for maternal age, smoking status, gestation and race. Discussion CenteringPregnancy can have positive impact for the woman and baby. This program implementation saw lower rates of elective cesarean sections and increased breastfeeding compared to women in traditional care.

16. An assessment of existing common traditional methods of water ...

African Journals Online (AJOL)

Classical water purification methods include boiling, filtration, irradiation and the use of chemicals while traditional water purification methods in use are boiling, filtration, sedimentation, long storage and solar radiation. Waterborne diseases are m ore common in the rural communities where potable water supply coverage ...

17. College Students' Perceptions of the Traditional Lecture Method

Science.gov (United States)

Covill, Amy E.

2011-01-01

Fifty-one college students responded to survey questions regarding their perceptions of the traditional lecture method of instruction that they received in a 200-level psychology course. At a time when many professors are being encouraged to use active learning methods instead of lectures, it is important to consider the students' perspective. Do…

18. Comparing Traditional and Crowdsourcing Methods for Pretesting Survey Questions

Directory of Open Access Journals (Sweden)

Jennifer Edgar

2016-10-01

19. Predicting Taxi-Out Time at Congested Airports with Optimization-Based Support Vector Regression Methods

Directory of Open Access Journals (Sweden)

Guan Lian

2018-01-01

Full Text Available Accurate prediction of taxi-out time is significant precondition for improving the operationality of the departure process at an airport, as well as reducing the long taxi-out time, congestion, and excessive emission of greenhouse gases. Unfortunately, several of the traditional methods of predicting taxi-out time perform unsatisfactorily at congested airports. This paper describes and tests three of those conventional methods which include Generalized Linear Model, Softmax Regression Model, and Artificial Neural Network method and two improved Support Vector Regression (SVR approaches based on swarm intelligence algorithm optimization, which include Particle Swarm Optimization (PSO and Firefly Algorithm. In order to improve the global searching ability of Firefly Algorithm, adaptive step factor and Lévy flight are implemented simultaneously when updating the location function. Six factors are analysed, of which delay is identified as one significant factor in congested airports. Through a series of specific dynamic analyses, a case study of Beijing International Airport (PEK is tested with historical data. The performance measures show that the proposed two SVR approaches, especially the Improved Firefly Algorithm (IFA optimization-based SVR method, not only perform as the best modelling measures and accuracy rate compared with the representative forecast models, but also can achieve a better predictive performance when dealing with abnormal taxi-out time states.

20. Method validation using weighted linear regression models for quantification of UV filters in water samples.

Science.gov (United States)

da Silva, Claudia Pereira; Emídio, Elissandro Soares; de Marchi, Mary Rosa Rodrigues

2015-01-01

This paper describes the validation of a method consisting of solid-phase extraction followed by gas chromatography-tandem mass spectrometry for the analysis of the ultraviolet (UV) filters benzophenone-3, ethylhexyl salicylate, ethylhexyl methoxycinnamate and octocrylene. The method validation criteria included evaluation of selectivity, analytical curve, trueness, precision, limits of detection and limits of quantification. The non-weighted linear regression model has traditionally been used for calibration, but it is not necessarily the optimal model in all cases. Because the assumption of homoscedasticity was not met for the analytical data in this work, a weighted least squares linear regression was used for the calibration method. The evaluated analytical parameters were satisfactory for the analytes and showed recoveries at four fortification levels between 62% and 107%, with relative standard deviations less than 14%. The detection limits ranged from 7.6 to 24.1 ng L(-1). The proposed method was used to determine the amount of UV filters in water samples from water treatment plants in Araraquara and Jau in São Paulo, Brazil. Copyright © 2014 Elsevier B.V. All rights reserved.

DEFF Research Database (Denmark)

Otto, Ton

2016-01-01

: beliefs, practices, institutions, and also things. In this sense, the meaning of the term in social research is very close to its usage in common language and is not always theoretically well developed (see Shils, 1971: 123). But the concept of tradition has also been central to major theoretical debates...... on the nature of social change, especially in connection with the notion of modernity. Here tradition is linked to various forms of agency as a factor of both stability and intentional change....

2. [Application of Delphi method in traditional Chinese medicine clinical research].

Science.gov (United States)

Bi, Ying-fei; Mao, Jing-yuan

2012-03-01

In recent years, Delphi method has been widely applied in traditional Chinese medicine (TCM) clinical research. This article analyzed the present application situation of Delphi method in TCM clinical research, and discussed some problems presented in the choice of evaluation method, classification of observation indexes and selection of survey items. On the basis of present application of Delphi method, the author analyzed the method on questionnaire making, selection of experts, evaluation of observation indexes and selection of survey items. Furthermore, the author summarized the steps of application of Delphi method in TCM clinical research.

3. Bacterial population in traditional sourdough evaluated by molecular methods

NARCIS (Netherlands)

Randazzo, C.L.; Heilig, G.H.J.; Restuccia, C.; Giudici, P.; Caggia, C.

2005-01-01

Aims: To study the microbial communities in artisanal sourdoughs, manufactured by traditional procedure in different areas of Sicily, and to evaluate the lactic acid bacteria (LAB) population by classical and culture-independent approaches. Methods and Results: Forty-five LAB isolates were

4. Comparison of traditional physico-chemical methods and molecular ...

African Journals Online (AJOL)

This study was aim to review the efficiency of molecular markers and traditional physico-chemical methods for the identification of basmati rice. The study involved 44 promising varieties of Indica rices collected from geographically distant places and adapted to irrigated and aerobic agro-ecosystems. Quality data for ...

5. Traditional and New methods for the Preparation of Diazocarbonyl Compounds

Directory of Open Access Journals (Sweden)

ANTONIO C.B. BURTOLOSO

2018-04-01

Full Text Available ABSTRACT For many years diazocarbonyl compounds have been studied due to their versatility and usability in many chemical transformations. In this review, we summarize the traditional methods to prepare these compounds as well as the new methods and recent improvements in experimental procedures. Moreover, emergence of continuous flow techniques has allowed safer and environmentally friendly procedures for the handling of diazomethane and diazo compounds and will also be a topic in this review.

6. Geographically weighted regression based methods for merging satellite and gauge precipitation

Science.gov (United States)

Chao, Lijun; Zhang, Ke; Li, Zhijia; Zhu, Yuelong; Wang, Jingfeng; Yu, Zhongbo

2018-03-01

Real-time precipitation data with high spatiotemporal resolutions are crucial for accurate hydrological forecasting. To improve the spatial resolution and quality of satellite precipitation, a three-step satellite and gauge precipitation merging method was formulated in this study: (1) bilinear interpolation is first applied to downscale coarser satellite precipitation to a finer resolution (PS); (2) the (mixed) geographically weighted regression methods coupled with a weighting function are then used to estimate biases of PS as functions of gauge observations (PO) and PS; and (3) biases of PS are finally corrected to produce a merged precipitation product. Based on the above framework, eight algorithms, a combination of two geographically weighted regression methods and four weighting functions, are developed to merge CMORPH (CPC MORPHing technique) precipitation with station observations on a daily scale in the Ziwuhe Basin of China. The geographical variables (elevation, slope, aspect, surface roughness, and distance to the coastline) and a meteorological variable (wind speed) were used for merging precipitation to avoid the artificial spatial autocorrelation resulting from traditional interpolation methods. The results show that the combination of the MGWR and BI-square function (MGWR-BI) has the best performance (R = 0.863 and RMSE = 7.273 mm/day) among the eight algorithms. The MGWR-BI algorithm was then applied to produce hourly merged precipitation product. Compared to the original CMORPH product (R = 0.208 and RMSE = 1.208 mm/hr), the quality of the merged data is significantly higher (R = 0.724 and RMSE = 0.706 mm/hr). The developed merging method not only improves the spatial resolution and quality of the satellite product but also is easy to implement, which is valuable for hydrological modeling and other applications.

7. Ethnomathematics: The use of multiple linier regression Y = b 1 X 1 + b 2 X 2 + e in traditional house construction Saka Roras in Songan Village

Science.gov (United States)

Darmayasa, J. B.; Wahyudin; Mulyana, T.

2018-01-01

Ethnomathematics may be the connecting bridge between culture and technology and arts. Therefore, the exploration of mathematics values that intersects with cultural anthropology should be significantly conducted. One case containing such issue is the construction of Traditional House of Saka Roras in Bali. Thus, this research aimed to explore the mathematic concept adopted in the construction of such traditional Bale (house) located in Songan Village, Kintamani, Bali. Specifically, this research also aimed to investigate the selection of linear regression coefficient for the saka (pillar) in the Bale. This research applied Embedded Mix-Method Design. Meanwhile, the data collection was conducted by interview, observation and measurement of pillars of 32 Bale Saka Roras. The result of this research revealed that the connection between the width and height of pillars was stated in the formula Y = 26,3 + 18,2X, where X acted as stimulus variable. The coefficient value amounted to 18.2 showed that most preceding architects in Songan Village were more likely to use 19 as the coefficient towards the pillar width than the other coefficients such as 17, 20 and 21 as mentioned in book/palm-leaf manuscript entitled Kosala-Kosali. The last but not least, the researchers also figured out that the pillar width depended on the length of the house-owner candidate’s index finger.

8. Traditions and Alcohol Use: A Mixed-Methods Analysis

Science.gov (United States)

Castro, Felipe González; Coe, Kathryn

2011-01-01

An integrative mixed-methods analysis examined traditional beliefs as associated with beliefs about self-care during pregnancy and with alcohol abstinence among young adult women from two rural U.S.–Mexico border communities. Quantitative (measured scale) variables and qualitative thematic variables generated from open-ended responses served as within-time predictors of these health-related outcomes. A weaker belief that life is better in big cities was associated with stronger self-care beliefs during pregnancy. Also, a weaker belief that small towns offer tranquil environments was associated with total abstinence from alcohol. Regarding the Hispanic Paradox, these results suggest that a critical appreciation of cultural traditions can be protective, as this avoids stereotypical or idyllic views of urban or rural lifeways, and promotes self-protective beliefs and behaviors. PMID:17967095

9. Parameter Selection Method for Support Vector Regression Based on Adaptive Fusion of the Mixed Kernel Function

Directory of Open Access Journals (Sweden)

Hailun Wang

2017-01-01

Full Text Available Support vector regression algorithm is widely used in fault diagnosis of rolling bearing. A new model parameter selection method for support vector regression based on adaptive fusion of the mixed kernel function is proposed in this paper. We choose the mixed kernel function as the kernel function of support vector regression. The mixed kernel function of the fusion coefficients, kernel function parameters, and regression parameters are combined together as the parameters of the state vector. Thus, the model selection problem is transformed into a nonlinear system state estimation problem. We use a 5th-degree cubature Kalman filter to estimate the parameters. In this way, we realize the adaptive selection of mixed kernel function weighted coefficients and the kernel parameters, the regression parameters. Compared with a single kernel function, unscented Kalman filter (UKF support vector regression algorithms, and genetic algorithms, the decision regression function obtained by the proposed method has better generalization ability and higher prediction accuracy.

Science.gov (United States)

Lewis, Roger D; Ong, Kee Hean; Emo, Brett; Kennedy, Jason; Brown, Christopher A; Condoor, Sridhar; Thummalakunta, Laxmi

2012-01-01

11. The Use of Nonparametric Kernel Regression Methods in Econometric Production Analysis

DEFF Research Database (Denmark)

Czekaj, Tomasz Gerard

and nonparametric estimations of production functions in order to evaluate the optimal firm size. The second paper discusses the use of parametric and nonparametric regression methods to estimate panel data regression models. The third paper analyses production risk, price uncertainty, and farmers' risk preferences...... within a nonparametric panel data regression framework. The fourth paper analyses the technical efficiency of dairy farms with environmental output using nonparametric kernel regression in a semiparametric stochastic frontier analysis. The results provided in this PhD thesis show that nonparametric......This PhD thesis addresses one of the fundamental problems in applied econometric analysis, namely the econometric estimation of regression functions. The conventional approach to regression analysis is the parametric approach, which requires the researcher to specify the form of the regression...

12. The ethics of improving African traditional medical practice: scientific or African traditional research methods?

Science.gov (United States)

Nyika, Aceme

2009-11-01

13. Bacterial population in traditional sourdough evaluated by molecular methods.

Science.gov (United States)

Randazzo, C L; Heilig, H; Restuccia, C; Giudici, P; Caggia, C

2005-01-01

To study the microbial communities in artisanal sourdoughs, manufactured by traditional procedure in different areas of Sicily, and to evaluate the lactic acid bacteria (LAB) population by classical and culture-independent approaches. Forty-five LAB isolates were identified both by phenotypic and molecular methods. The restriction fragment length polymorphism and 16S ribosomal DNA gene sequencing gave evidence of a variety of species with the dominance of Lactobacillus sanfranciscensis and Lactobacillus pentosus, in all sourdoughs tested. Culture-independent method, such as denaturing gradient gel electrophoresis (DGGE) of the V6-V8 regions of the 16S rDNA, was applied for microbial community fingerprint. The DGGE profiles revealed the dominance of L. sanfranciscensis species. In addition, Lactobacillus-specific primers were used to amplify the V1-V3 regions of the 16S rDNA. DGGE profiles flourished the dominance of L. sanfranciscensis and Lactobacillus fermentum in the traditional sourdoughs, and revealed that the closely related species Lactobacillus kimchii and Lactobacillus alimentarius were not discriminated. Lactobacillus-specific PCR-DGGE analysis is a rapid tool for rapid detection of Lactobacillus species in artisanal sourdough. This study reports a characterization of Lactobacillus isolates from artisanal sourdoughs and highlights the value of DGGE approach to detect uncultivable Lactobacillus species.

14. Two-Stage Method Based on Local Polynomial Fitting for a Linear Heteroscedastic Regression Model and Its Application in Economics

Directory of Open Access Journals (Sweden)

Liyun Su

2012-01-01

Full Text Available We introduce the extension of local polynomial fitting to the linear heteroscedastic regression model. Firstly, the local polynomial fitting is applied to estimate heteroscedastic function, then the coefficients of regression model are obtained by using generalized least squares method. One noteworthy feature of our approach is that we avoid the testing for heteroscedasticity by improving the traditional two-stage method. Due to nonparametric technique of local polynomial estimation, we do not need to know the heteroscedastic function. Therefore, we can improve the estimation precision, when the heteroscedastic function is unknown. Furthermore, we focus on comparison of parameters and reach an optimal fitting. Besides, we verify the asymptotic normality of parameters based on numerical simulations. Finally, this approach is applied to a case of economics, and it indicates that our method is surely effective in finite-sample situations.

15. Easy methods for extracting individual regression slopes: Comparing SPSS, R, and Excel

Directory of Open Access Journals (Sweden)

Roland Pfister

2013-10-01

Full Text Available Three different methods for extracting coefficientsof linear regression analyses are presented. The focus is on automatic and easy-to-use approaches for common statistical packages: SPSS, R, and MS Excel / LibreOffice Calc. Hands-on examples are included for each analysis, followed by a brief description of how a subsequent regression coefficient analysis is performed.

16. A simple linear regression method for quantitative trait loci linkage analysis with censored observations.

Science.gov (United States)

Anderson, Carl A; McRae, Allan F; Visscher, Peter M

2006-07-01

Standard quantitative trait loci (QTL) mapping techniques commonly assume that the trait is both fully observed and normally distributed. When considering survival or age-at-onset traits these assumptions are often incorrect. Methods have been developed to map QTL for survival traits; however, they are both computationally intensive and not available in standard genome analysis software packages. We propose a grouped linear regression method for the analysis of continuous survival data. Using simulation we compare this method to both the Cox and Weibull proportional hazards models and a standard linear regression method that ignores censoring. The grouped linear regression method is of equivalent power to both the Cox and Weibull proportional hazards methods and is significantly better than the standard linear regression method when censored observations are present. The method is also robust to the proportion of censored individuals and the underlying distribution of the trait. On the basis of linear regression methodology, the grouped linear regression model is computationally simple and fast and can be implemented readily in freely available statistical software.

17. Operational auditing versus traditional method: A comparative investigation

Directory of Open Access Journals (Sweden)

Reza Tehrani

2013-06-01

Full Text Available Operational auditing is one of the management consultancy services whose significance is on the rise day by day. This approach is, clearly, a systematic and methodical process used to evaluate economic savings of financial processes in organizations and the results of the evaluations are reported to interested people along with some comments to improve operational processes. Accordingly, it appears that the proper employment of the existing rationale in operational auditing can be a significant step towards the improvement of financial efficiency in Iranian public and private banking sector. This paper studies the effects of operational auditing on the improvement of economic saving of financial processes in Iranian private banks compared with traditional approaches where the operations are based on financial statements. The population of this survey includes 15 private and public Iranian banks and the proposed study selects 78 branches, randomly. The Cronbach alpha was used to test the reliability a questionnaire employed to collect the needed data in this study. The results obtained by SPSS Software indicated that the reliability of the instrumentsanged between 0.752 and 0.867, suggesting an acceptable level of the reliability for the questionnaire. Besides, content validity was used to confirm the validity of the instrument. The results of the study indicated that the operational auditing as a useful approach influencing the financial efficiency of public and private banks has significantly transformed the traditional thinking in the field of management auditing. The operational auditing has a number of significant advantages including a better method of controlling financial operations within Iranian banks, efficient planning in the future, facilitating efficient, appropriate, and accurate management decision making, and sound evaluation of managers’ financial operations.

18. Linear regression based on Minimum Covariance Determinant (MCD) and TELBS methods on the productivity of phytoplankton

Science.gov (United States)

Gusriani, N.; Firdaniza

2018-03-01

The existence of outliers on multiple linear regression analysis causes the Gaussian assumption to be unfulfilled. If the Least Square method is forcedly used on these data, it will produce a model that cannot represent most data. For that, we need a robust regression method against outliers. This paper will compare the Minimum Covariance Determinant (MCD) method and the TELBS method on secondary data on the productivity of phytoplankton, which contains outliers. Based on the robust determinant coefficient value, MCD method produces a better model compared to TELBS method.

19. Oil pulling: A traditional method on the edge of evidence

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H Mythri

2017-01-01

Full Text Available Introduction: Oil pulling is an ancient, traditional folk remedy that has been practiced for centuries in India and southern Asia as a holistic Ayurvedic technique. The practice of oil pulling involves placing a tablespoon of an edible oil (e.g. sesame, olive, sunflower, coconut inside the mouth, and swishing or “pulling” the oil through the teeth and oral cavity for anywhere from 1–5 minutes to up to 20 minutes or longer. Materials and Methods: Articles related to oil pulling were collected by using oil pulling as Keyword in Google and Medline. Out of the 21 related articles published till 2016, 6 articles with the proper study designs were used for analysis. Results: The studies were unreliable for many reasons, including the misinterpretation of results due to small sample size and improper study design. Conclusion: Though the promoters claim it as one of the best method to be as adjuvant to mechanical control methods, scientific evidences are lacking.

20. A nonparametric approach to calculate critical micelle concentrations: the local polynomial regression method

Energy Technology Data Exchange (ETDEWEB)

Lopez Fontan, J.L.; Costa, J.; Ruso, J.M.; Prieto, G. [Dept. of Applied Physics, Univ. of Santiago de Compostela, Santiago de Compostela (Spain); Sarmiento, F. [Dept. of Mathematics, Faculty of Informatics, Univ. of A Coruna, A Coruna (Spain)

2004-02-01

The application of a statistical method, the local polynomial regression method, (LPRM), based on a nonparametric estimation of the regression function to determine the critical micelle concentration (cmc) is presented. The method is extremely flexible because it does not impose any parametric model on the subjacent structure of the data but rather allows the data to speak for themselves. Good concordance of cmc values with those obtained by other methods was found for systems in which the variation of a measured physical property with concentration showed an abrupt change. When this variation was slow, discrepancies between the values obtained by LPRM and others methods were found. (orig.)

1. Predictors of Traditional Medical Practices in Illness Behavior in Northwestern Ethiopia: An Integrated Model of Behavioral Prediction Based Logistic Regression Analysis

Directory of Open Access Journals (Sweden)

Abenezer Yared

2017-01-01

Full Text Available This study aimed at investigating traditional medical beliefs and practices in illness behavior as well as predictors of the practices in Gondar city, northwestern Ethiopia, by using the integrated model of behavioral prediction. A cross-sectional quantitative survey was conducted to collect data through interviewer administered structured questionnaires from 496 individuals selected by probability proportional to size sampling technique. Unadjusted bivariate and adjusted multivariate logistic regression analyses were performed, and the results indicated that sociocultural predictors of normative response and attitude as well as psychosocial individual difference variables of traditional understanding of illness causation and perceived efficacy had statistically significant associations with traditional medical practices. Due to the influence of these factors, majority of the study population (85% thus relied on both herbal and spiritual varieties of traditional medicine to respond to their perceived illnesses, supporting the conclusion that characterized the illness behavior of the people as mainly involving traditional medical practices. The results implied two-way medicine needs to be developed with ongoing research, and health educations must take the traditional customs into consideration, for integrating interventions in the health care system in ways that the general public accepts yielding a better health outcome.

2. Fuzzy Linear Regression for the Time Series Data which is Fuzzified with SMRGT Method

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Seçil YALAZ

2016-10-01

Full Text Available Our work on regression and classification provides a new contribution to the analysis of time series used in many areas for years. Owing to the fact that convergence could not obtained with the methods used in autocorrelation fixing process faced with time series regression application, success is not met or fall into obligation of changing the models’ degree. Changing the models’ degree may not be desirable in every situation. In our study, recommended for these situations, time series data was fuzzified by using the simple membership function and fuzzy rule generation technique (SMRGT and to estimate future an equation has created by applying fuzzy least square regression (FLSR method which is a simple linear regression method to this data. Although SMRGT has success in determining the flow discharge in open channels and can be used confidently for flow discharge modeling in open canals, as well as in pipe flow with some modifications, there is no clue about that this technique is successful in fuzzy linear regression modeling. Therefore, in order to address the luck of such a modeling, a new hybrid model has been described within this study. In conclusion, to demonstrate our methods’ efficiency, classical linear regression for time series data and linear regression for fuzzy time series data were applied to two different data sets, and these two approaches performances were compared by using different measures.

3. An NCME Instructional Module on Data Mining Methods for Classification and Regression

Science.gov (United States)

Sinharay, Sandip

2016-01-01

Data mining methods for classification and regression are becoming increasingly popular in various scientific fields. However, these methods have not been explored much in educational measurement. This module first provides a review, which should be accessible to a wide audience in education measurement, of some of these methods. The module then…

4. Further Insight and Additional Inference Methods for Polynomial Regression Applied to the Analysis of Congruence

Science.gov (United States)

Cohen, Ayala; Nahum-Shani, Inbal; Doveh, Etti

2010-01-01

In their seminal paper, Edwards and Parry (1993) presented the polynomial regression as a better alternative to applying difference score in the study of congruence. Although this method is increasingly applied in congruence research, its complexity relative to other methods for assessing congruence (e.g., difference score methods) was one of the…

5. Statistical approach for selection of regression model during validation of bioanalytical method

Directory of Open Access Journals (Sweden)

Natalija Nakov

2014-06-01

Full Text Available The selection of an adequate regression model is the basis for obtaining accurate and reproducible results during the bionalytical method validation. Given the wide concentration range, frequently present in bioanalytical assays, heteroscedasticity of the data may be expected. Several weighted linear and quadratic regression models were evaluated during the selection of the adequate curve fit using nonparametric statistical tests: One sample rank test and Wilcoxon signed rank test for two independent groups of samples. The results obtained with One sample rank test could not give statistical justification for the selection of linear vs. quadratic regression models because slight differences between the error (presented through the relative residuals were obtained. Estimation of the significance of the differences in the RR was achieved using Wilcoxon signed rank test, where linear and quadratic regression models were treated as two independent groups. The application of this simple non-parametric statistical test provides statistical confirmation of the choice of an adequate regression model.

6. Internet-based versus traditional teaching and learning methods.

Science.gov (United States)

Guarino, Salvatore; Leopardi, Eleonora; Sorrenti, Salvatore; De Antoni, Enrico; Catania, Antonio; Alagaratnam, Swethan

2014-10-01

7. Methods of Conflict Resolution in African Traditional Society | Ajayi ...

African Journals Online (AJOL)

This study examined the patterns or mechanism for conflict resolution in traditional African societies with particular reference to Yoruba and Igbo societies in Nigeria and Pondo tribe in South Africa. The paper notes that conflict resolution in traditional African societies provides opportunity to interact with the parties ...

8. COMPARISON OF PARTIAL LEAST SQUARES REGRESSION METHOD ALGORITHMS: NIPALS AND PLS-KERNEL AND AN APPLICATION

Directory of Open Access Journals (Sweden)

ELİF BULUT

2013-06-01

Full Text Available Partial Least Squares Regression (PLSR is a multivariate statistical method that consists of partial least squares and multiple linear regression analysis. Explanatory variables, X, having multicollinearity are reduced to components which explain the great amount of covariance between explanatory and response variable. These components are few in number and they don’t have multicollinearity problem. Then multiple linear regression analysis is applied to those components to model the response variable Y. There are various PLSR algorithms. In this study NIPALS and PLS-Kernel algorithms will be studied and illustrated on a real data set.

9. The Bland-Altman Method Should Not Be Used in Regression Cross-Validation Studies

Science.gov (United States)

O'Connor, Daniel P.; Mahar, Matthew T.; Laughlin, Mitzi S.; Jackson, Andrew S.

2011-01-01

The purpose of this study was to demonstrate the bias in the Bland-Altman (BA) limits of agreement method when it is used to validate regression models. Data from 1,158 men were used to develop three regression equations to estimate maximum oxygen uptake (R[superscript 2] = 0.40, 0.61, and 0.82, respectively). The equations were evaluated in a…

10. An evaluation of regression methods to estimate nutritional condition of canvasbacks and other water birds

Science.gov (United States)

Sparling, D.W.; Barzen, J.A.; Lovvorn, J.R.; Serie, J.R.

1992-01-01

Regression equations that use mensural data to estimate body condition have been developed for several water birds. These equations often have been based on data that represent different sexes, age classes, or seasons, without being adequately tested for intergroup differences. We used proximate carcass analysis of 538 adult and juvenile canvasbacks (Aythya valisineria ) collected during fall migration, winter, and spring migrations in 1975-76 and 1982-85 to test regression methods for estimating body condition.

11. Treating experimental data of inverse kinetic method by unitary linear regression analysis

International Nuclear Information System (INIS)

Zhao Yusen; Chen Xiaoliang

2009-01-01

The theory of treating experimental data of inverse kinetic method by unitary linear regression analysis was described. Not only the reactivity, but also the effective neutron source intensity could be calculated by this method. Computer code was compiled base on the inverse kinetic method and unitary linear regression analysis. The data of zero power facility BFS-1 in Russia were processed and the results were compared. The results show that the reactivity and the effective neutron source intensity can be obtained correctly by treating experimental data of inverse kinetic method using unitary linear regression analysis and the precision of reactivity measurement is improved. The central element efficiency can be calculated by using the reactivity. The result also shows that the effect to reactivity measurement caused by external neutron source should be considered when the reactor power is low and the intensity of external neutron source is strong. (authors)

12. Regression Methods for Virtual Metrology of Layer Thickness in Chemical Vapor Deposition

DEFF Research Database (Denmark)

Purwins, Hendrik; Barak, Bernd; Nagi, Ahmed

2014-01-01

The quality of wafer production in semiconductor manufacturing cannot always be monitored by a costly physical measurement. Instead of measuring a quantity directly, it can be predicted by a regression method (Virtual Metrology). In this paper, a survey on regression methods is given to predict...... average Silicon Nitride cap layer thickness for the Plasma Enhanced Chemical Vapor Deposition (PECVD) dual-layer metal passivation stack process. Process and production equipment Fault Detection and Classification (FDC) data are used as predictor variables. Various variable sets are compared: one most...... algorithm, and Support Vector Regression (SVR). On a test set, SVR outperforms the other methods by a large margin, being more robust towards changes in the production conditions. The method performs better on high-dimensional multivariate input data than on the most predictive variables alone. Process...

13. Statistical methods in regression and calibration analysis of chromosome aberration data

International Nuclear Information System (INIS)

Merkle, W.

1983-01-01

The method of iteratively reweighted least squares for the regression analysis of Poisson distributed chromosome aberration data is reviewed in the context of other fit procedures used in the cytogenetic literature. As an application of the resulting regression curves methods for calculating confidence intervals on dose from aberration yield are described and compared, and, for the linear quadratic model a confidence interval is given. Emphasis is placed on the rational interpretation and the limitations of various methods from a statistical point of view. (orig./MG)

14. An Introduction to Graphical and Mathematical Methods for Detecting Heteroscedasticity in Linear Regression.

Science.gov (United States)

Thompson, Russel L.

Homoscedasticity is an important assumption of linear regression. This paper explains what it is and why it is important to the researcher. Graphical and mathematical methods for testing the homoscedasticity assumption are demonstrated. Sources of homoscedasticity and types of homoscedasticity are discussed, and methods for correction are…

15. Calculation of U, Ra, Th and K contents in uranium ore by multiple linear regression method

International Nuclear Information System (INIS)

Lin Chao; Chen Yingqiang; Zhang Qingwen; Tan Fuwen; Peng Guanghui

1991-01-01

A multiple linear regression method was used to compute γ spectra of uranium ore samples and to calculate contents of U, Ra, Th, and K. In comparison with the inverse matrix method, its advantage is that no standard samples of pure U, Ra, Th and K are needed for obtaining response coefficients

16. Comparing treatment effects after adjustment with multivariable Cox proportional hazards regression and propensity score methods

NARCIS (Netherlands)

Martens, Edwin P; de Boer, Anthonius; Pestman, Wiebe R; Belitser, Svetlana V; Stricker, Bruno H Ch; Klungel, Olaf H

PURPOSE: To compare adjusted effects of drug treatment for hypertension on the risk of stroke from propensity score (PS) methods with a multivariable Cox proportional hazards (Cox PH) regression in an observational study with censored data. METHODS: From two prospective population-based cohort

17. Impact of traditional processing methods on some physico chemical ...

African Journals Online (AJOL)

AJB SERVER

2006-10-16

Oct 16, 2006 ... 1Department of Food Science and Technology, University of ... need to educate traditional processors on good manufacturing practices, .... Table 3. Physical Contaminants in Fermented Cassava flour (“Kpor Umilin”) Samples.

18. Methods of Conflict Resolution in African Traditional Society

African Journals Online (AJOL)

Toshiba

Department of History and International Studies. Faculty of Arts, Ekiti State ... and market brawls, skirmishes and wars, public insurrections and assaults. ..... treaty making by traditional rulers and leaders of thought led by Igwe. Nzekwesi, for ...

19. Regression analysis of radial artery pulse palpation as a potential tool for traditional Chinese medicine training education.

Science.gov (United States)

Huang, Po-Yu; Lin, Wen-Chen; Chiu, Bill Yuan-Chi; Chang, Hen-Hong; Lin, Kang-Ping

2013-12-01

Pulse palpation was an important part of the traditional Chinese medicine (TCM) vascular examination. It is challenging for new physicians to learn to differentiate between palpations of various pulse types, due to limited comparative learning time with established masters, and so normally it takes many years to master the art. The purpose of this study was to introduce an offline TCM skill evaluation and comparison system that makes available learning of palpation without the master's presence. We record patient's radial artery pulse using an existing pressure-based pulse acquisition system, then annotate it with teachers' evaluation when palpating the same patient, assigned as likelihood of it being each pulse type, e.g. wiry, slippery, hesitant. These training data were separated into per-doctor and per-skill databases for evaluation and comparison purposes, using the following novel procedure: each database was used as training data to a panel of time-series data-mining algorithms, driven by two validation tests, with the created training models evaluated in mean-squared-error. Each validation of the panel and training data yielded an array of error terms, and we chose one to quantitatively evaluate palpation techniques, giving way to compute self consistency and mutual-similarity across different practitioners and techniques. Our experiment of two practitioners and 396 per-processing samples yielded the following: one of the physicians has much higher value of self-consistency for all tested pulse types. Also, the two physicians have high similarity in how they palpate the slipper pulse (P) type, but very dissimilar for hesitant (H) type. This system of skill comparisons may be more broadly applied in places where supervised learning algorithms can detect and use meaningful features in the data; we chose a panel of algorithms previously shown to be effective for many time-series types, but specialized algorithms may be added to improve feature-specific aspect

20. Whole-Genome Regression and Prediction Methods Applied to Plant and Animal Breeding

Science.gov (United States)

de los Campos, Gustavo; Hickey, John M.; Pong-Wong, Ricardo; Daetwyler, Hans D.; Calus, Mario P. L.

2013-01-01

Genomic-enabled prediction is becoming increasingly important in animal and plant breeding and is also receiving attention in human genetics. Deriving accurate predictions of complex traits requires implementing whole-genome regression (WGR) models where phenotypes are regressed on thousands of markers concurrently. Methods exist that allow implementing these large-p with small-n regressions, and genome-enabled selection (GS) is being implemented in several plant and animal breeding programs. The list of available methods is long, and the relationships between them have not been fully addressed. In this article we provide an overview of available methods for implementing parametric WGR models, discuss selected topics that emerge in applications, and present a general discussion of lessons learned from simulation and empirical data analysis in the last decade. PMID:22745228

1. Traditional and robust vector selection methods for use with similarity based models

International Nuclear Information System (INIS)

Hines, J. W.; Garvey, D. R.

2006-01-01

Vector selection, or instance selection as it is often called in the data mining literature, performs a critical task in the development of nonparametric, similarity based models. Nonparametric, similarity based modeling (SBM) is a form of 'lazy learning' which constructs a local model 'on the fly' by comparing a query vector to historical, training vectors. For large training sets the creation of local models may become cumbersome, since each training vector must be compared to the query vector. To alleviate this computational burden, varying forms of training vector sampling may be employed with the goal of selecting a subset of the training data such that the samples are representative of the underlying process. This paper describes one such SBM, namely auto-associative kernel regression (AAKR), and presents five traditional vector selection methods and one robust vector selection method that may be used to select prototype vectors from a larger data set in model training. The five traditional vector selection methods considered are min-max, vector ordering, combination min-max and vector ordering, fuzzy c-means clustering, and Adeli-Hung clustering. Each method is described in detail and compared using artificially generated data and data collected from the steam system of an operating nuclear power plant. (authors)

2. An improved partial least-squares regression method for Raman spectroscopy

Science.gov (United States)

Momenpour Tehran Monfared, Ali; Anis, Hanan

2017-10-01

It is known that the performance of partial least-squares (PLS) regression analysis can be improved using the backward variable selection method (BVSPLS). In this paper, we further improve the BVSPLS based on a novel selection mechanism. The proposed method is based on sorting the weighted regression coefficients, and then the importance of each variable of the sorted list is evaluated using root mean square errors of prediction (RMSEP) criterion in each iteration step. Our Improved BVSPLS (IBVSPLS) method has been applied to leukemia and heparin data sets and led to an improvement in limit of detection of Raman biosensing ranged from 10% to 43% compared to PLS. Our IBVSPLS was also compared to the jack-knifing (simpler) and Genetic Algorithm (more complex) methods. Our method was consistently better than the jack-knifing method and showed either a similar or a better performance compared to the genetic algorithm.

3. The Research of Regression Method for Forecasting Monthly Electricity Sales Considering Coupled Multi-factor

Science.gov (United States)

Wang, Jiangbo; Liu, Junhui; Li, Tiantian; Yin, Shuo; He, Xinhui

2018-01-01

The monthly electricity sales forecasting is a basic work to ensure the safety of the power system. This paper presented a monthly electricity sales forecasting method which comprehensively considers the coupled multi-factors of temperature, economic growth, electric power replacement and business expansion. The mathematical model is constructed by using regression method. The simulation results show that the proposed method is accurate and effective.

4. Estimating traffic volume on Wyoming low volume roads using linear and logistic regression methods

Directory of Open Access Journals (Sweden)

Dick Apronti

2016-12-01

5. Direct integral linear least square regression method for kinetic evaluation of hepatobiliary scintigraphy

International Nuclear Information System (INIS)

Shuke, Noriyuki

1991-01-01

In hepatobiliary scintigraphy, kinetic model analysis, which provides kinetic parameters like hepatic extraction or excretion rate, have been done for quantitative evaluation of liver function. In this analysis, unknown model parameters are usually determined using nonlinear least square regression method (NLS method) where iterative calculation and initial estimate for unknown parameters are required. As a simple alternative to NLS method, direct integral linear least square regression method (DILS method), which can determine model parameters by a simple calculation without initial estimate, is proposed, and tested the applicability to analysis of hepatobiliary scintigraphy. In order to see whether DILS method could determine model parameters as good as NLS method, or to determine appropriate weight for DILS method, simulated theoretical data based on prefixed parameters were fitted to 1 compartment model using both DILS method with various weightings and NLS method. The parameter values obtained were then compared with prefixed values which were used for data generation. The effect of various weights on the error of parameter estimate was examined, and inverse of time was found to be the best weight to make the error minimum. When using this weight, DILS method could give parameter values close to those obtained by NLS method and both parameter values were very close to prefixed values. With appropriate weighting, the DILS method could provide reliable parameter estimate which is relatively insensitive to the data noise. In conclusion, the DILS method could be used as a simple alternative to NLS method, providing reliable parameter estimate. (author)

6. A different approach to estimate nonlinear regression model using numerical methods

Science.gov (United States)

Mahaboob, B.; Venkateswarlu, B.; Mokeshrayalu, G.; Balasiddamuni, P.

2017-11-01

This research paper concerns with the computational methods namely the Gauss-Newton method, Gradient algorithm methods (Newton-Raphson method, Steepest Descent or Steepest Ascent algorithm method, the Method of Scoring, the Method of Quadratic Hill-Climbing) based on numerical analysis to estimate parameters of nonlinear regression model in a very different way. Principles of matrix calculus have been used to discuss the Gradient-Algorithm methods. Yonathan Bard [1] discussed a comparison of gradient methods for the solution of nonlinear parameter estimation problems. However this article discusses an analytical approach to the gradient algorithm methods in a different way. This paper describes a new iterative technique namely Gauss-Newton method which differs from the iterative technique proposed by Gorden K. Smyth [2]. Hans Georg Bock et.al [10] proposed numerical methods for parameter estimation in DAE’s (Differential algebraic equation). Isabel Reis Dos Santos et al [11], Introduced weighted least squares procedure for estimating the unknown parameters of a nonlinear regression metamodel. For large-scale non smooth convex minimization the Hager and Zhang (HZ) conjugate gradient Method and the modified HZ (MHZ) method were presented by Gonglin Yuan et al [12].

7. Feminist Policy Analysis: Expanding Traditional Social Work Methods

Science.gov (United States)

Kanenberg, Heather

2013-01-01

In an effort to move the methodology of policy analysis beyond the traditional and artificial position of being objective and value-free, this article is a call to those working and teaching in social work to consider a feminist policy analysis lens. A review of standard policy analysis models is presented alongside feminist models. Such a…

8. Performance of traditional and direct labour procurement methods ...

African Journals Online (AJOL)

The objective was to find out if one has any advantage over the other. Project success determinants like cost, time and quality formed the basis for ... and unit cost of projects were higher for those procured using the traditional contract system.

9. Non-traditional vibration mitigation methods for reciprocating compressor system

NARCIS (Netherlands)

Eijk, A.; Lange, T.J. de; Vreugd, J. de; Slis, E.J.P.

2016-01-01

Reciprocating compressors generate vibrations caused by pulsation-induced forces, mechanical (unbalanced) free forces and moments, crosshead guide forces and cylinder stretch forces. The traditional way of mitigating the vibration and cyclic stress levels to avoid fatigue failure of parts of the

10. Regression dilution bias: tools for correction methods and sample size calculation.

Science.gov (United States)

Berglund, Lars

2012-08-01

Random errors in measurement of a risk factor will introduce downward bias of an estimated association to a disease or a disease marker. This phenomenon is called regression dilution bias. A bias correction may be made with data from a validity study or a reliability study. In this article we give a non-technical description of designs of reliability studies with emphasis on selection of individuals for a repeated measurement, assumptions of measurement error models, and correction methods for the slope in a simple linear regression model where the dependent variable is a continuous variable. Also, we describe situations where correction for regression dilution bias is not appropriate. The methods are illustrated with the association between insulin sensitivity measured with the euglycaemic insulin clamp technique and fasting insulin, where measurement of the latter variable carries noticeable random error. We provide software tools for estimation of a corrected slope in a simple linear regression model assuming data for a continuous dependent variable and a continuous risk factor from a main study and an additional measurement of the risk factor in a reliability study. Also, we supply programs for estimation of the number of individuals needed in the reliability study and for choice of its design. Our conclusion is that correction for regression dilution bias is seldom applied in epidemiological studies. This may cause important effects of risk factors with large measurement errors to be neglected.

11. Estimation of Fine Particulate Matter in Taipei Using Landuse Regression and Bayesian Maximum Entropy Methods

Directory of Open Access Journals (Sweden)

Yi-Ming Kuo

2011-06-01

Full Text Available Fine airborne particulate matter (PM2.5 has adverse effects on human health. Assessing the long-term effects of PM2.5 exposure on human health and ecology is often limited by a lack of reliable PM2.5 measurements. In Taipei, PM2.5 levels were not systematically measured until August, 2005. Due to the popularity of geographic information systems (GIS, the landuse regression method has been widely used in the spatial estimation of PM concentrations. This method accounts for the potential contributing factors of the local environment, such as traffic volume. Geostatistical methods, on other hand, account for the spatiotemporal dependence among the observations of ambient pollutants. This study assesses the performance of the landuse regression model for the spatiotemporal estimation of PM2.5 in the Taipei area. Specifically, this study integrates the landuse regression model with the geostatistical approach within the framework of the Bayesian maximum entropy (BME method. The resulting epistemic framework can assimilate knowledge bases including: (a empirical-based spatial trends of PM concentration based on landuse regression, (b the spatio-temporal dependence among PM observation information, and (c site-specific PM observations. The proposed approach performs the spatiotemporal estimation of PM2.5 levels in the Taipei area (Taiwan from 2005–2007.

12. Estimation of fine particulate matter in Taipei using landuse regression and bayesian maximum entropy methods.

Science.gov (United States)

Yu, Hwa-Lung; Wang, Chih-Hsih; Liu, Ming-Che; Kuo, Yi-Ming

2011-06-01

Fine airborne particulate matter (PM2.5) has adverse effects on human health. Assessing the long-term effects of PM2.5 exposure on human health and ecology is often limited by a lack of reliable PM2.5 measurements. In Taipei, PM2.5 levels were not systematically measured until August, 2005. Due to the popularity of geographic information systems (GIS), the landuse regression method has been widely used in the spatial estimation of PM concentrations. This method accounts for the potential contributing factors of the local environment, such as traffic volume. Geostatistical methods, on other hand, account for the spatiotemporal dependence among the observations of ambient pollutants. This study assesses the performance of the landuse regression model for the spatiotemporal estimation of PM2.5 in the Taipei area. Specifically, this study integrates the landuse regression model with the geostatistical approach within the framework of the Bayesian maximum entropy (BME) method. The resulting epistemic framework can assimilate knowledge bases including: (a) empirical-based spatial trends of PM concentration based on landuse regression, (b) the spatio-temporal dependence among PM observation information, and (c) site-specific PM observations. The proposed approach performs the spatiotemporal estimation of PM2.5 levels in the Taipei area (Taiwan) from 2005-2007.

13. A Simple and Convenient Method of Multiple Linear Regression to Calculate Iodine Molecular Constants

Science.gov (United States)

Cooper, Paul D.

2010-01-01

A new procedure using a student-friendly least-squares multiple linear-regression technique utilizing a function within Microsoft Excel is described that enables students to calculate molecular constants from the vibronic spectrum of iodine. This method is advantageous pedagogically as it calculates molecular constants for ground and excited…

14. Estimating cavity tree and snag abundance using negative binomial regression models and nearest neighbor imputation methods

Science.gov (United States)

Bianca N.I. Eskelson; Hailemariam Temesgen; Tara M. Barrett

2009-01-01

Cavity tree and snag abundance data are highly variable and contain many zero observations. We predict cavity tree and snag abundance from variables that are readily available from forest cover maps or remotely sensed data using negative binomial (NB), zero-inflated NB, and zero-altered NB (ZANB) regression models as well as nearest neighbor (NN) imputation methods....

15. Cox regression with missing covariate data using a modified partial likelihood method

DEFF Research Database (Denmark)

Martinussen, Torben; Holst, Klaus K.; Scheike, Thomas H.

2016-01-01

Missing covariate values is a common problem in survival analysis. In this paper we propose a novel method for the Cox regression model that is close to maximum likelihood but avoids the use of the EM-algorithm. It exploits that the observed hazard function is multiplicative in the baseline hazard...

Science.gov (United States)

Cruse, Thomas A.; Chamis, Christos C. (Technical Monitor)

2001-01-01

The review effort identified research opportunities related to the use of nondeterministic, nontraditional methods to support aerospace design. The scope of the study was restricted to structural design rather than other areas such as control system design. Thus, the observations and conclusions are limited by that scope. The review identified a number of key results. The results include the potential for NASA/AF collaboration in the area of a design environment for advanced space access vehicles. The following key points set the context and delineate the key results. The Principal Investigator's (PI's) context for this study derived from participation as a Panel Member in the Air Force Scientific Advisory Board (AF/SAB) Summer Study Panel on 'Whither Hypersonics?' A key message from the Summer Study effort was a perceived need for a national program for a space access vehicle whose operating characteristics of cost, availability, deployability, and reliability most closely match the NASA 3rd Generation Reusable Launch Vehicle (RLV). The Panel urged the AF to make a significant joint commitment to such a program just as soon as the AF defined specific requirements for space access consistent with the AF Aerospace Vision 2020. The review brought home a concurrent need for a national vehicle design environment. Engineering design system technology is at a time point from which a revolution as significant as that brought about by the finite element method is possible, this one focusing on information integration on a scale that far surpasses current design environments. The study therefore fully supported the concept, if not some of the details of the Intelligent Synthesis Environment (ISE). It became abundantly clear during this study that the government (AF, NASA) and industry are not moving in the same direction in this regard, in fact each is moving in its own direction. NASA/ISE is not yet in an effective leadership position in this regard. However, NASA does

17. Convert a low-cost sensor to a colorimeter using an improved regression method

Science.gov (United States)

Wu, Yifeng

2008-01-01

Closed loop color calibration is a process to maintain consistent color reproduction for color printers. To perform closed loop color calibration, a pre-designed color target should be printed, and automatically measured by a color measuring instrument. A low cost sensor has been embedded to the printer to perform the color measurement. A series of sensor calibration and color conversion methods have been developed. The purpose is to get accurate colorimetric measurement from the data measured by the low cost sensor. In order to get high accuracy colorimetric measurement, we need carefully calibrate the sensor, and minimize all possible errors during the color conversion. After comparing several classical color conversion methods, a regression based color conversion method has been selected. The regression is a powerful method to estimate the color conversion functions. But the main difficulty to use this method is to find an appropriate function to describe the relationship between the input and the output data. In this paper, we propose to use 1D pre-linearization tables to improve the linearity between the input sensor measuring data and the output colorimetric data. Using this method, we can increase the accuracy of the regression method, so as to improve the accuracy of the color conversion.

18. Comparison of some biased estimation methods (including ordinary subset regression) in the linear model

Science.gov (United States)

Sidik, S. M.

1975-01-01

Ridge, Marquardt's generalized inverse, shrunken, and principal components estimators are discussed in terms of the objectives of point estimation of parameters, estimation of the predictive regression function, and hypothesis testing. It is found that as the normal equations approach singularity, more consideration must be given to estimable functions of the parameters as opposed to estimation of the full parameter vector; that biased estimators all introduce constraints on the parameter space; that adoption of mean squared error as a criterion of goodness should be independent of the degree of singularity; and that ordinary least-squares subset regression is the best overall method.

19. Molecular Methods for Identification of Microorganisms in Traditional Meat Products

Science.gov (United States)

Cocolin, Luca; Dolci, Paola; Rantsiou, Kalliopi

Traditional fermentations are those that have been used for centuries and even pre-date written historical records. Fermentation processes have been developed to upgrade plant and animal materials, to yield a more acceptable food, to add flavor, to prevent the growth of pathogenic and spoilage microorganisms, and to preserve food without refrigeration (Hesseltine & Wang, 1980). Among fermented foods, sausages are the meat products with a longer history and tradition. It is often assumed that sausages were invented by the Sumerians, in what is Iraq today, around 3000 BC. Chinese sausage làcháng, which consisted of goat and lamb meat, was first mentioned in 589 BC. Homer, the poet of The Ancient Greece, mentioned a kind of blood sausage in the Odyssey (book 20, verse 25), and Epicharmus (ca. 550 BC-ca. 460 BC) wrote a comedy entitled “The Sausage”.

20. A Simple Linear Regression Method for Quantitative Trait Loci Linkage Analysis With Censored Observations

OpenAIRE

Anderson, Carl A.; McRae, Allan F.; Visscher, Peter M.

2006-01-01

Standard quantitative trait loci (QTL) mapping techniques commonly assume that the trait is both fully observed and normally distributed. When considering survival or age-at-onset traits these assumptions are often incorrect. Methods have been developed to map QTL for survival traits; however, they are both computationally intensive and not available in standard genome analysis software packages. We propose a grouped linear regression method for the analysis of continuous survival data. Using...

1. A Comparative Study of Pairwise Learning Methods Based on Kernel Ridge Regression.

Science.gov (United States)

Stock, Michiel; Pahikkala, Tapio; Airola, Antti; De Baets, Bernard; Waegeman, Willem

2018-06-12

Many machine learning problems can be formulated as predicting labels for a pair of objects. Problems of that kind are often referred to as pairwise learning, dyadic prediction, or network inference problems. During the past decade, kernel methods have played a dominant role in pairwise learning. They still obtain a state-of-the-art predictive performance, but a theoretical analysis of their behavior has been underexplored in the machine learning literature. In this work we review and unify kernel-based algorithms that are commonly used in different pairwise learning settings, ranging from matrix filtering to zero-shot learning. To this end, we focus on closed-form efficient instantiations of Kronecker kernel ridge regression. We show that independent task kernel ridge regression, two-step kernel ridge regression, and a linear matrix filter arise naturally as a special case of Kronecker kernel ridge regression, implying that all these methods implicitly minimize a squared loss. In addition, we analyze universality, consistency, and spectral filtering properties. Our theoretical results provide valuable insights into assessing the advantages and limitations of existing pairwise learning methods.

2. Estimation Methods for Non-Homogeneous Regression - Minimum CRPS vs Maximum Likelihood

Science.gov (United States)

Gebetsberger, Manuel; Messner, Jakob W.; Mayr, Georg J.; Zeileis, Achim

2017-04-01

Non-homogeneous regression models are widely used to statistically post-process numerical weather prediction models. Such regression models correct for errors in mean and variance and are capable to forecast a full probability distribution. In order to estimate the corresponding regression coefficients, CRPS minimization is performed in many meteorological post-processing studies since the last decade. In contrast to maximum likelihood estimation, CRPS minimization is claimed to yield more calibrated forecasts. Theoretically, both scoring rules used as an optimization score should be able to locate a similar and unknown optimum. Discrepancies might result from a wrong distributional assumption of the observed quantity. To address this theoretical concept, this study compares maximum likelihood and minimum CRPS estimation for different distributional assumptions. First, a synthetic case study shows that, for an appropriate distributional assumption, both estimation methods yield to similar regression coefficients. The log-likelihood estimator is slightly more efficient. A real world case study for surface temperature forecasts at different sites in Europe confirms these results but shows that surface temperature does not always follow the classical assumption of a Gaussian distribution. KEYWORDS: ensemble post-processing, maximum likelihood estimation, CRPS minimization, probabilistic temperature forecasting, distributional regression models

3. A Fast Gradient Method for Nonnegative Sparse Regression With Self-Dictionary

Science.gov (United States)

Gillis, Nicolas; Luce, Robert

2018-01-01

A nonnegative matrix factorization (NMF) can be computed efficiently under the separability assumption, which asserts that all the columns of the given input data matrix belong to the cone generated by a (small) subset of them. The provably most robust methods to identify these conic basis columns are based on nonnegative sparse regression and self dictionaries, and require the solution of large-scale convex optimization problems. In this paper we study a particular nonnegative sparse regression model with self dictionary. As opposed to previously proposed models, this model yields a smooth optimization problem where the sparsity is enforced through linear constraints. We show that the Euclidean projection on the polyhedron defined by these constraints can be computed efficiently, and propose a fast gradient method to solve our model. We compare our algorithm with several state-of-the-art methods on synthetic data sets and real-world hyperspectral images.

4. Support vector methods for survival analysis: a comparison between ranking and regression approaches.

Science.gov (United States)

Van Belle, Vanya; Pelckmans, Kristiaan; Van Huffel, Sabine; Suykens, Johan A K

2011-10-01

To compare and evaluate ranking, regression and combined machine learning approaches for the analysis of survival data. The literature describes two approaches based on support vector machines to deal with censored observations. In the first approach the key idea is to rephrase the task as a ranking problem via the concordance index, a problem which can be solved efficiently in a context of structural risk minimization and convex optimization techniques. In a second approach, one uses a regression approach, dealing with censoring by means of inequality constraints. The goal of this paper is then twofold: (i) introducing a new model combining the ranking and regression strategy, which retains the link with existing survival models such as the proportional hazards model via transformation models; and (ii) comparison of the three techniques on 6 clinical and 3 high-dimensional datasets and discussing the relevance of these techniques over classical approaches fur survival data. We compare svm-based survival models based on ranking constraints, based on regression constraints and models based on both ranking and regression constraints. The performance of the models is compared by means of three different measures: (i) the concordance index, measuring the model's discriminating ability; (ii) the logrank test statistic, indicating whether patients with a prognostic index lower than the median prognostic index have a significant different survival than patients with a prognostic index higher than the median; and (iii) the hazard ratio after normalization to restrict the prognostic index between 0 and 1. Our results indicate a significantly better performance for models including regression constraints above models only based on ranking constraints. This work gives empirical evidence that svm-based models using regression constraints perform significantly better than svm-based models based on ranking constraints. Our experiments show a comparable performance for methods

5. Alpins and thibos vectorial astigmatism analyses: proposal of a linear regression model between methods

Directory of Open Access Journals (Sweden)

Giuliano de Oliveira Freitas

2013-10-01

Full Text Available PURPOSE: To determine linear regression models between Alpins descriptive indices and Thibos astigmatic power vectors (APV, assessing the validity and strength of such correlations. METHODS: This case series prospectively assessed 62 eyes of 31 consecutive cataract patients with preoperative corneal astigmatism between 0.75 and 2.50 diopters in both eyes. Patients were randomly assorted among two phacoemulsification groups: one assigned to receive AcrySof®Toric intraocular lens (IOL in both eyes and another assigned to have AcrySof Natural IOL associated with limbal relaxing incisions, also in both eyes. All patients were reevaluated postoperatively at 6 months, when refractive astigmatism analysis was performed using both Alpins and Thibos methods. The ratio between Thibos postoperative APV and preoperative APV (APVratio and its linear regression to Alpins percentage of success of astigmatic surgery, percentage of astigmatism corrected and percentage of astigmatism reduction at the intended axis were assessed. RESULTS: Significant negative correlation between the ratio of post- and preoperative Thibos APVratio and Alpins percentage of success (%Success was found (Spearman's ρ=-0.93; linear regression is given by the following equation: %Success = (-APVratio + 1.00x100. CONCLUSION: The linear regression we found between APVratio and %Success permits a validated mathematical inference concerning the overall success of astigmatic surgery.

6. Using the fuzzy linear regression method to benchmark the energy efficiency of commercial buildings

International Nuclear Information System (INIS)

Chung, William

2012-01-01

Highlights: ► Fuzzy linear regression method is used for developing benchmarking systems. ► The systems can be used to benchmark energy efficiency of commercial buildings. ► The resulting benchmarking model can be used by public users. ► The resulting benchmarking model can capture the fuzzy nature of input–output data. -- Abstract: Benchmarking systems from a sample of reference buildings need to be developed to conduct benchmarking processes for the energy efficiency of commercial buildings. However, not all benchmarking systems can be adopted by public users (i.e., other non-reference building owners) because of the different methods in developing such systems. An approach for benchmarking the energy efficiency of commercial buildings using statistical regression analysis to normalize other factors, such as management performance, was developed in a previous work. However, the field data given by experts can be regarded as a distribution of possibility. Thus, the previous work may not be adequate to handle such fuzzy input–output data. Consequently, a number of fuzzy structures cannot be fully captured by statistical regression analysis. This present paper proposes the use of fuzzy linear regression analysis to develop a benchmarking process, the resulting model of which can be used by public users. An illustrative example is given as well.

7. Study (Prediction of Main Pipes Break Rates in Water Distribution Systems Using Intelligent and Regression Methods

Directory of Open Access Journals (Sweden)

Massoud Tabesh

2011-07-01

Full Text Available Optimum operation of water distribution networks is one of the priorities of sustainable development of water resources, considering the issues of increasing efficiency and decreasing the water losses. One of the key subjects in optimum operational management of water distribution systems is preparing rehabilitation and replacement schemes, prediction of pipes break rate and evaluation of their reliability. Several approaches have been presented in recent years regarding prediction of pipe failure rates which each one requires especial data sets. Deterministic models based on age and deterministic multi variables and stochastic group modeling are examples of the solutions which relate pipe break rates to parameters like age, material and diameters. In this paper besides the mentioned parameters, more factors such as pipe depth and hydraulic pressures are considered as well. Then using multi variable regression method, intelligent approaches (Artificial neural network and neuro fuzzy models and Evolutionary polynomial Regression method (EPR pipe burst rate are predicted. To evaluate the results of different approaches, a case study is carried out in a part ofMashhadwater distribution network. The results show the capability and advantages of ANN and EPR methods to predict pipe break rates, in comparison with neuro fuzzy and multi-variable regression methods.

8. Development of Compressive Failure Strength for Composite Laminate Using Regression Analysis Method

Energy Technology Data Exchange (ETDEWEB)

Lee, Myoung Keon [Agency for Defense Development, Daejeon (Korea, Republic of); Lee, Jeong Won; Yoon, Dong Hyun; Kim, Jae Hoon [Chungnam Nat’l Univ., Daejeon (Korea, Republic of)

2016-10-15

This paper provides the compressive failure strength value of composite laminate developed by using regression analysis method. Composite material in this document is a Carbon/Epoxy unidirection(UD) tape prepreg(Cycom G40-800/5276-1) cured at 350°F(177°C). The operating temperature is –60°F~+200°F(-55°C - +95°C). A total of 56 compression tests were conducted on specimens from eight (8) distinct laminates that were laid up by standard angle layers (0°, +45°, –45° and 90°). The ASTM-D-6484 standard was used for test method. The regression analysis was performed with the response variable being the laminate ultimate fracture strength and the regressor variables being two ply orientations (0° and ±45°)

9. Development of Compressive Failure Strength for Composite Laminate Using Regression Analysis Method

International Nuclear Information System (INIS)

Lee, Myoung Keon; Lee, Jeong Won; Yoon, Dong Hyun; Kim, Jae Hoon

2016-01-01

This paper provides the compressive failure strength value of composite laminate developed by using regression analysis method. Composite material in this document is a Carbon/Epoxy unidirection(UD) tape prepreg(Cycom G40-800/5276-1) cured at 350°F(177°C). The operating temperature is –60°F~+200°F(-55°C - +95°C). A total of 56 compression tests were conducted on specimens from eight (8) distinct laminates that were laid up by standard angle layers (0°, +45°, –45° and 90°). The ASTM-D-6484 standard was used for test method. The regression analysis was performed with the response variable being the laminate ultimate fracture strength and the regressor variables being two ply orientations (0° and ±45°)

10. Conciliation as the traditional method of disputes settlement in PRC

Directory of Open Access Journals (Sweden)

Svetlana F. Litvinova

2011-12-01

Full Text Available The author of the article researches one of the peculiarities of civil disputes settlement in China. This peculiarity is the conciliatory method that is used during disputes settlement. The using of the method is based on Confucianism. The content of the method has been viewed in the article.

