Multinomial logistic regression ensembles.
Lee, Kyewon; Ahn, Hongshik; Moon, Hojin; Kodell, Ralph L; Chen, James J
2013-05-01
This article proposes a method for multiclass classification problems using ensembles of multinomial logistic regression models. A multinomial logit model is used as a base classifier in ensembles from random partitions of predictors. The multinomial logit model can be applied to each mutually exclusive subset of the feature space without variable selection. By combining multiple models the proposed method can handle a huge database without a constraint needed for analyzing high-dimensional data, and the random partition can improve the prediction accuracy by reducing the correlation among base classifiers. The proposed method is implemented using R, and the performance including overall prediction accuracy, sensitivity, and specificity for each category is evaluated on two real data sets and simulation data sets. To investigate the quality of prediction in terms of sensitivity and specificity, the area under the receiver operating characteristic (ROC) curve (AUC) is also examined. The performance of the proposed model is compared to a single multinomial logit model and it shows a substantial improvement in overall prediction accuracy. The proposed method is also compared with other classification methods such as the random forest, support vector machines, and random multinomial logit model. PMID:23611203
Multinomial logistic regression-based feature selection for hyperspectral data
NASA Astrophysics Data System (ADS)
Pal, Mahesh
2012-02-01
This paper evaluates the performance of three feature selection methods based on multinomial logistic regression, and compares the performance of the best multinomial logistic regression-based feature selection approach with the support vector machine based recurring feature elimination approach. Two hyperspectral datasets, one consisting of 65 features (DAIS data) and other with 185 features (AVIRIS data) were used. Result suggests that a total of between 15 and 10 features selected by using the multinomial logistic regression-based feature selection approach as proposed by Cawley and Talbot achieve a significant improvement in classification accuracy in comparison to the use of all the features of the DAIS and AVIRIS datasets. In addition to the improved performance, the Cawley and Talbot approach does not require any user-defined parameter, thus avoiding the requirement of a model selection stage. In comparison, the other two multinomial logistic regression-based feature selection approaches require one user-defined parameter and do not perform as well as the Cawley and Talbot approach in terms of (i) the number of features required to achieve classification accuracy comparable to that achieved using the full dataset, and (ii) the classification accuracy achieved by the selected features. The Cawley and Talbot approach was also found to be computationally more efficient than the SVM-RFE technique, though both use the same number of selected features to achieve an equal or even higher level of accuracy than that achieved with full hyperspectral datasets.
Modeling urban growth with geographically weighted multinomial logistic regression
NASA Astrophysics Data System (ADS)
Luo, Jun; Kanala, Nagaraj Kapi
2008-10-01
Spatial heterogeneity is usually ignored in previous land use change studies. This paper presents a geographically weighted multinomial logistic regression model for investigating multiple land use conversion in the urban growth process. The proposed model makes estimation at each sample location and generates local coefficients of driving factors for land use conversion. A Gaussian function is used for determine the geographic weights guarantying that all other samples are involved in the calibration of the model for one location. A case study on Springfield metropolitan area is conducted. A set of independent variables are selected as driving factors. A traditional multinomial logistic regression model is set up and compared with the proposed model. Spatial variations of coefficients of independent variables are revealed by investigating the estimations at sample locations.
NASA Astrophysics Data System (ADS)
Lin, Yingzhi; Deng, Xiangzheng; Li, Xing; Ma, Enjun
2014-12-01
Spatially explicit simulation of land use change is the basis for estimating the effects of land use and cover change on energy fluxes, ecology and the environment. At the pixel level, logistic regression is one of the most common approaches used in spatially explicit land use allocation models to determine the relationship between land use and its causal factors in driving land use change, and thereby to evaluate land use suitability. However, these models have a drawback in that they do not determine/allocate land use based on the direct relationship between land use change and its driving factors. Consequently, a multinomial logistic regression method was introduced to address this flaw, and thereby, judge the suitability of a type of land use in any given pixel in a case study area of the Jiangxi Province, China. A comparison of the two regression methods indicated that the proportion of correctly allocated pixels using multinomial logistic regression was 92.98%, which was 8.47% higher than that obtained using logistic regression. Paired t-test results also showed that pixels were more clearly distinguished by multinomial logistic regression than by logistic regression. In conclusion, multinomial logistic regression is a more efficient and accurate method for the spatial allocation of land use changes. The application of this method in future land use change studies may improve the accuracy of predicting the effects of land use and cover change on energy fluxes, ecology, and environment.
Robust Logistic and Probit Methods for Binary and Multinomial Regression
Tabatabai, MA; Li, H; Eby, WM; Kengwoung-Keumo, JJ; Manne, U; Bae, S; Fouad, M; Singh, KP
2015-01-01
In this paper we introduce new robust estimators for the logistic and probit regressions for binary, multinomial, nominal and ordinal data and apply these models to estimate the parameters when outliers or inluential observations are present. Maximum likelihood estimates don't behave well when outliers or inluential observations are present. One remedy is to remove inluential observations from the data and then apply the maximum likelihood technique on the deleted data. Another approach is to employ a robust technique that can handle outliers and inluential observations without removing any observations from the data sets. The robustness of the method is tested using real and simulated data sets. PMID:26078914
A note on the estimation of the multinomial logistic model with correlated responses in SAS.
Kuss, Oliver; McLerran, Dale
2007-09-01
We show how multinomial logistic models with correlated responses can be estimated within SAS software. To achieve this, random effects and marginal models are introduced and the respective SAS code is given. An example data set on physicians' recommendations and preferences in traumatic brain injury rehabilitation is used for illustration. The main motivation for this work are two recent papers that recommend estimating multinomial logistic models with correlated responses by using a Poisson likelihood which is statistically correct but computationally inefficient. PMID:17686544
ERIC Educational Resources Information Center
Anderson, Carolyn J.; Verkuilen, Jay; Peyton, Buddy L.
2010-01-01
Survey items with multiple response categories and multiple-choice test questions are ubiquitous in psychological and educational research. We illustrate the use of log-multiplicative association (LMA) models that are extensions of the well-known multinomial logistic regression model for multiple dependent outcome variables to reanalyze a set of…
A warning concerning the estimation of multinomial logistic models with correlated responses in SAS.
de Rooij, Mark; Worku, Hailemichael M
2012-08-01
Kuss and McLerran in a paper in this journal provide SAS code for the estimation of multinomial logistic models for correlated data. Their motivation derived from two papers that recommended to estimate such models using a Poisson likelihood, which is according to Kuss and McLerran "statistically correct but computationally inefficient". Kuss and McLerran propose several estimating methods. Some of these are based on the fact that the multinomial model is a multivariate binary model. Subsequently a procedure proposed by Wright is exploited to fit the models. In this paper we will show that the new computation methods, based on the approach by Wright, are statistically incorrect because they do not take into account that for multinomial data a multivariate link function is needed. An alternative estimation strategy is proposed using the clustered bootstrap. PMID:22398107
NASA Astrophysics Data System (ADS)
Snedden, Gregg A.; Steyer, Gregory D.
2013-02-01
Understanding plant community zonation along estuarine stress gradients is critical for effective conservation and restoration of coastal wetland ecosystems. We related the presence of plant community types to estuarine hydrology at 173 sites across coastal Louisiana. Percent relative cover by species was assessed at each site near the end of the growing season in 2008, and hourly water level and salinity were recorded at each site Oct 2007-Sep 2008. Nine plant community types were delineated with k-means clustering, and indicator species were identified for each of the community types with indicator species analysis. An inverse relation between salinity and species diversity was observed. Canonical correspondence analysis (CCA) effectively segregated the sites across ordination space by community type, and indicated that salinity and tidal amplitude were both important drivers of vegetation composition. Multinomial logistic regression (MLR) and Akaike's Information Criterion (AIC) were used to predict the probability of occurrence of the nine vegetation communities as a function of salinity and tidal amplitude, and probability surfaces obtained from the MLR model corroborated the CCA results. The weighted kappa statistic, calculated from the confusion matrix of predicted versus actual community types, was 0.7 and indicated good agreement between observed community types and model predictions. Our results suggest that models based on a few key hydrologic variables can be valuable tools for predicting vegetation community development when restoring and managing coastal wetlands.
Ismail, Abbas; Josephat, Peter
2014-01-01
Tuberculosis (TB) is one of the most important public health problems in Tanzania and was declared as a national public health emergency in 2006. Community and individual knowledge and perceptions are critical factors in the control of the disease. The objective of this study was to analyze the knowledge and perception on the transmission of TB in Tanzania. Multinomial Logistic Regression analysis was considered in order to quantify the impact of knowledge and perception on TB. The data used was adopted as secondary data from larger national survey 2007-08 Tanzania HIV/AIDS and Malaria Indicator Survey. The findings across groups revealed that knowledge on TB transmission increased with an increase in age and level of education. People in rural areas had less knowledge regarding tuberculosis transmission compared to urban areas [OR = 0.7]. People with the access to radio [OR = 1.7] were more knowledgeable on tuberculosis transmission compared to those who did not have access to radio. People who did not have telephone [OR = 0.6] were less knowledgeable on tuberculosis route of transmission compared to those who had telephone. The findings showed that socio-demographic factors such as age, education, place of residence and owning telephone or radio varied systematically with knowledge on tuberculosis transmission. PMID:26867270
Lewis, Kristin Nicole; Heckman, Bernadette Davantes; Himawan, Lina
2011-08-01
Growth mixture modeling (GMM) identified latent groups based on treatment outcome trajectories of headache disability measures in patients in headache subspecialty treatment clinics. Using a longitudinal design, 219 patients in headache subspecialty clinics in 4 large cities throughout Ohio provided data on their headache disability at pretreatment and 3 follow-up assessments. GMM identified 3 treatment outcome trajectory groups: (1) patients who initiated treatment with elevated disability levels and who reported statistically significant reductions in headache disability (high-disability improvers; 11%); (2) patients who initiated treatment with elevated disability but who reported no reductions in disability (high-disability nonimprovers; 34%); and (3) patients who initiated treatment with moderate disability and who reported statistically significant reductions in headache disability (moderate-disability improvers; 55%). Based on the final multinomial logistic regression model, a dichotomized treatment appointment attendance variable was a statistically significant predictor for differentiating high-disability improvers from high-disability nonimprovers. Three-fourths of patients who initiated treatment with elevated disability levels did not report reductions in disability after 5 months of treatment with new preventive pharmacotherapies. Preventive headache agents may be most efficacious for patients with moderate levels of disability and for patients with high disability levels who attend all treatment appointments. PMID:21420240
Snedden, Gregg A.; Steyer, Gregory D.
2013-01-01
Understanding plant community zonation along estuarine stress gradients is critical for effective conservation and restoration of coastal wetland ecosystems. We related the presence of plant community types to estuarine hydrology at 173 sites across coastal Louisiana. Percent relative cover by species was assessed at each site near the end of the growing season in 2008, and hourly water level and salinity were recorded at each site Oct 2007–Sep 2008. Nine plant community types were delineated with k-means clustering, and indicator species were identified for each of the community types with indicator species analysis. An inverse relation between salinity and species diversity was observed. Canonical correspondence analysis (CCA) effectively segregated the sites across ordination space by community type, and indicated that salinity and tidal amplitude were both important drivers of vegetation composition. Multinomial logistic regression (MLR) and Akaike's Information Criterion (AIC) were used to predict the probability of occurrence of the nine vegetation communities as a function of salinity and tidal amplitude, and probability surfaces obtained from the MLR model corroborated the CCA results. The weighted kappa statistic, calculated from the confusion matrix of predicted versus actual community types, was 0.7 and indicated good agreement between observed community types and model predictions. Our results suggest that models based on a few key hydrologic variables can be valuable tools for predicting vegetation community development when restoring and managing coastal wetlands.
2012-01-01
Background Identifying risk factors for Salmonella Enteritidis (SE) infections in Ontario will assist public health authorities to design effective control and prevention programs to reduce the burden of SE infections. Our research objective was to identify risk factors for acquiring SE infections with various phage types (PT) in Ontario, Canada. We hypothesized that certain PTs (e.g., PT8 and PT13a) have specific risk factors for infection. Methods Our study included endemic SE cases with various PTs whose isolates were submitted to the Public Health Laboratory-Toronto from January 20th to August 12th, 2011. Cases were interviewed using a standardized questionnaire that included questions pertaining to demographics, travel history, clinical symptoms, contact with animals, and food exposures. A multinomial logistic regression method using the Generalized Linear Latent and Mixed Model procedure and a case-case study design were used to identify risk factors for acquiring SE infections with various PTs in Ontario, Canada. In the multinomial logistic regression model, the outcome variable had three categories representing human infections caused by SE PT8, PT13a, and all other SE PTs (i.e., non-PT8/non-PT13a) as a referent category to which the other two categories were compared. Results In the multivariable model, SE PT8 was positively associated with contact with dogs (OR=2.17, 95% CI 1.01-4.68) and negatively associated with pepper consumption (OR=0.35, 95% CI 0.13-0.94), after adjusting for age categories and gender, and using exposure periods and health regions as random effects to account for clustering. Conclusions Our study findings offer interesting hypotheses about the role of phage type-specific risk factors. Multinomial logistic regression analysis and the case-case study approach are novel methodologies to evaluate associations among SE infections with different PTs and various risk factors. PMID:23057531
Jostins, Luke; McVean, Gilean
2016-01-01
Motivation: For many classes of disease the same genetic risk variants underly many related phenotypes or disease subtypes. Multinomial logistic regression provides an attractive framework to analyze multi-category phenotypes, and explore the genetic relationships between these phenotype categories. We introduce Trinculo, a program that implements a wide range of multinomial analyses in a single fast package that is designed to be easy to use by users of standard genome-wide association study software. Availability and implementation: An open source C implementation, with code and binaries for Linux and Mac OSX, is available for download at http://sourceforge.net/projects/trinculo Supplementary information: Supplementary data are available at Bioinformatics online. Contact: lj4@well.ox.ac.uk PMID:26873930
Ghazali, Amirul Syafiq Mohd; Ali, Zalila; Noor, Norlida Mohd; Baharum, Adam
2015-10-22
Multinomial logistic regression is widely used to model the outcomes of a polytomous response variable, a categorical dependent variable with more than two categories. The model assumes that the conditional mean of the dependent categorical variables is the logistic function of an affine combination of predictor variables. Its procedure gives a number of logistic regression models that make specific comparisons of the response categories. When there are q categories of the response variable, the model consists of q-1 logit equations which are fitted simultaneously. The model is validated by variable selection procedures, tests of regression coefficients, a significant test of the overall model, goodness-of-fit measures, and validation of predicted probabilities using odds ratio. This study used the multinomial logistic regression model to investigate obesity and overweight among primary school students in a rural area on the basis of their demographic profiles, lifestyles and on the diet and food intake. The results indicated that obesity and overweight of students are related to gender, religion, sleep duration, time spent on electronic games, breakfast intake in a week, with whom meals are taken, protein intake, and also, the interaction between breakfast intake in a week with sleep duration, and the interaction between gender and protein intake.
NASA Astrophysics Data System (ADS)
Ghazali, Amirul Syafiq Mohd; Ali, Zalila; Noor, Norlida Mohd; Baharum, Adam
2015-10-01
Multinomial logistic regression is widely used to model the outcomes of a polytomous response variable, a categorical dependent variable with more than two categories. The model assumes that the conditional mean of the dependent categorical variables is the logistic function of an affine combination of predictor variables. Its procedure gives a number of logistic regression models that make specific comparisons of the response categories. When there are q categories of the response variable, the model consists of q-1 logit equations which are fitted simultaneously. The model is validated by variable selection procedures, tests of regression coefficients, a significant test of the overall model, goodness-of-fit measures, and validation of predicted probabilities using odds ratio. This study used the multinomial logistic regression model to investigate obesity and overweight among primary school students in a rural area on the basis of their demographic profiles, lifestyles and on the diet and food intake. The results indicated that obesity and overweight of students are related to gender, religion, sleep duration, time spent on electronic games, breakfast intake in a week, with whom meals are taken, protein intake, and also, the interaction between breakfast intake in a week with sleep duration, and the interaction between gender and protein intake.
NASA Astrophysics Data System (ADS)
Al-Mudhafar, W. J.
2013-12-01
Precisely prediction of rock facies leads to adequate reservoir characterization by improving the porosity-permeability relationships to estimate the properties in non-cored intervals. It also helps to accurately identify the spatial facies distribution to perform an accurate reservoir model for optimal future reservoir performance. In this paper, the facies estimation has been done through Multinomial logistic regression (MLR) with respect to the well logs and core data in a well in upper sandstone formation of South Rumaila oil field. The entire independent variables are gamma rays, formation density, water saturation, shale volume, log porosity, core porosity, and core permeability. Firstly, Robust Sequential Imputation Algorithm has been considered to impute the missing data. This algorithm starts from a complete subset of the dataset and estimates sequentially the missing values in an incomplete observation by minimizing the determinant of the covariance of the augmented data matrix. Then, the observation is added to the complete data matrix and the algorithm continues with the next observation with missing values. The MLR has been chosen to estimate the maximum likelihood and minimize the standard error for the nonlinear relationships between facies & core and log data. The MLR is used to predict the probabilities of the different possible facies given each independent variable by constructing a linear predictor function having a set of weights that are linearly combined with the independent variables by using a dot product. Beta distribution of facies has been considered as prior knowledge and the resulted predicted probability (posterior) has been estimated from MLR based on Baye's theorem that represents the relationship between predicted probability (posterior) with the conditional probability and the prior knowledge. To assess the statistical accuracy of the model, the bootstrap should be carried out to estimate extra-sample prediction error by randomly
NASA Astrophysics Data System (ADS)
Nong, Yu; Du, Qingyun; Wang, Kun; Miao, Lei; Zhang, Weiwei
2008-10-01
Urban growth modeling, one of the most important aspects of land use and land cover change study, has attracted substantial attention because it helps to comprehend the mechanisms of land use change thus helps relevant policies made. This study applied multinomial logistic regression to model urban growth in the Jiayu county of Hubei province, China to discover the relationship between urban growth and the driving forces of which biophysical and social-economic factors are selected as independent variables. This type of regression is similar to binary logistic regression, but it is more general because the dependent variable is not restricted to two categories, as those previous studies did. The multinomial one can simulate the process of multiple land use competition between urban land, bare land, cultivated land and orchard land. Taking the land use type of Urban as reference category, parameters could be estimated with odds ratio. A probability map is generated from the model to predict where urban growth will occur as a result of the computation.
NASA Astrophysics Data System (ADS)
Lu, Q.; Wang, X. L.
2009-04-01
Detecting changepoints in a sequence of continuous random variables has been extensively explored in both statistics and climatology literature. There is little, however, for studying the case with multicategory random variables. For instance, the sky-cloudiness condition in Canada is reported in tenths of the sky dome and thus has 11 categories (from 0 for clear sky, to 10 tenths for overcast). This study develops an overall likelihood-ratio test statistic for detecting a sudden change in the parameters of the continuation-ratio logit random intercept model for a sequence of multinomial variables. A method of partitioning the overall test statistic is also proposed, which allows one to assess the significance of the effect of the detected change on individual categories. An application of this new technique to real sky cloudiness data is also presented.
NASA Astrophysics Data System (ADS)
Madhu, B.; Ashok, N. C.; Balasubramanian, S.
2014-11-01
Multinomial logistic regression analysis was used to develop statistical model that can predict the probability of breast cancer in Southern Karnataka using the breast cancer occurrence data during 2007-2011. Independent socio-economic variables describing the breast cancer occurrence like age, education, occupation, parity, type of family, health insurance coverage, residential locality and socioeconomic status of each case was obtained. The models were developed as follows: i) Spatial visualization of the Urban- rural distribution of breast cancer cases that were obtained from the Bharat Hospital and Institute of Oncology. ii) Socio-economic risk factors describing the breast cancer occurrences were complied for each case. These data were then analysed using multinomial logistic regression analysis in a SPSS statistical software and relations between the occurrence of breast cancer across the socio-economic status and the influence of other socio-economic variables were evaluated and multinomial logistic regression models were constructed. iii) the model that best predicted the occurrence of breast cancer were identified. This multivariate logistic regression model has been entered into a geographic information system and maps showing the predicted probability of breast cancer occurrence in Southern Karnataka was created. This study demonstrates that Multinomial logistic regression is a valuable tool for developing models that predict the probability of breast cancer Occurrence in Southern Karnataka.
NASA Astrophysics Data System (ADS)
Song, Sutao; Chen, Gongxiang; Zhan, Yu; Zhang, Jiacai; Yao, Li
2014-03-01
Recently, sparse algorithms, such as Sparse Multinomial Logistic Regression (SMLR), have been successfully applied in decoding visual information from functional magnetic resonance imaging (fMRI) data, where the contrast of visual stimuli was predicted by a classifier. The contrast classifier combined brain activities of voxels with sparse weights. For sparse algorithms, the goal is to learn a classifier whose weights distributed as sparse as possible by introducing some prior belief about the weights. There are two ways to introduce a sparse prior constraints for weights: the Automatic Relevance Determination (ARD-SMLR) and Laplace prior (LAP-SMLR). In this paper, we presented comparison results between the ARD-SMLR and LAP-SMLR models in computational time, classification accuracy and voxel selection. Results showed that, for fMRI data, no significant difference was found in classification accuracy between these two methods when voxels in V1 were chosen as input features (totally 1017 voxels). As for computation time, LAP-SMLR was superior to ARD-SMLR; the survived voxels for ARD-SMLR was less than LAP-SMLR. Using simulation data, we confirmed the classification performance for the two SMLR models was sensitive to the sparsity of the initial features, when the ratio of relevant features to the initial features was larger than 0.01, ARD-SMLR outperformed LAP-SMLR; otherwise, LAP-SMLR outperformed LAP-SMLR. Simulation data showed ARD-SMLR was more efficient in selecting relevant features.
Mala, A; Ravichandran, B; Raghavan, S; Rajmohan, H R
2010-08-01
There are only a few studies performed on multinomial logistic regression on the benzene-exposed occupational group. A study was carried out to assess the relationship between the benzene concentration and trans-trans-muconic acid (t,t-MA), biomarkers in urine samples from petrol filling workers. A total of 117 workers involved in this occupation were selected for this current study. Generally, logistic regression analysis (LR) is a common statistical technique that could be used to predict the likelihood of categorical or binary or dichotomous outcome variables. The multinomial logistic regression equations were used to predict the relationship between benzene concentration and t,t-MA. The results showed a significant correlation between benzene and t,t-MA among the petrol fillers. Prediction equations were estimated by adopting the physical characteristic viz., age, experience in years and job categories of petrol filling station workers. Interestingly, there was no significant difference observed among experience in years. Petrol fillers and cashiers having a higher occupational risk were in the age group of ≤24 and between 25 and 34 years. Among the petrol fillers, the t,t-MA levels with exceeding ACGIH TWA-TLV level was showing to be more significant. This study demonstrated that multinomial logistic regression is an effective model for profiling the greatest risk of the benzene-exposed group caused by different explanatory variables. PMID:21120078
Mala, A.; Ravichandran, B.; Raghavan, S.; Rajmohan, H. R.
2010-01-01
There are only a few studies performed on multinomial logistic regression on the benzene-exposed occupational group. A study was carried out to assess the relationship between the benzene concentration and trans-trans-muconic acid (t,t-MA), biomarkers in urine samples from petrol filling workers. A total of 117 workers involved in this occupation were selected for this current study. Generally, logistic regression analysis (LR) is a common statistical technique that could be used to predict the likelihood of categorical or binary or dichotomous outcome variables. The multinomial logistic regression equations were used to predict the relationship between benzene concentration and t,t-MA. The results showed a significant correlation between benzene and t,t-MA among the petrol fillers. Prediction equations were estimated by adopting the physical characteristic viz., age, experience in years and job categories of petrol filling station workers. Interestingly, there was no significant difference observed among experience in years. Petrol fillers and cashiers having a higher occupational risk were in the age group of ≤24 and between 25 and 34 years. Among the petrol fillers, the t,t-MA levels with exceeding ACGIH TWA-TLV level was showing to be more significant. This study demonstrated that multinomial logistic regression is an effective model for profiling the greatest risk of the benzene-exposed group caused by different explanatory variables. PMID:21120078
NASA Astrophysics Data System (ADS)
Venkataraman, Kartik; Uddameri, Venkatesh
2012-08-01
SummaryThe occurrence of elevated levels of arsenic and nitrate in aquifers impacted by agricultural activities is common and can result in adverse health effects in rural areas. Numerous wells located in the Ogallala aquifer in the Southern High Plains of Texas have tested positive for both arsenic and nitrate MCL exceedance. To model the simultaneous exceedance of both chemicals, two types of Logistic Regression (LR) models were developed by (a) treating arsenic and nitrate independently and combining the marginal probabilities of their exceedance, and (b) treating the two exceedances together by using a multinomial model. Influencing variables representative of both soil and aquifer properties and data for which was readily available were identified. The predictive capacities of the two models were evaluated using Received Operating Characteristics (ROCs) and spatial trends in predictions were studied. The LR model constructed from the marginal probabilities had lower overall accuracy (59% correct classifications) and was extremely conservative by over-predicting outcomes. In contrast, the multinomial model showed good overall accuracy (79% correct classifications), made the correct predictions 90% of the time when both arsenic and nitrate MCL exceedances were observed, and was a good fit for wells located in agricultural areas. The results of the multinomial model also confirm previous studies that attributed shallow subsurface arsenic to anthropogenic activities. Based on the insights provided by the model it is recommended that where agricultural areas are concerned, the occurrence of arsenic and nitrate are better evaluated together.
