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Sample records for multiple logistic model

  1. Determination of osteoporosis risk factors using a multiple logistic regression model in postmenopausal Turkish women.

    Science.gov (United States)

    Akkus, Zeki; Camdeviren, Handan; Celik, Fatma; Gur, Ali; Nas, Kemal

    2005-09-01

    To determine the risk factors of osteoporosis using a multiple binary logistic regression method and to assess the risk variables for osteoporosis, which is a major and growing health problem in many countries. We presented a case-control study, consisting of 126 postmenopausal healthy women as control group and 225 postmenopausal osteoporotic women as the case group. The study was carried out in the Department of Physical Medicine and Rehabilitation, Dicle University, Diyarbakir, Turkey between 1999-2002. The data from the 351 participants were collected using a standard questionnaire that contains 43 variables. A multiple logistic regression model was then used to evaluate the data and to find the best regression model. We classified 80.1% (281/351) of the participants using the regression model. Furthermore, the specificity value of the model was 67% (84/126) of the control group while the sensitivity value was 88% (197/225) of the case group. We found the distribution of residual values standardized for final model to be exponential using the Kolmogorow-Smirnow test (p=0.193). The receiver operating characteristic curve was found successful to predict patients with risk for osteoporosis. This study suggests that low levels of dietary calcium intake, physical activity, education, and longer duration of menopause are independent predictors of the risk of low bone density in our population. Adequate dietary calcium intake in combination with maintaining a daily physical activity, increasing educational level, decreasing birth rate, and duration of breast-feeding may contribute to healthy bones and play a role in practical prevention of osteoporosis in Southeast Anatolia. In addition, the findings of the present study indicate that the use of multivariate statistical method as a multiple logistic regression in osteoporosis, which maybe influenced by many variables, is better than univariate statistical evaluation.

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

    NARCIS (Netherlands)

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

    2017-01-01

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

  3. Logistic chain modelling

    NARCIS (Netherlands)

    Slats, P.A.; Bhola, B.; Evers, J.J.M.; Dijkhuizen, G.

    1995-01-01

    Logistic chain modelling is very important in improving the overall performance of the total logistic chain. Logistic models provide support for a large range of applications, such as analysing bottlenecks, improving customer service, configuring new logistic chains and adapting existing chains to

  4. VNM: An R Package for Finding Multiple-Objective Optimal Designs for the 4-Parameter Logistic Model

    OpenAIRE

    Hyun, Seung Won; Wong, Weng Kee; Yang, Yarong

    2018-01-01

    A multiple-objective optimal design is useful for dose-response studies because it can incorporate several objectives at the design stage. Objectives can be of varying interests and a properly constructed multiple-objective optimal design can provide user-specified efficiencies, delivering higher efficiencies for the more important objectives. In this work, we introduce the VNM package written in R for finding 3-objective locally optimal designs for the 4-parameter logistic (4PL) model widely...

  5. Multiple logistic regression model of signalling practices of drivers on urban highways

    Science.gov (United States)

    Puan, Othman Che; Ibrahim, Muttaka Na'iya; Zakaria, Rozana

    2015-05-01

    Giving signal is a way of informing other road users, especially to the conflicting drivers, the intention of a driver to change his/her movement course. Other users are exposed to hazard situation and risks of accident if the driver who changes his/her course failed to give signal as required. This paper describes the application of logistic regression model for the analysis of driver's signalling practices on multilane highways based on possible factors affecting driver's decision such as driver's gender, vehicle's type, vehicle's speed and traffic flow intensity. Data pertaining to the analysis of such factors were collected manually. More than 2000 drivers who have performed a lane changing manoeuvre while driving on two sections of multilane highways were observed. Finding from the study shows that relatively a large proportion of drivers failed to give any signals when changing lane. The result of the analysis indicates that although the proportion of the drivers who failed to provide signal prior to lane changing manoeuvre is high, the degree of compliances of the female drivers is better than the male drivers. A binary logistic model was developed to represent the probability of a driver to provide signal indication prior to lane changing manoeuvre. The model indicates that driver's gender, type of vehicle's driven, speed of vehicle and traffic volume influence the driver's decision to provide a signal indication prior to a lane changing manoeuvre on a multilane urban highway. In terms of types of vehicles driven, about 97% of motorcyclists failed to comply with the signal indication requirement. The proportion of non-compliance drivers under stable traffic flow conditions is much higher than when the flow is relatively heavy. This is consistent with the data which indicates a high degree of non-compliances when the average speed of the traffic stream is relatively high.

  6. Use of multiple linear regression and logistic regression models to investigate changes in birthweight for term singleton infants in Scotland.

    Science.gov (United States)

    Bonellie, Sandra R

    2012-10-01

    To illustrate the use of regression and logistic regression models to investigate changes over time in size of babies particularly in relation to social deprivation, age of the mother and smoking. Mean birthweight has been found to be increasing in many countries in recent years, but there are still a group of babies who are born with low birthweights. Population-based retrospective cohort study. Multiple linear regression and logistic regression models are used to analyse data on term 'singleton births' from Scottish hospitals between 1994-2003. Mothers who smoke are shown to give birth to lighter babies on average, a difference of approximately 0.57 Standard deviations lower (95% confidence interval. 0.55-0.58) when adjusted for sex and parity. These mothers are also more likely to have babies that are low birthweight (odds ratio 3.46, 95% confidence interval 3.30-3.63) compared with non-smokers. Low birthweight is 30% more likely where the mother lives in the most deprived areas compared with the least deprived, (odds ratio 1.30, 95% confidence interval 1.21-1.40). Smoking during pregnancy is shown to have a detrimental effect on the size of infants at birth. This effect explains some, though not all, of the observed socioeconomic birthweight. It also explains much of the observed birthweight differences by the age of the mother.   Identifying mothers at greater risk of having a low birthweight baby as important implications for the care and advice this group receives. © 2012 Blackwell Publishing Ltd.

  7. Logistic regression models

    CERN Document Server

    Hilbe, Joseph M

    2009-01-01

    This book really does cover everything you ever wanted to know about logistic regression … with updates available on the author's website. Hilbe, a former national athletics champion, philosopher, and expert in astronomy, is a master at explaining statistical concepts and methods. Readers familiar with his other expository work will know what to expect-great clarity.The book provides considerable detail about all facets of logistic regression. No step of an argument is omitted so that the book will meet the needs of the reader who likes to see everything spelt out, while a person familiar with some of the topics has the option to skip "obvious" sections. The material has been thoroughly road-tested through classroom and web-based teaching. … The focus is on helping the reader to learn and understand logistic regression. The audience is not just students meeting the topic for the first time, but also experienced users. I believe the book really does meet the author's goal … .-Annette J. Dobson, Biometric...