11. The regression-calibration method for fitting generalized linear models with additive measurement error

OpenAIRE

James W. Hardin; Henrik Schmeidiche; Raymond J. Carroll

2003-01-01

This paper discusses and illustrates the method of regression calibration. This is a straightforward technique for fitting models with additive measurement error. We present this discussion in terms of generalized linear models (GLMs) following the notation defined in Hardin and Carroll (2003). Discussion will include specified measurement error, measurement error estimated by replicate error-prone proxies, and measurement error estimated by instrumental variables. The discussion focuses on s...

12. Assessing the performance of variational methods for mixed logistic regression models

Czech Academy of Sciences Publication Activity Database

Rijmen, F.; Vomlel, Jiří

2008-01-01

Roč. 78, č. 8 (2008), s. 765-779 ISSN 0094-9655 R&D Projects: GA MŠk 1M0572 Grant - others:GA MŠk(CZ) 2C06019 Institutional research plan: CEZ:AV0Z10750506 Keywords : Mixed models * Logistic regression * Variational methods * Lower bound approximation Subject RIV: BB - Applied Statistics, Operational Research Impact factor: 0.353, year: 2008

13. Comparison of Adaline and Multiple Linear Regression Methods for Rainfall Forecasting

Science.gov (United States)

Sutawinaya, IP; Astawa, INGA; Hariyanti, NKD

2018-01-01

Heavy rainfall can cause disaster, therefore need a forecast to predict rainfall intensity. Main factor that cause flooding is there is a high rainfall intensity and it makes the river become overcapacity. This will cause flooding around the area. Rainfall factor is a dynamic factor, so rainfall is very interesting to be studied. In order to support the rainfall forecasting, there are methods that can be used from Artificial Intelligence (AI) to statistic. In this research, we used Adaline for AI method and Regression for statistic method. The more accurate forecast result shows the method that used is good for forecasting the rainfall. Through those methods, we expected which is the best method for rainfall forecasting here.

14. Statistical methods and regression analysis of stratospheric ozone and meteorological variables in Isfahan

Science.gov (United States)

Hassanzadeh, S.; Hosseinibalam, F.; Omidvari, M.

2008-04-01

Data of seven meteorological variables (relative humidity, wet temperature, dry temperature, maximum temperature, minimum temperature, ground temperature and sun radiation time) and ozone values have been used for statistical analysis. Meteorological variables and ozone values were analyzed using both multiple linear regression and principal component methods. Data for the period 1999-2004 are analyzed jointly using both methods. For all periods, temperature dependent variables were highly correlated, but were all negatively correlated with relative humidity. Multiple regression analysis was used to fit the meteorological variables using the meteorological variables as predictors. A variable selection method based on high loading of varimax rotated principal components was used to obtain subsets of the predictor variables to be included in the linear regression model of the meteorological variables. In 1999, 2001 and 2002 one of the meteorological variables was weakly influenced predominantly by the ozone concentrations. However, the model did not predict that the meteorological variables for the year 2000 were not influenced predominantly by the ozone concentrations that point to variation in sun radiation. This could be due to other factors that were not explicitly considered in this study.

15. Improvement in the traditional processing method and nutritional quality of traditional extruded cassava-based snack (modified Ajogun).

Science.gov (United States)

2013-07-01

This study was carried out to investigate and improve the traditional processing method and nutritional quality of the traditional cassava snack (Ajogun). Cassava root (Manihot esculenta Crantz L.) of TME 419 variety was processed into mash (40% moisture content). The cassava mash was mixed into different blends to produce fried traditional "Ajogun", fried and baked extrudates (modified Ajogun) as snacks. These products were analyzed to determine the proximate composition including carbohydrate, fat, protein, fiber, ash, and moisture contents and functional properties such as bulk density. The results obtained for the moisture, fat, protein, and ash contents showed significant difference (P extrudates. However, there was no significant difference (P > 0.05) in the carbohydrate and fiber contents between the three samples. There was no significant difference (P > 0.05) in the bulk density of the snacks. Also, sensory evaluation was carried out on the cassava-based snacks using the 9-point hedonic scale to determine the degree of acceptability. Results obtained showed significant difference (P extrudates and control sample in terms of appearance, taste, flavor, color, aroma, texture, and overall acceptability. The highest acceptability level of the product was at 8.04 for the control sample (traditional Ajogun). This study has shown that "Ajogun", which is a lesser known cassava product, is rich in protein and fat.

16. Correcting for cryptic relatedness by a regression-based genomic control method

Directory of Open Access Journals (Sweden)

Yang Yaning

2009-12-01

Full Text Available Abstract Background Genomic control (GC method is a useful tool to correct for the cryptic relatedness in population-based association studies. It was originally proposed for correcting for the variance inflation of Cochran-Armitage's additive trend test by using information from unlinked null markers, and was later generalized to be applicable to other tests with the additional requirement that the null markers are matched with the candidate marker in allele frequencies. However, matching allele frequencies limits the number of available null markers and thus limits the applicability of the GC method. On the other hand, errors in genotype/allele frequencies may cause further bias and variance inflation and thereby aggravate the effect of GC correction. Results In this paper, we propose a regression-based GC method using null markers that are not necessarily matched in allele frequencies with the candidate marker. Variation of allele frequencies of the null markers is adjusted by a regression method. Conclusion The proposed method can be readily applied to the Cochran-Armitage's trend tests other than the additive trend test, the Pearson's chi-square test and other robust efficiency tests. Simulation results show that the proposed method is effective in controlling type I error in the presence of population substructure.

17. A subagging regression method for estimating the qualitative and quantitative state of groundwater

Science.gov (United States)

Jeong, Jina; Park, Eungyu; Han, Weon Shik; Kim, Kue-Young

2017-08-01

A subsample aggregating (subagging) regression (SBR) method for the analysis of groundwater data pertaining to trend-estimation-associated uncertainty is proposed. The SBR method is validated against synthetic data competitively with other conventional robust and non-robust methods. From the results, it is verified that the estimation accuracies of the SBR method are consistent and superior to those of other methods, and the uncertainties are reasonably estimated; the others have no uncertainty analysis option. To validate further, actual groundwater data are employed and analyzed comparatively with Gaussian process regression (GPR). For all cases, the trend and the associated uncertainties are reasonably estimated by both SBR and GPR regardless of Gaussian or non-Gaussian skewed data. However, it is expected that GPR has a limitation in applications to severely corrupted data by outliers owing to its non-robustness. From the implementations, it is determined that the SBR method has the potential to be further developed as an effective tool of anomaly detection or outlier identification in groundwater state data such as the groundwater level and contaminant concentration.

18. Effect of Traditional smoking Method on Nutritive Values and ...

African Journals Online (AJOL)

SH

smoking method is an important preservation method which could enhance the nutritive values of fishes and possibly reduce post-harvest losses. Keywords: ... Fishery Laboratory of College of. Agricultural Sciences, Olabisi Onabanjo .... colour helps to determine quality, degree of processing or spoilage level (Clifford et al.,.

19. Understanding poisson regression.

Science.gov (United States)

Hayat, Matthew J; Higgins, Melinda

2014-04-01

Nurse investigators often collect study data in the form of counts. Traditional methods of data analysis have historically approached analysis of count data either as if the count data were continuous and normally distributed or with dichotomization of the counts into the categories of occurred or did not occur. These outdated methods for analyzing count data have been replaced with more appropriate statistical methods that make use of the Poisson probability distribution, which is useful for analyzing count data. The purpose of this article is to provide an overview of the Poisson distribution and its use in Poisson regression. Assumption violations for the standard Poisson regression model are addressed with alternative approaches, including addition of an overdispersion parameter or negative binomial regression. An illustrative example is presented with an application from the ENSPIRE study, and regression modeling of comorbidity data is included for illustrative purposes. Copyright 2014, SLACK Incorporated.

20. Impact of regression methods on improved effects of soil structure on soil water retention estimates

Science.gov (United States)

Nguyen, Phuong Minh; De Pue, Jan; Le, Khoa Van; Cornelis, Wim

2015-06-01

Increasing the accuracy of pedotransfer functions (PTFs), an indirect method for predicting non-readily available soil features such as soil water retention characteristics (SWRC), is of crucial importance for large scale agro-hydrological modeling. Adding significant predictors (i.e., soil structure), and implementing more flexible regression algorithms are among the main strategies of PTFs improvement. The aim of this study was to investigate whether the improved effect of categorical soil structure information on estimating soil-water content at various matric potentials, which has been reported in literature, could be enduringly captured by regression techniques other than the usually applied linear regression. Two data mining techniques, i.e., Support Vector Machines (SVM), and k-Nearest Neighbors (kNN), which have been recently introduced as promising tools for PTF development, were utilized to test if the incorporation of soil structure will improve PTF's accuracy under a context of rather limited training data. The results show that incorporating descriptive soil structure information, i.e., massive, structured and structureless, as grouping criterion can improve the accuracy of PTFs derived by SVM approach in the range of matric potential of -6 to -33 kPa (average RMSE decreased up to 0.005 m3 m-3 after grouping, depending on matric potentials). The improvement was primarily attributed to the outperformance of SVM-PTFs calibrated on structureless soils. No improvement was obtained with kNN technique, at least not in our study in which the data set became limited in size after grouping. Since there is an impact of regression techniques on the improved effect of incorporating qualitative soil structure information, selecting a proper technique will help to maximize the combined influence of flexible regression algorithms and soil structure information on PTF accuracy.

1. A method for fitting regression splines with varying polynomial order in the linear mixed model.

Science.gov (United States)

Edwards, Lloyd J; Stewart, Paul W; MacDougall, James E; Helms, Ronald W

2006-02-15

The linear mixed model has become a widely used tool for longitudinal analysis of continuous variables. The use of regression splines in these models offers the analyst additional flexibility in the formulation of descriptive analyses, exploratory analyses and hypothesis-driven confirmatory analyses. We propose a method for fitting piecewise polynomial regression splines with varying polynomial order in the fixed effects and/or random effects of the linear mixed model. The polynomial segments are explicitly constrained by side conditions for continuity and some smoothness at the points where they join. By using a reparameterization of this explicitly constrained linear mixed model, an implicitly constrained linear mixed model is constructed that simplifies implementation of fixed-knot regression splines. The proposed approach is relatively simple, handles splines in one variable or multiple variables, and can be easily programmed using existing commercial software such as SAS or S-plus. The method is illustrated using two examples: an analysis of longitudinal viral load data from a study of subjects with acute HIV-1 infection and an analysis of 24-hour ambulatory blood pressure profiles.

2. Hybrid ARIMAX quantile regression method for forecasting short term electricity consumption in east java

Science.gov (United States)

Prastuti, M.; Suhartono; Salehah, NA

2018-04-01

The need for energy supply, especially for electricity in Indonesia has been increasing in the last past years. Furthermore, the high electricity usage by people at different times leads to the occurrence of heteroscedasticity issue. Estimate the electricity supply that could fulfilled the community’s need is very important, but the heteroscedasticity issue often made electricity forecasting hard to be done. An accurate forecast of electricity consumptions is one of the key challenges for energy provider to make better resources and service planning and also take control actions in order to balance the electricity supply and demand for community. In this paper, hybrid ARIMAX Quantile Regression (ARIMAX-QR) approach was proposed to predict the short-term electricity consumption in East Java. This method will also be compared to time series regression using RMSE, MAPE, and MdAPE criteria. The data used in this research was the electricity consumption per half-an-hour data during the period of September 2015 to April 2016. The results show that the proposed approach can be a competitive alternative to forecast short-term electricity in East Java. ARIMAX-QR using lag values and dummy variables as predictors yield more accurate prediction in both in-sample and out-sample data. Moreover, both time series regression and ARIMAX-QR methods with addition of lag values as predictor could capture accurately the patterns in the data. Hence, it produces better predictions compared to the models that not use additional lag variables.

3. A robust and efficient stepwise regression method for building sparse polynomial chaos expansions

Energy Technology Data Exchange (ETDEWEB)

Abraham, Simon, E-mail: Simon.Abraham@ulb.ac.be [Vrije Universiteit Brussel (VUB), Department of Mechanical Engineering, Research Group Fluid Mechanics and Thermodynamics, Pleinlaan 2, 1050 Brussels (Belgium); Raisee, Mehrdad [School of Mechanical Engineering, College of Engineering, University of Tehran, P.O. Box: 11155-4563, Tehran (Iran, Islamic Republic of); Ghorbaniasl, Ghader; Contino, Francesco; Lacor, Chris [Vrije Universiteit Brussel (VUB), Department of Mechanical Engineering, Research Group Fluid Mechanics and Thermodynamics, Pleinlaan 2, 1050 Brussels (Belgium)

2017-03-01

Polynomial Chaos (PC) expansions are widely used in various engineering fields for quantifying uncertainties arising from uncertain parameters. The computational cost of classical PC solution schemes is unaffordable as the number of deterministic simulations to be calculated grows dramatically with the number of stochastic dimension. This considerably restricts the practical use of PC at the industrial level. A common approach to address such problems is to make use of sparse PC expansions. This paper presents a non-intrusive regression-based method for building sparse PC expansions. The most important PC contributions are detected sequentially through an automatic search procedure. The variable selection criterion is based on efficient tools relevant to probabilistic method. Two benchmark analytical functions are used to validate the proposed algorithm. The computational efficiency of the method is then illustrated by a more realistic CFD application, consisting of the non-deterministic flow around a transonic airfoil subject to geometrical uncertainties. To assess the performance of the developed methodology, a detailed comparison is made with the well established LAR-based selection technique. The results show that the developed sparse regression technique is able to identify the most significant PC contributions describing the problem. Moreover, the most important stochastic features are captured at a reduced computational cost compared to the LAR method. The results also demonstrate the superior robustness of the method by repeating the analyses using random experimental designs.

4. Logistic Regression with Multiple Random Effects: A Simulation Study of Estimation Methods and Statistical Packages.

Science.gov (United States)

Kim, Yoonsang; Choi, Young-Ku; Emery, Sherry

2013-08-01

Several statistical packages are capable of estimating generalized linear mixed models and these packages provide one or more of three estimation methods: penalized quasi-likelihood, Laplace, and Gauss-Hermite. Many studies have investigated these methods' performance for the mixed-effects logistic regression model. However, the authors focused on models with one or two random effects and assumed a simple covariance structure between them, which may not be realistic. When there are multiple correlated random effects in a model, the computation becomes intensive, and often an algorithm fails to converge. Moreover, in our analysis of smoking status and exposure to anti-tobacco advertisements, we have observed that when a model included multiple random effects, parameter estimates varied considerably from one statistical package to another even when using the same estimation method. This article presents a comprehensive review of the advantages and disadvantages of each estimation method. In addition, we compare the performances of the three methods across statistical packages via simulation, which involves two- and three-level logistic regression models with at least three correlated random effects. We apply our findings to a real dataset. Our results suggest that two packages-SAS GLIMMIX Laplace and SuperMix Gaussian quadrature-perform well in terms of accuracy, precision, convergence rates, and computing speed. We also discuss the strengths and weaknesses of the two packages in regard to sample sizes.

5. Logistic Regression with Multiple Random Effects: A Simulation Study of Estimation Methods and Statistical Packages

Science.gov (United States)

Kim, Yoonsang; Emery, Sherry

2013-01-01

Several statistical packages are capable of estimating generalized linear mixed models and these packages provide one or more of three estimation methods: penalized quasi-likelihood, Laplace, and Gauss-Hermite. Many studies have investigated these methods’ performance for the mixed-effects logistic regression model. However, the authors focused on models with one or two random effects and assumed a simple covariance structure between them, which may not be realistic. When there are multiple correlated random effects in a model, the computation becomes intensive, and often an algorithm fails to converge. Moreover, in our analysis of smoking status and exposure to anti-tobacco advertisements, we have observed that when a model included multiple random effects, parameter estimates varied considerably from one statistical package to another even when using the same estimation method. This article presents a comprehensive review of the advantages and disadvantages of each estimation method. In addition, we compare the performances of the three methods across statistical packages via simulation, which involves two- and three-level logistic regression models with at least three correlated random effects. We apply our findings to a real dataset. Our results suggest that two packages—SAS GLIMMIX Laplace and SuperMix Gaussian quadrature—perform well in terms of accuracy, precision, convergence rates, and computing speed. We also discuss the strengths and weaknesses of the two packages in regard to sample sizes. PMID:24288415

6. A novel relational regularization feature selection method for joint regression and classification in AD diagnosis.

Science.gov (United States)

Zhu, Xiaofeng; Suk, Heung-Il; Wang, Li; Lee, Seong-Whan; Shen, Dinggang

2017-05-01

In this paper, we focus on joint regression and classification for Alzheimer's disease diagnosis and propose a new feature selection method by embedding the relational information inherent in the observations into a sparse multi-task learning framework. Specifically, the relational information includes three kinds of relationships (such as feature-feature relation, response-response relation, and sample-sample relation), for preserving three kinds of the similarity, such as for the features, the response variables, and the samples, respectively. To conduct feature selection, we first formulate the objective function by imposing these three relational characteristics along with an ℓ 2,1 -norm regularization term, and further propose a computationally efficient algorithm to optimize the proposed objective function. With the dimension-reduced data, we train two support vector regression models to predict the clinical scores of ADAS-Cog and MMSE, respectively, and also a support vector classification model to determine the clinical label. We conducted extensive experiments on the Alzheimer's Disease Neuroimaging Initiative (ADNI) dataset to validate the effectiveness of the proposed method. Our experimental results showed the efficacy of the proposed method in enhancing the performances of both clinical scores prediction and disease status identification, compared to the state-of-the-art methods. Copyright © 2015 Elsevier B.V. All rights reserved.

7. Traditional Methods Used in Family Planning and Conception in ...

African Journals Online (AJOL)

... knowledge and incorporate it into the national health care delivery service. Researchers should document the available indigenous knowledge before they are forgotten while ascertaining the validity of some of the methods. Keywords: Maternal health, family planning, pregnancy management, homebased health care.

8. Effects of different traditional cooking methods on nutrients and ...

African Journals Online (AJOL)

The objective of this research was to determine the effect of cooking using two different methods of preparing okra soup in Ondo state on nutrient, mineral content including zinc bioavailability of okra, Abelmoschus esculentus. The okra fruits were grated and divided into four lots; two lots were cooked with other ingredients of ...

9. Innovative Teaching Practice: Traditional and Alternative Methods (Challenges and Implications)

Science.gov (United States)

Nurutdinova, Aida R.; Perchatkina, Veronika G.; Zinatullina, Liliya M.; Zubkova, Guzel I.; Galeeva, Farida T.

2016-01-01

The relevance of the present issue is caused be the strong need in alternative methods of learning foreign language and the need in language training and retraining for the modern professionals. The aim of the article is to identify the basic techniques and skills in using various modern techniques in the context of modern educational tasks. The…

10. [Essential procedure and key methods for survey of traditional knowledge related to Chinese materia medica resources].

Science.gov (United States)

Cheng, Gong; Huang, Lu-qi; Xue, Da-yuan; Zhang, Xiao-bo

2014-12-01

11. Estimating Penetration Resistance in Agricultural Soils of Ardabil Plain Using Artificial Neural Network and Regression Methods

Directory of Open Access Journals (Sweden)

2017-02-01

Full Text Available Introduction: Penetration resistance is one of the criteria for evaluating soil compaction. It correlates with several soil properties such as vehicle trafficability, resistance to root penetration, seedling emergence, and soil compaction by farm machinery. Direct measurement of penetration resistance is time consuming and difficult because of high temporal and spatial variability. Therefore, many different regressions and artificial neural network pedotransfer functions have been proposed to estimate penetration resistance from readily available soil variables such as particle size distribution, bulk density (Db and gravimetric water content (θm. The lands of Ardabil Province are one of the main production regions of potato in Iran, thus, obtaining the soil penetration resistance in these regions help with the management of potato production. The objective of this research was to derive pedotransfer functions by using regression and artificial neural network to predict penetration resistance from some soil variations in the agricultural soils of Ardabil plain and to compare the performance of artificial neural network with regression models. Materials and methods: Disturbed and undisturbed soil samples (n= 105 were systematically taken from 0-10 cm soil depth with nearly 3000 m distance in the agricultural lands of the Ardabil plain ((lat 38°15' to 38°40' N, long 48°16' to 48°61' E. The contents of sand, silt and clay (hydrometer method, CaCO3 (titration method, bulk density (cylinder method, particle density (Dp (pychnometer method, organic carbon (wet oxidation method, total porosity(calculating from Db and Dp, saturated (θs and field soil water (θf using the gravimetric method were measured in the laboratory. Mean geometric diameter (dg and standard deviation (σg of soil particles were computed using the percentages of sand, silt and clay. Penetration resistance was measured in situ using cone penetrometer (analog model at 10

12. Landslide susceptibility mapping on a global scale using the method of logistic regression

Directory of Open Access Journals (Sweden)

L. Lin

2017-08-01

Full Text Available This paper proposes a statistical model for mapping global landslide susceptibility based on logistic regression. After investigating explanatory factors for landslides in the existing literature, five factors were selected for model landslide susceptibility: relative relief, extreme precipitation, lithology, ground motion and soil moisture. When building the model, 70 % of landslide and nonlandslide points were randomly selected for logistic regression, and the others were used for model validation. To evaluate the accuracy of predictive models, this paper adopts several criteria including a receiver operating characteristic (ROC curve method. Logistic regression experiments found all five factors to be significant in explaining landslide occurrence on a global scale. During the modeling process, percentage correct in confusion matrix of landslide classification was approximately 80 % and the area under the curve (AUC was nearly 0.87. During the validation process, the above statistics were about 81 % and 0.88, respectively. Such a result indicates that the model has strong robustness and stable performance. This model found that at a global scale, soil moisture can be dominant in the occurrence of landslides and topographic factor may be secondary.

13. A consensus successive projections algorithm--multiple linear regression method for analyzing near infrared spectra.

Science.gov (United States)

Liu, Ke; Chen, Xiaojing; Li, Limin; Chen, Huiling; Ruan, Xiukai; Liu, Wenbin

2015-02-09

The successive projections algorithm (SPA) is widely used to select variables for multiple linear regression (MLR) modeling. However, SPA used only once may not obtain all the useful information of the full spectra, because the number of selected variables cannot exceed the number of calibration samples in the SPA algorithm. Therefore, the SPA-MLR method risks the loss of useful information. To make a full use of the useful information in the spectra, a new method named "consensus SPA-MLR" (C-SPA-MLR) is proposed herein. This method is the combination of consensus strategy and SPA-MLR method. In the C-SPA-MLR method, SPA-MLR is used to construct member models with different subsets of variables, which are selected from the remaining variables iteratively. A consensus prediction is obtained by combining the predictions of the member models. The proposed method is evaluated by analyzing the near infrared (NIR) spectra of corn and diesel. The results of C-SPA-MLR method showed a better prediction performance compared with the SPA-MLR and full-spectra PLS methods. Moreover, these results could serve as a reference for combination the consensus strategy and other variable selection methods when analyzing NIR spectra and other spectroscopic techniques. Copyright © 2014 Elsevier B.V. All rights reserved.

14. Development of K-Nearest Neighbour Regression Method in Forecasting River Stream Flow

Directory of Open Access Journals (Sweden)

2012-07-01

Full Text Available Different statistical, non-statistical and black-box methods have been used in forecasting processes. Among statistical methods, K-nearest neighbour non-parametric regression method (K-NN due to its natural simplicity and mathematical base is one of the recommended methods for forecasting processes. In this study, K-NN method is explained completely. Besides, development and improvement approaches such as best neighbour estimation, data transformation functions, distance functions and proposed extrapolation method are described. K-NN method in company with its development approaches is used in streamflow forecasting of Zayandeh-Rud Dam upper basin. Comparing between final results of classic K-NN method and modified K-NN (number of neighbour 5, transformation function of Range Scaling, distance function of Mahanalobis and proposed extrapolation method shows that modified K-NN in criteria of goodness of fit, root mean square error, percentage of volume of error and correlation has had performance improvement 45% , 59% and 17% respectively. These results approve necessity of applying mentioned approaches to derive more accurate forecasts.

15. Blasting vibrations control: The shortcomings of traditional methods

Energy Technology Data Exchange (ETDEWEB)

Vuillaume, P.M.; Kiszlo, M. [Institut National de l`Environnement Industriel et des Risques, Verneuil en Halatte (France); Bernard, T. [Compagnie Nouvelle de Scientifiques, Nice (France)

1996-12-31

In the context of its studies for the French ministry of the environment and for the French national coal board, INERIS (the French institute for the industrial environment and hazards, formerly CERCHAR) has made a complete critical survey of the methods generally used to reduce the levels of blasting vibrations. It is generally acknowledged that the main parameter to control vibrations is the so-called instantaneous charge, or charge per delay. This should be reduced as much as possible in order to diminish vibration levels. On account of this, the use of a new generation of blasting devices, such as non-electric detonators or electronic sequential timers has been developed since the seventies. INERIS has collected data from about 900 blasts in 2 quarries and 3 open pit mines. These data include input parameters such as borehole diameter, burden, spacing, charge per hole, charge per delay, total fired charge, etc ... They also include output measurements, such as vibration peak particle velocities, and main frequencies. These data have been analyzed with the help of multi variable statistical tools. Blasting tests were undertaken to evaluate new methods of vibrations control, such as the superposition of vibration signals. These methods appear to be accurate in many critical cases, but certainly would be highly improved with a better accuracy of firing delays. The development of electronic detonators seems to be the way of the future for a better blasting control.

16. Exploring Non-Traditional Learning Methods in Virtual and Real-World Environments

Science.gov (United States)

Lukman, Rebeka; Krajnc, Majda

2012-01-01

This paper identifies the commonalities and differences within non-traditional learning methods regarding virtual and real-world environments. The non-traditional learning methods in real-world have been introduced within the following courses: Process Balances, Process Calculation, and Process Synthesis, and within the virtual environment through…

17. Comparing the index-flood and multiple-regression methods using L-moments

Science.gov (United States)

Malekinezhad, H.; Nachtnebel, H. P.; Klik, A.

In arid and semi-arid regions, the length of records is usually too short to ensure reliable quantile estimates. Comparing index-flood and multiple-regression analyses based on L-moments was the main objective of this study. Factor analysis was applied to determine main influencing variables on flood magnitude. Ward’s cluster and L-moments approaches were applied to several sites in the Namak-Lake basin in central Iran to delineate homogeneous regions based on site characteristics. Homogeneity test was done using L-moments-based measures. Several distributions were fitted to the regional flood data and index-flood and multiple-regression methods as two regional flood frequency methods were compared. The results of factor analysis showed that length of main waterway, compactness coefficient, mean annual precipitation, and mean annual temperature were the main variables affecting flood magnitude. The study area was divided into three regions based on the Ward’s method of clustering approach. The homogeneity test based on L-moments showed that all three regions were acceptably homogeneous. Five distributions were fitted to the annual peak flood data of three homogeneous regions. Using the L-moment ratios and the Z-statistic criteria, GEV distribution was identified as the most robust distribution among five candidate distributions for all the proposed sub-regions of the study area, and in general, it was concluded that the generalised extreme value distribution was the best-fit distribution for every three regions. The relative root mean square error (RRMSE) measure was applied for evaluating the performance of the index-flood and multiple-regression methods in comparison with the curve fitting (plotting position) method. In general, index-flood method gives more reliable estimations for various flood magnitudes of different recurrence intervals. Therefore, this method should be adopted as regional flood frequency method for the study area and the Namak-Lake basin

18. Short term load forecasting technique based on the seasonal exponential adjustment method and the regression model

International Nuclear Information System (INIS)

Wu, Jie; Wang, Jianzhou; Lu, Haiyan; Dong, Yao; Lu, Xiaoxiao

2013-01-01

Highlights: ► The seasonal and trend items of the data series are forecasted separately. ► Seasonal item in the data series is verified by the Kendall τ correlation testing. ► Different regression models are applied to the trend item forecasting. ► We examine the superiority of the combined models by the quartile value comparison. ► Paired-sample T test is utilized to confirm the superiority of the combined models. - Abstract: For an energy-limited economy system, it is crucial to forecast load demand accurately. This paper devotes to 1-week-ahead daily load forecasting approach in which load demand series are predicted by employing the information of days before being similar to that of the forecast day. As well as in many nonlinear systems, seasonal item and trend item are coexisting in load demand datasets. In this paper, the existing of the seasonal item in the load demand data series is firstly verified according to the Kendall τ correlation testing method. Then in the belief of the separate forecasting to the seasonal item and the trend item would improve the forecasting accuracy, hybrid models by combining seasonal exponential adjustment method (SEAM) with the regression methods are proposed in this paper, where SEAM and the regression models are employed to seasonal and trend items forecasting respectively. Comparisons of the quartile values as well as the mean absolute percentage error values demonstrate this forecasting technique can significantly improve the accuracy though models applied to the trend item forecasting are eleven different ones. This superior performance of this separate forecasting technique is further confirmed by the paired-sample T tests

19. Evaluating the Performance of Polynomial Regression Method with Different Parameters during Color Characterization

Directory of Open Access Journals (Sweden)

Bangyong Sun

2014-01-01

Full Text Available The polynomial regression method is employed to calculate the relationship of device color space and CIE color space for color characterization, and the performance of different expressions with specific parameters is evaluated. Firstly, the polynomial equation for color conversion is established and the computation of polynomial coefficients is analysed. And then different forms of polynomial equations are used to calculate the RGB and CMYK’s CIE color values, while the corresponding color errors are compared. At last, an optimal polynomial expression is obtained by analysing several related parameters during color conversion, including polynomial numbers, the degree of polynomial terms, the selection of CIE visual spaces, and the linearization.

20. Face Hallucination with Linear Regression Model in Semi-Orthogonal Multilinear PCA Method

Science.gov (United States)

2018-04-01

In this paper, we propose a new face hallucination technique, face images reconstruction in HSV color space with a semi-orthogonal multilinear principal component analysis method. This novel hallucination technique can perform directly from tensors via tensor-to-vector projection by imposing the orthogonality constraint in only one mode. In our experiments, we use facial images from FERET database to test our hallucination approach which is demonstrated by extensive experiments with high-quality hallucinated color faces. The experimental results assure clearly demonstrated that we can generate photorealistic color face images by using the SO-MPCA subspace with a linear regression model.

1. Real-time prediction of respiratory motion based on local regression methods

International Nuclear Information System (INIS)

Ruan, D; Fessler, J A; Balter, J M

2007-01-01

Recent developments in modulation techniques enable conformal delivery of radiation doses to small, localized target volumes. One of the challenges in using these techniques is real-time tracking and predicting target motion, which is necessary to accommodate system latencies. For image-guided-radiotherapy systems, it is also desirable to minimize sampling rates to reduce imaging dose. This study focuses on predicting respiratory motion, which can significantly affect lung tumours. Predicting respiratory motion in real-time is challenging, due to the complexity of breathing patterns and the many sources of variability. We propose a prediction method based on local regression. There are three major ingredients of this approach: (1) forming an augmented state space to capture system dynamics, (2) local regression in the augmented space to train the predictor from previous observation data using semi-periodicity of respiratory motion, (3) local weighting adjustment to incorporate fading temporal correlations. To evaluate prediction accuracy, we computed the root mean square error between predicted tumor motion and its observed location for ten patients. For comparison, we also investigated commonly used predictive methods, namely linear prediction, neural networks and Kalman filtering to the same data. The proposed method reduced the prediction error for all imaging rates and latency lengths, particularly for long prediction lengths

2. Local regression type methods applied to the study of geophysics and high frequency financial data

Science.gov (United States)

Mariani, M. C.; Basu, K.

2014-09-01

In this work we applied locally weighted scatterplot smoothing techniques (Lowess/Loess) to Geophysical and high frequency financial data. We first analyze and apply this technique to the California earthquake geological data. A spatial analysis was performed to show that the estimation of the earthquake magnitude at a fixed location is very accurate up to the relative error of 0.01%. We also applied the same method to a high frequency data set arising in the financial sector and obtained similar satisfactory results. The application of this approach to the two different data sets demonstrates that the overall method is accurate and efficient, and the Lowess approach is much more desirable than the Loess method. The previous works studied the time series analysis; in this paper our local regression models perform a spatial analysis for the geophysics data providing different information. For the high frequency data, our models estimate the curve of best fit where data are dependent on time.

3. Comparing interactive videodisc training effectiveness to traditional training methods

International Nuclear Information System (INIS)

Kenworthy, N.W.

1987-01-01

Videodisc skills training programs developed by Industrial Training Corporation are being used and evaluated by major industrial facilities. In one such study, interactive videodisc training programs were compared to videotape and instructor-based training to determine the effectiveness of videodisc in terms of performance, training time and trainee attitudes. Results showed that when initial training was done using the interactive videodisc system, trainee performance was superior to the performance of trainees using videotape, and approximately equal to the performance of those trained by an instructor. When each method was used in follow-up training, interactive videodisc was definitely the most effective. Results also indicate that training time can be reduced using interactive videodisc. Attitudes of both trainees and instructors toward the interactive videodisc training were positive

4. Forecast daily indices of solar activity, F10.7, using support vector regression method

International Nuclear Information System (INIS)

Huang Cong; Liu Dandan; Wang Jingsong

2009-01-01

The 10.7 cm solar radio flux (F10.7), the value of the solar radio emission flux density at a wavelength of 10.7 cm, is a useful index of solar activity as a proxy for solar extreme ultraviolet radiation. It is meaningful and important to predict F10.7 values accurately for both long-term (months-years) and short-term (days) forecasting, which are often used as inputs in space weather models. This study applies a novel neural network technique, support vector regression (SVR), to forecasting daily values of F10.7. The aim of this study is to examine the feasibility of SVR in short-term F10.7 forecasting. The approach, based on SVR, reduces the dimension of feature space in the training process by using a kernel-based learning algorithm. Thus, the complexity of the calculation becomes lower and a small amount of training data will be sufficient. The time series of F10.7 from 2002 to 2006 are employed as the data sets. The performance of the approach is estimated by calculating the norm mean square error and mean absolute percentage error. It is shown that our approach can perform well by using fewer training data points than the traditional neural network. (research paper)

5. Device and method for traditional chinese medicine diagnosis using radioactive tracer method

Energy Technology Data Exchange (ETDEWEB)

Wu, Shanling; Shen, Miaohe

1997-05-29

Disclosed is a device and method for traditional chinese medicine diagnosis using radioactive-tracer method. At least two nuclear radiation probes are arranged apart along the channels to detect the changing with time and on space of the intensity of radioactivity of the nuclear radioactive tracer which has been injected into the body in the channel position. The detected signals are amplified by amplifiers, and the outputs of the amplifiers are applied to data processing means which monitor the whole detecting process in real time and analyse and process the detected information about the changing of the intensity of radioactivity with time and on space indicating the operating of vital energy and blood, and obtain state parameters about operating of vital energy and blood in the body which is then output through data output means. (author) figs.

6. QSAR Study of Insecticides of Phthalamide Derivatives Using Multiple Linear Regression and Artificial Neural Network Methods

Directory of Open Access Journals (Sweden)

2014-03-01

Full Text Available Quantitative structure activity relationship (QSAR for 21 insecticides of phthalamides containing hydrazone (PCH was studied using multiple linear regression (MLR, principle component regression (PCR and artificial neural network (ANN. Five descriptors were included in the model for MLR and ANN analysis, and five latent variables obtained from principle component analysis (PCA were used in PCR analysis. Calculation of descriptors was performed using semi-empirical PM6 method. ANN analysis was found to be superior statistical technique compared to the other methods and gave a good correlation between descriptors and activity (r2 = 0.84. Based on the obtained model, we have successfully designed some new insecticides with higher predicted activity than those of previously synthesized compounds, e.g.2-(decalinecarbamoyl-5-chloro-N’-((5-methylthiophen-2-ylmethylene benzohydrazide, 2-(decalinecarbamoyl-5-chloro-N’-((thiophen-2-yl-methylene benzohydrazide and 2-(decaline carbamoyl-N’-(4-fluorobenzylidene-5-chlorobenzohydrazide with predicted log LC50 of 1.640, 1.672, and 1.769 respectively.

7. Nonparametric Methods in Astronomy: Think, Regress, Observe—Pick Any Three

Science.gov (United States)

Steinhardt, Charles L.; Jermyn, Adam S.

2018-02-01

Telescopes are much more expensive than astronomers, so it is essential to minimize required sample sizes by using the most data-efficient statistical methods possible. However, the most commonly used model-independent techniques for finding the relationship between two variables in astronomy are flawed. In the worst case they can lead without warning to subtly yet catastrophically wrong results, and even in the best case they require more data than necessary. Unfortunately, there is no single best technique for nonparametric regression. Instead, we provide a guide for how astronomers can choose the best method for their specific problem and provide a python library with both wrappers for the most useful existing algorithms and implementations of two new algorithms developed here.

8. An Application of Robust Method in Multiple Linear Regression Model toward Credit Card Debt

Science.gov (United States)

Amira Azmi, Nur; Saifullah Rusiman, Mohd; Khalid, Kamil; Roslan, Rozaini; Sufahani, Suliadi; Mohamad, Mahathir; Salleh, Rohayu Mohd; Hamzah, Nur Shamsidah Amir

2018-04-01

Credit card is a convenient alternative replaced cash or cheque, and it is essential component for electronic and internet commerce. In this study, the researchers attempt to determine the relationship and significance variables between credit card debt and demographic variables such as age, household income, education level, years with current employer, years at current address, debt to income ratio and other debt. The provided data covers 850 customers information. There are three methods that applied to the credit card debt data which are multiple linear regression (MLR) models, MLR models with least quartile difference (LQD) method and MLR models with mean absolute deviation method. After comparing among three methods, it is found that MLR model with LQD method became the best model with the lowest value of mean square error (MSE). According to the final model, it shows that the years with current employer, years at current address, household income in thousands and debt to income ratio are positively associated with the amount of credit debt. Meanwhile variables for age, level of education and other debt are negatively associated with amount of credit debt. This study may serve as a reference for the bank company by using robust methods, so that they could better understand their options and choice that is best aligned with their goals for inference regarding to the credit card debt.

9. Estimating HIES Data through Ratio and Regression Methods for Different Sampling Designs

Directory of Open Access Journals (Sweden)

2007-01-01

Full Text Available In this study, comparison has been made for different sampling designs, using the HIES data of North West Frontier Province (NWFP for 2001-02 and 1998-99 collected from the Federal Bureau of Statistics, Statistical Division, Government of Pakistan, Islamabad. The performance of the estimators has also been considered using bootstrap and Jacknife. A two-stage stratified random sample design is adopted by HIES. In the first stage, enumeration blocks and villages are treated as the first stage Primary Sampling Units (PSU. The sample PSU’s are selected with probability proportional to size. Secondary Sampling Units (SSU i.e., households are selected by systematic sampling with a random start. They have used a single study variable. We have compared the HIES technique with some other designs, which are: Stratified Simple Random Sampling. Stratified Systematic Sampling. Stratified Ranked Set Sampling. Stratified Two Phase Sampling. Ratio and Regression methods were applied with two study variables, which are: Income (y and Household sizes (x. Jacknife and Bootstrap are used for variance replication. Simple Random Sampling with sample size (462 to 561 gave moderate variances both by Jacknife and Bootstrap. By applying Systematic Sampling, we received moderate variance with sample size (467. In Jacknife with Systematic Sampling, we obtained variance of regression estimator greater than that of ratio estimator for a sample size (467 to 631. At a sample size (952 variance of ratio estimator gets greater than that of regression estimator. The most efficient design comes out to be Ranked set sampling compared with other designs. The Ranked set sampling with jackknife and bootstrap, gives minimum variance even with the smallest sample size (467. Two Phase sampling gave poor performance. Multi-stage sampling applied by HIES gave large variances especially if used with a single study variable.

10. Prevalence of depressive symptoms among medical students taught using problem-based learning versus traditional methods.

Science.gov (United States)

Aragão, José Aderval; Freire, Marianna Ribeiro de Menezes; Nolasco Farias, Lucas Guimarães; Diniz, Sarah Santana; Sant'anna Aragão, Felipe Matheus; Sant'anna Aragão, Iapunira Catarina; Lima, Tarcisio Brandão; Reis, Francisco Prado

2018-06-01

To compare depressive symptoms among medical students taught using problem-based learning (PBL) and the traditional method. Beck's Depression Inventory was applied to 215 medical students. The prevalence of depression was calculated as the number of individuals with depression divided by the total number in the sample from each course, with 95% confidence intervals. The statistical significance level used was 5% (p ≤ .05). Among the 215 students, 52.1% were male and 47.9% were female; and 51.6% were being taught using PBL methodology and 48.4% using traditional methods. The prevalence of depression was 29.73% with PBL and 22.12% with traditional methods. There was higher prevalence among females: 32.8% with PBL and 23.1% with traditional methods. The prevalence of depression with PBL among students up to 21 years of age was 29.4% and among those over 21 years, 32.1%. With traditional methods among students up to 21 years of age, it was 16.7%%, and among those over 21 years, 30.1%. The prevalence of depression with PBL was highest among students in the second semester and with traditional methods, in the eighth. Depressive symptoms were highly prevalent among students taught both with PBL and with traditional methods.

11. Robust Methods for Moderation Analysis with a Two-Level Regression Model.

Science.gov (United States)

Yang, Miao; Yuan, Ke-Hai

2016-01-01

Moderation analysis has many applications in social sciences. Most widely used estimation methods for moderation analysis assume that errors are normally distributed and homoscedastic. When these assumptions are not met, the results from a classical moderation analysis can be misleading. For more reliable moderation analysis, this article proposes two robust methods with a two-level regression model when the predictors do not contain measurement error. One method is based on maximum likelihood with Student's t distribution and the other is based on M-estimators with Huber-type weights. An algorithm for obtaining the robust estimators is developed. Consistent estimates of standard errors of the robust estimators are provided. The robust approaches are compared against normal-distribution-based maximum likelihood (NML) with respect to power and accuracy of parameter estimates through a simulation study. Results show that the robust approaches outperform NML under various distributional conditions. Application of the robust methods is illustrated through a real data example. An R program is developed and documented to facilitate the application of the robust methods.

12. Applications of Monte Carlo method to nonlinear regression of rheological data

Science.gov (United States)

Kim, Sangmo; Lee, Junghaeng; Kim, Sihyun; Cho, Kwang Soo

2018-02-01

In rheological study, it is often to determine the parameters of rheological models from experimental data. Since both rheological data and values of the parameters vary in logarithmic scale and the number of the parameters is quite large, conventional method of nonlinear regression such as Levenberg-Marquardt (LM) method is usually ineffective. The gradient-based method such as LM is apt to be caught in local minima which give unphysical values of the parameters whenever the initial guess of the parameters is far from the global optimum. Although this problem could be solved by simulated annealing (SA), the Monte Carlo (MC) method needs adjustable parameter which could be determined in ad hoc manner. We suggest a simplified version of SA, a kind of MC methods which results in effective values of the parameters of most complicated rheological models such as the Carreau-Yasuda model of steady shear viscosity, discrete relaxation spectrum and zero-shear viscosity as a function of concentration and molecular weight.

13. [Applications of mathematical statistics methods on compatibility researches of traditional Chinese medicines formulae].

Science.gov (United States)

Mai, Lan-Yin; Li, Yi-Xuan; Chen, Yong; Xie, Zhen; Li, Jie; Zhong, Ming-Yu

2014-05-01

The compatibility of traditional Chinese medicines (TCMs) formulae containing enormous information, is a complex component system. Applications of mathematical statistics methods on the compatibility researches of traditional Chinese medicines formulae have great significance for promoting the modernization of traditional Chinese medicines and improving clinical efficacies and optimizations of formulae. As a tool for quantitative analysis, data inference and exploring inherent rules of substances, the mathematical statistics method can be used to reveal the working mechanisms of the compatibility of traditional Chinese medicines formulae in qualitatively and quantitatively. By reviewing studies based on the applications of mathematical statistics methods, this paper were summarized from perspective of dosages optimization, efficacies and changes of chemical components as well as the rules of incompatibility and contraindication of formulae, will provide the references for further studying and revealing the working mechanisms and the connotations of traditional Chinese medicines.

14. Perspective for applying traditional and inovative teaching and learning methods to nurses continuing education

OpenAIRE

Bendinskaitė, Irmina

2015-01-01

Bendinskaitė I. Perspective for applying traditional and innovative teaching and learning methods to nurse’s continuing education, magister thesis / supervisor Assoc. Prof. O. Riklikienė; Departament of Nursing and Care, Faculty of Nursing, Lithuanian University of Health Sciences. – Kaunas, 2015, – p. 92 The purpose of this study was to investigate traditional and innovative teaching and learning methods perspective to nurse’s continuing education. Material and methods. In a period fro...

15. A Comparative Investigation of the Combined Effects of Pre-Processing, Wavelength Selection, and Regression Methods on Near-Infrared Calibration Model Performance.

Science.gov (United States)

Wan, Jian; Chen, Yi-Chieh; Morris, A Julian; Thennadil, Suresh N

2017-07-01

role in the calibration while wavelength selection plays a marginal role and the combination of certain pre-processing, wavelength selection, and nonlinear regression methods can achieve superior performance over traditional linear regression-based calibration.

16. Logistic Regression and Path Analysis Method to Analyze Factors influencing Students’ Achievement

Science.gov (United States)

Noeryanti, N.; Suryowati, K.; Setyawan, Y.; Aulia, R. R.

2018-04-01

Students' academic achievement cannot be separated from the influence of two factors namely internal and external factors. The first factors of the student (internal factors) consist of intelligence (X1), health (X2), interest (X3), and motivation of students (X4). The external factors consist of family environment (X5), school environment (X6), and society environment (X7). The objects of this research are eighth grade students of the school year 2016/2017 at SMPN 1 Jiwan Madiun sampled by using simple random sampling. Primary data are obtained by distributing questionnaires. The method used in this study is binary logistic regression analysis that aims to identify internal and external factors that affect student’s achievement and how the trends of them. Path Analysis was used to determine the factors that influence directly, indirectly or totally on student’s achievement. Based on the results of binary logistic regression, variables that affect student’s achievement are interest and motivation. And based on the results obtained by path analysis, factors that have a direct impact on student’s achievement are students’ interest (59%) and students’ motivation (27%). While the factors that have indirect influences on students’ achievement, are family environment (97%) and school environment (37).

17. Modelling Status Food Security Households Disease Sufferers Pulmonary Tuberculosis Uses the Method Regression Logistics Binary

Science.gov (United States)

Wulandari, S. P.; Salamah, M.; Rositawati, A. F. D.

2018-04-01

Food security is the condition where the food fulfilment is managed well for the country till the individual. Indonesia is one of the country which has the commitment to create the food security becomes main priority. However, the food necessity becomes common thing means that it doesn’t care about nutrient standard and the health condition of family member, so in the fulfilment of food necessity also has to consider the disease suffered by the family member, one of them is pulmonary tuberculosa. From that reasons, this research is conducted to know the factors which influence on household food security status which suffered from pulmonary tuberculosis in the coastal area of Surabaya by using binary logistic regression method. The analysis result by using binary logistic regression shows that the variables wife latest education, house density and spacious house ventilation significantly affect on household food security status which suffered from pulmonary tuberculosis in the coastal area of Surabaya, where the wife education level is University/equivalent, the house density is eligible or 8 m2/person and spacious house ventilation 10% of the floor area has the opportunity to become food secure households amounted to 0.911089. While the chance of becoming food insecure households amounted to 0.088911. The model household food security status which suffered from pulmonary tuberculosis in the coastal area of Surabaya has been conformable, and the overall percentages of those classifications are at 71.8%.

18. TEMPERATURE PREDICTION IN 3013 CONTAINERS IN K AREA MATERIAL STORAGE (KAMS) FACILITY USING REGRESSION METHODS

International Nuclear Information System (INIS)

Gupta, N

2008-01-01

3013 containers are designed in accordance with the DOE-STD-3013-2004. These containers are qualified to store plutonium (Pu) bearing materials such as PuO2 for 50 years. DOT shipping packages such as the 9975 are used to store the 3013 containers in the K-Area Material Storage (KAMS) facility at Savannah River Site (SRS). DOE-STD-3013-2004 requires that a comprehensive surveillance program be set up to ensure that the 3013 container design parameters are not violated during the long term storage. To ensure structural integrity of the 3013 containers, thermal analyses using finite element models were performed to predict the contents and component temperatures for different but well defined parameters such as storage ambient temperature, PuO 2 density, fill heights, weights, and thermal loading. Interpolation is normally used to calculate temperatures if the actual parameter values are different from the analyzed values. A statistical analysis technique using regression methods is proposed to develop simple polynomial relations to predict temperatures for the actual parameter values found in the containers. The analysis shows that regression analysis is a powerful tool to develop simple relations to assess component temperatures

19. Multi-step polynomial regression method to model and forecast malaria incidence.

Directory of Open Access Journals (Sweden)

Chandrajit Chatterjee

Full Text Available Malaria is one of the most severe problems faced by the world even today. Understanding the causative factors such as age, sex, social factors, environmental variability etc. as well as underlying transmission dynamics of the disease is important for epidemiological research on malaria and its eradication. Thus, development of suitable modeling approach and methodology, based on the available data on the incidence of the disease and other related factors is of utmost importance. In this study, we developed a simple non-linear regression methodology in modeling and forecasting malaria incidence in Chennai city, India, and predicted future disease incidence with high confidence level. We considered three types of data to develop the regression methodology: a longer time series data of Slide Positivity Rates (SPR of malaria; a smaller time series data (deaths due to Plasmodium vivax of one year; and spatial data (zonal distribution of P. vivax deaths for the city along with the climatic factors, population and previous incidence of the disease. We performed variable selection by simple correlation study, identification of the initial relationship between variables through non-linear curve fitting and used multi-step methods for induction of variables in the non-linear regression analysis along with applied Gauss-Markov models, and ANOVA for testing the prediction, validity and constructing the confidence intervals. The results execute the applicability of our method for different types of data, the autoregressive nature of forecasting, and show high prediction power for both SPR and P. vivax deaths, where the one-lag SPR values plays an influential role and proves useful for better prediction. Different climatic factors are identified as playing crucial role on shaping the disease curve. Further, disease incidence at zonal level and the effect of causative factors on different zonal clusters indicate the pattern of malaria prevalence in the city

20. A novel classification method for aid decision of traditional Chinese patent medicines for stroke treatment.

Science.gov (United States)

Zhao, Yufeng; Liu, Bo; He, Liyun; Bai, Wenjing; Yu, Xueyun; Cao, Xinyu; Luo, Lin; Rong, Peijing; Zhao, Yuxue; Li, Guozheng; Liu, Baoyan

2017-09-01

1. A New Global Regression Analysis Method for the Prediction of Wind Tunnel Model Weight Corrections

Science.gov (United States)

Ulbrich, Norbert Manfred; Bridge, Thomas M.; Amaya, Max A.

2014-01-01

A new global regression analysis method is discussed that predicts wind tunnel model weight corrections for strain-gage balance loads during a wind tunnel test. The method determines corrections by combining "wind-on" model attitude measurements with least squares estimates of the model weight and center of gravity coordinates that are obtained from "wind-off" data points. The method treats the least squares fit of the model weight separate from the fit of the center of gravity coordinates. Therefore, it performs two fits of "wind- off" data points and uses the least squares estimator of the model weight as an input for the fit of the center of gravity coordinates. Explicit equations for the least squares estimators of the weight and center of gravity coordinates are derived that simplify the implementation of the method in the data system software of a wind tunnel. In addition, recommendations for sets of "wind-off" data points are made that take typical model support system constraints into account. Explicit equations of the confidence intervals on the model weight and center of gravity coordinates and two different error analyses of the model weight prediction are also discussed in the appendices of the paper.

2. Reducing false-positive incidental findings with ensemble genotyping and logistic regression based variant filtering methods.

Science.gov (United States)

Hwang, Kyu-Baek; Lee, In-Hee; Park, Jin-Ho; Hambuch, Tina; Choe, Yongjoon; Kim, MinHyeok; Lee, Kyungjoon; Song, Taemin; Neu, Matthew B; Gupta, Neha; Kohane, Isaac S; Green, Robert C; Kong, Sek Won

2014-08-01

As whole genome sequencing (WGS) uncovers variants associated with rare and common diseases, an immediate challenge is to minimize false-positive findings due to sequencing and variant calling errors. False positives can be reduced by combining results from orthogonal sequencing methods, but costly. Here, we present variant filtering approaches using logistic regression (LR) and ensemble genotyping to minimize false positives without sacrificing sensitivity. We evaluated the methods using paired WGS datasets of an extended family prepared using two sequencing platforms and a validated set of variants in NA12878. Using LR or ensemble genotyping based filtering, false-negative rates were significantly reduced by 1.1- to 17.8-fold at the same levels of false discovery rates (5.4% for heterozygous and 4.5% for homozygous single nucleotide variants (SNVs); 30.0% for heterozygous and 18.7% for homozygous insertions; 25.2% for heterozygous and 16.6% for homozygous deletions) compared to the filtering based on genotype quality scores. Moreover, ensemble genotyping excluded > 98% (105,080 of 107,167) of false positives while retaining > 95% (897 of 937) of true positives in de novo mutation (DNM) discovery in NA12878, and performed better than a consensus method using two sequencing platforms. Our proposed methods were effective in prioritizing phenotype-associated variants, and an ensemble genotyping would be essential to minimize false-positive DNM candidates. © 2014 WILEY PERIODICALS, INC.

3. A dynamic particle filter-support vector regression method for reliability prediction

International Nuclear Information System (INIS)

Wei, Zhao; Tao, Tao; ZhuoShu, Ding; Zio, Enrico

2013-01-01

Support vector regression (SVR) has been applied to time series prediction and some works have demonstrated the feasibility of its use to forecast system reliability. For accuracy of reliability forecasting, the selection of SVR's parameters is important. The existing research works on SVR's parameters selection divide the example dataset into training and test subsets, and tune the parameters on the training data. However, these fixed parameters can lead to poor prediction capabilities if the data of the test subset differ significantly from those of training. Differently, the novel method proposed in this paper uses particle filtering to estimate the SVR model parameters according to the whole measurement sequence up to the last observation instance. By treating the SVR training model as the observation equation of a particle filter, our method allows updating the SVR model parameters dynamically when a new observation comes. Because of the adaptability of the parameters to dynamic data pattern, the new PF–SVR method has superior prediction performance over that of standard SVR. Four application results show that PF–SVR is more robust than SVR to the decrease of the number of training data and the change of initial SVR parameter values. Also, even if there are trends in the test data different from those in the training data, the method can capture the changes, correct the SVR parameters and obtain good predictions. -- Highlights: •A dynamic PF–SVR method is proposed to predict the system reliability. •The method can adjust the SVR parameters according to the change of data. •The method is robust to the size of training data and initial parameter values. •Some cases based on both artificial and real data are studied. •PF–SVR shows superior prediction performance over standard SVR

4. Statistical learning method in regression analysis of simulated positron spectral data

International Nuclear Information System (INIS)

Avdic, S. Dz.

2005-01-01

Positron lifetime spectroscopy is a non-destructive tool for detection of radiation induced defects in nuclear reactor materials. This work concerns the applicability of the support vector machines method for the input data compression in the neural network analysis of positron lifetime spectra. It has been demonstrated that the SVM technique can be successfully applied to regression analysis of positron spectra. A substantial data compression of about 50 % and 8 % of the whole training set with two and three spectral components respectively has been achieved including a high accuracy of the spectra approximation. However, some parameters in the SVM approach such as the insensitivity zone e and the penalty parameter C have to be chosen carefully to obtain a good performance. (author)

5. The crux of the method: assumptions in ordinary least squares and logistic regression.

Science.gov (United States)

Long, Rebecca G

2008-10-01

Logistic regression has increasingly become the tool of choice when analyzing data with a binary dependent variable. While resources relating to the technique are widely available, clear discussions of why logistic regression should be used in place of ordinary least squares regression are difficult to find. The current paper compares and contrasts the assumptions of ordinary least squares with those of logistic regression and explains why logistic regression's looser assumptions make it adept at handling violations of the more important assumptions in ordinary least squares.

6. Regression trees for predicting mortality in patients with cardiovascular disease: What improvement is achieved by using ensemble-based methods?

Science.gov (United States)

Austin, Peter C; Lee, Douglas S; Steyerberg, Ewout W; Tu, Jack V

2012-01-01

In biomedical research, the logistic regression model is the most commonly used method for predicting the probability of a binary outcome. While many clinical researchers have expressed an enthusiasm for regression trees, this method may have limited accuracy for predicting health outcomes. We aimed to evaluate the improvement that is achieved by using ensemble-based methods, including bootstrap aggregation (bagging) of regression trees, random forests, and boosted regression trees. We analyzed 30-day mortality in two large cohorts of patients hospitalized with either acute myocardial infarction (N = 16,230) or congestive heart failure (N = 15,848) in two distinct eras (1999–2001 and 2004–2005). We found that both the in-sample and out-of-sample prediction of ensemble methods offered substantial improvement in predicting cardiovascular mortality compared to conventional regression trees. However, conventional logistic regression models that incorporated restricted cubic smoothing splines had even better performance. We conclude that ensemble methods from the data mining and machine learning literature increase the predictive performance of regression trees, but may not lead to clear advantages over conventional logistic regression models for predicting short-term mortality in population-based samples of subjects with cardiovascular disease. PMID:22777999

7. Using traditional methods and indigenous technologies for coping with climate variability

NARCIS (Netherlands)

Stigter, C.J.; Zheng Dawei,; Onyewotu, L.O.Z.; Mei Xurong,

2005-01-01

In agrometeorology and management of meteorology related natural resources, many traditional methods and indigenous technologies are still in use or being revived for managing low external inputs sustainable agriculture (LEISA) under conditions of climate variability. This paper starts with the

8. Efficacy of traditional maize (Zea mays L.) seed storage methods in ...

African Journals Online (AJOL)

Efficacy of traditional maize (Zea mays L.) seed storage methods in western Kenya. ... PROMOTING ACCESS TO AFRICAN RESEARCH. AFRICAN JOURNALS ONLINE (AJOL) ... African Journal of Food, Agriculture, Nutrition and Development.

9. Simultaneous chemometric determination of pyridoxine hydrochloride and isoniazid in tablets by multivariate regression methods.

Science.gov (United States)

Dinç, Erdal; Ustündağ, Ozgür; Baleanu, Dumitru

2010-08-01

The sole use of pyridoxine hydrochloride during treatment of tuberculosis gives rise to pyridoxine deficiency. Therefore, a combination of pyridoxine hydrochloride and isoniazid is used in pharmaceutical dosage form in tuberculosis treatment to reduce this side effect. In this study, two chemometric methods, partial least squares (PLS) and principal component regression (PCR), were applied to the simultaneous determination of pyridoxine (PYR) and isoniazid (ISO) in their tablets. A concentration training set comprising binary mixtures of PYR and ISO consisting of 20 different combinations were randomly prepared in 0.1 M HCl. Both multivariate calibration models were constructed using the relationships between the concentration data set (concentration data matrix) and absorbance data matrix in the spectral region 200-330 nm. The accuracy and the precision of the proposed chemometric methods were validated by analyzing synthetic mixtures containing the investigated drugs. The recovery results obtained by applying PCR and PLS calibrations to the artificial mixtures were found between 100.0 and 100.7%. Satisfactory results obtained by applying the PLS and PCR methods to both artificial and commercial samples were obtained. The results obtained in this manuscript strongly encourage us to use them for the quality control and the routine analysis of the marketing tablets containing PYR and ISO drugs. Copyright © 2010 John Wiley & Sons, Ltd.

10. Non-invasive diagnostic methods for atherosclerosis and use in assessing progression and regression in hypercholesterolemia

International Nuclear Information System (INIS)

Tsushima, Motoo; Fujii, Shigeki; Yutani, Chikao; Yamamoto, Akira; Naitoh, Hiroaki.