Tvedebrink, Torben; Eriksen, Poul Svante; Morling, Niels
2015-11-01
In this paper, we discuss the construction of a multivariate generalisation of the Dirichlet-multinomial distribution. An example from forensic genetics in the statistical analysis of DNA mixtures motivates the study of this multivariate extension. In forensic genetics, adjustment of the match probabilities due to remote ancestry in the population is often done using the so-called θ-correction. This correction increases the probability of observing multiple copies of rare alleles in a subpopulation and thereby reduces the weight of the evidence for rare genotypes. A recent publication by Cowell et al. (2015) showed elegantly how to use Bayesian networks for efficient computations of likelihood ratios in a forensic genetic context. However, their underlying population genetic model assumed independence of alleles, which is not realistic in real populations. We demonstrate how the so-called θ-correction can be incorporated in Bayesian networks to make efficient computations by modifying the Markov structure of Cowell et al. (2015). By numerical examples, we show how the θ-correction incorporated in the multivariate Dirichlet-multinomial distribution affects the weight of evidence. PMID:26344785
[Case-control studies with multinomial responses: a proposal for analysis].
Mafra, Ana Carolina Cintra Nunes; Nucci, Luciana Bertoldi; Cordeiro, Ricardo; Stephan, Celso
2010-03-01
This study reviews articles on case-control studies in which the cases were classified in two or more types. Application of multinomial models and their adequacy for case-control studies are discussed. Among the available multinomial adjustments, we argue that the polytomous logistic model is the most suitable for obtaining epidemiological measures of risk and association in case-control studies. By way of illustration, we present an application of this model in a population-based case-control study, comparing the results with those obtained in a binomial logistic model. The multinomial approach allows investigating, in a single analysis, the occurrence of associations between covariates and more or more subclasses of cases, thus providing the epidemiologically relevant possibility of identifying individualized risk and protective factors for each subclass. PMID:20464064
Algamal, Zakariya Yahya; Lee, Muhammad Hisyam
2015-12-01
Cancer classification and gene selection in high-dimensional data have been popular research topics in genetics and molecular biology. Recently, adaptive regularized logistic regression using the elastic net regularization, which is called the adaptive elastic net, has been successfully applied in high-dimensional cancer classification to tackle both estimating the gene coefficients and performing gene selection simultaneously. The adaptive elastic net originally used elastic net estimates as the initial weight, however, using this weight may not be preferable for certain reasons: First, the elastic net estimator is biased in selecting genes. Second, it does not perform well when the pairwise correlations between variables are not high. Adjusted adaptive regularized logistic regression (AAElastic) is proposed to address these issues and encourage grouping effects simultaneously. The real data results indicate that AAElastic is significantly consistent in selecting genes compared to the other three competitor regularization methods. Additionally, the classification performance of AAElastic is comparable to the adaptive elastic net and better than other regularization methods. Thus, we can conclude that AAElastic is a reliable adaptive regularized logistic regression method in the field of high-dimensional cancer classification. PMID:26520484
Brumback, Babette A; Cai, Zhuangyu; He, Zhulin; Zheng, Hao W; Dailey, Amy B
2013-04-15
In order to adjust individual-level covariate effects for confounding due to unmeasured neighborhood characteristics, we have recently developed conditional pseudolikelihood methods to estimate the parameters of a proportional odds model for clustered ordinal outcomes with complex survey data. The methods require sampling design joint probabilities for each within-neighborhood pair. In the present article, we develop a similar methodology for a baseline category logit model for clustered multinomial outcomes and for a loglinear model for clustered count outcomes. All of the estimators and asymptotic sampling distributions we present can be conveniently computed using standard logistic regression software for complex survey data, such as sas proc surveylogistic. We demonstrate validity of the methods theoretically and also empirically by using simulations. We apply the new method for clustered multinomial outcomes to data from the 2008 Florida Behavioral Risk Factor Surveillance System survey in order to investigate disparities in frequency of dental cleaning both unadjusted and adjusted for confounding by neighborhood. PMID:22976045
On exchangeable multinomial distributions
George, E. Olusegun; Cheon, Kyeongmi; Yuan, Yilian; Szabo, Aniko
2016-01-01
We derive an expression for the joint distribution of exchangeable multinomial random variables, which generalizes the multinomial distribution based on independent trials while retaining some of its important properties. Unlike de Finneti's representation theorem for a binary sequence, the exchangeable multinomial distribution derived here does not require that the finite set of random variables under consideration be a subset of an infinite sequence. Using expressions for higher moments and correlations, we show that the covariance matrix for exchangeable multinomial data has a different form from that usually assumed in the literature, and we analyse data from developmental toxicology studies. The proposed analyses have been implemented in R and are available on CRAN in the CorrBin package.
Li, Li; Brumback, Babette A; Weppelmann, Thomas A; Morris, J Glenn; Ali, Afsar
2016-08-15
Motivated by an investigation of the effect of surface water temperature on the presence of Vibrio cholerae in water samples collected from different fixed surface water monitoring sites in Haiti in different months, we investigated methods to adjust for unmeasured confounding due to either of the two crossed factors site and month. In the process, we extended previous methods that adjust for unmeasured confounding due to one nesting factor (such as site, which nests the water samples from different months) to the case of two crossed factors. First, we developed a conditional pseudolikelihood estimator that eliminates fixed effects for the levels of each of the crossed factors from the estimating equation. Using the theory of U-Statistics for independent but non-identically distributed vectors, we show that our estimator is consistent and asymptotically normal, but that its variance depends on the nuisance parameters and thus cannot be easily estimated. Consequently, we apply our estimator in conjunction with a permutation test, and we investigate use of the pigeonhole bootstrap and the jackknife for constructing confidence intervals. We also incorporate our estimator into a diagnostic test for a logistic mixed model with crossed random effects and no unmeasured confounding. For comparison, we investigate between-within models extended to two crossed factors. These generalized linear mixed models include covariate means for each level of each factor in order to adjust for the unmeasured confounding. We conduct simulation studies, and we apply the methods to the Haitian data. Copyright © 2016 John Wiley & Sons, Ltd. PMID:26892025
Multinomial pattern matching revisited
NASA Astrophysics Data System (ADS)
Horvath, Matthew S.; Rigling, Brian D.
2015-05-01
Multinomial pattern matching (MPM) is an automatic target recognition algorithm developed for specifically radar data at Sandia National Laboratories. The algorithm is in a family of algorithms that first quantizes pixel value into Nq bins based on pixel amplitude before training and classification. This quantization step reduces the sensitivity of algorithm performance to absolute intensity variation in the data, typical of radar data where signatures exhibit high variation for even small changes in aspect angle. Our previous work has focused on performance analysis of peaky template matching, a special case of MPM where binary quantization is used (Nq = 2). Unfortunately references on these algorithms are generally difficult to locate and here we revisit the MPM algorithm and illustrate the underlying statistical model and decision rules for two algorithm interpretations: the 1-of-K vector form and the scalar. MPM can also be used as a detector and specific attention is given to algorithm tuning where "peak pixels" are chosen based on their underlying empirical probabilities according to a reward minimization strategy aimed at reducing false alarms in the detection scenario and false positives in a classification capacity. The algorithms are demonstrated using Monte Carlo simulations on the AFRL civilian vehicle dataset for variety of choices of Nq.
Kleinman, Lawrence C; Norton, Edward C
2009-01-01
Objective To develop and validate a general method (called regression risk analysis) to estimate adjusted risk measures from logistic and other nonlinear multiple regression models. We show how to estimate standard errors for these estimates. These measures could supplant various approximations (e.g., adjusted odds ratio [AOR]) that may diverge, especially when outcomes are common. Study Design Regression risk analysis estimates were compared with internal standards as well as with Mantel–Haenszel estimates, Poisson and log-binomial regressions, and a widely used (but flawed) equation to calculate adjusted risk ratios (ARR) from AOR. Data Collection Data sets produced using Monte Carlo simulations. Principal Findings Regression risk analysis accurately estimates ARR and differences directly from multiple regression models, even when confounders are continuous, distributions are skewed, outcomes are common, and effect size is large. It is statistically sound and intuitive, and has properties favoring it over other methods in many cases. Conclusions Regression risk analysis should be the new standard for presenting findings from multiple regression analysis of dichotomous outcomes for cross-sectional, cohort, and population-based case–control studies, particularly when outcomes are common or effect size is large. PMID:18793213
NASA Astrophysics Data System (ADS)
Grégoire, G.
2014-12-01
The logistic regression originally is intended to explain the relationship between the probability of an event and a set of covariables. The model's coefficients can be interpreted via the odds and odds ratio, which are presented in introduction of the chapter. The observations are possibly got individually, then we speak of binary logistic regression. When they are grouped, the logistic regression is said binomial. In our presentation we mainly focus on the binary case. For statistical inference the main tool is the maximum likelihood methodology: we present the Wald, Rao and likelihoods ratio results and their use to compare nested models. The problems we intend to deal with are essentially the same as in multiple linear regression: testing global effect, individual effect, selection of variables to build a model, measure of the fitness of the model, prediction of new values… . The methods are demonstrated on data sets using R. Finally we briefly consider the binomial case and the situation where we are interested in several events, that is the polytomous (multinomial) logistic regression and the particular case of ordinal logistic regression.
Estimation of incomplete multinomial data
NASA Technical Reports Server (NTRS)
Credeur, K. R.
1980-01-01
Program estimates cell probabilities for data observed to fall in one of two or more categories when exact category cannot be determined. Data are assumed to be randomly incomplete. Estimation minimizes risk of quadratic loss. Program should be useful in projects where multinomial data is analyzed, but where observations are sometimes incomplete. Program is in FORTRAN IV and Assembler for batch execution on CYBER 173.
Fuzzy multinomial control chart and its application
NASA Astrophysics Data System (ADS)
Wibawati, Mashuri, Muhammad; Purhadi, Irhamah
2016-03-01
Control chart is a technique that has been used widely in industry and services. P chart is the simplest control chart. In this chart, item is classified into two categories as either conforming and non conforming. This chart based on binomial distribution. In practice, each item can classify in more than two categories such as very bad, bad, good and very good. Then to monitor the process we used multinomial p control chart. However, if the classification is an element of vagueness, the fuzzy multinomial control chart (FM) is more appropriately used. Control limit of FM chart obtained multinomial distribution and the degree of membership using fuzzy trianguler are 0, 0.25. 0.5 and 1. This chart will be applied to the data glass and will compare with multinomial p control chart.
Multinomial and Compound Multinomial Error Models for Tests with Complex Item Scoring
ERIC Educational Resources Information Center
Lee, Won-Chan
2007-01-01
This article introduces a multinomial error model, which models an examinee's test scores obtained over repeated measurements of an assessment that consists of polytomously scored items. A compound multinomial error model is also introduced for situations in which items are stratified according to content categories and/or prespecified numbers of…
Multinomial mixture model with heterogeneous classification probabilities
Holland, M.D.; Gray, B.R.
2011-01-01
Royle and Link (Ecology 86(9):2505-2512, 2005) proposed an analytical method that allowed estimation of multinomial distribution parameters and classification probabilities from categorical data measured with error. While useful, we demonstrate algebraically and by simulations that this method yields biased multinomial parameter estimates when the probabilities of correct category classifications vary among sampling units. We address this shortcoming by treating these probabilities as logit-normal random variables within a Bayesian framework. We use Markov chain Monte Carlo to compute Bayes estimates from a simulated sample from the posterior distribution. Based on simulations, this elaborated Royle-Link model yields nearly unbiased estimates of multinomial and correct classification probability estimates when classification probabilities are allowed to vary according to the normal distribution on the logit scale or according to the Beta distribution. The method is illustrated using categorical submersed aquatic vegetation data. ?? 2010 Springer Science+Business Media, LLC.
The Finite and Moving Order Multinomial Universal Portfolio
NASA Astrophysics Data System (ADS)
Tan, Choon Peng; Theng Pang, Sook
2013-04-01
An upper bound for the ratio of wealths of the best constant -rebalanced portfolio to that of the multinomial universal portfolio is derived. The finite- order multinomial universal portfolios can reduce the implementation time and computer-memory requirements for computation. The improved performance of the finite-order portfolios on some selected local stock-price data sets is observed.
Hierarchical Multinomial Processing Tree Models: A Latent-Class Approach
ERIC Educational Resources Information Center
Klauer, Karl Christoph
2006-01-01
Multinomial processing tree models are widely used in many areas of psychology. Their application relies on the assumption of parameter homogeneity, that is, on the assumption that participants do not differ in their parameter values. Tests for parameter homogeneity are proposed that can be routinely used as part of multinomial model analyses to…
A spatial scan statistic for multinomial data
Jung, Inkyung; Kulldorff, Martin; Richard, Otukei John
2014-01-01
As a geographical cluster detection analysis tool, the spatial scan statistic has been developed for different types of data such as Bernoulli, Poisson, ordinal, exponential and normal. Another interesting data type is multinomial. For example, one may want to find clusters where the disease-type distribution is statistically significantly different from the rest of the study region when there are different types of disease. In this paper, we propose a spatial scan statistic for such data, which is useful for geographical cluster detection analysis for categorical data without any intrinsic order information. The proposed method is applied to meningitis data consisting of five different disease categories to identify areas with distinct disease-type patterns in two counties in the U.K. The performance of the method is evaluated through a simulation study. PMID:20680984
Modeling abundance using multinomial N-mixture models
Royle, Andy
2016-01-01
Multinomial N-mixture models are a generalization of the binomial N-mixture models described in Chapter 6 to allow for more complex and informative sampling protocols beyond simple counts. Many commonly used protocols such as multiple observer sampling, removal sampling, and capture-recapture produce a multivariate count frequency that has a multinomial distribution and for which multinomial N-mixture models can be developed. Such protocols typically result in more precise estimates than binomial mixture models because they provide direct information about parameters of the observation process. We demonstrate the analysis of these models in BUGS using several distinct formulations that afford great flexibility in the types of models that can be developed, and we demonstrate likelihood analysis using the unmarked package. Spatially stratified capture-recapture models are one class of models that fall into the multinomial N-mixture framework, and we discuss analysis of stratified versions of classical models such as model Mb, Mh and other classes of models that are only possible to describe within the multinomial N-mixture framework.
Institutional Climate and Student Departure: A Multinomial Multilevel Modeling Approach
ERIC Educational Resources Information Center
Yi, Pyong-sik
2008-01-01
This study applied a multinomial HOLM technique to examine the extent to which the institutional climate for diversity influences the different types of college student withdrawal, such as stop out, drop out, and transfer. Based on a reformulation of Tinto's model along with the conceptualization of institutional climate for diversity by Hurtado…
Pig Data and Bayesian Inference on Multinomial Probabilities
ERIC Educational Resources Information Center
Kern, John C.
2006-01-01
Bayesian inference on multinomial probabilities is conducted based on data collected from the game Pass the Pigs[R]. Prior information on these probabilities is readily available from the instruction manual, and is easily incorporated in a Dirichlet prior. Posterior analysis of the scoring probabilities quantifies the discrepancy between empirical…
Hierarchical Multinomial Processing Tree Models: A Latent-Trait Approach
ERIC Educational Resources Information Center
Klauer, Karl Christoph
2010-01-01
Multinomial processing tree models are widely used in many areas of psychology. A hierarchical extension of the model class is proposed, using a multivariate normal distribution of person-level parameters with the mean and covariance matrix to be estimated from the data. The hierarchical model allows one to take variability between persons into…
A Multinomial Model of Event-Based Prospective Memory
ERIC Educational Resources Information Center
Smith, Rebekah E.; Bayen, Ute J.
2004-01-01
Prospective memory is remembering to perform an action in the future. The authors introduce the 1st formal model of event-based prospective memory, namely, a multinomial model that includes 2 separate parameters related to prospective memory processes. The 1st measures preparatory attentional processes, and the 2nd measures retrospective memory…
Zhang, Dezhi; Li, Shuangyan
2014-01-01
This paper proposes a new model of simultaneous optimization of three-level logistics decisions, for logistics authorities, logistics operators, and logistics users, for regional logistics network with environmental impact consideration. The proposed model addresses the interaction among the three logistics players in a complete competitive logistics service market with CO2 emission charges. We also explicitly incorporate the impacts of the scale economics of the logistics park and the logistics users' demand elasticity into the model. The logistics authorities aim to maximize the total social welfare of the system, considering the demand of green logistics development by two different methods: optimal location of logistics nodes and charging a CO2 emission tax. Logistics operators are assumed to compete with logistics service fare and frequency, while logistics users minimize their own perceived logistics disutility given logistics operators' service fare and frequency. A heuristic algorithm based on the multinomial logit model is presented for the three-level decision model, and a numerical example is given to illustrate the above optimal model and its algorithm. The proposed model provides a useful tool for modeling competitive logistics services and evaluating logistics policies at the strategic level. PMID:24977209
Analysis of multinomial models with unknown index using data augmentation
Royle, J. Andrew; Dorazio, R.M.; Link, W.A.
2007-01-01
Multinomial models with unknown index ('sample size') arise in many practical settings. In practice, Bayesian analysis of such models has proved difficult because the dimension of the parameter space is not fixed, being in some cases a function of the unknown index. We describe a data augmentation approach to the analysis of this class of models that provides for a generic and efficient Bayesian implementation. Under this approach, the data are augmented with all-zero detection histories. The resulting augmented dataset is modeled as a zero-inflated version of the complete-data model where an estimable zero-inflation parameter takes the place of the unknown multinomial index. Interestingly, data augmentation can be justified as being equivalent to imposing a discrete uniform prior on the multinomial index. We provide three examples involving estimating the size of an animal population, estimating the number of diabetes cases in a population using the Rasch model, and the motivating example of estimating the number of species in an animal community with latent probabilities of species occurrence and detection.
J. Richard Hess; Kevin L. Kenney; William A. Smith; Ian Bonner; David J. Muth
2015-04-01
Equipment manufacturers have made rapid improvements in biomass harvesting and handling equipment. These improvements have increased transportation and handling efficiencies due to higher biomass densities and reduced losses. Improvements in grinder efficiencies and capacity have reduced biomass grinding costs. Biomass collection efficiencies (the ratio of biomass collected to the amount available in the field) as high as 75% for crop residues and greater than 90% for perennial energy crops have also been demonstrated. However, as collection rates increase, the fraction of entrained soil in the biomass increases, and high biomass residue removal rates can violate agronomic sustainability limits. Advancements in quantifying multi-factor sustainability limits to increase removal rate as guided by sustainable residue removal plans, and mitigating soil contamination through targeted removal rates based on soil type and residue type/fraction is allowing the use of new high efficiency harvesting equipment and methods. As another consideration, single pass harvesting and other technologies that improve harvesting costs cause biomass storage moisture management challenges, which challenges are further perturbed by annual variability in biomass moisture content. Monitoring, sampling, simulation, and analysis provide basis for moisture, time, and quality relationships in storage, which has allowed the development of moisture tolerant storage systems and best management processes that combine moisture content and time to accommodate baled storage of wet material based upon “shelf-life.” The key to improving biomass supply logistics costs has been developing the associated agronomic sustainability and biomass quality technologies and processes that allow the implementation of equipment engineering solutions.
A computer program for estimation from incomplete multinomial data
NASA Technical Reports Server (NTRS)
Credeur, K. R.
1978-01-01
Coding is given for maximum likelihood and Bayesian estimation of the vector p of multinomial cell probabilities from incomplete data. Also included is coding to calculate and approximate elements of the posterior mean and covariance matrices. The program is written in FORTRAN 4 language for the Control Data CYBER 170 series digital computer system with network operating system (NOS) 1.1. The program requires approximately 44000 octal locations of core storage. A typical case requires from 72 seconds to 92 seconds on CYBER 175 depending on the value of the prior parameter.
Multinomial tau-leaping method for stochastic kinetic simulations.
Pettigrew, Michel F; Resat, Haluk
2007-02-28
We introduce the multinomial tau-leaping (MtauL) method for general reaction networks with multichannel reactant dependencies. The MtauL method is an extension of the binomial tau-leaping method where efficiency is improved in several ways. First, tau-leaping steps are determined simply and efficiently using a priori information and Poisson distribution-based estimates of expectation values for reaction numbers over a tentative tau-leaping step. Second, networks are partitioned into closed groups of reactions and corresponding reactants in which no group reactant set is found in any other group. Third, product formation is factored into upper-bound estimation of the number of times a particular reaction occurs. Together, these features allow larger time steps where the numbers of reactions occurring simultaneously in a multichannel manner are estimated accurately using a multinomial distribution. Furthermore, we develop a simple procedure that places a specific upper bound on the total reaction number to ensure non-negativity of species populations over a single multiple-reaction step. Using two disparate test case problems involving cellular processes--epidermal growth factor receptor signaling and a lactose operon model--we show that the tau-leaping based methods such as the MtauL algorithm can significantly reduce the number of simulation steps thus increasing the numerical efficiency over the exact stochastic simulation algorithm by orders of magnitude. PMID:17343434
Multinomial tau-leaping method for stochastic kinetic simulations
NASA Astrophysics Data System (ADS)
Pettigrew, Michel F.; Resat, Haluk
2007-02-01
We introduce the multinomial tau-leaping (MτL) method for general reaction networks with multichannel reactant dependencies. The MτL method is an extension of the binomial tau-leaping method where efficiency is improved in several ways. First, τ-leaping steps are determined simply and efficiently using a priori information and Poisson distribution-based estimates of expectation values for reaction numbers over a tentative τ-leaping step. Second, networks are partitioned into closed groups of reactions and corresponding reactants in which no group reactant set is found in any other group. Third, product formation is factored into upper-bound estimation of the number of times a particular reaction occurs. Together, these features allow larger time steps where the numbers of reactions occurring simultaneously in a multichannel manner are estimated accurately using a multinomial distribution. Furthermore, we develop a simple procedure that places a specific upper bound on the total reaction number to ensure non-negativity of species populations over a single multiple-reaction step. Using two disparate test case problems involving cellular processes—epidermal growth factor receptor signaling and a lactose operon model—we show that the τ-leaping based methods such as the MτL algorithm can significantly reduce the number of simulation steps thus increasing the numerical efficiency over the exact stochastic simulation algorithm by orders of magnitude.
Reis-Santos, Barbara; Gomes, Teresa; Horta, Bernardo Lessa; Maciel, Ethel Leonor Noia
2013-01-01
OBJECTIVE: To analyze the association between clinical/epidemiological characteristics and outcomes of tuberculosis treatment in patients with concomitant tuberculosis and chronic kidney disease (CKD) in Brazil. METHODS: We used the Brazilian Ministry of Health National Case Registry Database to identify patients with tuberculosis and CKD, treated between 2007 and 2011. The tuberculosis treatment outcomes were compared with epidemiological and clinical characteristics of the subjects using a hierarchical multinomial logistic regression model, in which cure was the reference outcome. RESULTS: The prevalence of CKD among patients with tuberculosis was 0.4% (95% CI: 0.37-0.42%). The sample comprised 1,077 subjects. The outcomes were cure, in 58%; treatment abandonment, in 7%; death from tuberculosis, in 13%; and death from other causes, in 22%. The characteristics that differentiated the ORs for treatment abandonment or death were age; alcoholism; AIDS; previous noncompliance with treatment; transfer to another facility; suspected tuberculosis on chest X-ray; positive results in the first smear microscopy; and indications for/use of directly observed treatment, short-course strategy. CONCLUSIONS: Our data indicate the importance of sociodemographic characteristics for the diagnosis of tuberculosis in patients with CKD and underscore the need for tuberculosis control strategies targeting patients with chronic noncommunicable diseases, such as CKD. PMID:24310632
NML computation algorithms for tree-structured multinomial Bayesian networks.
Kontkanen, Petri; Wettig, Hannes; Myllymäki, Petri
2007-01-01
Typical problems in bioinformatics involve large discrete datasets. Therefore, in order to apply statistical methods in such domains, it is important to develop efficient algorithms suitable for discrete data. The minimum description length (MDL) principle is a theoretically well-founded, general framework for performing statistical inference. The mathematical formalization of MDL is based on the normalized maximum likelihood (NML) distribution, which has several desirable theoretical properties. In the case of discrete data, straightforward computation of the NML distribution requires exponential time with respect to the sample size, since the definition involves a sum over all the possible data samples of a fixed size. In this paper, we first review some existing algorithms for efficient NML computation in the case of multinomial and naive Bayes model families. Then we proceed by extending these algorithms to more complex, tree-structured Bayesian networks. PMID:18382603
Pricing Asian options using moment matching on a multinomial lattice
NASA Astrophysics Data System (ADS)
Ogutu, Carolyne; Lundengârd, Karl; Silvestrov, Sergei; Weke, Patrick
2014-12-01
Pricing Asian options is often done using bi- or trinomial lattice methods. Here some results for generalizing these methods to lattices with more nodes are presented. We consider Asian option pricing on a lattice where the underlying asset follows Merton-Bates jump-diffusion model and describe the construction of a lattice using the moment matching technique which results in an equation system described by a rectangular Vandermonde matrix. The system is solved using the explicit expression for the inverse of the Vandermonde matrix and some restrictions on the jump sizes of the lattice and the distribution of moments are identified. The consequences of these restrictions for the suitability of the multinomial lattice methods are also discussed.
Multinomial pattern matching for high range resolution radar profiles
NASA Astrophysics Data System (ADS)
Koudelka, Melissa L.; Richards, John A.; Koch, Mark W.