  8. Relative accuracy of spatial predictive models for lynx Lynx canadensis derived using logistic regression-AIC, multiple criteria evaluation and Bayesian approaches

    Directory of Open Access Journals (Sweden)

    Shelley M. ALEXANDER

    2009-02-01

    Full Text Available We compared probability surfaces derived using one set of environmental variables in three Geographic Information Systems (GIS-based approaches: logistic regression and Akaike’s Information Criterion (AIC, Multiple Criteria Evaluation (MCE, and Bayesian Analysis (specifically Dempster-Shafer theory. We used lynx Lynx canadensis as our focal species, and developed our environment relationship model using track data collected in Banff National Park, Alberta, Canada, during winters from 1997 to 2000. The accuracy of the three spatial models were compared using a contingency table method. We determined the percentage of cases in which both presence and absence points were correctly classified (overall accuracy, the failure to predict a species where it occurred (omission error and the prediction of presence where there was absence (commission error. Our overall accuracy showed the logistic regression approach was the most accurate (74.51%. The multiple criteria evaluation was intermediate (39.22%, while the Dempster-Shafer (D-S theory model was the poorest (29.90%. However, omission and commission error tell us a different story: logistic regression had the lowest commission error, while D-S theory produced the lowest omission error. Our results provide evidence that habitat modellers should evaluate all three error measures when ascribing confidence in their model. We suggest that for our study area at least, the logistic regression model is optimal. However, where sample size is small or the species is very rare, it may also be useful to explore and/or use a more ecologically cautious modelling approach (e.g. Dempster-Shafer that would over-predict, protect more sites, and thereby minimize the risk of missing critical habitat in conservation plans[Current Zoology 55(1: 28 – 40, 2009].

  9. Interpreting Multiple Logistic Regression Coefficients in Prospective Observational Studies

    Science.gov (United States)

    1982-11-01

    prompted close examination of the issue at a workshop on hypertriglyceridemia where some of the cautions and perspectives given in this paper were...characteristics. If this is not the interest, then to isolate and-understand the effect of a characteris- tic on CHD when it could be one of several interacting...also easily extended to the case when several independent variables are modeled in a multiple logistic equation. In this instance, if xlx 2,..., x are

  10. Comparing the Discrete and Continuous Logistic Models

    Science.gov (United States)

    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.)

  11. A Solution to Separation and Multicollinearity in Multiple Logistic Regression.

    Science.gov (United States)

    Shen, Jianzhao; Gao, Sujuan

    2008-10-01

    In dementia screening tests, item selection for shortening an existing screening test can be achieved using multiple logistic regression. However, maximum likelihood estimates for such logistic regression models often experience serious bias or even non-existence because of separation and multicollinearity problems resulting from a large number of highly correlated items. Firth (1993, Biometrika, 80(1), 27-38) proposed a penalized likelihood estimator for generalized linear models and it was shown to reduce bias and the non-existence problems. The ridge regression has been used in logistic regression to stabilize the estimates in cases of multicollinearity. However, neither solves the problems for each other. In this paper, we propose a double penalized maximum likelihood estimator combining Firth's penalized likelihood equation with a ridge parameter. We present a simulation study evaluating the empirical performance of the double penalized likelihood estimator in small to moderate sample sizes. We demonstrate the proposed approach using a current screening data from a community-based dementia study.

  12. Quantitative Models for Reverse Logistics

    NARCIS (Netherlands)

    M. Fleischmann (Moritz)

    2000-01-01

    markdownabstractEconomic, marketing, and legislative considerations are increasingly leading companies to take back and recover their products after use. From a logistics perspective, these initiatives give rise to new goods flows from the user back to the producer. The management of these goods

  13. APPLICATION OF MULTIPLE LOGISTIC REGRESSION, BAYESIAN LOGISTIC AND CLASSIFICATION TREE TO IDENTIFY THE SIGNIFICANT FACTORS INFLUENCING CRASH SEVERITY

    Directory of Open Access Journals (Sweden)

    MILAD TAZIK

    2017-11-01

    Full Text Available Identifying cases in which road crashes result in fatality or injury of drivers may help improve their safety. In this study, datasets of crashes happened in TehranQom freeway, Iran, were examined by three models (multiple logistic regression, Bayesian logistic and classification tree to analyse the contribution of several variables to fatal accidents. For multiple logistic regression and Bayesian logistic models, the odds ratio was calculated for each variable. The model which best suited the identification of accident severity was determined based on AIC and DIC criteria. Based on the results of these two models, rollover crashes (OR = 14.58, %95 CI: 6.8-28.6, not using of seat belt (OR = 5.79, %95 CI: 3.1-9.9, exceeding speed limits (OR = 4.02, %95 CI: 1.8-7.9 and being female (OR = 2.91, %95 CI: 1.1-6.1 were the most important factors in fatalities of drivers. In addition, the results of the classification tree model have verified the findings of the other models.

  14. Logistics and Transport - a conceptual model

    DEFF Research Database (Denmark)

    Jespersen, Per Homann; Drewes, Lise

    2004-01-01

    This paper describes how the freight transport sector is influenced by logistical principles of production and distribution. It introduces new ways of understanding freight transport as an integrated part of the changing trends of mobility. By introducing a conceptual model for understanding...... the interaction between logistics and transport, it points at ways to over-come inherent methodological difficulties when studying this relation...

  15. Moment Closure for the Stochastic Logistic Model

    National Research Council Canada - National Science Library

    Singh, Abhyudai; Hespanha, Joao P

    2006-01-01

    ..., which we refer to as the moment closure function. In this paper, a systematic procedure for constructing moment closure functions of arbitrary order is presented for the stochastic logistic model...

  16. Cost Calculation Model for Logistics Service Providers

    Directory of Open Access Journals (Sweden)

    Zoltán Bokor

    2012-11-01

    Full Text Available The exact calculation of logistics costs has become a real challenge in logistics and supply chain management. It is essential to gain reliable and accurate costing information to attain efficient resource allocation within the logistics service provider companies. Traditional costing approaches, however, may not be sufficient to reach this aim in case of complex and heterogeneous logistics service structures. So this paper intends to explore the ways of improving the cost calculation regimes of logistics service providers and show how to adopt the multi-level full cost allocation technique in logistics practice. After determining the methodological framework, a sample cost calculation scheme is developed and tested by using estimated input data. Based on the theoretical findings and the experiences of the pilot project it can be concluded that the improved costing model contributes to making logistics costing more accurate and transparent. Moreover, the relations between costs and performances also become more visible, which enhances the effectiveness of logistics planning and controlling significantly

  17. Linear Logistic Test Modeling with R

    Science.gov (United States)

    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…

  18. Logistics Chains in Freight Transport Modelling

    NARCIS (Netherlands)

    Davydenko, I.Y.

    2015-01-01

    The flow of trade is not equal to transport flows, mainly due to the fact that warehouses and distribution facilities are used as intermediary stops on the way from production locations to the points of consumption or further rework of goods. This thesis proposes a logistics chain model, which

  19. Parameter identification in the logistic STAR model

    DEFF Research Database (Denmark)

    Ekner, Line Elvstrøm; Nejstgaard, Emil

    We propose a new and simple parametrization of the so-called speed of transition parameter of the logistic smooth transition autoregressive (LSTAR) model. The new parametrization highlights that a consequence of the well-known identification problem of the speed of transition parameter is that th...