1990-01-01

We evaluated the wall thickening and stenosis rate (ASI), the calcification rate (ACI), and the wall thickening and calcification stenosis rate (SCI) of the lower abdominal aorta calculated by the 12 sector method from simple or enhanced computed tomography. The intra-observer variation of the calculation of ASI was 5.7% and that of ACI was 2.4%. In 9 patients who underwent an autopsy examination, ACI was significantly correlated with the rate of the calcification dimension to the whole objective area of the abdominal aorta (r=0.856, p<0.01). However, there were no correlations between ASI and the surface involvement or the atherosclerotic index obtained by the point-counting method of the autopsy materials. In the analysis of 40 patients with atherosclerotic vascular diseases, ASI and ACI were also highly correlated with the percentage volume of the arterial wall in relation to the whole volume of the observed artery (r=0.852, p<0.0001) and also the percentage calcification volume (r=0.913, p<0.0001) calculated by the computed method, respectively. The percentage of atherosclerotic vascular diseases increased in the group of both high ASI (over 10%) and high ACI (over 20%). We used SCI as a reliable index when the progression and regression of atherosclerosis was considered. Among patients of hypercholesterolemia consisting of 15 with familial hypercholesterolemia (FH) and 6 non-FH patients, the change of SCI (d-SCI) was significantly correlated with the change of total cholesterol concentration (d-TC) after the treatment (r=0.466, p<0.05) and the change of the right Achilles' tendon thickening (d-ATT) was also correlated with d-TC (r=0.634, p<0.005). However, no correlation between d-SCI and d-ATT was observed. In conclusion, CT indices of atherosclerosis were useful as a noninvasive quantitative diagnostic method and we were able to use them to assess the progression and regression of atherosclerosis. (author)

11. Web-based versus traditional lecture: are they equally effective as a flexible bronchoscopy teaching method?

OpenAIRE

Sterse Mata, Caio Augusto [UNIFESP; Ota, Luiz Hirotoshi [UNIFESP; Suzuki, Iunis [UNIFESP; Telles, Adriana [UNIFESP; Miotto, Andre [UNIFESP; Leao, Luiz Eduardo Villaca [UNIFESP

2012-01-01

This study compares the traditional live lecture to a web-based approach in the teaching of bronchoscopy and evaluates the positive and negative aspects of both methods. We developed a web-based bronchoscopy curriculum, which integrates texts, images and animations. It was applied to first-year interns, who were later administered a multiple-choice test. Another group of eight first-year interns received the traditional teaching method and the same test. the two groups were compared using the...

12. Reflexion on linear regression trip production modelling method for ensuring good model quality

Science.gov (United States)

Suprayitno, Hitapriya; Ratnasari, Vita

2017-11-01

Transport Modelling is important. For certain cases, the conventional model still has to be used, in which having a good trip production model is capital. A good model can only be obtained from a good sample. Two of the basic principles of a good sampling is having a sample capable to represent the population characteristics and capable to produce an acceptable error at a certain confidence level. It seems that this principle is not yet quite understood and used in trip production modeling. Therefore, investigating the Trip Production Modelling practice in Indonesia and try to formulate a better modeling method for ensuring the Model Quality is necessary. This research result is presented as follows. Statistics knows a method to calculate span of prediction value at a certain confidence level for linear regression, which is called Confidence Interval of Predicted Value. The common modeling practice uses R2 as the principal quality measure, the sampling practice varies and not always conform to the sampling principles. An experiment indicates that small sample is already capable to give excellent R2 value and sample composition can significantly change the model. Hence, good R2 value, in fact, does not always mean good model quality. These lead to three basic ideas for ensuring good model quality, i.e. reformulating quality measure, calculation procedure, and sampling method. A quality measure is defined as having a good R2 value and a good Confidence Interval of Predicted Value. Calculation procedure must incorporate statistical calculation method and appropriate statistical tests needed. A good sampling method must incorporate random well distributed stratified sampling with a certain minimum number of samples. These three ideas need to be more developed and tested.

13. ON THE EFFECTS OF THE PRESENCE AND METHODS OF THE ELIMINATION HETEROSCEDASTICITY AND AUTOCORRELATION IN THE REGRESSION MODEL

Directory of Open Access Journals (Sweden)

Nina L. Timofeeva

2014-01-01

Full Text Available The article presents the methodological and technical bases for the creation of regression models that adequately reflect reality. The focus is on methods of removing residual autocorrelation in models. Algorithms eliminating heteroscedasticity and autocorrelation of the regression model residuals: reweighted least squares method, the method of Cochran-Orkutta are given. A model of "pure" regression is build, as well as to compare the effect on the dependent variable of the different explanatory variables when the latter are expressed in different units, a standardized form of the regression equation. The scheme of abatement techniques of heteroskedasticity and autocorrelation for the creation of regression models specific to the social and cultural sphere is developed.

14. Using a Regression Method for Estimating Performance in a Rapid Serial Visual Presentation Target-Detection Task

Science.gov (United States)

2017-12-01

Fig. 2 Simulation method; the process for one iteration of the simulation . It was repeated 250 times per combination of HR and FAR. Analysis was...distribution is unlimited. 8 Fig. 2 Simulation method; the process for one iteration of the simulation . It was repeated 250 times per combination of HR...stimuli. Simulations show that this regression method results in an unbiased and accurate estimate of target detection performance. The regression

15. Regression methods to investigate the relationship between facial measurements and widths of the maxillary anterior teeth.

Science.gov (United States)

Isa, Zakiah Mohd; Tawfiq, Omar Farouq; Noor, Norliza Mohd; Shamsudheen, Mohd Iqbal; Rijal, Omar Mohd

2010-03-01

In rehabilitating edentulous patients, selecting appropriately sized teeth in the absence of preextraction records is problematic. The purpose of this study was to investigate the relationships between some facial dimensions and widths of the maxillary anterior teeth to potentially provide a guide for tooth selection. Sixty full dentate Malaysian adults (18-36 years) representing 2 ethnic groups (Malay and Chinese), with well aligned maxillary anterior teeth and minimal attrition, participated in this study. Standardized digital images of the face, viewed frontally, were recorded. Using image analyzing software, the images were used to determine the interpupillary distance (IPD), inner canthal distance (ICD), and interalar width (IA). Widths of the 6 maxillary anterior teeth were measured directly from casts of the subjects using digital calipers. Regression analyses were conducted to measure the strength of the associations between the variables (alpha=.10). The means (standard deviations) of IPD, IA, and ICD of the subjects were 62.28 (2.47), 39.36 (3.12), and 34.36 (2.15) mm, respectively. The mesiodistal diameters of the maxillary central incisors, lateral incisors, and canines were 8.54 (0.50), 7.09 (0.48), and 7.94 (0.40) mm, respectively. The width of the central incisors was highly correlated to the IPD (r=0.99), while the widths of the lateral incisors and canines were highly correlated to a combination of IPD and IA (r=0.99 and 0.94, respectively). Using regression methods, the widths of the anterior teeth within the population tested may be predicted by a combination of the facial dimensions studied. (c) 2010 The Editorial Council of the Journal of Prosthetic Dentistry. Published by Mosby, Inc. All rights reserved.

16. A graphical method to evaluate spectral preprocessing in multivariate regression calibrations: example with Savitzky-Golay filters and partial least squares regression.

Science.gov (United States)

Delwiche, Stephen R; Reeves, James B

2010-01-01

In multivariate regression analysis of spectroscopy data, spectral preprocessing is often performed to reduce unwanted background information (offsets, sloped baselines) or accentuate absorption features in intrinsically overlapping bands. These procedures, also known as pretreatments, are commonly smoothing operations or derivatives. While such operations are often useful in reducing the number of latent variables of the actual decomposition and lowering residual error, they also run the risk of misleading the practitioner into accepting calibration equations that are poorly adapted to samples outside of the calibration. The current study developed a graphical method to examine this effect on partial least squares (PLS) regression calibrations of near-infrared (NIR) reflection spectra of ground wheat meal with two analytes, protein content and sodium dodecyl sulfate sedimentation (SDS) volume (an indicator of the quantity of the gluten proteins that contribute to strong doughs). These two properties were chosen because of their differing abilities to be modeled by NIR spectroscopy: excellent for protein content, fair for SDS sedimentation volume. To further demonstrate the potential pitfalls of preprocessing, an artificial component, a randomly generated value, was included in PLS regression trials. Savitzky-Golay (digital filter) smoothing, first-derivative, and second-derivative preprocess functions (5 to 25 centrally symmetric convolution points, derived from quadratic polynomials) were applied to PLS calibrations of 1 to 15 factors. The results demonstrated the danger of an over reliance on preprocessing when (1) the number of samples used in a multivariate calibration is low (<50), (2) the spectral response of the analyte is weak, and (3) the goodness of the calibration is based on the coefficient of determination (R(2)) rather than a term based on residual error. The graphical method has application to the evaluation of other preprocess functions and various

17. High cycle fatigue test and regression methods of S-N curve

International Nuclear Information System (INIS)

Kim, D. W.; Park, J. Y.; Kim, W. G.; Yoon, J. H.

2011-11-01

The fatigue design curve in the ASME Boiler and Pressure Vessel Code Section III are based on the assumption that fatigue life is infinite after 106 cycles. This is because standard fatigue testing equipment prior to the past decades was limited in speed to less than 200 cycles per second. Traditional servo-hydraulic machines work at frequency of 50 Hz. Servo-hydraulic machines working at 1000 Hz have been developed after 1997. This machines allow high frequency and displacement of up to ±0.1 mm and dynamic load of ±20 kN are guaranteed. The frequency of resonant fatigue test machine is 50-250 Hz. Various forced vibration-based system works at 500 Hz or 1.8 kHz. Rotating bending machines allow testing frequency at 0.1-200 Hz. The main advantage of ultrasonic fatigue testing at 20 kHz is performing Although S-N curve is determined by experiment, the fatigue strength corresponding to a given fatigue life should be determined by statistical method considering the scatter of fatigue properties. In this report, the statistical methods for evaluation of fatigue test data is investigated

18. Comparison of Online and Traditional Basic Life Support Renewal Training Methods for Registered Professional Nurses.

Science.gov (United States)

Serwetnyk, Tara M; Filmore, Kristi; VonBacho, Stephanie; Cole, Robert; Miterko, Cindy; Smith, Caitlin; Smith, Charlene M

2015-01-01

Basic Life Support certification for nursing staff is achieved through various training methods. This study compared three American Heart Association training methods for nurses seeking Basic Life Support renewal: a traditional classroom approach and two online options. Findings indicate that online methods for Basic Life Support renewal deliver cost and time savings, while maintaining positive learning outcomes, satisfaction, and confidence level of participants.

19. The review of the achieved degree of sustainable development in South Eastern Europe - The use of linear regression method

Energy Technology Data Exchange (ETDEWEB)

Golusin, Mirjana [Educons University, Vojvode Putnika st. bb, 21013 Sremska Kamnica (RS); Ivanovic, Olja Munitlak [Faculty of Business in Services, Vojvode Putnik st. bb, 21013 Sremska Kamenica (RS); Teodorovic, Natasa [Faculty of Entrepreneurial Management, Modene st. 5, 21000 Novi Sad (RS)

2011-01-15

The need for preservation and adequate management of the quality of environment requires the development of new methods and techniques by which the achieved degree of sustainable development can be defined as well as the laws regarding the relationship among its subsystems. Main objective of research is to point to a strong contradiction between the development of ecological and economic subsystems. In order to improve previous research, this study suggests the use of linear evaluation, by which it is possible to determine the exact degree of contradiction between these two subsystems and to define the regularities as well as the deviations. Authors present the essential steps that were used. Conducted by the method of linear regression this research shows a significant negative correlation between ecological and economic subsystem indicators, whereas its value R{sup 2} 0.58 proves the expected contradiction that exists between the two previously mentioned subsystems. By observing the sustainable development as a two-dimensional system that includes ecological and economic indicators, the authors suggest the methodology to modelling the relationship between economic and ecological development as an orthogonal distance between the degree of the current state measured by the relation between economic and ecological indicators of sustainable development and the degree which was obtained in a traditional way. The method used in this research proved to be extremely suitable for modelling the relationship between ecological and economic subsystems of sustainable development. This research was conducted on a repeated sample of countries of South East Europe by including the data for France and Germany, being two countries on the highest level of development in the European Union. (author)

20. Whole-genome regression and prediction methods applied to plant and animal breeding

NARCIS (Netherlands)

Los Campos, De G.; Hickey, J.M.; Pong-Wong, R.; Daetwyler, H.D.; Calus, M.P.L.

2013-01-01

Genomic-enabled prediction is becoming increasingly important in animal and plant breeding, and is also receiving attention in human genetics. Deriving accurate predictions of complex traits requires implementing whole-genome regression (WGR) models where phenotypes are regressed on thousands of

1. Modelling infant mortality rate in Central Java, Indonesia use generalized poisson regression method

Science.gov (United States)

Prahutama, Alan; Sudarno

2018-05-01

The infant mortality rate is the number of deaths under one year of age occurring among the live births in a given geographical area during a given year, per 1,000 live births occurring among the population of the given geographical area during the same year. This problem needs to be addressed because it is an important element of a country’s economic development. High infant mortality rate will disrupt the stability of a country as it relates to the sustainability of the population in the country. One of regression model that can be used to analyze the relationship between dependent variable Y in the form of discrete data and independent variable X is Poisson regression model. Recently The regression modeling used for data with dependent variable is discrete, among others, poisson regression, negative binomial regression and generalized poisson regression. In this research, generalized poisson regression modeling gives better AIC value than poisson regression. The most significant variable is the Number of health facilities (X1), while the variable that gives the most influence to infant mortality rate is the average breastfeeding (X9).

2. Selecting minimum dataset soil variables using PLSR as a regressive multivariate method

Science.gov (United States)

Stellacci, Anna Maria; Armenise, Elena; Castellini, Mirko; Rossi, Roberta; Vitti, Carolina; Leogrande, Rita; De Benedetto, Daniela; Ferrara, Rossana M.; Vivaldi, Gaetano A.

2017-04-01

Long-term field experiments and science-based tools that characterize soil status (namely the soil quality indices, SQIs) assume a strategic role in assessing the effect of agronomic techniques and thus in improving soil management especially in marginal environments. Selecting key soil variables able to best represent soil status is a critical step for the calculation of SQIs. Current studies show the effectiveness of statistical methods for variable selection to extract relevant information deriving from multivariate datasets. Principal component analysis (PCA) has been mainly used, however supervised multivariate methods and regressive techniques are progressively being evaluated (Armenise et al., 2013; de Paul Obade et al., 2016; Pulido Moncada et al., 2014). The present study explores the effectiveness of partial least square regression (PLSR) in selecting critical soil variables, using a dataset comparing conventional tillage and sod-seeding on durum wheat. The results were compared to those obtained using PCA and stepwise discriminant analysis (SDA). The soil data derived from a long-term field experiment in Southern Italy. On samples collected in April 2015, the following set of variables was quantified: (i) chemical: total organic carbon and nitrogen (TOC and TN), alkali-extractable C (TEC and humic substances - HA-FA), water extractable N and organic C (WEN and WEOC), Olsen extractable P, exchangeable cations, pH and EC; (ii) physical: texture, dry bulk density (BD), macroporosity (Pmac), air capacity (AC), and relative field capacity (RFC); (iii) biological: carbon of the microbial biomass quantified with the fumigation-extraction method. PCA and SDA were previously applied to the multivariate dataset (Stellacci et al., 2016). PLSR was carried out on mean centered and variance scaled data of predictors (soil variables) and response (wheat yield) variables using the PLS procedure of SAS/STAT. In addition, variable importance for projection (VIP

3. EPMLR: sequence-based linear B-cell epitope prediction method using multiple linear regression.

Science.gov (United States)

Lian, Yao; Ge, Meng; Pan, Xian-Ming

2014-12-19

B-cell epitopes have been studied extensively due to their immunological applications, such as peptide-based vaccine development, antibody production, and disease diagnosis and therapy. Despite several decades of research, the accurate prediction of linear B-cell epitopes has remained a challenging task. In this work, based on the antigen's primary sequence information, a novel linear B-cell epitope prediction model was developed using the multiple linear regression (MLR). A 10-fold cross-validation test on a large non-redundant dataset was performed to evaluate the performance of our model. To alleviate the problem caused by the noise of negative dataset, 300 experiments utilizing 300 sub-datasets were performed. We achieved overall sensitivity of 81.8%, precision of 64.1% and area under the receiver operating characteristic curve (AUC) of 0.728. We have presented a reliable method for the identification of linear B cell epitope using antigen's primary sequence information. Moreover, a web server EPMLR has been developed for linear B-cell epitope prediction: http://www.bioinfo.tsinghua.edu.cn/epitope/EPMLR/ .

4. Comparison the Students Satisfaction of Traditional and Integrated Teaching Method in Physiology Course

Directory of Open Access Journals (Sweden)

Keshavarzi Z.

2016-02-01

Full Text Available Aims: Different education methods play crucial roles to improve education quality and students’ satisfaction. In the recent years, medical education highly changes through new education methods. The aim of this study was to compare medical students’ satisfaction in traditional and integrated methods of teaching physiology course. Instrument and Methods: In the descriptive analysis study, fifty 4th semester medical students of Bojnourd University of Medical Sciences were studied in 2015. The subjects were randomly selected based on availability. Data was collected by two researcher-made questionnaires; their validity and reliability were confirmed. Questionnaure 1 was completed by the students after presenting renal and endocrinology topics via traditional and integrated methods. Questionnaire 2 was only completed by the students after presenting the course via integrated method. Data was analyzed by SPSS 16 software using dependent T test. Findings: Mean score of the students’ satisfaction in traditional method (24.80±3.48 was higher than integrated method (22.30±4.03; p<0.0001. In the integrated method, most of the students were agreed and completely agreed on telling stories from daily life (76%, sitting mode in the classroom (48%, an attribution of cell roles to the students (60%, showing movies and animations (76%, using models (84%, and using real animal parts (72% during teaching, as well as expressing clinical items to enhance learning motivations (76%. Conclusion: Favorable satisfaction of the students in traditional lecture method to understand the issues, as well as their acceptance of new and active methods of learning, show effectiveness and efficiency of traditional method and the requirement of its enhancement by the integrated methods

5. Analysis of Conflict Centers in Projects Procured with Traditional and Integrated Methods in Nigeria

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2012-07-01

6. Comparison of Traditional Design Nonlinear Programming Optimization and Stochastic Methods for Structural Design

Science.gov (United States)

Patnaik, Surya N.; Pai, Shantaram S.; Coroneos, Rula M.

2010-01-01

Structural design generated by traditional method, optimization method and the stochastic design concept are compared. In the traditional method, the constraints are manipulated to obtain the design and weight is back calculated. In design optimization, the weight of a structure becomes the merit function with constraints imposed on failure modes and an optimization algorithm is used to generate the solution. Stochastic design concept accounts for uncertainties in loads, material properties, and other parameters and solution is obtained by solving a design optimization problem for a specified reliability. Acceptable solutions were produced by all the three methods. The variation in the weight calculated by the methods was modest. Some variation was noticed in designs calculated by the methods. The variation may be attributed to structural indeterminacy. It is prudent to develop design by all three methods prior to its fabrication. The traditional design method can be improved when the simplified sensitivities of the behavior constraint is used. Such sensitivity can reduce design calculations and may have a potential to unify the traditional and optimization methods. Weight versus reliabilitytraced out an inverted-S-shaped graph. The center of the graph corresponded to mean valued design. A heavy design with weight approaching infinity could be produced for a near-zero rate of failure. Weight can be reduced to a small value for a most failure-prone design. Probabilistic modeling of load and material properties remained a challenge.

7. Developing Employability Skills in Information System Graduates: Traditional vs. Innovative Teaching Methods

Science.gov (United States)

Osmani, Mohamad; Hindi, Nitham M.; Weerakkody, Vishanth

2018-01-01

It is widely acknowledged that traditional teaching methods such as lectures, textbooks and case study techniques on their own are not adequate to improving the most in-demand employability skills for graduates. The aim of this article is to explore the potential impact that novel learning and teaching methods can have on improving the…

8. Deep learning versus traditional machine learning methods for aggregated energy demand prediction

NARCIS (Netherlands)

Paterakis, N.G.; Mocanu, E.; Gibescu, M.; Stappers, B.; van Alst, W.

2018-01-01

In this paper the more advanced, in comparison with traditional machine learning approaches, deep learning methods are explored with the purpose of accurately predicting the aggregated energy consumption. Despite the fact that a wide range of machine learning methods have been applied to

9. Computer game-based and traditional learning method: a comparison regarding students’ knowledge retention

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Rondon Silmara

2013-02-01

10. Research on the localization method of protecting traditional village landscape: a case study on Tangyin

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W. Li

2015-08-01

Full Text Available China has over 271 million villages and less than the number in ten years ago in which there are 363 million villages. New rural construction indeed do some good for common villages but still destroy hundreds and thousands traditional village which contain great cultural, science, artistic values. In addition, traditional villages can't meet the increasing needs in more convenient and comfortable living conditions. Increasing population also makes traditional villages out of control in construction. With the background of this, we have to set up in traditional village protection. This article put forward an idea in protection which make use of landscape localization to pursue the sustainable development and vernacular landscape protection. Tangyin Town is a famous trade center in history and left many cultural heritage, especially historical buildings. Take Tangyin as a case study to apply the localization method which could guide other similar villages to achieve same goals.

11. Steganalysis using logistic regression

Science.gov (United States)

Lubenko, Ivans; Ker, Andrew D.

2011-02-01

We advocate Logistic Regression (LR) as an alternative to the Support Vector Machine (SVM) classifiers commonly used in steganalysis. LR offers more information than traditional SVM methods - it estimates class probabilities as well as providing a simple classification - and can be adapted more easily and efficiently for multiclass problems. Like SVM, LR can be kernelised for nonlinear classification, and it shows comparable classification accuracy to SVM methods. This work is a case study, comparing accuracy and speed of SVM and LR classifiers in detection of LSB Matching and other related spatial-domain image steganography, through the state-of-art 686-dimensional SPAM feature set, in three image sets.

12. Functional regression method for whole genome eQTL epistasis analysis with sequencing data.

Science.gov (United States)

Xu, Kelin; Jin, Li; Xiong, Momiao

2017-05-18

Epistasis plays an essential rule in understanding the regulation mechanisms and is an essential component of the genetic architecture of the gene expressions. However, interaction analysis of gene expressions remains fundamentally unexplored due to great computational challenges and data availability. Due to variation in splicing, transcription start sites, polyadenylation sites, post-transcriptional RNA editing across the entire gene, and transcription rates of the cells, RNA-seq measurements generate large expression variability and collectively create the observed position level read count curves. A single number for measuring gene expression which is widely used for microarray measured gene expression analysis is highly unlikely to sufficiently account for large expression variation across the gene. Simultaneously analyzing epistatic architecture using the RNA-seq and whole genome sequencing (WGS) data poses enormous challenges. We develop a nonlinear functional regression model (FRGM) with functional responses where the position-level read counts within a gene are taken as a function of genomic position, and functional predictors where genotype profiles are viewed as a function of genomic position, for epistasis analysis with RNA-seq data. Instead of testing the interaction of all possible pair-wises SNPs, the FRGM takes a gene as a basic unit for epistasis analysis, which tests for the interaction of all possible pairs of genes and use all the information that can be accessed to collectively test interaction between all possible pairs of SNPs within two genome regions. By large-scale simulations, we demonstrate that the proposed FRGM for epistasis analysis can achieve the correct type 1 error and has higher power to detect the interactions between genes than the existing methods. The proposed methods are applied to the RNA-seq and WGS data from the 1000 Genome Project. The numbers of pairs of significantly interacting genes after Bonferroni correction

13. Computer game-based and traditional learning method: a comparison regarding students' knowledge retention.

Science.gov (United States)

Rondon, Silmara; Sassi, Fernanda Chiarion; Furquim de Andrade, Claudia Regina

2013-02-25

14. A SOCIOLOGICAL ANALYSIS OF THE CHILDBEARING COEFFICIENT IN THE ALTAI REGION BASED ON METHOD OF FUZZY LINEAR REGRESSION

Directory of Open Access Journals (Sweden)

2017-06-01

Full Text Available Purpose. Construction of a mathematical model of the dynamics of childbearing change in the Altai region in 2000–2016, analysis of the dynamics of changes in birth rates for multiple age categories of women of childbearing age. Methodology. A auxiliary analysis element is the construction of linear mathematical models of the dynamics of childbearing by using fuzzy linear regression method based on fuzzy numbers. Fuzzy linear regression is considered as an alternative to standard statistical linear regression for short time series and unknown distribution law. The parameters of fuzzy linear and standard statistical regressions for childbearing time series were defined with using the built in language MatLab algorithm. Method of fuzzy linear regression is not used in sociological researches yet. Results. There are made the conclusions about the socio-demographic changes in society, the high efficiency of the demographic policy of the leadership of the region and the country, and the applicability of the method of fuzzy linear regression for sociological analysis.

15. Reasons for using traditional methods and role of nurses in family planning.

Science.gov (United States)

Yurdakul, Mine; Vural, Gülsen

2002-05-01

The withdrawal method and other traditional methods of contraception are still used in Turkey. Ninety-eight percent of women in Turkey know about modern family planning methods and where to find contraceptives. In fact, only one in every three women uses an effective method. The aim of this descriptive and experimental study was to investigate reasons for using traditional methods and the role of nurses in family planning. The women included in the sample were visited in their homes by nurses and educated for family planning in four sessions. Overall, 53.3% of women were using an effective method. However, 54.3% of women living in the Sirintepe district and 41.6% of women living in the Yenikent district were still using the traditional methods they used before. After the education sessions, the most widely used method was found to be intrauterine device (22.8%) in Sirintepe and condom (25%) in Yenikent. There was a significant difference in family planning methods between these two districts (p < 0.001).

16. Use of traditional and modern contraceptives among childbearing women: findings from a mixed methods study in two southwestern Nigerian states.

Science.gov (United States)

2018-05-09

Contraceptive use has numerous health benefits such as preventing unplanned pregnancies, ensuring optimum spacing between births, reducing maternal and child mortality, and improving the lives of women and children in general. This study examines the level of contraceptive use, its determinants, reasons for non-use of contraception among women in the reproductive age group (18-49 years) in two southwestern Nigerian states. The study adopted an interviewer-administered questionnaire to collect data from 809 participants selected using a 3-stage cluster random sampling technique. We also conducted 46 in-depth interviews. In order to investigate the association between the socio-demographic variables and use of contraceptive methods, we estimated the binary logistic regression models. The findings indicated that knowledge of any methods of contraception was almost universal among the participants. The rates of ever use and current use of contraception was 80 and 66.6%, respectively. However, only 43.9% of the participants had ever used any modern contraceptive methods, considered to be more reliable. The fear of side effects of modern contraceptive methods drove women to rely on less effective traditional methods (withdrawal and rhythm methods). Some women employed crude and unproven contraceptive methods to prevent pregnancies. Our findings show that the rate of contraceptive use was high in the study setting. However, many women chose less effective traditional contraceptive methods over more effective modern contraceptive methods due to fear of side effects of the latter. Patient education on the various options of modern contraceptives, their side effects and management would be crucial towards expanding the family planning services in the study setting.

17. Thermoluminescence dating of chinese porcelain using a regression method of saturating exponential in pre-dose technique

International Nuclear Information System (INIS)

Wang Weida; Xia Junding; Zhou Zhixin; Leung, P.L.

2001-01-01

Thermoluminescence (TL) dating using a regression method of saturating exponential in pre-dose technique was described. 23 porcelain samples from past dynasties of China were dated by this method. The results show that the TL ages are in reasonable agreement with archaeological dates within a standard deviation of 27%. Such error can be accepted in porcelain dating

18. [Discussion on ideological concept implied in traditional reinforcing and reducing method of acupuncture].

Science.gov (United States)

Li, Suyun; Zhao, Jingsheng

2017-11-12

The forming and development of traditional reinforcing and reducing method of acupuncture was rooted in traditional culture of China, and was based on the ancients' special understanding of nature, life and diseases, therefore its principle and methods were inevitably influenced by philosophy culture and medicine concept at that time. With deep study on Inner Canon of Huangdi and representative reinforcing and reducing method of acupuncture, the implied ideological concept, including contradiction view and profit-loss view in ancient dialectic, yin-yang balance theory, concept of life flow, monophyletic theory of qi , theory of existence of disease-evil, yin - yang astrology theory, theory of inter-promotion of five elements, were summarized and analyzed. The clarified and systematic understanding on guiding ideology of reinforcing and reducing method of acupuncture could significantly promote the understanding on principle, method, content and manipulation.

19. The analysis of survival data in nephrology: basic concepts and methods of Cox regression

NARCIS (Netherlands)

van Dijk, Paul C.; Jager, Kitty J.; Zwinderman, Aeilko H.; Zoccali, Carmine; Dekker, Friedo W.

2008-01-01

How much does the survival of one group differ from the survival of another group? How do differences in age in these two groups affect such a comparison? To obtain a quantity to compare the survival of different patient groups and to account for confounding effects, a multiple regression technique

20. The determinants of traditional medicine use in Northern Tanzania: a mixed-methods study.

Directory of Open Access Journals (Sweden)

John W Stanifer

Full Text Available Traditional medicines are an important part of healthcare in sub-Saharan Africa, and building successful disease treatment programs that are sensitive to traditional medicine practices will require an understanding of their current use and roles, including from a biomedical perspective. Therefore, we conducted a mixed-method study in Northern Tanzania in order to characterize the extent of and reasons for the use of traditional medicines among the general population so that we can better inform public health efforts in the region.Between December 2013 and June 2014 in Kilimanjaro, Tanzania, we conducted 5 focus group discussions and 27 in-depth interviews of key informants. The data from these sessions were analyzed using an inductive framework method with cultural insider-outsider coding. From these results, we developed a structured survey designed to test different aspects of traditional medicine use and administered it to a random sample of 655 adults from the community. The results were triangulated to explore converging and diverging themes.Most structured survey participants (68% reported knowing someone who frequently used traditional medicines, and the majority (56% reported using them themselves in the previous year. The most common uses were for symptomatic ailments (42%, chronic diseases (15%, reproductive problems (11%, and malaria/febrile illnesses (11%. We identified five major determinants for traditional medicine use in Northern Tanzania: biomedical healthcare delivery, credibility of traditional practices, strong cultural identities, individual health status, and disease understanding.In order to better formulate effective local disease management programs that are sensitive to TM practices, we described the determinants of TM use. Additionally, we found TM use to be high in Northern Tanzania and that its use is not limited to lower-income areas or rural settings. After symptomatic ailments, chronic diseases were reported as

1. How often do patients in primary care use the methods of traditional medicine

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Petrov-Kiurski Miloranka

2014-01-01

Full Text Available Introduction: Traditional medicine is a comprehensive system of theory and practice, implemented in the prevention, diagnostics and treatment of diseases, which utilizes preparations of vegetable, animal and mineral origin, as well as methods of spiritual therapy Objective: 1. To estimate how many patients in primary care use traditional medicine for diagnostics, treatment and prevention of diseases, and to establish possible differences regarding gender, age and urban or rural location. 2. What methods of traditional medicine are the most often used, and for which diseases and conditions? 3. Why did the subjects opted for this type of treatment, and what was the effect of the therapy? Method: Multicentric research based on interviewing patients in five outpatient health centers in Serbia. As a survey instrument was used a questionnaire with 10 questions. Results: The study included 1157 subjects, 683 women and 474 men, mean age 60.22±14.54, The traditional medicine was used by 83.66% (79.96% males and 86.245% females. Information about the methods of traditional medicine subjects usually received from their friends and acquaintances (54.9% and the media (39.3%. There is no significant difference in the way of obtaining information in relation to gender. Information on the internet was obtained more often in subjects younger than 65 (p=0.000 and in urban population (p=0.000. The same is true for information obtained from doctor or pharmacist (p=0.003. They opted for this method because in their opinion it is less harmful and have less adverse effects (72.8%. This type of treatment patients used for treatment of muscles, bone and joint diseases - 28.5%, diseases of the heart and blood vessels -21,1 %, and for the treatment of pain 19.7%. Patients from rural areas more often used traditional medicine for treatment of cardiovascular diseases (p=0.000. Outcome of treatment was good or satisfactory in 45.3%, moderate in 32%, and in 15.8% effect was

2. Subset selection in regression

CERN Document Server

Miller, Alan

2002-01-01

Originally published in 1990, the first edition of Subset Selection in Regression filled a significant gap in the literature, and its critical and popular success has continued for more than a decade. Thoroughly revised to reflect progress in theory, methods, and computing power, the second edition promises to continue that tradition. The author has thoroughly updated each chapter, incorporated new material on recent developments, and included more examples and references. New in the Second Edition:A separate chapter on Bayesian methodsComplete revision of the chapter on estimationA major example from the field of near infrared spectroscopyMore emphasis on cross-validationGreater focus on bootstrappingStochastic algorithms for finding good subsets from large numbers of predictors when an exhaustive search is not feasible Software available on the Internet for implementing many of the algorithms presentedMore examplesSubset Selection in Regression, Second Edition remains dedicated to the techniques for fitting...

3. Teaching-learning: stereoscopic 3D versus Traditional methods in Mexico City.

Science.gov (United States)

Mendoza Oropeza, Laura; Ortiz Sánchez, Ricardo; Ojeda Villagómez, Raúl

2015-01-01

4. Intravenous catheter training system: computer-based education versus traditional learning methods.

Science.gov (United States)

Engum, Scott A; Jeffries, Pamela; Fisher, Lisa

2003-07-01

Virtual reality simulators allow trainees to practice techniques without consequences, reduce potential risk associated with training, minimize animal use, and help to develop standards and optimize procedures. Current intravenous (IV) catheter placement training methods utilize plastic arms, however, the lack of variability can diminish the educational stimulus for the student. This study compares the effectiveness of an interactive, multimedia, virtual reality computer IV catheter simulator with a traditional laboratory experience of teaching IV venipuncture skills to both nursing and medical students. A randomized, pretest-posttest experimental design was employed. A total of 163 participants, 70 baccalaureate nursing students and 93 third-year medical students beginning their fundamental skills training were recruited. The students ranged in age from 20 to 55 years (mean 25). Fifty-eight percent were female and 68% percent perceived themselves as having average computer skills (25% declaring excellence). The methods of IV catheter education compared included a traditional method of instruction involving a scripted self-study module which involved a 10-minute videotape, instructor demonstration, and hands-on-experience using plastic mannequin arms. The second method involved an interactive multimedia, commercially made computer catheter simulator program utilizing virtual reality (CathSim). The pretest scores were similar between the computer and the traditional laboratory group. There was a significant improvement in cognitive gains, student satisfaction, and documentation of the procedure with the traditional laboratory group compared with the computer catheter simulator group. Both groups were similar in their ability to demonstrate the skill correctly. CONCLUSIONS; This evaluation and assessment was an initial effort to assess new teaching methodologies related to intravenous catheter placement and their effects on student learning outcomes and behaviors

5. The Efficacy of the clay meat ball as a method of traditional meat ...

African Journals Online (AJOL)

Keywords: meat ball, protein, mineral content. This work was carried out to determine the effectiveness of the use of clay meat balls (an African traditional method of preserving meat) in extending the shelf life of meat over a period of months against microbial (bacterial and fungal) spoilage and contamination without ...

6. A Comparison of Traditional Worksheet and Linear Programming Methods for Teaching Manure Application Planning.

Science.gov (United States)

Schmitt, M. A.; And Others

1994-01-01

Compares traditional manure application planning techniques calculated to meet agronomic nutrient needs on a field-by-field basis with plans developed using computer-assisted linear programming optimization methods. Linear programming provided the most economical and environmentally sound manure application strategy. (Contains 15 references.) (MDH)

7. Enhancing Learning Using 3D Printing: An Alternative to Traditional Student Project Methods

Science.gov (United States)

McGahern, Patricia; Bosch, Frances; Poli, DorothyBelle

2015-01-01

Student engagement during the development of a three-dimensional visual aid or teaching model can vary for a number of reasons. Some students report that they are not "creative" or "good at art," often as an excuse to justify less professional outcomes. Student engagement can be low when using traditional methods to produce a…

8. Spatial Visualization Learning in Engineering: Traditional Methods vs. a Web-Based Tool

Science.gov (United States)

Pedrosa, Carlos Melgosa; Barbero, Basilio Ramos; Miguel, Arturo Román

2014-01-01

This study compares an interactive learning manager for graphic engineering to develop spatial vision (ILMAGE_SV) to traditional methods. ILMAGE_SV is an asynchronous web-based learning tool that allows the manipulation of objects with a 3D viewer, self-evaluation, and continuous assessment. In addition, student learning may be monitored, which…

9. An Aural Learning Project: Assimilating Jazz Education Methods for Traditional Applied Pedagogy

Science.gov (United States)

Gamso, Nancy M.

2011-01-01

The Aural Learning Project (ALP) was developed to incorporate jazz method components into the author's classical practice and her applied woodwind lesson curriculum. The primary objective was to place a more focused pedagogical emphasis on listening and hearing than is traditionally used in the classical applied curriculum. The components of the…

10. Radioligand assays - methods and applications. IV. Uniform regression of hyperbolic and linear radioimmunoassay calibration curves

Energy Technology Data Exchange (ETDEWEB)

Keilacker, H; Becker, G; Ziegler, M; Gottschling, H D [Zentralinstitut fuer Diabetes, Karlsburg (German Democratic Republic)

1980-10-01

In order to handle all types of radioimmunoassay (RIA) calibration curves obtained in the authors' laboratory in the same way, they tried to find a non-linear expression for their regression which allows calibration curves with different degrees of curvature to be fitted. Considering the two boundary cases of the incubation protocol they derived a hyperbolic inverse regression function: x = a/sub 1/y + a/sub 0/ + asub(-1)y/sup -1/, where x is the total concentration of antigen, asub(i) are constants, and y is the specifically bound radioactivity. An RIA evaluation procedure based on this function is described providing a fitted inverse RIA calibration curve and some statistical quality parameters. The latter are of an order which is normal for RIA systems. There is an excellent agreement between fitted and experimentally obtained calibration curves having a different degree of curvature.

11. Identification of the traditional methods of newborn mothers regarding jaundice in Turkey.

Science.gov (United States)

Aydin, Diler; Karaca Ciftci, Esra; Karatas, Hulya

2014-02-01

To detect traditional methods applied for the treatment of newborn jaundice by mothers in Turkey. Traditional methods are generally used in our society. Instead of using medical services, people often use already-known traditional methods to treat the disease. In such cases, the prognosis of the disease generally becomes worse, the treatment period longer and healthcare costs higher, and more medicine is used. A cross-sectional descriptive study. The participants of this study were 229 mothers with newborn babies aged 0-28 days in one university hospital and one public children's hospital in Sanliurfa. The study was conducted between March and May 2012. In this research, the Beliefs and Traditional Methods of Mothers for Jaundice Questionnaire, which was formed by searching the relevant literature, is used as a data collection tool. The data are evaluated by percentage distributions. Mothers apply conventional practices in cases of health problems such as jaundice, and application of these methods is important to mothers. Moreover, mothers reported applying hazardous conventional methods in cases of neonatal jaundice, such as cutting the area between the baby's eyebrows with a blade, cutting the back of the ear and the body and burning the body, which are not applied in different cultures. Education regarding the effects of conventional methods being applied in families should be provided, and the results of this study should serve to guide further studies in assessing the effects of such education. This approach can support beneficial practices involving individual care and prevent the negative health effects of hazardous practices. © 2013 John Wiley & Sons Ltd.

12. Predicting Charging Time of Battery Electric Vehicles Based on Regression and Time-Series Methods: A Case Study of Beijing

Directory of Open Access Journals (Sweden)

Jun Bi

2018-04-01

Full Text Available Battery electric vehicles (BEVs reduce energy consumption and air pollution as compared with conventional vehicles. However, the limited driving range and potential long charging time of BEVs create new problems. Accurate charging time prediction of BEVs helps drivers determine travel plans and alleviate their range anxiety during trips. This study proposed a combined model for charging time prediction based on regression and time-series methods according to the actual data from BEVs operating in Beijing, China. After data analysis, a regression model was established by considering the charged amount for charging time prediction. Furthermore, a time-series method was adopted to calibrate the regression model, which significantly improved the fitting accuracy of the model. The parameters of the model were determined by using the actual data. Verification results confirmed the accuracy of the model and showed that the model errors were small. The proposed model can accurately depict the charging time characteristics of BEVs in Beijing.

13. Comparison of traditional and interactive teaching methods in a UK emergency department.

Science.gov (United States)

Armstrong, Peter; Elliott, Tim; Ronald, Julie; Paterson, Brodie

2009-12-01

Didactic teaching remains a core component of undergraduate education, but developing computer assisted learning (CAL) packages may provide useful alternatives. We compared the effectiveness of interactive multimedia-based tutorials with traditional, lecture-based models for teaching arterial blood gas interpretation to fourth year medical students. Participants were randomized to complete a tutorial in either lecture or multimedia format containing identical content. Upon completion, students answered five multiple choice questions assessing post-tutorial knowledge, and provided feedback on their allocated learning method. Marks revealed no significant difference between either group. All lecture candidates rated their teaching as good, compared with 89% of the CAL group. All CAL users found multiple choice questions assessment useful, compared with 83% of lecture participants. Both groups highlighted the importance of interaction. CAL complements other teaching methods, but should be seen as an adjunct to, rather than a replacement for, traditional methods, thus offering students a blended learning environment.

14. Identification of some Fusarium species from selected crop seeds using traditional method and BIO-PCR

Directory of Open Access Journals (Sweden)

Tomasz Kulik

2012-12-01

Full Text Available We identified a species level of the fungal cultures isolated from selected crop seeds using traditional method and BIO-PCR. The use of BIO-PCR did not correspond completely to the morphological analyses. Both methods showed increased infection with F. poae in winter wheat seed sample originated from north Poland. Fungal culture No 40 (isolated from faba bean and identified with traditional method as mixed culture with F. culmorum and F. graminearum did not produce expected product after PCR reaction with species specific primers OPT18F470, OPT18R470. However, the use of additional primers Fc01F, Fc01R allowed for reliable identification of F. culmorum in the culture.

15. A Composite Model of Wound Segmentation Based on Traditional Methods and Deep Neural Networks

Directory of Open Access Journals (Sweden)

Fangzhao Li

2018-01-01

Full Text Available Wound segmentation plays an important supporting role in the wound observation and wound healing. Current methods of image segmentation include those based on traditional process of image and those based on deep neural networks. The traditional methods use the artificial image features to complete the task without large amounts of labeled data. Meanwhile, the methods based on deep neural networks can extract the image features effectively without the artificial design, but lots of training data are required. Combined with the advantages of them, this paper presents a composite model of wound segmentation. The model uses the skin with wound detection algorithm we designed in the paper to highlight image features. Then, the preprocessed images are segmented by deep neural networks. And semantic corrections are applied to the segmentation results at last. The model shows a good performance in our experiment.

16. Performance and separation occurrence of binary probit regression estimator using maximum likelihood method and Firths approach under different sample size

Science.gov (United States)

Lusiana, Evellin Dewi

2017-12-01

The parameters of binary probit regression model are commonly estimated by using Maximum Likelihood Estimation (MLE) method. However, MLE method has limitation if the binary data contains separation. Separation is the condition where there are one or several independent variables that exactly grouped the categories in binary response. It will result the estimators of MLE method become non-convergent, so that they cannot be used in modeling. One of the effort to resolve the separation is using Firths approach instead. This research has two aims. First, to identify the chance of separation occurrence in binary probit regression model between MLE method and Firths approach. Second, to compare the performance of binary probit regression model estimator that obtained by MLE method and Firths approach using RMSE criteria. Those are performed using simulation method and under different sample size. The results showed that the chance of separation occurrence in MLE method for small sample size is higher than Firths approach. On the other hand, for larger sample size, the probability decreased and relatively identic between MLE method and Firths approach. Meanwhile, Firths estimators have smaller RMSE than MLEs especially for smaller sample sizes. But for larger sample sizes, the RMSEs are not much different. It means that Firths estimators outperformed MLE estimator.

17. Regression to fuzziness method for estimation of remaining useful life in power plant components

Science.gov (United States)

Alamaniotis, Miltiadis; Grelle, Austin; Tsoukalas, Lefteri H.

2014-10-01

Mitigation of severe accidents in power plants requires the reliable operation of all systems and the on-time replacement of mechanical components. Therefore, the continuous surveillance of power systems is a crucial concern for the overall safety, cost control, and on-time maintenance of a power plant. In this paper a methodology called regression to fuzziness is presented that estimates the remaining useful life (RUL) of power plant components. The RUL is defined as the difference between the time that a measurement was taken and the estimated failure time of that component. The methodology aims to compensate for a potential lack of historical data by modeling an expert's operational experience and expertise applied to the system. It initially identifies critical degradation parameters and their associated value range. Once completed, the operator's experience is modeled through fuzzy sets which span the entire parameter range. This model is then synergistically used with linear regression and a component's failure point to estimate the RUL. The proposed methodology is tested on estimating the RUL of a turbine (the basic electrical generating component of a power plant) in three different cases. Results demonstrate the benefits of the methodology for components for which operational data is not readily available and emphasize the significance of the selection of fuzzy sets and the effect of knowledge representation on the predicted output. To verify the effectiveness of the methodology, it was benchmarked against the data-based simple linear regression model used for predictions which was shown to perform equal or worse than the presented methodology. Furthermore, methodology comparison highlighted the improvement in estimation offered by the adoption of appropriate of fuzzy sets for parameter representation.

18. Prevalence and Determinants of Preterm Birth in Tehran, Iran: A Comparison between Logistic Regression and Decision Tree Methods.

Science.gov (United States)

Amini, Payam; Maroufizadeh, Saman; Samani, Reza Omani; Hamidi, Omid; Sepidarkish, Mahdi

2017-06-01

Preterm birth (PTB) is a leading cause of neonatal death and the second biggest cause of death in children under five years of age. The objective of this study was to determine the prevalence of PTB and its associated factors using logistic regression and decision tree classification methods. This cross-sectional study was conducted on 4,415 pregnant women in Tehran, Iran, from July 6-21, 2015. Data were collected by a researcher-developed questionnaire through interviews with mothers and review of their medical records. To evaluate the accuracy of the logistic regression and decision tree methods, several indices such as sensitivity, specificity, and the area under the curve were used. The PTB rate was 5.5% in this study. The logistic regression outperformed the decision tree for the classification of PTB based on risk factors. Logistic regression showed that multiple pregnancies, mothers with preeclampsia, and those who conceived with assisted reproductive technology had an increased risk for PTB ( p logistic regression model for the classification of risk groups for PTB.

19. Methods for significance testing of categorical covariates in logistic regression models after multiple imputation: power and applicability analysis

NARCIS (Netherlands)

Eekhout, I.; Wiel, M.A. van de; Heymans, M.W.

2017-01-01

Background. Multiple imputation is a recommended method to handle missing data. For significance testing after multiple imputation, Rubin’s Rules (RR) are easily applied to pool parameter estimates. In a logistic regression model, to consider whether a categorical covariate with more than two levels

20. Determination of benzo(apyrene content in PM10 using regression methods

Directory of Open Access Journals (Sweden)

Jacek Gębicki

2015-12-01

Full Text Available The paper presents an attempt of application of multidimensional linear regression to estimation of an empirical model describing the factors influencing on B(aP content in suspended dust PM10 in Olsztyn and Elbląg city regions between 2010 and 2013. During this period annual average concentration of B(aP in PM10 exceeded the admissible level 1.5-3 times. Conducted investigations confirm that the reasons of B(aP concentration increase are low-efficiency individual home heat stations or low-temperature heat sources, which are responsible for so-called low emission during heating period. Dependences between the following quantities were analysed: concentration of PM10 dust in air, air temperature, wind velocity, air humidity. A measure of model fitting to actual B(aP concentration in PM10 was the coefficient of determination of the model. Application of multidimensional linear regression yielded the equations characterized by high values of the coefficient of determination of the model, especially during heating season. This parameter ranged from 0.54 to 0.80 during the analyzed period.

1. A study of machine learning regression methods for major elemental analysis of rocks using laser-induced breakdown spectroscopy

Science.gov (United States)

Boucher, Thomas F.; Ozanne, Marie V.; Carmosino, Marco L.; Dyar, M. Darby; Mahadevan, Sridhar; Breves, Elly A.; Lepore, Kate H.; Clegg, Samuel M.

2015-05-01

The ChemCam instrument on the Mars Curiosity rover is generating thousands of LIBS spectra and bringing interest in this technique to public attention. The key to interpreting Mars or any other types of LIBS data are calibrations that relate laboratory standards to unknowns examined in other settings and enable predictions of chemical composition. Here, LIBS spectral data are analyzed using linear regression methods including partial least squares (PLS-1 and PLS-2), principal component regression (PCR), least absolute shrinkage and selection operator (lasso), elastic net, and linear support vector regression (SVR-Lin). These were compared against results from nonlinear regression methods including kernel principal component regression (K-PCR), polynomial kernel support vector regression (SVR-Py) and k-nearest neighbor (kNN) regression to discern the most effective models for interpreting chemical abundances from LIBS spectra of geological samples. The results were evaluated for 100 samples analyzed with 50 laser pulses at each of five locations averaged together. Wilcoxon signed-rank tests were employed to evaluate the statistical significance of differences among the nine models using their predicted residual sum of squares (PRESS) to make comparisons. For MgO, SiO2, Fe2O3, CaO, and MnO, the sparse models outperform all the others except for linear SVR, while for Na2O, K2O, TiO2, and P2O5, the sparse methods produce inferior results, likely because their emission lines in this energy range have lower transition probabilities. The strong performance of the sparse methods in this study suggests that use of dimensionality-reduction techniques as a preprocessing step may improve the performance of the linear models. Nonlinear methods tend to overfit the data and predict less accurately, while the linear methods proved to be more generalizable with better predictive performance. These results are attributed to the high dimensionality of the data (6144 channels

2. A Trajectory Regression Clustering Technique Combining a Novel Fuzzy C-Means Clustering Algorithm with the Least Squares Method

Directory of Open Access Journals (Sweden)

Xiangbing Zhou

2018-04-01

Full Text Available Rapidly growing GPS (Global Positioning System trajectories hide much valuable information, such as city road planning, urban travel demand, and population migration. In order to mine the hidden information and to capture better clustering results, a trajectory regression clustering method (an unsupervised trajectory clustering method is proposed to reduce local information loss of the trajectory and to avoid getting stuck in the local optimum. Using this method, we first define our new concept of trajectory clustering and construct a novel partitioning (angle-based partitioning method of line segments; second, the Lagrange-based method and Hausdorff-based K-means++ are integrated in fuzzy C-means (FCM clustering, which are used to maintain the stability and the robustness of the clustering process; finally, least squares regression model is employed to achieve regression clustering of the trajectory. In our experiment, the performance and effectiveness of our method is validated against real-world taxi GPS data. When comparing our clustering algorithm with the partition-based clustering algorithms (K-means, K-median, and FCM, our experimental results demonstrate that the presented method is more effective and generates a more reasonable trajectory.

3. Gender preference between traditional and PowerPoint methods of teaching gross anatomy.

Science.gov (United States)

Nuhu, Saleh; Adamu, Lawan Hassan; Buba, Mohammed Alhaji; Garba, Sani Hyedima; Dalori, Babagana Mohammed; Yusuf, Ashiru Hassan

2018-01-01

Teaching and learning process is increasingly metamorphosing from the traditional chalk and talk to the modern dynamism in the information and communication technology. Medical education is no exception to this dynamism more especially in the teaching of gross anatomy, which serves as one of the bases of understanding the human structure. This study was conducted to determine the gender preference of preclinical medical students on the use of traditional (chalk and talk) and PowerPoint presentation in the teaching of gross anatomy. This was cross-sectional and prospective study, which was conducted among preclinical medical students in the University of Maiduguri, Nigeria. Using simple random techniques, a questionnaire was circulated among 280 medical students, where 247 students filled the questionnaire appropriately. The data obtained was analyzed using SPSS version 20 (IBM Corporation, Armonk, NY, USA) to find the method preferred by the students among other things. Majority of the preclinical medical students in the University of Maiduguri preferred PowerPoint method in the teaching of gross anatomy over the conventional methods. The Cronbach alpha value of 0.76 was obtained which is an acceptable level of internal consistency. A statistically significant association was found between gender and preferred method of lecture delivery on the clarity of lecture content where females prefer the conventional method of lecture delivery whereas males prefer the PowerPoint method, On the reproducibility of text and diagram, females prefer PowerPoint method of teaching gross anatomy while males prefer the conventional method of teaching gross anatomy. There are gender preferences with regard to clarity of lecture contents and reproducibility of text and diagram. It was also revealed from this study that majority of the preclinical medical students in the University of Maiduguri prefer PowerPoint presentation over the traditional chalk and talk method in most of the

4. Islamic geometric patterns their historical development and traditional methods of construction

CERN Document Server

Bonner, Jay

2017-01-01

The main focus of this unique book is an in-depth examination of the polygonal technique; the primary method used by master artists of the past in creating Islamic geometric patterns. The author details the design methodology responsible for this all-but-lost art form and presents evidence for its use from the historical record, both of which are vital contributions to the understanding of this ornamental tradition. Additionally, the author examines the historical development of Islamic geometric patterns, the significance of geometric design within the broader context of Islamic ornament as a whole, the formative role that geometry plays throughout the Islamic ornamental arts (including calligraphy, the floral idiom, dome decoration, geometric patterns, and more), and the underexamined question of pattern classification. Featuring over 600 beautiful color images, Islamic Geometric Patterns: Their Historical Development and Traditional Methods of Construction is a valuable addition to the literature of Islam...

5. A method to determine the necessity for global signal regression in resting-state fMRI studies.

Science.gov (United States)

Chen, Gang; Chen, Guangyu; Xie, Chunming; Ward, B Douglas; Li, Wenjun; Antuono, Piero; Li, Shi-Jiang

2012-12-01

In resting-state functional MRI studies, the global signal (operationally defined as the global average of resting-state functional MRI time courses) is often considered a nuisance effect and commonly removed in preprocessing. This global signal regression method can introduce artifacts, such as false anticorrelated resting-state networks in functional connectivity analyses. Therefore, the efficacy of this technique as a correction tool remains questionable. In this article, we establish that the accuracy of the estimated global signal is determined by the level of global noise (i.e., non-neural noise that has a global effect on the resting-state functional MRI signal). When the global noise level is low, the global signal resembles the resting-state functional MRI time courses of the largest cluster, but not those of the global noise. Using real data, we demonstrate that the global signal is strongly correlated with the default mode network components and has biological significance. These results call into question whether or not global signal regression should be applied. We introduce a method to quantify global noise levels. We show that a criteria for global signal regression can be found based on the method. By using the criteria, one can determine whether to include or exclude the global signal regression in minimizing errors in functional connectivity measures. Copyright © 2012 Wiley Periodicals, Inc.

6. Stepwise multiple regression method of greenhouse gas emission modeling in the energy sector in Poland.

Science.gov (United States)

Kolasa-Wiecek, Alicja

2015-04-01

The energy sector in Poland is the source of 81% of greenhouse gas (GHG) emissions. Poland, among other European Union countries, occupies a leading position with regard to coal consumption. Polish energy sector actively participates in efforts to reduce GHG emissions to the atmosphere, through a gradual decrease of the share of coal in the fuel mix and development of renewable energy sources. All evidence which completes the knowledge about issues related to GHG emissions is a valuable source of information. The article presents the results of modeling of GHG emissions which are generated by the energy sector in Poland. For a better understanding of the quantitative relationship between total consumption of primary energy and greenhouse gas emission, multiple stepwise regression model was applied. The modeling results of CO2 emissions demonstrate a high relationship (0.97) with the hard coal consumption variable. Adjustment coefficient of the model to actual data is high and equal to 95%. The backward step regression model, in the case of CH4 emission, indicated the presence of hard coal (0.66), peat and fuel wood (0.34), solid waste fuels, as well as other sources (-0.64) as the most important variables. The adjusted coefficient is suitable and equals R2=0.90. For N2O emission modeling the obtained coefficient of determination is low and equal to 43%. A significant variable influencing the amount of N2O emission is the peat and wood fuel consumption. Copyright © 2015. Published by Elsevier B.V.

7. Efectivity of Additive Spline for Partial Least Square Method in Regression Model Estimation

Directory of Open Access Journals (Sweden)

2005-04-01

Full Text Available Additive Spline of Partial Least Square method (ASPL as one generalization of Partial Least Square (PLS method. ASPLS method can be acommodation to non linear and multicollinearity case of predictor variables. As a principle, The ASPLS method approach is cahracterized by two idea. The first is to used parametric transformations of predictors by spline function; the second is to make ASPLS components mutually uncorrelated, to preserve properties of the linear PLS components. The performance of ASPLS compared with other PLS method is illustrated with the fisher economic application especially the tuna fish production.

8. Product-service system method to measure sustainability level of traditional smoked fish processing industries

OpenAIRE

Purwaningsih Ratna; Cahyantari Anggaina Elfandora; Ariyani Zulfaida; Susanty Aries; Arvianto Ary; Santoso Haryo

2018-01-01

Small Medium Enterprise’s (SME) of traditional fish processing at Semarang, Central Java, Indonesia still focus their business on gain more profits. Sustainability aspect has not received enough attention yet. This study aims to review the sustainability level of SME smoked fish Semarang using product service system (PSS) method. PSS consists of three dimensions (1) Environment, (2) Socio-cultural and (3) Economic. Each dimension consists of 6 criteria's. PSS not only assess the level of sust...

9. Analysis of Conflict Centers in Projects Procured with Traditional and Integrated Methods in Nigeria

OpenAIRE

2012-01-01

Conflicts in any organization can either be functional or dysfunctional and can contribute to or detract from the achievement of organizational or project objectives. This study investigated the frequency and intensity of conflicts, using five conflict centers, on projects executed with either the integrated or traditional method in Nigeria. Questionnaires were administered through purposive and snowballing techniques on 274 projects located in twelve states of Nigeria and Abuja. 94 usable ...

10. Dual Regression

OpenAIRE

2012-01-01

We propose dual regression as an alternative to the quantile regression process for the global estimation of conditional distribution functions under minimal assumptions. Dual regression provides all the interpretational power of the quantile regression process while avoiding the need for repairing the intersecting conditional quantile surfaces that quantile regression often produces in practice. Our approach introduces a mathematical programming characterization of conditional distribution f...

11. Linear regression

CERN Document Server

Olive, David J

2017-01-01

This text covers both multiple linear regression and some experimental design models. The text uses the response plot to visualize the model and to detect outliers, does not assume that the error distribution has a known parametric distribution, develops prediction intervals that work when the error distribution is unknown, suggests bootstrap hypothesis tests that may be useful for inference after variable selection, and develops prediction regions and large sample theory for the multivariate linear regression model that has m response variables. A relationship between multivariate prediction regions and confidence regions provides a simple way to bootstrap confidence regions. These confidence regions often provide a practical method for testing hypotheses. There is also a chapter on generalized linear models and generalized additive models. There are many R functions to produce response and residual plots, to simulate prediction intervals and hypothesis tests, to detect outliers, and to choose response trans...

12. Prediction of protein binding sites using physical and chemical descriptors and the support vector machine regression method

International Nuclear Information System (INIS)

Sun Zhong-Hua; Jiang Fan

2010-01-01

In this paper a new continuous variable called core-ratio is defined to describe the probability for a residue to be in a binding site, thereby replacing the previous binary description of the interface residue using 0 and 1. So we can use the support vector machine regression method to fit the core-ratio value and predict the protein binding sites. We also design a new group of physical and chemical descriptors to characterize the binding sites. The new descriptors are more effective, with an averaging procedure used. Our test shows that much better prediction results can be obtained by the support vector regression (SVR) method than by the support vector classification method. (rapid communication)

13. [Current development of rapid high-throughout determination technology for total components of traditional Chinese medicines and formula and synthetic immunity chip method].