2007-04-01
Airborne ground moving-target indication (GMTI) radar can track moving vehicles at large standoff distances. Unfortunately, trajectories from multiple vehicles can become kinematically ambiguous, resulting in confusion between a target vehicle of interest and other vehicles. We propose the use of high range resolution (HRR) radar profiles and multinomial pattern matching (MPM) for target fingerprinting and track stitching to overcome kinematic ambiguities. Sandia's MPM algorithm is a robust template-based identification algorithm that has been applied successfully to various target recognition problems. MPM utilizes a quantile transformation to map target intensity samples to a small number of grayscale values, or quantiles. The algorithm relies on a statistical characterization of the multinomial distribution of the sample-by-sample intensity values for target profiles. The quantile transformation and statistical characterization procedures are extremely well suited to a robust representation of targets for HRR profiles: they are invariant to sensor calibration, robust to target signature variations, and lend themselves to efficient matching algorithms. In typical HRR tracking applications, target fingerprints must be initiated on the fly from a limited number of HRR profiles. Data may accumulate indefinitely as vehicles are tracked, and their templates must be continually updated without becoming unbounded in size or complexity. To address this need, an incrementally updated version of MPM has been developed. This implementation of MPM incorporates individual HRR profiles as they become available, and fuses data from multiple aspect angles for a given target to aid in track stitching. This paper provides a description of the incrementally updated version of MPM.
GAM & RF for 3D mapping of multinomial peat properties.
NASA Astrophysics Data System (ADS)
Poggio, Laura; Gimona, Alessandro; Aalders, Inge; Morrice, Jane; Hough, Rupert
2013-04-01
Different statistical methods have been proposed for fitting the empirical quantitative function linking the soil information to the scorpan factors, while taking into account the spatial structure of the data . Regression kriging extends the methods of kriging and co-kriging and it has been further extended by the use of GAMs (Generalized Additive Models) with the estimation of uncertainty. When multinomial data are modelled, advanced non-parametric methods, such as CART (Classification and Regression Tree), can be used. CARTs have been used widely to estimate soil properties. Bagging trees and Random Forest (RF) approaches have among the best performances among CART methods. CARTs have been used in DSM applications, While RF have often been used in ecological modelling, fewer examples exist in DSM, such as soil erosion occurrence, soil types prediction and soil organic carbon content. In this paper we propose a methodology to map multinomial peat properties in 3D space with a combination of GAMs and RF. The methodology was applied to the humification (according to the VonPost classification) classes in a bog (18 km2) in the north-east of Scotland. A large survey campaign was carried out in 1955 and humification information were collected at 125 points. In order to integrate the information from the GAM in the RT, a series of binary GAMs were fitted using DEM-derived information as covariates. The binary GAMs were fitted assigning 1 if the class considered was present at the location, 0 if the class considered was absent. The probability predictions resulting from the binary GAMs, were included in the pool of covariates used for the RT together with other ancillary covariates. The model diagnostics had a fair to good agreement between measured and modelled values (K statistics). The probability predictions resulting from the binary GAMs proved to be important variables, increasing the agreement of the model. The obtained spatial distribution of values on the
Using a multinomial tree model for detecting mixtures in perceptual detection
Chechile, Richard A.
2014-01-01
In the area of memory research there have been two rival approaches for memory measurement—signal detection theory (SDT) and multinomial processing trees (MPT). Both approaches provide measures for the quality of the memory representation, and both approaches provide for corrections for response bias. In recent years there has been a strong case advanced for the MPT approach because of the finding of stochastic mixtures on both target-present and target-absent tests. In this paper a case is made that perceptual detection, like memory recognition, involves a mixture of processes that are readily represented as a MPT model. The Chechile (2004) 6P memory measurement model is modified in order to apply to the case of perceptual detection. This new MPT model is called the Perceptual Detection (PD) model. The properties of the PD model are developed, and the model is applied to some existing data of a radiologist examining CT scans. The PD model brings out novel features that were absent from a standard SDT analysis. Also the topic of optimal parameter estimation on an individual-observer basis is explored with Monte Carlo simulations. These simulations reveal that the mean of the Bayesian posterior distribution is a more accurate estimator than the corresponding maximum likelihood estimator (MLE). Monte Carlo simulations also indicate that model estimates based on only the data from an individual observer can be improved upon (in the sense of being more accurate) by an adjustment that takes into account the parameter estimate based on the data pooled across all the observers. The adjustment of the estimate for an individual is discussed as an analogous statistical effect to the improvement over the individual MLE demonstrated by the James–Stein shrinkage estimator in the case of the multiple-group normal model. PMID:25018741
NASA Technical Reports Server (NTRS)
Tellado, Joseph
2014-01-01
The presentation contains a status of KSC ISS Logistics Operations. It basically presents current top level ISS Logistics tasks being conducted at KSC, current International Partner activities, hardware processing flow focussing on late Stow operations, list of KSC Logistics POC's, and a backup list of Logistics launch site services. This presentation is being given at the annual International Space Station (ISS) Multi-lateral Logistics Maintenance Control Panel meeting to be held in Turin, Italy during the week of May 13-16. The presentatiuon content doesn't contain any potential lessons learned.
Packaging for logistical support
NASA Astrophysics Data System (ADS)
Twede, Diana; Hughes, Harold
Logistical packaging is conducted to furnish protection, utility, and communication for elements of a logistical system. Once the functional requirements of space logistical support packaging have been identified, decision-makers have a reasonable basis on which to compare package alternatives. Flexible packages may be found, for example, to provide adequate protection and superior utility to that of rigid packages requiring greater storage and postuse waste volumes.
Burgette, Lane F.; Reiter, Jerome P.
2013-01-01
Multinomial outcomes with many levels can be challenging to model. Information typically accrues slowly with increasing sample size, yet the parameter space expands rapidly with additional covariates. Shrinking all regression parameters towards zero, as often done in models of continuous or binary response variables, is unsatisfactory, since setting parameters equal to zero in multinomial models does not necessarily imply “no effect.” We propose an approach to modeling multinomial outcomes with many levels based on a Bayesian multinomial probit (MNP) model and a multiple shrinkage prior distribution for the regression parameters. The prior distribution encourages the MNP regression parameters to shrink toward a number of learned locations, thereby substantially reducing the dimension of the parameter space. Using simulated data, we compare the predictive performance of this model against two other recently-proposed methods for big multinomial models. The results suggest that the fully Bayesian, multiple shrinkage approach can outperform these other methods. We apply the multiple shrinkage MNP to simulating replacement values for areal identifiers, e.g., census tract indicators, in order to protect data confidentiality in public use datasets. PMID:24358073
Burgette, Lane F; Reiter, Jerome P
2013-06-01
Multinomial outcomes with many levels can be challenging to model. Information typically accrues slowly with increasing sample size, yet the parameter space expands rapidly with additional covariates. Shrinking all regression parameters towards zero, as often done in models of continuous or binary response variables, is unsatisfactory, since setting parameters equal to zero in multinomial models does not necessarily imply "no effect." We propose an approach to modeling multinomial outcomes with many levels based on a Bayesian multinomial probit (MNP) model and a multiple shrinkage prior distribution for the regression parameters. The prior distribution encourages the MNP regression parameters to shrink toward a number of learned locations, thereby substantially reducing the dimension of the parameter space. Using simulated data, we compare the predictive performance of this model against two other recently-proposed methods for big multinomial models. The results suggest that the fully Bayesian, multiple shrinkage approach can outperform these other methods. We apply the multiple shrinkage MNP to simulating replacement values for areal identifiers, e.g., census tract indicators, in order to protect data confidentiality in public use datasets. PMID:24358073
Significant Improvements to LOGIST.
ERIC Educational Resources Information Center
Wingersky, Marilyn S.
The computer program LOGIST (Wingersky, Patrick, and Lord, 1988) estimates the item parameters and the examinee's abilities for Birnbaum's three-parameter logistic item response theory model using Newton's method for solving the joint maximum likelihood equations. In 1989, Martha Stocking discovered a problem with this procedure in that when the…
Pei, Qinglin; Zuleger, Cindy L; Macklin, Michael D; Albertini, Mark R; Newton, Michael A
2014-01-01
Immunological experiments that record primary molecular sequences of T-cell receptors produce moderate to high-dimensional categorical data, some of which may be subject to extra-multinomial variation caused by technical constraints of cell-based assays. Motivated by such experiments in melanoma research, we develop a statistical procedure for testing the equality of two discrete populations, where one population delivers multinomial data and the other is subject to a specific form of overdispersion. The procedure computes a conditional-predictive p-value by splitting the data set into two, obtaining a predictive distribution for one piece given the other, and using the observed predictive ordinate to generate a p-value. The procedure has a simple interpretation, requires fewer modeling assumptions than would be required of a fully Bayesian analysis, and has reasonable operating characteristics as evidenced empirically and by asymptotic analysis. PMID:24096387
Estimation from incomplete multinomial data. Ph.D. Thesis - Harvard Univ.
NASA Technical Reports Server (NTRS)
Credeur, K. R.
1978-01-01
The vector of multinomial cell probabilities was estimated from incomplete data, incomplete in that it contains partially classified observations. Each such partially classified observation was observed to fall in one of two or more selected categories but was not classified further into a single category. The data were assumed to be incomplete at random. The estimation criterion was minimization of risk for quadratic loss. The estimators were the classical maximum likelihood estimate, the Bayesian posterior mode, and the posterior mean. An approximation was developed for the posterior mean. The Dirichlet, the conjugate prior for the multinomial distribution, was assumed for the prior distribution.
NASA Astrophysics Data System (ADS)
Chang, Yoon S.; Oh, Chang H.
Nowadays, environmental management becomes a critical business consideration for companies to survive from many regulations and tough business requirements. Most of world-leading companies are now aware that environment friendly technology and management are critical to the sustainable growth of the company. The environment market has seen continuous growth marking 532B in 2000, and 590B in 2004. This growth rate is expected to grow to 700B in 2010. It is not hard to see the environment-friendly efforts in almost all aspects of business operations. Such trends can be easily found in logistics area. Green logistics aims to make environmental friendly decisions throughout a product lifecycle. Therefore for the success of green logistics, it is critical to have real time tracking capability on the product throughout the product lifecycle and smart solution service architecture. In this chapter, we introduce an RFID based green logistics solution and service.
A General Family of Limited Information Goodness-of-Fit Statistics for Multinomial Data
ERIC Educational Resources Information Center
Joe, Harry; Maydeu-Olivares, Alberto
2010-01-01
Maydeu-Olivares and Joe (J. Am. Stat. Assoc. 100:1009-1020, "2005"; Psychometrika 71:713-732, "2006") introduced classes of chi-square tests for (sparse) multidimensional multinomial data based on low-order marginal proportions. Our extension provides general conditions under which quadratic forms in linear functions of cell residuals are…
NASA Astrophysics Data System (ADS)
Gözükirmizi, Coşar; Demiralp, Metin
2015-12-01
This paper serves as a tutorial for the implementation of probabilistic evolution theory for the solution of initial value problem of ordinary differential equation sets with second degree multinomial right hand side functions. It also involves certain original ideas in technicality level and some novel observations.
ERIC Educational Resources Information Center
Smith, Rebekah E.; Bayen, Ute J.
2006-01-01
Event-based prospective memory involves remembering to perform an action in response to a particular future event. Normal younger and older adults performed event-based prospective memory tasks in 2 experiments. The authors applied a formal multinomial processing tree model of prospective memory (Smith & Bayen, 2004) to disentangle age differences…
Logistics planning for phased programs.
NASA Technical Reports Server (NTRS)
Cook, W. H.
1973-01-01
It is pointed out that the proper and early integration of logistics planning into the phased program planning process will drastically reduce these logistics costs. Phased project planning is a phased approach to the planning, approval, and conduct of major research and development activity. A progressive build-up of knowledge of all aspects of the program is provided. Elements of logistics are discussed together with aspects of integrated logistics support, logistics program planning, and logistics activities for phased programs. Continuing logistics support can only be assured if there is a comprehensive sequential listing of all logistics activities tied to the program schedule and a real-time inventory of assets.
Practical Session: Logistic Regression
NASA Astrophysics Data System (ADS)
Clausel, M.; Grégoire, G.
2014-12-01
An exercise is proposed to illustrate the logistic regression. One investigates the different risk factors in the apparition of coronary heart disease. It has been proposed in Chapter 5 of the book of D.G. Kleinbaum and M. Klein, "Logistic Regression", Statistics for Biology and Health, Springer Science Business Media, LLC (2010) and also by D. Chessel and A.B. Dufour in Lyon 1 (see Sect. 6 of http://pbil.univ-lyon1.fr/R/pdf/tdr341.pdf). This example is based on data given in the file evans.txt coming from http://www.sph.emory.edu/dkleinb/logreg3.htm#data.
Brody, Gene H.; Yu, Tianyi; Chen, Yi-fu; Kogan, Steven M.; Evans, Gary W.; Beach, Steven R. H.; Windle, Michael; Simons, Ronald L.; Gerrard, Meg; Gibbons, Frederick X.; Philibert, Robert A.
2012-01-01
The health disparities literature identified a common pattern among middle-aged African Americans that includes high rates of chronic disease along with low rates of psychiatric disorders despite exposure to high levels of cumulative SES risk. The current study was designed to test hypotheses about the developmental precursors to this pattern. Hypotheses were tested with a representative sample of 443 African American youths living in the rural South. Cumulative SES risk and protective processes were assessed at 11-13 years; psychological adjustment was assessed at ages 14-18 years; genotyping at the 5-HTTLPR was conducted at age 16 years; and allostatic load (AL) was assessed at age 19 years. A Latent Profile Analysis identified 5 profiles that evinced distinct patterns of SES risk, AL, and psychological adjustment, with 2 relatively large profiles designated as focal profiles: a physical health vulnerability profile characterized by high SES risk/high AL/low adjustment problems, and a resilient profile characterized by high SES risk/low AL/low adjustment problems. The physical health vulnerability profile mirrored the pattern found in the adult health disparities literature. Multinomial logistic regression analyses indicated that carrying an s allele at the 5-HTTLPR and receiving less peer support distinguished the physical health vulnerability profile from the resilient profile. Protective parenting and planful self-regulation distinguished both focal profiles from the other 3 profiles. The results suggest the public health importance of preventive interventions that enhance coping and reduce the effects of stress across childhood and adolescence. PMID:22709130
A multinomial maximum likelihood program /MUNOML/. [in modeling sensory and decision phenomena
NASA Technical Reports Server (NTRS)
Curry, R. E.
1975-01-01
A multinomial maximum likelihood program (MUNOML) for signal detection and for behavior models is discussed. It is found to be useful in day to day operation since it provides maximum flexibility with minimum duplicated effort. It has excellent convergence qualities and rarely goes beyond 10 iterations. A library of subroutines is being collected for use with MUNOML, including subroutines for a successive categories model and for signal detectability models.
Past epidemiologic studies suggest maternal ambient air pollution exposure during critical periods of the pregnancy is associated with fetal development. We introduce a multinomial probit model that allows for the joint identification of susceptible daily periods during the pregn...
Computing measures of explained variation for logistic regression models.
Mittlböck, M; Schemper, M
1999-01-01
The proportion of explained variation (R2) is frequently used in the general linear model but in logistic regression no standard definition of R2 exists. We present a SAS macro which calculates two R2-measures based on Pearson and on deviance residuals for logistic regression. Also, adjusted versions for both measures are given, which should prevent the inflation of R2 in small samples. PMID:10195643
American Psychiatric Association. Diagnostic and statistical manual of mental disorders. 5th ed. Arlington, Va: American Psychiatric Publishing. 2013. Powell AD. Grief, bereavement, and adjustment disorders. In: Stern TA, Rosenbaum ...
Killeen, Peter R
2015-07-01
The generalized matching law (GML) is reconstructed as a logistic regression equation that privileges no particular value of the sensitivity parameter, a. That value will often approach 1 due to the feedback that drives switching that is intrinsic to most concurrent schedules. A model of that feedback reproduced some features of concurrent data. The GML is a law only in the strained sense that any equation that maps data is a law. The machine under the hood of matching is in all likelihood the very law that was displaced by the Matching Law. It is now time to return the Law of Effect to centrality in our science. PMID:25988932
Steganalysis using logistic regression
NASA Astrophysics Data System (ADS)
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.
De Valpine, Perry; Harmon-Threatt, Alexandra N
2013-12-01
Many ecological studies investigate how organisms use resources, such as habitats or foods, in relation to availability or other variables. Related statistical problems include analysis of proportions of species or genotypes in a community or population. These require statistical modeling of compositional count data: data on relative proportions of each category collected as counts. Common methods for analyzing compositional count data lack one or more important considerations. Some methods lack explicit accommodation of count data, dealing instead with proportions. Others do not handle between-sample heterogeneity for overdispersed data. Yet others do not allow general types of relationships between explanatory variables and resource use. All three components have been combined in a Bayesian framework, but for frequentist hypothesis tests and AIC model selection, maximum-likelihood estimation is needed. Here we propose the Dirichlet-multinomial distribution to accommodate overdispersed compositional count data. This approach can be used flexibly in combination with explanatory models, but the only correlations among compositional proportions that it can accommodate are the negative correlations due to the fact that proportions must sum to 1. Many existing models can be generalized to use the Dirichlet-multinomial distribution for residual variation, and the flexibility of the approach allows new hypotheses that have often not been considered in resource preference analysis, including that availability has no relation to use. We also highlight a new design for resource use studies, with multiple individual-use data sets from each of multiple sites, with different explanatory data for each site. We illustrate the approach with three examples. For two previously published habitat use data sets, we support the original conclusions and show that use is not unrelated to availability. For a data set of pollen collected by multiple bees from each of two sites, pollen use
Bao, J Y
1991-04-01
The commonly used microforceps have a much greater opening distance and spring resistance than needed. A piece of plastic ring or rubber band can be used to adjust the opening distance and reduce most of the spring resistance, making the user feel more comfortable and less fatigued. PMID:2051437
Landscape effects on diets of two canids in Northwestern Texas: A multinomial modeling approach
Lemons, P.R.; Sedinger, J.S.; Herzog, M.P.; Gipson, P.S.; Gilliland, R.L.
2010-01-01
Analyses of feces, stomach contents, and regurgitated pellets are common techniques for assessing diets of vertebrates and typically contain more than 1 food item per sampling unit. When analyzed, these individual food items have traditionally been treated as independent, which represents pseudoreplication. When food types are recorded as present or absent, these samples can be treated as multinomial vectors of food items, with each vector representing 1 realization of a possible diet. We suggest such data have a similar structure to capture histories for closed-capture, capturemarkrecapture data. To assess the effects of landscapes and presence of a potential competitor, we used closed-capture models implemented in program MARK into analyze diet data generated from feces of swift foxes (Vulpes velox) and coyotes (Canis latrans) in northwestern Texas. The best models of diet contained season and location for both swift foxes and coyotes, but year accounted for less variation, suggesting that landscape type is an important predictor of diets of both species. Models containing the effect of coyote reduction were not competitive (??QAICc 53.6685), consistent with the hypothesis that presence of coyotes did not influence diet of swift foxes. Our findings suggest that landscape type may have important influences on diets of both species. We believe that multinomial models represent an effective approach to assess hypotheses when diet studies have a data structure similar to ours. ?? 2010 American Society of Mammalogists.
Uncovering a latent multinomial: Analysis of mark-recapture data with misidentification
Link, W.A.; Yoshizaki, J.; Bailey, L.L.; Pollock, K.H.
2010-01-01
Natural tags based on DNA fingerprints or natural features of animals are now becoming very widely used in wildlife population biology. However, classic capture-recapture models do not allow for misidentification of animals which is a potentially very serious problem with natural tags. Statistical analysis of misidentification processes is extremely difficult using traditional likelihood methods but is easily handled using Bayesian methods. We present a general framework for Bayesian analysis of categorical data arising from a latent multinomial distribution. Although our work is motivated by a specific model for misidentification in closed population capture-recapture analyses, with crucial assumptions which may not always be appropriate, the methods we develop extend naturally to a variety of other models with similar structure. Suppose that observed frequencies f are a known linear transformation f = A???x of a latent multinomial variable x with cell probability vector ?? = ??(??). Given that full conditional distributions [?? | x] can be sampled, implementation of Gibbs sampling requires only that we can sample from the full conditional distribution [x | f, ??], which is made possible by knowledge of the null space of A???. We illustrate the approach using two data sets with individual misidentification, one simulated, the other summarizing recapture data for salamanders based on natural marks. ?? 2009, The International Biometric Society.
Uncovering a Latent Multinomial: Analysis of Mark-Recapture Data with Misidentification
Link, W.A.; Yoshizaki, J.; Bailey, L.L.; Pollock, K.H.
2009-01-01
Natural tags based on DNA fingerprints or natural features of animals are now becoming very widely used in wildlife population biology. However, classic capture-recapture models do not allow for misidentification of animals which is a potentially very serious problem with natural tags. Statistical analysis of misidentification processes is extremely difficult using traditional likelihood methods but is easily handled using Bayesian methods. We present a general framework for Bayesian analysis of categorical data arising from a latent multinomial distribution. Although our work is motivated by a specific model for misidentification in closed population capture-recapture analyses, with crucial assumptions which may not always be appropriate, the methods we develop extend naturally to a variety of other models with similar structure. Suppose that observed frequencies f are a known linear transformation f=A'x of a latent multinomial variable x with cell probability vector pi= pi(theta). Given that full conditional distributions [theta | x] can be sampled, implementation of Gibbs sampling requires only that we can sample from the full conditional distribution [x | f, theta], which is made possible by knowledge of the null space of A'. We illustrate the approach using two data sets with individual misidentification, one simulated, the other summarizing recapture data for salamanders based on natural marks.
Space Shuttle operational logistics plan
NASA Technical Reports Server (NTRS)
Botts, J. W.
1983-01-01
The Kennedy Space Center plan for logistics to support Space Shuttle Operations and to establish the related policies, requirements, and responsibilities are described. The Directorate of Shuttle Management and Operations logistics responsibilities required by the Kennedy Organizational Manual, and the self-sufficiency contracting concept are implemented. The Space Shuttle Program Level 1 and Level 2 logistics policies and requirements applicable to KSC that are presented in HQ NASA and Johnson Space Center directives are also implemented.
Jieke theory and logistic model
Cao, H.; Feng, G.
1996-06-01
What is a shell or a JIEKE (in Chinese) is introduced firstly, jieke is a sort of system boundary. From the concept of jieke theory, a new logistic model which takes account of the switch effect of the jieke is suggested. The model is analyzed and nonlinear mapping of the model is made. The results show the feature of the switch logistic model far differ from the original logistic model. {copyright} {ital 1996 American Institute of Physics.}
Harry, Herbert H.
1989-01-01
Apparatus and method for the adjustment and alignment of shafts in high power devices. A plurality of adjacent rotatable angled cylinders are positioned between a base and the shaft to be aligned which when rotated introduce an axial offset. The apparatus is electrically conductive and constructed of a structurally rigid material. The angled cylinders allow the shaft such as the center conductor in a pulse line machine to be offset in any desired alignment position within the range of the apparatus.
Technical issues: logistics. AAMC.
Stillman, P L
1993-06-01
The author states that she became interested in standardized patients (SPs) around 20 years ago as a means of developing a more uniform and effective way to provide instruction and evaluation of basic clinical skills. She reflects upon in detail: (1) the logistics of using SPs in teaching; (2) how SPs are used in assessment; (3) what aspects of performance SPs can be trained to record and evaluate; (4) issues concerning checklists; (5) evaluation of interviewing skills; (6) evaluation of written communication skills; (7) importance of defining what is being tested; (8) various kinds and uses of inter-station exercises and problems of scoring them; (9) case development and the various sources for case material; (10) ways to generate scores; (11) selecting and training SPs; (12) role of the faculty and primary importance of bedside training with real patients; and (13) pros and cons of national versus single-school efforts to use SPs. She concludes by cautioning that further research must be done before SPs can be used for high-stakes certifying and licensing examinations. PMID:8507311
Transfer Learning Based on Logistic Regression
NASA Astrophysics Data System (ADS)
Paul, A.; Rottensteiner, F.; Heipke, C.
2015-08-01
In this paper we address the problem of classification of remote sensing images in the framework of transfer learning with a focus on domain adaptation. The main novel contribution is a method for transductive transfer learning in remote sensing on the basis of logistic regression. Logistic regression is a discriminative probabilistic classifier of low computational complexity, which can deal with multiclass problems. This research area deals with methods that solve problems in which labelled training data sets are assumed to be available only for a source domain, while classification is needed in the target domain with different, yet related characteristics. Classification takes place with a model of weight coefficients for hyperplanes which separate features in the transformed feature space. In term of logistic regression, our domain adaptation method adjusts the model parameters by iterative labelling of the target test data set. These labelled data features are iteratively added to the current training set which, at the beginning, only contains source features and, simultaneously, a number of source features are deleted from the current training set. Experimental results based on a test series with synthetic and real data constitutes a first proof-of-concept of the proposed method.
A note on Verhulst's logistic equation and related logistic maps
NASA Astrophysics Data System (ADS)
Ranferi Gutiérrez, M.; Reyes, M. A.; Rosu, H. C.
2010-05-01
We consider the Verhulst logistic equation and a couple of forms of the corresponding logistic maps. For the case of the logistic equation we show that using the general Riccati solution only changes the initial conditions of the equation. Next, we consider two forms of corresponding logistic maps reporting the following results. For the map xn + 1 = rxn(1 - xn) we propose a new way to write the solution for r = -2 which allows better precision of the iterative terms, while for the map xn + 1 - xn = rxn(1 - xn + 1) we show that it behaves identically to the logistic equation from the standpoint of the general Riccati solution, which is also provided herein for any value of the parameter r.