  20. Planning model of purchasing logistics in outsourcing

    Directory of Open Access Journals (Sweden)

    Igor JAKOMIN

    2014-03-01

    Full Text Available It is often the case that when preparing their offers, potential outsourcers of logistic activities do not thoroughly research all the activities that have an influence on the process of logistics. Consequently, they prepare relatively expensive offers (that can later lead to greater unexpected costs which, in many cases, business partners decide against and persist with their own existing methods of doing business. The original contribution to science in this article is a model that will aid better understanding of dealing with problems and will, in practice, serve as a tool for the successful execution of business offers by outsourcers. Following research we have discovered, and are able to confirm, that despite the high start-up costs of the outsourcing, in the long term the company can reduce logistic costs. The model presented serves as an in-depth analysis of the company which enables the definition of favourable and optimal offers for outsourcing. The model shown helps to minimise the influence of mistrust and emphasises the importance of reducing the logistic costs with outsourcing.

  1. Cloud Shade by Dynamic Logistic Modeling

    Czech Academy of Sciences Publication Activity Database

    Brabec, Marek; Badescu, V.; Paulescu, M.

    2014-01-01

    Roč. 41, č. 6 (2014), s. 1174-1188 ISSN 0266-4763 R&D Projects: GA MŠk LD12009 Grant - others:European Cooperation in Science and Technology(XE) COST ES1002 Institutional support: RVO:67985807 Keywords : clouds * random process * sunshine number * Markovian logistic regression model Subject RIV: BB - Applied Statistics, Operational Research Impact factor: 0.417, year: 2014

  2. Nowcasting sunshine number using logistic modeling

    Czech Academy of Sciences Publication Activity Database

    Brabec, Marek; Badescu, V.; Paulescu, M.

    2013-01-01

    Roč. 120, č. 1-2 (2013), s. 61-71 ISSN 0177-7971 R&D Projects: GA MŠk LD12009 Grant - others:European Cooperation in Science and Technology(XE) COST ES1002 Institutional research plan: CEZ:AV0Z1030915 Keywords : logistic regression * Markov model * sunshine number Subject RIV: BB - Applied Statistics, Operational Research Impact factor: 1.245, year: 2013

  3. Neo-logistic model for the growth of bacteria

    OpenAIRE

    Tashiro, Tohru; Yoshimura, Fujiko

    2017-01-01

    We propose a neo-logistic model that can describe bacterial growth data precisely. This model is not derived by modifying the logistic model formally, but by incorporating the synthesis of inducible enzymes into the logistic model indirectly. Therefore, the meaning of the parameters of the neo-logistic model becomes physically clear. The neo-logistic model can approximate bacterial growth better than models previously presented, and predict the order of the saturated number of bacteria in the...

  4. Logistic map with memory from economic model

    International Nuclear Information System (INIS)

    Tarasova, Valentina V.; Tarasov, Vasily E.

    2017-01-01

    A generalization of the economic model of logistic growth, which takes into account the effects of memory and crises, is suggested. Memory effect means that the economic factors and parameters at any given time depend not only on their values at that time, but also on their values at previous times. For the mathematical description of the memory effects, we use the theory of derivatives of non-integer order. Crises are considered as sharp splashes (bursts) of the price, which are mathematically described by the delta-functions. Using the equivalence of fractional differential equations and the Volterra integral equations, we obtain discrete maps with memory that are exact discrete analogs of fractional differential equations of economic processes. We derive logistic map with memory, its generalizations, and “economic” discrete maps with memory from the fractional differential equations, which describe the economic natural growth with competition, power-law memory and crises.

  5. A robust optimization model for green regional logistics network design with uncertainty in future logistics demand

    Directory of Open Access Journals (Sweden)

    Dezhi Zhang

    2015-12-01

    Full Text Available This article proposes a new model to address the design problem of a sustainable regional logistics network with uncertainty in future logistics demand. In the proposed model, the future logistics demand is assumed to be a random variable with a given probability distribution. A set of chance constraints with regard to logistics service capacity and environmental impacts is incorporated to consider the sustainability of logistics network design. The proposed model is formulated as a two-stage robust optimization problem. The first-stage problem before the realization of future logistics demand aims to minimize a risk-averse objective by determining the optimal location and size of logistics parks with CO2 emission taxes consideration. The second stage after the uncertain logistics demand has been determined is a scenario-based stochastic logistics service route choices equilibrium problem. A heuristic solution algorithm, which is a combination of penalty function method, genetic algorithm, and Gauss–Seidel decomposition approach, is developed to solve the proposed model. An illustrative example is given to show the application of the proposed model and solution algorithm. The findings show that total social welfare of the logistics system depends very much on the level of uncertainty in future logistics demand, capital budget for logistics parks, and confidence levels of the chance constraints.

  6. A Theoretic Model of Transport Logistics Demand

    OpenAIRE

    Natalija Jolić; Nikolina Brnjac; Ivica Oreb

    2006-01-01

    Concerning transport logistics as relation between transportand integrated approaches to logistics, some transport and logisticsspecialists consider the tenn tautological. However,transport is one of the components of logistics, along with inventories,resources, warehousing, infonnation and goods handling.Transport logistics considers wider commercial and operationalframeworks within which the flow of goods is plannedand managed. The demand for transport logistics services canbe valorised as ...

  7. Visualization of logistic algorithm in Wilson model

    Science.gov (United States)

    Glushchenko, A. S.; Rodin, V. A.; Sinegubov, S. V.

    2018-05-01

    Economic order quantity (EOQ), defined by the Wilson's model, is widely used at different stages of production and distribution of different products. It is useful for making decisions in the management of inventories, providing a more efficient business operation and thus bringing more economic benefits. There is a large amount of reference material and extensive computer shells that help solving various logistics problems. However, the use of large computer environments is not always justified and requires special user training. A tense supply schedule in a logistics model is optimal, if, and only if, the planning horizon coincides with the beginning of the next possible delivery. For all other possible planning horizons, this plan is not optimal. It is significant that when the planning horizon changes, the plan changes immediately throughout the entire supply chain. In this paper, an algorithm and a program for visualizing models of the optimal value of supplies and their number, depending on the magnitude of the planned horizon, have been obtained. The program allows one to trace (visually and quickly) all main parameters of the optimal plan on the charts. The results of the paper represent a part of the authors’ research work in the field of optimization of protection and support services of ports in the Russian North.

  8. Logistic Regression Modeling of Diminishing Manufacturing Sources for Integrated Circuits

    National Research Council Canada - National Science Library

    Gravier, Michael

    1999-01-01

    .... The research identified logistic regression as a powerful tool for analysis of DMSMS and further developed twenty models attempting to identify the "best" way to model and predict DMSMS using logistic regression...

  9. Analysis of Jingdong Mall Logistics Distribution Model

    Science.gov (United States)

    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.