Science.gov (United States)

He, Fu-Yuan; Deng, Kai-Wen; Zeng, Jiao-Li; Dai, Ru-Wen; Dai, Ru-Wen; Xia, Zan-Shao; Liu, Weng-Long; Shi, Ji-Lian

2012-10-01

The qualitative and quantitative analysis on traditional Chinese medicine and formula components can be made by chemical and instrumental analysis methods. Of both, the instrumental analysis methods play a dominant role, including HPLC, HPLC-MS, HPLC-NMR, GC, GC-MS, biochemical and biological effect. But because traditional Chinese medicines and formula have complicated components, chemical methods are so unspecific that they shall be used less or with caution. While instrumental analysis methods are so specific that they are appropriate for analyzing complicated single component. The analysis techniques for multiple components of traditional Chinese medicines and formula focus on fingerprints, but all of these analysis techniques are limited by the pre-requisite of separation and the lack of general-purpose detectors and therefore being hard to realize the determination of all components of traditional Chinese medicines and formula. In the natural world, however, organisms identify native and alien components through specificity and non-specificity of clusters decided by antigens and antibodies. For example, components of traditional Chinese medicines are directly or indirectly synthesized into antigens and injected into animals, in order to generate specific antibodies and then collect cross reaction information of these components to specific antibodies. As for components without cross reaction, their contents shall be directly read out on the basis of the inhibition rate curve of competitive reaction for specificity of antigens and antibodies. Besides, a cross inhibition rate matrix shall be established first, and them a multiple regression linear equation between cross component concentration or concentration logarithm and inhibition rate by labeling the immunity competitive reaction between antibodies and haptens of traditional Chinese medicine and compound components, and then solved to obtain concentration of each component. The two results are combined to

14. Quantitative Research Methods in Chaos and Complexity: From Probability to Post Hoc Regression Analyses

Science.gov (United States)

Gilstrap, Donald L.

2013-01-01

In addition to qualitative methods presented in chaos and complexity theories in educational research, this article addresses quantitative methods that may show potential for future research studies. Although much in the social and behavioral sciences literature has focused on computer simulations, this article explores current chaos and…

15. Acupuncture as a Complementary Method of Traditional Psoriasis Treatment: Myth or Reality?

Science.gov (United States)

Mahović, Darija; Mrsić, Fanika

2016-08-01

16. A new criterion of photostimulated luminescence (PSL) method to detect irradiated traditional Chinese medicinal herbs

International Nuclear Information System (INIS)

Zhang, Liwen; Lin, Tong; Jiang, Yingqiao; Bi, Fujun

2013-01-01

17. Web-based versus traditional lecture: are they equally effective as a flexible bronchoscopy teaching method?

Science.gov (United States)

Mata, Caio Augusto Sterse; Ota, Luiz Hirotoshi; Suzuki, Iunis; Telles, Adriana; Miotto, Andre; Leão, Luiz Eduardo Vilaça

2012-01-01

This study compares the traditional live lecture to a web-based approach in the teaching of bronchoscopy and evaluates the positive and negative aspects of both methods. We developed a web-based bronchoscopy curriculum, which integrates texts, images and animations. It was applied to first-year interns, who were later administered a multiple-choice test. Another group of eight first-year interns received the traditional teaching method and the same test. The two groups were compared using the Student's t-test. The mean scores (± SD) of students who used the website were 14.63 ± 1.41 (range 13-17). The test scores of the other group had the same range, with a mean score of 14.75 ± 1. The Student's t-test showed no difference between the test results. The common positive point noted was the presence of multimedia content. The web group cited as positive the ability to review the pages, and the other one the role of the teacher. Web-based bronchoscopy education showed results similar to the traditional live lecture in effectiveness.

18. Laser-induced Breakdown spectroscopy quantitative analysis method via adaptive analytical line selection and relevance vector machine regression model

International Nuclear Information System (INIS)

Yang, Jianhong; Yi, Cancan; Xu, Jinwu; Ma, Xianghong

2015-01-01

A new LIBS quantitative analysis method based on analytical line adaptive selection and Relevance Vector Machine (RVM) regression model is proposed. First, a scheme of adaptively selecting analytical line is put forward in order to overcome the drawback of high dependency on a priori knowledge. The candidate analytical lines are automatically selected based on the built-in characteristics of spectral lines, such as spectral intensity, wavelength and width at half height. The analytical lines which will be used as input variables of regression model are determined adaptively according to the samples for both training and testing. Second, an LIBS quantitative analysis method based on RVM is presented. The intensities of analytical lines and the elemental concentrations of certified standard samples are used to train the RVM regression model. The predicted elemental concentration analysis results will be given with a form of confidence interval of probabilistic distribution, which is helpful for evaluating the uncertainness contained in the measured spectra. Chromium concentration analysis experiments of 23 certified standard high-alloy steel samples have been carried out. The multiple correlation coefficient of the prediction was up to 98.85%, and the average relative error of the prediction was 4.01%. The experiment results showed that the proposed LIBS quantitative analysis method achieved better prediction accuracy and better modeling robustness compared with the methods based on partial least squares regression, artificial neural network and standard support vector machine. - Highlights: • Both training and testing samples are considered for analytical lines selection. • The analytical lines are auto-selected based on the built-in characteristics of spectral lines. • The new method can achieve better prediction accuracy and modeling robustness. • Model predictions are given with confidence interval of probabilistic distribution

19. Assessing the reliability of the borderline regression method as a standard setting procedure for objective structured clinical examination

Directory of Open Access Journals (Sweden)

Sara Mortaz Hejri

2013-01-01

Full Text Available Background: One of the methods used for standard setting is the borderline regression method (BRM. This study aims to assess the reliability of BRM when the pass-fail standard in an objective structured clinical examination (OSCE was calculated by averaging the BRM standards obtained for each station separately. Materials and Methods: In nine stations of the OSCE with direct observation the examiners gave each student a checklist score and a global score. Using a linear regression model for each station, we calculated the checklist score cut-off on the regression equation for the global scale cut-off set at 2. The OSCE pass-fail standard was defined as the average of all station′s standard. To determine the reliability, the root mean square error (RMSE was calculated. The R2 coefficient and the inter-grade discrimination were calculated to assess the quality of OSCE. Results: The mean total test score was 60.78. The OSCE pass-fail standard and its RMSE were 47.37 and 0.55, respectively. The R2 coefficients ranged from 0.44 to 0.79. The inter-grade discrimination score varied greatly among stations. Conclusion: The RMSE of the standard was very small indicating that BRM is a reliable method of setting standard for OSCE, which has the advantage of providing data for quality assurance.

20. Single-electron multiplication statistics as a combination of Poissonian pulse height distributions using constraint regression methods

International Nuclear Information System (INIS)

Ballini, J.-P.; Cazes, P.; Turpin, P.-Y.

1976-01-01

Analysing the histogram of anode pulse amplitudes allows a discussion of the hypothesis that has been proposed to account for the statistical processes of secondary multiplication in a photomultiplier. In an earlier work, good agreement was obtained between experimental and reconstructed spectra, assuming a first dynode distribution including two Poisson distributions of distinct mean values. This first approximation led to a search for a method which could give the weights of several Poisson distributions of distinct mean values. Three methods have been briefly exposed: classical linear regression, constraint regression (d'Esopo's method), and regression on variables subject to error. The use of these methods gives an approach of the frequency function which represents the dispersion of the punctual mean gain around the whole first dynode mean gain value. Comparison between this function and the one employed in Polya distribution allows the statement that the latter is inadequate to describe the statistical process of secondary multiplication. Numerous spectra obtained with two kinds of photomultiplier working under different physical conditions have been analysed. Then two points are discussed: - Does the frequency function represent the dynode structure and the interdynode collection process. - Is the model (the multiplication process of all dynodes but the first one, is Poissonian) valid whatever the photomultiplier and the utilization conditions. (Auth.)

1. Recursive least squares method of regression coefficients estimation as a special case of Kalman filter

Science.gov (United States)

Borodachev, S. M.

2016-06-01

The simple derivation of recursive least squares (RLS) method equations is given as special case of Kalman filter estimation of a constant system state under changing observation conditions. A numerical example illustrates application of RLS to multicollinearity problem.

2. Auto Regressive Moving Average (ARMA) Modeling Method for Gyro Random Noise Using a Robust Kalman Filter

Science.gov (United States)

Huang, Lei

2015-01-01

To solve the problem in which the conventional ARMA modeling methods for gyro random noise require a large number of samples and converge slowly, an ARMA modeling method using a robust Kalman filtering is developed. The ARMA model parameters are employed as state arguments. Unknown time-varying estimators of observation noise are used to achieve the estimated mean and variance of the observation noise. Using the robust Kalman filtering, the ARMA model parameters are estimated accurately. The developed ARMA modeling method has the advantages of a rapid convergence and high accuracy. Thus, the required sample size is reduced. It can be applied to modeling applications for gyro random noise in which a fast and accurate ARMA modeling method is required. PMID:26437409

3. Quantification methods of Black Carbon: Comparison of Rock-Eval analysis with traditional methods

NARCIS (Netherlands)

Poot, A.; Quik, J.T.K.; Veld, H.; Koelmans, A.A.

2009-01-01

Black Carbon (BC) quantification methods are reviewed, including new Rock-Eval 6 data on BC reference materials. BC has been reported to have major impacts on climate, human health and environmental quality. Especially for risk assessment of persistent organic pollutants (POPs) it is important to

4. Study on the traditional pattern retrieval method of minorities in Gansu province

Science.gov (United States)

Zheng, Gang; Wang, Beizhan; Sun, Yuchun; Xu, Jin

2018-03-01

The traditional patterns of ethnic minorities in gansu province are ethnic arts with strong ethnic characteristics. It is the crystallization of the hard work and wisdom of minority nationalities in gansu province. Unique traditional patterns of ethnic minorities in Gansu province with rich ethnic folk arts, is the crystallization of geographical environment in Gansu minority diligence and wisdom. By using the Surf feature point identification algorithm, the feature point extractor in OpenCV is used to extract the feature points. And the feature points are applied to compare the pattern features to find patterns similar to the artistic features. The application of this method can quickly or efficiently extract pattern information in a database.

5. Soft-tissues Image Processing: Comparison of Traditional Segmentation Methods with 2D active Contour Methods

Czech Academy of Sciences Publication Activity Database

Mikulka, J.; Gescheidtová, E.; Bartušek, Karel

2012-01-01

Roč. 12, č. 4 (2012), s. 153-161 ISSN 1335-8871 R&D Projects: GA ČR GAP102/11/0318; GA ČR GAP102/12/1104; GA MŠk ED0017/01/01 Institutional support: RVO:68081731 Keywords : Medical image processing * image segmentation * liver tumor * temporomandibular joint disc * watershed method Subject RIV: JA - Electronics ; Optoelectronics, Electrical Engineering Impact factor: 1.233, year: 2012

6. Evaluating the Effectiveness of Traditional Training Methods in Non-Traditional Training Programs for Adult Learners through a Pre-Test/Post-Test Comparison of Food Safety Knowledge

Science.gov (United States)

Dodd, Caleb D.; Burris, Scott; Fraze, Steve; Doerfert, David; McCulloch, Abigail

2013-01-01

The incorporation of hot and cold food bars into grocery stores in an effort to capture a portion of the home meal replacement industry is presenting new challenges for retail food establishments. To ensure retail success and customer safety, employees need to be educated in food safety practices. Traditional methods of training are not meeting…

7. Direct and regression methods do not give different estimates of digestible and metabolizable energy of wheat for pigs.

Science.gov (United States)

2012-12-01

Digestible and metabolizable energy contents of feed ingredients for pigs can be determined by direct or indirect methods. There are situations when only the indirect approach is suitable and the regression method is a robust indirect approach. This study was conducted to compare the direct and regression methods for determining the energy value of wheat for pigs. Twenty-four barrows with an average initial BW of 31 kg were assigned to 4 diets in a randomized complete block design. The 4 diets consisted of 969 g wheat/kg plus minerals and vitamins (sole wheat) for the direct method, corn (Zea mays)-soybean (Glycine max) meal reference diet (RD), RD + 300 g wheat/kg, and RD + 600 g wheat/kg. The 3 corn-soybean meal diets were used for the regression method and wheat replaced the energy-yielding ingredients, corn and soybean meal, so that the same ratio of corn and soybean meal across the experimental diets was maintained. The wheat used was analyzed to contain 883 g DM, 15.2 g N, and 3.94 Mcal GE/kg. Each diet was fed to 6 barrows in individual metabolism crates for a 5-d acclimation followed by a 5-d total but separate collection of feces and urine. The DE and ME for the sole wheat diet were 3.83 and 3.77 Mcal/kg DM, respectively. Because the sole wheat diet contained 969 g wheat/kg, these translate to 3.95 Mcal DE/kg DM and 3.89 Mcal ME/kg DM. The RD used for the regression approach yielded 4.00 Mcal DE and 3.91 Mcal ME/kg DM diet. Increasing levels of wheat in the RD linearly reduced (P direct method (3.95 and 3.89 Mcal/kg DM) did not differ (0.78 < P < 0.89) from those obtained using the regression method (3.96 and 3.88 Mcal/kg DM).

8. Multivariate regression methods for estimating velocity of ictal discharges from human microelectrode recordings

Science.gov (United States)

Liou, Jyun-you; Smith, Elliot H.; Bateman, Lisa M.; McKhann, Guy M., II; Goodman, Robert R.; Greger, Bradley; Davis, Tyler S.; Kellis, Spencer S.; House, Paul A.; Schevon, Catherine A.

2017-08-01

Objective. Epileptiform discharges, an electrophysiological hallmark of seizures, can propagate across cortical tissue in a manner similar to traveling waves. Recent work has focused attention on the origination and propagation patterns of these discharges, yielding important clues to their source location and mechanism of travel. However, systematic studies of methods for measuring propagation are lacking. Approach. We analyzed epileptiform discharges in microelectrode array recordings of human seizures. The array records multiunit activity and local field potentials at 400 micron spatial resolution, from a small cortical site free of obstructions. We evaluated several computationally efficient statistical methods for calculating traveling wave velocity, benchmarking them to analyses of associated neuronal burst firing. Main results. Over 90% of discharges met statistical criteria for propagation across the sampled cortical territory. Detection rate, direction and speed estimates derived from a multiunit estimator were compared to four field potential-based estimators: negative peak, maximum descent, high gamma power, and cross-correlation. Interestingly, the methods that were computationally simplest and most efficient (negative peak and maximal descent) offer non-inferior results in predicting neuronal traveling wave velocities compared to the other two, more complex methods. Moreover, the negative peak and maximal descent methods proved to be more robust against reduced spatial sampling challenges. Using least absolute deviation in place of least squares error minimized the impact of outliers, and reduced the discrepancies between local field potential-based and multiunit estimators. Significance. Our findings suggest that ictal epileptiform discharges typically take the form of exceptionally strong, rapidly traveling waves, with propagation detectable across millimeter distances. The sequential activation of neurons in space can be inferred from clinically

9. The effect of non traditional teaching methods in entrepreneurship education on students entrepreneurial interest and business startups: A data article.

Science.gov (United States)

Olokundun, Maxwell; Moses, Chinonye Love; Iyiola, Oluwole; Ibidunni, Stephen; Ogbari, Mercy; Peter, Fred; Borishade, Taiye

2018-08-01

Traditional methods of teaching entrepreneurship in universities involves more theoretical approaches which are less effective in motivating considerations for an entrepreneurship career. This owes to the fact that such techniques essentially make students develop a dormant attitude rather than active participation. Expert views suggest that experiential entrepreneurship teaching methods in universities which involve practical activities and active participation can be considered salient to students' development of entrepreneurial interest an business startup potentials. This present study presents data on the extent to which experiential teaching methods in entrepreneurship adopted by Nigerian universities stimulate students' entrepreneurial interest and business startups. Data have been gathered following a descriptive cross-sectional quantitative survey conducted among university students ( N = 600) of four selected institutions in Nigeria offering a degree programme in entrepreneurship. Hierarchical Multiple Regression Analysis was used in confirming the hypothesis proposed in the study using the Statistical Package for Social Sciences (SPSS) version 22.The findings from the analysis showed that the adoption of experiential practical activities considered as best practices in entrepreneurship teaching in Nigerian universities can stimulate students' interest and drive for engaging in business start-up activities even as undergraduates. The field data set is made extensively available to allow for critical investigation.

10. Power system state estimation using an iteratively reweighted least squares method for sequential L{sub 1}-regression

Energy Technology Data Exchange (ETDEWEB)

Jabr, R.A. [Electrical, Computer and Communication Engineering Department, Notre Dame University, P.O. Box 72, Zouk Mikhael, Zouk Mosbeh (Lebanon)

2006-02-15

This paper presents an implementation of the least absolute value (LAV) power system state estimator based on obtaining a sequence of solutions to the L{sub 1}-regression problem using an iteratively reweighted least squares (IRLS{sub L1}) method. The proposed implementation avoids reformulating the regression problem into standard linear programming (LP) form and consequently does not require the use of common methods of LP, such as those based on the simplex method or interior-point methods. It is shown that the IRLS{sub L1} method is equivalent to solving a sequence of linear weighted least squares (LS) problems. Thus, its implementation presents little additional effort since the sparse LS solver is common to existing LS state estimators. Studies on the termination criteria of the IRLS{sub L1} method have been carried out to determine a procedure for which the proposed estimator is more computationally efficient than a previously proposed non-linear iteratively reweighted least squares (IRLS) estimator. Indeed, it is revealed that the proposed method is a generalization of the previously reported IRLS estimator, but is based on more rigorous theory. (author)

11. A study of machine learning regression methods for major elemental analysis of rocks using laser-induced breakdown spectroscopy

Energy Technology Data Exchange (ETDEWEB)

Boucher, Thomas F., E-mail: boucher@cs.umass.edu [School of Computer Science, University of Massachusetts Amherst, 140 Governor' s Drive, Amherst, MA 01003, United States. (United States); Ozanne, Marie V. [Department of Astronomy, Mount Holyoke College, South Hadley, MA 01075 (United States); Carmosino, Marco L. [School of Computer Science, University of Massachusetts Amherst, 140 Governor' s Drive, Amherst, MA 01003, United States. (United States); Dyar, M. Darby [Department of Astronomy, Mount Holyoke College, South Hadley, MA 01075 (United States); Mahadevan, Sridhar [School of Computer Science, University of Massachusetts Amherst, 140 Governor' s Drive, Amherst, MA 01003, United States. (United States); Breves, Elly A.; Lepore, Kate H. [Department of Astronomy, Mount Holyoke College, South Hadley, MA 01075 (United States); Clegg, Samuel M. [Los Alamos National Laboratory, P.O. Box 1663, MS J565, Los Alamos, NM 87545 (United States)

2015-05-01

The ChemCam instrument on the Mars Curiosity rover is generating thousands of LIBS spectra and bringing interest in this technique to public attention. The key to interpreting Mars or any other types of LIBS data are calibrations that relate laboratory standards to unknowns examined in other settings and enable predictions of chemical composition. Here, LIBS spectral data are analyzed using linear regression methods including partial least squares (PLS-1 and PLS-2), principal component regression (PCR), least absolute shrinkage and selection operator (lasso), elastic net, and linear support vector regression (SVR-Lin). These were compared against results from nonlinear regression methods including kernel principal component regression (K-PCR), polynomial kernel support vector regression (SVR-Py) and k-nearest neighbor (kNN) regression to discern the most effective models for interpreting chemical abundances from LIBS spectra of geological samples. The results were evaluated for 100 samples analyzed with 50 laser pulses at each of five locations averaged together. Wilcoxon signed-rank tests were employed to evaluate the statistical significance of differences among the nine models using their predicted residual sum of squares (PRESS) to make comparisons. For MgO, SiO{sub 2}, Fe{sub 2}O{sub 3}, CaO, and MnO, the sparse models outperform all the others except for linear SVR, while for Na{sub 2}O, K{sub 2}O, TiO{sub 2}, and P{sub 2}O{sub 5}, the sparse methods produce inferior results, likely because their emission lines in this energy range have lower transition probabilities. The strong performance of the sparse methods in this study suggests that use of dimensionality-reduction techniques as a preprocessing step may improve the performance of the linear models. Nonlinear methods tend to overfit the data and predict less accurately, while the linear methods proved to be more generalizable with better predictive performance. These results are attributed to the high

12. A study of machine learning regression methods for major elemental analysis of rocks using laser-induced breakdown spectroscopy

International Nuclear Information System (INIS)

Boucher, Thomas F.; Ozanne, Marie V.; Carmosino, Marco L.; Dyar, M. Darby; Mahadevan, Sridhar; Breves, Elly A.; Lepore, Kate H.; Clegg, Samuel M.

2015-01-01

The ChemCam instrument on the Mars Curiosity rover is generating thousands of LIBS spectra and bringing interest in this technique to public attention. The key to interpreting Mars or any other types of LIBS data are calibrations that relate laboratory standards to unknowns examined in other settings and enable predictions of chemical composition. Here, LIBS spectral data are analyzed using linear regression methods including partial least squares (PLS-1 and PLS-2), principal component regression (PCR), least absolute shrinkage and selection operator (lasso), elastic net, and linear support vector regression (SVR-Lin). These were compared against results from nonlinear regression methods including kernel principal component regression (K-PCR), polynomial kernel support vector regression (SVR-Py) and k-nearest neighbor (kNN) regression to discern the most effective models for interpreting chemical abundances from LIBS spectra of geological samples. The results were evaluated for 100 samples analyzed with 50 laser pulses at each of five locations averaged together. Wilcoxon signed-rank tests were employed to evaluate the statistical significance of differences among the nine models using their predicted residual sum of squares (PRESS) to make comparisons. For MgO, SiO 2 , Fe 2 O 3 , CaO, and MnO, the sparse models outperform all the others except for linear SVR, while for Na 2 O, K 2 O, TiO 2 , and P 2 O 5 , the sparse methods produce inferior results, likely because their emission lines in this energy range have lower transition probabilities. The strong performance of the sparse methods in this study suggests that use of dimensionality-reduction techniques as a preprocessing step may improve the performance of the linear models. Nonlinear methods tend to overfit the data and predict less accurately, while the linear methods proved to be more generalizable with better predictive performance. These results are attributed to the high dimensionality of the data (6144

13. An Improved Method for Sizing Standalone Photovoltaic Systems Using Generalized Regression Neural Network

Directory of Open Access Journals (Sweden)

Tamer Khatib

2014-01-01

Full Text Available In this research an improved approach for sizing standalone PV system (SAPV is presented. This work is an improved work developed previously by the authors. The previous work is based on the analytical method which faced some concerns regarding the difficulty of finding the model’s coefficients. Therefore, the proposed approach in this research is based on a combination of an analytical method and a machine learning approach for a generalized artificial neural network (GRNN. The GRNN assists to predict the optimal size of a PV system using the geographical coordinates of the targeted site instead of using mathematical formulas. Employing the GRNN facilitates the use of a previously developed method by the authors and avoids some of its drawbacks. The approach has been tested using data from five Malaysian sites. According to the results, the proposed method can be efficiently used for SAPV sizing whereas the proposed GRNN based model predicts the sizing curves of the PV system accurately with a prediction error of 0.6%. Moreover, hourly meteorological and load demand data are used in this research in order to consider the uncertainty of the solar energy and the load demand.

14. Comparison of Sparse and Jack-knife partial least squares regression methods for variable selection

DEFF Research Database (Denmark)

Karaman, Ibrahim; Qannari, El Mostafa; Martens, Harald

2013-01-01

The objective of this study was to compare two different techniques of variable selection, Sparse PLSR and Jack-knife PLSR, with respect to their predictive ability and their ability to identify relevant variables. Sparse PLSR is a method that is frequently used in genomics, whereas Jack-knife PL...

15. Using a Linear Regression Method to Detect Outliers in IRT Common Item Equating

Science.gov (United States)

He, Yong; Cui, Zhongmin; Fang, Yu; Chen, Hanwei

2013-01-01

Common test items play an important role in equating alternate test forms under the common item nonequivalent groups design. When the item response theory (IRT) method is applied in equating, inconsistent item parameter estimates among common items can lead to large bias in equated scores. It is prudent to evaluate inconsistency in parameter…

16. A novel adaptive kernel method with kernel centers determined by a support vector regression approach

NARCIS (Netherlands)

Sun, L.G.; De Visser, C.C.; Chu, Q.P.; Mulder, J.A.

2012-01-01

The optimality of the kernel number and kernel centers plays a significant role in determining the approximation power of nearly all kernel methods. However, the process of choosing optimal kernels is always formulated as a global optimization task, which is hard to accomplish. Recently, an

17. Quality evaluation of fish and other seafood by traditional and nondestructive instrumental methods: Advantages and limitations.

Science.gov (United States)

Hassoun, Abdo; Karoui, Romdhane

2017-06-13

Although being one of the most vulnerable and perishable products, fish and other seafoods provide a wide range of health-promoting compounds. Recently, the growing interest of consumers in food quality and safety issues has contributed to the increasing demand for sensitive and rapid analytical technologies. Several traditional physicochemical, textural, sensory, and electrical methods have been used to evaluate freshness and authentication of fish and other seafood products. Despite the importance of these standard methods, they are expensive and time-consuming, and often susceptible to large sources of variation. Recently, spectroscopic methods and other emerging techniques have shown great potential due to speed of analysis, minimal sample preparation, high repeatability, low cost, and, most of all, the fact that these techniques are noninvasive and nondestructive and, therefore, could be applied to any online monitoring system. This review describes firstly and briefly the basic principles of multivariate data analysis, followed by the most commonly traditional methods used for the determination of the freshness and authenticity of fish and other seafood products. A special focus is put on the use of rapid and nondestructive techniques (spectroscopic techniques and instrumental sensors) to address several issues related to the quality of these products. Moreover, the advantages and limitations of each technique are reviewed and some perspectives are also given.

18. A novel hybrid method of beta-turn identification in protein using binary logistic regression and neural network.

Science.gov (United States)

Asghari, Mehdi Poursheikhali; Hayatshahi, Sayyed Hamed Sadat; Abdolmaleki, Parviz

2012-01-01

From both the structural and functional points of view, β-turns play important biological roles in proteins. In the present study, a novel two-stage hybrid procedure has been developed to identify β-turns in proteins. Binary logistic regression was initially used for the first time to select significant sequence parameters in identification of β-turns due to a re-substitution test procedure. Sequence parameters were consisted of 80 amino acid positional occurrences and 20 amino acid percentages in sequence. Among these parameters, the most significant ones which were selected by binary logistic regression model, were percentages of Gly, Ser and the occurrence of Asn in position i+2, respectively, in sequence. These significant parameters have the highest effect on the constitution of a β-turn sequence. A neural network model was then constructed and fed by the parameters selected by binary logistic regression to build a hybrid predictor. The networks have been trained and tested on a non-homologous dataset of 565 protein chains. With applying a nine fold cross-validation test on the dataset, the network reached an overall accuracy (Qtotal) of 74, which is comparable with results of the other β-turn prediction methods. In conclusion, this study proves that the parameter selection ability of binary logistic regression together with the prediction capability of neural networks lead to the development of more precise models for identifying β-turns in proteins.

19. Improving ASTER GDEM Accuracy Using Land Use-Based Linear Regression Methods: A Case Study of Lianyungang, East China

Directory of Open Access Journals (Sweden)

Xiaoyan Yang

2018-04-01

Full Text Available The Advanced Spaceborne Thermal-Emission and Reflection Radiometer Global Digital Elevation Model (ASTER GDEM is important to a wide range of geographical and environmental studies. Its accuracy, to some extent associated with land-use types reflecting topography, vegetation coverage, and human activities, impacts the results and conclusions of these studies. In order to improve the accuracy of ASTER GDEM prior to its application, we investigated ASTER GDEM errors based on individual land-use types and proposed two linear regression calibration methods, one considering only land use-specific errors and the other considering the impact of both land-use and topography. Our calibration methods were tested on the coastal prefectural city of Lianyungang in eastern China. Results indicate that (1 ASTER GDEM is highly accurate for rice, wheat, grass and mining lands but less accurate for scenic, garden, wood and bare lands; (2 despite improvements in ASTER GDEM2 accuracy, multiple linear regression calibration requires more data (topography and a relatively complex calibration process; (3 simple linear regression calibration proves a practicable and simplified means to systematically investigate and improve the impact of land-use on ASTER GDEM accuracy. Our method is applicable to areas with detailed land-use data based on highly accurate field-based point-elevation measurements.

20. Neural networks and traditional time series methods: a synergistic combination in state economic forecasts.

Science.gov (United States)

Hansen, J V; Nelson, R D

1997-01-01

Ever since the initial planning for the 1997 Utah legislative session, neural-network forecasting techniques have provided valuable insights for analysts forecasting tax revenues. These revenue estimates are critically important since agency budgets, support for education, and improvements to infrastructure all depend on their accuracy. Underforecasting generates windfalls that concern taxpayers, whereas overforecasting produces budget shortfalls that cause inadequately funded commitments. The pattern finding ability of neural networks gives insightful and alternative views of the seasonal and cyclical components commonly found in economic time series data. Two applications of neural networks to revenue forecasting clearly demonstrate how these models complement traditional time series techniques. In the first, preoccupation with a potential downturn in the economy distracts analysis based on traditional time series methods so that it overlooks an emerging new phenomenon in the data. In this case, neural networks identify the new pattern that then allows modification of the time series models and finally gives more accurate forecasts. In the second application, data structure found by traditional statistical tools allows analysts to provide neural networks with important information that the networks then use to create more accurate models. In summary, for the Utah revenue outlook, the insights that result from a portfolio of forecasts that includes neural networks exceeds the understanding generated from strictly statistical forecasting techniques. In this case, the synergy clearly results in the whole of the portfolio of forecasts being more accurate than the sum of the individual parts.

1. Comparison of prosthetic models produced by traditional and additive manufacturing methods.

Science.gov (United States)

Park, Jin-Young; Kim, Hae-Young; Kim, Ji-Hwan; Kim, Jae-Hong; Kim, Woong-Chul

2015-08-01

The purpose of this study was to verify the clinical-feasibility of additive manufacturing by comparing the accuracy of four different manufacturing methods for metal coping: the conventional lost wax technique (CLWT); subtractive methods with wax blank milling (WBM); and two additive methods, multi jet modeling (MJM), and micro-stereolithography (Micro-SLA). Thirty study models were created using an acrylic model with the maxillary upper right canine, first premolar, and first molar teeth. Based on the scan files from a non-contact blue light scanner (Identica; Medit Co. Ltd., Seoul, Korea), thirty cores were produced using the WBM, MJM, and Micro-SLA methods, respectively, and another thirty frameworks were produced using the CLWT method. To measure the marginal and internal gap, the silicone replica method was adopted, and the silicone images obtained were evaluated using a digital microscope (KH-7700; Hirox, Tokyo, Japan) at 140X magnification. Analyses were performed using two-way analysis of variance (ANOVA) and Tukey post hoc test (α=.05). The mean marginal gaps and internal gaps showed significant differences according to tooth type (Pmanufacturing method (Pmanufacturing methods were within a clinically allowable range, and, thus, the clinical use of additive manufacturing methods is acceptable as an alternative to the traditional lost wax-technique and subtractive manufacturing.

2. Coconut oil extraction by the traditional Java method : An investigation of its potential application in aqueous Jatropha oil extraction

NARCIS (Netherlands)

Marasabessy, Ahmad; Moeis, Maelita R.; Sanders, Johan P. M.; Weusthuis, Ruud A.

A traditional Java method of coconut oil extraction assisted by paddy crabs was investigated to find out if crabs or crab-derived components can be used to extract oil from Jatropha curcas seed kernels. Using the traditional Java method the addition of crab paste liberated 54% w w(-1) oil from

3. A comparison on parameter-estimation methods in multiple regression analysis with existence of multicollinearity among independent variables

Directory of Open Access Journals (Sweden)

Hukharnsusatrue, A.

2005-11-01

Full Text Available The objective of this research is to compare multiple regression coefficients estimating methods with existence of multicollinearity among independent variables. The estimation methods are Ordinary Least Squares method (OLS, Restricted Least Squares method (RLS, Restricted Ridge Regression method (RRR and Restricted Liu method (RL when restrictions are true and restrictions are not true. The study used the Monte Carlo Simulation method. The experiment was repeated 1,000 times under each situation. The analyzed results of the data are demonstrated as follows. CASE 1: The restrictions are true. In all cases, RRR and RL methods have a smaller Average Mean Square Error (AMSE than OLS and RLS method, respectively. RRR method provides the smallest AMSE when the level of correlations is high and also provides the smallest AMSE for all level of correlations and all sample sizes when standard deviation is equal to 5. However, RL method provides the smallest AMSE when the level of correlations is low and middle, except in the case of standard deviation equal to 3, small sample sizes, RRR method provides the smallest AMSE.The AMSE varies with, most to least, respectively, level of correlations, standard deviation and number of independent variables but inversely with to sample size.CASE 2: The restrictions are not true.In all cases, RRR method provides the smallest AMSE, except in the case of standard deviation equal to 1 and error of restrictions equal to 5%, OLS method provides the smallest AMSE when the level of correlations is low or median and there is a large sample size, but the small sample sizes, RL method provides the smallest AMSE. In addition, when error of restrictions is increased, OLS method provides the smallest AMSE for all level, of correlations and all sample sizes, except when the level of correlations is high and sample sizes small. Moreover, the case OLS method provides the smallest AMSE, the most RLS method has a smaller AMSE than

4. A computer program for uncertainty analysis integrating regression and Bayesian methods

Science.gov (United States)

Lu, Dan; Ye, Ming; Hill, Mary C.; Poeter, Eileen P.; Curtis, Gary

2014-01-01

This work develops a new functionality in UCODE_2014 to evaluate Bayesian credible intervals using the Markov Chain Monte Carlo (MCMC) method. The MCMC capability in UCODE_2014 is based on the FORTRAN version of the differential evolution adaptive Metropolis (DREAM) algorithm of Vrugt et al. (2009), which estimates the posterior probability density function of model parameters in high-dimensional and multimodal sampling problems. The UCODE MCMC capability provides eleven prior probability distributions and three ways to initialize the sampling process. It evaluates parametric and predictive uncertainties and it has parallel computing capability based on multiple chains to accelerate the sampling process. This paper tests and demonstrates the MCMC capability using a 10-dimensional multimodal mathematical function, a 100-dimensional Gaussian function, and a groundwater reactive transport model. The use of the MCMC capability is made straightforward and flexible by adopting the JUPITER API protocol. With the new MCMC capability, UCODE_2014 can be used to calculate three types of uncertainty intervals, which all can account for prior information: (1) linear confidence intervals which require linearity and Gaussian error assumptions and typically 10s–100s of highly parallelizable model runs after optimization, (2) nonlinear confidence intervals which require a smooth objective function surface and Gaussian observation error assumptions and typically 100s–1,000s of partially parallelizable model runs after optimization, and (3) MCMC Bayesian credible intervals which require few assumptions and commonly 10,000s–100,000s or more partially parallelizable model runs. Ready access allows users to select methods best suited to their work, and to compare methods in many circumstances.

5. Empirical methods for the estimation of Southern Ocean CO2: support vector and random forest regression

CSIR Research Space (South Africa)

Gregor, Luke

2017-12-01

Full Text Available understanding with spatially integrated air–sea flux estimates (Fay and McKinley, 2014). Conversely, ocean biogeochemical process models are good tools for mechanis- tic understanding, but fail to represent the seasonality of CO2 fluxes in the Southern Ocean... of including coordinate variables as proxies of 1pCO2 in the empirical methods. In the inter- comparison study by Rödenbeck et al. (2015) proxies typi- cally include, but are not limited to, sea surface temperature (SST), chlorophyll a (Chl a), mixed layer...

6. Consistency analysis of subspace identification methods based on a linear regression approach

DEFF Research Database (Denmark)

Knudsen, Torben

2001-01-01

In the literature results can be found which claim consistency for the subspace method under certain quite weak assumptions. Unfortunately, a new result gives a counter example showing inconsistency under these assumptions and then gives new more strict sufficient assumptions which however does n...... not include important model structures as e.g. Box-Jenkins. Based on a simple least squares approach this paper shows the possible inconsistency under the weak assumptions and develops only slightly stricter assumptions sufficient for consistency and which includes any model structure...

7. Complete Dentures Fabricated with CAD/CAM Technology and a Traditional Clinical Recording Method.

Science.gov (United States)

Janeva, Nadica; Kovacevska, Gordana; Janev, Edvard

2017-10-15

The introduction of computer-aided design/computer-aided manufacturing (CAD/CAM) technology into complete denture (CD) fabrication ushered in a new era in removable prosthodontics. Commercially available CAD/CAM denture systems are expected to improve upon the disadvantages associated with conventional fabrication. The purpose of this report is to present the workflow involved in fabricating a CD with a traditional clinical recording method and CAD/CAM technology and to summarize the advantages to the dental practitioner and the patient.

8. Combining traditional dietary assessment methods with novel metabolomics techniques: present efforts by the Food Biomarker Alliance

DEFF Research Database (Denmark)

Brouwer-Brolsma, Elske M; Brennan, Lorraine; Drevon, Christian A

2017-01-01

food metabolomics techniques that allow the quantification of up to thousands of metabolites simultaneously, which may be applied in intervention and observational studies. As biomarkers are often influenced by various other factors than the food under investigation, FoodBAll developed a food intake...... in these metabolomics studies, knowledge about available electronic metabolomics resources is necessary and further developments of these resources are essential. Ultimately, present efforts in this research area aim to advance quality control of traditional dietary assessment methods, advance compliance evaluation...

9. Panel presentation: Should some type of incentive regulation replace traditional methods for LDC's?

International Nuclear Information System (INIS)

Richard, O.G.

1992-01-01

This paper discusses the problems with existing fixed-rate price regulation and how a deregulation of both the pipeline and gas utility companies are needed to enhance competition. The paper suggests alternative methods to traditional regulation which include a financial incentive package which allows or encourages utilities to make investments in more efficient energy management, to improve load factors to balance the energy demands between industrial and residential users, and reward purchases of gas supplies that out-perform an agreed upon level of rates of a cost index. Other incentive programs are proposed by the author with a relative detailed discussion on each topic

10. Assessing Health Promotion Interventions: Limitations of Traditional Research Methods in Community-Based Studies.

Science.gov (United States)

Dressel, Anne; Schneider, Robert; DeNomie, Melissa; Kusch, Jennifer; Welch, Whitney; Sosa, Mirtha; Yeldell, Sally; Maida, Tatiana; Wineberg, Jessica; Holt, Keith; Bernstein, Rebecca

2017-09-01

Most low-income Americans fail to meet physical activity recommendations. Inactivity and poor diet contribute to obesity, a risk factor for multiple chronic diseases. Health promotion activities have the potential to improve health outcomes for low-income populations. Measuring the effectiveness of these activities, however, can be challenging in community settings. A "Biking for Health" study tested the impact of a bicycling intervention on overweight or obese low-income Latino and African American adults to reduce barriers to cycling and increase physical activity and fitness. A randomized controlled trial was conducted in Milwaukee, Wisconsin, in summer 2015. A 12-week bicycling intervention was implemented at two sites with low-income, overweight, or obese Latino and African American adults. We found that randomized controlled trial methodology was suboptimal for use in this small pilot study and that it negatively affected participation. More discussion is needed about the effectiveness of using traditional research methods in community settings to assess the effectiveness of health promotion interventions. Modifications or alternative methods may yield better results. The aim of this article is to discuss the effectiveness and feasibility of using traditional research methods to assess health promotion interventions in community-based settings.

11. ITPI: Initial Transcription Process-Based Identification Method of Bioactive Components in Traditional Chinese Medicine Formula

Directory of Open Access Journals (Sweden)

Baixia Zhang

2016-01-01

Full Text Available Identification of bioactive components is an important area of research in traditional Chinese medicine (TCM formula. The reported identification methods only consider the interaction between the components and the target proteins, which is not sufficient to explain the influence of TCM on the gene expression. Here, we propose the Initial Transcription Process-based Identification (ITPI method for the discovery of bioactive components that influence transcription factors (TFs. In this method, genome-wide chip detection technology was used to identify differentially expressed genes (DEGs. The TFs of DEGs were derived from GeneCards. The components influencing the TFs were derived from STITCH. The bioactive components in the formula were identified by evaluating the molecular similarity between the components in formula and the components that influence the TF of DEGs. Using the formula of Tian-Zhu-San (TZS as an example, the reliability and limitation of ITPI were examined and 16 bioactive components that influence TFs were identified.

12. Adaptive methods for flood forecasting using linear regression models in the upper basin of Senegal River

International Nuclear Information System (INIS)

Sambou, Soussou

2004-01-01

In flood forecasting modelling, large basins are often considered as hydrological systems with multiple inputs and one output. Inputs are hydrological variables such rainfall, runoff and physical characteristics of basin; output is runoff. Relating inputs to output can be achieved using deterministic, conceptual, or stochastic models. Rainfall runoff models generally lack of accuracy. Physical hydrological processes based models, either deterministic or conceptual are highly data requirement demanding and by the way very complex. Stochastic multiple input-output models, using only historical chronicles of hydrological variables particularly runoff are by the way very popular among the hydrologists for large river basin flood forecasting. Application is made on the Senegal River upstream of Bakel, where the River is formed by the main branch, Bafing, and two tributaries, Bakoye and Faleme; Bafing being regulated by Manantaly Dam. A three inputs and one output model has been used for flood forecasting on Bakel. Influence of the lead forecasting, and of the three inputs taken separately, then associated two by two, and altogether has been verified using a dimensionless variance as criterion of quality. Inadequacies occur generally between model output and observations; to put model in better compliance with current observations, we have compared four parameter updating procedure, recursive least squares, Kalman filtering, stochastic gradient method, iterative method, and an AR errors forecasting model. A combination of these model updating have been used in real time flood forecasting.(Author)

13. Variable selection methods in PLS regression - a comparison study on metabolomics data

DEFF Research Database (Denmark)

Karaman, İbrahim; Hedemann, Mette Skou; Knudsen, Knud Erik Bach

. The aim of the metabolomics study was to investigate the metabolic profile in pigs fed various cereal fractions with special attention to the metabolism of lignans using LC-MS based metabolomic approach. References 1. Lê Cao KA, Rossouw D, Robert-Granié C, Besse P: A Sparse PLS for Variable Selection when...... integrated approach. Due to the high number of variables in data sets (both raw data and after peak picking) the selection of important variables in an explorative analysis is difficult, especially when different data sets of metabolomics data need to be related. Variable selection (or removal of irrelevant...... different strategies for variable selection on PLSR method were considered and compared with respect to selected subset of variables and the possibility for biological validation. Sparse PLSR [1] as well as PLSR with Jack-knifing [2] was applied to data in order to achieve variable selection prior...

14. Predicting volume of distribution with decision tree-based regression methods using predicted tissue:plasma partition coefficients.

Science.gov (United States)

Freitas, Alex A; Limbu, Kriti; Ghafourian, Taravat

2015-01-01

Volume of distribution is an important pharmacokinetic property that indicates the extent of a drug's distribution in the body tissues. This paper addresses the problem of how to estimate the apparent volume of distribution at steady state (Vss) of chemical compounds in the human body using decision tree-based regression methods from the area of data mining (or machine learning). Hence, the pros and cons of several different types of decision tree-based regression methods have been discussed. The regression methods predict Vss using, as predictive features, both the compounds' molecular descriptors and the compounds' tissue:plasma partition coefficients (Kt:p) - often used in physiologically-based pharmacokinetics. Therefore, this work has assessed whether the data mining-based prediction of Vss can be made more accurate by using as input not only the compounds' molecular descriptors but also (a subset of) their predicted Kt:p values. Comparison of the models that used only molecular descriptors, in particular, the Bagging decision tree (mean fold error of 2.33), with those employing predicted Kt:p values in addition to the molecular descriptors, such as the Bagging decision tree using adipose Kt:p (mean fold error of 2.29), indicated that the use of predicted Kt:p values as descriptors may be beneficial for accurate prediction of Vss using decision trees if prior feature selection is applied. Decision tree based models presented in this work have an accuracy that is reasonable and similar to the accuracy of reported Vss inter-species extrapolations in the literature. The estimation of Vss for new compounds in drug discovery will benefit from methods that are able to integrate large and varied sources of data and flexible non-linear data mining methods such as decision trees, which can produce interpretable models. Graphical AbstractDecision trees for the prediction of tissue partition coefficient and volume of distribution of drugs.

15. A mixed methods inquiry into the determinants of traditional food consumption among three Cree communities of Eeyou Istchee from an ecological perspective.

Science.gov (United States)

Gaudin, Véronique Laberge; Receveur, Olivier; Walz, Leah; Girard, Félix; Potvin, Louise

2014-01-01

16. Measuring decision weights in recognition experiments with multiple response alternatives: comparing the correlation and multinomial-logistic-regression methods.

Science.gov (United States)

Dai, Huanping; Micheyl, Christophe

2012-11-01

Psychophysical "reverse-correlation" methods allow researchers to gain insight into the perceptual representations and decision weighting strategies of individual subjects in perceptual tasks. Although these methods have gained momentum, until recently their development was limited to experiments involving only two response categories. Recently, two approaches for estimating decision weights in m-alternative experiments have been put forward. One approach extends the two-category correlation method to m > 2 alternatives; the second uses multinomial logistic regression (MLR). In this article, the relative merits of the two methods are discussed, and the issues of convergence and statistical efficiency of the methods are evaluated quantitatively using Monte Carlo simulations. The results indicate that, for a range of values of the number of trials, the estimated weighting patterns are closer to their asymptotic values for the correlation method than for the MLR method. Moreover, for the MLR method, weight estimates for different stimulus components can exhibit strong correlations, making the analysis and interpretation of measured weighting patterns less straightforward than for the correlation method. These and other advantages of the correlation method, which include computational simplicity and a close relationship to other well-established psychophysical reverse-correlation methods, make it an attractive tool to uncover decision strategies in m-alternative experiments.

17. [Correlation coefficient-based classification method of hydrological dependence variability: With auto-regression model as example].

Science.gov (United States)

Zhao, Yu Xi; Xie, Ping; Sang, Yan Fang; Wu, Zi Yi

2018-04-01

Hydrological process evaluation is temporal dependent. Hydrological time series including dependence components do not meet the data consistency assumption for hydrological computation. Both of those factors cause great difficulty for water researches. Given the existence of hydrological dependence variability, we proposed a correlationcoefficient-based method for significance evaluation of hydrological dependence based on auto-regression model. By calculating the correlation coefficient between the original series and its dependence component and selecting reasonable thresholds of correlation coefficient, this method divided significance degree of dependence into no variability, weak variability, mid variability, strong variability, and drastic variability. By deducing the relationship between correlation coefficient and auto-correlation coefficient in each order of series, we found that the correlation coefficient was mainly determined by the magnitude of auto-correlation coefficient from the 1 order to p order, which clarified the theoretical basis of this method. With the first-order and second-order auto-regression models as examples, the reasonability of the deduced formula was verified through Monte-Carlo experiments to classify the relationship between correlation coefficient and auto-correlation coefficient. This method was used to analyze three observed hydrological time series. The results indicated the coexistence of stochastic and dependence characteristics in hydrological process.

18. The Use of Alternative Regression Methods in Social Sciences and the Comparison of Least Squares and M Estimation Methods in Terms of the Determination of Coefficient

Science.gov (United States)

Coskuntuncel, Orkun

2013-01-01

The purpose of this study is two-fold; the first aim being to show the effect of outliers on the widely used least squares regression estimator in social sciences. The second aim is to compare the classical method of least squares with the robust M-estimator using the "determination of coefficient" (R[superscript 2]). For this purpose,…

19. Comparative analysis to determine asphalt density and content, using nuclear and traditional methods

International Nuclear Information System (INIS)

Margffoy S, F.R.; Robayo S, A.M.

1989-01-01

Quality control for flex pavement construction in Colombia for asphaltic mix, as well as for granular and granular sub base layers is made by means of methods that does not guarantee the quality of the job, due to the difficult execution of tests, which impede more to be done or due to inherent problems of the test process. Thanks to the inherent characteristics and advantages of nuclear techniques, those become the optimal alternative to this quality control job. The present research project has been developed with the objective of justifying the use of new technologies applied to road construction; making a comparative analysis between traditional methods used in our country and nuclear techniques that have been using in United States with great success in quality control in road construction

20. Countermeasures for electrolytic corrosion - Part I: Traditional methods and their problems

International Nuclear Information System (INIS)

Ha, Yoon-Cheol; Kim, Dae-Kyeong; Bae, Jeong-Hyo; Ha, Tae-Hyun; Lee, Hyun-Goo

2004-01-01

When an underground pipeline runs parallel with DC-powered railways, it suffers from electrolytic corrosion caused by the stray current leaked from the railway negative returns. Perforation due to the electrolytic corrosion may bring about large-scale accidents even in cathodically protected systems. Traditionally, bonding methods such as direct drainage, polarized drainage and forced drainage have been used in order to mitigate the damage on pipelines. In particular, the forced drainage method is widely adopted in Korea. In this paper, we report the real-time measurement data of the pipe-to-soil potential variation in the presence and absence of the IR compensation. The drainage current variation was also measured using the Stray Current Logger developed. By analysing them, the problems of current countermeasures for electrolytic corrosion are discussed. (authors)

1. Countermeasures for electrolytic corrosion - Part I: Traditional methods and their problems

Energy Technology Data Exchange (ETDEWEB)

Ha, Yoon-Cheol; Kim, Dae-Kyeong; Bae, Jeong-Hyo; Ha, Tae-Hyun; Lee, Hyun-Goo [Underground Systems Group, Korea Electrotechnology Research Institute, 28-1 Sungju-dong, Changwon (Korea, Republic of)

2004-07-01

When an underground pipeline runs parallel with DC-powered railways, it suffers from electrolytic corrosion caused by the stray current leaked from the railway negative returns. Perforation due to the electrolytic corrosion may bring about large-scale accidents even in cathodically protected systems. Traditionally, bonding methods such as direct drainage, polarized drainage and forced drainage have been used in order to mitigate the damage on pipelines. In particular, the forced drainage method is widely adopted in Korea. In this paper, we report the real-time measurement data of the pipe-to-soil potential variation in the presence and absence of the IR compensation. The drainage current variation was also measured using the Stray Current Logger developed. By analysing them, the problems of current countermeasures for electrolytic corrosion are discussed. (authors)

2. Reliability studies of diagnostic methods in Indian traditional Ayurveda medicine: An overview

Science.gov (United States)

Kurande, Vrinda Hitendra; Waagepetersen, Rasmus; Toft, Egon; Prasad, Ramjee

2013-01-01

Recently, a need to develop supportive new scientific evidence for contemporary Ayurveda has emerged. One of the research objectives is an assessment of the reliability of diagnoses and treatment. Reliability is a quantitative measure of consistency. It is a crucial issue in classification (such as prakriti classification), method development (pulse diagnosis), quality assurance for diagnosis and treatment and in the conduct of clinical studies. Several reliability studies are conducted in western medicine. The investigation of the reliability of traditional Chinese, Japanese and Sasang medicine diagnoses is in the formative stage. However, reliability studies in Ayurveda are in the preliminary stage. In this paper, examples are provided to illustrate relevant concepts of reliability studies of diagnostic methods and their implication in practice, education, and training. An introduction to reliability estimates and different study designs and statistical analysis is given for future studies in Ayurveda. PMID:23930037

3. Bioassessment of a Drinking Water Reservoir Using Plankton: High Throughput Sequencing vs. Traditional Morphological Method

Directory of Open Access Journals (Sweden)

Wanli Gao

2018-01-01

Full Text Available Drinking water safety is increasingly perceived as one of the top global environmental issues. Plankton has been commonly used as a bioindicator for water quality in lakes and reservoirs. Recently, DNA sequencing technology has been applied to bioassessment. In this study, we compared the effectiveness of the 16S and 18S rRNA high throughput sequencing method (HTS and the traditional optical microscopy method (TOM in the bioassessment of drinking water quality. Five stations reflecting different habitats and hydrological conditions in Danjiangkou Reservoir, one of the largest drinking water reservoirs in Asia, were sampled May 2016. Non-metric multi-dimensional scaling (NMDS analysis showed that plankton assemblages varied among the stations and the spatial patterns revealed by the two methods were consistent. The correlation between TOM and HTS in a symmetric Procrustes analysis was 0.61, revealing overall good concordance between the two methods. Procrustes analysis also showed that site-specific differences between the two methods varied among the stations. Station Heijizui (H, a site heavily influenced by two tributaries, had the largest difference while station Qushou (Q, a confluence site close to the outlet dam, had the smallest difference between the two methods. Our results show that DNA sequencing has the potential to provide consistent identification of taxa, and reliable bioassessment in a long-term biomonitoring and assessment program for drinking water reservoirs.

4. A comparison of two prospective risk analysis methods: Traditional FMEA and a modified healthcare FMEA.

Science.gov (United States)

Rah, Jeong-Eun; Manger, Ryan P; Yock, Adam D; Kim, Gwe-Ya

2016-12-01

To examine the abilities of a traditional failure mode and effects analysis (FMEA) and modified healthcare FMEA (m-HFMEA) scoring methods by comparing the degree of congruence in identifying high risk failures. The authors applied two prospective methods of the quality management to surface image guided, linac-based radiosurgery (SIG-RS). For the traditional FMEA, decisions on how to improve an operation were based on the risk priority number (RPN). The RPN is a product of three indices: occurrence, severity, and detectability. The m-HFMEA approach utilized two indices, severity and frequency. A risk inventory matrix was divided into four categories: very low, low, high, and very high. For high risk events, an additional evaluation was performed. Based upon the criticality of the process, it was decided if additional safety measures were needed and what they comprise. The two methods were independently compared to determine if the results and rated risks matched. The authors' results showed an agreement of 85% between FMEA and m-HFMEA approaches for top 20 risks of SIG-RS-specific failure modes. The main differences between the two approaches were the distribution of the values and the observation that failure modes (52, 54, 154) with high m-HFMEA scores do not necessarily have high FMEA-RPN scores. In the m-HFMEA analysis, when the risk score is determined, the basis of the established HFMEA Decision Tree™ or the failure mode should be more thoroughly investigated. m-HFMEA is inductive because it requires the identification of the consequences from causes, and semi-quantitative since it allows the prioritization of high risks and mitigation measures. It is therefore a useful tool for the prospective risk analysis method to radiotherapy.

5. Comparison of Satellite Surveying to Traditional Surveying Methods for the Resources Industry

Science.gov (United States)

Osborne, B. P.; Osborne, V. J.; Kruger, M. L.

Modern ground-based survey methods involve detailed survey, which provides three-space co-ordinates for surveyed points, to a high level of accuracy. The instruments are operated by surveyors, who process the raw results to create survey location maps for the subject of the survey. Such surveys are conducted for a location or region and referenced to the earth global co- ordinate system with global positioning system (GPS) positioning. Due to this referencing the survey is only as accurate as the GPS reference system. Satellite survey remote sensing utilise satellite imagery which have been processed using commercial geographic information system software. Three-space co-ordinate maps are generated, with an accuracy determined by the datum position accuracy and optical resolution of the satellite platform.This paper presents a case study, which compares topographic surveying undertaken by traditional survey methods with satellite surveying, for the same location. The purpose of this study is to assess the viability of satellite remote sensing for surveying in the resources industry. The case study involves a topographic survey of a dune field for a prospective mining project area in Pakistan. This site has been surveyed using modern surveying techniques and the results are compared to a satellite survey performed on the same area.Analysis of the results from traditional survey and from the satellite survey involved a comparison of the derived spatial co- ordinates from each method. In addition, comparisons have been made of costs and turnaround time for both methods.The results of this application of remote sensing is of particular interest for survey in areas with remote and extreme environments, weather extremes, political unrest, poor travel links, which are commonly associated with mining projects. Such areas frequently suffer language barriers, poor onsite technical support and resources.

6. Product-service system method to measure sustainability level of traditional smoked fish processing industries

Directory of Open Access Journals (Sweden)

Purwaningsih Ratna

2018-01-01

Full Text Available Small Medium Enterprise’s (SME of traditional fish processing at Semarang, Central Java, Indonesia still focus their business on gain more profits. Sustainability aspect has not received enough attention yet. This study aims to review the sustainability level of SME smoked fish Semarang using product service system (PSS method. PSS consists of three dimensions (1 Environment, (2 Socio-cultural and (3 Economic. Each dimension consists of 6 criteria's. PSS not only assess the level of sustainability but also formulated the recommendation to increase the industries sustainability level. Sustainability assessment and recommendations formulation is guided by a check-list form. Then, the portfolio diagram used to select these recommendations according to its feasibility to be implemented and its importance for the industries. The result of sustainability assessment for traditional fish processing is 0.44, categorized as medium level. The recommendations for the environmental dimension are (1 use of liquid smoke on fish processing and (2 use of wastewater treatment with anaerobic ponds Recommendation for the socio-cultural dimension is use personal protective tool to reduce worker risk on safety and health. Recommendation for the economic dimension is used social media for product marketing and increasing the economic value of fish lung wastes. Recommendations are then illustrated in a diagram in the form of radar sustainability.

7. Color electron microprobe cathodoluminescence of Bishunpur meteorite compared with the traditional optical microscopy method

Directory of Open Access Journals (Sweden)

Amanda Araujo Tosi

Full Text Available Abstract Cathodoluminescence (CL imaging is an outstanding method for sub classification of Unequilibrated Ordinary Chondrites (UOC - petrological type 3. CL can be obtained by several electron beam apparatuses. The traditional method uses an electron gun coupled to an optical microscope (OM. Although many scanning electron microscopes (SEM and electron microprobes (EPMA have been equipped with a cathodoluminescence, this technique was not fully explored. Images obtained by the two methods differ due to a different kind of signal acquisition. While in the CL-OM optical photography true colors are obtained, in the CL-EPMA the results are grayscale monochromatic electronic signals. L-RGB filters were used in the CL-EPMA analysis in order to obtain color data. The aim of this work is to compare cathodoluminescence data obtained from both techniques, optical microscope and electron microprobe, on the Bishunpur meteorite classified as LL 3.1 chondrite. The present study allows concluding that 20 KeV and 7 nA is the best analytical condition at EPMA in order to test the equivalence between CL-EPMA and CL-OM colour results. Moreover, the color index revealed to be a method for aiding the study of the thermal metamorphism, but it is not definitive for the meteorite classification.

8. Comparison of exact, efron and breslow parameter approach method on hazard ratio and stratified cox regression model

Science.gov (United States)

Fatekurohman, Mohamat; Nurmala, Nita; Anggraeni, Dian

2018-04-01

Lungs are the most important organ, in the case of respiratory system. Problems related to disorder of the lungs are various, i.e. pneumonia, emphysema, tuberculosis and lung cancer. Comparing all those problems, lung cancer is the most harmful. Considering about that, the aim of this research applies survival analysis and factors affecting the endurance of the lung cancer patient using comparison of exact, Efron and Breslow parameter approach method on hazard ratio and stratified cox regression model. The data applied are based on the medical records of lung cancer patients in Jember Paru-paru hospital on 2016, east java, Indonesia. The factors affecting the endurance of the lung cancer patients can be classified into several criteria, i.e. sex, age, hemoglobin, leukocytes, erythrocytes, sedimentation rate of blood, therapy status, general condition, body weight. The result shows that exact method of stratified cox regression model is better than other. On the other hand, the endurance of the patients is affected by their age and the general conditions.

9. Use of Geographically Weighted Regression (GWR Method to Estimate the Effects of Location Attributes on the Residential Property Values

Directory of Open Access Journals (Sweden)

Mohd Faris Dziauddin

2017-07-01

Full Text Available This study estimates the effect of locational attributes on residential property values in Kuala Lumpur, Malaysia. Geographically weighted regression (GWR enables the use of the local parameter rather than the global parameter to be estimated, with the results presented in map form. The results of this study reveal that residential property values are mainly determined by the property’s physical (structural attributes, but proximity to locational attributes also contributes marginally. The use of GWR in this study is considered a better approach than other methods to examine the effect of locational attributes on residential property values. GWR has the capability to produce meaningful results in which different locational attributes have differential spatial effects across a geographical area on residential property values. This method has the ability to determine the factors on which premiums depend, and in turn it can assist the government in taxation matters.