Logistic Regression: Concept and Application
ERIC Educational Resources Information Center
Cokluk, Omay
2010-01-01
The main focus of logistic regression analysis is classification of individuals in different groups. The aim of the present study is to explain basic concepts and processes of binary logistic regression analysis intended to determine the combination of independent variables which best explain the membership in certain groups called dichotomous…
A multinomial modeling analysis of the mnemonic benefits of bizarre imagery.
Riefer, D M; Rouder, J N
1992-11-01
A series of experiments was conducted to explore the cognitive processes that mediate the bizarreness effect, that is, the finding that bizarre or unusual imagery is recalled better than common imagery. In all experiments, subjects were presented with noun pairs that were embedded within bizarre or common sentences in a mixed-list design. None of the experiments produced a bizarreness effect for cued recall; however, for two of the experiments, the bizarre noun pairs were remembered significantly better than the common pairs for free recall. To determine if these differences were due to the storage or retrieval of the items, a multinomial model for the analysis of imagery mediation in paired-associate learning was developed and applied to the data from the experiments. The model revealed that bizarre sentences benefited the retrieval of the noun pairs but not their storage within memory. The empirical and modeling results are discussed relative to previous findings and theories on the bizarreness effect. PMID:1435263
NASA Astrophysics Data System (ADS)
Gözükirmizi, Coşar; Demiralp, Metin
2014-10-01
Constancy adding space extension is a technique to convert ODE of the form ẋ(t) = F0+F1x(t)+F2x(t)⊗2 to form ṡ = G1s+G2P-1s⊗2. There are arbitrary parameters in the representation. These parameters may be utilized in such a way that G1 becomes a multiple of identity matrix. Then, using a function transformation it is possible to obtain the form ds˜(u)/du = G2P-1s˜(u)⊗2. Therefore, a new universal representation for ODEs with second degree multinomial right hand side functions is proposed. There are remaining arbitrary parameters of the space extension and this paper also focuses on how to choose them.
MPTinR: analysis of multinomial processing tree models in R.
Singmann, Henrik; Kellen, David
2013-06-01
We introduce MPTinR, a software package developed for the analysis of multinomial processing tree (MPT) models. MPT models represent a prominent class of cognitive measurement models for categorical data with applications in a wide variety of fields. MPTinR is the first software for the analysis of MPT models in the statistical programming language R, providing a modeling framework that is more flexible than standalone software packages. MPTinR also introduces important features such as (1) the ability to calculate the Fisher information approximation measure of model complexity for MPT models, (2) the ability to fit models for categorical data outside the MPT model class, such as signal detection models, (3) a function for model selection across a set of nested and nonnested candidate models (using several model selection indices), and (4) multicore fitting. MPTinR is available from the Comprehensive R Archive Network at http://cran.r-project.org/web/packages/MPTinR/ . PMID:23344733
A new method for multinomial inference using Dempster-Shafer theory
Lawrence, Earl Christopher; Vander Wiel, Scott; Liu, Chuanhai; Zhang, Jianchun
2009-01-01
A new method for multinomial inference is proposed by representing the cell probabilities as unordered segments on the unit interval and following Dempster-Shafer (DS) theory. The resulting DS posterior is then strengthened to improve symmetry and learning properties with the final posterior model being characterized by a Dirichlet distribution. In addition to computational simplicity, the new model has desirable invariance properties related to category permutations, refinements, and coarsenings. Furthemore, posterior inference on relative probabilities amongst certain cells depends only on data for the cells in question. Finally, the model is quite flexible with regard to parameterization and the range of testable assertions. Comparisons are made to existing methods and illustrated with two examples.
ERIC Educational Resources Information Center
Johnson, Timothy R.; Bolt, Daniel M.
2010-01-01
Multidimensional item response models are usually implemented to model the relationship between item responses and two or more traits of interest. We show how multidimensional multinomial logit item response models can also be used to account for individual differences in response style. This is done by specifying a factor-analytic model for…
ERIC Educational Resources Information Center
Olkin, Ingram
Bounds for the tails of Dirichlet integrals are established by showing that each integral as a function of the limits is a Schur function. In particular, it is shown how these bounds apply to the simultaneous analysis of variance test and to the multinomial distribution. (Author)
Fungible weights in logistic regression.
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 PMID:26651981
Tailored logistics: the next advantage.
Fuller, J B; O'Conor, J; Rawlinson, R
1993-01-01
How many top executives have ever visited with managers who move materials from the factory to the store? How many still reduce the costs of logistics to the rent of warehouses and the fees charged by common carriers? To judge by hours of senior management attention, logistics problems do not rank high. But logistics have the potential to become the next governing element of strategy. Whether they know it or not, senior managers of every retail store and diversified manufacturing company compete in logistically distinct businesses. Customer needs vary, and companies can tailor their logistics systems to serve their customers better and more profitably. Companies do not create value for customers and sustainable advantage for themselves merely by offering varieties of goods. Rather, they offer goods in distinct ways. A particular can of Coca-Cola, for example, might be a can of Coca-Cola going to a vending machine, or a can of Coca-Cola that comes with billing services. There is a fortune buried in this distinction. The goal of logistics strategy is building distinct approaches to distinct groups of customers. The first step is organizing a cross-functional team to proceed through the following steps: segmenting customers according to purchase criteria, establishing different standards of service for different customer segments, tailoring logistics pipelines to support each segment, and creating economics of scale to determine which assets can be shared among various pipelines. The goal of establishing logistically distinct businesses is familiar: improved knowledge of customers and improved means of satisfying them. PMID:10126157
NASA Space Rocket Logistics Challenges
NASA Technical Reports Server (NTRS)
Neeley, James R.; Jones, James V.; Watson, Michael D.; Bramon, Christopher J.; Inman, Sharon K.; Tuttle, Loraine
2014-01-01
The Space Launch System (SLS) is the new NASA heavy lift launch vehicle and is scheduled for its first mission in 2017. The goal of the first mission, which will be uncrewed, is to demonstrate the integrated system performance of the SLS rocket and spacecraft before a crewed flight in 2021. SLS has many of the same logistics challenges as any other large scale program. Common logistics concerns for SLS include integration of discreet programs geographically separated, multiple prime contractors with distinct and different goals, schedule pressures and funding constraints. However, SLS also faces unique challenges. The new program is a confluence of new hardware and heritage, with heritage hardware constituting seventy-five percent of the program. This unique approach to design makes logistics concerns such as commonality especially problematic. Additionally, a very low manifest rate of one flight every four years makes logistics comparatively expensive. That, along with the SLS architecture being developed using a block upgrade evolutionary approach, exacerbates long-range planning for supportability considerations. These common and unique logistics challenges must be clearly identified and tackled to allow SLS to have a successful program. This paper will address the common and unique challenges facing the SLS programs, along with the analysis and decisions the NASA Logistics engineers are making to mitigate the threats posed by each.
Logistics Management: New trends in the Reverse Logistics
NASA Astrophysics Data System (ADS)
Antonyová, A.; Antony, P.; Soewito, B.
2016-04-01
Present level and quality of the environment are directly dependent on our access to natural resources, as well as their sustainability. In particular production activities and phenomena associated with it have a direct impact on the future of our planet. Recycling process, which in large enterprises often becomes an important and integral part of the production program, is usually in small and medium-sized enterprises problematic. We can specify a few factors, which have direct impact on the development and successful application of the effective reverse logistics system. Find the ways to economically acceptable model of reverse logistics, focusing on converting waste materials for renewable energy, is the task in progress.
Lessons in logistics from Somalia.
Kemball-Cook, D; Stephenson, R
1984-03-01
By February 1981 the refugee relief operation in Somalia was close to breakdown. The Governor of Somalia and the United Nations High Commission for Refugees (UNHCR) contracted the agency CARE to manage the logistics of the operation. By August 1981 over 99 % of food received at Mogadishu was reaching the camps. Here we describe this apparent success, and attempt to diagnose the contributing factors. Chief among these are dynamic leadership, 'systems' management, adaptability of personnel, the use of professional Indian food monitors in the camps, and the support given by the Government. The chief qualification on the success of the operation has been the continued dependency on expatriate expertise. General conclusions are offered relating to the management of logistics in relief operations. The most important conclusion is that there is a prime need for logistics to be centralized in a single organization at the start of major emergencies. We point to the current inadequacy in an international relief system which fails to ensure this, and suggest that a new or existing part of the United Nations family be given a 'brief for in-country logistics' to become a UN Emergency Logistics Office. PMID:20958559
Gordóvil-Merino, Amalia; Guàrdia-Olmos, Joan; Peró-Cebollero, Maribel; de la Fuente-Solanas, Emilia I
2010-04-01
The limitations inherent to classical estimation of the logistic regression models are known. The Bayesian approach in statistical analysis is an alternative to be considered, given that it makes it possible to introduce prior information about the phenomenon under study. The aim of the present work is to analyze binary and multinomial logistic regression simple models estimated by means of a Bayesian approach in comparison to classical estimation. To that effect, Child Attention Deficit Hyperactivity Disorder (ADHD) clinical data were analyzed. The sample included 286 participants of 6-12 years (78% boys, 22% girls) with ADHD positive diagnosis in 86.7% of the cases. The results show a reduction of standard errors associated to the coefficients obtained from the Bayesian analysis, thus bringing a greater stability to the coefficients. Complex models where parameter estimation may be easily compromised could benefit from this advantage. PMID:20524554
Logistic Stick-Breaking Process
Ren, Lu; Du, Lan; Carin, Lawrence; Dunson, David B.
2013-01-01
A logistic stick-breaking process (LSBP) is proposed for non-parametric clustering of general spatially- or temporally-dependent data, imposing the belief that proximate data are more likely to be clustered together. The sticks in the LSBP are realized via multiple logistic regression functions, with shrinkage priors employed to favor contiguous and spatially localized segments. The LSBP is also extended for the simultaneous processing of multiple data sets, yielding a hierarchical logistic stick-breaking process (H-LSBP). The model parameters (atoms) within the H-LSBP are shared across the multiple learning tasks. Efficient variational Bayesian inference is derived, and comparisons are made to related techniques in the literature. Experimental analysis is performed for audio waveforms and images, and it is demonstrated that for segmentation applications the LSBP yields generally homogeneous segments with sharp boundaries. PMID:25258593
Source and destination memory in face-to-face interaction: A multinomial modeling approach.
Fischer, Nele M; Schult, Janette C; Steffens, Melanie C
2015-06-01
Arguing that people are often in doubt concerning to whom they have presented what information, Gopie and MacLeod (2009) introduced a new memory component, destination memory: remembering the destination of output information (i.e., "Who did you tell this to?"). They investigated source (i.e., "Who told you that?") versus destination memory in computer-based imagined interactions. The present study investigated destination memory in real interaction situations. In 2 experiments with mixed-gender (N = 53) versus same-gender (N = 89) groups, source and destination memory were manipulated by creating a setup similar to speed dating. In dyads, participants completed phrase fragments with personal information, taking turns. At recognition, participants decided whether fragments were new or old and, if old, whether they were listened to or spoken and which depicted person was the source or the destination of the information. A multinomial model was used for analyses. Source memory significantly exceeded destination memory, whereas information itself was better remembered in the destination than in the source condition. These findings corroborate the trade-off hypothesis: Context is better remembered in input than in output events, but information itself is better remembered in output than in input events. We discuss the implications of these findings for real-world conversation situations. PMID:25893444
Küpper-Tetzel, Carolina E; Erdfelder, Edgar
2012-01-01
Short-term studies on repeated learning of verbatim material have typically revealed an overall benefit of long lags compared to short lags between repetitions. This has been referred to as the lag effect. On educationally relevant time scales, however, an inverted-U-shaped relation between lag and memory performance is often observed. Recently, Cepeda et al. (2009) showed that the optimal lag for relearning depends heavily on the time interval between the last learning session and the final memory test (i.e., the retention interval; RI). In order to explore the cognitive mechanisms underlying this result in more detail we independently manipulated both the lag and the RI in a 3×2 experimental design and analysed our data using a multinomial processing tree model for free-then-cued-recall data. Our results reveal that the lag effect trends are mainly driven by encoding and maintenance processes rather than by retrieval mechanisms. Our findings have important implications for theories of the lag effect. PMID:22171809
Decomposing retrieval and integration in memory for actions: a multinomial modeling approach.
Steffens, Melanie C; Jelenec, Petra; Mecklenbräuker, Silvia; Thompson, Erin Marie
2006-03-01
Typically, action phrases are recalled better if participants are asked to enact the phrases than if they are just asked to remember them. When investigating which processes constitute this enactment effect a difficulty is that observable effects in standard memory tests are ambiguous because such tests require several processes. In the present article, we introduce a multinomial model that decomposes observable memory performance into a retrieval parameter and a parameter concerning the item-specific processing and integration of an action phrase. These parameters are estimated from free recall and cued recall performance. The model fitted the data of two experiments designed to test it. Experiment 1 demonstrated the basic usefulness of the model by showing expected differences in the integration parameter in the absence of unexpected differences in the retrieval parameter. Experiment 2 extended the conditions under which the model is useful by showing expected differences in the retrieval parameter even in the presence of unexpected differences in the integration parameter. Together, these findings support our theoretical framework according to which enactment generally boosts integration of action phrases, but increases retrieval only for phrases with context cues. PMID:16627356
Class-specific Gaussian-multinomial latent Dirichlet allocation for image annotation
NASA Astrophysics Data System (ADS)
Qian, Zhiming; Zhong, Ping; Wang, Runsheng
2015-12-01
Image annotation has been a challenging problem due to the well-known semantic gap between two heterogeneous information modalities, i.e., the visual modality referring to low-level visual features and the semantic modality referring to high-level human concepts. To bridge the semantic gap, we present an extension of latent Dirichlet allocation (LDA), denoted as class-specific Gaussian-multinomial latent Dirichlet allocation (csGM-LDA), in an effort to simulate the human's visual perception system. An analysis of previous supervised LDA models shows that the topics discovered by generative LDA models are driven by general image regularities rather than the semantic regularities for image annotation. To address this, csGM-LDA is introduced by using class supervision at the level of visual features for multimodal topic modeling. The csGM-LDA model combines the labeling strength of topic supervision with the flexibility of topic discovery, and the modeling problem can be effectively solved by a variational expectation-maximization (EM) algorithm. Moreover, as natural images usually generate an enormous size of high-dimensional data in annotation applications, an efficient descriptor based on Laplacian regularized uncorrelated tensor representation is proposed for explicitly exploiting the manifold structures in the high-order image space. Experimental results on two standard annotation datasets have shown the effectiveness of the proposed method by comparing with several state-of-the-art annotation methods.
A general class of multinomial mixture models for anuran calling survey data
Royle, J. Andrew; Link, W.A.
2005-01-01
We propose a general framework for modeling anuran abundance using data collected from commonly used calling surveys. The data generated from calling surveys are indices of calling intensity (vocalization of males) that do not have a precise link to actual population size and are sensitive to factors that influence anuran behavior. We formulate a model for calling-index data in terms of the maximum potential calling index that could be observed at a site (the 'latent abundance class'), given its underlying breeding population, and we focus attention on estimating the distribution of this latent abundance class. A critical consideration in estimating the latent structure is imperfect detection, which causes the observed abundance index to be less than or equal to the latent abundance class. We specify a multinomial sampling model for the observed abundance index that is conditional on the latent abundance class. Estimation of the latent abundance class distribution is based on the marginal likelihood of the index data, having integrated over the latent class distribution. We apply the proposed modeling framework to data collected as part of the North American Amphibian Monitoring Program (NAAMP).
Model-based Clustering of Categorical Time Series with Multinomial Logit Classification
NASA Astrophysics Data System (ADS)
Frühwirth-Schnatter, Sylvia; Pamminger, Christoph; Winter-Ebmer, Rudolf; Weber, Andrea
2010-09-01
A common problem in many areas of applied statistics is to identify groups of similar time series in a panel of time series. However, distance-based clustering methods cannot easily be extended to time series data, where an appropriate distance-measure is rather difficult to define, particularly for discrete-valued time series. Markov chain clustering, proposed by Pamminger and Frühwirth-Schnatter [6], is an approach for clustering discrete-valued time series obtained by observing a categorical variable with several states. This model-based clustering method is based on finite mixtures of first-order time-homogeneous Markov chain models. In order to further explain group membership we present an extension to the approach of Pamminger and Frühwirth-Schnatter [6] by formulating a probabilistic model for the latent group indicators within the Bayesian classification rule by using a multinomial logit model. The parameters are estimated for a fixed number of clusters within a Bayesian framework using an Markov chain Monte Carlo (MCMC) sampling scheme representing a (full) Gibbs-type sampler which involves only draws from standard distributions. Finally, an application to a panel of Austrian wage mobility data is presented which leads to an interesting segmentation of the Austrian labour market.
Logistics background study: underground mining
Hanslovan, J. J.; Visovsky, R. G.
1982-02-01
Logistical functions that are normally associated with US underground coal mining are investigated and analyzed. These functions imply all activities and services that support the producing sections of the mine. The report provides a better understanding of how these functions impact coal production in terms of time, cost, and safety. Major underground logistics activities are analyzed and include: transportation and personnel, supplies and equipment; transportation of coal and rock; electrical distribution and communications systems; water handling; hydraulics; and ventilation systems. Recommended areas for future research are identified and prioritized.
Continual Improvement in Shuttle Logistics
NASA Technical Reports Server (NTRS)
Flowers, Jean; Schafer, Loraine
1995-01-01
It has been said that Continual Improvement (CI) is difficult to apply to service oriented functions, especially in a government agency such as NASA. However, a constrained budget and increasing requirements are a way of life at NASA Kennedy Space Center (KSC), making it a natural environment for the application of CI tools and techniques. This paper describes how KSC, and specifically the Space Shuttle Logistics Project, a key contributor to KSC's mission, has embraced the CI management approach as a means of achieving its strategic goals and objectives. An overview of how the KSC Space Shuttle Logistics Project has structured its CI effort and examples of some of the initiatives are provided.
Chen, Cong; Zhang, Guohui; Tarefder, Rafiqul; Ma, Jianming; Wei, Heng; Guan, Hongzhi
2015-07-01
Rear-end crash is one of the most common types of traffic crashes in the U.S. A good understanding of its characteristics and contributing factors is of practical importance. Previously, both multinomial Logit models and Bayesian network methods have been used in crash modeling and analysis, respectively, although each of them has its own application restrictions and limitations. In this study, a hybrid approach is developed to combine multinomial logit models and Bayesian network methods for comprehensively analyzing driver injury severities in rear-end crashes based on state-wide crash data collected in New Mexico from 2010 to 2011. A multinomial logit model is developed to investigate and identify significant contributing factors for rear-end crash driver injury severities classified into three categories: no injury, injury, and fatality. Then, the identified significant factors are utilized to establish a Bayesian network to explicitly formulate statistical associations between injury severity outcomes and explanatory attributes, including driver behavior, demographic features, vehicle factors, geometric and environmental characteristics, etc. The test results demonstrate that the proposed hybrid approach performs reasonably well. The Bayesian network reference analyses indicate that the factors including truck-involvement, inferior lighting conditions, windy weather conditions, the number of vehicles involved, etc. could significantly increase driver injury severities in rear-end crashes. The developed methodology and estimation results provide insights for developing effective countermeasures to reduce rear-end crash injury severities and improve traffic system safety performance. PMID:25888994
A development of logistics management models for the Space Transportation System
NASA Technical Reports Server (NTRS)
Carrillo, M. J.; Jacobsen, S. E.; Abell, J. B.; Lippiatt, T. F.
1983-01-01
A new analytic queueing approach was described which relates stockage levels, repair level decisions, and the project network schedule of prelaunch operations directly to the probability distribution of the space transportation system launch delay. Finite source population and limited repair capability were additional factors included in this logistics management model developed specifically for STS maintenance requirements. Data presently available to support logistics decisions were based on a comparability study of heavy aircraft components. A two-phase program is recommended by which NASA would implement an integrated data collection system, assemble logistics data from previous STS flights, revise extant logistics planning and resource requirement parameters using Bayes-Lin techniques, and adjust for uncertainty surrounding logistics systems performance parameters. The implementation of these recommendations can be expected to deliver more cost-effective logistics support.
Logistics support of space facilities
NASA Technical Reports Server (NTRS)
Lewis, William C.
1988-01-01
The logistic support of space facilities is described, with special attention given to the problem of sizing the inventory of ready spares kept at the space facility. Where possible, data from the Space Shuttle Orbiter is extrapolated to provide numerical estimates for space facilities. Attention is also given to repair effort estimation and long duration missions.
NASA Space Rocket Logistics Challenges
NASA Technical Reports Server (NTRS)
Bramon, Chris; Neeley, James R.; Jones, James V.; Watson, Michael D.; Inman, Sharon K.; Tuttle, Loraine
2014-01-01
The Space Launch System (SLS) is the new NASA heavy lift launch vehicle in development and is scheduled for its first mission in 2017. SLS has many of the same logistics challenges as any other large scale program. However, SLS also faces unique challenges. This presentation will address the SLS challenges, along with the analysis and decisions to mitigate the threats posed by each.
Multisource information fusion for logistics
NASA Astrophysics Data System (ADS)
Woodley, Robert; Petrov, Plamen; Noll, Warren
2011-05-01
Current Army logistical systems and databases contain massive amounts of data that need an effective method to extract actionable information. The databases do not contain root cause and case-based analysis needed to diagnose or predict breakdowns. A system is needed to find data from as many sources as possible, process it in an integrated fashion, and disseminate information products on the readiness of the fleet vehicles. 21st Century Systems, Inc. introduces the Agent- Enabled Logistics Enterprise Intelligence System (AELEIS) tool, designed to assist logistics analysts with assessing the availability and prognostics of assets in the logistics pipeline. AELEIS extracts data from multiple, heterogeneous data sets. This data is then aggregated and mined for data trends. Finally, data reasoning tools and prognostics tools evaluate the data for relevance and potential issues. Multiple types of data mining tools may be employed to extract the data and an information reasoning capability determines what tools are needed to apply them to extract information. This can be visualized as a push-pull system where data trends fire a reasoning engine to search for corroborating evidence and then integrate the data into actionable information. The architecture decides on what reasoning engine to use (i.e., it may start with a rule-based method, but, if needed, go to condition based reasoning, and even a model-based reasoning engine for certain types of equipment). Initial results show that AELEIS is able to indicate to the user of potential fault conditions and root-cause information mined from a database.
Logistics, electronic commerce, and the environment
NASA Astrophysics Data System (ADS)
Sarkis, Joseph; Meade, Laura; Talluri, Srinivas
2002-02-01
Organizations realize that a strong supporting logistics or electronic logistics (e-logistics) function is important from both commercial and consumer perspectives. The implications of e-logistics models and practices cover the forward and reverse logistics functions of organizations. They also have direct and profound impact on the natural environment. This paper will focus on a discussion of forward and reverse e-logistics and their relationship to the natural environment. After discussion of the many pertinent issues in these areas, directions of practice and implications for study and research are then described.
2014-01-01
Background This paper constitutes an important ethnobiological survey in the context of utilizing biological resources by residents of Kala Chitta hills of Pothwar region, Pakistan. The fundamental aim of this research endeavour was to catalogue and analyse the indigenous knowledge of native community about plants and animals. The study is distinctive in the sense to explore both ethnobotanical and ethnozoological aspects of indigenous culture, and exhibits novelty, being based on empirical approach of Multinomial Logit Specifications (MLS) for examining ethnobotanical and ethnozoological uses of specific plants and animals. Methods To document the ethnobiological knowledge, the survey was conducted during 2011–12 by employing a semi-structured questionnaire and thus 54 informants were interviewed. Plant and animal specimens were collected, photographed and properly identified. Distribution of plants and animals were explored by descriptive and graphical examination. MLS were further incorporated to identify the probability of occurrence of diversified utilization of plants and animals in multipurpose domains. Results Traditional uses of 91 plant and 65 animal species were reported. Data analysis revealed more medicinal use of plants and animals than all other use categories. MLS findings are also in line with these proportional configurations. They reveal that medicinal and food consumption of underground and perennial plants was more as compared to aerial and annual categories of plants. Likewise, medicinal utilization of wild animals and domestic animals were more commonly observed as food items. However, invertebrates are more in the domain of medicinal and food utilization. Also carnivores are fairly common in the use of medicine while herbivores are in the category of food consumption. Conclusion This study empirically scans a good chunk of ethnobiological knowledge and depicts its strong connection with indigenous traditions. It is important to make local
Comparing the Discrete and Continuous Logistic Models
ERIC Educational Resources Information Center
Gordon, Sheldon P.
2008-01-01
The solutions of the discrete logistic growth model based on a difference equation and the continuous logistic growth model based on a differential equation are compared and contrasted. The investigation is conducted using a dynamic interactive spreadsheet. (Contains 5 figures.)
Research on 6R Military Logistics Network
NASA Astrophysics Data System (ADS)
Jie, Wan; Wen, Wang
The building of military logistics network is an important issue for the construction of new forces. This paper has thrown out a concept model of 6R military logistics network model based on JIT. Then we conceive of axis spoke y logistics centers network, flexible 6R organizational network, lean 6R military information network based grid. And then the strategy and proposal for the construction of the three sub networks of 6Rmilitary logistics network are given.
Mini pressurized logistics module (MPLM)
NASA Astrophysics Data System (ADS)
Vallerani, E.; Brondolo, D.; Basile, L.