  10. Multiple Imputation of a Randomly Censored Covariate Improves Logistic Regression Analysis.

    Science.gov (United States)

    Atem, Folefac D; Qian, Jing; Maye, Jacqueline E; Johnson, Keith A; Betensky, Rebecca A

    2016-01-01

    Randomly censored covariates arise frequently in epidemiologic studies. The most commonly used methods, including complete case and single imputation or substitution, suffer from inefficiency and bias. They make strong parametric assumptions or they consider limit of detection censoring only. We employ multiple imputation, in conjunction with semi-parametric modeling of the censored covariate, to overcome these shortcomings and to facilitate robust estimation. We develop a multiple imputation approach for randomly censored covariates within the framework of a logistic regression model. We use the non-parametric estimate of the covariate distribution or the semiparametric Cox model estimate in the presence of additional covariates in the model. We evaluate this procedure in simulations, and compare its operating characteristics to those from the complete case analysis and a survival regression approach. We apply the procedures to an Alzheimer's study of the association between amyloid positivity and maternal age of onset of dementia. Multiple imputation achieves lower standard errors and higher power than the complete case approach under heavy and moderate censoring and is comparable under light censoring. The survival regression approach achieves the highest power among all procedures, but does not produce interpretable estimates of association. Multiple imputation offers a favorable alternative to complete case analysis and ad hoc substitution methods in the presence of randomly censored covariates within the framework of logistic regression.

  11. Reference model analysis of suitability for logistics management

    Directory of Open Access Journals (Sweden)

    Cezary Mańkowski

    2011-12-01

    Full Text Available Reference models are one of the many instruments aspiring to find into a set of different concepts, methods and techniques used in managing the logistics. Therefore, the aim of this paper is to present the results of assessing the suitability of reference models for solving logistical problems. This evaluation indicates that they are universal, support the realization of all the logistics management function in various areas, such as logistics of manufacturing glass products.

  12. Model performance analysis and model validation in logistic regression

    Directory of Open Access Journals (Sweden)

    Rosa Arboretti Giancristofaro

    2007-10-01

    Full Text Available In this paper a new model validation procedure for a logistic regression model is presented. At first, we illustrate a brief review of different techniques of model validation. Next, we define a number of properties required for a model to be considered "good", and a number of quantitative performance measures. Lastly, we describe a methodology for the assessment of the performance of a given model by using an example taken from a management study.

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

    Science.gov (United States)

    Kim, Yoonsang; Emery, Sherry

    2013-01-01

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

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

    Science.gov (United States)

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

    2013-08-01

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

  15. Logistics of Mathematical Modeling-Focused Projects

    Science.gov (United States)

    Harwood, R. Corban

    2018-01-01

    This article addresses the logistics of implementing projects in an undergraduate mathematics class and is intended both for new instructors and for instructors who have had negative experiences implementing projects in the past. Project implementation is given for both lower- and upper-division mathematics courses with an emphasis on mathematical…

  16. Bayesian Estimation of the Logistic Positive Exponent IRT Model

    Science.gov (United States)

    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…

  17. A Mathematical Model to Improve the Performance of Logistics Network

    Directory of Open Access Journals (Sweden)

    Muhammad Izman Herdiansyah

    2012-01-01

    Full Text Available The role of logistics nowadays is expanding from just providing transportation and warehousing to offering total integrated logistics. To remain competitive in the global market environment, business enterprises need to improve their logistics operations performance. The improvement will be achieved when we can provide a comprehensive analysis and optimize its network performances. In this paper, a mixed integer linier model for optimizing logistics network performance is developed. It provides a single-product multi-period multi-facilities model, as well as the multi-product concept. The problem is modeled in form of a network flow problem with the main objective to minimize total logistics cost. The problem can be solved using commercial linear programming package like CPLEX or LINDO. Even in small case, the solver in Excel may also be used to solve such model.Keywords: logistics network, integrated model, mathematical programming, network optimization

  18. Framework for Modelling Multi-stakeholder City Logistics Domain Using the Agent based Modelling Approach

    NARCIS (Netherlands)

    Anand, Nilesh; van Duin, Ron; Tavasszy, L.A.

    2016-01-01

    Efficiency of city logistics activities suffers due to conflicting personal preferences and distributed decision making by multiple city logistics stakeholders. This is exacerbated by interdependency of city logistics activities, decision making with limited information and stakeholders’ preference

  19. Risk factors for low birth weight according to the multiple logistic regression model. A retrospective cohort study in José María Morelos municipality, Quintana Roo, Mexico.

    Science.gov (United States)

    Franco Monsreal, José; Tun Cobos, Miriam Del Ruby; Hernández Gómez, José Ricardo; Serralta Peraza, Lidia Esther Del Socorro

    2018-01-17

    Low birth weight has been an enigma for science over time. There have been many researches on its causes and its effects. Low birth weight is an indicator that predicts the probability of a child surviving. In fact, there is an exponential relationship between weight deficit, gestational age, and perinatal mortality. Multiple logistic regression is one of the most expressive and versatile statistical instruments available for the analysis of data in both clinical and epidemiology settings, as well as in public health. To assess in a multivariate fashion the importance of 17 independent variables in low birth weight (dependent variable) of children born in the Mayan municipality of José María Morelos, Quintana Roo, Mexico. Analytical observational epidemiological cohort study with retrospective temporality. Births that met the inclusion criteria occurred in the "Hospital Integral Jose Maria Morelos" of the Ministry of Health corresponding to the Maya municipality of Jose Maria Morelos during the period from August 1, 2014 to July 31, 2015. The total number of newborns recorded was 1,147; 84 of which (7.32%) had low birth weight. To estimate the independent association between the explanatory variables (potential risk factors) and the response variable, a multiple logistic regression analysis was performed using the IBM SPSS Statistics 22 software. In ascending numerical order values of odds ratio > 1 indicated the positive contribution of explanatory variables or possible risk factors: "unmarried" marital status (1.076, 95% confidence interval: 0.550 to 2.104); age at menarche ≤ 12 years (1.08, 95% confidence interval: 0.64 to 1.84); history of abortion(s) (1.14, 95% confidence interval: 0.44 to 2.93); maternal weight < 50 kg (1.51, 95% confidence interval: 0.83 to 2.76); number of prenatal consultations ≤ 5 (1.86, 95% confidence interval: 0.94 to 3.66); maternal age ≥ 36 years (3.5, 95% confidence interval: 0.40 to 30.47); maternal age ≤ 19 years (3

  20. Estimating Engineering and Manufacturing Development Cost Risk Using Logistic and Multiple Regression

    National Research Council Canada - National Science Library

    Bielecki, John

    2003-01-01

    .... Previous research has demonstrated the use of a two-step logistic and multiple regression methodology to predicting cost growth produces desirable results versus traditional single-step regression...

  1. City Logistics Modeling Efforts : Trends and Gaps - A Review

    NARCIS (Netherlands)

    Anand, N.R.; Quak, H.J.; Van Duin, J.H.R.; Tavasszy, L.A.