10. A study on relationship between operating cash flows and performance evaluation criteria based on the theory of constraints (TOC versus traditional method

Directory of Open Access Journals (Sweden)

2013-08-01

Full Text Available This study presents an empirical investigation to measure the relationship between traditional accounting performance measurement as well as theory of constraint-based figures with operating cash flow. Traditional accounting measurement includes net profit and return of investment and theory of constraint method includes net profit and return of investment based on theory of constraints. The study selects 69 firms list on Tehran Stock Exchange over the period 2000-2010. Using panel data and fixed effect, the study performs regression analysis and the results confirm that there was a positive relationship between net profit measured by theory of constraints and cash flow and it can be effectively used for performance measurement.

11. Regression Phalanxes

OpenAIRE

Zhang, Hongyang; Welch, William J.; Zamar, Ruben H.

2017-01-01

Tomal et al. (2015) introduced the notion of "phalanxes" in the context of rare-class detection in two-class classification problems. A phalanx is a subset of features that work well for classification tasks. In this paper, we propose a different class of phalanxes for application in regression settings. We define a "Regression Phalanx" - a subset of features that work well together for prediction. We propose a novel algorithm which automatically chooses Regression Phalanxes from high-dimensi...

12. Volatile profile characterisation of Chilean sparkling wines produced by traditional and Charmat methods via sequential stir bar sorptive extraction.

Science.gov (United States)

Ubeda, C; Callejón, R M; Troncoso, A M; Peña-Neira, A; Morales, M L

2016-09-15

The volatile compositions of Charmat and traditional Chilean sparkling wines were studied for the first time. For this purpose, EG-Silicone and PDMS polymeric phases were compared and, afterwards, the most adequate was selected. The best extraction method turned out to be a sequential extraction in the headspace and by immersion using two PDMS twisters. A total of 130 compounds were determined. In traditional Chilean sparkling wines, ethyl esters were significantly higher, while acetic esters and ketones were predominant in the Charmat wines. PCA and LDA confirmed the differences in the volatile profiles between the production methods (traditional vs. Charmat). Copyright © 2016 Elsevier Ltd. All rights reserved.

13. A structured sparse regression method for estimating isoform expression level from multi-sample RNA-seq data.

Science.gov (United States)

Zhang, L; Liu, X J

2016-06-03

With the rapid development of next-generation high-throughput sequencing technology, RNA-seq has become a standard and important technique for transcriptome analysis. For multi-sample RNA-seq data, the existing expression estimation methods usually deal with each single-RNA-seq sample, and ignore that the read distributions are consistent across multiple samples. In the current study, we propose a structured sparse regression method, SSRSeq, to estimate isoform expression using multi-sample RNA-seq data. SSRSeq uses a non-parameter model to capture the general tendency of non-uniformity read distribution for all genes across multiple samples. Additionally, our method adds a structured sparse regularization, which not only incorporates the sparse specificity between a gene and its corresponding isoform expression levels, but also reduces the effects of noisy reads, especially for lowly expressed genes and isoforms. Four real datasets were used to evaluate our method on isoform expression estimation. Compared with other popular methods, SSRSeq reduced the variance between multiple samples, and produced more accurate isoform expression estimations, and thus more meaningful biological interpretations.

Science.gov (United States)

Ingadottir, Brynja; Blondal, Katrin; Jaarsma, Tiny; Thylen, Ingela

2016-11-01

The aim of this study was to explore the perceptions of surgical patients about traditional and novel methods to learn about postoperative pain management. Patient education is an important part of postoperative care. Contemporary technology offers new ways for patients to learn about self-care, although face-to-face discussions and brochures are the most common methods of delivering education in nursing practice. A qualitative design with a vignette and semi-structured interviews used for data collection. A purposeful sample of 13 postsurgical patients, who had been discharged from hospital, was recruited during 2013-2014. The patients were given a vignette about anticipated hospital discharge after surgery with four different options for communication (face-to-face, brochure, website, serious game) to learn about postoperative pain management. They were asked to rank their preferred method of learning and thereafter to reflect on their choices. Data were analysed using an inductive content analysis approach. Patients preferred face-to-face education with a nurse, followed by brochures and websites, while games were least preferred. Two categories, each with two sub-categories, emerged from the data. These conceptualized the factors affecting patients' perceptions: (1) 'Trusting the source', sub-categorized into 'Being familiar with the method' and 'Having own prejudgments'; and (2) 'Being motivated to learn' sub-categorized into 'Managing an impaired cognition' and 'Aspiring for increased knowledge'. To implement successfully novel educational methods into postoperative care, healthcare professionals need to be aware of the factors influencing patients' perceptions about how to learn, such as trust and motivation. © 2016 John Wiley & Sons Ltd.

15. [New method for analyzing pharmacodynamic material basis of traditional Chinese medicines by using specific knockout technology with monoclonal antibodies].

Science.gov (United States)

Zhao, Yan; Qu, Hui-Hua; Wang, Qing-Guo

2013-09-01

Study on pharmacodynamic material basis of traditional Chinese medicines is one of the key issues for the modernization of traditional Chinese medicine. Having introduced the monoclonal antibody technology into the study on pharmacodynamic material basis of traditional Chinese medicines, the author prepared the immunoaffinity chromatography column by using monoclonal antibodies in active components of traditional Chinese medicines, so as to selectively knock out the component from herbs or traditional Chinese medicine compounds, while preserving all of the other components and keeping their amount and ratio unchanged. A comparative study on pharmacokinetics and pharmacodynamics was made to explicitly reveal the correlation between the component and the main purpose of traditional Chinese medicines and compounds. The analysis on pharmacodynamic material basis of traditional Chinese medicines by using specific knockout technology with monoclonal antibodies is a new method for study pharmacodynamic material basis in line with the characteristics of traditional Chinese medicines. Its results can not only help study material basis from a new perspective, but also help find the modern scientific significance in single herb or among compounds of traditional Chinese medicines.

16. Computational Study of Estrogen Receptor-Alpha Antagonist with Three-Dimensional Quantitative Structure-Activity Relationship, Support Vector Regression, and Linear Regression Methods

Directory of Open Access Journals (Sweden)

Ying-Hsin Chang

2013-01-01

Full Text Available Human estrogen receptor (ER isoforms, ERα and ERβ, have long been an important focus in the field of biology. To better understand the structural features associated with the binding of ERα ligands to ERα and modulate their function, several QSAR models, including CoMFA, CoMSIA, SVR, and LR methods, have been employed to predict the inhibitory activity of 68 raloxifene derivatives. In the SVR and LR modeling, 11 descriptors were selected through feature ranking and sequential feature addition/deletion to generate equations to predict the inhibitory activity toward ERα. Among four descriptors that constantly appear in various generated equations, two agree with CoMFA and CoMSIA steric fields and another two can be correlated to a calculated electrostatic potential of ERα.

17. [Research on medical speciality of traditional Chinese medicines using dot-immunoblotting method based on polyclonal antibody prepared from traditional Chinese medicines with hot/cold nature].

Science.gov (United States)

Wang, Houwei; Dou, Yanling; Tian, Jingzhen; Li, Feng; Wang, Shijun; Wang, Zhenguo

2009-02-01

To research on the substantial foundation of the medical speciality of Chinese traditional medicines from immunogenicity. Control antigen with hot nature was prepared from the mixture of the aqueous extracts of three Chinese traditional medicines with three typical hot nature of Alpinia officinarum, Cinnamomum cassia and Curculigo orchioides, while that with cold nature prepared with Rheum palmatum, Anemarrhena asphodeloides, Coptis chinensis, and polyclonal antibody was prepared by immunizing rabbit with control antigen. Dot blotting was performed between the polyclonal antibody of control antigen and the aqueous extracts of nine Chinese traditional medicines on a piece of PVDF membrane, and the blotting signals were analyzed by the software of Quantity One. Blotting signals with hot control antigen of nine Chinese traditional medicines in descending were Zingiber officinale, Aconitum carmichaeli, Eucommia ulmoides, Fraxinus rhynchophylla, Lonicera japonica, Anemarrhena asphodeloides, Coptis chinensis, Rheum palmatum and Phellodendron chinense, which degree of similarity to control antigen in peak value were 57.33%, 43.56 %, 34.16%, 30.2%, 28.81%, 26.53%, 21.68%, 17.62% and 14.85%, respectively. Blotting signals with cold control antigen were Rheum palmatum, Anemarrhena asphodeloides, Coptis chinensis, Phellodendron chinense, Zingiber officinale, Lonicera japonica, Fraxinus rhynchophylla, Eucommia ulmoides and Aconitum carmichaeli in descending, of which degree of similarity to cold control antigen in peak value were 55.22%, 54.23%, 46.72%, 34.08%, 30.3%, 24.48%, 24.33%, 20.35% and 15.17%, respectively. Results of cluster analysis with Wistar's method showed that nine medicines were classified into two groups, one group included Phellodendron chinense, Anemarrhena asphodeloides, Coptis chinensis, Rheum palmatum, another was Zingiber officinale, Aconitum carmichaeli, Eucommia ulmoides, Fraxinus rhynchophylla, Lonicera japonica. Blotting signals of nine medicines

18. Blended learning – integrating E-learning with traditional learning methods in teaching basic medical science

OpenAIRE

J.G. Bagi; N.K. Hashilkar

2014-01-01

Background: Blended learning includes an integration of face to face classroom learning with technology enhanced online material. It provides the convenience, speed and cost effectiveness of e-learning with the personal touch of traditional learning. Objective: The objective of the present study was to assess the effectiveness of a combination of e-learning module and traditional teaching (Blended learning) as compared to traditional teaching alone to teach acid base homeostasis to Phase I MB...

19. Consistency analysis of Keratograph and traditional methods to evaluate tear film function

Directory of Open Access Journals (Sweden)

Pei-Yang Shen

2015-05-01

Full Text Available AIM: To investigate repeatability and accuracy of a latest Keratograph for evaluating the tear film stability and to compare its measurements with that of traditional examination methods. METHODS: The results of noninvasive tear film break-up time(NI-BUTincluding the first tear film break-up time(BUT-fand the average tear film break-up time(BUT-avewere measured by Keratograph. The repeatability of the measurements was evaluated by coefficient of variation(CVand intraclass correlation coefficient(ICC. Wilcoxon Signed-Rank test was used to compare NI-BUT with fluorescein tear film break-up time(FBUTto confirm the correlation between NI-BUT and FBUT, Schirmer I test values. Bland-Altman analysis was used to evaluate consistency. RESULTS: The study recruited 48 subjects(48 eyes(mean age 38.7±15.2 years. The CV and ICC of BUT-f were respectively 12.6% and 0.95, those of BUT-ave were 9.8% and 0.96. The value of BUT-f was lower than that of FBUT. The difference had statistical significance(6.16±2.46s vs 7.46±1.92s, PPCONCLUSION: Keratograph can provide NI-BUT data that has a better repeatability and reliability, which has great application prospects in diagnosis and treatment of dry eye and refractive corneal surgery.

20. Integration of membrane distillation into traditional salt farming method: Process development and modelling

Science.gov (United States)

Hizam, S.; Bilad, M. R.; Putra, Z. A.

2017-10-01

Farmers still practice the traditional salt farming in many regions, particularly in Indonesia. This archaic method not only produces low yield and poor salt quality, it is also laborious. Furthermore, the farming locations typically have poor access to fresh water and are far away from electricity grid, which restrict upgrade to a more advanced technology for salt production. This paper proposes a new concept of salt harvesting method that improves the salt yield and at the same time facilitates recovery of fresh water from seawater. The new concept integrates solar powered membrane distillation (MD) and photovoltaic cells to drive the pumping. We performed basic solar still experiments to quantify the heat flux received by a pond. The data were used as insight for designing the proposed concept, particularly on operational strategy and the most effective way to integrate MD. After the conceptual design had been developed, we formulated mass and energy balance to estimate the performance of the proposed concept. Based on our data and design, it is expected that the system would improve the yield and quality of the salt production, maximizing fresh water harvesting, and eventually provides economical gain for salt farmers hence improving their quality of life. The key performance can only be measured via experiment using gain output ratio as performance indicator, which will be done in a future study.

1. Developing a Pictorial Sisterhood Method in collaboration with illiterate Maasai traditional birth attendants in northern Tanzania.

Science.gov (United States)

Roggeveen, Yadira; Schreuder, Renske; Zweekhorst, Marjolein; Manyama, Mange; Hatfield, Jennifer; Scheele, Fedde; van Roosmalen, Jos

2016-10-01

To study whether data on maternal mortality can be gathered while maintaining local ownership of data in a pastoralist setting where a scarcity of data sources and a culture of silence around maternal death amplifies limited awareness of the magnitude of maternal mortality. As part of a participatory action research project, investigators and illiterate traditional birth attendants (TBAs) collaboratively developed a quantitative participatory tool-the Pictorial Sisterhood Method-that was pilot-tested between March 12 and May 30, 2011, by researchers and TBAs in a cross-sectional study. Fourteen TBAs interviewed 496 women (sample), which led to 2241 sister units of risk and a maternal mortality ratio of 689 deaths per 100000 live births (95% confidence interval 419-959). Researchers interviewed 474 women (sample), leading to 1487 sister units of risk and a maternal mortality ratio of 484 (95% confidence interval 172-795). The Pictorial Sisterhood Method is an innovative application that might increase the participation of illiterate individuals in maternal health research and advocacy. It offers interesting opportunities to increase maternal mortality data ownership and awareness, and warrants further study and validation. Copyright © 2016 International Federation of Gynecology and Obstetrics. Published by Elsevier Ireland Ltd. All rights reserved.

2. Application of PROMETHEE-GAIA method for non-traditional machining processes selection

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2012-10-01

Full Text Available With ever increasing demand for manufactured products of hard alloys and metals with high surface finish and complex shape geometry, more interest is now being paid to non-traditional machining (NTM processes, where energy in its direct form is used to remove material from workpiece surface. Compared to conventional machining processes, NTM processes possess almost unlimited capabilities and there is a strong believe that use of NTM processes would go on increasing in diverse range of applications. Presence of a large number of NTM processes along with complex characteristics and capabilities, and lack of experts in NTM process selection domain compel for development of a structured approach for NTM process selection for a given machining application. Past researchers have already attempted to solve NTM process selection problems using various complex mathematical approaches which often require a profound knowledge in mathematics/artificial intelligence from the part of process engineers. In this paper, four NTM process selection problems are solved using an integrated PROMETHEE (preference ranking organization method for enrichment evaluation and GAIA (geometrical analysis for interactive aid method which would act as a visual decision aid to the process engineers. The observed results are quite satisfactory and exactly match with the expected solutions.

3. Use of different marker pre-selection methods based on single SNP regression in the estimation of Genomic-EBVs

Directory of Open Access Journals (Sweden)

2010-01-01

Full Text Available Two methods of SNPs pre-selection based on single marker regression for the estimation of genomic breeding values (G-EBVs were compared using simulated data provided by the XII QTL-MAS workshop: i Bonferroni correction of the significance threshold and ii Permutation test to obtain the reference distribution of the null hypothesis and identify significant markers at P<0.01 and P<0.001 significance thresholds. From the set of markers significant at P<0.001, random subsets of 50% and 25% markers were extracted, to evaluate the effect of further reducing the number of significant SNPs on G-EBV predictions. The Bonferroni correction method allowed the identification of 595 significant SNPs that gave the best G-EBV accuracies in prediction generations (82.80%. The permutation methods gave slightly lower G-EBV accuracies even if a larger number of SNPs resulted significant (2,053 and 1,352 for 0.01 and 0.001 significance thresholds, respectively. Interestingly, halving or dividing by four the number of SNPs significant at P<0.001 resulted in an only slightly decrease of G-EBV accuracies. The genetic structure of the simulated population with few QTL carrying large effects, might have favoured the Bonferroni method.

4. VOLATILE CONSTITUENTS OF GINGER OIL PREPARED ACCORDING TO IRANIAN TRADITIONAL MEDICINE AND CONVENTIONAL METHOD: A COMPARATIVE STUDY.

Science.gov (United States)

2016-01-01

Herbal medicines formulated as oils were believed to possess more powerful effects than their original plants in Iranian Traditional Medicine (ITM). One of the popular oils suggested for treatment of various indications was ginger oil. In the present study, to suggest a more convenient method of oil preparation (compared to the traditional method), ginger oil has been prepared according to both the traditional and conventional maceration methods and the volatile oil constituents have been compared. Ginger oil was obtained in sesame oil according to both the traditional way and the conventional (maceration) methods. The volatile oil of dried ginger and both oils were obtained by hydro-distillation and analyzed by gas chromatography/mass spectroscopy. Fifty five, fifty nine and fifty one components consisting 94 %, 94 % and 98 % of the total compounds were identified in the volatile oil of ginger, traditional and conventional oils, respectively. The most dominant compounds of the traditional and conventional oils were almost similar; however they were different from ginger essential oil which has also been to possess limited amounts of anti-inflammatory components. It was concluded that ginger oil could be prepared through maceration method and used for indications mentioned in ITM.

5. QSAR Modeling of COX -2 Inhibitory Activity of Some Dihydropyridine and Hydroquinoline Derivatives Using Multiple Linear Regression (MLR) Method.

Science.gov (United States)

Akbari, Somaye; Zebardast, Tannaz; Zarghi, Afshin; Hajimahdi, Zahra

2017-01-01

COX-2 inhibitory activities of some 1,4-dihydropyridine and 5-oxo-1,4,5,6,7,8-hexahydroquinoline derivatives were modeled by quantitative structure-activity relationship (QSAR) using stepwise-multiple linear regression (SW-MLR) method. The built model was robust and predictive with correlation coefficient (R 2 ) of 0.972 and 0.531 for training and test groups, respectively. The quality of the model was evaluated by leave-one-out (LOO) cross validation (LOO correlation coefficient (Q 2 ) of 0.943) and Y-randomization. We also employed a leverage approach for the defining of applicability domain of model. Based on QSAR models results, COX-2 inhibitory activity of selected data set had correlation with BEHm6 (highest eigenvalue n. 6 of Burden matrix/weighted by atomic masses), Mor03u (signal 03/unweighted) and IVDE (Mean information content on the vertex degree equality) descriptors which derived from their structures.

6. Field camp: Using traditional methods to train the next generation of petroleum geologists

Science.gov (United States)

Puckette, J.O.; Suneson, N.H.

2009-01-01

The summer field camp experience provides many students with their best opportunity to learn the scientific process by making observations and collecting, recording, evaluating, and interpreting geologic data. Field school projects enhance student professional development by requiring cooperation and interpersonal interaction, report writing to communicate interpretations, and the development of project management skills to achieve a common goal. The field school setting provides students with the opportunity to observe geologic features and their spatial distribution, size, and shape that will impact the student's future careers as geoscientists. The Les Huston Geology Field Camp (a.k.a. Oklahoma Geology Camp) near Ca??on City, Colorado, focuses on time-tested traditional methods of geological mapping and fieldwork to accomplish these goals. The curriculum consists of an introduction to field techniques (pacing, orienteering, measuring strike and dip, and using a Jacob's staff), sketching outcrops, section measuring (one illustrating facies changes), three mapping exercises (of increasing complexity), and a field geophysics project. Accurate rock and contact descriptions are emphasized, and attitudes and contacts are mapped in the field. Mapping is done on topographic maps at 1:12,000 and 1:6000 scales; air photos are provided. Global positioning system (GPS)-assisted mapping is allowed, but we insist that locations be recorded in the field and confirmed using visual observations. The course includes field trips to the Cripple Creek and Leadville mining districts, Floris-sant/Guffey volcano area, Pikes Peak batholith, and the Denver Basin. Each field trip is designed to emphasize aspects of geology that are not stressed in the field exercises. Students are strongly encouraged to accurately describe geologic features and gather evidence to support their interpretations of the geologic history. Concise reports are a part of each major exercise. Students are grouped

7. Improving Nursing Students' Learning Outcomes in Fundamentals of Nursing Course through Combination of Traditional and e-Learning Methods.

Science.gov (United States)

Sheikhaboumasoudi, Rouhollah; Bagheri, Maryam; Hosseini, Sayed Abbas; Ashouri, Elaheh; Elahi, Nasrin

2018-01-01

Fundamentals of nursing course are prerequisite to providing comprehensive nursing care. Despite development of technology on nursing education, effectiveness of using e-learning methods in fundamentals of nursing course is unclear in clinical skills laboratory for nursing students. The aim of this study was to compare the effect of blended learning (combining e-learning with traditional learning methods) with traditional learning alone on nursing students' scores. A two-group post-test experimental study was administered from February 2014 to February 2015. Two groups of nursing students who were taking the fundamentals of nursing course in Iran were compared. Sixty nursing students were selected as control group (just traditional learning methods) and experimental group (combining e-learning with traditional learning methods) for two consecutive semesters. Both groups participated in Objective Structured Clinical Examination (OSCE) and were evaluated in the same way using a prepared checklist and questionnaire of satisfaction. Statistical analysis was conducted through SPSS software version 16. Findings of this study reflected that mean of midterm (t = 2.00, p = 0.04) and final score (t = 2.50, p = 0.01) of the intervention group (combining e-learning with traditional learning methods) were significantly higher than the control group (traditional learning methods). The satisfaction of male students in intervention group was higher than in females (t = 2.60, p = 0.01). Based on the findings, this study suggests that the use of combining traditional learning methods with e-learning methods such as applying educational website and interactive online resources for fundamentals of nursing course instruction can be an effective supplement for improving nursing students' clinical skills.

8. Modified Regression Correlation Coefficient for Poisson Regression Model

Science.gov (United States)

Kaengthong, Nattacha; Domthong, Uthumporn

2017-09-01

This study gives attention to indicators in predictive power of the Generalized Linear Model (GLM) which are widely used; however, often having some restrictions. We are interested in regression correlation coefficient for a Poisson regression model. This is a measure of predictive power, and defined by the relationship between the dependent variable (Y) and the expected value of the dependent variable given the independent variables [E(Y|X)] for the Poisson regression model. The dependent variable is distributed as Poisson. The purpose of this research was modifying regression correlation coefficient for Poisson regression model. We also compare the proposed modified regression correlation coefficient with the traditional regression correlation coefficient in the case of two or more independent variables, and having multicollinearity in independent variables. The result shows that the proposed regression correlation coefficient is better than the traditional regression correlation coefficient based on Bias and the Root Mean Square Error (RMSE).

9. Comparing the Effects of Objective Structured Assessment of Technical Skills (OSATS) and Traditional Method on Learning of Students.

Science.gov (United States)

Mansoorian, Mohammad Reza; Hosseiny, Marzeih Sadat; Khosravan, Shahla; Alami, Ali; Alaviani, Mehri

2015-06-01

10. Association between traditional oral hygiene methods with tooth wear, gingival bleeding, and recession: A descriptive cross-sectional study.

Science.gov (United States)

Shah, Naseem; Mathur, Vijay Prakash; Jain, Veena; Logani, Ajay

2018-01-01

Oral hygiene maintenance is crucial for prevention of various oral diseases. Oral hygiene practices across the country vary largely and people in peri-urban and rural areas use traditional methods of oral hygiene like powders, bark, oil and salt etc. Their effect on oral soft and hard tissues need to be studied to understand their beneficial and/ or harmful effects on maintenance of oral hygiene and prevention or causation of oral diseases. This study aimed to assess the plaque-cleaning efficacy, gingival bleeding, recession and tooth wear with different traditional oral hygiene methods as compared to use of toothpaste-toothbrush, the most accepted method of oral hygiene practice. Hospital based cross sectional analytical study. Results: Total 1062 traditional oral hygiene method users were compared with same number of toothpaste-brush users. The maximum number in the former group used tooth powder (76%) as compared to other indigenous methods, such as use of bark of trees etc and out of tooth powder users; almost 75% reported using red toothpowder. The plaque scores and gingival bleeding & recession were found to be more in traditional oral hygiene method users. The toothwear was also more severe among the toothpowder users. Traditional methods were found to be inferior in plaque control as was documented by increased bleeding and gingival recession. Its effect on hard tissues of teeth was very damaging with higher tooth wear scores on all surfaces.

11. Andragogical Teaching Methods to Enhance Non-Traditional Student Classroom Engagement

Science.gov (United States)

Allen, Pamela; Withey, Paul; Lawton, Deb; Aquino, Carlos Tasso

2016-01-01

The aim of this study was to provide a reflection of current trends in higher education, identify some of the changes in student behavior, and potential identification of non-traditional classroom facilitation with the purpose of strengthening active learning and use of technology in the classroom. Non-traditional teaching is emerging in the form…

12. Regression toward the mean – a detection method for unknown population mean based on Mee and Chua's algorithm

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Lüdtke Rainer

2008-08-01

Full Text Available Abstract Background Regression to the mean (RTM occurs in situations of repeated measurements when extreme values are followed by measurements in the same subjects that are closer to the mean of the basic population. In uncontrolled studies such changes are likely to be interpreted as a real treatment effect. Methods Several statistical approaches have been developed to analyse such situations, including the algorithm of Mee and Chua which assumes a known population mean μ. We extend this approach to a situation where μ is unknown and suggest to vary it systematically over a range of reasonable values. Using differential calculus we provide formulas to estimate the range of μ where treatment effects are likely to occur when RTM is present. Results We successfully applied our method to three real world examples denoting situations when (a no treatment effect can be confirmed regardless which μ is true, (b when a treatment effect must be assumed independent from the true μ and (c in the appraisal of results of uncontrolled studies. Conclusion Our method can be used to separate the wheat from the chaff in situations, when one has to interpret the results of uncontrolled studies. In meta-analysis, health-technology reports or systematic reviews this approach may be helpful to clarify the evidence given from uncontrolled observational studies.

13. Traditional methods v. new technologies – dilemmas for dietary assessment in large-scale nutrition surveys and studies

DEFF Research Database (Denmark)

Amoutzopoulos, B.; Steer, T.; Roberts, C.

2018-01-01

assessment in population surveys’, was held at the 9th International Conference on Diet and Activity Methods (ICDAM9), Brisbane, September 2015. Despite respondent and researcher burden, traditional methods have been most commonly used in nutrition surveys. However, dietary assessment technologies offer...... of traditional dietary assessment methods (food records, FFQ, 24 h recalls, diet history with interviewer-assisted data collection) v. new technology-based dietary assessment methods (web-based and mobile device applications). The panel discussion ‘Traditional methods v. new technologies: dilemmas for dietary......The aim of the present paper is to summarise current and future applications of dietary assessment technologies in nutrition surveys in developed countries. It includes the discussion of key points and highlights of subsequent developments from a panel discussion to address strengths and weaknesses...

14. Regression analysis by example

CERN Document Server

Chatterjee, Samprit

2012-01-01

Praise for the Fourth Edition: ""This book is . . . an excellent source of examples for regression analysis. It has been and still is readily readable and understandable."" -Journal of the American Statistical Association Regression analysis is a conceptually simple method for investigating relationships among variables. Carrying out a successful application of regression analysis, however, requires a balance of theoretical results, empirical rules, and subjective judgment. Regression Analysis by Example, Fifth Edition has been expanded

15. Exploring the Ligand-Protein Networks in Traditional Chinese Medicine: Current Databases, Methods, and Applications

Directory of Open Access Journals (Sweden)

Mingzhu Zhao

2013-01-01

Full Text Available The traditional Chinese medicine (TCM, which has thousands of years of clinical application among China and other Asian countries, is the pioneer of the “multicomponent-multitarget” and network pharmacology. Although there is no doubt of the efficacy, it is difficult to elucidate convincing underlying mechanism of TCM due to its complex composition and unclear pharmacology. The use of ligand-protein networks has been gaining significant value in the history of drug discovery while its application in TCM is still in its early stage. This paper firstly surveys TCM databases for virtual screening that have been greatly expanded in size and data diversity in recent years. On that basis, different screening methods and strategies for identifying active ingredients and targets of TCM are outlined based on the amount of network information available, both on sides of ligand bioactivity and the protein structures. Furthermore, applications of successful in silico target identification attempts are discussed in detail along with experiments in exploring the ligand-protein networks of TCM. Finally, it will be concluded that the prospective application of ligand-protein networks can be used not only to predict protein targets of a small molecule, but also to explore the mode of action of TCM.

16. Interobserver Reliability of Four Diagnostic Methods Using Traditional Korean Medicine for Stroke Patients

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Ju Ah Lee

2014-01-01

Full Text Available Objective. The aim of this study is to evaluate the consistency of pattern identification (PI, a set of diagnostic indicators used by traditional Korean medicine (TKM clinicians. Methods. A total of 168 stroke patients who were admitted into oriental medical university hospitals from June 2012 through January 2013 were included in the study. Using the PI indicators, each patient was independently diagnosed by two experts from the same department. Interobserver consistency was assessed by simple percentage agreement as well as by kappa and AC1 statistics. Results. Interobserver agreement on the PI indicators (for all patients was generally high: pulse diagnosis signs (AC1=0.66–0.89; inspection signs (AC1=0.66–0.95; listening/smelling signs (AC1=0.67–0.88; and inquiry signs (AC1=0.62–0.94. Conclusion. In four examinations, there was moderate agreement between the clinicians on the PI indicators. To improve clinician consistency (e.g., in the diagnostic criteria used, it is necessary to analyze the reasons for inconsistency and to improve clinician training.

17. Application methods of infrared thermal images in the health care field of traditional Chinese medicine

Science.gov (United States)

Li, Ziru; Zhang, Xusheng

2008-12-01

Infrared thermal imaging (ITI) is the potential imaging technique for the health care field of traditional Chinese medicine (TCM). Successful application demands obeying the characteristics and regularity of the ITI of human body and designing rigorous trials. First, the influence of time must be taken into account as the ITI of human body varies with time markedly. Second, relative magnitude is preferred to be the index of the image features. Third, scatter diagrams and the method of least square could present important information for evaluating the health care effect. A double-blind placebo-controlled randomized trial was undertaken to study the influences of Shengsheng capsule, one of the TCM health food with immunity adjustment function, on the ITI of human body. The results showed that the effect of Shengsheng capsule to people with weak constitution or in the period of being weak could be reflected objectively by ITI. The relative efficacy rate was 81.3% for the trial group and 30.0% for the control group, there was significant difference between the two groups (P=0.003). So the sensitivity and objectivity of ITI are of great importance to the health care field of TCM.

18. Cultural continuity, traditional Indigenous language, and diabetes in Alberta First Nations: a mixed methods study.

Science.gov (United States)

Oster, Richard T; Grier, Angela; Lightning, Rick; Mayan, Maria J; Toth, Ellen L

2014-10-19

We used an exploratory sequential mixed methods approach to study the association between cultural continuity, self-determination, and diabetes prevalence in First Nations in Alberta, Canada. We conducted a qualitative description where we interviewed 10 Cree and Blackfoot leaders (members of Chief and Council) from across the province to understand cultural continuity, self-determination, and their relationship to health and diabetes, in the Alberta First Nations context. Based on the qualitative findings, we then conducted a cross-sectional analysis using provincial administrative data and publically available data for 31 First Nations communities to quantitatively examine any relationship between cultural continuity and diabetes prevalence. Cultural continuity, or "being who we are", is foundational to health in successful First Nations. Self-determination, or "being a self-sufficient Nation", stems from cultural continuity and is seriously compromised in today's Alberta Cree and Blackfoot Nations. Unfortunately, First Nations are in a continuous struggle with government policy. The intergenerational effects of colonization continue to impact the culture, which undermines the sense of self-determination, and contributes to diabetes and ill health. Crude diabetes prevalence varied dramatically among First Nations with values as low as 1.2% and as high as 18.3%. Those First Nations that appeared to have more cultural continuity (measured by traditional Indigenous language knowledge) had significantly lower diabetes prevalence after adjustment for socio-economic factors (p =0.007). First Nations that have been better able to preserve their culture may be relatively protected from diabetes.

19. Model creation of moving redox reaction boundary in agarose gel electrophoresis by traditional potassium permanganate method.

Science.gov (United States)

Xie, Hai-Yang; Liu, Qian; Li, Jia-Hao; Fan, Liu-Yin; Cao, Cheng-Xi

2013-02-21

A novel moving redox reaction boundary (MRRB) model was developed for studying electrophoretic behaviors of analytes involving redox reaction on the principle of moving reaction boundary (MRB). Traditional potassium permanganate method was used to create the boundary model in agarose gel electrophoresis because of the rapid reaction rate associated with MnO(4)(-) ions and Fe(2+) ions. MRB velocity equation was proposed to describe the general functional relationship between velocity of moving redox reaction boundary (V(MRRB)) and concentration of reactant, and can be extrapolated to similar MRB techniques. Parameters affecting the redox reaction boundary were investigated in detail. Under the selected conditions, good linear relationship between boundary movement distance and time were obtained. The potential application of MRRB in electromigration redox reaction titration was performed in two different concentration levels. The precision of the V(MRRB) was studied and the relative standard deviations were below 8.1%, illustrating the good repeatability achieved in this experiment. The proposed MRRB model enriches the MRB theory and also provides a feasible realization of manual control of redox reaction process in electrophoretic analysis.

20. Assessing Knowledge Retention of an Immersive Serious Game vs. a Traditional Education Method in Aviation Safety.

Science.gov (United States)

Chittaro, Luca; Buttussi, Fabio

2015-04-01

Thanks to the increasing availability of consumer head-mounted displays, educational applications of immersive VR could now reach to the general public, especially if they include gaming elements (immersive serious games). Safety education of citizens could be a particularly promising domain for immersive serious games, because people tend not to pay attention to and benefit from current safety materials. In this paper, we propose an HMD-based immersive game for educating passengers about aviation safety that allows players to experience a serious aircraft emergency with the goal of surviving it. We compare the proposed approach to a traditional aviation safety education method (the safety card) used by airlines. Unlike most studies of VR for safety knowledge acquisition, we do not focus only on assessing learning immediately after the experience but we extend our attention to knowledge retention over a longer time span. This is a fundamental requirement, because people need to retain safety procedures in order to apply them when faced with danger. A knowledge test administered before, immediately after and one week after the experimental condition showed that the immersive serious game was superior to the safety card. Moreover, subjective as well as physiological measurements employed in the study showed that the immersive serious game was more engaging and fear-arousing than the safety card, a factor that can contribute to explain the obtained superior retention, as we discuss in the paper.

1. Projected regression method for solving Fredholm integral equations arising in the analytic continuation problem of quantum physics

International Nuclear Information System (INIS)

Arsenault, Louis-François; Millis, Andrew J; Neuberg, Richard; Hannah, Lauren A

2017-01-01

We present a supervised machine learning approach to the inversion of Fredholm integrals of the first kind as they arise, for example, in the analytic continuation problem of quantum many-body physics. The approach provides a natural regularization for the ill-conditioned inverse of the Fredholm kernel, as well as an efficient and stable treatment of constraints. The key observation is that the stability of the forward problem permits the construction of a large database of outputs for physically meaningful inputs. Applying machine learning to this database generates a regression function of controlled complexity, which returns approximate solutions for previously unseen inputs; the approximate solutions are then projected onto the subspace of functions satisfying relevant constraints. Under standard error metrics the method performs as well or better than the Maximum Entropy method for low input noise and is substantially more robust to increased input noise. We suggest that the methodology will be similarly effective for other problems involving a formally ill-conditioned inversion of an integral operator, provided that the forward problem can be efficiently solved. (paper)

2. Bayesian logistic regression analysis

NARCIS (Netherlands)

Van Erp, H.R.N.; Van Gelder, P.H.A.J.M.

2012-01-01

In this paper we present a Bayesian logistic regression analysis. It is found that if one wishes to derive the posterior distribution of the probability of some event, then, together with the traditional Bayes Theorem and the integrating out of nuissance parameters, the Jacobian transformation is an

3. Comparative Study of Powdered Ginger Drink Processed by Different Method:Traditional and using Evaporation Machine

Science.gov (United States)

Apriyana, Wuri; Taufika Rosyida, Vita; Nur Hayati, Septi; Darsih, Cici; Dewi Poeloengasih, Crescentiana

2017-12-01

Ginger drink is one of the traditional beverage that became one of the products of interest by consumers in Indonesia. This drink is believed to have excellent properties for the health of the body. In this study, we have compared the moisture content, ash content, metal content and the identified compound of product which processed with traditional technique and using an evaporator machine. The results show that both of products fulfilled some parameters of the Indonesian National Standard for the traditional powdered drink. GC-MS analysis data showed the identified compound of both product. The major of hydrocarbon groups that influenced the flavor such as zingiberene, camphene, beta-phelladrine, beta-sesquepelladrine, curcumene, and beta-bisabolene were found higher in ginger drink powder treated with a machine than those processed traditionally.

4. Hydraulic transmissivity determination for the groundwater exploration using vertical electric sounding method in comparison to the traditional methods

International Nuclear Information System (INIS)

2013-01-01

An important aquifer characteristic, transmissivity significantly contributes to the development of local and regional groundwater resources and solute transport management. Estimation of this property allows quantitative prediction of the hydraulic response and solute transport of the aquifer to recharge and pumping. This study presents the three techniques, used to compare transmissivity determination by Vertical Electric Sounding (VES) over the traditional techniques. The validation of VES was compared with the old widely used methods such as grain size distribution and pumping test techniques. Grain size distribution analysis was carried out to determine transmissivity. Pumping test was performed to determine transmissivity using the type curves solution for unconfined aquifer and taking into account the delayed yield. In resistivity imaging survey, the soil layers were detected through interpretation of resistivity data. Formation factor for each layer was determined with the relation of aquifer soil resistivity and ground water resistivity. The estimated transmissivities though grain size distribution, pumping test and resistivity survey were 0.588, 0.578 and 0.756m/sup 2//min, respectively. The results emphasized the potential of the resistivity survey for aquifer transmissivity determination. (author)

5. Development of nondestructive detection method for adulterated powder products using Raman spectroscopy and partial least squares regression

Energy Technology Data Exchange (ETDEWEB)

Lee, Sang Dae; Lohumi, Santosh; Cho, Byoung Kwan [Dept. of Biosystems Machinery Engineering, Chungnam National University, Daejeon (Korea, Republic of); Kim, Moon Sung [United States Department of Agriculture Agricultural Research Service, Washington (United States); Lee, Soo Hee [Life and Technology Co.,Ltd., Hwasung (Korea, Republic of)

2014-08-15

This study was conducted to develop a non-destructive detection method for adulterated powder products using Raman spectroscopy and partial least squares regression(PLSR). Garlic and ginger powder, which are used as natural seasoning and in health supplement foods, were selected for this experiment. Samples were adulterated with corn starch in concentrations of 5-35%. PLSR models for adulterated garlic and ginger powders were developed and their performances evaluated using cross validation. The R{sup 2}{sub c} and SEC of an optimal PLSR model were 0.99 and 2.16 for the garlic powder samples, and 0.99 and 0.84 for the ginger samples, respectively. The variable importance in projection (VIP) score is a useful and simple tool for the evaluation of the importance of each variable in a PLSR model. After the VIP scores were taken pre-selection, the Raman spectrum data was reduced by one third. New PLSR models, based on a reduced number of wavelengths selected by the VIP scores technique, gave good predictions for the adulterated garlic and ginger powder samples.

6. Large scale air pollution estimation method combining land use regression and chemical transport modeling in a geostatistical framework.

Science.gov (United States)

Akita, Yasuyuki; Baldasano, Jose M; Beelen, Rob; Cirach, Marta; de Hoogh, Kees; Hoek, Gerard; Nieuwenhuijsen, Mark; Serre, Marc L; de Nazelle, Audrey

2014-04-15

In recognition that intraurban exposure gradients may be as large as between-city variations, recent air pollution epidemiologic studies have become increasingly interested in capturing within-city exposure gradients. In addition, because of the rapidly accumulating health data, recent studies also need to handle large study populations distributed over large geographic domains. Even though several modeling approaches have been introduced, a consistent modeling framework capturing within-city exposure variability and applicable to large geographic domains is still missing. To address these needs, we proposed a modeling framework based on the Bayesian Maximum Entropy method that integrates monitoring data and outputs from existing air quality models based on Land Use Regression (LUR) and Chemical Transport Models (CTM). The framework was applied to estimate the yearly average NO2 concentrations over the region of Catalunya in Spain. By jointly accounting for the global scale variability in the concentration from the output of CTM and the intraurban scale variability through LUR model output, the proposed framework outperformed more conventional approaches.

7. Development of nondestructive detection method for adulterated powder products using Raman spectroscopy and partial least squares regression

International Nuclear Information System (INIS)

Lee, Sang Dae; Lohumi, Santosh; Cho, Byoung Kwan; Kim, Moon Sung; Lee, Soo Hee

2014-01-01

This study was conducted to develop a non-destructive detection method for adulterated powder products using Raman spectroscopy and partial least squares regression(PLSR). Garlic and ginger powder, which are used as natural seasoning and in health supplement foods, were selected for this experiment. Samples were adulterated with corn starch in concentrations of 5-35%. PLSR models for adulterated garlic and ginger powders were developed and their performances evaluated using cross validation. The R 2 c and SEC of an optimal PLSR model were 0.99 and 2.16 for the garlic powder samples, and 0.99 and 0.84 for the ginger samples, respectively. The variable importance in projection (VIP) score is a useful and simple tool for the evaluation of the importance of each variable in a PLSR model. After the VIP scores were taken pre-selection, the Raman spectrum data was reduced by one third. New PLSR models, based on a reduced number of wavelengths selected by the VIP scores technique, gave good predictions for the adulterated garlic and ginger powder samples.

8. Autistic Regression

Science.gov (United States)

Matson, Johnny L.; Kozlowski, Alison M.

2010-01-01

Autistic regression is one of the many mysteries in the developmental course of autism and pervasive developmental disorders not otherwise specified (PDD-NOS). Various definitions of this phenomenon have been used, further clouding the study of the topic. Despite this problem, some efforts at establishing prevalence have been made. The purpose of…

9. A Comparison of Kernel Equating and Traditional Equipercentile Equating Methods and the Parametric Bootstrap Methods for Estimating Standard Errors in Equipercentile Equating

Science.gov (United States)

Choi, Sae Il

2009-01-01

This study used simulation (a) to compare the kernel equating method to traditional equipercentile equating methods under the equivalent-groups (EG) design and the nonequivalent-groups with anchor test (NEAT) design and (b) to apply the parametric bootstrap method for estimating standard errors of equating. A two-parameter logistic item response…

10. The Use Potential of Traditional Building Materials for the Realization of Structures by Modern Methods of Construction

Science.gov (United States)

Spišáková, Marcela; Mačková, Daniela

2015-11-01

The sustainable building has taken off in recent years with many investors looking for new and different methods of construction. The traditional building materials can be made out of natural materials, while others can help to lower energy costs of the occupant once built. Regardless of what the goal of the investor is, traditional building materials and their use is on the rise. The submitted paper provides an overview of natural building materials and possible modern building systems using these construction materials. Based on the questionnaire survey is defined the use potential of traditional building materials for the realization of the construction by methods of modern constructions and then are determined the drivers and barriers of traditional materials through using modern methods of construction. Considering the analysis of the achieved results, we can identify the gaps in the construction market in Slovakia and also to assess the perception of potential investors in the field of traditional building materials use, which is the purpose of submitted paper.

11. The Use Potential of Traditional Building Materials for the Realization of Structures by Modern Methods of Construction

Directory of Open Access Journals (Sweden)

Spišáková Marcela

2015-11-01

Full Text Available The sustainable building has taken off in recent years with many investors looking for new and different methods of construction. The traditional building materials can be made out of natural materials, while others can help to lower energy costs of the occupant once built. Regardless of what the goal of the investor is, traditional building materials and their use is on the rise. The submitted paper provides an overview of natural building materials and possible modern building systems using these construction materials. Based on the questionnaire survey is defined the use potential of traditional building materials for the realization of the construction by methods of modern constructions and then are determined the drivers and barriers of traditional materials through using modern methods of construction. Considering the analysis of the achieved results, we can identify the gaps in the construction market in Slovakia and also to assess the perception of potential investors in the field of traditional building materials use, which is the purpose of submitted paper.

12. H0 from cosmic chronometers and Type Ia supernovae, with Gaussian Processes and the novel Weighted Polynomial Regression method

Science.gov (United States)

2018-04-01

In this paper we present new constraints on the Hubble parameter H0 using: (i) the available data on H(z) obtained from cosmic chronometers (CCH); (ii) the Hubble rate data points extracted from the supernovae of Type Ia (SnIa) of the Pantheon compilation and the Hubble Space Telescope (HST) CANDELS and CLASH Multy-Cycle Treasury (MCT) programs; and (iii) the local HST measurement of H0 provided by Riess et al. (2018), H0HST=(73.45±1.66) km/s/Mpc. Various determinations of H0 using the Gaussian processes (GPs) method and the most updated list of CCH data have been recently provided by Yu, Ratra & Wang (2018). Using the Gaussian kernel they find H0=(67.42± 4.75) km/s/Mpc. Here we extend their analysis to also include the most released and complete set of SnIa data, which allows us to reduce the uncertainty by a factor ~ 3 with respect to the result found by only considering the CCH information. We obtain H0=(67.06± 1.68) km/s/Mpc, which favors again the lower range of values for H0 and is in tension with H0HST. The tension reaches the 2.71σ level. We round off the GPs determination too by taking also into account the error propagation of the kernel hyperparameters when the CCH with and without H0HST are used in the analysis. In addition, we present a novel method to reconstruct functions from data, which consists in a weighted sum of polynomial regressions (WPR). We apply it from a cosmographic perspective to reconstruct H(z) and estimate H0 from CCH and SnIa measurements. The result obtained with this method, H0=(68.90± 1.96) km/s/Mpc, is fully compatible with the GPs ones. Finally, a more conservative GPs+WPR value is also provided, H0=(68.45± 2.00) km/s/Mpc, which is still almost 2σ away from H0HST.

13. Traditional versus Contemporary Goals and Methods in Accounting Education: Bridging the Gap with Cooperative Learning.

Science.gov (United States)

Lindquist, Tim M.

1995-01-01

In groups, 49 accounting students completed a 5-week analysis of audit reporting issues using cooperative learning. Positive student reactions and achievement suggested that contemporary active learning approaches are compatible with the traditional accounting goal of preparing for the Certified Public Accountants examination. (SK)

14. Current Status of Surgical Planning for Orthognathic Surgery: Traditional Methods versus 3D Surgical Planning

Directory of Open Access Journals (Sweden)

Jeffrey A. Hammoudeh, MD, DDS

2015-02-01

Conclusions: It is our opinion that virtual model surgery will displace and replace traditional model surgery as it will become cost and time effective in both the private and academic setting for practitioners providing orthognathic surgical care in cleft and noncleft patients.

15. A Follow-up Study of Two Methods of Teaching Mathematics: Traditional versus New Math

Science.gov (United States)

Walton, Gene A.; And Others

1977-01-01

When high school mathematics grades and test scores were analyzed, findings showed that high- and middle-ability students who had a modern mathematics course in the seventh grade received significantly higher grades in Algebra I, II, III, and Geometry than did students who had a traditional seventh grade mathematics course. (DT)

16. A Comparison of Traditional and Cooperative Learning Methods in Online Learning

Science.gov (United States)

Kupczynski, Lori; Mundy, Marie-Anne; Ruiz, Alberto

2013-01-01

The purpose of this study was to examine the effects of the Community of Inquiry framework through an in-depth examination of learning comprised of teaching, social and cognitive presence in traditional versus cooperative online teaching at a community college. A total of 21 students participated in this study, with approximately 45% having taken…

17. Energy value of poultry byproduct meal and animal-vegetable oil blend for broiler chickens by the regression method.

Science.gov (United States)

2016-02-01

The energy values of poultry byproduct meal (PBM) and animal-vegetable oil blend (A-V blend) were determined in 2 experiments with 288 broiler chickens from d 19 to 25 post hatching. The birds were fed a starter diet from d 0 to 19 post hatching. In each experiment, 144 birds were grouped by weight into 8 replicates of cages with 6 birds per cage. There were 3 diets in each experiment consisting of one reference diet (RD) and 2 test diets (TD). The TD contained 2 levels of PBM (Exp. 1) or A-V blend (Exp. 2) that replaced the energy sources in the RD at 50 or 100 g/kg (Exp. 1) or 40 or 80 g/kg (Exp. 2) in such a way that the same ratio were maintained for energy ingredients across experimental diets. The ileal digestible energy (IDE), ME, and MEn of PBM and A-V blend were determined by the regression method. Dry matter of PBM and A-V blend were 984 and 999 g/kg; the gross energies were 5,284 and 9,604 kcal/kg of DM, respectively. Addition of PBM to the RD in Exp. 1 linearly decreased (P blend to the RD linearly increased (P blend as follows: IDE = 10,616x + 7.350, r(2) = 0.96; ME = 10,121x + 0.447, r(2) = 0.99; MEn = 10,124x + 2.425, r(2) = 0.99. These data indicate the respective IDE, ME, MEn values (kcal/kg of DM) of PBM evaluated to be 3,537, 3,805, and 3,278, and A-V blend evaluated to be 10,616, 10,121, and 10,124. © 2015 Poultry Science Association Inc.

18. A Comparison of Case Study and Traditional Teaching Methods for Improvement of Oral Communication and Critical-Thinking Skills

Science.gov (United States)

Noblitt, Lynnette; Vance, Diane E.; Smith, Michelle L. DePoy

2010-01-01

This study compares a traditional paper presentation approach and a case study method for the development and improvement of oral communication skills and critical-thinking skills in a class of junior forensic science majors. A rubric for rating performance in these skills was designed on the basis of the oral communication competencies developed…

19. A Comparative Study on Power Point Presentation and Traditional Lecture Method in Material Understandability, Effectiveness and Attitude

Science.gov (United States)

Sewasew, Daniel; Mengestle, Missaye; Abate, Gebeyehu

2015-01-01

The aim of this study was to compare PPT and traditional lecture method in material understandability, effectiveness and attitude among university students. Comparative descriptive survey research design was employed to answer the research questions raised. Four hundred and twenty nine participants were selected randomly using stratified sampling…

20. Traditional Mold Analysis Compared to a DNA-based Method of Mold Analysis with Applications in Asthmatics' Homes

Science.gov (United States)

Traditional environmental mold analysis is based-on microscopic observations and counting of mold structures collected from the air on a sticky surface or culturing of molds on growth media for identification and quantification. A DNA-based method of mold analysis called mol...

1. Field calibration of blowfly-derived DNA against traditional methods for assessing mammal diversity in tropical forests.

Science.gov (United States)

Lee, Ping-Shin; Gan, Han Ming; Clements, Gopalasamy Reuben; Wilson, John-James

2016-11-01

Mammal diversity assessments based on DNA derived from invertebrates have been suggested as alternatives to assessments based on traditional methods; however, no study has field-tested both approaches simultaneously. In Peninsular Malaysia, we calibrated the performance of mammal DNA derived from blowflies (Diptera: Calliphoridae) against traditional methods used to detect species. We first compared five methods (cage trapping, mist netting, hair trapping, scat collection, and blowfly-derived DNA) in a forest reserve with no recent reports of megafauna. Blowfly-derived DNA and mist netting detected the joint highest number of species (n = 6). Only one species was detected by multiple methods. Compared to the other methods, blowfly-derived DNA detected both volant and non-volant species. In another forest reserve, rich in megafauna, we calibrated blowfly-derived DNA against camera traps. Blowfly-derived DNA detected more species (n = 11) than camera traps (n = 9), with only one species detected by both methods. The rarefaction curve indicated that blowfly-derived DNA would continue to detect more species with greater sampling effort. With further calibration, blowfly-derived DNA may join the list of traditional field methods. Areas for further investigation include blowfly feeding and dispersal biology, primer biases, and the assembly of a comprehensive and taxonomically-consistent DNA barcode reference library.

2. A study on modeling nitrogen dioxide concentrations using land-use regression and conventionally used exposure assessment methods

Science.gov (United States)

Choi, Giehae; Bell, Michelle L.; Lee, Jong-Tae

2017-04-01

The land-use regression (LUR) approach to estimate the levels of ambient air pollutants is becoming popular due to its high validity in predicting small-area variations. However, only a few studies have been conducted in Asian countries, and much less research has been conducted on comparing the performances and applied estimates of different exposure assessments including LUR. The main objectives of the current study were to conduct nitrogen dioxide (NO2) exposure assessment with four methods including LUR in the Republic of Korea, to compare the model performances, and to estimate the empirical NO2 exposures of a cohort. The study population was defined as the year 2010 participants of a government-supported cohort established for bio-monitoring in Ulsan, Republic of Korea. The annual ambient NO2 exposures of the 969 study participants were estimated with LUR, nearest station, inverse distance weighting, and ordinary kriging. Modeling was based on the annual NO2 average, traffic-related data, land-use data, and altitude of the 13 regularly monitored stations. The final LUR model indicated that area of transportation, distance to residential area, and area of wetland were important predictors of NO2. The LUR model explained 85.8% of the variation observed in the 13 monitoring stations of the year 2009. The LUR model outperformed the others based on leave-one out cross-validation comparing the correlations and root-mean square error. All NO2 estimates ranged from 11.3-18.0 ppb, with that of LUR having the widest range. The NO2 exposure levels of the residents differed by demographics. However, the average was below the national annual guidelines of the Republic of Korea (30 ppb). The LUR models showed high performances in an industrial city in the Republic of Korea, despite the small sample size and limited data. Our findings suggest that the LUR method may be useful in similar settings in Asian countries where the target region is small and availability of data is

3. Festival of Curses: A Traditional Crime Control Method In Edo State –Nigeria

OpenAIRE

Rashidi Akanji Okunola; Adediran Daniel Ikuomola

2016-01-01

Festivals and ceremonies are part and parcel of African culture, usually in all its pump, merriment and pageantry. However, with the increasing wave of criminal activities in Nigeria especially in Edo state, festivals and ceremonies are being redefined and conceptualized in practice. Only recently a new festival ‘Festival of Curses’ was brought to the fore in combating crime in Edo state. The study therefore seeks to explain the festival as a traditional mechanism in crime control, the nature...

4. Modified Right Heart Contrast Echocardiography Versus Traditional Method in Diagnosis of Right-to-Left Shunt: A Comparative Study

OpenAIRE

Wang, Yi; Zeng, Jie; Yin, Lixue; Zhang, Mei; Hou, Dailun

2016-01-01

BACKGROUND: The purpose of this study was to evaluate the reliability, effectiveness, and safety of modified right heart contrast transthoracic echocardiography (cTTE) in comparison with the traditional method. MATERIAL AND METHODS: We performed a modified right heart cTTE using saline mixed with a small sample of patient's own blood. Samples were agitated with varying intensity. This study protocol involved microscopic analysis and patient evaluation. 1. Microscopic analysis: After two contr...

5. Active learning on the ward: outcomes from a comparative trial with traditional methods.

Science.gov (United States)

Melo Prado, Hegla; Hannois Falbo, Gilliatt; Rodrigues Falbo, Ana; Natal Figueirôa, José

2011-03-01

Academic activity during internship is essentially practical and ward rounds are traditionally considered the cornerstone of clinical education. However, the efficacy and effectiveness of ward rounds for learning purposes have been under-investigated and it is necessary to assess alternative educational paradigms for this activity. This study aimed to compare the educational effectiveness of ward rounds conducted with two different learning methodologies. Student subjects were first tested on 30 true/false questions to assess their initial degree of knowledge on pneumonia and diarrhoea. Afterwards, they attended ward rounds conducted using an active and a traditional learning methodology. The participants were submitted to a second test 48hours later in order to assess knowledge acquisition and were asked to answer two questions about self-directed learning and their opinions on the two learning methodologies used. Seventy-two medical students taking part in a paediatric clinic rotation were enrolled. The active methodology proved to be more effective than the traditional methodology for the three outcomes considered: knowledge acquisition (33 students [45.8%] versus 21 students [29.2%]; p=0.03); self-directed learning (38 students [52.8%] versus 11 students [15.3%]; pmethods (61 students [84.7%] versus 38 students [52.8%]; ptraditional methodology in a ward-based context. This study seems to be valuable in terms of the new evidence it demonstrates on learning methodologies in the context of the ward round. © Blackwell Publishing Ltd 2011.

6. Comparison Of Keyword Based Clustering Of Web Documents By Using Openstack 4j And By Traditional Method

Directory of Open Access Journals (Sweden)

Shiza Anand

2015-08-01

Full Text Available As the number of hypertext documents are increasing continuously day by day on world wide web. Therefore clustering methods will be required to bind documents into the clusters repositories according to the similarity lying between the documents. Various clustering methods exist such as Hierarchical Based K-means Fuzzy Logic Based Centroid Based etc. These keyword based clustering methods takes much more amount of time for creating containers and putting documents in their respective containers. These traditional methods use File Handling techniques of different programming languages for creating repositories and transferring web documents into these containers. In contrast openstack4j SDK is a new technique for creating containers and shifting web documents into these containers according to the similarity in much more less amount of time as compared to the traditional methods. Another benefit of this technique is that this SDK understands and reads all types of files such as jpg html pdf doc etc. This paper compares the time required for clustering of documents by using openstack4j and by traditional methods and suggests various search engines to adopt this technique for clustering so that they give result to the user querries in less amount of time.

7. [Method of traditional Chinese medicine formula design based on 3D-database pharmacophore search and patent retrieval].

Science.gov (United States)

He, Yu-su; Sun, Zhi-yi; Zhang, Yan-ling

2014-11-01

By using the pharmacophore model of mineralocorticoid receptor antagonists as a starting point, the experiment stud- ies the method of traditional Chinese medicine formula design for anti-hypertensive. Pharmacophore models were generated by 3D-QSAR pharmacophore (Hypogen) program of the DS3.5, based on the training set composed of 33 mineralocorticoid receptor antagonists. The best pharmacophore model consisted of two Hydrogen-bond acceptors, three Hydrophobic and four excluded volumes. Its correlation coefficient of training set and test set, N, and CAI value were 0.9534, 0.6748, 2.878, and 1.119. According to the database screening, 1700 active compounds from 86 source plant were obtained. Because of lacking of available anti-hypertensive medi cation strategy in traditional theory, this article takes advantage of patent retrieval in world traditional medicine patent database, in order to design drug formula. Finally, two formulae was obtained for antihypertensive.

8. Socio-economic comparison between traditional and improved cultivation methods in agroforestry systems, East Usambara Mountains, Tanzania.

Science.gov (United States)

Reyes, Teija; Quiroz, Roberto; Msikula, Shija

2005-11-01

The East Usambara Mountains, recognized as one of the 25 most important biodiversity hot spots in the world, have a high degree of species diversity and endemism that is threatened by increasing human pressure on resources. Traditional slash and burn cultivation in the area is no longer sustainable. However, it is possible to maintain land productivity, decrease land degradation, and improve rural people's livelihood by ameliorating cultivation methods. Improved agroforestry seems to be a very convincing and suitable method for buffer zones of conservation areas. Farmers could receive a reasonable net income from their farm with little investment in terms of time, capital, and labor. By increasing the diversity and production of already existing cultivations, the pressure on natural forests can be diminished. The present study shows a significant gap between traditional cultivation methods and improved agroforestry systems in socio-economic terms. Improved agroforestry systems provide approximately double income per capita in comparison to traditional methods. More intensified cash crop cultivation in the highlands of the East Usambara also results in double income compared to that in the lowlands. However, people are sensitive to risks of changing farming practices. Encouraging farmers to apply better land management and practice sustainable cultivation of cash crops in combination with multipurpose trees would be relevant in improving their economic situation in the relatively short term. The markets of most cash crops are already available. Improved agroforestry methods could ameliorate the living conditions of the local population and protect the natural reserves from human disturbance.

9. Paleodemographic age-at-death distributions of two Mexican skeletal collections: a comparison of transition analysis and traditional aging methods.

Science.gov (United States)

Bullock, Meggan; Márquez, Lourdes; Hernández, Patricia; Ruíz, Fernando

2013-09-01

10. Prediction, Regression and Critical Realism

DEFF Research Database (Denmark)

Næss, Petter

2004-01-01

This paper considers the possibility of prediction in land use planning, and the use of statistical research methods in analyses of relationships between urban form and travel behaviour. Influential writers within the tradition of critical realism reject the possibility of predicting social...... phenomena. This position is fundamentally problematic to public planning. Without at least some ability to predict the likely consequences of different proposals, the justification for public sector intervention into market mechanisms will be frail. Statistical methods like regression analyses are commonly...... seen as necessary in order to identify aggregate level effects of policy measures, but are questioned by many advocates of critical realist ontology. Using research into the relationship between urban structure and travel as an example, the paper discusses relevant research methods and the kinds...