1996-06-01
The MPLM Program was initiated through a Memorandum of Understanding (MOU) between the United States' National Aeronautics and Space Administration (NASA) and Italy's ASI, the Italian Space Agency, that was signed on 6 December 1991. The MPLM is a pressurized logistics module that will be used to transport supplies and materials (up to 20,000 lb), including user experiments, between Earth and International Space Station Alpha (ISSA) using the Shuttle, to support active and passive storage, and to provide a habitable environment for two people when docked to the Station. The Italian Space Agency has selected Alenia Spazio to develop MPLM modules that have always been considered a key element for the new International Space Station taking benefit from its design flexibility and consequent possible cost saving based on the maximum utilization of the Shuttle launch capability for any mission. In the frame of the very recent agreement between the U.S. and Russia for cooperation in space, that foresees the utilization of MIR 1 hardware, the Italian MPLM will remain an important element of the logistics system, being the only pressurized module designed for re-entry. Within the new scenario of anticipated Shuttle flights to MIR 1 during Space Station phase 1, MPLM remains a candidate for one or more missions to provide MIR 1 resupply capabilities and advanced ISSA hardware/procedures verification. Based on the concept of Flexible Carriers, Alenia Spazio is providing NASA with three MPLM flight units that can be configured according to the requirements of the Human-Tended Capability (HTC) and Permanent Human Capability (PHC) of the Space Station. Configurability will allow transportation of passive cargo only, or a combination of passive and cold cargo accommodated in R/F racks. Having developed and qualified the baseline configuration with respect to the worst enveloping condition, each unit could be easily configured to the passive or active version depending upon the
Logistics Handbook, 1976. Colorado Outward Bound School.
ERIC Educational Resources Information Center
Colorado Outward Bound School, Denver.
Logistics, a support mission, is vital to the successful operation of the Colorado Outward Bound School (COBS) courses. Logistics is responsible for purchasing, maintaining, transporting, and replenishing a wide variety of items, i.e., food, mountaineering and camping equipment, medical and other supplies, and vehicles. The Logistics coordinator…
Tian, Xinyu; Wang, Xuefeng; Chen, Jun
2014-01-01
Classic multinomial logit model, commonly used in multiclass regression problem, is restricted to few predictors and does not take into account the relationship among variables. It has limited use for genomic data, where the number of genomic features far exceeds the sample size. Genomic features such as gene expressions are usually related by an underlying biological network. Efficient use of the network information is important to improve classification performance as well as the biological interpretability. We proposed a multinomial logit model that is capable of addressing both the high dimensionality of predictors and the underlying network information. Group lasso was used to induce model sparsity, and a network-constraint was imposed to induce the smoothness of the coefficients with respect to the underlying network structure. To deal with the non-smoothness of the objective function in optimization, we developed a proximal gradient algorithm for efficient computation. The proposed model was compared to models with no prior structure information in both simulations and a problem of cancer subtype prediction with real TCGA (the cancer genome atlas) gene expression data. The network-constrained mode outperformed the traditional ones in both cases. PMID:25635165
Country logistics performance and disaster impact.
Vaillancourt, Alain; Haavisto, Ira
2016-04-01
The aim of this paper is to deepen the understanding of the relationship between country logistics performance and disaster impact. The relationship is analysed through correlation analysis and regression models for 117 countries for the years 2007 to 2012 with disaster impact variables from the International Disaster Database (EM-DAT) and logistics performance indicators from the World Bank. The results show a significant relationship between country logistics performance and disaster impact overall and for five out of six specific logistic performance indicators. These specific indicators were further used to explore the relationship between country logistic performance and disaster impact for three specific disaster types (epidemic, flood and storm). The findings enhance the understanding of the role of logistics in a humanitarian context with empirical evidence of the importance of country logistics performance in disaster response operations. PMID:26282578
Logistic equation of arbitrary order
NASA Astrophysics Data System (ADS)
Grabowski, Franciszek
2010-08-01
The paper is concerned with the new logistic equation of arbitrary order which describes the performance of complex executive systems X vs. number of tasks N, operating at limited resources K, at non-extensive, heterogeneous self-organization processes characterized by parameter f. In contrast to the classical logistic equation which exclusively relates to the special case of sub-extensive homogeneous self-organization processes at f=1, the proposed model concerns both homogeneous and heterogeneous processes in sub-extensive and super-extensive areas. The parameter of arbitrary order f, where -∞
ADJUSTABLE DOUBLE PULSE GENERATOR
Gratian, J.W.; Gratian, A.C.
1961-08-01
>A modulator pulse source having adjustable pulse width and adjustable pulse spacing is described. The generator consists of a cross coupled multivibrator having adjustable time constant circuitry in each leg, an adjustable differentiating circuit in the output of each leg, a mixing and rectifying circuit for combining the differentiated pulses and generating in its output a resultant sequence of negative pulses, and a final amplifying circuit for inverting and square-topping the pulses. (AEC)
Adjustable sutures in children.
Engel, J Mark; Guyton, David L; Hunter, David G
2014-06-01
Although adjustable sutures are considered a standard technique in adult strabismus surgery, most surgeons are hesitant to attempt the technique in children, who are believed to be unlikely to cooperate for postoperative assessment and adjustment. Interest in using adjustable sutures in pediatric patients has increased with the development of surgical techniques specific to infants and children. This workshop briefly reviews the literature supporting the use of adjustable sutures in children and presents the approaches currently used by three experienced strabismus surgeons. PMID:24924284
Optimal distributions for multiplex logistic networks.
Solá Conde, Luis E; Used, Javier; Romance, Miguel
2016-06-01
This paper presents some mathematical models for distribution of goods in logistic networks based on spectral analysis of complex networks. Given a steady distribution of a finished product, some numerical algorithms are presented for computing the weights in a multiplex logistic network that reach the equilibrium dynamics with high convergence rate. As an application, the logistic networks of Germany and Spain are analyzed in terms of their convergence rates. PMID:27368801
Integrated Computer System of Management in Logistics
NASA Astrophysics Data System (ADS)
Chwesiuk, Krzysztof
2011-06-01
This paper aims at presenting a concept of an integrated computer system of management in logistics, particularly in supply and distribution chains. Consequently, the paper includes the basic idea of the concept of computer-based management in logistics and components of the system, such as CAM and CIM systems in production processes, and management systems for storage, materials flow, and for managing transport, forwarding and logistics companies. The platform which integrates computer-aided management systems is that of electronic data interchange.
Optimal distributions for multiplex logistic networks
NASA Astrophysics Data System (ADS)
Solá Conde, Luis E.; Used, Javier; Romance, Miguel
2016-06-01
This paper presents some mathematical models for distribution of goods in logistic networks based on spectral analysis of complex networks. Given a steady distribution of a finished product, some numerical algorithms are presented for computing the weights in a multiplex logistic network that reach the equilibrium dynamics with high convergence rate. As an application, the logistic networks of Germany and Spain are analyzed in terms of their convergence rates.
Logistics Reduction Technologies for Exploration Missions
NASA Technical Reports Server (NTRS)
Broyan, James L., Jr.; Ewert, Michael K.; Fink, Patrick W.
2014-01-01
Human exploration missions under study are limited by the launch mass capacity of existing and planned launch vehicles. The logistical mass of crew items is typically considered separate from the vehicle structure, habitat outfitting, and life support systems. Although mass is typically the focus of exploration missions, due to its strong impact on launch vehicle and habitable volume for the crew, logistics volume also needs to be considered. NASA's Advanced Exploration Systems (AES) Logistics Reduction and Repurposing (LRR) Project is developing six logistics technologies guided by a systems engineering cradle-to-grave approach to enable after-use crew items to augment vehicle systems. Specifically, AES LRR is investigating the direct reduction of clothing mass, the repurposing of logistical packaging, the use of autonomous logistics management technologies, the processing of spent crew items to benefit radiation shielding and water recovery, and the conversion of trash to propulsion gases. Reduction of mass has a corresponding and significant impact to logistical volume. The reduction of logistical volume can reduce the overall pressurized vehicle mass directly, or indirectly benefit the mission by allowing for an increase in habitable volume during the mission. The systematic implementation of these types of technologies will increase launch mass efficiency by enabling items to be used for secondary purposes and improve the habitability of the vehicle as mission durations increase. Early studies have shown that the use of advanced logistics technologies can save approximately 20 m(sup 3) of volume during transit alone for a six-person Mars conjunction class mission.
Analysis of Jingdong Mall Logistics Distribution Model
NASA Astrophysics Data System (ADS)
Shao, Kang; Cheng, Feng
In recent years, the development of electronic commerce in our country to speed up the pace. The role of logistics has been highlighted, more and more electronic commerce enterprise are beginning to realize the importance of logistics in the success or failure of the enterprise. In this paper, the author take Jingdong Mall for example, performing a SWOT analysis of their current situation of self-built logistics system, find out the problems existing in the current Jingdong Mall logistics distribution and give appropriate recommendations.
FUTURE LOGISTICS AND OPERATIONAL ADAPTABILITY
Houck, Roger P.
2009-10-01
While we cannot predict the future, we can ascertain trends and examine them through the use of alternative futures methodologies and tools. From a logistics perspective, we know that many different futures are possible, all of which are obviously dependent on decisions we make in the present. As professional logisticians we are obligated to provide the field - our Soldiers - with our best professional opinion of what will result in success on the battlefield. Our view of the future should take history and contemporary conflict into account, but it must also consider that continuity with the past cannot be taken for granted. If we are too focused on past and current experience, then our vision of the future will be limited indeed. On the one hand, the future must be explained in language that does not defy common sense. On the other hand, the pace of change is such that we must conduct qualitative and quantitative trend analyses, forecasting, and explorative scenario development in ways that allow for significant breaks - or "shocks" - that may "change the game". We will need capabilities and solutions that are constantly evolving - and improving - to match the operational tempo of a radically changing threat environment. For those who provide quartermaster services, this article will briefly examine what this means from the perspective of creating what might be termed a preferred future.
Biomass supply logistics and infrastructure.
Sokhansanj, Shahabaddine; Hess, J Richard
2009-01-01
Feedstock supply system encompasses numerous unit operations necessary to move lignocellulosic feedstock from the place where it is produced (in the field or on the stump) to the start of the conversion process (reactor throat) of the biorefinery. These unit operations, which include collection, storage, preprocessing, handling, and transportation, represent one of the largest technical and logistics challenges to the emerging lignocellulosic biorefining industry. This chapter briefly reviews the methods of estimating the quantities of biomass, followed by harvesting and collection processes based on current practices on handling wet and dry forage materials. Storage and queuing are used to deal with seasonal harvest times, variable yields, and delivery schedules. Preprocessing can be as simple as grinding and formatting the biomass for increased bulk density or improved conversion efficiency, or it can be as complex as improving feedstock quality through fractionation, tissue separation, drying, blending, and densification. Handling and transportation consists of using a variety of transport equipment (truck, train, ship) for moving the biomass from one point to another. The chapter also provides typical cost figures for harvest and processing of biomass. PMID:19768612
Biomass Supply Logistics and Infrastructure
Sokhansanj, Shahabaddine
2009-04-01
Feedstock supply system encompasses numerous unit operations necessary to move lignocellulosic feedstock from the place where it is produced (in the field or on the stump) to the start of the conversion process (reactor throat) of the Biorefinery. These unit operations, which include collection, storage, preprocessing, handling, and transportation, represent one of the largest technical and logistics challenges to the emerging lignocellulosic biorefining industry. This chapter briefly reviews methods of estimating the quantities of biomass followed by harvesting and collection processes based on current practices on handling wet and dry forage materials. Storage and queuing are used to deal with seasonal harvest times, variable yields, and delivery schedules. Preprocessing can be as simple as grinding and formatting the biomass for increased bulk density or improved conversion efficiency, or it can be as complex as improving feedstock quality through fractionation, tissue separation, drying, blending, and densification. Handling and Transportation consists of using a variety of transport equipment (truck, train, ship) for moving the biomass from one point to another. The chapter also provides typical cost figures for harvest and processing of biomass.
Biomass Supply Logistics and Infrastructure
NASA Astrophysics Data System (ADS)
Sokhansanj, Shahabaddine; Hess, J. Richard
Feedstock supply system encompasses numerous unit operations necessary to move lignocellulosic feedstock from the place where it is produced (in the field or on the stump) to the start of the conversion process (reactor throat) of the biorefinery. These unit operations, which include collection, storage, preprocessing, handling, and transportation, represent one of the largest technical and logistics challenges to the emerging lignocellulosic biorefining industry. This chapter briefly reviews the methods of estimating the quantities of biomass, followed by harvesting and collection processes based on current practices on handling wet and dry forage materials. Storage and queuing are used to deal with seasonal harvest times, variable yields, and delivery schedules. Preprocessing can be as simple as grinding and formatting the biomass for increased bulk density or improved conversion efficiency, or it can be as complex as improving feedstock quality through fractionation, tissue separation, drying, blending, and densification. Handling and transportation consists of using a variety of transport equipment (truck, train, ship) for moving the biomass from one point to another. The chapter also provides typical cost figures for harvest and processing of biomass.
Higgs, Megan D.; Link, William; White, Gary C.; Haroldson, Mark A.; Bjornlie, Daniel D
2013-01-01
Mark-resight designs for estimation of population abundance are common and attractive to researchers. However, inference from such designs is very limited when faced with sparse data, either from a low number of marked animals, a low probability of detection, or both. In the Greater Yellowstone Ecosystem, yearly mark-resight data are collected for female grizzly bears with cubs-of-the-year (FCOY), and inference suffers from both limitations. To overcome difficulties due to sparseness, we assume homogeneity in sighting probabilities over 16 years of bi-annual aerial surveys. We model counts of marked and unmarked animals as multinomial random variables, using the capture frequencies of marked animals for inference about the latent multinomial frequencies for unmarked animals. We discuss undesirable behavior of the commonly used discrete uniform prior distribution on the population size parameter and provide OpenBUGS code for fitting such models. The application provides valuable insights into subtleties of implementing Bayesian inference for latent multinomial models. We tie the discussion to our application, though the insights are broadly useful for applications of the latent multinomial model.
Visualizing the Logistic Map with a Microcontroller
ERIC Educational Resources Information Center
Serna, Juan D.; Joshi, Amitabh
2012-01-01
The logistic map is one of the simplest nonlinear dynamical systems that clearly exhibits the route to chaos. In this paper, we explore the evolution of the logistic map using an open-source microcontroller connected to an array of light-emitting diodes (LEDs). We divide the one-dimensional domain interval [0,1] into ten equal parts, an associate…
Standards for Standardized Logistic Regression Coefficients
ERIC Educational Resources Information Center
Menard, Scott
2011-01-01
Standardized coefficients in logistic regression analysis have the same utility as standardized coefficients in linear regression analysis. Although there has been no consensus on the best way to construct standardized logistic regression coefficients, there is now sufficient evidence to suggest a single best approach to the construction of a…
Exploration Mission Benefits From Logistics Reduction Technologies
NASA Technical Reports Server (NTRS)
Broyan, James Lee, Jr.; Ewert, Michael K.; Schlesinger, Thilini
2016-01-01
Technologies that reduce logistical mass, volume, and the crew time dedicated to logistics management become more important as exploration missions extend further from the Earth. Even modest reductions in logistical mass can have a significant impact because it also reduces the packaging burden. NASA's Advanced Exploration Systems' Logistics Reduction Project is developing technologies that can directly reduce the mass and volume of crew clothing and metabolic waste collection. Also, cargo bags have been developed that can be reconfigured for crew outfitting, and trash processing technologies are under development to increase habitable volume and improve protection against solar storm events. Additionally, Mars class missions are sufficiently distant that even logistics management without resupply can be problematic due to the communication time delay with Earth. Although exploration vehicles are launched with all consumables and logistics in a defined configuration, the configuration continually changes as the mission progresses. Traditionally significant ground and crew time has been required to understand the evolving configuration and to help locate misplaced items. For key mission events and unplanned contingencies, the crew will not be able to rely on the ground for logistics localization assistance. NASA has been developing a radio-frequency-identification autonomous logistics management system to reduce crew time for general inventory and enable greater crew self-response to unplanned events when a wide range of items may need to be located in a very short time period. This paper provides a status of the technologies being developed and their mission benefits for exploration missions.
On some generalized discrete logistic maps
Radwan, Ahmed G.
2012-01-01
Recently, conventional logistic maps have been used in different vital applications like modeling and security. However, unfortunately the conventional logistic maps can tolerate only one changeable parameter. In this paper, three different generalized logistic maps are introduced with arbitrary powers which can be reduced to the conventional logistic map. The added parameter (arbitrary power) increases the degree of freedom of each map and gives us a versatile response that can fit many applications. Therefore, the conventional logistic map is considered only a special case from each proposed map. This new parameter increases the flexibility of the system, and illustrates the performance of the conventional system within any required neighborhood. Many cases will be illustrated showing the effect of the arbitrary power and the equation parameter on the number of equilibrium points, their locations, stability conditions, and bifurcation diagrams up to the chaotic behavior. PMID:25685414
Comparison of logistic equations for population growth.
Jensen, A L
1975-12-01
Two different forms of the logistic equation for population growth appear in the ecological literature. In the form of the logistic equation that appears in recent ecology textbooks the parameters are the instantaneous rate of natural increase per individual and the carrying capacity of the environment. In the form of the logistic equation that appears in some older literature the parameters are the instantaneous birth rate per individual and the carrying capacity. The decision whether to use one form or the other depends on which form of the equation is biologically more realistic. In this study the form of the logistic equation in which the instantaneous birth rate per individual is a parameter is shown to be more realistic in terms of the birth and death processes of population growth. Application of the logistic equation to calculate yield from an exploited fish population also shows that the parameters must be the instantaneous birth rate per individual and the carrying capacity. PMID:1203427
Improvement in fresh fruit and vegetable logistics quality: berry logistics field studies.
do Nascimento Nunes, M Cecilia; Nicometo, Mike; Emond, Jean Pierre; Melis, Ricardo Badia; Uysal, Ismail
2014-06-13
Shelf life of fresh fruits and vegetables is greatly influenced by environmental conditions. Increasing temperature usually results in accelerated loss of quality and shelf-life reduction, which is not physically visible until too late in the supply chain to adjust logistics to match shelf life. A blackberry study showed that temperatures inside pallets varied significantly and 57% of the berries arriving at the packinghouse did not have enough remaining shelf life for the longest supply routes. Yet, the advanced shelf-life loss was not physically visible. Some of those pallets would be sent on longer supply routes than necessary, creating avoidable waste. Other studies showed that variable pre-cooling at the centre of pallets resulted in physically invisible uneven shelf life. We have shown that using simple temperature measurements much waste can be avoided using 'first expiring first out'. Results from our studies showed that shelf-life prediction should not be based on a single quality factor as, depending on the temperature history, the quality attribute that limits shelf life may vary. Finally, methods to use air temperature to predict product temperature for highest shelf-life prediction accuracy in the absence of individual sensors for each monitored product have been developed. Our results show a significant reduction of up to 98% in the root-mean-square-error difference between the product temperature and air temperature when advanced estimation methods are used. PMID:24797135
Exploration Mission Benefits From Logistics Reduction Technologies
NASA Technical Reports Server (NTRS)
Broyan, James Lee, Jr.; Schlesinger, Thilini; Ewert, Michael K.
2016-01-01
Technologies that reduce logistical mass, volume, and the crew time dedicated to logistics management become more important as exploration missions extend further from the Earth. Even modest reductions in logical mass can have a significant impact because it also reduces the packing burden. NASA's Advanced Exploration Systems' Logistics Reduction Project is developing technologies that can directly reduce the mass and volume of crew clothing and metabolic waste collection. Also, cargo bags have been developed that can be reconfigured for crew outfitting and trash processing technologies to increase habitable volume and improve protection against solar storm events are under development. Additionally, Mars class missions are sufficiently distant that even logistics management without resupply can be problematic due to the communication time delay with Earth. Although exploration vehicles are launched with all consumables and logistics in a defined configuration, the configuration continually changes as the mission progresses. Traditionally significant ground and crew time has been required to understand the evolving configuration and locate misplaced items. For key mission events and unplanned contingencies, the crew will not be able to rely on the ground for logistics localization assistance. NASA has been developing a radio frequency identification autonomous logistics management system to reduce crew time for general inventory and enable greater crew self-response to unplanned events when a wide range of items may need to be located in a very short time period. This paper provides a status of the technologies being developed and there mission benefits for exploration missions.
Logistics Modeling for Lunar Exploration Systems
NASA Technical Reports Server (NTRS)
Andraschko, Mark R.; Merrill, R. Gabe; Earle, Kevin D.
2008-01-01
The extensive logistics required to support extended crewed operations in space make effective modeling of logistics requirements and deployment critical to predicting the behavior of human lunar exploration systems. This paper discusses the software that has been developed as part of the Campaign Manifest Analysis Tool in support of strategic analysis activities under the Constellation Architecture Team - Lunar. The described logistics module enables definition of logistics requirements across multiple surface locations and allows for the transfer of logistics between those locations. A key feature of the module is the loading algorithm that is used to efficiently load logistics by type into carriers and then onto landers. Attention is given to the capabilities and limitations of this loading algorithm, particularly with regard to surface transfers. These capabilities are described within the context of the object-oriented software implementation, with details provided on the applicability of using this approach to model other human exploration scenarios. Some challenges of incorporating probabilistics into this type of logistics analysis model are discussed at a high level.
ISS Logistics Hardware Disposition and Metrics Validation
NASA Technical Reports Server (NTRS)
Rogers, Toneka R.
2010-01-01
I was assigned to the Logistics Division of the International Space Station (ISS)/Spacecraft Processing Directorate. The Division consists of eight NASA engineers and specialists that oversee the logistics portion of the Checkout, Assembly, and Payload Processing Services (CAPPS) contract. Boeing, their sub-contractors and the Boeing Prime contract out of Johnson Space Center, provide the Integrated Logistics Support for the ISS activities at Kennedy Space Center. Essentially they ensure that spares are available to support flight hardware processing and the associated ground support equipment (GSE). Boeing maintains a Depot for electrical, mechanical and structural modifications and/or repair capability as required. My assigned task was to learn project management techniques utilized by NASA and its' contractors to provide an efficient and effective logistics support infrastructure to the ISS program. Within the Space Station Processing Facility (SSPF) I was exposed to Logistics support components, such as, the NASA Spacecraft Services Depot (NSSD) capabilities, Mission Processing tools, techniques and Warehouse support issues, required for integrating Space Station elements at the Kennedy Space Center. I also supported the identification of near-term ISS Hardware and Ground Support Equipment (GSE) candidates for excessing/disposition prior to October 2010; and the validation of several Logistics Metrics used by the contractor to measure logistics support effectiveness.
NASA Astrophysics Data System (ADS)
Koloc, Z.; Korf, J.; Kavan, P.
The adjustment (modification) deals with gear chains intermediating (transmitting) motion transfer between the sprocket wheels on parallel shafts. The purpose of the adjustments of chain gear is to remove the unwanted effects by using the chain guide on the links (sliding guide rail) ensuring a smooth fit of the chain rollers into the wheel tooth gap.
Adjustment to Recruit Training.
ERIC Educational Resources Information Center
Anderson, Betty S.
The thesis examines problems of adjustment encountered by new recruits entering the military services. Factors affecting adjustment are discussed: the recruit training staff and environment, recruit background characteristics, the military's image, the changing values and motivations of today's youth, and the recruiting process. Sources of…
Front-End Analysis Cornerstone of Logistics
NASA Technical Reports Server (NTRS)
Nager, Paul J.
2000-01-01
The presentation provides an overview of Front-End Logistics Support Analysis (FELSA), when it should be performed, benefits of performing FELSA and why it should be performed, how it is conducted, and examples.
Satellite rainfall retrieval by logistic regression
NASA Technical Reports Server (NTRS)
Chiu, Long S.
1986-01-01
The potential use of logistic regression in rainfall estimation from satellite measurements is investigated. Satellite measurements provide covariate information in terms of radiances from different remote sensors.The logistic regression technique can effectively accommodate many covariates and test their significance in the estimation. The outcome from the logistical model is the probability that the rainrate of a satellite pixel is above a certain threshold. By varying the thresholds, a rainrate histogram can be obtained, from which the mean and the variant can be estimated. A logistical model is developed and applied to rainfall data collected during GATE, using as covariates the fractional rain area and a radiance measurement which is deduced from a microwave temperature-rainrate relation. It is demonstrated that the fractional rain area is an important covariate in the model, consistent with the use of the so-called Area Time Integral in estimating total rain volume in other studies. To calibrate the logistical model, simulated rain fields generated by rainfield models with prescribed parameters are needed. A stringent test of the logistical model is its ability to recover the prescribed parameters of simulated rain fields. A rain field simulation model which preserves the fractional rain area and lognormality of rainrates as found in GATE is developed. A stochastic regression model of branching and immigration whose solutions are lognormally distributed in some asymptotic limits has also been developed.
Logistics Reduction Technologies for Exploration Missions
NASA Technical Reports Server (NTRS)
Broyan, James L., Jr.; Ewert, Michael K.; Fink, Patrick W.
2014-01-01
Human exploration missions under study are very limited by the launch mass capacity of existing and planned vehicles. The logistical mass of crew items is typically considered separate from the vehicle structure, habitat outfitting, and life support systems. Consequently, crew item logistical mass is typically competing with vehicle systems for mass allocation. NASA's Advanced Exploration Systems (AES) Logistics Reduction and Repurposing (LRR) Project is developing five logistics technologies guided by a systems engineering cradle-to-grave approach to enable used crew items to augment vehicle systems. Specifically, AES LRR is investigating the direct reduction of clothing mass, the repurposing of logistical packaging, the use of autonomous logistics management technologies, the processing of spent crew items to benefit radiation shielding and water recovery, and the conversion of trash to propulsion gases. The systematic implementation of these types of technologies will increase launch mass efficiency by enabling items to be used for secondary purposes and improve the habitability of the vehicle as the mission duration increases. This paper provides a description and the challenges of the five technologies under development and the estimated overall mission benefits of each technology.