    2012-01-01

    In this paper, we present a review of city logistics modeling efforts reported in the literature for urban freight analysis. The review framework takes into account the diversity and complexity found in the present-day city logistics practice. Next, it covers the different aspects in the modeling

  2. The logistic model-generated carrying capacities, maximum ...

    African Journals Online (AJOL)

    This paper deals with the derivation of logistic models for cattle, sheep and goats in a commercial ranching system in Machakos District, Kenya, a savannah ecosystem with average annual rainfall of 589.3 ± 159.3mm and an area of 10 117ha. It involves modelling livestock population dynamics as discrete-time logistic ...

  3. Parameters Estimation of Geographically Weighted Ordinal Logistic Regression (GWOLR) Model

    Science.gov (United States)

    Zuhdi, Shaifudin; Retno Sari Saputro, Dewi; Widyaningsih, Purnami

    2017-06-01

    A regression model is the representation of relationship between independent variable and dependent variable. The dependent variable has categories used in the logistic regression model to calculate odds on. The logistic regression model for dependent variable has levels in the logistics regression model is ordinal. GWOLR model is an ordinal logistic regression model influenced the geographical location of the observation site. Parameters estimation in the model needed to determine the value of a population based on sample. The purpose of this research is to parameters estimation of GWOLR model using R software. Parameter estimation uses the data amount of dengue fever patients in Semarang City. Observation units used are 144 villages in Semarang City. The results of research get GWOLR model locally for each village and to know probability of number dengue fever patient categories.

  4. Systems Integration Operations/Logistics Model (SOLMOD)

    International Nuclear Information System (INIS)

    Vogel, L.W.; Joy, D.S.

    1990-01-01

    SOLMOD is a discrete event simulation model written in FORTRAN 77 and operates in a VAX or PC environment. The model emulates the movement and interaction of equipment and radioactive waste as it is processed through the FWMS. SOLMOD can be used to measure the impacts of different operating schedules and rules, system configurations, reliability, availability, maintainability (RAM) considerations, and equipment and other resource availabilities on the performance of processes comprising the FWMS and how these factors combine to determine overall system performance. Model outputs are a series of measurements of the amount and characteristics of waste at selected points in the FWMS and the utilization of resources needed to transport and process the waste. The model results may be reported on a yearly, monthly, weekly, or daily basis to facilitate analysis. 3 refs., 3 figs., 2 tabs

  5. The Logistic Maturity Model: Application to a Fashion Company

    Directory of Open Access Journals (Sweden)

    Claudia Battista

    2013-08-01

    Full Text Available This paper describes the structure of the logistic maturity model (LMM in detail and shows the possible improvements that can be achieved by using this model in terms of the identification of the most appropriate actions to be taken in order to increase the performance of the logistics processes in industrial companies. The paper also gives an example of the LMM’s application to a famous Italian female fashion firm, which decided to use the model as a guideline for the optimization of its supply chain. Relying on a 5-level maturity staircase, specific achievement indicators as well as key performance indicators and best practices are defined and related to each logistics area/process/sub-process, allowing any user to easily and rapidly understand the more critical logistical issues in terms of process immaturity.

  6. Robust mislabel logistic regression without modeling mislabel probabilities.

    Science.gov (United States)

    Hung, Hung; Jou, Zhi-Yu; Huang, Su-Yun

    2018-03-01

    Logistic regression is among the most widely used statistical methods for linear discriminant analysis. In many applications, we only observe possibly mislabeled responses. Fitting a conventional logistic regression can then lead to biased estimation. One common resolution is to fit a mislabel logistic regression model, which takes into consideration of mislabeled responses. Another common method is to adopt a robust M-estimation by down-weighting suspected instances. In this work, we propose a new robust mislabel logistic regression based on γ-divergence. Our proposal possesses two advantageous features: (1) It does not need to model the mislabel probabilities. (2) The minimum γ-divergence estimation leads to a weighted estimating equation without the need to include any bias correction term, that is, it is automatically bias-corrected. These features make the proposed γ-logistic regression more robust in model fitting and more intuitive for model interpretation through a simple weighting scheme. Our method is also easy to implement, and two types of algorithms are included. Simulation studies and the Pima data application are presented to demonstrate the performance of γ-logistic regression. © 2017, The International Biometric Society.

  7. Sustainable logistics and transportation optimization models and algorithms

    CERN Document Server

    Gakis, Konstantinos; Pardalos, Panos

    2017-01-01

    Focused on the logistics and transportation operations within a supply chain, this book brings together the latest models, algorithms, and optimization possibilities. Logistics and transportation problems are examined within a sustainability perspective to offer a comprehensive assessment of environmental, social, ethical, and economic performance measures. Featured models, techniques, and algorithms may be used to construct policies on alternative transportation modes and technologies, green logistics, and incentives by the incorporation of environmental, economic, and social measures. Researchers, professionals, and graduate students in urban regional planning, logistics, transport systems, optimization, supply chain management, business administration, information science, mathematics, and industrial and systems engineering will find the real life and interdisciplinary issues presented in this book informative and useful.

  8. Logistic regression and multiple classification analyses to explore risk factors of under-5 mortality in bangladesh

    International Nuclear Information System (INIS)

    Bhowmik, K.R.; Islam, S.

    2016-01-01

    Logistic regression (LR) analysis is the most common statistical methodology to find out the determinants of childhood mortality. However, the significant predictors cannot be ranked according to their influence on the response variable. Multiple classification (MC) analysis can be applied to identify the significant predictors with a priority index which helps to rank the predictors. The main objective of the study is to find the socio-demographic determinants of childhood mortality at neonatal, post-neonatal, and post-infant period by fitting LR model as well as to rank those through MC analysis. The study is conducted using the data of Bangladesh Demographic and Health Survey 2007 where birth and death information of children were collected from their mothers. Three dichotomous response variables are constructed from children age at death to fit the LR and MC models. Socio-economic and demographic variables significantly associated with the response variables separately are considered in LR and MC analyses. Both the LR and MC models identified the same significant predictors for specific childhood mortality. For both the neonatal and child mortality, biological factors of children, regional settings, and parents socio-economic status are found as 1st, 2nd, and 3rd significant groups of predictors respectively. Mother education and household environment are detected as major significant predictors of post-neonatal mortality. This study shows that MC analysis with or without LR analysis can be applied to detect determinants with rank which help the policy makers taking initiatives on a priority basis. (author)

  9. Geographically Weighted Logistic Regression Applied to Credit Scoring Models

    Directory of Open Access Journals (Sweden)

    Pedro Henrique Melo Albuquerque

    Full Text Available Abstract This study used real data from a Brazilian financial institution on transactions involving Consumer Direct Credit (CDC, granted to clients residing in the Distrito Federal (DF, to construct credit scoring models via Logistic Regression and Geographically Weighted Logistic Regression (GWLR techniques. The aims were: to verify whether the factors that influence credit risk differ according to the borrower’s geographic location; to compare the set of models estimated via GWLR with the global model estimated via Logistic Regression, in terms of predictive power and financial losses for the institution; and to verify the viability of using the GWLR technique to develop credit scoring models. The metrics used to compare the models developed via the two techniques were the AICc informational criterion, the accuracy of the models, the percentage of false positives, the sum of the value of false positive debt, and the expected monetary value of portfolio default compared with the monetary value of defaults observed. The models estimated for each region in the DF were distinct in their variables and coefficients (parameters, with it being concluded that credit risk was influenced differently in each region in the study. The Logistic Regression and GWLR methodologies presented very close results, in terms of predictive power and financial losses for the institution, and the study demonstrated viability in using the GWLR technique to develop credit scoring models for the target population in the study.