11. Cultural Heritage Digitalization on Traditional Sundanese Music Instrument Using Augmented Reality Markerless Marker Method

Directory of Open Access Journals (Sweden)

Budi Arifitama

2017-07-01

Full Text Available Research into cultural heritage which implements augmented reality technology is limited. Most recent research on cultural heritage are limited on storing data and information in the form of databases, this creates a disadvantage for people who wants to see and feel at the same moment on actual cultural heritage objects. This paper, proposes a solution which could merge the existing cultural object with people using augmented reality technology. This technology would preserve traditional instrument in the form of 3D object which can be digitally protected. The result showed that the use of augmented reality on preserving cultural heritage would benefit people who try to protect their culture.

12. The critical assessment of research traditional and new methods of evaluation

CERN Document Server

Bailin, Alan

2010-01-01

This book examines the following factors: sponsorship of research, control of the dissemination of research, effects of dominant research paradigms, financial interests of authors, publishers, and editors, role of new technologies (for example, Web 2.0).It is widely accepted among researchers and educators that the peer review process, the reputation of the publisher and examination of the author's credentials are the gold standards for assessing the quality of research and information. However, the traditional gold standards are not sufficient, and the effective evaluation of information req

13. Regression and direct methods do not give different estimates of digestible and metabolizable energy values of barley, sorghum, and wheat for pigs.

Science.gov (United States)

2016-02-01

Direct or indirect methods can be used to determine the DE and ME of feed ingredients for pigs. In situations when only the indirect approach is suitable, the regression method presents a robust indirect approach. Three experiments were conducted to compare the direct and regression methods for determining the DE and ME values of barley, sorghum, and wheat for pigs. In each experiment, 24 barrows with an average initial BW of 31, 32, and 33 kg were assigned to 4 diets in a randomized complete block design. The 4 diets consisted of 969 g barley, sorghum, or wheat/kg plus minerals and vitamins for the direct method; a corn-soybean meal reference diet (RD); the RD + 300 g barley, sorghum, or wheat/kg; and the RD + 600 g barley, sorghum, or wheat/kg. The 3 corn-soybean meal diets were used for the regression method. Each diet was fed to 6 barrows in individual metabolism crates for a 5-d acclimation followed by a 5-d period of total but separate collection of feces and urine in each experiment. Graded substitution of barley or wheat, but not sorghum, into the RD linearly reduced ( direct method-derived DE and ME for barley were 3,669 and 3,593 kcal/kg DM, respectively. The regressions of barley contribution to DE and ME in kilocalories against the quantity of barley DMI in kilograms generated 3,746 kcal DE/kg DM and 3,647 kcal ME/kg DM. The DE and ME for sorghum by the direct method were 4,097 and 4,042 kcal/kg DM, respectively; the corresponding regression-derived estimates were 4,145 and 4,066 kcal/kg DM. Using the direct method, energy values for wheat were 3,953 kcal DE/kg DM and 3,889 kcal ME/kg DM. The regressions of wheat contribution to DE and ME in kilocalories against the quantity of wheat DMI in kilograms generated 3,960 kcal DE/kg DM and 3,874 kcal ME/kg DM. The DE and ME of barley using the direct method were not different (0.3 direct method-derived DE and ME of sorghum were not different (0.5 direct method- and regression method-derived DE (3,953 and 3

14. Deficiency of the Space Syntax method as an urban design tool in designing traditional urban space and the need for some supplementary methods

Directory of Open Access Journals (Sweden)

Hossein Bahrainy

2015-12-01

Full Text Available Urban design problems have become so complex that no single designer is able to consider all aspects of a design area simultaneously. Lately the application of computerized and scientific methods have helped designers analyze complex problems. One of these new methods is Space Syntax. The purpose of this study is to first investigate the strengths and weaknesses of this method and then suggest some supplementary methods to cover its pitfalls. On the next phase Space Syntax and supplementary methods will be used to design a pedestrian pathway in the Imamzade Ghasem neighborhood as a traditional context. Space Syntax will identify the existing spatial structure and direct future changes toward its strengthening. The case study reveals that Space Syntax can be successfully used in analysis of traditional spaces, but in order to successfully design a neighborhood in such a complex context, it involves logistical shortcomings which could be eliminated through supplementary methods.

15. Traditional methods used by patients for the management of recurrent aphthous stomatitis.

Directory of Open Access Journals (Sweden)

Shruthi Hegde

2017-12-01

Results: A total of 326 patients reported with RAS. The study sample consisted of 171 females (52.5% and 155 males (47.5%. In our study 198 subjects (60.7% gave history of receiving treatment and 128 subjects (39.3 % did not receive any kind of treatment. Out of the 198 subjects, 63(31.8% of individuals received conventional treatment, alternative treatments were opted by 85(43% patients and combined treatment modalities were opted by 50(25.2% patients. Over the counter medications were used by 36 (18% patients. Treatment outcome was satisfactory according to 137(69% individuals and treatment was not satisfactory for 61 (31% patients. Conclusion: This study gives insight into the various traditional medicines used in south India for RAS and to the best of our knowledge, this is first study which describes the same. Our study adds new information to the current literature about traditional medications for RAS. [J Complement Med Res 2017; 6(4.000: 364-368

16. Panel presentation: Should some type of incentive regulation replace traditional methods for regulating LDC's?

International Nuclear Information System (INIS)

Farman, R.D.

1992-01-01

This paper discusses the wants and fears of gas utility companies with regards to incentive regulation. The idea of replacing the traditional rate-of-return regulation with incentive regulation sound very desirous in that it should provide greater management flexibility, quicker and more streamlined regulatory processes, and utility financial rewards based on how well customer needs are met. However, the main fear is that this could result in arbitrary, inappropriate productivity or efficiency targets, or would embody a risk/reward ratio skewed more heavily toward financial penalties than opportunities to increase earnings. The paper presents some of the obstacles of traditional regulation which include a lack of incentive to minimize operational costs; a lack of incentive to introduce new technology, products, or services; prevent the need for flexibility to compete in contestable markets; and the diversion caused by utility managers having to manage the regulatory process rather than delivering value to customers. The paper concludes by comparing the incentive regulation program used in the telecommunications industry to the natural gas industry to demonstrate why the success of the telecommunications model doesn't apply to the gas utilities incentive model

17. Traditional Methods which are Known and Applied in order to Achieve Voluntary Abortion by Married Women Living in Elazig.

Directory of Open Access Journals (Sweden)

Feyza (Nazik Sevindik

2007-10-01

Full Text Available This study have been performed in order to describe traditional methods which are known and applied for achieving voluntary abortion by married women living in downtown of Elazig. 426 women have been selected rely on the fifteen years old and married by the represantive 67500 living women in the downtown Elazig. It has been reached to 417 women at repetetive visits. Mean age of women is 36,39±10,26, first pregnancy years are 19,96±4,99, first birth age is 20,02±6,05. Numbers of avarage pregnancy are 3,61±0,12, numbers of voluntary abortion is 0,32±0,04. Voluntary abortion rate is %18,2. %93 of women have stated that they know at least one traditional abortion method, and %19,7 of women declared that they used traditional abortion methods. %14,9 of them stated that they lift a heavy furniture or goods, while %8,2 drink flu drug and asprin, %11,3 jump rope and jump by shaking from high where, %4,8 put a poultry quill, matchstick and knitting needle into uterus, %3,6 put a mallow or aubergine root into uterus servicks, %2,6 drink a boiled quinine henna and mallow, %3,1 sit into vapour of boiled straw or parsley by milk during stomacache, and %10,8 shake a carpet. As education level of women decrase, usage of traditional abortion methods increase (p=0,001. In order to decrease the use of these unsafe methods, public education, increasing usage of family planning services, and prevention of unwanted pregnancies should be obtained. [TAF Prev Med Bull 2007; 6(5.000: 321-324

18. Traditional Methods which are Known and Applied in order to Achieve Voluntary Abortion by Married Women Living in Elazig.

Directory of Open Access Journals (Sweden)

Feyza (Nazik Sevindik

2007-10-01

Full Text Available This study have been performed in order to describe traditional methods which are known and applied for achieving voluntary abortion by married women living in downtown of Elazig. 426 women have been selected rely on the fifteen years old and married by the represantive 67500 living women in the downtown Elazig. It has been reached to 417 women at repetetive visits. Mean age of women is 36,39±10,26, first pregnancy years are 19,96±4,99, first birth age is 20,02±6,05. Numbers of avarage pregnancy are 3,61±0,12, numbers of voluntary abortion is 0,32±0,04. Voluntary abortion rate is %18,2. %93 of women have stated that they know at least one traditional abortion method, and %19,7 of women declared that they used traditional abortion methods. %14,9 of them stated that they lift a heavy furniture or goods, while %8,2 drink flu drug and asprin, %11,3 jump rope and jump by shaking from high where, %4,8 put a poultry quill, matchstick and knitting needle into uterus, %3,6 put a mallow or aubergine root into uterus servicks, %2,6 drink a boiled quinine henna and mallow, %3,1 sit into vapour of boiled straw or parsley by milk during stomacache, and %10,8 shake a carpet. As education level of women decrase, usage of traditional abortion methods increase (p=0,001. In order to decrease the use of these unsafe methods, public education, increasing usage of family planning services, and prevention of unwanted pregnancies should be obtained. [TAF Prev Med Bull. 2007; 6(5: 321-324

19. Discriminative Elastic-Net Regularized Linear Regression.

Science.gov (United States)

Zhang, Zheng; Lai, Zhihui; Xu, Yong; Shao, Ling; Wu, Jian; Xie, Guo-Sen

2017-03-01

In this paper, we aim at learning compact and discriminative linear regression models. Linear regression has been widely used in different problems. However, most of the existing linear regression methods exploit the conventional zero-one matrix as the regression targets, which greatly narrows the flexibility of the regression model. Another major limitation of these methods is that the learned projection matrix fails to precisely project the image features to the target space due to their weak discriminative capability. To this end, we present an elastic-net regularized linear regression (ENLR) framework, and develop two robust linear regression models which possess the following special characteristics. First, our methods exploit two particular strategies to enlarge the margins of different classes by relaxing the strict binary targets into a more feasible variable matrix. Second, a robust elastic-net regularization of singular values is introduced to enhance the compactness and effectiveness of the learned projection matrix. Third, the resulting optimization problem of ENLR has a closed-form solution in each iteration, which can be solved efficiently. Finally, rather than directly exploiting the projection matrix for recognition, our methods employ the transformed features as the new discriminate representations to make final image classification. Compared with the traditional linear regression model and some of its variants, our method is much more accurate in image classification. Extensive experiments conducted on publicly available data sets well demonstrate that the proposed framework can outperform the state-of-the-art methods. The MATLAB codes of our methods can be available at http://www.yongxu.org/lunwen.html.

20. Remote-sensing data processing with the multivariate regression analysis method for iron mineral resource potential mapping: a case study in the Sarvian area, central Iran

Science.gov (United States)

Mansouri, Edris; Feizi, Faranak; Jafari Rad, Alireza; Arian, Mehran

2018-03-01

This paper uses multivariate regression to create a mathematical model for iron skarn exploration in the Sarvian area, central Iran, using multivariate regression for mineral prospectivity mapping (MPM). The main target of this paper is to apply multivariate regression analysis (as an MPM method) to map iron outcrops in the northeastern part of the study area in order to discover new iron deposits in other parts of the study area. Two types of multivariate regression models using two linear equations were employed to discover new mineral deposits. This method is one of the reliable methods for processing satellite images. ASTER satellite images (14 bands) were used as unique independent variables (UIVs), and iron outcrops were mapped as dependent variables for MPM. According to the results of the probability value (p value), coefficient of determination value (R2) and adjusted determination coefficient (Radj2), the second regression model (which consistent of multiple UIVs) fitted better than other models. The accuracy of the model was confirmed by iron outcrops map and geological observation. Based on field observation, iron mineralization occurs at the contact of limestone and intrusive rocks (skarn type).

1. Improving validation methods for molecular diagnostics: application of Bland-Altman, Deming and simple linear regression analyses in assay comparison and evaluation for next-generation sequencing.

Science.gov (United States)

Misyura, Maksym; Sukhai, Mahadeo A; Kulasignam, Vathany; Zhang, Tong; Kamel-Reid, Suzanne; Stockley, Tracy L

2018-02-01

A standard approach in test evaluation is to compare results of the assay in validation to results from previously validated methods. For quantitative molecular diagnostic assays, comparison of test values is often performed using simple linear regression and the coefficient of determination (R 2 ), using R 2 as the primary metric of assay agreement. However, the use of R 2 alone does not adequately quantify constant or proportional errors required for optimal test evaluation. More extensive statistical approaches, such as Bland-Altman and expanded interpretation of linear regression methods, can be used to more thoroughly compare data from quantitative molecular assays. We present the application of Bland-Altman and linear regression statistical methods to evaluate quantitative outputs from next-generation sequencing assays (NGS). NGS-derived data sets from assay validation experiments were used to demonstrate the utility of the statistical methods. Both Bland-Altman and linear regression were able to detect the presence and magnitude of constant and proportional error in quantitative values of NGS data. Deming linear regression was used in the context of assay comparison studies, while simple linear regression was used to analyse serial dilution data. Bland-Altman statistical approach was also adapted to quantify assay accuracy, including constant and proportional errors, and precision where theoretical and empirical values were known. The complementary application of the statistical methods described in this manuscript enables more extensive evaluation of performance characteristics of quantitative molecular assays, prior to implementation in the clinical molecular laboratory. © Article author(s) (or their employer(s) unless otherwise stated in the text of the article) 2018. All rights reserved. No commercial use is permitted unless otherwise expressly granted.

2. The comparison of solar water heating system operation parameters calculated using traditional method and dynamic simulations

Directory of Open Access Journals (Sweden)

Sornek Krzysztof

2016-01-01

Full Text Available The proper design of renewable energy based systems is really important to provide their efficient and safe operation. The aim of this paper is to compare the results obtained during traditional static calculations, with the results of dynamic simulations. For this reason, simulations of solar water heating (SWH system, designed for a typical residential building, were conducted in the TRNSYS (Transient System Simulation Tool. Carried out calculations allowed to determine the heat generation in the discussed system as well as to estimate the efficiency of considered installation. Obtained results were compared with the results from other available tool based on the static calculations. It may be concluded, that using dynamic simulations at the designing stage of renewable energy based systems may help to avoid many exploitation problems (including low efficiency, overheating etc. and allows to provide safe exploitation of such installations.

3. Protein extraction method for the proteomic study of a Mexican traditional fermented starchy food.

Science.gov (United States)

Cárdenas, C; Barkla, B J; Wacher, C; Delgado-Olivares, L; Rodríguez-Sanoja, R

2014-12-05

Pozol is a traditional fermented maize dough prepared in southeastern Mexico. Wide varieties of microorganisms have already been isolated from this spontaneously fermented product; and include fungi, yeasts, and lactic- and non-lactic acid bacteria. Pozol presents physicochemical features different from that of other food fermentation products, such as a high starch content, in addition to a low protein content. It is these qualities that make it intractable for protein recovery and characterization. The aim of this study was to develop a methodology to optimize the recovery of proteins from the pozol dough following fermentation, by reducing the complexity of the mixture prior to 2D-PAGE analysis and sequencing, to allow the characterization of the metaproteome of the dough. The proteome of 15day fermented maize dough was characterized; proteins were separated and analyzed by mass spectrometry (LC-MS/MS). Subsequent sequence homology database searching, identified numerous bacterial and fungi proteins; with a predominance of lactic acid bacterial proteins, mainly from the Lactobacillus genus. Fungi are mainly represented by Aspergillus. For dominant genera, the most prevalent proteins belong to carbohydrate metabolism and energy production, which suggest that at 15days of fermentation not only fungi but also bacteria are metabolically active. Several methodologies have been employed to study pozol, with a specific focus toward the identification of the microbiota of this fermented maize dough, using both traditional cultivation techniques and culture independent molecular techniques. However to date, the dynamics of this complex fermentation is not well understood. With the purpose to gain further insight into the nature of the fermentation, we used proteomic technologies to identify the origin of proteins and enzymes that facilitate substrate utilization and ultimately the development of the microbiota and fermentation. In this paper we overcome the first general

4. Comparison of traditional methods with 3D computer models in the instruction of hepatobiliary anatomy.

Science.gov (United States)

Keedy, Alexander W; Durack, Jeremy C; Sandhu, Parmbir; Chen, Eric M; O'Sullivan, Patricia S; Breiman, Richard S

2011-01-01

This study was designed to determine whether an interactive three-dimensional presentation depicting liver and biliary anatomy is more effective for teaching medical students than a traditional textbook format presentation of the same material. Forty-six medical students volunteered for participation in this study. Baseline demographic information, spatial ability, and knowledge of relevant anatomy were measured. Participants were randomized into two groups and presented with a computer-based interactive learning module comprised of animations and still images to highlight various anatomical structures (3D group), or a computer-based text document containing the same images and text without animation or interactive features (2D group). Following each teaching module, students completed a satisfaction survey and nine-item anatomic knowledge post-test. The 3D group scored higher on the post-test than the 2D group, with a mean score of 74% and 64%, respectively; however, when baseline differences in pretest scores were accounted for, this difference was not statistically significant (P = 0.33). Spatial ability did not statistically significantly correlate with post-test scores for the 3D group or the 2D group. In the post-test satisfaction survey the 3D group expressed a statistically significantly higher overall satisfaction rating compared to students in the 2D control group (4.5 versus 3.7 out of 5, P = 0.02). While the interactive 3D multimedia module received higher satisfaction ratings from students, it neither enhanced nor inhibited learning of complex hepatobiliary anatomy compared to an informationally equivalent traditional textbook style approach. . Copyright © 2011 American Association of Anatomists.

5. Computerized tablet based versus traditional paper- based survey methods: results from adolescent's health research in schools of Maharashtra, India

OpenAIRE

Naveen Agarwal; Balram Paswan; Prakash H. Fulpagare; Dhirendra N Sinha; Thaksaphon Thamarangsi; Manju Rani

2018-01-01

Background and challenges to implementation Technological advancement is growing very fast in India and majority of young population is handling electronic devices often during leisure as well as at work. This study indicates that electronic tablets are less time consuming and improves survey response rate over the traditional paper-pencil survey method. Intervention or response An Android-based Global School-based Health Survey (GSHS) questionnaire was used with the...

6. How do Millennial Engineering and Technology Students Experience Learning Through Traditional Teaching Methods Employed in the University Setting?

OpenAIRE

Howard, Elizabeth A

2011-01-01

The purpose of the study was to document and analyze how Millennial engineering and technology students experience learning in large lecture classrooms. To help achieve this purpose, perceptions Millennials have toward traditional teaching methods employed in large lecture classes were analyzed and discussed. Additionally, this study documented how Millennials experienced technology within large lecture classrooms. A learning model depicting how Millennials experience learning within the larg...

7. Development and Psychometric Evaluation of the HPV Clinical Trial Survey for Parents (CTSP-HPV) Using Traditional Survey Development Methods and Community Engagement Principles.

Science.gov (United States)

Cunningham, Jennifer; Wallston, Kenneth A; Wilkins, Consuelo H; Hull, Pamela C; Miller, Stephania T

2015-12-01

This study describes the development and psychometric evaluation of HPV Clinical Trial Survey for Parents with Children Aged 9 to 15 (CTSP-HPV) using traditional instrument development methods and community engagement principles. An expert panel and parental input informed survey content and parents recommended study design changes (e.g., flyer wording). A convenience sample of 256 parents completed the final survey measuring parental willingness to consent to HPV clinical trial (CT) participation and other factors hypothesized to influence willingness (e.g., HPV vaccine benefits). Cronbach's a, Spearman correlations, and multiple linear regression were used to estimate internal consistency, convergent and discriminant validity, and predictively validity, respectively. Internal reliability was confirmed for all scales (a ≥ 0.70.). Parental willingness was positively associated (p < 0.05) with trust in medical researchers, adolescent CT knowledge, HPV vaccine benefits, advantages of adolescent CTs (r range 0.33-0.42), supporting convergent validity. Moderate discriminant construct validity was also demonstrated. Regression results indicate reasonable predictive validity with the six scales accounting for 31% of the variance in parents' willingness. This instrument can inform interventions based on factors that influence parental willingness, which may lead to the eventual increase in trial participation. Further psychometric testing is warranted. © 2015 Wiley Periodicals, Inc.

8. Running and Metabolic Demands of Elite Rugby Union Assessed Using Traditional, Metabolic Power, and Heart Rate Monitoring Methods

Science.gov (United States)

Dubois, Romain; Paillard, Thierry; Lyons, Mark; McGrath, David; Maurelli, Olivier; Prioux, Jacques

2017-01-01

The aims of this study were (1) to analyze elite rugby union game demands using 3 different approaches: traditional, metabolic and heart rate-based methods (2) to explore the relationship between these methods and (3) to explore positional differences between the backs and forwards players. Time motion analysis and game demands of fourteen professional players (24.1 ± 3.4 y), over 5 European challenge cup games, were analyzed. Thresholds of 14.4 km·h-1, 20 W.kg-1 and 85% of maximal heart rate (HRmax) were set for high-intensity efforts across the three methods. The mean % of HRmax was 80.6 ± 4.3 % while 42.2 ± 16.5% of game time was spent above 85% of HRmax with no significant differences between the forwards and the backs. Our findings also show that the backs cover greater distances at high-speed than forwards (% difference: +35.2 ± 6.6%; pdemands of professional rugby games. The traditional and the metabolic-power approaches shows a close correlation concerning their relative values, nevertheless the difference in absolute values especially for the high-intensity thresholds demonstrates that the metabolic power approach may represent an interesting alternative to the traditional approaches used in evaluating the high-intensity running efforts required in rugby union games. Key points Elite/professional rugby union players Heart rate monitoring during official games Metabolic power approach PMID:28344455

9. Is there still a role for traditional methods in the management of fractures of the zygomatic complex?

LENUS (Irish Health Repository)

O'Sullivan, S T

2012-02-03

With the introduction of low-profile mini-plating systems, a trend has developed towards open reduction and rigid internal fixation (ORIF) of fractures of the cranio-facial skeleton. The current policy for management of zygomatic fractures in our unit is to attempt primary reduction by traditional methods, and proceed to ORIF in the event of unsatisfactory fracture stability or alignment. Over a one-year period, 109 patients underwent surgical correction of fractures of the zygomatic complex. Standard Gilles\\' elevation was performed in 71 cases, percutaneous elevation in three cases, and ORIF was performed in 35 cases. Mean follow-up was 190 days. One case of persistent infraorbital step and three cases of residual malar flattening were documented in patients who underwent Gilles or percutaneous elevation. Morbidity associated with ORIF was minimal. We conclude that while ORIF of zygomatic fractures may offer better results than traditional methods in the management of complex fractures, traditional methods still have a role to play in less complex fractures.

10. A Survey of a System of Methods for Fire Safety Design of Traditional Concrete Constructions

DEFF Research Database (Denmark)

Hertz, Kristian

2000-01-01

constructions DS411. And the bases for many of the methods have been distributed by CIB W14 reports. But a survey of all the methods in coherence has never been presented, and much of this documentation and the additional documentation produced for the work with the codes needs still to be printed in papers......During the years since 1978 the author has been developing a series of calculation methods and sup-porting test methods for the fire safety design of concrete constructions. The basic methods have been adopted in the fire chapters of the Eurocode ENV1992-1-2 and the Danish code for concrete.......It is the aim of this paper to give a coherent presentation of the design methods, their degree of documentation and the available references in order to facilitate the application of them....

11. The Effect of Laboratory Training Model of Teaching and Traditional Method on Knowledge, Comprehension, Application, Skills-Components of Achievement, Total Achievement and Retention Level in Chemistry

Science.gov (United States)

2011-01-01

The present study aimed at finding the effectiveness of the Laboratory Training Model of Teaching (LTM) and comparing it with the traditional methods of teaching chemistry to seventh standard students. It strived to determine whether the (LTM) method in chemistry would be significantly more effective than the Traditional method in respect to the…

12. [Methodology of the description of atmospheric air pollution by nitrogen dioxide by land use regression method in Ekaterinburg].

Science.gov (United States)

Antropov, K M; Varaksin, A N

2013-01-01

This paper provides the description of Land Use Regression (LUR) modeling and the result of its application in the study of nitrogen dioxide air pollution in Ekaterinburg. The paper describes the difficulties of the modeling for air pollution caused by motor vehicles exhaust, and the ways to address these challenges. To create LUR model of the NO2 air pollution in Ekaterinburg, concentrations of NO2 were measured, data on factors affecting air pollution were collected, a statistical analysis of the data were held. A statistical model of NO2 air pollution (coefficient of determination R2 = 0.70) and a map of pollution were created.

13. Dynamics of contraceptive use in India: apprehension versus future intention among non-users and traditional method users.

Science.gov (United States)

Rai, Rajesh Kumar; Unisa, Sayeed

2013-06-01

This study examines the reasons for not using any method of contraception as well as reasons for not using modern methods of contraception, and factors associated with the future intention to use different types of contraceptives in India and its selected states, namely Uttar Pradesh, Assam and West Bengal. Data from the third wave of District Level Household and Facility Survey, 2007-08 were used. Bivariate as well as logistic regression analyses were performed to fulfill the study objective. Postpartum amenorrhea and breastfeeding practices were reported as the foremost causes for not using any method of contraception. Opposition to use, health concerns and fear of side effects were reported to be major hurdles in the way of using modern methods of contraception. Results from logistic regression suggest considerable variation in explaining the factors associated with future intention to use contraceptives. Promotion of health education addressing the advantages of contraceptive methods and eliminating apprehension about the use of these methods through effective communication by community level workers is the need of the hour. Copyright © 2013 Elsevier B.V. All rights reserved.

14. A comparative study of traditional lecture methods and interactive lecture methods in introductory geology courses for non-science majors at the college level

Science.gov (United States)

Hundley, Stacey A.

In recent years there has been a national call for reform in undergraduate science education. The goal of this reform movement in science education is to develop ways to improve undergraduate student learning with an emphasis on developing more effective teaching practices. Introductory science courses at the college level are generally taught using a traditional lecture format. Recent studies have shown incorporating active learning strategies within the traditional lecture classroom has positive effects on student outcomes. This study focuses on incorporating interactive teaching methods into the traditional lecture classroom to enhance student learning for non-science majors enrolled in introductory geology courses at a private university. Students' experience and instructional preferences regarding introductory geology courses were identified from survey data analysis. The information gained from responses to the questionnaire was utilized to develop an interactive lecture introductory geology course for non-science majors. Student outcomes were examined in introductory geology courses based on two teaching methods: interactive lecture and traditional lecture. There were no significant statistical differences between the groups based on the student outcomes and teaching methods. Incorporating interactive lecture methods did not statistically improve student outcomes when compared to traditional lecture teaching methods. However, the responses to the survey revealed students have a preference for introductory geology courses taught with lecture and instructor-led discussions and students prefer to work independently or in small groups. The results of this study are useful to individuals who teach introductory geology courses and individuals who teach introductory science courses for non-science majors at the college level.

15. Comparison of chest compression quality between the modified chest compression method with the use of smartphone application and the standardized traditional chest compression method during CPR.

Science.gov (United States)

Park, Sang-Sub

2014-01-01

The purpose of this study is to grasp difference in quality of chest compression accuracy between the modified chest compression method with the use of smartphone application and the standardized traditional chest compression method. Participants were progressed 64 people except 6 absentees among 70 people who agreed to participation with completing the CPR curriculum. In the classification of group in participants, the modified chest compression method was called as smartphone group (33 people). The standardized chest compression method was called as traditional group (31 people). The common equipments in both groups were used Manikin for practice and Manikin for evaluation. In the meantime, the smartphone group for application was utilized Android and iOS Operating System (OS) of 2 smartphone products (G, i). The measurement period was conducted from September 25th to 26th, 2012. Data analysis was used SPSS WIN 12.0 program. As a result of research, the proper compression depth (mm) was shown the proper compression depth (p< 0.01) in traditional group (53.77 mm) compared to smartphone group (48.35 mm). Even the proper chest compression (%) was formed suitably (p< 0.05) in traditional group (73.96%) more than smartphone group (60.51%). As for the awareness of chest compression accuracy, the traditional group (3.83 points) had the higher awareness of chest compression accuracy (p< 0.001) than the smartphone group (2.32 points). In the questionnaire that was additionally carried out 1 question only in smartphone group, the modified chest compression method with the use of smartphone had the high negative reason in rescuer for occurrence of hand back pain (48.5%) and unstable posture (21.2%).

16. Understanding Foster Youth Outcomes: Is Propensity Scoring Better than Traditional Methods?

Science.gov (United States)

Berzin, Stephanie Cosner

2010-01-01

Objectives: This study seeks to examine the relationship between foster care and outcomes using multiple comparison methods to account for factors that put foster youth at risk independent of care. Methods: Using the National Longitudinal Survey of Youth 1997, matching, propensity scoring, and comparisons to the general population are used to…

17. Methodological comparison of marginal structural model, time-varying Cox regression, and propensity score methods : the example of antidepressant use and the risk of hip fracture

NARCIS (Netherlands)

Ali, M Sanni; Groenwold, Rolf H H; Belitser, Svetlana V; Souverein, Patrick C; Martín, Elisa; Gatto, Nicolle M; Huerta, Consuelo; Gardarsdottir, Helga; Roes, Kit C B; Hoes, Arno W; de Boer, Antonius; Klungel, Olaf H

2016-01-01

BACKGROUND: Observational studies including time-varying treatments are prone to confounding. We compared time-varying Cox regression analysis, propensity score (PS) methods, and marginal structural models (MSMs) in a study of antidepressant [selective serotonin reuptake inhibitors (SSRIs)] use and

18. Panel presentation: Should some type of incentive regulation replace traditional methods for regulating LDCs?

International Nuclear Information System (INIS)

Turner, J.L.

1992-01-01

This paper reviews the advantages and disadvantages of using incentive regulation to provide the best service and rates for natural gas consumers and compares it to the traditional rate-of-return regulation. It discusses some of the allegations used to prevent incentive regulation such as the rate-of-return regulation provides an incentive to over-build and pad rate base, thus creating inefficiencies. The author also feels that strict competition is not necessarily beneficial and that some form of regulation is necessary. The paper goes on to outline the author's ideas of how a successful incentive plan should work while emphasizing his preference for a rate-of-return regulation. From the ratepayers' view, the incentives granted should be rewards for improvement in a utility's performance. In other words, there must be clear goals set for management and the fulfillment or lack of fulfillment should result in rewards or penalties. The author feels that incentive regulation could prove to be appropriate in the areas of demand side management such as energy conservation programs

19. Evaluation of two methods for monitoring surface cleanliness-ATP bioluminescence and traditional hygiene swabbing.

Science.gov (United States)

Davidson, C A; Griffith, C J; Peters, A C; Fielding, L M

1999-01-01

The minimum bacterial detection limits and operator reproducibility of the Biotrace Clean-Tracetrade mark Rapid Cleanliness Test and traditional hygiene swabbing were determined. Areas (100 cm2) of food grade stainless steel were separately inoculated with known levels of Staphylococcus aureus (NCTC 6571) and Escherichia coli (ATCC 25922). Surfaces were sampled either immediately after inoculation while still wet, or after 60 min when completely dry. For both organisms the minimum detection limit of the ATP Clean-Tracetrade mark Rapid Cleanliness Test was 10(4) cfu/100 cm2 (p 10(7) cfu/100 cm2. Hygiene swabbing percentage recovery rates for both organisms were less than 0.1% for dried surfaces but ranged from 0.33% to 8.8% for wet surfaces. When assessed by six technically qualified operators, the Biotrace Clean-Tracetrade mark Rapid Cleanliness Test gave superior reproducibility for both clean and inoculated surfaces, giving mean coefficients of variation of 24% and 32%, respectively. Hygiene swabbing of inoculated surfaces gave a mean CV of 130%. The results are discussed in the context of hygiene monitoring within the food industry. Copyright 1999 John Wiley & Sons, Ltd.

20. Video-based Learning Versus Traditional Method for Preclinical Course of Complete Denture Fabrication.

Science.gov (United States)

2015-03-01

Advances in computer science and technology allow the instructors to use instructional multimedia programs to enhance the process of learning for dental students. The purpose of this study was to determine the effect of a new educational modality by using videotapes on the performance of dental students in preclinical course of complete denture fabrication. This quasi-experimental study was performed on 54 junior dental students in Shahid Beheshti University of Medical Sciences (SBMU). Twenty-five and 29 students were evaluated in two consecutive semesters as controls and cases, respectively for the same course. The two groups were matched in terms of "knowledge about complete denture fabrication" and "basic dental skills" using a written test and a practical exam, respectively. After the intervention, performance and clinical skills of students were assessed in 8 steps. Eventually, a post-test was carried out to find changes in knowledge and skills of students in this regard. In the two groups with the same baseline level of knowledge and skills, independent T-test showed that students in the test group had a significantly superior performance in primary impression taking (p= 0.001) and primary cast fabrication (p= 0.001). In terms of anterior teeth set up, students in the control group had a significantly better performance (p= 0.001). Instructional videotapes can aid in teaching fabrication of complete denture and are as effective as the traditional teaching system.

1. Nutritional value of traditional Italian meat-based dishes: influence of cooking methods and recipe formulation.

Science.gov (United States)

D'Evoli, L; Salvatore, P; Lucarini, M; Nicoli, S; Aguzzi, A; Gabrielli, P; Lombardi-Boccia, G

2009-01-01

The present study provides a picture of the compositional figure and nutritive value of meat-based dishes typical of Italian culinary tradition. Recipes specific for a bovine meat cut (top-side) were selected among the most widespread ones in Italy: in pan, pizzaiola, cutlet, meat ball, and escalope. The total fat and cholesterol content varied depending on the ingredients utilized (extra-virgin olive oil, parmesan, egg). Meat-based dishes that utilized extra-virgin olive oil showed a significant reduction in palmitic and stearic acids and a parallel increase in oleic acid compared with raw meat; furthermore, the ratio among saturated fatty acids, monounsaturated fatty acids and polyunsaturated fatty acids shifted in favour of monounsaturated fatty acids. B vitamins were affected at different extent by heating; by contrast, vitamin E content increased because of the new sources of this vitamin, which masked losses due to heating. Ingredients (parmesan, discretionary salt) induced significant increases in the calcium and sodium concentrations compared with raw meat. The total iron content did not show marked differences in most of the meat-based dishes compared with raw meat; by contrast, losses in the heme-iron concentration were detected depending on the severity of heating treatments. Our findings suggest that heme iron, because of its important health aspects, might be a useful index of the nutritional quality of cooked meats.

2. Motivation in service-learning: an improvement over traditional instructional methods

Directory of Open Access Journals (Sweden)

Monika Ciesielkiewicz

2018-05-01

Full Text Available This paper aims at exploring the motivation of university students who participated in service-learning projects as part of their coursework, and to determine whether their level of motivation is higher for the service-learning project as compared to performing more traditional academic tasks and assignments. The Service-Learning project carried out during the ICT in Education course intended to support the development of digital literacy in a Maasai school in Kenya. The instrument used to evaluate motivation of the university students is the motivation scale called Motivated Strategies for Learning Questionnaire (MSLQ proposed by Pintrich and his collaborators (1991 adapted to the Spanish population by Roces Montero (1996. The results of the research indicate that there are significant differences in favor of service-learning in relation to motivation in general for the completion of the activities and specifically in relation to the utility of the activity as seen at the present moment and in the future, as well as promoting creativity, the interest in the task which includes the perception of the importance of the project, the need to work hard and thoroughly and willingness to face challenges and difficulties in order to achieve the set objective. No significant differences have been observed in relation to the desire to obtain a better grade for completing the activity or need to prove personal value to others, as well as to broaden the information to complete the activity.

3. Festival of Curses: A Traditional Crime Control Method In Edo State –Nigeria

Directory of Open Access Journals (Sweden)

Rashidi Akanji Okunola

2016-02-01

Full Text Available Festivals and ceremonies are part and parcel of African culture, usually in all its pump, merriment and pageantry. However, with the increasing wave of criminal activities in Nigeria especially in Edo state, festivals and ceremonies are being redefined and conceptualized in practice. Only recently a new festival ‘Festival of Curses’ was brought to the fore in combating crime in Edo state. The study therefore seeks to explain the festival as a traditional mechanism in crime control, the nature of the festival, the factors that led to its emergence in the 21st century, the level of acceptance and its impact in reducing criminal activities in the State. The study employed principally secondary literature and in-depth interviews among a cross section of the Bini. Major findings revealed that immediately after the festival of curses, a lot of criminals in the state besieged the Bini Monarch’s Palace to confess their atrocities; and pleaded for forgiveness. There was an overwhelming acceptance of the festival irrespective of the people’s religious affiliations to Christianity and Islam as a result of the potency and sudden drop in crime during the period. The study concludes that the festival should be taken as a mechanism of crime control and policing in Nigeria.

4. Panel presentation: Should some type of incentive regulation replace traditional methods for regulating LDCs?

International Nuclear Information System (INIS)

Costello, K.W.

1992-01-01

State regulators should consider new approaches to regulating LDCs. They should seriously look at different incentive systems, even if only as an experiment, to address the major inefficiencies they see plaguing LDCs. Regulators have become more receptive in recent years to applying different incentive systems for historically heavily regulated industries such as the telecommunications and electric industries. In view of prevailing conditions in the natural gas industry, there is no good reason why regulators should not be as receptive to applying incentive systems for LDCs. For gas services offered in competitive markets, regulators should ask themselves whether regulation is necessary any longer. For services still requiring regulation, regulators should explore whether changes in traditional regulation are needed. While some PUCs have undertaken new regulatory practices, the question before them today is whether they should do more; whether, for example, states should accelerate their efforts toward adopting more flexible pricing and other incentive-based regulations or toward considering deregulating selected services. PUCs have different options. They can choose from among a large number of incentive systems. Their choices should hinge upon what they view as major sources of inefficiencies. For example, if uneconomical bypass is perceived as a problem then different price rules might constitute the cornerstone of an incentive-based policy. On the other hand, if excessive purchased-gas costs seem to be a major problem, a PUC may want to consider abolishing the PGA or modifying it in a form that would eliminate the cost-plus component

5. Regression Analysis

CERN Document Server

Freund, Rudolf J; Sa, Ping

2006-01-01

The book provides complete coverage of the classical methods of statistical analysis. It is designed to give students an understanding of the purpose of statistical analyses, to allow the student to determine, at least to some degree, the correct type of statistical analyses to be performed in a given situation, and have some appreciation of what constitutes good experimental design

6. A comparison of a track shape analysis-based automated slide scanner system with traditional methods

International Nuclear Information System (INIS)

Bator, G.; Csordas, A.; Horvath, D.; Somlai, J.; Kovacs, T.

2015-01-01

During recent years, CR-39 detector measurements have gained attention due to improvements in image processing methods. An assessment method based on the application of a high-resolution slide scanner and its quality checks is introduced, using commercially available software and hardware. Using the conventional (visual) comparing analysis for 563 detectors, the method was found suitable for high-precision and reliable track analysis. The accuracy of the measurements were not disturbed by any other pseudo-tracks (scratches or contamination) due to the signal shape of the analysis. (author)

7. Avocado oil extraction processes: method for cold-pressed high-quality edible oil production versus traditional production

Directory of Open Access Journals (Sweden)

Giacomo Costagli

2015-10-01

8. Integration of Traditional and E-Learning Methods to Improve Learning Outcomes for Dental Students in Histopathology.

Science.gov (United States)

Ariana, Armin; Amin, Moein; Pakneshan, Sahar; Dolan-Evans, Elliot; Lam, Alfred K

2016-09-01

Dental students require a basic ability to explain and apply general principles of pathology to systemic, dental, and oral pathology. Although there have been recent advances in electronic and online resources, the academic effectiveness of using self-directed e-learning tools in pathology courses for dental students is unclear. The aim of this study was to determine if blended learning combining e-learning with traditional learning methods of lectures and tutorials would improve students' scores and satisfaction over those who experienced traditional learning alone. Two consecutive cohorts of Bachelor of Dentistry and Oral Health students taking the general pathology course at Griffith University in Australia were compared. The control cohort experienced traditional methods only, while members of the study cohort were also offered self-directed learning materials including online resources and online microscopy classes. Final assessments for the course were used to compare the differences in effectiveness of the intervention, and students' satisfaction with the teaching format was evaluated using questionnaires. On the final course assessments, students in the study cohort had significantly higher scores than students in the control cohort (plearning tools such as virtual microscopy and interactive online resources for delivering pathology instruction can be an effective supplement for developing dental students' competence, confidence, and satisfaction.

9. Running and Metabolic Demands of Elite Rugby Union Assessed Using Traditional, Metabolic Power, and Heart Rate Monitoring Methods

Directory of Open Access Journals (Sweden)

Romain Dubois, Thierry Paillard, Mark Lyons, David McGrath, Olivier Maurelli, Jacques Prioux

2017-03-01

Full Text Available The aims of this study were (1 to analyze elite rugby union game demands using 3 different approaches: traditional, metabolic and heart rate-based methods (2 to explore the relationship between these methods and (3 to explore positional differences between the backs and forwards players. Time motion analysis and game demands of fourteen professional players (24.1 ± 3.4 y, over 5 European challenge cup games, were analyzed. Thresholds of 14.4 km·h-1, 20 W.kg-1 and 85% of maximal heart rate (HRmax were set for high-intensity efforts across the three methods. The mean % of HRmax was 80.6 ± 4.3 % while 42.2 ± 16.5% of game time was spent above 85% of HRmax with no significant differences between the forwards and the backs. Our findings also show that the backs cover greater distances at high-speed than forwards (% difference: +35.2 ± 6.6%; p<0.01 while the forwards cover more distance than the backs (+26.8 ± 5.7%; p<0.05 in moderate-speed zone (10-14.4 km·h-1. However, no significant difference in high-metabolic power distance was found between the backs and forwards. Indeed, the high-metabolic power distances were greater than high-speed running distances of 24.8 ± 17.1% for the backs, and 53.4 ± 16.0% for the forwards with a significant difference (+29.6 ± 6.0% for the forwards; p<0.001 between the two groups. Nevertheless, nearly perfect correlations were found between the total distance assessed using the traditional approach and the metabolic power approach (r = 0.98. Furthermore, there is a strong association (r = 0.93 between the high-speed running distance (assessed using the traditional approach and the high-metabolic power distance. The HR monitoring methods demonstrate clearly the high physiological demands of professional rugby games. The traditional and the metabolic-power approaches shows a close correlation concerning their relative values, nevertheless the difference in absolute values especially for the high

10. [Methods of traditional chinese medicine in the treatment of patients with interstitial cystitis/bladder pain syndrome].

Science.gov (United States)

Ignashov, A Yu; Deng, B; Kuzmin, I V; Slesarevskaya, M N

2018-03-01

In recent years, there has been an increasing interest in alternative (complementary) treatments of interstitial cystitis/bladder pain syndrome (IC/BPS). This is due both to the high incidence of IC/BPS and to a lack of effectiveness of conventional treatments. One of the directions of alternative therapies is a traditional Chinese medicine using a special diet, various animal and plant-derived medicines, breathing exercises and acupuncture. This review analyzes the accumulated experience in using traditional Chinese medicine in the treatment of patients with IC/BPS. The presented data indicate that these methods appear to be promising, since they are effective in a significant number of patients, lead to an improvement in their quality of life, are non-invasive and well tolerated. However, due to the lack of clinical studies, the efficacy of this treatment modalities needs to be confirmed.

11. Ethics, Collaboration, and Presentation Methods for Local and Traditional Knowledge for Understanding Arctic Change

Science.gov (United States)

Parsons, M. A.; Gearheard, S.; McNeave, C.

2009-12-01

Local and traditional knowledge (LTK) provides rich information about the Arctic environment at spatial and temporal scales that scientific knowledge often does not have access to (e.g. localized observations of fine-scale ecological change potentially from many different communities, or local sea ice and conditions prior to 1950s ice charts and 1970s satellite records). Community-based observations and monitoring are an opportunity for Arctic residents to provide ‘frontline’ observations and measurements that are an early warning system for Arctic change. The Exchange for Local Observations and Knowledge of the Arctic (ELOKA) was established in response to the growing number of community-based and community-oriented research and observation projects in the Arctic. ELOKA provides data management and user support to facilitate the collection, preservation, exchange, and use of local observations and knowledge. Managing these data presents unique ethical challenges in terms of appropriate use of rare human knowledge and ensuring that knowledge is not lost from the local communities and not exploited in ways antithetical to community culture and desires. Local Arctic residents must be engaged as true collaborative partners while respecting their perspectives, which may vary substantially from a western science perspective. At the same time, we seek to derive scientific meaning from the local knowledge that can be used in conjunction with quantitative science data. This creates new challenges in terms of data presentation, knowledge representations, and basic issues of metadata. This presentation reviews these challenges, some initial approaches to addressing them, and overall lessons learned and future directions.

12. Traditional method of fish treatment, microbial count and palatability studies on spoiled fish

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Abd Aziz, N. A.

2013-01-01

Full Text Available Aims: To evaluate the microbial count and palatability acceptance of spoiled fish after treatment with traditionally used naturalsolution.Methodology and results: To compare microbial count of spoiled fish before and after treatment with natural solution practicedby local people in Malaysia, 10 g of spoiled fish was respectively rinsed with 100 mL of 0.1% of natural solution such as Averrhoabilimbi extract, rice rinsed water, rice vinegar, Citrus aurantifolia extract, salt, flour, and Tamarindus indica extract. Flesh of fishrinsed with rice vinegar was found to be able to reduce microbial count (CFU/mL = 0.37 X 107 more than 4.5 times whencompared to spoiled fish (CFU/mL=1.67x 107. Spoiled fish that was treated with rice vinegar was prepared into a cutlet and fried.The cutlet was subjected to palatability acceptance study by a group of residents in Palm Court Condominium, Brickfields, KualaLumpur. The palatability study from the Cronbach alpha shown that the taste have the reliability of 0.802, the aroma has thereliability of 0.888, colour with the reliability of 0.772, texture or mouth feel have reliability of 0.840 and physical structure of thecutlet is 0.829.Conclusion, significance and impact of study: Treatment of spoiled fish using rice vinegar as practice by local peopletraditionally shown a significant reduction in microbial count and the vinegar-treated fish could be developed into a product that issafe and acceptable by the consumer.

13. A comparative study on generating simulated Landsat NDVI images using data fusion and regression method-the case of the Korean Peninsula.

Science.gov (United States)

Lee, Mi Hee; Lee, Soo Bong; Eo, Yang Dam; Kim, Sun Woong; Woo, Jung-Hun; Han, Soo Hee

2017-07-01

Landsat optical images have enough spatial and spectral resolution to analyze vegetation growth characteristics. But, the clouds and water vapor degrade the image quality quite often, which limits the availability of usable images for the time series vegetation vitality measurement. To overcome this shortcoming, simulated images are used as an alternative. In this study, weighted average method, spatial and temporal adaptive reflectance fusion model (STARFM) method, and multilinear regression analysis method have been tested to produce simulated Landsat normalized difference vegetation index (NDVI) images of the Korean Peninsula. The test results showed that the weighted average method produced the images most similar to the actual images, provided that the images were available within 1 month before and after the target date. The STARFM method gives good results when the input image date is close to the target date. Careful regional and seasonal consideration is required in selecting input images. During summer season, due to clouds, it is very difficult to get the images close enough to the target date. Multilinear regression analysis gives meaningful results even when the input image date is not so close to the target date. Average R 2 values for weighted average method, STARFM, and multilinear regression analysis were 0.741, 0.70, and 0.61, respectively.

14. Predicting the cross-reactivities of polycyclic aromatic hydrocarbons in ELISA by regression analysis and CoMFA methods

Energy Technology Data Exchange (ETDEWEB)

Zhang, Yan-Feng; Dai, Shu-Gui [College of Environmental Science and Engineering, Nankai University, Key Laboratory for Pollution Process and Environmental Criteria of Ministry of Education, Tianjin (China); Ma, Yi [College of Chemistry, Nankai University, Institute of Elemento-Organic Chemistry, Tianjin (China); Gao, Zhi-Xian [Institute of Hygiene and Environmental Medicine, Tianjin (China)

2010-07-15

Immunoassays have been regarded as a possible alternative or supplement for measuring polycyclic aromatic hydrocarbons (PAHs) in the environment. Since there are too many potential cross-reactants for PAH immunoassays, it is difficult to determine all the cross-reactivities (CRs) by experimental tests. The relationship between CR and the physical-chemical properties of PAHs and related compounds was investigated using the CR data from a commercial enzyme-linked immunosorbent assay (ELISA) kit test. Two quantitative structure-activity relationship (QSAR) techniques, regression analysis and comparative molecular field analysis (CoMFA), were applied for predicting the CR of PAHs in this ELISA kit. Parabolic regression indicates that the CRs are significantly correlated with the logarithm of the partition coefficient for the octanol-water system (log K{sub ow}) (r{sup 2}=0.643, n=23, P<0.0001), suggesting that hydrophobic interactions play an important role in the antigen-antibody binding and the cross-reactions in this ELISA test. The CoMFA model obtained shows that the CRs of the PAHs are correlated with the 3D structure of the molecules (r{sub cv}{sup 2}=0.663, r{sup 2}=0.873, F{sub 4,32}=55.086). The contributions of the steric and electrostatic fields to CR were 40.4 and 59.6%, respectively. Both of the QSAR models satisfactorily predict the CR in this PAH immunoassay kit, and help in understanding the mechanisms of antigen-antibody interaction. (orig.)

15. Investigation of Pear Drying Performance by Different Methods and Regression of Convective Heat Transfer Coefficient with Support Vector Machine

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Mehmet Das

2018-01-01

Full Text Available In this study, an air heated solar collector (AHSC dryer was designed to determine the drying characteristics of the pear. Flat pear slices of 10 mm thickness were used in the experiments. The pears were dried both in the AHSC dryer and under the sun. Panel glass temperature, panel floor temperature, panel inlet temperature, panel outlet temperature, drying cabinet inlet temperature, drying cabinet outlet temperature, drying cabinet temperature, drying cabinet moisture, solar radiation, pear internal temperature, air velocity and mass loss of pear were measured at 30 min intervals. Experiments were carried out during the periods of June 2017 in Elazig, Turkey. The experiments started at 8:00 a.m. and continued till 18:00. The experiments were continued until the weight changes in the pear slices stopped. Wet basis moisture content (MCw, dry basis moisture content (MCd, adjustable moisture ratio (MR, drying rate (DR, and convective heat transfer coefficient (hc were calculated with both in the AHSC dryer and the open sun drying experiment data. It was found that the values of hc in both drying systems with a range 12.4 and 20.8 W/m2 °C. Three different kernel models were used in the support vector machine (SVM regression to construct the predictive model of the calculated hc values for both systems. The mean absolute error (MAE, root mean squared error (RMSE, relative absolute error (RAE and root relative absolute error (RRAE analysis were performed to indicate the predictive model’s accuracy. As a result, the rate of drying of the pear was examined for both systems and it was observed that the pear had dried earlier in the AHSC drying system. A predictive model was obtained using the SVM regression for the calculated hc values for the pear in the AHSC drying system. The normalized polynomial kernel was determined as the best kernel model in SVM for estimating the hc values.

16. Collaborative regression.

Science.gov (United States)

Gross, Samuel M; Tibshirani, Robert

2015-04-01

We consider the scenario where one observes an outcome variable and sets of features from multiple assays, all measured on the same set of samples. One approach that has been proposed for dealing with these type of data is "sparse multiple canonical correlation analysis" (sparse mCCA). All of the current sparse mCCA techniques are biconvex and thus have no guarantees about reaching a global optimum. We propose a method for performing sparse supervised canonical correlation analysis (sparse sCCA), a specific case of sparse mCCA when one of the datasets is a vector. Our proposal for sparse sCCA is convex and thus does not face the same difficulties as the other methods. We derive efficient algorithms for this problem that can be implemented with off the shelf solvers, and illustrate their use on simulated and real data. © The Author 2014. Published by Oxford University Press. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

17. A Method of Calculating Functional Independence Measure at Discharge from Functional Independence Measure Effectiveness Predicted by Multiple Regression Analysis Has a High Degree of Predictive Accuracy.

Science.gov (United States)

Tokunaga, Makoto; Watanabe, Susumu; Sonoda, Shigeru

2017-09-01

Multiple linear regression analysis is often used to predict the outcome of stroke rehabilitation. However, the predictive accuracy may not be satisfactory. The objective of this study was to elucidate the predictive accuracy of a method of calculating motor Functional Independence Measure (mFIM) at discharge from mFIM effectiveness predicted by multiple regression analysis. The subjects were 505 patients with stroke who were hospitalized in a convalescent rehabilitation hospital. The formula "mFIM at discharge = mFIM effectiveness × (91 points - mFIM at admission) + mFIM at admission" was used. By including the predicted mFIM effectiveness obtained through multiple regression analysis in this formula, we obtained the predicted mFIM at discharge (A). We also used multiple regression analysis to directly predict mFIM at discharge (B). The correlation between the predicted and the measured values of mFIM at discharge was compared between A and B. The correlation coefficients were .916 for A and .878 for B. Calculating mFIM at discharge from mFIM effectiveness predicted by multiple regression analysis had a higher degree of predictive accuracy of mFIM at discharge than that directly predicted. Copyright © 2017 National Stroke Association. Published by Elsevier Inc. All rights reserved.

18. Re-Defining Traditional Bazaar Areas and Shade Structures Via Parametric Design Methods

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Ahmet Emre Dinçer

2017-12-01

19. Machine cost analysis using the traditional machine-rate method and ChargeOut!

Science.gov (United States)

E. M. (Ted) Bilek

2009-01-01

Forestry operations require ever more use of expensive capital equipment. Mechanization is frequently necessary to perform cost-effective and safe operations. Increased capital should mean more sophisticated capital costing methodologies. However the machine rate method, which is the costing methodology most frequently used, dates back to 1942. CHARGEOUT!, a recently...

20. Combining traditional dietary assessment methods with novel metabolomics techniques : present efforts by the Food Biomarker Alliance

NARCIS (Netherlands)

Brouwer-Brolsma, Elske M.; Brennan, Lorraine; Drevon, Christian A.; van Kranen, Henk; Manach, Claudine; Dragsted, Lars Ove; Roche, Helen M.; Andres-Lacueva, Cristina; Bakker, Stephan J. L.; Bouwman, Jildau; Capozzi, Francesco; De Saeger, Sarah; Gundersen, Thomas E.; Kolehmainen, Marjukka; Kulling, Sabine E.; Landberg, Rikard; Linseisen, Jakob; Mattivi, Fulvio; Mensink, Ronald P.; Scaccini, Cristina; Skurk, Thomas; Tetens, Inge; Vergeres, Guy; Wishart, David S.; Scalbert, Augustin; Feskens, Edith J. M.

FFQ, food diaries and 24 h recall methods represent the most commonly used dietary assessment tools in human studies on nutrition and health, but food intake biomarkers are assumed to provide a more objective reflection of intake. Unfortunately, very few of these biomarkers are sufficiently

1. Developing a Pictorial Sisterhood Method in collaboration with illiterate Maasai traditional birth attendants in northern Tanzania

NARCIS (Netherlands)

Roggeveen, Yadira; Schreuder, Renske; Zweekhorst, Marjolein; Manyama, Mange; Hatfield, Jennifer; Scheele, Fedde; van Roosmalen, Jos

2016-01-01

Objective To study whether data on maternal mortality can be gathered while maintaining local ownership of data in a pastoralist setting where a scarcity of data sources and a culture of silence around maternal death amplifies limited awareness of the magnitude of maternal mortality. Methods As part

2. A method for the selection of a functional form for a thermodynamic equation of state using weighted linear least squares stepwise regression

Science.gov (United States)

Jacobsen, R. T.; Stewart, R. B.; Crain, R. W., Jr.; Rose, G. L.; Myers, A. F.

1976-01-01

A method was developed for establishing a rational choice of the terms to be included in an equation of state with a large number of adjustable coefficients. The methods presented were developed for use in the determination of an equation of state for oxygen and nitrogen. However, a general application of the methods is possible in studies involving the determination of an optimum polynomial equation for fitting a large number of data points. The data considered in the least squares problem are experimental thermodynamic pressure-density-temperature data. Attention is given to a description of stepwise multiple regression and the use of stepwise regression in the determination of an equation of state for oxygen and nitrogen.

3. Comparison study between traditional and finite element methods for slopes under heavy rainfall

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M. Rabie

2014-08-01

Moreover, slope stability concerning rainfall and infiltration is analyzed. Specially, two kinds of infiltrations (saturated and unsaturated are considered. Many slopes become saturated during periods of intense rainfall or snowmelt, with the water table rising to the ground surface, and water flowing essentially parallel to the direction of the “slope” and “Influence” of the change in shear strength, density, pore-water pressure and seepage force in soil slices on the slope stability is explained. Finally, it is found that classical limit equilibrium methods are highly conservative compared to the finite element approach. For assessment the factor of safety for slope using the later technique, no assumption needs to be made in advance about the shape or location of the failure surface, slice side forces and their directions. This document outlines the capabilities of the finite element method in the analysis of slope stability problems.

4. A better way to teach knot tying: a randomized controlled trial comparing the kinesthetic and traditional methods.

Science.gov (United States)

Huang, Emily; Chern, Hueylan; O'Sullivan, Patricia; Cook, Brian; McDonald, Erik; Palmer, Barnard; Liu, Terrence; Kim, Edward

2014-10-01

Knot tying is a fundamental and crucial surgical skill. We developed a kinesthetic pedagogical approach that increases precision and economy of motion by explicitly teaching suture-handling maneuvers and studied its effects on novice performance. Seventy-four first-year medical students were randomized to learn knot tying via either the traditional or the novel "kinesthetic" method. After 1 week of independent practice, students were videotaped performing 4 tying tasks. Three raters scored deidentified videos using a validated visual analog scale. The groups were compared using analysis of covariance with practice knots as a covariate and visual analog scale score (range, 0 to 100) as the dependent variable. Partial eta-square was calculated to indicate effect size. Overall rater reliability was .92. The kinesthetic group scored significantly higher than the traditional group for individual tasks and overall, controlling for practice (all P kinesthetic overall mean was 64.15 (standard deviation = 16.72) vs traditional 46.31 (standard deviation = 16.20; P kinesthetic suture handling substantively improved performance on knot tying. We believe this effect can be extrapolated to more complex surgical skills. Copyright © 2014 Elsevier Inc. All rights reserved.

5. Teaching design in the first years of a traditional mechanical engineering degree: methods, issues and future perspectives

Science.gov (United States)

Silva, Arlindo; Fontul, Mihail; Henriques, Elsa

2015-01-01

Engineering design is known as an answer to an ill-defined problem. As any answer to an ill-defined problem, it can never be completely right or absolutely wrong. The methods that universities use to teach engineering design, as a consequence of this, suffer from the same fate. However, the accumulated experience with the 'chalk and talk' teaching tradition has led to a reality in which the employers of fresh graduates are not happy with the engineers they are getting. Part of their complaints are related with the inability of recently graduate engineers to work in problems where the boundaries are not well defined, are interdisciplinary, require the use of effective communication and integrate non-technical issues. These skills are mostly absent from traditional engineering curricula. This paper demonstrates the implementation of engineering design perspectives enhancing some of the aforementioned skills in a traditional mechanical engineering curriculum. It emphasises in particular a design project that is tackled in a sequence of conventional courses with a focus that depends on the course objectives and disciplinary domain. This transdisciplinary design project conveys the idea (and effectively implements it concurrently) that design is multidisciplinary.