McKenzie, K.R.
1959-07-01
An electrode support which permits accurate alignment and adjustment of the electrode in a plurality of planes and about a plurality of axes in a calutron is described. The support will align the slits in the electrode with the slits of an ionizing chamber so as to provide for the egress of ions. The support comprises an insulator, a leveling plate carried by the insulator and having diametrically opposed attaching screws screwed to the plate and the insulator and diametrically opposed adjusting screws for bearing against the insulator, and an electrode associated with the plate for adjustment therewith.
Kautter, John; Pope, Gregory C.
2004-01-01
The authors document the development of the CMS frailty adjustment model, a Medicare payment approach that adjusts payments to a Medicare managed care organization (MCO) according to the functional impairment of its community-residing enrollees. Beginning in 2004, this approach is being applied to certain organizations, such as Program of All-Inclusive Care for the Elderly (PACE), that specialize in providing care to the community-residing frail elderly. In the future, frailty adjustment could be extended to more Medicare managed care organizations. PMID:25372243
Ksantini, Riadh; Ziou, Djemel; Colin, Bernard; Dubeau, François
2008-02-01
In this paper, we investigate the effectiveness of a Bayesian logistic regression model to compute the weights of a pseudo-metric, in order to improve its discriminatory capacity and thereby increase image retrieval accuracy. In the proposed Bayesian model, the prior knowledge of the observations is incorporated and the posterior distribution is approximated by a tractable Gaussian form using variational transformation and Jensen's inequality, which allow a fast and straightforward computation of the weights. The pseudo-metric makes use of the compressed and quantized versions of wavelet decomposed feature vectors, and in our previous work, the weights were adjusted by classical logistic regression model. A comparative evaluation of the Bayesian and classical logistic regression models is performed for content-based image retrieval as well as for other classification tasks, in a decontextualized evaluation framework. In this same framework, we compare the Bayesian logistic regression model to some relevant state-of-the-art classification algorithms. Experimental results show that the Bayesian logistic regression model outperforms these linear classification algorithms, and is a significantly better tool than the classical logistic regression model to compute the pseudo-metric weights and improve retrieval and classification performance. Finally, we perform a comparison with results obtained by other retrieval methods. PMID:18084057
Suryawanshi, Dipak; Sharma, Varun; Saggurti, Niranjan; Bharat, Shalini
2016-08-01
Female sex workers (FSWs) are vulnerable to HIV infection. Their socioeconomic and behavioural vulnerabilities are crucial push factors for movement for sex work. This paper assesses the factors associated with the likelihood of movement of sex workers from their current place of work. Data were derived from a cross-sectional survey conducted among 5498 mobile FSWs in 22 districts of high in-migration across four states in southern India. A multinomial logit model was constructed to predict the likelihood of FSWs moving from their current place of work. Ten per cent of the sampled mobile FSWs were planning to move from their current place of sex work. Educational attainment, marital status, income at current place of work, debt, sexual coercion, experience of violence and having tested for HIV and collected the results were found to be significant predictors of the likelihood of movement from the current place of work. Consistent condom use with different clients was significantly low among those planning to move. Likewise, the likelihood of movement was significantly higher among those who had any STI symptom in the last six months and those who had a high self-perceived risk of HIV. The findings highlight the need to address factors associated with movement among mobile FSWs as part of HIV prevention and access to care interventions. PMID:26257210
Puig-Junoy, J; Saez, M; Martínez-García, E
1998-09-01
This paper analyzes the nature of health care provider choice in the case of patient-initiated contacts, with special reference to a National Health Service setting, where monetary prices are zero and general practitioners act as gatekeepers to publicly financed specialized care. We focus our attention on the factors that may explain the continuously increasing use of hospital emergency visits as opposed to other provider alternatives. An extended version of a discrete choice model of demand for patient-initiated contacts is presented, allowing for individual and town residence size differences in perceived quality (preferences) between alternative providers and including travel and waiting time as non-monetary costs. Results of a nested multinomial logit model of provider choice are presented. Individual choice between alternatives considers, in a repeated nested structure, self-care, primary care, hospital and clinic emergency services. Welfare implications and income effects are analyzed by computing compensating variations, and by simulating the effects of user fees by levels of income. Results indicate that compensating variation per visit is higher than the direct marginal cost of emergency visits, and consequently, emergency visits do not appear as an inefficient alternative even for non-urgent conditions. PMID:10916583
Botella, Juan; Huang, Huiling; Suero, Manuel
2013-01-01
Studies that evaluate the accuracy of binary classification tools are needed. Such studies provide 2 × 2 cross-classifications of test outcomes and the categories according to an unquestionable reference (or gold standard). However, sometimes a suboptimal reliability reference is employed. Several methods have been proposed to deal with studies where the observations are cross-classified with an imperfect reference. These methods require that the status of the reference, as a gold standard or as an imperfect reference, is known. In this paper a procedure for determining whether it is appropriate to maintain the assumption that the reference is a gold standard or an imperfect reference, is proposed. This procedure fits two nested multinomial tree models, and assesses and compares their absolute and incremental fit. Its implementation requires the availability of the results of several independent studies. These should be carried out using similar designs to provide frequencies of cross-classification between a test and the reference under investigation. The procedure is applied in two examples with real data. PMID:24106484
Adolescent suicide attempts and adult adjustment
Brière, Frédéric N.; Rohde, Paul; Seeley, John R.; Klein, Daniel; Lewinsohn, Peter M.
2014-01-01
Background Adolescent suicide attempts are disproportionally prevalent and frequently of low severity, raising questions regarding their long-term prognostic implications. In this study, we examined whether adolescent attempts were associated with impairments related to suicidality, psychopathology, and psychosocial functioning in adulthood (objective 1) and whether these impairments were better accounted for by concurrent adolescent confounders (objective 2). Method 816 adolescents were assessed using interviews and questionnaires at four time points from adolescence to adulthood. We examined whether lifetime suicide attempts in adolescence (by T2, mean age 17) predicted adult outcomes (by T4, mean age 30) using linear and logistic regressions in unadjusted models (objective 1) and adjusting for sociodemographic background, adolescent psychopathology, and family risk factors (objective 2). Results In unadjusted analyses, adolescent suicide attempts predicted poorer adjustment on all outcomes, except those related to social role status. After adjustment, adolescent attempts remained predictive of axis I and II psychopathology (anxiety disorder, antisocial and borderline personality disorder symptoms), global and social adjustment, risky sex, and psychiatric treatment utilization. However, adolescent attempts no longer predicted most adult outcomes, notably suicide attempts and major depressive disorder. Secondary analyses indicated that associations did not differ by sex and attempt characteristics (intent, lethality, recurrence). Conclusions Adolescent suicide attempters are at high risk of protracted and wide-ranging impairments, regardless of the characteristics of their attempt. Although attempts specifically predict (and possibly influence) several outcomes, results suggest that most impairments reflect the confounding contributions of other individual and family problems or vulnerabilites in adolescent attempters. PMID:25421360
Remotely Adjustable Hydraulic Pump
NASA Technical Reports Server (NTRS)
Kouns, H. H.; Gardner, L. D.
1987-01-01
Outlet pressure adjusted to match varying loads. Electrohydraulic servo has positioned sleeve in leftmost position, adjusting outlet pressure to maximum value. Sleeve in equilibrium position, with control land covering control port. For lowest pressure setting, sleeve shifted toward right by increased pressure on sleeve shoulder from servovalve. Pump used in aircraft and robots, where hydraulic actuators repeatedly turned on and off, changing pump load frequently and over wide range.
Weighted triangulation adjustment
Anderson, Walter L.
1969-01-01
The variation of coordinates method is employed to perform a weighted least squares adjustment of horizontal survey networks. Geodetic coordinates are required for each fixed and adjustable station. A preliminary inverse geodetic position computation is made for each observed line. Weights associated with each observed equation for direction, azimuth, and distance are applied in the formation of the normal equations in-the least squares adjustment. The number of normal equations that may be solved is twice the number of new stations and less than 150. When the normal equations are solved, shifts are produced at adjustable stations. Previously computed correction factors are applied to the shifts and a most probable geodetic position is found for each adjustable station. Pinal azimuths and distances are computed. These may be written onto magnetic tape for subsequent computation of state plane or grid coordinates. Input consists of punch cards containing project identification, program options, and position and observation information. Results listed include preliminary and final positions, residuals, observation equations, solution of the normal equations showing magnitudes of shifts, and a plot of each adjusted and fixed station. During processing, data sets containing irrecoverable errors are rejected and the type of error is listed. The computer resumes processing of additional data sets.. Other conditions cause warning-errors to be issued, and processing continues with the current data set.
NASA Space Exploration Logistics Workshop Proceedings
NASA Technical Reports Server (NTRS)
deWeek, Oliver; Evans, William A.; Parrish, Joe; James, Sarah
2006-01-01
As NASA has embarked on a new Vision for Space Exploration, there is new energy and focus around the area of manned space exploration. These activities encompass the design of new vehicles such as the Crew Exploration Vehicle (CEV) and Crew Launch Vehicle (CLV) and the identification of commercial opportunities for space transportation services, as well as continued operations of the Space Shuttle and the International Space Station. Reaching the Moon and eventually Mars with a mix of both robotic and human explorers for short term missions is a formidable challenge in itself. How to achieve this in a safe, efficient and long-term sustainable way is yet another question. The challenge is not only one of vehicle design, launch, and operations but also one of space logistics. Oftentimes, logistical issues are not given enough consideration upfront, in relation to the large share of operating budgets they consume. In this context, a group of 54 experts in space logistics met for a two-day workshop to discuss the following key questions: 1. What is the current state-of the art in space logistics, in terms of architectures, concepts, technologies as well as enabling processes? 2. What are the main challenges for space logistics for future human exploration of the Moon and Mars, at the intersection of engineering and space operations? 3. What lessons can be drawn from past successes and failures in human space flight logistics? 4. What lessons and connections do we see from terrestrial analogies as well as activities in other areas, such as U.S. military logistics? 5. What key advances are required to enable long-term success in the context of a future interplanetary supply chain? These proceedings summarize the outcomes of the workshop, reference particular presentations, panels and breakout sessions, and record specific observations that should help guide future efforts.
Definition of main pollen season using a logistic model.
Ribeiro, Helena; Cunha, Mário; Abreu, Ilda
2007-01-01
This paper proposes a method to unify the definition of the main pollen season based on statistical analysis. For this, an aerobiological study was carried out in Porto region (Portugal), from 2003-2005 using a 7-day Hirst-type volumetric spore trap. To define the main pollen season, a non-linear logistic regression model was fitted to the values of the accumulated sum of the daily airborne pollen concentration from several allergological species. An important feature of this method is that the main pollen season will be characterized by the model parameters calculated. These parameters are identifiable aspects of the flowering phenology, and determine not only the beginning and end of the main pollen season, but are also influenced by the meteorological conditions. The results obtained with the proposed methodology were also compared with two of the most used percentage methods. The logistic model fitted well with the sum of accumulated pollen. The explained variance was always higher than 97%, and the exponential part of the predicted curve was well adjusted to the time when higher atmospheric pollen concentration was sampled. The comparison between the different methods tested showed large divergence in the duration and end dates of the main pollen season of the studied species. PMID:18247462
ISS Update: Logistics Reduction and Repurposing (Part 2)
Public Affairs Officer Brandi Dean interviews Sarah Shull, Deputy Project Manager Logistics Reduction and Repurposing. Shull, who is with the Advanced Exploration Systems, discusses the Logistics t...
ISS Update: Logistics Reduction and Repurposing (Part 1)
Public Affairs Officer Brandi Dean interviews Sarah Shull, Deputy Project Manager Logistics Reduction and Repurposing. Shull, who is with the Advanced Exploration Systems, discusses the Logistics t...
Logistics Lessons Learned in NASA Space Flight
NASA Technical Reports Server (NTRS)
Evans, William A.; DeWeck, Olivier; Laufer, Deanna; Shull, Sarah
2006-01-01
The Vision for Space Exploration sets out a number of goals, involving both strategic and tactical objectives. These include returning the Space Shuttle to flight, completing the International Space Station, and conducting human expeditions to the Moon by 2020. Each of these goals has profound logistics implications. In the consideration of these objectives,a need for a study on NASA logistics lessons learned was recognized. The study endeavors to identify both needs for space exploration and challenges in the development of past logistics architectures, as well as in the design of space systems. This study may also be appropriately applied as guidance in the development of an integrated logistics architecture for future human missions to the Moon and Mars. This report first summarizes current logistics practices for the Space Shuttle Program (SSP) and the International Space Station (ISS) and examines the practices of manifesting, stowage, inventory tracking, waste disposal, and return logistics. The key findings of this examination are that while the current practices do have many positive aspects, there are also several shortcomings. These shortcomings include a high-level of excess complexity, redundancy of information/lack of a common database, and a large human-in-the-loop component. Later sections of this report describe the methodology and results of our work to systematically gather logistics lessons learned from past and current human spaceflight programs as well as validating these lessons through a survey of the opinions of current space logisticians. To consider the perspectives on logistics lessons, we searched several sources within NASA, including organizations with direct and indirect connections with the system flow in mission planning. We utilized crew debriefs, the John Commonsense lessons repository for the JSC Mission Operations Directorate, and the Skylab Lessons Learned. Additionally, we searched the public version of the Lessons Learned
Reverse logistics in the construction industry.
Hosseini, M Reza; Rameezdeen, Raufdeen; Chileshe, Nicholas; Lehmann, Steffen
2015-06-01
Reverse logistics in construction refers to the movement of products and materials from salvaged buildings to a new construction site. While there is a plethora of studies looking at various aspects of the reverse logistics chain, there is no systematic review of literature on this important subject as applied to the construction industry. Therefore, the objective of this study is to integrate the fragmented body of knowledge on reverse logistics in construction, with the aim of promoting the concept among industry stakeholders and the wider construction community. Through a qualitative meta-analysis, the study synthesises the findings of previous studies and presents some actions needed by industry stakeholders to promote this concept within the real-life context. First, the trend of research and terminology related with reverse logistics is introduced. Second, it unearths the main advantages and barriers of reverse logistics in construction while providing some suggestions to harness the advantages and mitigate these barriers. Finally, it provides a future research direction based on the review. PMID:26018543
Humanitarian response: improving logistics to save lives.
McCoy, Jessica
2008-01-01
Each year, millions of people worldwide are affected by disasters, underscoring the importance of effective relief efforts. Many highly visible disaster responses have been inefficient and ineffective. Humanitarian agencies typically play a key role in disaster response (eg, procuring and distributing relief items to an affected population, assisting with evacuation, providing healthcare, assisting in the development of long-term shelter), and thus their efficiency is critical for a successful disaster response. The field of disaster and emergency response modeling is well established, but the application of such techniques to humanitarian logistics is relatively recent. This article surveys models of humanitarian response logistics and identifies promising opportunities for future work. Existing models analyze a variety of preparation and response decisions (eg, warehouse location and the distribution of relief supplies), consider both natural and manmade disasters, and typically seek to minimize cost or unmet demand. Opportunities to enhance the logistics of humanitarian response include the adaptation of models developed for general disaster response; the use of existing models, techniques, and insights from the literature on commercial supply chain management; the development of working partnerships between humanitarian aid organizations and private companies with expertise in logistics; and the consideration of behavioral factors relevant to a response. Implementable, realistic models that support the logistics of humanitarian relief can improve the preparation for and the response to disasters, which in turn can save lives. PMID:19069032
Partial covariate adjusted regression
Şentürk, Damla; Nguyen, Danh V.
2008-01-01
Covariate adjusted regression (CAR) is a recently proposed adjustment method for regression analysis where both the response and predictors are not directly observed (Şentürk and Müller, 2005). The available data has been distorted by unknown functions of an observable confounding covariate. CAR provides consistent estimators for the coefficients of the regression between the variables of interest, adjusted for the confounder. We develop a broader class of partial covariate adjusted regression (PCAR) models to accommodate both distorted and undistorted (adjusted/unadjusted) predictors. The PCAR model allows for unadjusted predictors, such as age, gender and demographic variables, which are common in the analysis of biomedical and epidemiological data. The available estimation and inference procedures for CAR are shown to be invalid for the proposed PCAR model. We propose new estimators and develop new inference tools for the more general PCAR setting. In particular, we establish the asymptotic normality of the proposed estimators and propose consistent estimators of their asymptotic variances. Finite sample properties of the proposed estimators are investigated using simulation studies and the method is also illustrated with a Pima Indians diabetes data set. PMID:20126296
Warren, Joshua L; Stingone, Jeanette A; Herring, Amy H; Luben, Thomas J; Fuentes, Montserrat; Aylsworth, Arthur S; Langlois, Peter H; Botto, Lorenzo D; Correa, Adolfo; Olshan, Andrew F
2016-07-20
Epidemiologic studies suggest that maternal ambient air pollution exposure during critical periods of pregnancy is associated with adverse effects on fetal development. In this work, we introduce new methodology for identifying critical periods of development during post-conception gestational weeks 2-8 where elevated exposure to particulate matter less than 2.5 µm (PM2.5 ) adversely impacts development of the heart. Past studies have focused on highly aggregated temporal levels of exposure during the pregnancy and have failed to account for anatomical similarities between the considered congenital heart defects. We introduce a multinomial probit model in the Bayesian setting that allows for joint identification of susceptible daily periods during pregnancy for 12 types of congenital heart defects with respect to maternal PM2.5 exposure. We apply the model to a dataset of mothers from the National Birth Defect Prevention Study where daily PM2.5 exposures from post-conception gestational weeks 2-8 are assigned using predictions from the downscaler pollution model. This approach is compared with two aggregated exposure models that define exposure as the average value over post-conception gestational weeks 2-8 and the average over individual weeks, respectively. Results suggest an association between increased PM2.5 exposure on post-conception gestational day 53 with the development of pulmonary valve stenosis and exposures during days 50 and 51 with tetralogy of Fallot. Significant associations are masked when using the aggregated exposure models. Simulation study results suggest that the findings are robust to multiple sources of error. The general form of the model allows for different exposures and health outcomes to be considered in future applications. Copyright © 2016 John Wiley & Sons, Ltd. PMID:26853919
Using Cultural Algorithms to Improve Intelligent Logistics
NASA Astrophysics Data System (ADS)
Ochoa, Alberto; García, Yazmani; Yañez, Javier; Teymanoglu, Yaddik
Today the issue of logistics is a very important within companies to the extent that some have departments devoted exclusively to it. This has evolved over time and today is a fundamental aspect in the fight business seeking to consolidate or remain leaders in their field. With the above we know that logistics can be divided into different classes, however, in this regard, our study is based on the timely distribution to the customer with a lower cost, higher sales and better utilization of space resulting in excellent service. Finally, prepare a comparative analysis of the results with respect to another method of optimization solution space.
Asymptotic behavior of degenerate logistic equations
NASA Astrophysics Data System (ADS)
Arrieta, José M.; Pardo, Rosa; Rodríguez-Bernal, Aníbal
2015-12-01
We analyze the asymptotic behavior of positive solutions of parabolic equations with a class of degenerate logistic nonlinearities of the type λu - n (x)uρ. An important characteristic of this work is that the region where the logistic term n (ṡ) vanishes, that is K0 = { x : n (x) = 0 }, may be non-smooth. We analyze conditions on λ, ρ, n (ṡ) and K0 guaranteeing that the solution starting at a positive initial condition remains bounded or blows up as time goes to infinity. The asymptotic behavior may not be the same in different parts of K0.
ERIC Educational Resources Information Center
Abramson, Jane A.
Personal interviews with 100 former farm operators living in Saskatoon, Saskatchewan, were conducted in an attempt to understand the nature of the adjustment process caused by migration from rural to urban surroundings. Requirements for inclusion in the study were that respondents had owned or operated a farm for at least 3 years, had left their…
Hunter, Steven L.
2002-01-01
An inclinometer utilizing synchronous demodulation for high resolution and electronic offset adjustment provides a wide dynamic range without any moving components. A device encompassing a tiltmeter and accompanying electronic circuitry provides quasi-leveled tilt sensors that detect highly resolved tilt change without signal saturation.
NASA Technical Reports Server (NTRS)
1986-01-01
Corning Glass Works' Serengeti Driver sunglasses are unique in that their lenses self-adjust and filter light while suppressing glare. They eliminate more than 99% of the ultraviolet rays in sunlight. The frames are based on the NASA Anthropometric Source Book.
Applying waste logistics modeling to regional planning
Holter, G.M.; Khawaja, A.; Shaver, S.R.; Peterson, K.L.
1995-05-01
Waste logistics modeling is a powerful analytical technique that can be used for effective planning of future solid waste storage, treatment, and disposal activities. Proper waste management is essential for preventing unacceptable environmental degradation from ongoing operations, and is also a critical part of any environmental remediation activity. Logistics modeling allows for analysis of alternate scenarios for future waste flowrates and routings, facility schedules, and processing or handling capacities. Such analyses provide an increased understanding of the critical needs for waste storage, treatment, transport, and disposal while there is still adequate lead time to plan accordingly. They also provide a basis for determining the sensitivity of these critical needs to the various system parameters. This paper discusses the application of waste logistics modeling concepts to regional planning. In addition to ongoing efforts to aid in planning for a large industrial complex, the Pacific Northwest Laboratory (PNL) is currently involved in implementing waste logistics modeling as part of the planning process for material recovery and recycling within a multi-city region in the western US.
A Logistic Regression Model for Personnel Selection.
ERIC Educational Resources Information Center
Raju, Nambury S.; And Others
1991-01-01
A two-parameter logistic regression model for personnel selection is proposed. The model was tested with a database of 84,808 military enlistees. The probability of job success was related directly to trait levels, addressing such topics as selection, validity generalization, employee classification, selection bias, and utility-based fair…
Biomass round bales infield aggregation logistic scenarios
Technology Transfer Automated Retrieval System (TEKTRAN)
Biomass bales often need to be aggregated (collected into groups and transported) to a field-edge stack for temporary storage for feedlots or processing facilities. Aggregating the bales with the least total distance involved is a goal of producers and bale handlers. Several logistics scenarios for ...
Predicting Social Trust with Binary Logistic Regression
ERIC Educational Resources Information Center
Adwere-Boamah, Joseph; Hufstedler, Shirley
2015-01-01
This study used binary logistic regression to predict social trust with five demographic variables from a national sample of adult individuals who participated in The General Social Survey (GSS) in 2012. The five predictor variables were respondents' highest degree earned, race, sex, general happiness and the importance of personally assisting…
Linear Logistic Test Modeling with R
ERIC Educational Resources Information Center
Baghaei, Purya; Kubinger, Klaus D.
2015-01-01
The present paper gives a general introduction to the linear logistic test model (Fischer, 1973), an extension of the Rasch model with linear constraints on item parameters, along with eRm (an R package to estimate different types of Rasch models; Mair, Hatzinger, & Mair, 2014) functions to estimate the model and interpret its parameters. The…
LOGISTICS OF ECOLOGICAL SAMPLING ON LARGE RIVERS
The objectives of this document are to provide an overview of the logistical problems associated with the ecological sampling of boatable rivers and to suggest solutions to those problems. It is intended to be used as a resource for individuals preparing to collect biological dat...
Mission Benefits Analysis of Logistics Reduction Technologies
NASA Technical Reports Server (NTRS)
Ewert, Michael K.; Broyan, James L.
2012-01-01
Future space exploration missions will need to use less logistical supplies if humans are to live for longer periods away from our home planet. Anything that can be done to reduce initial mass and volume of supplies or reuse or recycle items that have been launched will be very valuable. Reuse and recycling also reduce the trash burden and associated nuisances, such as smell, but require good systems engineering and operations integration to reap the greatest benefits. A systems analysis was conducted to quantify the mass and volume savings of four different technologies currently under development by NASA fs Advanced Exploration Systems (AES) Logistics Reduction and Repurposing project. Advanced clothing systems lead to savings by direct mass reduction and increased wear duration. Reuse of logistical items, such as packaging, for a second purpose allows fewer items to be launched. A device known as a heat melt compactor drastically reduces the volume of trash, recovers water and produces a stable tile that can be used instead of launching additional radiation protection. The fourth technology, called trash ]to ]supply ]gas, can benefit a mission by supplying fuel such as methane to the propulsion system. This systems engineering work will help improve logistics planning and overall mission architectures by determining the most effective use, and reuse, of all resources.
Mission Benefits Analysis of Logistics Reduction Technologies
NASA Technical Reports Server (NTRS)
Ewert, Michael K.; Broyan, James Lee, Jr.
2013-01-01
Future space exploration missions will need to use less logistical supplies if humans are to live for longer periods away from our home planet. Anything that can be done to reduce initial mass and volume of supplies or reuse or recycle items that have been launched will be very valuable. Reuse and recycling also reduce the trash burden and associated nuisances, such as smell, but require good systems engineering and operations integration to reap the greatest benefits. A systems analysis was conducted to quantify the mass and volume savings of four different technologies currently under development by NASA s Advanced Exploration Systems (AES) Logistics Reduction and Repurposing project. Advanced clothing systems lead to savings by direct mass reduction and increased wear duration. Reuse of logistical items, such as packaging, for a second purpose allows fewer items to be launched. A device known as a heat melt compactor drastically reduces the volume of trash, recovers water and produces a stable tile that can be used instead of launching additional radiation protection. The fourth technology, called trash-to-gas, can benefit a mission by supplying fuel such as methane to the propulsion system. This systems engineering work will help improve logistics planning and overall mission architectures by determining the most effective use, and reuse, of all resources.