  10. Logistics management for storing multiple cask plug and remote handling systems in ITER

    International Nuclear Information System (INIS)

    Ventura, Rodrigo; Ferreira, João; Filip, Iulian; Vale, Alberto

    2013-01-01

    Highlights: ► We model the logistics management problem in ITER, taking into account casks of multiple typologies. ► We propose a method to determine the best position of the casks inside a given storage area. ► Our method obtains the sequence of operations required to retrieve or store an arbitrary cask, given its storage place. ► We illustrate our method with simulation results in an example scenario. -- Abstract: During operation, maintenance inside the reactor building at ITER (International Thermonuclear Experimental Reactor) has to be performed by remote handling, due to the presence of activated materials. Maintenance operations involve the transportation and storage of large, heavyweight casks from and to the tokamak building. The transportation is carried out by autonomous vehicles that lift and move beneath these casks. The storage of these casks face several challenges, since (1) the cask storage area is limited in space, and (2) all casks have to be accessible for transportation by the vehicles. In particular, casks in the storage area may block other casks, so that the former has to be moved to a temporary position to give way to the latter. This paper addresses the challenge of managing the logistics of cask storage, where casks may have different typologies. In particular, we propose an approach to (1) determine the best position of the casks inside the storage area, and to (2) obtain the sequence of operations required to retrieve and store an arbitrary cask from/to a given storage place. A combinatorial optimization approach is used to obtain solutions to both these problems. Simulation results illustrate the application of the proposed method to a simple scenario

  11. Logistics management for storing multiple cask plug and remote handling systems in ITER

    Energy Technology Data Exchange (ETDEWEB)

    Ventura, Rodrigo, E-mail: rodrigo.ventura@isr.ist.utl.pt [Laboratório de Robótica e Sistemas em Engenharia e Ciência – Laboratório Associado, Instituto Superior Técnico, Universidade Técnica de Lisboa, Av. Rovisco Pais 1, 1049-001 Lisboa (Portugal); Ferreira, João, E-mail: jftferreira@ipfn.ist.utl.pt [Instituto de Plasmas e Fusão Nuclear – Laboratório Associado, Instituto Superior Técnico, Universidade Técnica de Lisboa, Av. Rovisco Pais 1, 1049-001 Lisboa (Portugal); Filip, Iulian, E-mail: ifilip@gmail.com [Faculty of Mechanical Engineering – Technical University Gheorghe Asachi of Iasi, 61 Dimitrie Mangeron Bldv., Iasi 700050 (Romania); Vale, Alberto, E-mail: avale@ipfn.ist.utl.pt [Instituto de Plasmas e Fusão Nuclear – Laboratório Associado, Instituto Superior Técnico, Universidade Técnica de Lisboa, Av. Rovisco Pais 1, 1049-001 Lisboa (Portugal)

    2013-10-15

    Highlights: ► We model the logistics management problem in ITER, taking into account casks of multiple typologies. ► We propose a method to determine the best position of the casks inside a given storage area. ► Our method obtains the sequence of operations required to retrieve or store an arbitrary cask, given its storage place. ► We illustrate our method with simulation results in an example scenario. -- Abstract: During operation, maintenance inside the reactor building at ITER (International Thermonuclear Experimental Reactor) has to be performed by remote handling, due to the presence of activated materials. Maintenance operations involve the transportation and storage of large, heavyweight casks from and to the tokamak building. The transportation is carried out by autonomous vehicles that lift and move beneath these casks. The storage of these casks face several challenges, since (1) the cask storage area is limited in space, and (2) all casks have to be accessible for transportation by the vehicles. In particular, casks in the storage area may block other casks, so that the former has to be moved to a temporary position to give way to the latter. This paper addresses the challenge of managing the logistics of cask storage, where casks may have different typologies. In particular, we propose an approach to (1) determine the best position of the casks inside the storage area, and to (2) obtain the sequence of operations required to retrieve and store an arbitrary cask from/to a given storage place. A combinatorial optimization approach is used to obtain solutions to both these problems. Simulation results illustrate the application of the proposed method to a simple scenario.

  12. Modeling logistic performance in quantitative microbial risk assessment.

    Science.gov (United States)

    Rijgersberg, Hajo; Tromp, Seth; Jacxsens, Liesbeth; Uyttendaele, Mieke

    2010-01-01

    In quantitative microbial risk assessment (QMRA), food safety in the food chain is modeled and simulated. In general, prevalences, concentrations, and numbers of microorganisms in media are investigated in the different steps from farm to fork. The underlying rates and conditions (such as storage times, temperatures, gas conditions, and their distributions) are determined. However, the logistic chain with its queues (storages, shelves) and mechanisms for ordering products is usually not taken into account. As a consequence, storage times-mutually dependent in successive steps in the chain-cannot be described adequately. This may have a great impact on the tails of risk distributions. Because food safety risks are generally very small, it is crucial to model the tails of (underlying) distributions as accurately as possible. Logistic performance can be modeled by describing the underlying planning and scheduling mechanisms in discrete-event modeling. This is common practice in operations research, specifically in supply chain management. In this article, we present the application of discrete-event modeling in the context of a QMRA for Listeria monocytogenes in fresh-cut iceberg lettuce. We show the potential value of discrete-event modeling in QMRA by calculating logistic interventions (modifications in the logistic chain) and determining their significance with respect to food safety.

  13. Model building strategy for logistic regression: purposeful selection.

    Science.gov (United States)

    Zhang, Zhongheng

    2016-03-01

    Logistic regression is one of the most commonly used models to account for confounders in medical literature. The article introduces how to perform purposeful selection model building strategy with R. I stress on the use of likelihood ratio test to see whether deleting a variable will have significant impact on model fit. A deleted variable should also be checked for whether it is an important adjustment of remaining covariates. Interaction should be checked to disentangle complex relationship between covariates and their synergistic effect on response variable. Model should be checked for the goodness-of-fit (GOF). In other words, how the fitted model reflects the real data. Hosmer-Lemeshow GOF test is the most widely used for logistic regression model.

  14. Survival Analysis of a Nonautonomous Logistic Model with Stochastic Perturbation

    Directory of Open Access Journals (Sweden)

    Chun Lu

    2012-01-01

    Full Text Available Taking white noise into account, a stochastic nonautonomous logistic model is proposed and investigated. Sufficient conditions for extinction, nonpersistence in the mean, weak persistence, stochastic permanence, and global asymptotic stability are established. Moreover, the threshold between weak persistence and extinction is obtained. Finally, we introduce some numerical simulink graphics to illustrate our main results.