6. REGARDING A METHOD OF PERFORMING ON THE VIOLIN IN TRADITIONAL MUSIC

Directory of Open Access Journals (Sweden)

MIRONENCO IAROSLAV

2016-06-01

Full Text Available Following a field study in the village of Lozova, Străşeni, aimed at identifying the variants of a folk song recorded by I. Mironenko from an informant living in the village of Thamaha, North Caucasus — Russia, a village inhabited by Moldovans, the musicologist discovered a fiddler who demonstrated him a specific process of executation on the violin. This method is representative of an advanced level of interpretation on the violin.

7. [Study on two preparation methods for beta-CD inclusion compound of four traditional Chinese medicine volatile oils].

Science.gov (United States)

Li, Hailiang; Cui, Xiaoli; Tong, Yan; Gong, Muxin

2012-04-01

To compare inclusion effects and process conditions of two preparation methods-colloid mill and saturated solution-for beta-CD inclusion compound of four traditional Chinese medicine volatile oils and study the relationship between each process condition and volatile oil physical properties and the regularity of selective inclusion of volatile oil components. Volatile oils from Nardostachyos Radix et Rhizoma, Amomi Fructus, Zingiberis Rhizoma and Angelicaesinensis Radix were prepared using two methods in the orthogonal test. These inclusion compounds by optimized processes were assessed and compared by such methods as TLC, IR and scanning electron microscope. Inclusion oils were extracted by steam distillation, and the components found before and after inclusion were analyzed by GC-MS. Analysis showed that new inclusion compounds, but inclusion compounds prepared by the two processes had differences to some extent. The colloid mill method showed a better inclusion effect than the saturated solution method, indicating that their process conditions had relations with volatile oil physical properties. There were differences in the inclusion selectivity of components between each other. The colloid mill method for inclusion preparation is more suitable for industrial requirements. To prepare volatile oil inclusion compounds with heavy gravity and high refractive index, the colloid mill method needs longer time and more water, while the saturated solution method requires higher temperature and more beta-cyclodextrin. The inclusion complex prepared with the colloid mill method contains extended molecular weight chemical composition, but the kinds of components are reduced.

8. Practical implications of procedures developed in IDEA project - Comparison with traditional methods

International Nuclear Information System (INIS)

Andrasi, A.; Bouvier, C.; Brandl, A.; De Carlan, L.; Fischer, H.; Franck, D.; Hoellriegl, V.; Li, W. B.; Oeh, U.; Ritt, J.; Roth, P.; Schlagbauer, M.; Schmitzer, Ch; Wahl, W.; Zombori, P.

2007-01-01

The idea of the IDEA project aimed to improve assessment of incorporated radionuclides through developments of more reliable and possibly faster in vivo and bioassay monitoring techniques and making use of such enhancements for improvements in routine monitoring. In direct in vivo monitoring technique the optimum choice of the detectors to be applied for different monitoring tasks has been investigated in terms of material, size and background in order to improve conditions namely to increase counting efficiency and reduce background. Detailed studies have been performed to investigate the manifold advantageous applications and capabilities of numerical simulation method for the calibration and optimisation of in vivo counting systems. This calibration method can be advantageously applied especially in the measurement of low-energy photon emitting radionuclides, where individual variability is a significant source of uncertainty. In bioassay measurements the use of inductively coupled plasma mass spectrometry (ICP-MS) can improve considerably both the measurement speed and the lower limit of detection currently achievable with alpha spectrometry for long-lived radionuclides. The work carried out in this project provided detailed guidelines for optimum performance of the technique of ICP-MS applied mainly for the determination of uranium and thorium nuclides in the urine including sampling procedure, operational parameters of the instruments and interpretation of the measured data. The paper demonstrates the main advantages of investigated techniques in comparison with the performances of methods commonly applied in routine monitoring practice. (authors)

9. Comparison of teaching about breast cancer via mobile or traditional learning methods in gynecology residents.

Science.gov (United States)

2012-01-01

Mobile learning enables users to interact with educational resources while in variable locations. Medical students in residency positions need to assimilate considerable knowledge besides their practical training and we therefore aimed to evaluate the impact of using short message service via cell phone as a learning tool in residents of Obstetrics and Gynecology in our hospital. We sent short messages including data about breast cancer to the cell phones of 25 residents of gynecology and obstetrics and asked them to study a well-designed booklet containing another set of information about the disease in the same period. The rate of learning derived from the two methods was compared by pre- and post-tests and self-satisfaction assessed by a relevant questionnaire at the end of the program. The mobile learning method had a significantly better effect on learning and created more interest in the subject. Learning via receiving SMS can be an effective and appealing method of knowledge acquisition in higher levels of education.

10. Interval ridge regression (iRR) as a fast and robust method for quantitative prediction and variable selection applied to edible oil adulteration.

Science.gov (United States)

Jović, Ozren; Smrečki, Neven; Popović, Zora

2016-04-01

A novel quantitative prediction and variable selection method called interval ridge regression (iRR) is studied in this work. The method is performed on six data sets of FTIR, two data sets of UV-vis and one data set of DSC. The obtained results show that models built with ridge regression on optimal variables selected with iRR significantly outperfom models built with ridge regression on all variables in both calibration (6 out of 9 cases) and validation (2 out of 9 cases). In this study, iRR is also compared with interval partial least squares regression (iPLS). iRR outperfomed iPLS in validation (insignificantly in 6 out of 9 cases and significantly in one out of 9 cases for poil, a well known health beneficial nutrient, is studied in this work by mixing it with cheap and widely used oils such as soybean (So) oil, rapeseed (R) oil and sunflower (Su) oil. Binary mixture sets of hempseed oil with these three oils (HSo, HR and HSu) and a ternary mixture set of H oil, R oil and Su oil (HRSu) were considered. The obtained accuracy indicates that using iRR on FTIR and UV-vis data, each particular oil can be very successfully quantified (in all 8 cases RMSEPoil (R(2)>0.99). Copyright © 2015 Elsevier B.V. All rights reserved.

11. Formulation of an aloe-based product according to Iranian traditional medicine and development of its analysis method.

Science.gov (United States)

Moein, Elham; Hajimehdipoor, Homa; Toliyat, Tayebeh; Choopani, Rasool; Hamzeloo-Moghadam, Maryam

2017-08-29

Currently, people are more interested to traditional medicine. The traditional formulations should be converted to modern drug delivery systems to be more acceptable for the patients. In the present investigation, a poly herbal medicine "Ayarij-e-Faiqra" (AF) based on Iranian traditional medicine (ITM) has been formulated and its quality control parameters have been developed. The main ingredients of AF including barks of Cinnamomum zeylanicum Blume and Cinnamomum cassia J. Presl, the rhizomes of Nardostachys jatamansi DC., the fruits of Piper cubeba L.f., the flowers of Rosa damascena Herrm., the oleo gum resin of Pistacia terebinthus L. and Aloe spp. dried juice were powdered and used for preparing seven tablet formulations of the herbal mixture. Flowability of the different formulated powders was examined and the best formulations were selected (F6&F7). The tablets were prepared from the selected formulations compared according to the physical characteristics and finally, F7 was selected and coated. Physicochemical characters of core and coated AF tablets were determined and the HPLC method for quantitation of aloin as a marker of tablets was selected and verified according to selectivity, linearity, precision, recovery, LOD and LOQ. The results showed that core and coated AF tablets were in agreement with USP requirements for herbal drugs. They had acceptable appearance, disintegration time, friability, hardness, dissolution behavior, weight variation and content uniformity. The amount of aloin in tablets was found 123.1 mg/tab. The HPLC method for aloin determination in AF tablets was verified according to selectivity, linearity (5-500 μg/ml, r 2 :0.9999), precision (RSD: 1.62%), recovery (108.0%), LOD & LOQ (0.0053 & 0.0161 μg/ml). The formulated tablets could be a good substitute for powder and capsules of AF in ITM clinics with a feasible and precise method for its quality control. Ayarij-e-Faiqra formulation.

12. Configuring calendar variation based on time series regression method for forecasting of monthly currency inflow and outflow in Central Java

Science.gov (United States)

Setiawan, Suhartono, Ahmad, Imam Safawi; Rahmawati, Noorgam Ika

2015-12-01

Bank Indonesia (BI) as the central bank of Republic Indonesiahas a single overarching objective to establish and maintain rupiah stability. This objective could be achieved by monitoring traffic of inflow and outflow money currency. Inflow and outflow are related to stock and distribution of money currency around Indonesia territory. It will effect of economic activities. Economic activities of Indonesia,as one of Moslem country, absolutely related to Islamic Calendar (lunar calendar), that different with Gregorian calendar. This research aims to forecast the inflow and outflow money currency of Representative Office (RO) of BI Semarang Central Java region. The results of the analysis shows that the characteristics of inflow and outflow money currency influenced by the effects of the calendar variations, that is the day of Eid al-Fitr (moslem holyday) as well as seasonal patterns. In addition, the period of a certain week during Eid al-Fitr also affect the increase of inflow and outflow money currency. The best model based on the value of the smallestRoot Mean Square Error (RMSE) for inflow data is ARIMA model. While the best model for predicting the outflow data in RO of BI Semarang is ARIMAX model or Time Series Regression, because both of them have the same model. The results forecast in a period of 2015 shows an increase of inflow money currency happened in August, while the increase in outflow money currency happened in July.

13. HPLC Method for Simultaneous Quantitative Detection of Quercetin and Curcuminoids in Traditional Chinese Medicines

Directory of Open Access Journals (Sweden)

Lee Fung Ang

2014-12-01

Full Text Available Objectives: Quercetin and curcuminoids are important bioactive compounds found in many herbs. Previously reported high performance liquid chromatography ultraviolet (HPLC-UV methods for the detection of quercetin and curcuminoids have several disadvantages, including unsatisfactory separation times and lack of validation according the standard guidelines of the International Conference on Harmonisation of Technical Requirements for Registration of Pharmaceuticals for Human Use. Methods: A rapid, specific, reversed phase, HPLC-UV method with an isocratic elution of acetonitrile and 2% v/v acetic acid (40% : 60% v/v (pH 2.6 at a flow rate of 1.3 mL/minutes, a column temperature of 35°C, and ultraviolet (UV detection at 370 nm was developed. The method was validated and applied to the quantification of different types of market available Chinese medicine extracts, pills and tablets. Results: The method allowed simultaneous determination of quercetin, bisdemethoxycurcumin, demethoxycurcumin and curcumin in the concentration ranges of 0.00488 ─ 200 μg/mL, 0.625 ─ 320 μg/mL, 0.07813 ─ 320 μg/mL and 0.03906 ─ 320 μg/mL, respectively. The limits of detection and quantification, respectively, were 0.00488 and 0.03906 μg/mL for quercetin, 0.62500 and 2.50000 μg/mL for bisdemethoxycurcumin, 0.07813 and 0.31250 μg/mL for demethoxycurcumin, and 0.03906 and 0.07813 μg/mL for curcumin. The percent relative intra day standard deviation (% RSD values were 0.432 ─ 0.806 μg/mL, 0.576 ─ 0.723 μg/ mL, 0.635 ─ 0.752 μg/mL and 0.655 ─ 0.732 μg/mL for quercetin, bisdemethoxycurcumin, demethoxycurcumin and curcumin, respectively, and those for intra day precision were 0.323 ─ 0.968 μg/mL, 0.805 ─ 0.854 μg/mL, 0.078 ─ 0.844 μg/mL and 0.275 ─ 0.829 μg/mL, respectively. The intra day accuracies were 99.589% ─ 100.821%, 98.588% ─ 101.084%, 9.289% ─ 100.88%, and 98.292% ─ 101.022% for quercetin, bisdemethoxycurcumin

Science.gov (United States)

Ferreira, J Andries; Crissey, Jacqueline M; Brown, Marybeth

2011-03-10

The Morey-Holton hindlimb unloading (HU) method is a widely accepted National Aeronautics and Space Administration (NASA) ground-based model for studying disuse-atrophy in rodents. Our study evaluated an alternant method to the gold-standard Morey-Holton HU tail-traction technique in mice. Fifty-four female mice (4-8 mo.) were HU for 14 days (n=34) or 28 days (n=20). Recovery from HU was assessed after 3 days of normal cage ambulation following HU (n=22). Aged matched mice (n=76) served as weight-bearing controls. Prior to HU a tail ring was formed with a 2-0 sterile surgical steel wire that was passed through the 5(th), 6(th), or 7(th) inter-vertebral disc space and shaped into a ring from which the mice were suspended. Vertebral location for the tail-ring was selected to appropriately balance animal body weight without interfering with defecation. We determined the success of this novel HU technique by assessing body weight before and after HU, degree of soleus atrophy, and adrenal mass following HU. Body weight of the mice prior to HU (24.3 ± 2.9g) did not significantly decline immediately after 14d of HU (22.7 ± 1.9g), 28d of HU (21.3 + 2.1g) or after 3 days recovery (24.0 ± 1.8g). Soleus muscle mass significantly declined (-39.1%, and -46.6%) following HU for 14 days and 28 days respectively (p<0.001). Following 3 days of recovery soleus mass significantly increased to 74% of control values. Adrenal weights of HU mice were not different compared to control mice. The success of our novel HU method is evidenced by the maintenance of animal body weight, comparable adrenal gland weights, and soleus atrophy following HU, corresponding to expected literature values. The primary advantages of this HU method include: 1) ease of tail examination during suspension; 2) decreased likelihood of cyanotic, inflamed, and/or necrotic tails frequently observed with tail-taping and HU; 3) no possibility of mice chewing the traction tape and coming out of the suspension

15. Avocado oil extraction processes: method for cold-pressed high-quality edible oil production versus traditional production

OpenAIRE

Giacomo Costagli; Matteo Betti

2015-01-01

Nowadays the avocado fruit (Persea americana Mill.) is widely regarded as an important fruit for its nutritional values, as it is rich in vital human nutrients. The avocado fruit is mainly sold fresh on the market, which however trades also a relevant quantity of second-grade fruits with a relatively high oil content. Traditionally, this oil is extracted from dried fruits by means of organic solvents, but a mechanical method is also used in general in locations where drying systems and/or sol...

16. Boosted beta regression.

Directory of Open Access Journals (Sweden)

Matthias Schmid

Full Text Available Regression analysis with a bounded outcome is a common problem in applied statistics. Typical examples include regression models for percentage outcomes and the analysis of ratings that are measured on a bounded scale. In this paper, we consider beta regression, which is a generalization of logit models to situations where the response is continuous on the interval (0,1. Consequently, beta regression is a convenient tool for analyzing percentage responses. The classical approach to fit a beta regression model is to use maximum likelihood estimation with subsequent AIC-based variable selection. As an alternative to this established - yet unstable - approach, we propose a new estimation technique called boosted beta regression. With boosted beta regression estimation and variable selection can be carried out simultaneously in a highly efficient way. Additionally, both the mean and the variance of a percentage response can be modeled using flexible nonlinear covariate effects. As a consequence, the new method accounts for common problems such as overdispersion and non-binomial variance structures.

17. HPLC method for simultaneous quantitative detection of quercetin and curcuminoids in traditional chinese medicines.

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Ang, Lee Fung; Yam, Mun Fei; Fung, Yvonne Tan Tze; Kiang, Peh Kok; Darwin, Yusrida

2014-12-01

Quercetin and curcuminoids are important bioactive compounds found in many herbs. Previously reported high performance liquid chromatography ultraviolet (HPLC-UV) methods for the detection of quercetin and curcuminoids have several disadvantages, including unsatisfactory separation times and lack of validation according the standard guidelines of the International Conference on Harmonisation of Technical Requirements for Registration of Pharmaceuticals for Human Use. A rapid, specific, reversed phase, HPLC-UV method with an isocratic elution of acetonitrile and 2% v/v acetic acid (40% : 60% v/v) (pH 2.6) at a flow rate of 1.3 mL/minutes, a column temperature of 35°C, and ultraviolet (UV) detection at 370 nm was developed. The method was validated and applied to the quantification of different types of market available Chinese medicine extracts, pills and tablets. The method allowed simultaneous determination of quercetin, bisdemethoxycurcumin, demethoxycurcumin and curcumin in the concentration ranges of 0.00488 ─ 200 μg/mL, 0.625 ─ 320 μg/mL, 0.07813 ─ 320 μg/mL and 0.03906 ─ 320 μg/mL, respectively. The limits of detection and quantification, respectively, were 0.00488 and 0.03906 μg/mL for quercetin, 0.62500 and 2.50000 μg/mL for bisdemethoxycurcumin, 0.07813 and 0.31250 μg/mL for demethoxycurcumin, and 0.03906 and 0.07813 μg/mL for curcumin. The percent relative intra day standard deviation (% RSD) values were 0.432 ─ 0.806 μg/mL, 0.576 ─ 0.723 μg/mL, 0.635 ─ 0.752 μg/mL and 0.655 ─ 0.732 μg/mL for quercetin, bisdemethoxycurcumin, demethoxycurcumin and curcumin, respectively, and those for intra day precision were 0.323 ─ 0.968 μg/mL, 0.805 ─ 0.854 μg/mL, 0.078 ─ 0.844 μg/mL and 0.275 ─ 0.829 μg/mL, respectively. The intra day accuracies were 99.589% ─ 100.821%, 98.588% ─ 101.084%, 9.289% ─ 100.88%, and 98.292% ─ 101.022% for quercetin, bisdemethoxycurcumin, demethoxycurcumin and curcumin, respectively, and the

18. Simulation Experiments in Practice: Statistical Design and Regression Analysis

OpenAIRE

Kleijnen, J.P.C.

2007-01-01

In practice, simulation analysts often change only one factor at a time, and use graphical analysis of the resulting Input/Output (I/O) data. The goal of this article is to change these traditional, naïve methods of design and analysis, because statistical theory proves that more information is obtained when applying Design Of Experiments (DOE) and linear regression analysis. Unfortunately, classic DOE and regression analysis assume a single simulation response that is normally and independen...

19. An experimental detrending approach to attributing change of pan evaporation in comparison with the traditional partial differential method

Science.gov (United States)

Wang, Tingting; Sun, Fubao; Xia, Jun; Liu, Wenbin; Sang, Yanfang

2017-04-01

20. The CREATE Method Does Not Result in Greater Gains in Critical Thinking than a More Traditional Method of Analyzing the Primary Literature †

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Segura-Totten, Miriam; Dalman, Nancy E.

2013-01-01

Analysis of the primary literature in the undergraduate curriculum is associated with gains in student learning. In particular, the CREATE (Consider, Read, Elucidate hypotheses, Analyze and interpret the data, and Think of the next Experiment) method is associated with an increase in student critical thinking skills. We adapted the CREATE method within a required cell biology class and compared the learning gains of students using CREATE to those of students involved in less structured literature discussions. We found that while both sets of students had gains in critical thinking, students who used the CREATE method did not show significant improvement over students engaged in a more traditional method for dissecting the literature. Students also reported similar learning gains for both literature discussion methods. Our study suggests that, at least in our educational context, the CREATE method does not lead to higher learning gains than a less structured way of reading primary literature. PMID:24358379

1. [Screen potential CYP450 2E1 inhibitors from Chinese herbal medicine based on support vector regression and molecular docking method].

Science.gov (United States)

Chen, Xi; Lu, Fang; Jiang, Lu-di; Cai, Yi-Lian; Li, Gong-Yu; Zhang, Yan-Ling

2016-07-01

Inhibition of cytochrome P450 (CYP450) enzymes is the most common reasons for drug interactions, so the study on early prediction of CYPs inhibitors can help to decrease the incidence of adverse reactions caused by drug interactions.CYP450 2E1(CYP2E1), as a key role in drug metabolism process, has broad spectrum of drug metabolism substrate. In this study, 32 CYP2E1 inhibitors were collected for the construction of support vector regression (SVR) model. The test set data were used to verify CYP2E1 quantitative models and obtain the optimal prediction model of CYP2E1 inhibitor. Meanwhile, one molecular docking program, CDOCKER, was utilized to analyze the interaction pattern between positive compounds and active pocket to establish the optimal screening model of CYP2E1 inhibitors.SVR model and molecular docking prediction model were combined to screen traditional Chinese medicine database (TCMD), which could improve the calculation efficiency and prediction accuracy. 6 376 traditional Chinese medicine (TCM) compounds predicted by SVR model were obtained, and in further verification by using molecular docking model, 247 TCM compounds with potential inhibitory activities against CYP2E1 were finally retained. Some of them have been verified by experiments. The results demonstrated that this study could provide guidance for the virtual screening of CYP450 inhibitors and the prediction of CYPs-mediated DDIs, and also provide references for clinical rational drug use. Copyright© by the Chinese Pharmaceutical Association.

2. Effects of combined traditional processing methods on the nutritional quality of beans.

Science.gov (United States)

Nakitto, Aisha M; Muyonga, John H; Nakimbugwe, Dorothy

2015-05-01

Consumption of dry beans is limited by long cooking times thus high fuel requirement. The bioavailability of nutrients in beans is also limited due to presence of antinutrients such as phytates and tannins. Little research has been done on combined processing methods for production of nutritious fast cooking bean flour and the effect of combined treatments on nutritional quality of beans has not previously determined. The aim of this study was to reduce cooking time and enhance the nutritional value of dry beans. Specifically to: develop protocols for production of fast cooking bean flours and assess the effect of processing on the nutritional characteristics of the flours. Dry beans (K131 variety) were soaked for 12 h; sprouted for 48 h; dehulled and steamed for 25 and 15 min for whole and dehulled beans respectively or roasted at 170°C for 45 and 15 min for whole and dehulled beans respectively. Dehulling eliminated phytates and tannins and increased protein digestibility. In vitro protein digestibility and mineral (iron and zinc) extractability were negatively correlated with tannin and phytate content. Total available carbohydrates were highest in moist heat-treated bean flours. Overall, combined processing of beans improved the nutritional quality of dry beans and the resulting precooked flours need less cooking time compared to whole dry beans.

3. Informed consent recall and comprehension in orthodontics: traditional vs improved readability and processability methods.

Science.gov (United States)

Kang, Edith Y; Fields, Henry W; Kiyak, Asuman; Beck, F Michael; Firestone, Allen R

2009-10-01

Low general and health literacy in the United States means informed consent documents are not well understood by most adults. Methods to improve recall and comprehension of informed consent have not been tested in orthodontics. The purposes of this study were to evaluate (1) recall and comprehension among patients and parents by using the American Association of Orthodontists' (AAO) informed consent form and new forms incorporating improved readability and processability; (2) the association between reading ability, anxiety, and sociodemographic variables and recall and comprehension; and (3) how various domains (treatment, risk, and responsibility) of information are affected by the forms. Three treatment groups (30 patient-parent pairs in each) received an orthodontic case presentation and either the AAO form, an improved readability form (MIC), or an improved readability and processability (pairing audio and visual cues) form (MIC + SS). Structured interviews were transcribed and coded to evaluate recall and comprehension. Significant relationships among patient-related variables and recall and comprehension explained little of the variance. The MIC + SS form significantly improved patient recall and parent recall and comprehension. Recall was better than comprehension, and parents performed better than patients. The MIC + SS form significantly improved patient treatment comprehension and risk recall and parent treatment recall and comprehension. Patients and parents both overestimated their understanding of the materials. Improving the readability of consent materials made little difference, but combining improved readability and processability benefited both patients' recall and parents' recall and comprehension compared with the AAO form.

4. An investigation into the Traditional Method of Production of Omani Sarooj

Directory of Open Access Journals (Sweden)

A. W. Hago

1999-12-01

Full Text Available In the past, sarooj had been used as the basic cementing material with which the A flaj system (the irrigation system used in Oman was built. Worldwide, materials like sarooj existed and were known for their good impermeability and long durability. For this reason it was extensively used in hydraulic structures. Even in this century and with the ready availability of Portland cements, special plants were erected to produce materials like sarooj for major dams in the world. In the process of hydration In sarooj-lime mixes or in sarooj-cement mixes free lime is released which causes distress through the expansion of the mortar if allowed to accumulate. If free lime is stabilized within the structure of the mortar. it imparts additional strength and durability to it. The mortar becomes less permeable to water, which increases its resistance to wearhering. The stabilization is possible through the presence of a reactive silica/alumina in the mix so that it reacts with the free lime to form calcium silicates/aluminates. The properties of sarooj depend largely on the type of the raw material and the calcination parameters. This paper describes this material, its method of production and uses, and highlights research currently conducted to improve its properties.

5. Detecting sea-level hazards: Simple regression-based methods for calculating the acceleration of sea level

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Doran, Kara S.; Howd, Peter A.; Sallenger,, Asbury H.

2016-01-04

This report documents the development of statistical tools used to quantify the hazard presented by the response of sea-level elevation to natural or anthropogenic changes in climate and ocean circulation. A hazard is a physical process (or processes) that, when combined with vulnerability (or susceptibility to the hazard), results in risk. This study presents the development and comparison of new and existing sea-level analysis methods, exploration of the strengths and weaknesses of the methods using synthetic time series, and when appropriate, synthesis of the application of the method to observed sea-level time series. These reports are intended to enhance material presented in peer-reviewed journal articles where it is not always possible to provide the level of detail that might be necessary to fully support or recreate published results.

6. Data-driven method based on particle swarm optimization and k-nearest neighbor regression for estimating capacity of lithium-ion battery

International Nuclear Information System (INIS)

Hu, Chao; Jain, Gaurav; Zhang, Puqiang; Schmidt, Craig; Gomadam, Parthasarathy; Gorka, Tom

2014-01-01

Highlights: • We develop a data-driven method for the battery capacity estimation. • Five charge-related features that are indicative of the capacity are defined. • The kNN regression model captures the dependency of the capacity on the features. • Results with 10 years’ continuous cycling data verify the effectiveness of the method. - Abstract: Reliability of lithium-ion (Li-ion) rechargeable batteries used in implantable medical devices has been recognized as of high importance from a broad range of stakeholders, including medical device manufacturers, regulatory agencies, physicians, and patients. To ensure Li-ion batteries in these devices operate reliably, it is important to be able to assess the battery health condition by estimating the battery capacity over the life-time. This paper presents a data-driven method for estimating the capacity of Li-ion battery based on the charge voltage and current curves. The contributions of this paper are three-fold: (i) the definition of five characteristic features of the charge curves that are indicative of the capacity, (ii) the development of a non-linear kernel regression model, based on the k-nearest neighbor (kNN) regression, that captures the complex dependency of the capacity on the five features, and (iii) the adaptation of particle swarm optimization (PSO) to finding the optimal combination of feature weights for creating a kNN regression model that minimizes the cross validation (CV) error in the capacity estimation. Verification with 10 years’ continuous cycling data suggests that the proposed method is able to accurately estimate the capacity of Li-ion battery throughout the whole life-time

7. A regression-based method for mapping traffic-related air pollution. Application and testing in four contrasting urban environments

International Nuclear Information System (INIS)

Briggs, D.J.; De Hoogh, C.; Elliot, P.; Gulliver, J.; Wills, J.; Kingham, S.; Smallbone, K.

2000-01-01

Accurate, high-resolution maps of traffic-related air pollution are needed both as a basis for assessing exposures as part of epidemiological studies, and to inform urban air-quality policy and traffic management. This paper assesses the use of a GIS-based, regression mapping technique to model spatial patterns of traffic-related air pollution. The model - developed using data from 80 passive sampler sites in Huddersfield, as part of the SAVIAH (Small Area Variations in Air Quality and Health) project - uses data on traffic flows and land cover in the 300-m buffer zone around each site, and altitude of the site, as predictors of NO 2 concentrations. It was tested here by application in four urban areas in the UK: Huddersfield (for the year following that used for initial model development), Sheffield, Northampton, and part of London. In each case, a GIS was built in ArcInfo, integrating relevant data on road traffic, urban land use and topography. Monitoring of NO 2 was undertaken using replicate passive samplers (in London, data were obtained from surveys carried out as part of the London network). In Huddersfield, Sheffield and Northampton, the model was first calibrated by comparing modelled results with monitored NO 2 concentrations at 10 randomly selected sites; the calibrated model was then validated against data from a further 10-28 sites. In London, where data for only 11 sites were available, validation was not undertaken. Results showed that the model performed well in all cases. After local calibration, the model gave estimates of mean annual NO 2 concentrations within a factor of 1.5 of the actual mean (approx. 70-90%) of the time and within a factor of 2 between 70 and 100% of the time. r 2 values between modelled and observed concentrations are in the range of 0.58-0.76. These results are comparable to those achieved by more sophisticated dispersion models. The model also has several advantages over dispersion modelling. It is able, for example, to

8. The comparison of composite aircraft field repair method (cafrm) with traditional aircraft repair technologies

Science.gov (United States)

Whelan, Mary Elizabeth

The sulfur biogeochemical cycle includes biotic and abiotic processes important to global climate, atmospheric chemistry, food security, and the study of related cycles. The largest flux of sulfur on Earth is weathering from the continents into the sulfate-rich oceans; one way in which sulfur can be returned to land is through transport of reduced sulfur gases via the atmosphere. Here I developed a method for quantifying low-level environmental fluxes of several sulfur-containing gases, H2S, COS, CH3SCH 3 (DMS), and HSCH3, between terrestrial ecosystems and the atmosphere. COS is the most prevalent reduced sulfur gas in the atmosphere, considered to be inert in the troposphere except for its uptake in plant leaves and to a smaller extent aerobic soils. This dissertation reports two surprising cases that go against conventional thinking about the sulfur cycle. We found that the common salt marsh plant Batis maritima can mediate net COS production to the atmosphere. We also found that an aerobic wheat field soil produces COS abiotically when incubated in the dark at > 25 °C and at lower temperatures under light conditions. We then sought to separately quantify plant and soil sulfur gas fluxes by undertaking a year-long field campaign in a grassland with a Mediterranean climate, where green plants were present only half of the year. We measured in situ soil fluxes of COS and DMS during the non- growing dry season, using water additions to simulate soil fluxes of the growing, wet season. COS and CO2 are consumed in a predictable ratio by enzymes involved in photosynthetic pathways; however, while CO2 is released by back diffusion and autorespiration, COS is usually not generated by plants. Using measurements during the growing season, we were then able to calculate gross primary production by using the special relationship between CO2 and COS. This dissertation has developed a greater understanding of the vagaries of the atmospheric-terrestrial sulfur cycle and

9. A building characterization-based method for the advancement of knowledge on external architectural features of traditional rural buildings

Directory of Open Access Journals (Sweden)

Porto, S. M. C.

2013-12-01

10. Effects of global signal regression and subtraction methods on resting-state functional connectivity using arterial spin labeling data.

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Silva, João Paulo Santos; Mônaco, Luciana da Mata; Paschoal, André Monteiro; Oliveira, Ícaro Agenor Ferreira de; Leoni, Renata Ferranti

2018-05-16

Arterial spin labeling (ASL) is an established magnetic resonance imaging (MRI) technique that is finding broader applications in functional studies of the healthy and diseased brain. To promote improvement in cerebral blood flow (CBF) signal specificity, many algorithms and imaging procedures, such as subtraction methods, were proposed to eliminate or, at least, minimize noise sources. Therefore, this study addressed the main considerations of how CBF functional connectivity (FC) is changed, regarding resting brain network (RBN) identification and correlations between regions of interest (ROI), by different subtraction methods and removal of residual motion artifacts and global signal fluctuations (RMAGSF). Twenty young healthy participants (13 M/7F, mean age = 25 ± 3 years) underwent an MRI protocol with a pseudo-continuous ASL (pCASL) sequence. Perfusion-based images were obtained using simple, sinc and running subtraction. RMAGSF removal was applied to all CBF time series. Independent Component Analysis (ICA) was used for RBN identification, while Pearson' correlation was performed for ROI-based FC analysis. Temporal signal-to-noise ratio (tSNR) was higher in CBF maps obtained by sinc subtraction, although RMAGSF removal had a significant effect on maps obtained with simple and running subtractions. Neither the subtraction method nor the RMAGSF removal directly affected the identification of RBNs. However, the number of correlated and anti-correlated voxels varied for different subtraction and filtering methods. In an ROI-to-ROI level, changes were prominent in FC values and their statistical significance. Our study showed that both RMAGSF filtering and subtraction method might influence resting-state FC results, especially in an ROI level, consequently affecting FC analysis and its interpretation. Taking our results and the whole discussion together, we understand that for an exploratory assessment of the brain, one could avoid removing RMAGSF to

11. Application of NIRS coupled with PLS regression as a rapid, non-destructive alternative method for quantification of KBA in Boswellia sacra

Science.gov (United States)

Al-Harrasi, Ahmed; Rehman, Najeeb Ur; Mabood, Fazal; Albroumi, Muhammaed; Ali, Liaqat; Hussain, Javid; Hussain, Hidayat; Csuk, René; Khan, Abdul Latif; Alam, Tanveer; Alameri, Saif

2017-09-01

In the present study, for the first time, NIR spectroscopy coupled with PLS regression as a rapid and alternative method was developed to quantify the amount of Keto-β-Boswellic Acid (KBA) in different plant parts of Boswellia sacra and the resin exudates of the trunk. NIR spectroscopy was used for the measurement of KBA standards and B. sacra samples in absorption mode in the wavelength range from 700-2500 nm. PLS regression model was built from the obtained spectral data using 70% of KBA standards (training set) in the range from 0.1 ppm to 100 ppm. The PLS regression model obtained was having R-square value of 98% with 0.99 corelationship value and having good prediction with RMSEP value 3.2 and correlation of 0.99. It was then used to quantify the amount of KBA in the samples of B. sacra. The results indicated that the MeOH extract of resin has the highest concentration of KBA (0.6%) followed by essential oil (0.1%). However, no KBA was found in the aqueous extract. The MeOH extract of the resin was subjected to column chromatography to get various sub-fractions at different polarity of organic solvents. The sub-fraction at 4% MeOH/CHCl3 (4.1% of KBA) was found to contain the highest percentage of KBA followed by another sub-fraction at 2% MeOH/CHCl3 (2.2% of KBA). The present results also indicated that KBA is only present in the gum-resin of the trunk and not in all parts of the plant. These results were further confirmed through HPLC analysis and therefore it is concluded that NIRS coupled with PLS regression is a rapid and alternate method for quantification of KBA in Boswellia sacra. It is non-destructive, rapid, sensitive and uses simple methods of sample preparation.

12. Polynomial regression analysis and significance test of the regression function

International Nuclear Information System (INIS)

Gao Zhengming; Zhao Juan; He Shengping

2012-01-01

In order to analyze the decay heating power of a certain radioactive isotope per kilogram with polynomial regression method, the paper firstly demonstrated the broad usage of polynomial function and deduced its parameters with ordinary least squares estimate. Then significance test method of polynomial regression function is derived considering the similarity between the polynomial regression model and the multivariable linear regression model. Finally, polynomial regression analysis and significance test of the polynomial function are done to the decay heating power of the iso tope per kilogram in accord with the authors' real work. (authors)

13. A note on the relationships between multiple imputation, maximum likelihood and fully Bayesian methods for missing responses in linear regression models.

Science.gov (United States)

Chen, Qingxia; Ibrahim, Joseph G

2014-07-01

Multiple Imputation, Maximum Likelihood and Fully Bayesian methods are the three most commonly used model-based approaches in missing data problems. Although it is easy to show that when the responses are missing at random (MAR), the complete case analysis is unbiased and efficient, the aforementioned methods are still commonly used in practice for this setting. To examine the performance of and relationships between these three methods in this setting, we derive and investigate small sample and asymptotic expressions of the estimates and standard errors, and fully examine how these estimates are related for the three approaches in the linear regression model when the responses are MAR. We show that when the responses are MAR in the linear model, the estimates of the regression coefficients using these three methods are asymptotically equivalent to the complete case estimates under general conditions. One simulation and a real data set from a liver cancer clinical trial are given to compare the properties of these methods when the responses are MAR.

14. Preliminary study on the inactivation of anisakid larvae in baccalà prepared according to traditional methods

Directory of Open Access Journals (Sweden)

Giorgio Smaldone

2017-11-01

Full Text Available The European Food Safety Authority stated that many traditional marinating and cold smoking methods are not sufficient to kill A. simplex and asked to evaluate alternative treatments for killing viable parasites in fishery. Baccalà is a well-liked traditional product. The aim of study was to evaluate the effectiveness of the salting process on the inactivation of nematodes of the genus Anisakis in naturally infected Baccalà fillets. N. 19 fillets, subjected to a dual salting process (brine and dry salting were analyzed. Visual inspection and chloropeptic digestion were performed. Larvae viability was evaluated, and parameters such as NaCl (%, moisture (%, WPS and aw were determined. In n. 17 samples parasites were found 123 parasites with a mean intensity of 7.23±4.78 and an mean abundance of 6.47±5.05. Visual examination has revealed 109 parasites. 61.8% of larvae were found in the ventral portions. The results show that salting process with a salt concentration of 18.6%, aw values of 0.7514 and 24.15% WPS in all parts of baccalà fillets, devitalise Anisakidae larvae in a 15-day period.

15. Preliminary study on the inactivation of anisakid larvae in baccalà prepared according to traditional methods.

Science.gov (United States)

Smaldone, Giorgio; Marrone, Raffaele; Palma, Giuseppe; Sarnelli, Paolo; Anastasio, Aniello

2017-10-20

The European Food Safety Authority stated that many traditional marinating and cold smoking methods are not sufficient to kill A. simplex and asked to evaluate alternative treatments for killing viable parasites in fishery . Baccalà is a well-liked traditional product. The aim of study was to evaluate the effectiveness of the salting process on the inactivation of nematodes of the genus Anisakis in naturally infected Baccalà fillets. N. 19 fillets, subjected to a dual salting process (brine and dry salting) were analyzed. Visual inspection and chloropeptic digestion were performed. Larvae viability was evaluated, and parameters such as NaCl (%), moisture (%), WPS and a w were determined. In n. 17 samples parasites were found 123 parasites with a mean intensity of 7.23±4.78 and an mean abundance of 6.47±5.05. Visual examination has revealed 109 parasites. 61.8% of larvae were found in the ventral portions. The results show that salting process with a salt concentration of 18.6%, a w values of 0.7514 and 24.15% WPS in all parts of baccalà fillets, devitalise Anisakidae larvae in a 15-day period.

16. Determination of genetic structure of germplasm collections: are traditional hierarchical clustering methods appropriate for molecular marker data?

NARCIS (Netherlands)

Odong, T.L.; Heerwaarden, van J.; Jansen, J.; Hintum, van T.J.L.; Eeuwijk, van F.A.

2011-01-01

Despite the availability of newer approaches, traditional hierarchical clustering remains very popular in genetic diversity studies in plants. However, little is known about its suitability for molecular marker data. We studied the performance of traditional hierarchical clustering techniques using

17. Linear Regression Analysis

CERN Document Server

Seber, George A F

2012-01-01

Concise, mathematically clear, and comprehensive treatment of the subject.* Expanded coverage of diagnostics and methods of model fitting.* Requires no specialized knowledge beyond a good grasp of matrix algebra and some acquaintance with straight-line regression and simple analysis of variance models.* More than 200 problems throughout the book plus outline solutions for the exercises.* This revision has been extensively class-tested.

18. Support vector machine regression (SVR/LS-SVM)--an alternative to neural networks (ANN) for analytical chemistry? Comparison of nonlinear methods on near infrared (NIR) spectroscopy data.

Science.gov (United States)

Balabin, Roman M; Lomakina, Ekaterina I

2011-04-21

In this study, we make a general comparison of the accuracy and robustness of five multivariate calibration models: partial least squares (PLS) regression or projection to latent structures, polynomial partial least squares (Poly-PLS) regression, artificial neural networks (ANNs), and two novel techniques based on support vector machines (SVMs) for multivariate data analysis: support vector regression (SVR) and least-squares support vector machines (LS-SVMs). The comparison is based on fourteen (14) different datasets: seven sets of gasoline data (density, benzene content, and fractional composition/boiling points), two sets of ethanol gasoline fuel data (density and ethanol content), one set of diesel fuel data (total sulfur content), three sets of petroleum (crude oil) macromolecules data (weight percentages of asphaltenes, resins, and paraffins), and one set of petroleum resins data (resins content). Vibrational (near-infrared, NIR) spectroscopic data are used to predict the properties and quality coefficients of gasoline, biofuel/biodiesel, diesel fuel, and other samples of interest. The four systems presented here range greatly in composition, properties, strength of intermolecular interactions (e.g., van der Waals forces, H-bonds), colloid structure, and phase behavior. Due to the high diversity of chemical systems studied, general conclusions about SVM regression methods can be made. We try to answer the following question: to what extent can SVM-based techniques replace ANN-based approaches in real-world (industrial/scientific) applications? The results show that both SVR and LS-SVM methods are comparable to ANNs in accuracy. Due to the much higher robustness of the former, the SVM-based approaches are recommended for practical (industrial) application. This has been shown to be especially true for complicated, highly nonlinear objects.

19. Empirical estimation of the grades of hearing impairment among industrial workers based on new artificial neural networks and classical regression methods.

Science.gov (United States)

2015-01-01

Prediction models are used in a variety of medical domains, and they are frequently built from experience which constitutes data acquired from actual cases. This study aimed to analyze the potential of artificial neural networks and logistic regression techniques for estimation of hearing impairment among industrial workers. A total of 210 workers employed in a steel factory (in West of Iran) were selected, and their occupational exposure histories were analyzed. The hearing loss thresholds of the studied workers were determined using a calibrated audiometer. The personal noise exposures were also measured using a noise dosimeter in the workstations. Data obtained from five variables, which can influence the hearing loss, were used as input features, and the hearing loss thresholds were considered as target feature of the prediction methods. Multilayer feedforward neural networks and logistic regression were developed using MATLAB R2011a software. Based on the World Health Organization classification for the grades of hearing loss, 74.2% of the studied workers have normal hearing thresholds, 23.4% have slight hearing loss, and 2.4% have moderate hearing loss. The accuracy and kappa coefficient of the best developed neural networks for prediction of the grades of hearing loss were 88.6 and 66.30, respectively. The accuracy and kappa coefficient of the logistic regression were also 84.28 and 51.30, respectively. Neural networks could provide more accurate predictions of the hearing loss than logistic regression. The prediction method can provide reliable and comprehensible information for occupational health and medicine experts.

20. Comparative evaluation of reproductive parameters between the automatic GEDIS cervical insemination method and the traditional in multicolor bristles

Directory of Open Access Journals (Sweden)

Núñez-Torres Oscar Patricio

2017-04-01

Full Text Available The research was carried out in Ecuador, in the province of Tungurahua, Cevallos county. A comparison of reproductive parameters between the cervical self insemination method and the traditional one in multiparous sows was performed using 12 sows (hybrid females between the second and fourth calving, dividing In two groups of 6 sows respectively, using the insemination protocol 12h - 24h - 36h. Fresh semen was prepared with long-term diluent + bidistilled water, at a concentration of 3 x 109 spermatozoa/mL in total volume per 100 mL straw. At the time of insemination the amount of seminal reflux was determined and when the Student's T test was applied with paired observations in the results, they statistically reported a significant difference at 5% among the evaluated methods, the calculated T value was 9.50 Which is greater than the T of tables at 5% of 2.57. The duration of each method was determined, results that reported similarity between the two methods (15 min. At 21 days post insemination pregnancy was diagnosed by ultrasound and evaluation of no return of heat, results that reported in both methods 100% effectiveness. Subsequently, at the time of delivery, the number of total born piglets was evaluated, using the Student's T-test with paired observations that statistically there was no significant difference at 5% between the two methods, the calculated T value was 0, 14 which is less than the T of tables at 5% of 2.57. We also determined the weight of piglets at birth, reported by Student's t-test with paired observations that there is a statistically significant difference to 5% among the evaluated methods, the calculated T value was 5.17, which is higher than the T Of tables at 5% of 2.57. As for costs there is no considerable difference.

1. Application of nonparametric regression methods to study the relationship between NO2 concentrations and local wind direction and speed at background sites.

Science.gov (United States)

Donnelly, Aoife; Misstear, Bruce; Broderick, Brian

2011-02-15

Background concentrations of nitrogen dioxide (NO(2)) are not constant but vary temporally and spatially. The current paper presents a powerful tool for the quantification of the effects of wind direction and wind speed on background NO(2) concentrations, particularly in cases where monitoring data are limited. In contrast to previous studies which applied similar methods to sites directly affected by local pollution sources, the current study focuses on background sites with the aim of improving methods for predicting background concentrations adopted in air quality modelling studies. The relationship between measured NO(2) concentration in air at three such sites in Ireland and locally measured wind direction has been quantified using nonparametric regression methods. The major aim was to analyse a method for quantifying the effects of local wind direction on background levels of NO(2) in Ireland. The method was expanded to include wind speed as an added predictor variable. A Gaussian kernel function is used in the analysis and circular statistics employed for the wind direction variable. Wind direction and wind speed were both found to have a statistically significant effect on background levels of NO(2) at all three sites. Frequently environmental impact assessments are based on short term baseline monitoring producing a limited dataset. The presented non-parametric regression methods, in contrast to the frequently used methods such as binning of the data, allow concentrations for missing data pairs to be estimated and distinction between spurious and true peaks in concentrations to be made. The methods were found to provide a realistic estimation of long term concentration variation with wind direction and speed, even for cases where the data set is limited. Accurate identification of the actual variation at each location and causative factors could be made, thus supporting the improved definition of background concentrations for use in air quality modelling

2. Linear regression in astronomy. I

Science.gov (United States)

Isobe, Takashi; Feigelson, Eric D.; Akritas, Michael G.; Babu, Gutti Jogesh

1990-01-01

Five methods for obtaining linear regression fits to bivariate data with unknown or insignificant measurement errors are discussed: ordinary least-squares (OLS) regression of Y on X, OLS regression of X on Y, the bisector of the two OLS lines, orthogonal regression, and 'reduced major-axis' regression. These methods have been used by various researchers in observational astronomy, most importantly in cosmic distance scale applications. Formulas for calculating the slope and intercept coefficients and their uncertainties are given for all the methods, including a new general form of the OLS variance estimates. The accuracy of the formulas was confirmed using numerical simulations. The applicability of the procedures is discussed with respect to their mathematical properties, the nature of the astronomical data under consideration, and the scientific purpose of the regression. It is found that, for problems needing symmetrical treatment of the variables, the OLS bisector performs significantly better than orthogonal or reduced major-axis regression.

3. Classification and regression trees

CERN Document Server

Breiman, Leo; Olshen, Richard A; Stone, Charles J

1984-01-01

The methodology used to construct tree structured rules is the focus of this monograph. Unlike many other statistical procedures, which moved from pencil and paper to calculators, this text's use of trees was unthinkable before computers. Both the practical and theoretical sides have been developed in the authors' study of tree methods. Classification and Regression Trees reflects these two sides, covering the use of trees as a data analysis method, and in a more mathematical framework, proving some of their fundamental properties.

4. The Combination of DGT Technique and Traditional Chemical Methods for Evaluation of Cadmium Bioavailability in Contaminated Soils with Organic Amendment

Science.gov (United States)

Yao, Yu; Sun, Qin; Wang, Chao; Wang, Pei-Fang; Miao, Ling-Zhan; Ding, Shi-Ming

2016-01-01

Organic amendments have been proposed as a means of remediation for Cd-contaminated soils. However, understanding the inhibitory effects of organic materials on metal immobilization requires further research. In this study colza cake, a typical organic amendment material, was investigated in order to elucidate the ability of this material to reduce toxicity of Cd-contaminated soil. Available concentrations of Cd in soils were measured using an in situ diffusive gradients in thin films (DGT) technique in combination with traditional chemical methods, such as HOAc (aqua regia), EDTA (ethylene diamine tetraacetic acid), NaOAc (sodium acetate), CaCl2, and labile Cd in pore water. These results were applied to predict the Cd bioavailability after the addition of colza cake to Cd-contaminated soil. Two commonly grown cash crops, wheat and maize, were selected for Cd accumulation studies, and were found to be sensitive to Cd bioavailability. Results showed that the addition of colza cake may inhibit the growth of wheat and maize. Furthermore, the addition of increasing colza cake doses led to decreasing shoot and root biomass accumulation. However, increasing colza cake doses did lead to the reduction of Cd accumulation in plant tissues, as indicated by the decreasing Cd concentrations in shoots and roots. The labile concentration of Cd obtained by DGT measurements and the traditional chemical extraction methods, showed the clear decrease of Cd with the addition of increasing colza cake doses. All indicators showed significant positive correlations (p soil solution decreased with increasing colza cake doses. This was reflected by the decreases in the ratio (R) value of CDGT to Csol. Our study suggests that the sharp decrease in R values could not only reflect the extremely low capability of labile Cd to be released from its solid phase, but may also be applied to evaluate the abnormal growth of the plants. PMID:27314376

5. The Combination of DGT Technique and Traditional Chemical Methods for Evaluation of Cadmium Bioavailability in Contaminated Soils with Organic Amendment.

Science.gov (United States)

Yao, Yu; Sun, Qin; Wang, Chao; Wang, Pei-Fang; Miao, Ling-Zhan; Ding, Shi-Ming

2016-06-15

Organic amendments have been proposed as a means of remediation for Cd-contaminated soils. However, understanding the inhibitory effects of organic materials on metal immobilization requires further research. In this study colza cake, a typical organic amendment material, was investigated in order to elucidate the ability of this material to reduce toxicity of Cd-contaminated soil. Available concentrations of Cd in soils were measured using an in situ diffusive gradients in thin films (DGT) technique in combination with traditional chemical methods, such as HOAc (aqua regia), EDTA (ethylene diamine tetraacetic acid), NaOAc (sodium acetate), CaCl₂, and labile Cd in pore water. These results were applied to predict the Cd bioavailability after the addition of colza cake to Cd-contaminated soil. Two commonly grown cash crops, wheat and maize, were selected for Cd accumulation studies, and were found to be sensitive to Cd bioavailability. Results showed that the addition of colza cake may inhibit the growth of wheat and maize. Furthermore, the addition of increasing colza cake doses led to decreasing shoot and root biomass accumulation. However, increasing colza cake doses did lead to the reduction of Cd accumulation in plant tissues, as indicated by the decreasing Cd concentrations in shoots and roots. The labile concentration of Cd obtained by DGT measurements and the traditional chemical extraction methods, showed the clear decrease of Cd with the addition of increasing colza cake doses. All indicators showed significant positive correlations (p soil solution decreased with increasing colza cake doses. This was reflected by the decreases in the ratio (R) value of CDGT to Csol. Our study suggests that the sharp decrease in R values could not only reflect the extremely low capability of labile Cd to be released from its solid phase, but may also be applied to evaluate the abnormal growth of the plants.

6. Effects of categorization method, regression type, and variable distribution on the inflation of Type-I error rate when categorizing a confounding variable.

Science.gov (United States)

Barnwell-Ménard, Jean-Louis; Li, Qing; Cohen, Alan A

2015-03-15

The loss of signal associated with categorizing a continuous variable is well known, and previous studies have demonstrated that this can lead to an inflation of Type-I error when the categorized variable is a confounder in a regression analysis estimating the effect of an exposure on an outcome. However, it is not known how the Type-I error may vary under different circumstances, including logistic versus linear regression, different distributions of the confounder, and different categorization methods. Here, we analytically quantified the effect of categorization and then performed a series of 9600 Monte Carlo simulations to estimate the Type-I error inflation associated with categorization of a confounder under different regression scenarios. We show that Type-I error is unacceptably high (>10% in most scenarios and often 100%). The only exception was when the variable categorized was a continuous mixture proxy for a genuinely dichotomous latent variable, where both the continuous proxy and the categorized variable are error-ridden proxies for the dichotomous latent variable. As expected, error inflation was also higher with larger sample size, fewer categories, and stronger associations between the confounder and the exposure or outcome. We provide online tools that can help researchers estimate the potential error inflation and understand how serious a problem this is. Copyright © 2014 John Wiley & Sons, Ltd.

7. Data mining methods in the prediction of Dementia: A real-data comparison of the accuracy, sensitivity and specificity of linear discriminant analysis, logistic regression, neural networks, support vector machines, classification trees and random forests

Directory of Open Access Journals (Sweden)

Santana Isabel

2011-08-01

Full Text Available Abstract Background Dementia and cognitive impairment associated with aging are a major medical and social concern. Neuropsychological testing is a key element in the diagnostic procedures of Mild Cognitive Impairment (MCI, but has presently a limited value in the prediction of progression to dementia. We advance the hypothesis that newer statistical classification methods derived from data mining and machine learning methods like Neural Networks, Support Vector Machines and Random Forests can improve accuracy, sensitivity and specificity of predictions obtained from neuropsychological testing. Seven non parametric classifiers derived from data mining methods (Multilayer Perceptrons Neural Networks, Radial Basis Function Neural Networks, Support Vector Machines, CART, CHAID and QUEST Classification Trees and Random Forests were compared to three traditional classifiers (Linear Discriminant Analysis, Quadratic Discriminant Analysis and Logistic Regression in terms of overall classification accuracy, specificity, sensitivity, Area under the ROC curve and Press'Q. Model predictors were 10 neuropsychological tests currently used in the diagnosis of dementia. Statistical distributions of classification parameters obtained from a 5-fold cross-validation were compared using the Friedman's nonparametric test. Results Press' Q test showed that all classifiers performed better than chance alone (p Conclusions When taking into account sensitivity, specificity and overall classification accuracy Random Forests and Linear Discriminant analysis rank first among all the classifiers tested in prediction of dementia using several neuropsychological tests. These methods may be used to improve accuracy, sensitivity and specificity of Dementia predictions from neuropsychological testing.

8. Vector regression introduced

Directory of Open Access Journals (Sweden)

Mok Tik

2014-06-01

Full Text Available This study formulates regression of vector data that will enable statistical analysis of various geodetic phenomena such as, polar motion, ocean currents, typhoon/hurricane tracking, crustal deformations, and precursory earthquake signals. The observed vector variable of an event (dependent vector variable is expressed as a function of a number of hypothesized phenomena realized also as vector variables (independent vector variables and/or scalar variables that are likely to impact the dependent vector variable. The proposed representation has the unique property of solving the coefficients of independent vector variables (explanatory variables also as vectors, hence it supersedes multivariate multiple regression models, in which the unknown coefficients are scalar quantities. For the solution, complex numbers are used to rep- resent vector information, and the method of least squares is deployed to estimate the vector model parameters after transforming the complex vector regression model into a real vector regression model through isomorphism. Various operational statistics for testing the predictive significance of the estimated vector parameter coefficients are also derived. A simple numerical example demonstrates the use of the proposed vector regression analysis in modeling typhoon paths.

9. GEPSI: A Gene Expression Profile Similarity-Based Identification Method of Bioactive Components in Traditional Chinese Medicine Formula.

Science.gov (United States)

Zhang, Baixia; He, Shuaibing; Lv, Chenyang; Zhang, Yanling; Wang, Yun

2018-01-01

The identification of bioactive components in traditional Chinese medicine (TCM) is an important part of the TCM material foundation research. Recently, molecular docking technology has been extensively used for the identification of TCM bioactive components. However, target proteins that are used in molecular docking may not be the actual TCM target. For this reason, the bioactive components would likely be omitted or incorrect. To address this problem, this study proposed the GEPSI method that identified the target proteins of TCM based on the similarity of gene expression profiles. The similarity of the gene expression profiles affected by TCM and small molecular drugs was calculated. The pharmacological action of TCM may be similar to that of small molecule drugs that have a high similarity score. Indeed, the target proteins of the small molecule drugs could be considered TCM targets. Thus, we identified the bioactive components of a TCM by molecular docking and verified the reliability of this method by a literature investigation. Using the target proteins that TCM actually affected as targets, the identification of the bioactive components was more accurate. This study provides a fast and effective method for the identification of TCM bioactive components.

10. A comparison of two methods of teaching. Computer managed instruction and keypad questions versus traditional classroom lecture.

Science.gov (United States)

Halloran, L

1995-01-01

Computers increasingly are being integrated into nursing education. One method of integration is through computer managed instruction (CMI). Recently, technology has become available that allows the integration of keypad questions into CMI. This brings a new type of interactivity between students and teachers into the classroom. The purpose of this study was to evaluate differences in achievement between a control group taught by traditional classroom lecture (TCL) and an experimental group taught using CMI and keypad questions. Both control and experimental groups consisted of convenience samples of junior nursing students in a baccalaureate program taking a medical/surgical nursing course. Achievement was measured by three instructor-developed multiple choice examinations. Findings demonstrated that although the experimental group demonstrated increasingly higher test scores as the semester progressed, no statistical difference was found in achievement between the two groups. One reason for this may be phenomenon of vampire video. Initially, the method of presentation overshadowed the content. As students became desensitized to the method, they were able to focus and absorb more content. This study suggests that CMI and keypads are a viable teaching option for nursing education. It is equal to TCL in student achievement and provides a new level of interaction in the classroom setting.

11. Estimating alcohol content of traditional brew in Western Kenya using culturally relevant methods: the case for cost over volume.

Science.gov (United States)

Papas, Rebecca K; Sidle, John E; Wamalwa, Emmanuel S; Okumu, Thomas O; Bryant, Kendall L; Goulet, Joseph L; Maisto, Stephen A; Braithwaite, R Scott; Justice, Amy C

2010-08-01

Traditional homemade brew is believed to represent the highest proportion of alcohol use in sub-Saharan Africa. In Eldoret, Kenya, two types of brew are common: chang'aa, spirits, and busaa, maize beer. Local residents refer to the amount of brew consumed by the amount of money spent, suggesting a culturally relevant estimation method. The purposes of this study were to analyze ethanol content of chang'aa and busaa; and to compare two methods of alcohol estimation: use by cost, and use by volume, the latter the current international standard. Laboratory results showed mean ethanol content was 34% (SD = 14%) for chang'aa and 4% (SD = 1%) for busaa. Standard drink unit equivalents for chang'aa and busaa, respectively, were 2 and 1.3 (US) and 3.5 and 2.3 (Great Britain). Using a computational approach, both methods demonstrated comparable results. We conclude that cost estimation of alcohol content is more culturally relevant and does not differ in accuracy from the international standard.

12. Differentiating regressed melanoma from regressed lichenoid keratosis.

Science.gov (United States)

Chan, Aegean H; Shulman, Kenneth J; Lee, Bonnie A

2017-04-01

Distinguishing regressed lichen planus-like keratosis (LPLK) from regressed melanoma can be difficult on histopathologic examination, potentially resulting in mismanagement of patients. We aimed to identify histopathologic features by which regressed melanoma can be differentiated from regressed LPLK. Twenty actively inflamed LPLK, 12 LPLK with regression and 15 melanomas with regression were compared and evaluated by hematoxylin and eosin staining as well as Melan-A, microphthalmia transcription factor (MiTF) and cytokeratin (AE1/AE3) immunostaining. (1) A total of 40% of regressed melanomas showed complete or near complete loss of melanocytes within the epidermis with Melan-A and MiTF immunostaining, while 8% of regressed LPLK exhibited this finding. (2) Necrotic keratinocytes were seen in the epidermis in 33% regressed melanomas as opposed to all of the regressed LPLK. (3) A dense infiltrate of melanophages in the papillary dermis was seen in 40% of regressed melanomas, a feature not seen in regressed LPLK. In summary, our findings suggest that a complete or near complete loss of melanocytes within the epidermis strongly favors a regressed melanoma over a regressed LPLK. In addition, necrotic epidermal keratinocytes and the presence of a dense band-like distribution of dermal melanophages can be helpful in differentiating these lesions. © 2016 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

13. Multiple Linear Regression Modeling To Predict the Stability of Polymer-Drug Solid Dispersions: Comparison of the Effects of Polymers and Manufacturing Methods on Solid Dispersion Stability.