Multinomial Diffusion Equation
Balter, Ariel I.; Tartakovsky, Alexandre M.
2011-06-01
We have developed a novel stochastic, space/time discrete representation of particle diffusion (e.g. Brownian motion) based on discrete probability distributions. We show that in the limit of both very small time step and large concentration, our description is equivalent to the space/time continuous stochastic diffusion equation. Being discrete in both time and space, our model can be used as an extremely accurate, efficient, and stable stochastic finite-difference diffusion algorithm when concentrations are so small that computationally expensive particle-based methods are usually needed. Through numerical simulations, we show that our method can generate realizations that capture the statistical properties of particle simulations. While our method converges converges to both the correct ensemble mean and ensemble variance very quickly with decreasing time step, but for small concentration, the stochastic diffusion PDE does not, even for very small time steps.
Multinomial diffusion equation
NASA Astrophysics Data System (ADS)
Balter, Ariel; Tartakovsky, Alexandre M.
2011-06-01
We describe a new, microscopic model for diffusion that captures diffusion induced fluctuations at scales where the concept of concentration gives way to discrete particles. We show that in the limit as the number of particles N→∞, our model is equivalent to the classical stochastic diffusion equation (SDE). We test our new model and the SDE against Langevin dynamics in numerical simulations, and show that our model successfully reproduces the correct ensemble statistics, while the classical model fails.
Multinomial diffusion equation
Balter, Ariel I.; Tartakovsky, Alexandre M.
2011-06-24
We describe a new, microscopic model for diffusion that captures diffusion induced uctuations at scales where the concept of concentration gives way to discrete par- ticles. We show that in the limit as the number of particles N ! 1, our model is equivalent to the classical stochastic diffusion equation (SDE). We test our new model and the SDE against Langevin dynamics in numerical simulations, and show that our model successfully reproduces the correct ensemble statistics, while the classical model fails.
Cutburth, Ronald W.; Silva, Leonard L.
1988-01-01
An improved mounting stage of the type used for the detection of laser beams is disclosed. A stage center block is mounted on each of two opposite sides by a pair of spaced ball bearing tracks which provide stability as well as simplicity. The use of the spaced ball bearing pairs in conjunction with an adjustment screw which also provides support eliminates extraneous stabilization components and permits maximization of the area of the center block laser transmission hole.
NASA Technical Reports Server (NTRS)
Malin, Jane T.; Schrenkenghost, Debra K.
2001-01-01
The Adjustable Autonomy Testbed (AAT) is a simulation-based testbed located in the Intelligent Systems Laboratory in the Automation, Robotics and Simulation Division at NASA Johnson Space Center. The purpose of the testbed is to support evaluation and validation of prototypes of adjustable autonomous agent software for control and fault management for complex systems. The AA T project has developed prototype adjustable autonomous agent software and human interfaces for cooperative fault management. This software builds on current autonomous agent technology by altering the architecture, components and interfaces for effective teamwork between autonomous systems and human experts. Autonomous agents include a planner, flexible executive, low level control and deductive model-based fault isolation. Adjustable autonomy is intended to increase the flexibility and effectiveness of fault management with an autonomous system. The test domain for this work is control of advanced life support systems for habitats for planetary exploration. The CONFIG hybrid discrete event simulation environment provides flexible and dynamically reconfigurable models of the behavior of components and fluids in the life support systems. Both discrete event and continuous (discrete time) simulation are supported, and flows and pressures are computed globally. This provides fast dynamic simulations of interacting hardware systems in closed loops that can be reconfigured during operations scenarios, producing complex cascading effects of operations and failures. Current object-oriented model libraries support modeling of fluid systems, and models have been developed of physico-chemical and biological subsystems for processing advanced life support gases. In FY01, water recovery system models will be developed.
NASA Technical Reports Server (NTRS)
Renfroe, Michael B.; Mcdonald, Edward J.; Bradshaw, Kimberly
1988-01-01
The Logistics Asset Tracking System (LATS) devised by NASA contains data on Space Shuttle LRUs that are daily updated to reflect such LRU status changes as repair due to failure or modification due to changing engineering requirements. The implementation of LATS has substantially increased personnel responsiveness, preventing costly delays in Space Shuttle processing and obviating hardware cannibalization. An evaluation is presented of LATS achievements in the direction of an integrated logistical support posture.
Imbalanced Learning Based on Logistic Discrimination
Guo, Huaping; Zhi, Weimei; Liu, Hongbing; Xu, Mingliang
2016-01-01
In recent years, imbalanced learning problem has attracted more and more attentions from both academia and industry, and the problem is concerned with the performance of learning algorithms in the presence of data with severe class distribution skews. In this paper, we apply the well-known statistical model logistic discrimination to this problem and propose a novel method to improve its performance. To fully consider the class imbalance, we design a new cost function which takes into account the accuracies of both positive class and negative class as well as the precision of positive class. Unlike traditional logistic discrimination, the proposed method learns its parameters by maximizing the proposed cost function. Experimental results show that, compared with other state-of-the-art methods, the proposed one shows significantly better performance on measures of recall, g-mean, f-measure, AUC, and accuracy. PMID:26880877
Technological Support for Logistics Transportation Systems
NASA Astrophysics Data System (ADS)
Bujak, Andrzej; Śliwa, Zdzisław; Gębczyńska, Alicja
The modern world is changing introducing robots, remotely controlled vehicles and other crewless means of transportation to reduce people's mistakes, as the main cause of incidents and crashes during traffic. New technologies are supporting operators and drivers, and according to some studies they can even replace them. Such programs as: AHS, UAH, IVBSS or MTVR are under development to improve traffic flow and its safety, to reduce traffic hazards and crashes. It is necessary to analyze such concepts and implement them boldly, including Polish logistics' companies, new programs, highways' system etc., as they will be applied in the future, so it is necessary to prepare logistics infrastructure ahead of time in order to capitalize on these improvements. The problem is quite urgent as transportation in the country must not be outdated to meet clients' expectations and to keep pace with competing foreign companies.
Exact solution to fractional logistic equation
NASA Astrophysics Data System (ADS)
West, Bruce J.
2015-07-01
The logistic equation is one of the most familiar nonlinear differential equations in the biological and social sciences. Herein we provide an exact solution to an extension of this equation to incorporate memory through the use of fractional derivatives in time. The solution to the fractional logistic equation (FLE) is obtained using the Carleman embedding technique that allows the nonlinear equation to be replaced by an infinite-order set of linear equations, which we then solve exactly. The formal series expansion for the initial value solution of the FLE is shown to be expressed in terms of a series of weighted Mittag-Leffler functions that reduces to the well known analytic solution in the limit where the fractional index for the derivative approaches unity. The numerical integration to the FLE provides an excellent fit to the analytic solution. We propose this approach as a general technique for solving a class of nonlinear fractional differential equations.
Jiang, Honghua; Kulkarni, Pandurang M; Mallinckrodt, Craig H; Shurzinske, Linda; Molenberghs, Geert; Lipkovich, Ilya
2015-01-01
The benefits of adjusting for baseline covariates are not as straightforward with repeated binary responses as with continuous response variables. Therefore, in this study, we compared different methods for analyzing repeated binary data through simulations when the outcome at the study endpoint is of interest. Methods compared included chi-square, Fisher's exact test, covariate adjusted/unadjusted logistic regression (Adj.logit/Unadj.logit), covariate adjusted/unadjusted generalized estimating equations (Adj.GEE/Unadj.GEE), covariate adjusted/unadjusted generalized linear mixed model (Adj.GLMM/Unadj.GLMM). All these methods preserved the type I error close to the nominal level. Covariate adjusted methods improved power compared with the unadjusted methods because of the increased treatment effect estimates, especially when the correlation between the baseline and outcome was strong, even though there was an apparent increase in standard errors. Results of the Chi-squared test were identical to those for the unadjusted logistic regression. Fisher's exact test was the most conservative test regarding the type I error rate and also with the lowest power. Without missing data, there was no gain in using a repeated measures approach over a simple logistic regression at the final time point. Analysis of results from five phase III diabetes trials of the same compound was consistent with the simulation findings. Therefore, covariate adjusted analysis is recommended for repeated binary data when the study endpoint is of interest. PMID:25866149
Model selection for logistic regression models
NASA Astrophysics Data System (ADS)
Duller, Christine
2012-09-01
Model selection for logistic regression models decides which of some given potential regressors have an effect and hence should be included in the final model. The second interesting question is whether a certain factor is heterogeneous among some subsets, i.e. whether the model should include a random intercept or not. In this paper these questions will be answered with classical as well as with Bayesian methods. The application show some results of recent research projects in medicine and business administration.
Moment closure and the stochastic logistic model.
Nåsell, Ingemar
2003-03-01
The quasi-stationary distribution of the stochastic logistic model is studied in the parameter region where its body is approximately normal. Improved asymptotic approximations of its first three cumulants are derived. It is shown that the same results can be derived with the aid of the moment closure method. This indicates that the moment closure method leads to expressions for the cumulants that are asymptotic approximations of the cumulants of the quasi-stationary distribution. PMID:12615498
Space Station - An integrated approach to operational logistics support
NASA Technical Reports Server (NTRS)
Hosmer, G. J.
1986-01-01
Development of an efficient and cost effective operational logistics system for the Space Station will require logistics planning early in the program's design and development phase. This paper will focus on Integrated Logistics Support (ILS) Program techniques and their application to the Space Station program design, production and deployment phases to assure the development of an effective and cost efficient operational logistics system. The paper will provide the methodology and time-phased programmatic steps required to establish a Space Station ILS Program that will provide an operational logistics system based on planned Space Station program logistics support.
Continuously adjustable Pulfrich spectacles
NASA Astrophysics Data System (ADS)
Jacobs, Ken; Karpf, Ron
2011-03-01
A number of Pulfrich 3-D movies and TV shows have been produced, but the standard implementation has inherent drawbacks. The movie and TV industries have correctly concluded that the standard Pulfrich 3-D implementation is not a useful 3-D technique. Continuously Adjustable Pulfrich Spectacles (CAPS) is a new implementation of the Pulfrich effect that allows any scene containing movement in a standard 2-D movie, which are most scenes, to be optionally viewed in 3-D using inexpensive viewing specs. Recent scientific results in the fields of human perception, optoelectronics, video compression and video format conversion are translated into a new implementation of Pulfrich 3- D. CAPS uses these results to continuously adjust to the movie so that the viewing spectacles always conform to the optical density that optimizes the Pulfrich stereoscopic illusion. CAPS instantly provides 3-D immersion to any moving scene in any 2-D movie. Without the glasses, the movie will appear as a normal 2-D image. CAPS work on any viewing device, and with any distribution medium. CAPS is appropriate for viewing Internet streamed movies in 3-D.
Subsea adjustable choke valves
Cyvas, M.K. )
1989-08-01
With emphasis on deepwater wells and marginal offshore fields growing, the search for reliable subsea production systems has become a high priority. A reliable subsea adjustable choke is essential to the realization of such a system, and recent advances are producing the degree of reliability required. Technological developments have been primarily in (1) trim material (including polycrystalline diamond), (2) trim configuration, (3) computer programs for trim sizing, (4) component materials, and (5) diver/remote-operated-vehicle (ROV) interfaces. These five facets are overviewed and progress to date is reported. A 15- to 20-year service life for adjustable subsea chokes is now a reality. Another factor vital to efficient use of these technological developments is to involve the choke manufacturer and ROV/diver personnel in initial system conceptualization. In this manner, maximum benefit can be derived from the latest technology. Major areas of development still required and under way are listed, and the paper closes with a tabulation of successful subsea choke installations in recent years.
Micro-Logistics Analysis for Human Space Exploration
NASA Technical Reports Server (NTRS)
Cirillo, William; Stromgren, Chel; Galan, Ricardo
2008-01-01
Traditionally, logistics analysis for space missions has focused on the delivery of elements and goods to a destination. This type of logistics analysis can be referred to as "macro-logistics". While the delivery of goods is a critical component of mission analysis, it captures only a portion of the constraints that logistics planning may impose on a mission scenario. The other component of logistics analysis concerns the local handling of goods at the destination, including storage, usage, and disposal. This type of logistics analysis, referred to as "micro-logistics", may also be a primary driver in the viability of a human lunar exploration scenario. With the rigorous constraints that will be placed upon a human lunar outpost, it is necessary to accurately evaluate micro-logistics operations in order to develop exploration scenarios that will result in an acceptable level of system performance.
Risk adjusting capitation: applications in employed and disabled populations.
Madden, C W; Mackay, B P; Skillman, S M; Ciol, M; Diehr, P K
2000-02-01
Risk adjustment may be a sensible strategy to reduce selection bias because it links managed care payment directly to the costs of providing services. In this paper we compare risk adjustment models in two populations (public employees and their dependents, and publicly-insured low income individuals with disabilities) in Washington State using two statistical approaches and three health status measures. We conclude that a two-part logistic/GLM statistical model performs better in populations with large numbers of individuals who do not use health services. This model was successfully implemented in the employed population, but the managed care program for the publicly insured population was terminated before risk adjustment could be applied. The choice of the most appropriate health status measure depends on purchasers' principles and desired outcomes. PMID:10780278
The Application used RFID in Third Party Logistics*
NASA Astrophysics Data System (ADS)
Mingxiu, Zheng; Chunchang, Fu; Minggen, Yang
RFID is a non-contact automatic identification technology, which will be the future information storage extraction and processing technology. In recent years the mainstream of the large-scale development has manifested the situation. RFID is the key technology of tripartite logistics information and automation. RFID-based logistics system can enlarge the logistics operation capacity, and improve labor productivity to reduce logistics operations mistakes.
Research and design of logistical information system based on SOA
NASA Astrophysics Data System (ADS)
Zhang, Bo
2013-03-01
Through the study on the existing logistics information systems and SOA technology, based on the current situation of enterprise logistics management and business features, this paper puts forward a SOA-based logistics system design program. This program is made in the WCF framework, with the combination of SOA and the actual characteristics of logistics enterprises, is simple to realize, easy to operate, and has strong expansion characteristic, therefore has high practical value.
77 FR 40387 - Price Adjustment
Federal Register 2010, 2011, 2012, 2013, 2014
2012-07-09
... Price Adjustment AGENCY: Postal Regulatory Commission. ACTION: Notice. SUMMARY: The Commission is noticing a recently filed Postal Service request to adjust prices for several market dominant products... announcing its intent to adjust prices for several market dominant products within First-Class Mail...
Comparison of a Bayesian Network with a Logistic Regression Model to Forecast IgA Nephropathy
Ducher, Michel; Kalbacher, Emilie; Combarnous, François; Finaz de Vilaine, Jérome; McGregor, Brigitte; Fouque, Denis; Fauvel, Jean Pierre
2013-01-01
Models are increasingly used in clinical practice to improve the accuracy of diagnosis. The aim of our work was to compare a Bayesian network to logistic regression to forecast IgA nephropathy (IgAN) from simple clinical and biological criteria. Retrospectively, we pooled the results of all biopsies (n = 155) performed by nephrologists in a specialist clinical facility between 2002 and 2009. Two groups were constituted at random. The first subgroup was used to determine the parameters of the models adjusted to data by logistic regression or Bayesian network, and the second was used to compare the performances of the models using receiver operating characteristics (ROC) curves. IgAN was found (on pathology) in 44 patients. Areas under the ROC curves provided by both methods were highly significant but not different from each other. Based on the highest Youden indices, sensitivity reached (100% versus 67%) and specificity (73% versus 95%) using the Bayesian network and logistic regression, respectively. A Bayesian network is at least as efficient as logistic regression to estimate the probability of a patient suffering IgAN, using simple clinical and biological data obtained during consultation. PMID:24328031
77 FR 46653 - Defense Logistics Agency Privacy Program
Federal Register 2010, 2011, 2012, 2013, 2014
2012-08-06
... of the Secretary 32 CFR Part 323 RIN 0790-AI86 Defense Logistics Agency Privacy Program AGENCY: Defense Logistics Agency, DoD. ACTION: Proposed rule with request for comments. SUMMARY: The Defense Logistics Agency (DLA) is proposing to amend the DLA Privacy Program Regulation. The DLA Privacy...
Using Dominance Analysis to Determine Predictor Importance in Logistic Regression
ERIC Educational Resources Information Center
Azen, Razia; Traxel, Nicole
2009-01-01
This article proposes an extension of dominance analysis that allows researchers to determine the relative importance of predictors in logistic regression models. Criteria for choosing logistic regression R[superscript 2] analogues were determined and measures were selected that can be used to perform dominance analysis in logistic regression. A…
The dynamics of coupled logistic social groups
NASA Astrophysics Data System (ADS)
McCartney, Mark; Glass, David H.
2015-06-01
A society made up of a network of social groups is investigated. Each group is partitioned into two mutually exclusive subsets with the movement of members between the two subsets being modelled via a logistic-like equation. We consider various ways in which the groups in the network may influence each other, via both group size and the utility groups place on the possible subsets. Scenarios where social groups act as 'agenda setters' for the rest of the society are considered. A number of analytic and numerical results are presented.
Iezzoni, L I; Ash, A S; Shwartz, M; Daley, J; Hughes, J S; Mackiernan, Y D
1996-01-01
OBJECTIVES: This research examined whether judgments about a hospital's risk-adjusted mortality performance are affected by the severity-adjustment method. METHODS: Data came from 100 acute care hospitals nationwide and 11880 adults admitted in 1991 for acute myocardial infarction. Ten severity measures were used in separate multivariable logistic models predicting in-hospital death. Observed-to-expected death rates and z scores were calculated with each severity measure for each hospital. RESULTS: Unadjusted mortality rates for the 100 hospitals ranged from 4.8% to 26.4%. For 32 hospitals, observed mortality rates differed significantly from expected rates for 1 or more, but not for all 10, severity measures. Agreement between pairs of severity measures on whether hospitals were flagged as statistical mortality outliers ranged from fair to good. Severity measures based on medical records frequently disagreed with measures based on discharge abstracts. CONCLUSIONS: Although the 10 severity measures agreed about relative hospital performance more often than would be expected by chance, assessments of individual hospital mortality rates varied by different severity-adjustment methods. PMID:8876505
Supporting Regularized Logistic Regression Privately and Efficiently.
Li, Wenfa; Liu, Hongzhe; Yang, Peng; Xie, Wei
2016-01-01
As one of the most popular statistical and machine learning models, logistic regression with regularization has found wide adoption in biomedicine, social sciences, information technology, and so on. These domains often involve data of human subjects that are contingent upon strict privacy regulations. Concerns over data privacy make it increasingly difficult to coordinate and conduct large-scale collaborative studies, which typically rely on cross-institution data sharing and joint analysis. Our work here focuses on safeguarding regularized logistic regression, a widely-used statistical model while at the same time has not been investigated from a data security and privacy perspective. We consider a common use scenario of multi-institution collaborative studies, such as in the form of research consortia or networks as widely seen in genetics, epidemiology, social sciences, etc. To make our privacy-enhancing solution practical, we demonstrate a non-conventional and computationally efficient method leveraging distributing computing and strong cryptography to provide comprehensive protection over individual-level and summary data. Extensive empirical evaluations on several studies validate the privacy guarantee, efficiency and scalability of our proposal. We also discuss the practical implications of our solution for large-scale studies and applications from various disciplines, including genetic and biomedical studies, smart grid, network analysis, etc. PMID:27271738
Reducing food losses by intelligent food logistics
Jedermann, Reiner; Nicometo, Mike; Uysal, Ismail; Lang, Walter
2014-01-01
The need to feed an ever-increasing world population makes it obligatory to reduce the millions of tons of avoidable perishable waste along the food supply chain. A considerable share of these losses is caused by non-optimal cold chain processes and management. This Theme Issue focuses on technologies, models and applications to monitor changes in the product shelf life, defined as the time remaining until the quality of a food product drops below an acceptance limit, and to plan successive chain processes and logistics accordingly to uncover and prevent invisible or latent losses in product quality, especially following the first-expired-first-out strategy for optimized matching between the remaining shelf life and the expected transport duration. This introductory article summarizes the key findings of this Theme Issue, which brings together research study results from around the world to promote intelligent food logistics. The articles include three case studies on the cold chain for berries, bananas and meat and an overview of different post-harvest treatments. Further contributions focus on the required technical solutions, such as the wireless sensor and communication system for remote quality supervision, gas sensors to detect ethylene as an indicator of unwanted ripening and volatile components to indicate mould infections. The final section of this introduction discusses how improvements in food quality can be targeted by strategic changes in the food chain. PMID:24797131
Electronically-implemented coupled logistic maps
NASA Astrophysics Data System (ADS)
L'Her, Alexandre; Amil, Pablo; Rubido, Nicolás; Marti, Arturo C.; Cabeza, Cecilia
2016-03-01
The logistic map is a paradigmatic dynamical system originally conceived to model the discrete-time demographic growth of a population, which shockingly, shows that discrete chaos can emerge from trivial low-dimensional non-linear dynamics. In this work, we design and characterize a simple, low-cost, easy-to-handle, electronic implementation of the logistic map. In particular, our implementation allows for straightforward circuit-modifications to behave as different one-dimensional discrete-time systems. Also, we design a coupling block in order to address the behavior of two coupled maps, although, our design is unrestricted to the discrete-time system implementation and it can be generalized to handle coupling between many dynamical systems, as in a complex system. Our findings show that the isolated and coupled maps' behavior has a remarkable agreement between the experiments and the simulations, even when fine-tuning the parameters with a resolution of ~10-3. We support these conclusions by comparing the Lyapunov exponents, periodicity of the orbits, and phase portraits of the numerical and experimental data for a wide range of coupling strengths and map's parameters.
Reducing food losses by intelligent food logistics.
Jedermann, Reiner; Nicometo, Mike; Uysal, Ismail; Lang, Walter
2014-06-13
The need to feed an ever-increasing world population makes it obligatory to reduce the millions of tons of avoidable perishable waste along the food supply chain. A considerable share of these losses is caused by non-optimal cold chain processes and management. This Theme Issue focuses on technologies, models and applications to monitor changes in the product shelf life, defined as the time remaining until the quality of a food product drops below an acceptance limit, and to plan successive chain processes and logistics accordingly to uncover and prevent invisible or latent losses in product quality, especially following the first-expired-first-out strategy for optimized matching between the remaining shelf life and the expected transport duration. This introductory article summarizes the key findings of this Theme Issue, which brings together research study results from around the world to promote intelligent food logistics. The articles include three case studies on the cold chain for berries, bananas and meat and an overview of different post-harvest treatments. Further contributions focus on the required technical solutions, such as the wireless sensor and communication system for remote quality supervision, gas sensors to detect ethylene as an indicator of unwanted ripening and volatile components to indicate mould infections. The final section of this introduction discusses how improvements in food quality can be targeted by strategic changes in the food chain. PMID:24797131
Supporting Regularized Logistic Regression Privately and Efficiently
Li, Wenfa; Liu, Hongzhe; Yang, Peng; Xie, Wei
2016-01-01
As one of the most popular statistical and machine learning models, logistic regression with regularization has found wide adoption in biomedicine, social sciences, information technology, and so on. These domains often involve data of human subjects that are contingent upon strict privacy regulations. Concerns over data privacy make it increasingly difficult to coordinate and conduct large-scale collaborative studies, which typically rely on cross-institution data sharing and joint analysis. Our work here focuses on safeguarding regularized logistic regression, a widely-used statistical model while at the same time has not been investigated from a data security and privacy perspective. We consider a common use scenario of multi-institution collaborative studies, such as in the form of research consortia or networks as widely seen in genetics, epidemiology, social sciences, etc. To make our privacy-enhancing solution practical, we demonstrate a non-conventional and computationally efficient method leveraging distributing computing and strong cryptography to provide comprehensive protection over individual-level and summary data. Extensive empirical evaluations on several studies validate the privacy guarantee, efficiency and scalability of our proposal. We also discuss the practical implications of our solution for large-scale studies and applications from various disciplines, including genetic and biomedical studies, smart grid, network analysis, etc. PMID:27271738
NASA Technical Reports Server (NTRS)
Palguta, T.; Bradley, W.; Stockton, T.
1988-01-01
The purpose is to outline an Office of Space Science and Applications (OSSA) integrated logistics support strategy that will ensure effective logistics support of OSSA payloads at an affordable life-cycle cost. Program objectives, organizational relationships, and implementation of the logistics strategy are discussed.
Complex Logistics Strategy for Industrial Companies in Slovakia
NASA Astrophysics Data System (ADS)
Horňáková, Natália; Hudák, Ján; Vidová, Helena
2014-12-01
Presented paper is a part of the dissertation thesis titled as "A proposal to develop Complex Logistics Strategy for industrial companies. The result of the thesis will be a methodology for developing a Complex Logistics Strategy for industrial companies in Slovakia. The main aim of the paper is to present some trends and strategies in Logistics and clarify the need of resolving the issue of Logistics Strategy based on the theoretical knowledge, case studies and analysis of current state of Logistics Strategies in industrial companies in Slovakia and other European countries.
Flexible use and technique extension of logistics management
NASA Astrophysics Data System (ADS)
Xiong, Furong
2011-10-01
As we all know, the origin of modern logistics was in the United States, developed in Japan, became mature in Europe, and expanded in China. This is a historical development of the modern logistics recognized track. Due to China's economic and technological development, and with the construction of Shanghai International Shipping Center and Shanghai Yangshan International Deepwater development, China's modern logistics industry will attain a leap-forward development of a strong pace, and will also catch up with developed countries in the Western modern logistics level. In this paper, the author explores the flexibility of China's modern logistics management techniques to extend the use, and has certain practical and guidance significances.