  15. Risk matrix model applied to the outsourcing of logistics' activities

    Directory of Open Access Journals (Sweden)

    Fouad Jawab

    2015-09-01

    Full Text Available Purpose: This paper proposes the application of the risk matrix model in the field of logistics outsourcing. Such an application can serve as the basis for decision making regarding the conduct of a risk management in the logistics outsourcing process and allow its prevention. Design/methodology/approach: This study is based on the risk management of logistics outsourcing in the field of the retail sector in Morocco. The authors identify all possible risks and then classify and prioritize them using the Risk Matrix Model. Finally, we have come to four possible decisions for the identified risks. The analysis was made possible through interviews and discussions with the heads of departments and agents who are directly involved in each outsourced activity. Findings and Originality/value: It is possible to improve the risk matrix model by proposing more personalized prevention measures according to each company that operates in the mass-market retailing. Originality/value: This study is the only one made in the process of logistics outsourcing in the retail sector in Morocco through Label’vie as a case study. First, we had identified as thorough as we could all possible risks, then we applied the Risk Matrix Model to sort them out in an ascending order of importance and criticality. As a result, we could hand out to the decision-makers the mapping for an effective control of risks and a better guiding of the process of risk management.

  16. On the small-time behavior of stochastic logistic models

    Directory of Open Access Journals (Sweden)

    Dung Tien Nguyen

    2017-09-01

    Full Text Available In this paper we investigate the small-time behaviors of the solution to  a stochastic logistic model. The obtained results allow us to estimate the number of individuals in the population and can be used to study stochastic prey-predator systems.

  17. Flower Power: Sunflowers as a Model for Logistic Growth

    Science.gov (United States)

    Fernandez, Eileen; Geist, Kristi A.

    2011-01-01

    Logistic growth displays an interesting pattern: It starts fast, exhibiting the rapid growth characteristic of exponential models. As time passes, it slows in response to constraints such as limited resources or reallocation of energy. The growth continues to slow until it reaches a limit, called capacity. When the growth describes a population,…

  18. A binary logistic regression model with complex sampling design of ...

    African Journals Online (AJOL)

    2017-09-03

    Sep 3, 2017 ... Bi-variable and multi-variable binary logistic regression model with complex sampling design was fitted. .... Data was entered into STATA-12 and analyzed using. SPSS-21. .... lack of access/too far or costs too much. 35. 1.2.

  19. Optimal item discrimination and maximum information for logistic IRT models

    NARCIS (Netherlands)

    Veerkamp, W.J.J.; Veerkamp, Wim J.J.; Berger, Martijn P.F.; Berger, Martijn

    1999-01-01

    Items with the highest discrimination parameter values in a logistic item response theory model do not necessarily give maximum information. This paper derives discrimination parameter values, as functions of the guessing parameter and distances between person parameters and item difficulty, that

  20. Logistic regression for risk factor modelling in stuttering research.

    Science.gov (United States)

    Reed, Phil; Wu, Yaqionq

    2013-06-01

    To outline the uses of logistic regression and other statistical methods for risk factor analysis in the context of research on stuttering. The principles underlying the application of a logistic regression are illustrated, and the types of questions to which such a technique has been applied in the stuttering field are outlined. The assumptions and limitations of the technique are discussed with respect to existing stuttering research, and with respect to formulating appropriate research strategies to accommodate these considerations. Finally, some alternatives to the approach are briefly discussed. The way the statistical procedures are employed are demonstrated with some hypothetical data. Research into several practical issues concerning stuttering could benefit if risk factor modelling were used. Important examples are early diagnosis, prognosis (whether a child will recover or persist) and assessment of treatment outcome. After reading this article you will: (a) Summarize the situations in which logistic regression can be applied to a range of issues about stuttering; (b) Follow the steps in performing a logistic regression analysis; (c) Describe the assumptions of the logistic regression technique and the precautions that need to be checked when it is employed; (d) Be able to summarize its advantages over other techniques like estimation of group differences and simple regression. Copyright © 2012 Elsevier Inc. All rights reserved.

  1. Logistic regression models for polymorphic and antagonistic pleiotropic gene action on human aging and longevity

    DEFF Research Database (Denmark)

    Tan, Qihua; Bathum, L; Christiansen, L

    2003-01-01

    In this paper, we apply logistic regression models to measure genetic association with human survival for highly polymorphic and pleiotropic genes. By modelling genotype frequency as a function of age, we introduce a logistic regression model with polytomous responses to handle the polymorphic...... situation. Genotype and allele-based parameterization can be used to investigate the modes of gene action and to reduce the number of parameters, so that the power is increased while the amount of multiple testing minimized. A binomial logistic regression model with fractional polynomials is used to capture...... the age-dependent or antagonistic pleiotropic effects. The models are applied to HFE genotype data to assess the effects on human longevity by different alleles and to detect if an age-dependent effect exists. Application has shown that these methods can serve as useful tools in searching for important...

  2. A Review on Quantitative Models for Sustainable Food Logistics Management

    Directory of Open Access Journals (Sweden)

    M. Soysal

    2012-12-01

    Full Text Available The last two decades food logistics systems have seen the transition from a focus on traditional supply chain management to food supply chain management, and successively, to sustainable food supply chain management. The main aim of this study is to identify key logistical aims in these three phases and analyse currently available quantitative models to point out modelling challenges in sustainable food logistics management (SFLM. A literature review on quantitative studies is conducted and also qualitative studies are consulted to understand the key logistical aims more clearly and to identify relevant system scope issues. Results show that research on SFLM has been progressively developing according to the needs of the food industry. However, the intrinsic characteristics of food products and processes have not yet been handled properly in the identified studies. The majority of the works reviewed have not contemplated on sustainability problems, apart from a few recent studies. Therefore, the study concludes that new and advanced quantitative models are needed that take specific SFLM requirements from practice into consideration to support business decisions and capture food supply chain dynamics.

  3. Stochastic growth logistic model with aftereffect for batch fermentation process

    Science.gov (United States)

    Rosli, Norhayati; Ayoubi, Tawfiqullah; Bahar, Arifah; Rahman, Haliza Abdul; Salleh, Madihah Md

    2014-06-01

    In this paper, the stochastic growth logistic model with aftereffect for the cell growth of C. acetobutylicum P262 and Luedeking-Piret equations for solvent production in batch fermentation system is introduced. The parameters values of the mathematical models are estimated via Levenberg-Marquardt optimization method of non-linear least squares. We apply Milstein scheme for solving the stochastic models numerically. The effciency of mathematical models is measured by comparing the simulated result and the experimental data of the microbial growth and solvent production in batch system. Low values of Root Mean-Square Error (RMSE) of stochastic models with aftereffect indicate good fits.