Science.gov (United States)

Fridgeirsdottir, Gudrun A; Harris, Robert J; Dryden, Ian L; Fischer, Peter M; Roberts, Clive J

2018-03-29

Solid dispersions can be a successful way to enhance the bioavailability of poorly soluble drugs. Here 60 solid dispersion formulations were produced using ten chemically diverse, neutral, poorly soluble drugs, three commonly used polymers, and two manufacturing techniques, spray-drying and melt extrusion. Each formulation underwent a six-month stability study at accelerated conditions, 40 °C and 75% relative humidity (RH). Significant differences in times to crystallization (onset of crystallization) were observed between both the different polymers and the two processing methods. Stability from zero days to over one year was observed. The extensive experimental data set obtained from this stability study was used to build multiple linear regression models to correlate physicochemical properties of the active pharmaceutical ingredients (API) with the stability data. The purpose of these models is to indicate which combination of processing method and polymer carrier is most likely to give a stable solid dispersion. Six quantitative mathematical multiple linear regression-based models were produced based on selection of the most influential independent physical and chemical parameters from a set of 33 possible factors, one model for each combination of polymer and processing method, with good predictability of stability. Three general rules are proposed from these models for the formulation development of suitably stable solid dispersions. Namely, increased stability is correlated with increased glass transition temperature ( T g ) of solid dispersions, as well as decreased number of H-bond donors and increased molecular flexibility (such as rotatable bonds and ring count) of the drug molecule.

14. A comparison between univariate probabilistic and multivariate (logistic regression) methods for landslide susceptibility analysis: the example of the Febbraro valley (Northern Alps, Italy)

Science.gov (United States)

Rossi, M.; Apuani, T.; Felletti, F.

2009-04-01

The aim of this paper is to compare the results of two statistical methods for landslide susceptibility analysis: 1) univariate probabilistic method based on landslide susceptibility index, 2) multivariate method (logistic regression). The study area is the Febbraro valley, located in the central Italian Alps, where different types of metamorphic rocks croup out. On the eastern part of the studied basin a quaternary cover represented by colluvial and secondarily, by glacial deposits, is dominant. In this study 110 earth flows, mainly located toward NE portion of the catchment, were analyzed. They involve only the colluvial deposits and their extension mainly ranges from 36 to 3173 m2. Both statistical methods require to establish a spatial database, in which each landslide is described by several parameters that can be assigned using a main scarp central point of landslide. The spatial database is constructed using a Geographical Information System (GIS). Each landslide is described by several parameters corresponding to the value of main scarp central point of the landslide. Based on bibliographic review a total of 15 predisposing factors were utilized. The width of the intervals, in which the maps of the predisposing factors have to be reclassified, has been defined assuming constant intervals to: elevation (100 m), slope (5 °), solar radiation (0.1 MJ/cm2/year), profile curvature (1.2 1/m), tangential curvature (2.2 1/m), drainage density (0.5), lineament density (0.00126). For the other parameters have been used the results of the probability-probability plots analysis and the statistical indexes of landslides site. In particular slope length (0 ÷ 2, 2 ÷ 5, 5 ÷ 10, 10 ÷ 20, 20 ÷ 35, 35 ÷ 260), accumulation flow (0 ÷ 1, 1 ÷ 2, 2 ÷ 5, 5 ÷ 12, 12 ÷ 60, 60 ÷27265), Topographic Wetness Index 0 ÷ 0.74, 0.74 ÷ 1.94, 1.94 ÷ 2.62, 2.62 ÷ 3.48, 3.48 ÷ 6,00, 6.00 ÷ 9.44), Stream Power Index (0 ÷ 0.64, 0.64 ÷ 1.28, 1.28 ÷ 1.81, 1.81 ÷ 4.20, 4.20 ÷ 9

15. Synthesis of Black and Red Mercury Sulfide Nano-Powder by Traditional Indian Method for Biomedical Application

International Nuclear Information System (INIS)

Padhi, Payodhar; Sahoo, G.; Das, K.; Ghosh, Sudipto; Panigrahi, S. C.

2008-01-01

The use of metals and minerals in the traditional Indian system of medicine known as aired is very common and is practiced since seventh century B.C. Metals were reduced to calcined powder form for medicinal purpose. For detoxification, a further step of purification of the metals and minerals with different vegetable extracts was practiced. The people of East India were using mercury and its sulfide as medicine. Gradually this secret was leaked to Arabic physicians who used mercury in skin ointment. Subsequently Italian Physicians adopted Arabic prescriptions of mercurial ointments for skin diseases. In the olden days, metals and minerals were impregnated with decoction and juice of vegetables and animal products like milk and fat for purification. These were then reduced to fine particles by milling with a pestle and mortar. It was known by then that the fineness of the powder had a significant influence on the color, texture, and medicinal properties as is cited by Charak. Nagarjun studied in detail the processing of metals and minerals, particularly mercury and the influence of the processing parameters on the medicinal values. Mercury is unique in many aspects. Indian alchemy developed a wide variety a chemical processes for the ostensible transmutation of metals and preparation of elixir of life, in which mercury occupied a prime position .The present investigation attempts to use the traditional methods as prescribed in the ancient texts to prepare mercury sulfide in both red and black form for medicinal use. XRD, SEM and HRTEM investigations of the sulfides obtained shows that the ancient Indians were able to produce nano-sized powders. Possibly this may be taken as the earliest application of the production and use of nano powder. The study proves that even in ancient time the knowledge of nano particle synthesis was prevalent and used to enhance effectiveness of medicines. Further mercury in the free form is not acceptable in medicines. The ancient

16. Synthesis of Black and Red Mercury Sulfide Nano-Powder by Traditional Indian Method for Biomedical Application

Science.gov (United States)

Padhi, Payodhar; Sahoo, G.; Das, K.; Ghosh, Sudipto; Panigrahi, S. C.

2008-10-01

The use of metals and minerals in the traditional Indian system of medicine known as aired is very common and is practiced since seventh century B.C. Metals were reduced to calcined powder form for medicinal purpose. For detoxification, a further step of purification of the metals and minerals with different vegetable extracts was practiced. The people of East India were using mercury and its sulfide as medicine. Gradually this secret was leaked to Arabic physicians who used mercury in skin ointment. Subsequently Italian Physicians adopted Arabic prescriptions of mercurial ointments for skin diseases. In the olden days, metals and minerals were impregnated with decoction and juice of vegetables and animal products like milk and fat for purification. These were then reduced to fine particles by milling with a pestle and mortar. It was known by then that the fineness of the powder had a significant influence on the color, texture, and medicinal properties as is cited by Charak. Nagarjun studied in detail the processing of metals and minerals, particularly mercury and the influence of the processing parameters on the medicinal values. Mercury is unique in many aspects. Indian alchemy developed a wide variety a chemical processes for the ostensible transmutation of metals and preparation of elixir of life, in which mercury occupied a prime position .The present investigation attempts to use the traditional methods as prescribed in the ancient texts to prepare mercury sulfide in both red and black form for medicinal use. XRD, SEM and HRTEM investigations of the sulfides obtained shows that the ancient Indians were able to produce nano-sized powders. Possibly this may be taken as the earliest application of the production and use of nano powder. The study proves that even in ancient time the knowledge of nano particle synthesis was prevalent and used to enhance effectiveness of medicines. Further mercury in the free form is not acceptable in medicines. The ancient

17. Field test comparison of an autocorrelation technique for determining grain size using a digital 'beachball' camera versus traditional methods

Science.gov (United States)

Barnard, P.L.; Rubin, D.M.; Harney, J.; Mustain, N.

2007-01-01

This extensive field test of an autocorrelation technique for determining grain size from digital images was conducted using a digital bed-sediment camera, or 'beachball' camera. Using 205 sediment samples and >1200 images from a variety of beaches on the west coast of the US, grain size ranging from sand to granules was measured from field samples using both the autocorrelation technique developed by Rubin [Rubin, D.M., 2004. A simple autocorrelation algorithm for determining grain size from digital images of sediment. Journal of Sedimentary Research, 74(1): 160-165.] and traditional methods (i.e. settling tube analysis, sieving, and point counts). To test the accuracy of the digital-image grain size algorithm, we compared results with manual point counts of an extensive image data set in the Santa Barbara littoral cell. Grain sizes calculated using the autocorrelation algorithm were highly correlated with the point counts of the same images (r2 = 0.93; n = 79) and had an error of only 1%. Comparisons of calculated grain sizes and grain sizes measured from grab samples demonstrated that the autocorrelation technique works well on high-energy dissipative beaches with well-sorted sediment such as in the Pacific Northwest (r2 ??? 0.92; n = 115). On less dissipative, more poorly sorted beaches such as Ocean Beach in San Francisco, results were not as good (r2 ??? 0.70; n = 67; within 3% accuracy). Because the algorithm works well compared with point counts of the same image, the poorer correlation with grab samples must be a result of actual spatial and vertical variability of sediment in the field; closer agreement between grain size in the images and grain size of grab samples can be achieved by increasing the sampling volume of the images (taking more images, distributed over a volume comparable to that of a grab sample). In all field tests the autocorrelation method was able to predict the mean and median grain size with ???96% accuracy, which is more than

18. The Combination of DGT Technique and Traditional Chemical Methods for Evaluation of Cadmium Bioavailability in Contaminated Soils with Organic Amendment

Directory of Open Access Journals (Sweden)

Yu Yao

2016-06-01

Full Text Available Organic amendments have been proposed as a means of remediation for Cd-contaminated soils. However, understanding the inhibitory effects of organic materials on metal immobilization requires further research. In this study colza cake, a typical organic amendment material, was investigated in order to elucidate the ability of this material to reduce toxicity of Cd-contaminated soil. Available concentrations of Cd in soils were measured using an in situ diffusive gradients in thin films (DGT technique in combination with traditional chemical methods, such as HOAc (aqua regia, EDTA (ethylene diamine tetraacetic acid, NaOAc (sodium acetate, CaCl2, and labile Cd in pore water. These results were applied to predict the Cd bioavailability after the addition of colza cake to Cd-contaminated soil. Two commonly grown cash crops, wheat and maize, were selected for Cd accumulation studies, and were found to be sensitive to Cd bioavailability. Results showed that the addition of colza cake may inhibit the growth of wheat and maize. Furthermore, the addition of increasing colza cake doses led to decreasing shoot and root biomass accumulation. However, increasing colza cake doses did lead to the reduction of Cd accumulation in plant tissues, as indicated by the decreasing Cd concentrations in shoots and roots. The labile concentration of Cd obtained by DGT measurements and the traditional chemical extraction methods, showed the clear decrease of Cd with the addition of increasing colza cake doses. All indicators showed significant positive correlations (p < 0.01 with the accumulation of Cd in plant tissues, however, all of the methods could not reflect plant growth status. Additionally, the capability of Cd to change from solid phase to become available in a soil solution decreased with increasing colza cake doses. This was reflected by the decreases in the ratio (R value of CDGT to Csol. Our study suggests that the sharp decrease in R values could not only

19. Using a binary logistic regression method and GIS for evaluating and mapping the groundwater spring potential in the Sultan Mountains (Aksehir, Turkey)

Science.gov (United States)

2011-07-01

SummaryThe purpose of this study is to produce a groundwater spring potential map of the Sultan Mountains in central Turkey, based on a logistic regression method within a Geographic Information System (GIS) environment. Using field surveys, the locations of the springs (440 springs) were determined in the study area. In this study, 17 spring-related factors were used in the analysis: geology, relative permeability, land use/land cover, precipitation, elevation, slope, aspect, total curvature, plan curvature, profile curvature, wetness index, stream power index, sediment transport capacity index, distance to drainage, distance to fault, drainage density, and fault density map. The coefficients of the predictor variables were estimated using binary logistic regression analysis and were used to calculate the groundwater spring potential for the entire study area. The accuracy of the final spring potential map was evaluated based on the observed springs. The accuracy of the model was evaluated by calculating the relative operating characteristics. The area value of the relative operating characteristic curve model was found to be 0.82. These results indicate that the model is a good estimator of the spring potential in the study area. The spring potential map shows that the areas of very low, low, moderate and high groundwater spring potential classes are 105.586 km 2 (28.99%), 74.271 km 2 (19.906%), 101.203 km 2 (27.14%), and 90.05 km 2 (24.671%), respectively. The interpretations of the potential map showed that stream power index, relative permeability of lithologies, geology, elevation, aspect, wetness index, plan curvature, and drainage density play major roles in spring occurrence and distribution in the Sultan Mountains. The logistic regression approach has not yet been used to delineate groundwater potential zones. In this study, the logistic regression method was used to locate potential zones for groundwater springs in the Sultan Mountains. The evolved model

20. Evaluation of a method to determine the natural occurrence of aflatoxins in commercial traditional herbal medicines from Malaysia and Indonesia.

Science.gov (United States)

Ali, N; Hashim, N H; Saad, B; Safan, K; Nakajima, M; Yoshizawa, T

2005-12-01

Traditional herbal medicines, popularly known as 'jamu' and 'makjun' in Malaysia and Indonesia, are consumed regularly to promote health. In consideration of their frequent and prolonged consumption, the natural occurrence of aflatoxins (AF) in these products was determined using immunoaffinity column clean-up and high-performance liquid chromatography with pre-column derivatization. The evaluated method, which entails dilution of sample extracts with Tween 20-phosphate buffered saline (1:9, v/v) and a chromatographic system using isocratic mobile phase composed of water-methanol-acetonitrile (70:20:10, v/v/v), was effective in separating AFB1, AFG1 and AFG2 from interference at their retention times. Results were confirmed using post-column derivatization with photochemical reactor. For 23 commercial samples analyzed, mean levels (incidence) of AFB(1), AFB(2) and AFG1 in positive samples were 0.26 (70%), 0.07 (61%) and 0.10 (30%) microg/kg, respectively; one sample was positive for AFG2 at a level of 0.03 (4%) microg/kg. In contrast to the high levels of AF in crude herbal drugs and medicinal plants reported previously by other researchers, the low contamination levels reported in this study may be attributed to the higher selectivity to AF of the method applied. Based on the AFB1 levels and the daily consumption of positive samples, a mean probable daily intake of 0.022 ng/kg body weight was calculated.

1. [Research progress on standardization study of NIR spectroscopy based method for quality control of traditional Chinese medicine].

Science.gov (United States)

Li, Wen-Long; Qu, Hai-Bin

2016-10-01

In recent years, the near infrared (NIR) spectroscopy has gained wide acceptance within the quantitative analysis of traditional Chinese medicine (TCM). However, the lack of technical standards is the bottleneck problem in this process. To address this issue, standardization study of the NIR spectroscopy based method for the quantitative analysis of TCM is needed, in which the specific characteristics of TCM should be given full considerations. The main research contents include:the scope definition for the application of NIR spectroscopy in the TCM quantitative analysis field, the selection criteria for the sample pretreatment and spectral acquisition conditions, the rules for the model optimization and evaluation, and the regulations for the model update and transfer. In this paper, some foreign studies in the agricultural areas are reviewed for reference. Different chemometrics methods reported in the literature are investigated and compared systematically. This research is important actual significance to the theoretical development of NIR spectroscopy analytical techniques, and will effectively promote the application of the technology in the TCM industry. Furthermore, it is beneficial to improve the technical level of TCM quality control, and can also be used as references to achieve similar purposes for other natural products. Copyright© by the Chinese Pharmaceutical Association.

2. Compression method of anastomosis of large intestines by implants with memory of shape: alternative to traditional sutures

Directory of Open Access Journals (Sweden)

F. Sh. Aliev

2015-01-01

Full Text Available Research objective. To prove experimentally the possibility of forming a compression colonic anastomoses using nickel-titanium devices in comparison with traditional methods of anastomosis. Materials and methods. In experimental studies the quality of the compression anastomosis of the colon in comparison with sutured and stapled anastomoses was performed. There were three experimental groups in mongrel dogs formed: in the 1st series (n = 30 compression anastomoses nickel-titanium implants were formed; in the 2nd (n = 25 – circular stapling anastomoses; in the 3rd (n = 25 – ligature way to Mateshuk– Lambert. In the experiment the physical durability, elasticity, and biological tightness, morphogenesis colonic anastomoses were studied. Results. Optimal sizes of compression devices are 32 × 18 and 28 × 15 mm with a wire diameter of 2.2 mm, the force of winding compression was 740 ± 180 g/mm2. Compression suture has a higher physical durability compared to stapled (W = –33.0; p < 0.05 and sutured (W = –28.0; p < 0.05, higher elasticity (p < 0.05 in all terms of tests and biological tightness since 3 days (p < 0.001 after surgery. The regularities of morphogenesis colonic anastomoses allocated by 4 periods of the regeneration of intestinal suture. Conclusion. Obtained experimental data of the use of compression anastomosis of the colon by the nickel-titanium devices are the convincing arguments for their clinical application.

3. The method of quality marker research and quality evaluation of traditional Chinese medicine based on drug properties and effect characteristics.

Science.gov (United States)

Zhang, Tiejun; Bai, Gang; Han, Yanqi; Xu, Jun; Gong, Suxiao; Li, Yazhuo; Zhang, Hongbing; Liu, Changxiao

2018-05-15

Quality of traditional Chinese medicine (TCM) plays a critical role in industry of TCM. Rapid development of TCM pharmaceutical areas is, however, greatly limited, since there are many issues not been resolved, concerning the quality study of TCM. Core concept of TCM quality as well as the characteristics of TCM was discussed, in order to guide the quality research and evaluation of TCM, further improve the level of TCM quality control. In this review, on the basis of systematic analysis of fundamental property and features of TCM in clinical application, the approaches and methods of quality marker (Q-marker) study were proposed through combination of transitivity and traceability of essentials of quality, correlation between chemical ingredients and drug property/efficacy, as well as analysis of endemicity of ingredients sharing similar pharmacophylogenetic and biosynthetic approaches. The approaches and methods of Q-marker study were proposed and the novel integrated pattern for quality assessment and control of TCM was established. The core concept of Q-marker has helped to break through the bottleneck of the current fragmented quality research of TCM and improved the scientificity, integrity and systematicness of quality control. Copyright © 2018 Elsevier GmbH. All rights reserved.

4. Comparison of computer-assisted instruction (CAI) versus traditional textbook methods for training in abdominal examination (Japanese experience).

Science.gov (United States)

Qayumi, A K; Kurihara, Y; Imai, M; Pachev, G; Seo, H; Hoshino, Y; Cheifetz, R; Matsuura, K; Momoi, M; Saleem, M; Lara-Guerra, H; Miki, Y; Kariya, Y

2004-10-01

This study aimed to compare the effects of computer-assisted, text-based and computer-and-text learning conditions on the performances of 3 groups of medical students in the pre-clinical years of their programme, taking into account their academic achievement to date. A fourth group of students served as a control (no-study) group. Participants were recruited from the pre-clinical years of the training programmes in 2 medical schools in Japan, Jichi Medical School near Tokyo and Kochi Medical School near Osaka. Participants were randomly assigned to 4 learning conditions and tested before and after the study on their knowledge of and skill in performing an abdominal examination, in a multiple-choice test and an objective structured clinical examination (OSCE), respectively. Information about performance in the programme was collected from school records and students were classified as average, good or excellent. Student and faculty evaluations of their experience in the study were explored by means of a short evaluation survey. Compared to the control group, all 3 study groups exhibited significant gains in performance on knowledge and performance measures. For the knowledge measure, the gains of the computer-assisted and computer-assisted plus text-based learning groups were significantly greater than the gains of the text-based learning group. The performances of the 3 groups did not differ on the OSCE measure. Analyses of gains by performance level revealed that high achieving students' learning was independent of study method. Lower achieving students performed better after using computer-based learning methods. The results suggest that computer-assisted learning methods will be of greater help to students who do not find the traditional methods effective. Explorations of the factors behind this are a matter for future research.

5. Regression: A Bibliography.

Science.gov (United States)

Pedrini, D. T.; Pedrini, Bonnie C.

Regression, another mechanism studied by Sigmund Freud, has had much research, e.g., hypnotic regression, frustration regression, schizophrenic regression, and infra-human-animal regression (often directly related to fixation). Many investigators worked with hypnotic age regression, which has a long history, going back to Russian reflexologists.…

6. A comparative study of frequency ratio, weights of evidence and logistic regression methods for landslide susceptibility mapping: Sultan Mountains, SW Turkey

Science.gov (United States)

2013-03-01

This study evaluated and compared landslide susceptibility maps produced with three different methods, frequency ratio, weights of evidence, and logistic regression, by using validation datasets. The field surveys performed as part of this investigation mapped the locations of 90 landslides that had been identified in the Sultan Mountains of south-western Turkey. The landslide influence parameters used for this study are geology, relative permeability, land use/land cover, precipitation, elevation, slope, aspect, total curvature, plan curvature, profile curvature, wetness index, stream power index, sediment transportation capacity index, distance to drainage, distance to fault, drainage density, fault density, and spring density maps. The relationships between landslide distributions and these parameters were analysed using the three methods, and the results of these methods were then used to calculate the landslide susceptibility of the entire study area. The accuracy of the final landslide susceptibility maps was evaluated based on the landslides observed during the fieldwork, and the accuracy of the models was evaluated by calculating each model's relative operating characteristic curve. The predictive capability of each model was determined from the area under the relative operating characteristic curve and the areas under the curves obtained using the frequency ratio, logistic regression, and weights of evidence methods are 0.976, 0.952, and 0.937, respectively. These results indicate that the frequency ratio and weights of evidence models are relatively good estimators of landslide susceptibility in the study area. Specifically, the results of the correlation analysis show a high correlation between the frequency ratio and weights of evidence results, and the frequency ratio and logistic regression methods exhibit correlation coefficients of 0.771 and 0.727, respectively. The frequency ratio model is simple, and its input, calculation and output processes are

7. DIAGNOSTIC CARDIAC CATHETERIZATION USING THE MEDRAD AVANTA FLUID MANAGEMENT SYSTEM AS COMPARED TO THE TRADITIONAL MANUAL INJECTION METHOD

Energy Technology Data Exchange (ETDEWEB)

Winniford, Michael D

2013-02-08

Nearly 4 million patient procedures performed annually in US cardiac catheterization laboratories utilize contrast media to achieve vessel opacification. The amount of contrast media used is variable and depends on the complexity of the procedure, the method of contrast delivery as well as the skill-level of the operator. Since the total amount of contrast used for each procedure can have both patient safety and economic implications, it is essential for cardiologists to have the ability to control contrast delivery such that optimal angiographic image quality is achieved using the least amount of contrast. Although the complication rate associated with cardiac catheterization remains low, the most common serious complication, contrast-induced nephropathy (CIN), is associated with poor prognosis and a high mortality rate. Numerous interventional strategies for preventing and reducing the severity of CIN have demonstrated varying degrees of clinical benefit, but none has been shown to reliably prevent this serious complication. To date, the most effective approach for reducing the risk of CIN is to properly hydrate the patient and to minimize the amount of contrast media administered. Automated injection systems are intended for use in virtually all cardiac catheterization procedures and have numerous features which can provide potential advantages over traditional methods. With automated injection technology the operator is able to control and precisely monitor contrast delivery. Additionally, the MEDRAD Avanta Fluid Management Injection System utilizes a sterile contrast reservoir which eliminates the need to discard unused contrast in individual opened containers following each procedure. Considering that an average of 50% of opened contrast media is wasted using manual injection methods, this savings can provide a substantial economic benefit. Automated systems also facilitate the use of smaller (5 French) catheter sizes. Precise flow control and the use of

8. The Applicability of Traditional Protection Methods to Lines Emanating from VSC-HVDC Interconnectors and a Novel Protection Principle

Directory of Open Access Journals (Sweden)

Shimin Xue

2016-05-01

Full Text Available Voltage source converter (VSC-based high voltage direct current (VSC-HVDC interconnectors can realize accurate and fast control of power transmission among AC networks, and provide emergency power support for AC networks. VSC-HVDC interconnectors bring exclusive fault characteristics to AC networks, thus influencing the performance of traditional protections. Since fault characteristics are related to the control schemes of interconnectors, a fault ride-through (FRT strategy which is applicable to the interconnector operating characteristic of working in four quadrants and capable of eliminating negative-sequence currents under unbalanced fault conditions is proposed first. Then, the additional terms of measured impedances of distance relays caused by fault resistances are derived using a symmetrical component method. Theoretical analysis shows the output currents of interconnectors are controllable after faults, which may cause malfunctions in distance protections installed on lines emanating from interconnectors under the effect of fault resistances. Pilot protection is also inapplicable to lines emanating from interconnectors. Furthermore, a novel pilot protection principle based on the ratio between phase currents and the ratio between negative-sequence currents flowing through both sides is proposed for lines emanating from the interconnectors whose control scheme aims at eliminating negative-sequence currents. The validity of theoretical analysis and the protection principle is verified by PSCAD/EMTDC simulations.

9. Determining antioxidant activities of lactobacilli cell-free supernatants by cellular antioxidant assay: a comparison with traditional methods.

Directory of Open Access Journals (Sweden)

Jiali Xing

Full Text Available Antioxidant activity of lactic acid bacteria is associated with multiple health-protective effects. Traditional indexes of chemical antioxidant activities poorly reflect the antioxidant effects of these bacteria in vivo. Cellular antioxidant activity (CAA assay was used in this study to determine the antioxidant activity of cell-free supernatants (CFSs of 10 Lactobacillus strains. The performance of the CAA assay was compared with that of four chemical antioxidant activity assays, namely, DPPH radical scavenging, hydroxyl radical scavenging (HRS, reducing power (RP, and inhibition of linoleic acid peroxidation (ILAP. Results of the CAA assay were associated with those of DPPH and ILAP assays, but not with those of RP and HRS assays. The inter- and intra-specific antioxidant activities of CFS were characterized by chemical and CAA assays. L. rhamnosus CCFM 1107 displayed a high antioxidative effect similar to positive control L. rhamnosus GG ATCC 53103 in all of the assays. The CAA assay is a potential method for the detection of antioxidant activities of lactobacilli CFSs.

10. Active methodologies in Financial Management classes: an alternative to the traditional teaching method for awakening intrinsic motivation and developing autonomy

Directory of Open Access Journals (Sweden)

Guilherme Muniz Pereira Chaves Urias

2017-01-01

Full Text Available This article presents a pedagogical experience in Financial Management classes. The objective of this study was to investigate whether the educational activity based on active methodologies, applied in the Financial Management classes in an undergraduate course in Business Administration, can offer formative spaces that enhance the development of the students’ intrinsic motivation to the point of being relevant to the development of their autonomy and thus to be characterized as a viable manner of putting the Freirean pedagogy into practice. In order to do so, the adopted teaching strategy aimed at creating opportunities for interpretating problems that simulated real situations. A questionnaire was applied and the Bardinian content analysis was used to verify the students' impressions about the activity itself and its respective contribution to their professional and personal training. The analysis points to the fact that active methodologies are viable alternatives to the traditional method of teaching regarding the awakening of interest, motivation and the development of learning. It also points to their consonance with the Freirian pedagogy.

11. [Correlation between physical characteristics of sticks and quality of traditional Chinese medicine pills prepared by plastic molded method].

Science.gov (United States)

Wang, Ling; Xian, Jiechen; Hong, Yanlong; Lin, Xiao; Feng, Yi

2012-05-01

To quantify the physical characteristics of sticks of traditional Chinese medicine (TCM) honeyed pills prepared by the plastic molded method and the correlation of adhesiveness and plasticity-related parameters of sticks and quality of pills, in order to find major parameters and the appropriate range impacting pill quality. Sticks were detected by texture analyzer for their physical characteristic parameters such as hardness and compression action, and pills were observed by visual evaluation for their quality. The correlation of both data was determined by the stepwise discriminant analysis. Stick physical characteristic parameter l(CD) can exactly depict the adhesiveness, with the discriminant equation of Y0 - Y1 = 6.415 - 41.594l(CD). When Y0 Y1, pills were adhesive with each other. Pills' physical characteristic parameters l(CD) and l(AC), Ar, Tr can exactly depict smoothness of pills, with the discriminant equation of Z0 - Z1 = -195.318 + 78.79l(AC) - 3 258. 982Ar + 3437.935Tr. When Z0 Z1, pills were rough on surface. The stepwise discriminant analysis is made to show the obvious correlation between key physical characteristic parameters l(CD) and l(AC), Ar, Tr of sticks and appearance quality of pills, defining the molding process for preparing pills by the plastic molded and qualifying ranges of key physical characteristic parameters characterizing intermediate sticks, in order to provide theoretical basis for prescription screening and technical parameter adjustment for pills.

12. Measurement agreement between a newly developed sensing insole and traditional laboratory-based method for footstrike pattern detection in runners.

Directory of Open Access Journals (Sweden)

Roy T H Cheung

Full Text Available This study introduced a novel but simple method to continuously measure footstrike patterns in runners using inexpensive force sensors. Two force sensing resistors were firmly affixed at the heel and second toe of both insoles to collect the time signal of foot contact. A total of 109 healthy young adults (42 males and 67 females were recruited in this study. They ran on an instrumented treadmill at 0°, +10°, and -10° inclinations and attempted rearfoot, midfoot, and forefoot landings using real time visual biofeedback. Intra-step strike index and onset time difference between two force sensors were measured and analyzed with univariate linear regression. We analyzed 25,655 footfalls and found that onset time difference between two sensors explained 80-84% of variation in the prediction model of strike index (R-squared = 0.799-0.836, p<0.001. However, the time windows to detect footstrike patterns on different surface inclinations were not consistent. These findings may allow laboratory-based gait retraining to be implemented in natural running environments to aid in both injury prevention and performance enhancement.

13. Measurement agreement between a newly developed sensing insole and traditional laboratory-based method for footstrike pattern detection in runners

Science.gov (United States)

Cheung, Roy T. H.; An, Winko W.; Au, Ivan P. H.; Zhang, Janet H.; Chan, Zoe Y. S.; Man, Alfred; Lau, Fannie O. Y.; Lam, Melody K. Y.; Lau, K. K.; Leung, C. Y.; Tsang, N. W.; Sze, Louis K. Y.; Lam, Gilbert W. K.

2017-01-01

This study introduced a novel but simple method to continuously measure footstrike patterns in runners using inexpensive force sensors. Two force sensing resistors were firmly affixed at the heel and second toe of both insoles to collect the time signal of foot contact. A total of 109 healthy young adults (42 males and 67 females) were recruited in this study. They ran on an instrumented treadmill at 0°, +10°, and -10° inclinations and attempted rearfoot, midfoot, and forefoot landings using real time visual biofeedback. Intra-step strike index and onset time difference between two force sensors were measured and analyzed with univariate linear regression. We analyzed 25,655 footfalls and found that onset time difference between two sensors explained 80–84% of variation in the prediction model of strike index (R-squared = 0.799–0.836, p<0.001). However, the time windows to detect footstrike patterns on different surface inclinations were not consistent. These findings may allow laboratory-based gait retraining to be implemented in natural running environments to aid in both injury prevention and performance enhancement. PMID:28599003

14. Quantification of endocrine disruptors and pesticides in water by gas chromatography-tandem mass spectrometry. Method validation using weighted linear regression schemes.

Science.gov (United States)

Mansilha, C; Melo, A; Rebelo, H; Ferreira, I M P L V O; Pinho, O; Domingues, V; Pinho, C; Gameiro, P

2010-10-22

A multi-residue methodology based on a solid phase extraction followed by gas chromatography-tandem mass spectrometry was developed for trace analysis of 32 compounds in water matrices, including estrogens and several pesticides from different chemical families, some of them with endocrine disrupting properties. Matrix standard calibration solutions were prepared by adding known amounts of the analytes to a residue-free sample to compensate matrix-induced chromatographic response enhancement observed for certain pesticides. Validation was done mainly according to the International Conference on Harmonisation recommendations, as well as some European and American validation guidelines with specifications for pesticides analysis and/or GC-MS methodology. As the assumption of homoscedasticity was not met for analytical data, weighted least squares linear regression procedure was applied as a simple and effective way to counteract the greater influence of the greater concentrations on the fitted regression line, improving accuracy at the lower end of the calibration curve. The method was considered validated for 31 compounds after consistent evaluation of the key analytical parameters: specificity, linearity, limit of detection and quantification, range, precision, accuracy, extraction efficiency, stability and robustness. Copyright © 2010 Elsevier B.V. All rights reserved.

15. Influence of regression model and incremental test protocol on the relationship between lactate threshold using the maximal-deviation method and performance in female runners.

Science.gov (United States)

2012-01-01

This study examined the influence of the regression model and initial intensity of an incremental test on the relationship between the lactate threshold estimated by the maximal-deviation method and the endurance performance. Sixteen non-competitive, recreational female runners performed a discontinuous incremental treadmill test. The initial speed was set at 7 km · h⁻¹, and increased every 3 min by 1 km · h⁻¹ with a 30-s rest between the stages used for earlobe capillary blood sample collection. Lactate-speed data were fitted by an exponential-plus-constant and a third-order polynomial equation. The lactate threshold was determined for both regression equations, using all the coordinates, excluding the first and excluding the first and second initial points. Mean speed of a 10-km road race was the performance index (3.04 ± 0.22 m · s⁻¹). The exponentially-derived lactate threshold had a higher correlation (0.98 ≤ r ≤ 0.99) and smaller standard error of estimate (SEE) (0.04 ≤ SEE ≤ 0.05 m · s⁻¹) with performance than the polynomially-derived equivalent (0.83 ≤ r ≤ 0.89; 0.10 ≤ SEE ≤ 0.13 m · s⁻¹). The exponential lactate threshold was greater than the polynomial equivalent (P performance index that is independent of the initial intensity of the incremental test and better than the polynomial equivalent.

16. Blending online techniques with traditional face to face teaching methods to deliver final year undergraduate radiology learning content

Energy Technology Data Exchange (ETDEWEB)

Howlett, David, E-mail: david.howlett@esht.nhs.uk [Department of Radiology, Eastbourne District General Hospital, Kings Drive, Eastbourne, East Sussex BN21 2UD (United Kingdom); Vincent, Tim [Department of IT, Brighton and Sussex Medical School (BSMS) (United Kingdom); Watson, Gillian; Owens, Emma [Department of Radiology, Eastbourne District General Hospital, Kings Drive, Eastbourne, East Sussex BN21 2UD (United Kingdom); Webb, Richard; Gainsborough, Nicola [Department of Medicine, Royal Sussex County Hospital, Brighton (United Kingdom); Fairclough, Jil [Department of IT, Brighton and Sussex Medical School (BSMS) (United Kingdom); Taylor, Nick [Department of Medical Illustration, Eastbourne District General Hospital (United Kingdom); Miles, Ken [Department of Imaging, BSMS (United Kingdom); Cohen, Jon [Department of Infectious Diseases, BSMS (United Kingdom); Vincent, Richard [Department of Cardiology, BSMS (United Kingdom)

2011-06-15

17. Blending online techniques with traditional face to face teaching methods to deliver final year undergraduate radiology learning content

International Nuclear Information System (INIS)

Howlett, David; Vincent, Tim; Watson, Gillian; Owens, Emma; Webb, Richard; Gainsborough, Nicola; Fairclough, Jil; Taylor, Nick; Miles, Ken; Cohen, Jon; Vincent, Richard

2011-01-01

18. The feasibility of using explicit method for linear correction of the particle size variation using NIR Spectroscopy combined with PLS2regression method

Science.gov (United States)

Yulia, M.; Suhandy, D.

2018-03-01

NIR spectra obtained from spectral data acquisition system contains both chemical information of samples as well as physical information of the samples, such as particle size and bulk density. Several methods have been established for developing calibration models that can compensate for sample physical information variations. One common approach is to include physical information variation in the calibration model both explicitly and implicitly. The objective of this study was to evaluate the feasibility of using explicit method to compensate the influence of different particle size of coffee powder in NIR calibration model performance. A number of 220 coffee powder samples with two different types of coffee (civet and non-civet) and two different particle sizes (212 and 500 µm) were prepared. Spectral data was acquired using NIR spectrometer equipped with an integrating sphere for diffuse reflectance measurement. A discrimination method based on PLS-DA was conducted and the influence of different particle size on the performance of PLS-DA was investigated. In explicit method, we add directly the particle size as predicted variable results in an X block containing only the NIR spectra and a Y block containing the particle size and type of coffee. The explicit inclusion of the particle size into the calibration model is expected to improve the accuracy of type of coffee determination. The result shows that using explicit method the quality of the developed calibration model for type of coffee determination is a little bit superior with coefficient of determination (R2) = 0.99 and root mean square error of cross-validation (RMSECV) = 0.041. The performance of the PLS2 calibration model for type of coffee determination with particle size compensation was quite good and able to predict the type of coffee in two different particle sizes with relatively high R2 pred values. The prediction also resulted in low bias and RMSEP values.

19. CLASSIFICATION OF IRANIAN NURSES ACCORDING TO THEIR MENTAL HEALTH OUTCOMES USING GHQ-12 QUESTIONNAIRE: A COMPARISON BETWEEN LATENT CLASS ANALYSIS AND K-MEANS CLUSTERING WITH TRADITIONAL SCORING METHOD.

Science.gov (United States)

Jamali, Jamshid; Ayatollahi, Seyyed Mohammad Taghi

2015-10-01

Nurses constitute the most providers of health care systems. Their mental health can affect the quality of services and patients' satisfaction. General Health Questionnaire (GHQ-12) is a general screening tool used to detect mental disorders. Scoring method and determining thresholds for this questionnaire are debatable and the cut-off points can vary from sample to sample. This study was conducted to estimate the prevalence of mental disorders among Iranian nurses using GHQ-12 and also compare Latent Class Analysis (LCA) and K-means clustering with traditional scoring method. A cross-sectional study was carried out in Fars and Bushehr provinces of southern Iran in 2014. Participants were 771 Iranian nurses, who filled out the GHQ-12 questionnaire. Traditional scoring method, LCA and K-means were used to estimate the prevalence of mental disorder among Iranian nurses. Cohen's kappa statistic was applied to assess the agreement between the LCA and K-means with traditional scoring method of GHQ-12. The nurses with mental disorder by scoring method, LCA and K-mean were 36.3% (n=280), 32.2% (n=248), and 26.5% (n=204), respectively. LCA and logistic regression revealed that the prevalence of mental disorder in females was significantly higher than males. Mental disorder in nurses was in a medium level compared to other people living in Iran. There was a little difference between prevalence of mental disorder estimated by scoring method, K-means and LCA. According to the advantages of LCA than K-means and different results in scoring method, we suggest LCA for classification of Iranian nurses according to their mental health outcomes using GHQ-12 questionnaire.

20. Influence of regression model and initial intensity of an incremental test on the relationship between the lactate threshold estimated by the maximal-deviation method and running performance.

Science.gov (United States)

Santos-Concejero, Jordan; Tucker, Ross; Granados, Cristina; Irazusta, Jon; Bidaurrazaga-Letona, Iraia; Zabala-Lili, Jon; Gil, Susana María

2014-01-01

This study investigated the influence of the regression model and initial intensity during an incremental test on the relationship between the lactate threshold estimated by the maximal-deviation method and performance in elite-standard runners. Twenty-three well-trained runners completed a discontinuous incremental running test on a treadmill. Speed started at 9 km · h(-1) and increased by 1.5 km · h(-1) every 4 min until exhaustion, with a minute of recovery for blood collection. Lactate-speed data were fitted by exponential and polynomial models. The lactate threshold was determined for both models, using all the co-ordinates, excluding the first and excluding the first and second points. The exponential lactate threshold was greater than the polynomial equivalent in any co-ordinate condition (P performance and is independent of the initial intensity of the test.

1. Factors influencing superimposition error of 3D cephalometric landmarks by plane orientation method using 4 reference points: 4 point superimposition error regression model.

Science.gov (United States)

Hwang, Jae Joon; Kim, Kee-Deog; Park, Hyok; Park, Chang Seo; Jeong, Ho-Gul

2014-01-01

Superimposition has been used as a method to evaluate the changes of orthodontic or orthopedic treatment in the dental field. With the introduction of cone beam CT (CBCT), evaluating 3 dimensional changes after treatment became possible by superimposition. 4 point plane orientation is one of the simplest ways to achieve superimposition of 3 dimensional images. To find factors influencing superimposition error of cephalometric landmarks by 4 point plane orientation method and to evaluate the reproducibility of cephalometric landmarks for analyzing superimposition error, 20 patients were analyzed who had normal skeletal and occlusal relationship and took CBCT for diagnosis of temporomandibular disorder. The nasion, sella turcica, basion and midpoint between the left and the right most posterior point of the lesser wing of sphenoidal bone were used to define a three-dimensional (3D) anatomical reference co-ordinate system. Another 15 reference cephalometric points were also determined three times in the same image. Reorientation error of each landmark could be explained substantially (23%) by linear regression model, which consists of 3 factors describing position of each landmark towards reference axes and locating error. 4 point plane orientation system may produce an amount of reorientation error that may vary according to the perpendicular distance between the landmark and the x-axis; the reorientation error also increases as the locating error and shift of reference axes viewed from each landmark increases. Therefore, in order to reduce the reorientation error, accuracy of all landmarks including the reference points is important. Construction of the regression model using reference points of greater precision is required for the clinical application of this model.

2. Using reduced rank regression methods to identify dietary patterns associated with obesity: a cross-country study among European and Australian adolescents.

Science.gov (United States)

Huybrechts, Inge; Lioret, Sandrine; Mouratidou, Theodora; Gunter, Marc J; Manios, Yannis; Kersting, Mathilde; Gottrand, Frederic; Kafatos, Anthony; De Henauw, Stefaan; Cuenca-García, Magdalena; Widhalm, Kurt; Gonzales-Gross, Marcela; Molnar, Denes; Moreno, Luis A; McNaughton, Sarah A

2017-01-01

3. A primer of statistical methods for correlating parameters and properties of electrospun poly( l -lactide) scaffolds for tissue engineering-PART 2: Regression

KAUST Repository

Seyedmahmoud, Rasoul

2014-04-07

This two-articles series presents an in-depth discussion of electrospun poly-l-lactide scaffolds for tissue engineering by means of statistical methodologies that can be used, in general, to gain a quantitative and systematic insight about effects and interactions between a handful of key scaffold properties (Ys) and a set of process parameters (Xs) in electrospinning. While Part-1 dealt with the DOE methods to unveil the interactions between Xs in determining the morphomechanical properties (ref. Y1-4), this Part-2 article continues and refocuses the discussion on the interdependence of scaffold properties investigated by standard regression methods. The discussion first explores the connection between mechanical properties (Y4) and morphological descriptors of the scaffolds (Y1-3) in 32 types of scaffolds, finding that the mean fiber diameter (Y1) plays a predominant role which is nonetheless and crucially modulated by the molecular weight (MW) of PLLA. The second part examines the biological performance (Y5) (i.e. the cell proliferation of seeded bone marrow-derived mesenchymal stromal cells) on a random subset of eight scaffolds vs. the mechanomorphological properties (Y1-4). In this case, the featured regression analysis on such an incomplete set was not conclusive, though, indirectly suggesting in quantitative terms that cell proliferation could not fully be explained as a function of considered mechanomorphological properties (Y1-4), but in the early stage seeding, and that a randomization effects occurs over time such that the differences in initial cell proliferation performance (at day 1) is smeared over time. The findings may be the cornerstone of a novel route to accrue sufficient understanding and establish design rules for scaffold biofunctional vs. architecture, mechanical properties, and process parameters.

4. Methodological comparison of marginal structural model, time-varying Cox regression, and propensity score methods: the example of antidepressant use and the risk of hip fracture.

Science.gov (United States)

Ali, M Sanni; Groenwold, Rolf H H; Belitser, Svetlana V; Souverein, Patrick C; Martín, Elisa; Gatto, Nicolle M; Huerta, Consuelo; Gardarsdottir, Helga; Roes, Kit C B; Hoes, Arno W; de Boer, Antonius; Klungel, Olaf H

2016-03-01

Observational studies including time-varying treatments are prone to confounding. We compared time-varying Cox regression analysis, propensity score (PS) methods, and marginal structural models (MSMs) in a study of antidepressant [selective serotonin reuptake inhibitors (SSRIs)] use and the risk of hip fracture. A cohort of patients with a first prescription for antidepressants (SSRI or tricyclic antidepressants) was extracted from the Dutch Mondriaan and Spanish Base de datos para la Investigación Farmacoepidemiológica en Atención Primaria (BIFAP) general practice databases for the period 2001-2009. The net (total) effect of SSRI versus no SSRI on the risk of hip fracture was estimated using time-varying Cox regression, stratification and covariate adjustment using the PS, and MSM. In MSM, censoring was accounted for by inverse probability of censoring weights. The crude hazard ratio (HR) of SSRI use versus no SSRI use on hip fracture was 1.75 (95%CI: 1.12, 2.72) in Mondriaan and 2.09 (1.89, 2.32) in BIFAP. After confounding adjustment using time-varying Cox regression, stratification, and covariate adjustment using the PS, HRs increased in Mondriaan [2.59 (1.63, 4.12), 2.64 (1.63, 4.25), and 2.82 (1.63, 4.25), respectively] and decreased in BIFAP [1.56 (1.40, 1.73), 1.54 (1.39, 1.71), and 1.61 (1.45, 1.78), respectively]. MSMs with stabilized weights yielded HR 2.15 (1.30, 3.55) in Mondriaan and 1.63 (1.28, 2.07) in BIFAP when accounting for censoring and 2.13 (1.32, 3.45) in Mondriaan and 1.66 (1.30, 2.12) in BIFAP without accounting for censoring. In this empirical study, differences between the different methods to control for time-dependent confounding were small. The observed differences in treatment effect estimates between the databases are likely attributable to different confounding information in the datasets, illustrating that adequate information on (time-varying) confounding is crucial to prevent bias. Copyright © 2016 John Wiley & Sons, Ltd.

5. Advanced statistics: linear regression, part I: simple linear regression.

Science.gov (United States)

Marill, Keith A

2004-01-01

Simple linear regression is a mathematical technique used to model the relationship between a single independent predictor variable and a single dependent outcome variable. In this, the first of a two-part series exploring concepts in linear regression analysis, the four fundamental assumptions and the mechanics of simple linear regression are reviewed. The most common technique used to derive the regression line, the method of least squares, is described. The reader will be acquainted with other important concepts in simple linear regression, including: variable transformations, dummy variables, relationship to inference testing, and leverage. Simplified clinical examples with small datasets and graphic models are used to illustrate the points. This will provide a foundation for the second article in this series: a discussion of multiple linear regression, in which there are multiple predictor variables.

6. STELLAR COLOR REGRESSION: A SPECTROSCOPY-BASED METHOD FOR COLOR CALIBRATION TO A FEW MILLIMAGNITUDE ACCURACY AND THE RECALIBRATION OF STRIPE 82

International Nuclear Information System (INIS)

Yuan, Haibo; Liu, Xiaowei; Xiang, Maosheng; Huang, Yang; Zhang, Huihua; Chen, Bingqiu

2015-01-01

In this paper we propose a spectroscopy-based stellar color regression (SCR) method to perform accurate color calibration for modern imaging surveys, taking advantage of millions of stellar spectra now available. The method is straightforward, insensitive to systematic errors in the spectroscopically determined stellar atmospheric parameters, applicable to regions that are effectively covered by spectroscopic surveys, and capable of delivering an accuracy of a few millimagnitudes for color calibration. As an illustration, we have applied the method to the Sloan Digital Sky Survey (SDSS) Stripe 82 data. With a total number of 23,759 spectroscopically targeted stars, we have mapped out the small but strongly correlated color zero-point errors present in the photometric catalog of Stripe 82, and we improve the color calibration by a factor of two to three. Our study also reveals some small but significant magnitude dependence errors in the z band for some charge-coupled devices (CCDs). Such errors are likely to be present in all the SDSS photometric data. Our results are compared with those from a completely independent test based on the intrinsic colors of red galaxies presented by Ivezić et al. The comparison, as well as other tests, shows that the SCR method has achieved a color calibration internally consistent at a level of about 5 mmag in u – g, 3 mmag in g – r, and 2 mmag in r – i and i – z. Given the power of the SCR method, we discuss briefly the potential benefits by applying the method to existing, ongoing, and upcoming imaging surveys

7. Evaluation of organic amendment on the effect of cadmium bioavailability in contaminated soils using the DGT technique and traditional methods.

Science.gov (United States)

Yao, Yu; Sun, Qin; Wang, Chao; Wang, Pei-Fang; Ding, Shi-Ming

2017-03-01

Organic amendments have been widely proposed as a remediation technology for metal-contaminated soils, but there exist controversial results on their effectiveness. In this study, the effect of pig manure addition on cadmium (Cd) bioavailability in Cd-contaminated soils was systematically evaluated by one dynamic, in situ technique of diffusive gradients in thin films (DGT) and four traditional methods based on the equilibrium theory (soil solution concentration and the three commonly used extractants, i.e., acetic acid (HAc), ethylenediamine tetraacetic acid (EDTA), and calcium chloride (CaCl 2 ). Wheat and maize were selected for measurement of plant Cd uptake. The results showed that pig manure addition could promote the growth of two plants, accompanied by increasing biomasses of shoots and roots with increasing doses of pig manure addition. Correspondingly, increasing additions of pig manure reduced plant Cd uptake and accumulation, as indicated by the decreases of Cd concentrations in shoots and roots. The bioavailable concentrations of Cd in Cd-contaminated soils reflected by the DGT technique obviously decreased with increasing doses of pig manure addition, following the same changing trend as plant Cd uptake. Changes in soil solution Cd concentration and extractable Cd by HAc, EDTA, and CaCl 2 in soils were similar to DGT measurement. Meanwhile, the capability of Cd resupply from solid phase to soil solution decreased with increasing additions of pig manure, as reflected by the decreases in the ratio (R) value of C DGT to C sol . Positive correlations were observed between various bioavailable indicators of Cd in soils and Cd concentrations in the tissues of the two plants. These findings provide stronger evidence that pig manure amendment is effective in reducing Cd mobility and bioavailability in soils and it is an ideal organic material for remediation of Cd-contaminated soils.

8. Blending online techniques with traditional face to face teaching methods to deliver final year undergraduate radiology learning content.

Science.gov (United States)

Howlett, David; Vincent, Tim; Watson, Gillian; Owens, Emma; Webb, Richard; Gainsborough, Nicola; Fairclough, Jil; Taylor, Nick; Miles, Ken; Cohen, Jon; Vincent, Richard

2011-06-01

9. [Ideas and methods of two-dimensional zebrafish model combined with chromatographic techniques in high-throughput screening of active anti-osteoporosis components of traditional Chinese medicines].

Science.gov (United States)

Wei, Ying-Jie; Jing, Li-Jun; Zhan, Yang; Sun, E; Jia, Xiao-Bin

2014-05-01

To break through the restrictions of the evaluation model and the quantity of compounds by using the two-dimensional zebrafish model combined with chromatographic techniques, and establish a new method for the high-throughput screening of active anti-osteoporosis components. According to the research group-related studies and relevant foreign literatures, on the basis of the fact that the zebrafish osteoporosis model could efficiently evaluate the activity, the zebrafish metabolism model could efficiently enrich metabolites and the chromatographic techniques could efficiently separate and analyze components of traditional Chinese medicines, we proposed that the inherent combination of the three methods is expected to efficiently decode in vivo and in vitro efficacious anti-osteoporosis materials of traditional Chinese medicines. The method makes it simple and efficient in the enrichment, separation and analysis on components of traditional Chinese medicines, particularly micro-components and metabolites and the screening anti-osteoporosis activity, fully reflects that efficacious materials of traditional Chinese medicines contain original components and metabolites, with characteristic of "multi-components, multi-targets and integral effect", which provides new ideas and methods for the early and rapid discovery of active anti-osteoporosis components of traditional Chinese medicines.

10. Mass movement susceptibility mapping - A comparison of logistic regression and Weight of evidence methods in Taounate-Ain Aicha region (Central Rif, Morocco

Directory of Open Access Journals (Sweden)

JEMMAH A I

2018-01-01

Full Text Available Taounate region is known by a high density of mass movements which cause several human and economic losses. The goal of this paper is to assess the landslide susceptibility of Taounate using the Weight of Evidence method (WofE and the Logistic Regression method (LR. Seven conditioning factors were used in this study: lithology, fault, drainage, slope, elevation, exposure and land use. Over the years, this site and its surroundings have experienced repeated landslides. For this reason, landslide susceptibility mapping is mandatory for risk prevention and land-use management. In this study, we have focused on recent large-scale mass movements. Finally, the ROC curves were established to evaluate the degree of fit of the model and to choose the best landslide susceptibility zonation. A total mass movements location were detected; 50% were randomly selected as input data for the entire process using the Spatial Data Model (SDM and the remaining locations were used for validation purposes. The obtained WofE’s landslide susceptibility map shows that high to very high susceptibility zones contain 62% of the total of inventoried landslides, while the same zones contain only 47% of landslides in the map obtained by the LR method. This landslide susceptibility map obtained is a major contribution to various urban and regional development plans under the Taounate Region National Development Program.

11. Fungible weights in logistic regression.

Science.gov (United States)

Jones, Jeff A; Waller, Niels G

2016-06-01

In this article we develop methods for assessing parameter sensitivity in logistic regression models. To set the stage for this work, we first review Waller's (2008) equations for computing fungible weights in linear regression. Next, we describe 2 methods for computing fungible weights in logistic regression. To demonstrate the utility of these methods, we compute fungible logistic regression weights using data from the Centers for Disease Control and Prevention's (2010) Youth Risk Behavior Surveillance Survey, and we illustrate how these alternate weights can be used to evaluate parameter sensitivity. To make our work accessible to the research community, we provide R code (R Core Team, 2015) that will generate both kinds of fungible logistic regression weights. (PsycINFO Database Record (c) 2016 APA, all rights reserved).

12. Testing discontinuities in nonparametric regression

KAUST Repository

Dai, Wenlin

2017-01-19

In nonparametric regression, it is often needed to detect whether there are jump discontinuities in the mean function. In this paper, we revisit the difference-based method in [13 H.-G. Müller and U. Stadtmüller, Discontinuous versus smooth regression, Ann. Stat. 27 (1999), pp. 299–337. doi: 10.1214/aos/1018031100

13. Testing discontinuities in nonparametric regression

KAUST Repository

Dai, Wenlin; Zhou, Yuejin; Tong, Tiejun

2017-01-01

In nonparametric regression, it is often needed to detect whether there are jump discontinuities in the mean function. In this paper, we revisit the difference-based method in [13 H.-G. Müller and U. Stadtmüller, Discontinuous versus smooth regression, Ann. Stat. 27 (1999), pp. 299–337. doi: 10.1214/aos/1018031100

14. Quantile regression theory and applications

CERN Document Server

Davino, Cristina; Vistocco, Domenico

2013-01-01

A guide to the implementation and interpretation of Quantile Regression models This book explores the theory and numerous applications of quantile regression, offering empirical data analysis as well as the software tools to implement the methods. The main focus of this book is to provide the reader with a comprehensivedescription of the main issues concerning quantile regression; these include basic modeling, geometrical interpretation, estimation and inference for quantile regression, as well as issues on validity of the model, diagnostic tools. Each methodological aspect is explored and

15. Logistic regression models

CERN Document Server

Hilbe, Joseph M

2009-01-01

This book really does cover everything you ever wanted to know about logistic regression … with updates available on the author's website. Hilbe, a former national athletics champion, philosopher, and expert in astronomy, is a master at explaining statistical concepts and methods. Readers familiar with his other expository work will know what to expect-great clarity.The book provides considerable detail about all facets of logistic regression. No step of an argument is omitted so that the book will meet the needs of the reader who likes to see everything spelt out, while a person familiar with some of the topics has the option to skip "obvious" sections. The material has been thoroughly road-tested through classroom and web-based teaching. … The focus is on helping the reader to learn and understand logistic regression. The audience is not just students meeting the topic for the first time, but also experienced users. I believe the book really does meet the author's goal … .-Annette J. Dobson, Biometric...

16. Virtual reality and the traditional method for phlebotomy training among college of nursing students in Kuwait: implications for nursing education and practice.

Science.gov (United States)

Vidal, Victoria L; Ohaeri, Beatrice M; John, Pamela; Helen, Delles

2013-01-01

This quasi-experimental study, with a control group and experimental group, compares the effectiveness of virtual reality simulators on developing phlebotomy skills of nursing students with the effectiveness of traditional methods of teaching. Performance of actual phlebotomy on a live client was assessed after training, using a standardized form. Findings showed that students who were exposed to the virtual reality simulator performed better in the following performance metrics: pain factor, hematoma formation, and number of reinsertions. This study confirms that the use of the virtual reality-based system to supplement the traditional method may be the optimal program for training.

17. Linear regression in astronomy. II

Science.gov (United States)

Feigelson, Eric D.; Babu, Gutti J.

1992-01-01

A wide variety of least-squares linear regression procedures used in observational astronomy, particularly investigations of the cosmic distance scale, are presented and discussed. The classes of linear models considered are (1) unweighted regression lines, with bootstrap and jackknife resampling; (2) regression solutions when measurement error, in one or both variables, dominates the scatter; (3) methods to apply a calibration line to new data; (4) truncated regression models, which apply to flux-limited data sets; and (5) censored regression models, which apply when nondetections are present. For the calibration problem we develop two new procedures: a formula for the intercept offset between two parallel data sets, which propagates slope errors from one regression to the other; and a generalization of the Working-Hotelling confidence bands to nonstandard least-squares lines. They can provide improved error analysis for Faber-Jackson, Tully-Fisher, and similar cosmic distance scale relations.

DEFF Research Database (Denmark)

Møller, Jan Kloppenborg; Nielsen, Henrik Aalborg; Madsen, Henrik

2008-01-01

and an updating procedure are combined into a new algorithm for time-adaptive quantile regression, which generates new solutions on the basis of the old solution, leading to savings in computation time. The suggested algorithm is tested against a static quantile regression model on a data set with wind power......An algorithm for time-adaptive quantile regression is presented. The algorithm is based on the simplex algorithm, and the linear optimization formulation of the quantile regression problem is given. The observations have been split to allow a direct use of the simplex algorithm. The simplex method...... production, where the models combine splines and quantile regression. The comparison indicates superior performance for the time-adaptive quantile regression in all the performance parameters considered....

19. SEPARATION PHENOMENA LOGISTIC REGRESSION

Directory of Open Access Journals (Sweden)

Ikaro Daniel de Carvalho Barreto

2014-03-01

Full Text Available This paper proposes an application of concepts about the maximum likelihood estimation of the binomial logistic regression model to the separation phenomena. It generates bias in the estimation and provides different interpretations of the estimates on the different statistical tests (Wald, Likelihood Ratio and Score and provides different estimates on the different iterative methods (Newton-Raphson and Fisher Score. It also presents an example that demonstrates the direct implications for the validation of the model and validation of variables, the implications for estimates of odds ratios and confidence intervals, generated from the Wald statistics. Furthermore, we present, briefly, the Firth correction to circumvent the phenomena of separation.

20. COMPARISON OF EFFECTIVENESS OF TRADITIONAL AND INTERACTIVE LECTURE METHODS FOR TEACHING BIOCHEMISTRY AMONG FIRST YEAR MEDICAL STUDENTS IN GOVERNMENT MEDICAL COLLEGE, IDUKKI, KERALA

Directory of Open Access Journals (Sweden)

Sajeevan K. C

2016-09-01

Full Text Available BACKGROUND Traditional lecture is the most common type of teaching learning method used in professional colleges of India. Interactive lecture seems to be an important and feasible teaching learning method to increase the effect of learning in medical education. MATERIALS & METHODS The study was performed from July 2015 to October 2015 among first year medical students in Government Medical College, Idukki. All fifty first year MBBS students of 2014 batch were divided into group A and group B by simple random method. Two topics of translation were taken to both groups by two different lecture methods. The first topic was taught by interactive lecture to group A and traditional lecture to group B on the first day. Pre-test and post-test were done to assess gain in knowledge by two lecture methods. Second topic was taken to both groups on the second day by exchanging lecture methods. Their increase in knowledge was assessed by pre-test and post-test. On the second day, their feedback regarding perceptions and preferences were taken. STATISTICAL ANALYSIS Mean scores of pre and post-test were analysed by paired t test. Level of knowledge gained among two lecture methods was compared by independent t test and qualitative data on feedback was analysed using Chi square test. RESULTS The level of knowledge gained by interactive lectures was significantly higher than traditional lectures. Students agreed that interactive lectures motivated them for self-learning and increased their confidence regarding study materials. It also helped them in the recollection of lecture content and clearing doubt than traditional lectures. CONCLUSIONS Interactive lectures were accepted and considered to be more useful than traditional lectures for teaching biochemistry at Government Medical College, Idukki.