Space Shuttle Orbiter logistics - Managing in a dynamic environment
NASA Technical Reports Server (NTRS)
Renfroe, Michael B.; Bradshaw, Kimberly
1990-01-01
The importance and methods of monitoring logistics vital signs, logistics data sources and acquisition, and converting data into useful management information are presented. With the launch and landing site for the Shuttle Orbiter project at the Kennedy Space Center now totally responsible for its own supportability posture, it is imperative that logistics resource requirements and management be continually monitored and reassessed. Detailed graphs and data concerning various aspects of logistics activities including objectives, inventory operating levels, customer environment, and data sources are provided. Finally, some lessons learned from the Shuttle Orbiter project and logistics options which should be considered by other space programs are discussed.
Logistics of Guinea Worm Disease Eradication in South Sudan
Jones, Alexander H.; Becknell, Steven; Withers, P. Craig; Ruiz-Tiben, Ernesto; Hopkins, Donald R.; Stobbelaar, David; Makoy, Samuel Yibi
2014-01-01
From 2006 to 2012, the South Sudan Guinea Worm Eradication Program reduced new Guinea worm disease (dracunculiasis) cases by over 90%, despite substantial programmatic challenges. Program logistics have played a key role in program achievements to date. The program uses disease surveillance and program performance data and integrated technical–logistical staffing to maintain flexible and effective logistical support for active community-based surveillance and intervention delivery in thousands of remote communities. Lessons learned from logistical design and management can resonate across similar complex surveillance and public health intervention delivery programs, such as mass drug administration for the control of neglected tropical diseases and other disease eradication programs. Logistical challenges in various public health scenarios and the pivotal contribution of logistics to Guinea worm case reductions in South Sudan underscore the need for additional inquiry into the role of logistics in public health programming in low-income countries. PMID:24445199
Analysis of Logistics in Support of a Human Lunar Outpost
NASA Technical Reports Server (NTRS)
Cirillo, William; Earle, Kevin; Goodliff, Kandyce; Reeves, j. D.; Andrashko, Mark; Merrill, R. Gabe; Stromgren, Chel
2008-01-01
Strategic level analysis of the integrated behavior of lunar transportation system and lunar surface system architecture options is performed to inform NASA Constellation Program senior management on the benefit, viability, affordability, and robustness of system design choices. This paper presents an overview of the approach used to perform the campaign (strategic) analysis, with an emphasis on the logistics modeling and the impacts of logistics resupply on campaign behavior. An overview of deterministic and probabilistic analysis approaches is provided, with a discussion of the importance of each approach to understanding the integrated system behavior. The logistics required to support lunar surface habitation are analyzed from both 'macro-logistics' and 'micro-logistics' perspectives, where macro-logistics focuses on the delivery of goods to a destination and micro-logistics focuses on local handling of re-supply goods at a destination. An example campaign is provided to tie the theories of campaign analysis to results generation capabilities.
Delay Adjusted Incidence Infographic
This Infographic shows the National Cancer Institute SEER Incidence Trends. The graphs show the Average Annual Percent Change (AAPC) 2002-2011. For Men, Thyroid: 5.3*,Liver & IBD: 3.6*, Melanoma: 2.3*, Kidney: 2.0*, Myeloma: 1.9*, Pancreas: 1.2*, Leukemia: 0.9*, Oral Cavity: 0.5, Non-Hodgkin Lymphoma: 0.3*, Esophagus: -0.1, Brain & ONS: -0.2*, Bladder: -0.6*, All Sites: -1.1*, Stomach: -1.7*, Larynx: -1.9*, Prostate: -2.1*, Lung & Bronchus: -2.4*, and Colon & Rectum: -3/0*. For Women, Thyroid: 5.8*, Liver & IBD: 2.9*, Myeloma: 1.8*, Kidney: 1.6*, Melanoma: 1.5, Corpus & Uterus: 1.3*, Pancreas: 1.1*, Leukemia: 0.6*, Brain & ONS: 0, Non-Hodgkin Lymphoma: -0.1, All Sites: -0.1, Breast: -0.3, Stomach: -0.7*, Oral Cavity: -0.7*, Bladder: -0.9*, Ovary: -0.9*, Lung & Bronchus: -1.0*, Cervix: -2.4*, and Colon & Rectum: -2.7*. * AAPC is significantly different from zero (p<.05). Rates were adjusted for reporting delay in the registry. www.cancer.gov Source: Special section of the Annual Report to the Nation on the Status of Cancer, 1975-2011.
48 CFR 5416.203 - Fixed-price contracts with economic price adjustment.
Code of Federal Regulations, 2013 CFR
2013-10-01
... 48 Federal Acquisition Regulations System 7 2013-10-01 2012-10-01 true Fixed-price contracts with economic price adjustment. 5416.203 Section 5416.203 Federal Acquisition Regulations System DEFENSE LOGISTICS AGENCY, DEPARTMENT OF DEFENSE TYPES OF CONTRACTS Fixed Price Contracts 5416.203...
48 CFR 5416.203 - Fixed-price contracts with economic price adjustment.
Code of Federal Regulations, 2014 CFR
2014-10-01
... 48 Federal Acquisition Regulations System 7 2014-10-01 2014-10-01 false Fixed-price contracts with economic price adjustment. 5416.203 Section 5416.203 Federal Acquisition Regulations System DEFENSE LOGISTICS AGENCY, DEPARTMENT OF DEFENSE TYPES OF CONTRACTS Fixed Price Contracts 5416.203...
48 CFR 5416.203 - Fixed-price contracts with economic price adjustment.
Code of Federal Regulations, 2012 CFR
2012-10-01
... 48 Federal Acquisition Regulations System 7 2012-10-01 2012-10-01 false Fixed-price contracts with economic price adjustment. 5416.203 Section 5416.203 Federal Acquisition Regulations System DEFENSE LOGISTICS AGENCY, DEPARTMENT OF DEFENSE TYPES OF CONTRACTS Fixed Price Contracts 5416.203...
48 CFR 5416.203 - Fixed-price contracts with economic price adjustment.
Code of Federal Regulations, 2010 CFR
2010-10-01
... 48 Federal Acquisition Regulations System 7 2010-10-01 2010-10-01 false Fixed-price contracts with economic price adjustment. 5416.203 Section 5416.203 Federal Acquisition Regulations System DEFENSE LOGISTICS AGENCY, DEPARTMENT OF DEFENSE TYPES OF CONTRACTS Fixed Price Contracts 5416.203...
Stochastic dynamics and logistic population growth.
Méndez, Vicenç; Assaf, Michael; Campos, Daniel; Horsthemke, Werner
2015-06-01
The Verhulst model is probably the best known macroscopic rate equation in population ecology. It depends on two parameters, the intrinsic growth rate and the carrying capacity. These parameters can be estimated for different populations and are related to the reproductive fitness and the competition for limited resources, respectively. We investigate analytically and numerically the simplest possible microscopic scenarios that give rise to the logistic equation in the deterministic mean-field limit. We provide a definition of the two parameters of the Verhulst equation in terms of microscopic parameters. In addition, we derive the conditions for extinction or persistence of the population by employing either the momentum-space spectral theory or the real-space Wentzel-Kramers-Brillouin approximation to determine the probability distribution function and the mean time to extinction of the population. Our analytical results agree well with numerical simulations. PMID:26172687
Green Packaging Management of Logistics Enterprises
NASA Astrophysics Data System (ADS)
Zhang, Guirong; Zhao, Zongjian
From the connotation of green logistics management, we discuss the principles of green packaging, and from the two levels of government and enterprises, we put forward a specific management strategy. The management of green packaging can be directly and indirectly promoted by laws, regulations, taxation, institutional and other measures. The government can also promote new investment to the development of green packaging materials, and establish specialized institutions to identify new packaging materials, standardization of packaging must also be accomplished through the power of the government. Business units of large scale through the packaging and container-based to reduce the use of packaging materials, develop and use green packaging materials and easy recycling packaging materials for proper packaging.
Space station synergetic RAM-logistics analysis
NASA Technical Reports Server (NTRS)
Dejulio, Edmund T.; Leet, Joel H.
1988-01-01
NASA's Space Station Maintenance Planning and Analysis (MP&A) Study is a step in the overall Space Station Program to define optimum approaches for on-orbit maintenance planning and logistics support. The approach used in the MP&A study and the analysis process used are presented. Emphasis is on maintenance activities and processes that can be accomplished on orbit within the known design and support constraints of the Space Station. From these analyses, recommendations for maintainability/maintenance requirements are established. The ultimate goal of the study is to reduce on-orbit maintenance requirements to a practical and safe minimum, thereby conserving crew time for productive endeavors. The reliability, availability, and maintainability (RAM) and operations performance evaluation models used were assembled and developed as part of the MP&A study and are described. A representative space station system design is presented to illustrate the analysis process.
Stochastic dynamics and logistic population growth
NASA Astrophysics Data System (ADS)
Méndez, Vicenç; Assaf, Michael; Campos, Daniel; Horsthemke, Werner
2015-06-01
The Verhulst model is probably the best known macroscopic rate equation in population ecology. It depends on two parameters, the intrinsic growth rate and the carrying capacity. These parameters can be estimated for different populations and are related to the reproductive fitness and the competition for limited resources, respectively. We investigate analytically and numerically the simplest possible microscopic scenarios that give rise to the logistic equation in the deterministic mean-field limit. We provide a definition of the two parameters of the Verhulst equation in terms of microscopic parameters. In addition, we derive the conditions for extinction or persistence of the population by employing either the momentum-space spectral theory or the real-space Wentzel-Kramers-Brillouin approximation to determine the probability distribution function and the mean time to extinction of the population. Our analytical results agree well with numerical simulations.
Development of a comprehensive logistics and warfighting simulation system.
Hummel, J. R.
1998-08-12
An efficient logistics system is critical to the success of military operations. Recently, the Department of Defense (DoD) has begun to move from a ''just in case'' logistics system that relies on large stores of inventoried materials toward a ''just in time'' system based on obtaining and delivering supplies when and where they are needed. For this new logistics concept to operate smoothly and responsively and be highly robust, one must understand the interrelationships between warfighting and logistics, such as the impact of losses of logistics links/nodes and the changing pace of warfighting operations. Two DoD programs, the Distributed Intelligent Agents for Logistics (DIAL) and the Warfighting Logistics Technology and Assessment Environment (WLTAE), are focusing on different aspects of this problem. These programs are being integrated to develop a Comprehensive Logistics and Warfighting System (CLAWS) that can be used to address a variety of different logistics applications in the military arena. In this paper, we describe how CLAWS will be developed, including the development of a generalized Federation Object Model that could be used in a variety of logistics and military operations applications.
Federal Register 2010, 2011, 2012, 2013, 2014
2013-12-09
...; Comment Request; Logistics Capability Assistance Tool (LCAT) AGENCY: Federal Emergency Management Agency... accordance with the Paperwork Reduction Act of 1995, this notice seeks comments concerning the Logistics... Repass, Program Analyst, Logistics Management Directorate, Logistics Plans & Exercises Division,...
Federal Register 2010, 2011, 2012, 2013, 2014
2013-06-24
... Tesoro Corporation and Tesoro Logistics Operations LLC; Analysis of Proposed Agreement Containing Consent... Tesoro Logistics Operations LLC (``Respondents''). On December 6, 2012, Respondents executed related.... Tesoro Logistics Operations LLC Tesoro Logistics Operations LLC, a limited liability company, is a...
Federal Register 2010, 2011, 2012, 2013, 2014
2011-05-18
... of the Secretary Defense Logistics Agency Revised Regulation 1000.22, Environmental Considerations in Defense Logistics Agency Actions AGENCY: Defense Logistics Agency, Department of Defense. ACTION: Notice of Availability (NOA) of Revised Defense Logistics Agency Regulation. SUMMARY: The Defense...
Federal Register 2010, 2011, 2012, 2013, 2014
2013-10-22
... Rate Adjustment AGENCY: Postal Regulatory Commission. ACTION: Notice. SUMMARY: The Commission is noticing a recent Postal Service filing seeking postal rate adjustments based on exigent circumstances... On September 26, 2013, the Postal Service filed an exigent rate request with the Commission...
Adjustable holder for transducer mounting
NASA Technical Reports Server (NTRS)
Deotsch, R. C.
1980-01-01
Positioning of acoustic sensor, strain gage, or similar transducer is facilitated by adjustable holder. Developed for installation on Space Shuttle, it includes springs for maintaining uniform load on transducer with adjustable threaded cap for precisely controlling position of sensor with respect to surrounding structure.
Spousal Adjustment to Myocardial Infarction.
ERIC Educational Resources Information Center
Ziglar, Elisa J.
This paper reviews the literature on the stresses and coping strategies of spouses of patients with myocardial infarction (MI). It attempts to identify specific problem areas of adjustment for the spouse and to explore the effects of spousal adjustment on patient recovery. Chapter one provides an overview of the importance in examining the…
Mood Adjustment via Mass Communication.
ERIC Educational Resources Information Center
Knobloch, Silvia
2003-01-01
Proposes and experimentally tests mood adjustment approach, complementing mood management theory. Discusses how results regarding self-exposure across time show that patterns of popular music listening among a group of undergraduate students differ with initial mood and anticipation, lending support to mood adjustment hypotheses. Describes how…
Space Station logistics policy - Risk management from the top down
NASA Technical Reports Server (NTRS)
Paules, Granville; Graham, James L., Jr.
1990-01-01
Considerations are presented in the area of risk management specifically relating to logistics and system supportability. These considerations form a basis for confident application of concurrent engineering principles to a development program, aiming at simultaneous consideration of support and logistics requirements within the engineering process as the system concept and designs develop. It is shown that, by applying such a process, the chances of minimizing program logistics and supportability risk in the long term can be improved. The problem of analyzing and minimizing integrated logistics risk for the Space Station Freedom Program is discussed.
Use of Ubiquitous Technologies in Military Logistic System in Iran
NASA Astrophysics Data System (ADS)
Jafari, P.; Sadeghi-Niaraki, A.
2013-09-01
This study is about integration and evaluation of RFID and ubiquitous technologies in military logistic system management. Firstly, supply chain management and the necessity of a revolution in logistic systems especially in military area, are explained. Secondly RFID and ubiquitous technologies and the advantages of their use in supply chain management are introduced. Lastly a system based on these technologies for controlling and increasing the speed and accuracy in military logistic system in Iran with its unique properties, is presented. The system is based on full control of military logistics (supplies) from the time of deployment to replenishment using sensor network, ubiquitous and RFID technologies.
Logistics Reduction and Repurposing Beyond Low Earth Orbit
NASA Technical Reports Server (NTRS)
Broyan, James Lee, Jr.; Ewert, Michael K.
2011-01-01
All human space missions, regardless of destination, require significant logistical mass and volume that is strongly proportional to mission duration. Anything that can be done to reduce initial mass and volume of supplies or reuse items that have been launched will be very valuable. Often, the logistical items require disposal and represent a trash burden. Utilizing systems engineering to analyze logistics from cradle-to-grave and then to potential reuse, can minimize logistics contributions to total mission architecture mass. In NASA's Advanced Exploration Systems Logistics Reduction and Repurposing Project , various tasks will reduce the intrinsic mass of logistical packaging, enable reuse and repurposing of logistical packaging and carriers for other habitation, life support, crew health, and propulsion functions, and reduce or eliminate the nuisances aspects of trash at the same time. Repurposing reduces the trash burden and eliminates the need for hardware whose function can be provided by use of spent logistic items. However, these reuse functions need to be identified and built into future logical systems to enable them to effectively have a secondary function. These technologies and innovations will help future logistic systems to support multiple exploration missions much more efficiently.
Effect of randomness in logistic maps
NASA Astrophysics Data System (ADS)
Khaleque, Abdul; Sen, Parongama
2015-01-01
We study a random logistic map xt+1 = atxt[1 - xt] where at are bounded (q1 ≤ at ≤ q2), random variables independently drawn from a distribution. xt does not show any regular behavior in time. We find that xt shows fully ergodic behavior when the maximum allowed value of at is 4. However
Nowcasting sunshine number using logistic modeling
NASA Astrophysics Data System (ADS)
Brabec, Marek; Badescu, Viorel; Paulescu, Marius
2013-04-01
In this paper, we present a formalized approach to statistical modeling of the sunshine number, binary indicator of whether the Sun is covered by clouds introduced previously by Badescu (Theor Appl Climatol 72:127-136, 2002). Our statistical approach is based on Markov chain and logistic regression and yields fully specified probability models that are relatively easily identified (and their unknown parameters estimated) from a set of empirical data (observed sunshine number and sunshine stability number series). We discuss general structure of the model and its advantages, demonstrate its performance on real data and compare its results to classical ARIMA approach as to a competitor. Since the model parameters have clear interpretation, we also illustrate how, e.g., their inter-seasonal stability can be tested. We conclude with an outlook to future developments oriented to construction of models allowing for practically desirable smooth transition between data observed with different frequencies and with a short discussion of technical problems that such a goal brings.
Source Recertification, Refurbishment, and Transfer Logistics
Gastelum, Zoe N.; Duckworth, Leesa L.; Greenfield, Bryce A.; Doll, Stephanie R.
2013-09-01
The 2012 Gap Analysis of Department of Energy Radiological Sealed Sources, Standards, and Materials for Safeguards Technology Development [1] report, and the subsequent Reconciliation of Source Needs and Surpluses across the U.S. Department of Energy National Laboratory Complex [2] report, resulted in the identification of 33 requests for nuclear or radiological sealed sources for which there was potentially available, suitable material from within the U.S. Department of Energy (DOE) complex to fill the source need. Available, suitable material was defined by DOE laboratories as material slated for excess, or that required recertification or refurbishment before being used for safeguards technology development. This report begins by outlining the logistical considerations required for the shipment of nuclear and radiological materials between DOE laboratories. Then, because of the limited need for transfer of matching sources, the report also offers considerations for an alternative approach – the shipment of safeguards equipment between DOE laboratories or technology testing centers. Finally, this report addresses repackaging needs for the two source requests for which there was available, suitable material within the DOE complex.
Final adjustments in payload bay prior to door closure
NASA Technical Reports Server (NTRS)
2001-01-01
Final adjustments in payload bay prior to door closure KSC-01PD-1732 KENNEDY SPACE CENTER, Fla. - A worker makes a final adjustment in the payload bay of Space Shuttle Endeavour before door closure. Inside the bay is the Multi-Purpose Logistics Module Raffaello (foreground), carrying supplies, equipment and experiments for the International Space Station. Sharing the payload bay are several carriers with varying experiment packages, such as Starshine-2, a Get-Away Special. Endeavour is scheduled to launch Nov. 29 on this first Utilization Flight to the International Space Station. Endeavour will also carry the replacement Expedition 4 crew to the Station and return to Earth with the Expedition 3 crew.
ERIC Educational Resources Information Center
Shih, Ching-Lin; Liu, Tien-Hsiang; Wang, Wen-Chung
2014-01-01
The simultaneous item bias test (SIBTEST) method regression procedure and the differential item functioning (DIF)-free-then-DIF strategy are applied to the logistic regression (LR) method simultaneously in this study. These procedures are used to adjust the effects of matching true score on observed score and to better control the Type I error…
Logistics engineering education from the point of view environment
NASA Astrophysics Data System (ADS)
Bányai, Ágota
2010-05-01
A new field of MSc programme offered by the Faculty of Mechanical Engineering and Informatics of the University of Miskolc is represented by the programme in logistics engineering. The Faculty has always laid great emphasis on assigning processes connected with environment protection and globalisation issues the appropriate weight in its programmes. This is based on the fact that the Faculty has initiated and been involved in a great number of research and development projects with a substantial emphasis on the fundamental principles of sustainable development. The objective of the programme of logistics engineering is to train engineers who, in possession of the science, engineering, economic, informatics and industrial, transportation technological knowledge related to the professional field of logistics, are able to analyse, design, organise, and control logistics processes and systems (freight transportation, materials handling, storage, commissioning, loading, purchasing, distribution and waste management) as well as to design and develop machinery and equipment as the elements of logistic systems and also to be involved in their manufacture and quality control and are able to control their operation. The programme prepares its students for performing the logistics management tasks in a company, for creative participation in solving research and development problems in logistics and for pursuing logistics studies in doctoral programmes. There are several laboratories available for practice-oriented training. The 'Integrated Logistics Laboratory' consists of various fixed and mobile, real industrial, i.e. not model-level equipment, the integration of which in one system facilitates not only the presentation, examination and development of the individual self-standing facilities, but the study of their interaction as well in terms of mechatronics, engineering, control engineering, informatics, identification technology and logistics. The state
Pattern formation, logistics, and maximum path probability
NASA Astrophysics Data System (ADS)
Kirkaldy, J. S.
1985-05-01
The concept of pattern formation, which to current researchers is a synonym for self-organization, carries the connotation of deductive logic together with the process of spontaneous inference. Defining a pattern as an equivalence relation on a set of thermodynamic objects, we establish that a large class of irreversible pattern-forming systems, evolving along idealized quasisteady paths, approaches the stable steady state as a mapping upon the formal deductive imperatives of a propositional function calculus. In the preamble the classical reversible thermodynamics of composite systems is analyzed as an externally manipulated system of space partitioning and classification based on ideal enclosures and diaphragms. The diaphragms have discrete classification capabilities which are designated in relation to conserved quantities by descriptors such as impervious, diathermal, and adiabatic. Differentiability in the continuum thermodynamic calculus is invoked as equivalent to analyticity and consistency in the underlying class or sentential calculus. The seat of inference, however, rests with the thermodynamicist. In the transition to an irreversible pattern-forming system the defined nature of the composite reservoirs remains, but a given diaphragm is replaced by a pattern-forming system which by its nature is a spontaneously evolving volume partitioner and classifier of invariants. The seat of volition or inference for the classification system is thus transferred from the experimenter or theoretician to the diaphragm, and with it the full deductive facility. The equivalence relations or partitions associated with the emerging patterns may thus be associated with theorems of the natural pattern-forming calculus. The entropy function, together with its derivatives, is the vehicle which relates the logistics of reservoirs and diaphragms to the analog logistics of the continuum. Maximum path probability or second-order differentiability of the entropy in isolation are
Logistic Regression: Going beyond Point-and-Click.
ERIC Educational Resources Information Center
King, Jason E.
A review of the literature reveals that important statistical algorithms and indices pertaining to logistic regression are being underused. This paper describes logistic regression in comparison with discriminant analysis and linear regression, and suggests that some techniques only accessible through computer syntax should be consulted in…
Bayesian Estimation of the Logistic Positive Exponent IRT Model
ERIC Educational Resources Information Center
Bolfarine, Heleno; Bazan, Jorge Luis
2010-01-01
A Bayesian inference approach using Markov Chain Monte Carlo (MCMC) is developed for the logistic positive exponent (LPE) model proposed by Samejima and for a new skewed Logistic Item Response Theory (IRT) model, named Reflection LPE model. Both models lead to asymmetric item characteristic curves (ICC) and can be appropriate because a symmetric…
A Model for Logistics Systems Engineering Management Education in Europe.
ERIC Educational Resources Information Center
Naim, M.; Lalwani, C.; Fortuin, L.; Schmidt, T.; Taylor, J.; Aronsson, H.
2000-01-01
Presents the need for a systems and process perspective of logistics, and develops a template for a logistics education course. The template addresses functional, process, and supply chain needs and was developed by a number of university partners with core skills in different traditional disciplines. (Contains 31 references.) (Author/WRM)
Preliminary analysis of an integrated logistics system for OSSA payloads
NASA Technical Reports Server (NTRS)
Palguta, T.; Bradley, W.; Stockton, T.
1988-01-01
The results of studies of the Office of Space Science and Applications' (OSSA) need for an integrated logistics system to support OSSA payloads, whether attached to the Space Station or free-flying are detailed. An executive summary, the integrated logistics support strategy, preparation of planning documents and a supportability analysis of the 1.8 meter centrifuge are discussed.
The Impact of Logistical Resources on Prereferral Team Acceptability
ERIC Educational Resources Information Center
Yetter, Georgette; Doll, Beth
2007-01-01
This study investigated the impact of logistical resources on the acceptability of student assistance team consultation to school staff. Elementary and middle school staff (N=113) completed a measure of the acceptability of prereferral intervention team procedures while also rating the importance of five logistical supports for effective team…
Logistics Reduction and Repurposing Beyond Low Earth Orbit
NASA Technical Reports Server (NTRS)
Ewert, Michael K.; Broyan, James L., Jr.
2012-01-01
All human space missions, regardless of destination, require significant logistical mass and volume that is strongly proportional to mission duration. Anything that can be done to reduce initial mass and volume of supplies or reuse items that have been launched will be very valuable. Often, the logistical items require disposal and represent a trash burden. Logistics contributions to total mission architecture mass can be minimized by considering potential reuse using systems engineering analysis. In NASA's Advanced Exploration Systems "Logistics Reduction and Repurposing Project," various tasks will reduce the intrinsic mass of logistical packaging, enable reuse and repurposing of logistical packaging and carriers for other habitation, life support, crew health, and propulsion functions, and reduce or eliminate the nuisance aspects of trash at the same time. Repurposing reduces the trash burden and eliminates the need for hardware whose function can be provided by use of spent logistical items. However, these reuse functions need to be identified and built into future logical systems to enable them to effectively have a secondary function. These technologies and innovations will help future logistics systems to support multiple exploration missions much more efficiently.