  4. Stochastic growth logistic model with aftereffect for batch fermentation process

    International Nuclear Information System (INIS)

    Rosli, Norhayati; Ayoubi, Tawfiqullah; Bahar, Arifah; Rahman, Haliza Abdul; Salleh, Madihah Md

    2014-01-01

    In this paper, the stochastic growth logistic model with aftereffect for the cell growth of C. acetobutylicum P262 and Luedeking-Piret equations for solvent production in batch fermentation system is introduced. The parameters values of the mathematical models are estimated via Levenberg-Marquardt optimization method of non-linear least squares. We apply Milstein scheme for solving the stochastic models numerically. The effciency of mathematical models is measured by comparing the simulated result and the experimental data of the microbial growth and solvent production in batch system. Low values of Root Mean-Square Error (RMSE) of stochastic models with aftereffect indicate good fits

  5. Stochastic growth logistic model with aftereffect for batch fermentation process

    Energy Technology Data Exchange (ETDEWEB)

    Rosli, Norhayati; Ayoubi, Tawfiqullah [Faculty of Industrial Sciences and Technology, Universiti Malaysia Pahang, Lebuhraya Tun Razak, 26300 Gambang, Pahang (Malaysia); Bahar, Arifah; Rahman, Haliza Abdul [Department of Mathematical Sciences, Faculty of Science, Universiti Teknologi Malaysia, 81310 Johor Bahru, Johor (Malaysia); Salleh, Madihah Md [Department of Biotechnology Industry, Faculty of Biosciences and Bioengineering, Universiti Teknologi Malaysia, 81310 Johor Bahru, Johor (Malaysia)

    2014-06-19

    In this paper, the stochastic growth logistic model with aftereffect for the cell growth of C. acetobutylicum P262 and Luedeking-Piret equations for solvent production in batch fermentation system is introduced. The parameters values of the mathematical models are estimated via Levenberg-Marquardt optimization method of non-linear least squares. We apply Milstein scheme for solving the stochastic models numerically. The effciency of mathematical models is measured by comparing the simulated result and the experimental data of the microbial growth and solvent production in batch system. Low values of Root Mean-Square Error (RMSE) of stochastic models with aftereffect indicate good fits.

  6. Short-Run Asset Selection using a Logistic Model

    Directory of Open Access Journals (Sweden)

    Walter Gonçalves Junior

    2011-06-01

    Full Text Available Investors constantly look for significant predictors and accurate models to forecast future results, whose occasional efficacy end up being neutralized by market efficiency. Regardless, such predictors are widely used for seeking better (and more unique perceptions. This paper aims to investigate to what extent some of the most notorious indicators have discriminatory power to select stocks, and if it is feasible with such variables to build models that could anticipate those with good performance. In order to do that, logistical regressions were conducted with stocks traded at Bovespa using the selected indicators as explanatory variables. Investigated in this study were the outputs of Bovespa Index, liquidity, the Sharpe Ratio, ROE, MB, size and age evidenced to be significant predictors. Also examined were half-year, logistical models, which were adjusted in order to check the potential acceptable discriminatory power for the asset selection.

  7. Predictors of postoperative outcomes of cubital tunnel syndrome treatments using multiple logistic regression analysis.

    Science.gov (United States)

    Suzuki, Taku; Iwamoto, Takuji; Shizu, Kanae; Suzuki, Katsuji; Yamada, Harumoto; Sato, Kazuki

    2017-05-01

    This retrospective study was designed to investigate prognostic factors for postoperative outcomes for cubital tunnel syndrome (CubTS) using multiple logistic regression analysis with a large number of patients. Eighty-three patients with CubTS who underwent surgeries were enrolled. The following potential prognostic factors for disease severity were selected according to previous reports: sex, age, type of surgery, disease duration, body mass index, cervical lesion, presence of diabetes mellitus, Workers' Compensation status, preoperative severity, and preoperative electrodiagnostic testing. Postoperative severity of disease was assessed 2 years after surgery by Messina's criteria which is an outcome measure specifically for CubTS. Bivariate analysis was performed to select candidate prognostic factors for multiple linear regression analyses. Multiple logistic regression analysis was conducted to identify the association between postoperative severity and selected prognostic factors. Both bivariate and multiple linear regression analysis revealed only preoperative severity as an independent risk factor for poor prognosis, while other factors did not show any significant association. Although conflicting results exist regarding prognosis of CubTS, this study supports evidence from previous studies and concludes early surgical intervention portends the most favorable prognosis. Copyright © 2017 The Japanese Orthopaedic Association. Published by Elsevier B.V. All rights reserved.

  8. Modelling of Processes of Logistics in Cyberspace Security

    Directory of Open Access Journals (Sweden)

    Konečný Jiří

    2017-01-01

    Full Text Available The goal of this contribution is especially to familiarize experts in various fields with the need for a new approach to the system-defined model and modelling of processes in the engineering practice and the expression of some state variables' possibilities for the modelling of real-world systems with regard to the highly dynamic development of structures and to the behaviour of systems of logistics. Thus, in this contribution, the necessity of making full use of cybernetics as a field for the management and communication of information is expressed, and also the environment of cybernetics as a much needed cybernetic realm (cyberspace, determining the steady state between cyber-attacks and cyber-defence as a modern knowledge-based potential in general and specifically of logistics in cyber security. Connected with this process is the very important area of lifelong training of experts in the dynamic world of science and technology (that is, also in a social system which is also expressed here briefly, and also the cyber and information security, all of which falls under the cyberspace of new perspective electronic learning (e-learning with the use of modern laboratories with new effects also for future possibilities of process modelling of artificial intelligence (AI with a perspective of mass use of UAVs in logistics.

  9. Comparison of the binary logistic and skewed logistic (Scobit) models of injury severity in motor vehicle collisions.

    Science.gov (United States)

    Tay, Richard

    2016-03-01

    The binary logistic model has been extensively used to analyze traffic collision and injury data where the outcome of interest has two categories. However, the assumption of a symmetric distribution may not be a desirable property in some cases, especially when there is a significant imbalance in the two categories of outcome. This study compares the standard binary logistic model with the skewed logistic model in two cases in which the symmetry assumption is violated in one but not the other case. The differences in the estimates, and thus the marginal effects obtained, are significant when the assumption of symmetry is violated. Copyright © 2015 Elsevier Ltd. All rights reserved.

  10. Multiple Logistic Regression Analysis of Cigarette Use among High School Students

    Science.gov (United States)

    Adwere-Boamah, Joseph

    2011-01-01

    A binary logistic regression analysis was performed to predict high school students' cigarette smoking behavior from selected predictors from 2009 CDC Youth Risk Behavior Surveillance Survey. The specific target student behavior of interest was frequent cigarette use. Five predictor variables included in the model were: a) race, b) frequency of…

  11. New robust statistical procedures for the polytomous logistic regression models.

    Science.gov (United States)

    Castilla, Elena; Ghosh, Abhik; Martin, Nirian; Pardo, Leandro

    2018-05-17

    This article derives a new family of estimators, namely the minimum density power divergence estimators, as a robust generalization of the maximum likelihood estimator for the polytomous logistic regression model. Based on these estimators, a family of Wald-type test statistics for linear hypotheses is introduced. Robustness properties of both the proposed estimators and the test statistics are theoretically studied through the classical influence function analysis. Appropriate real life examples are presented to justify the requirement of suitable robust statistical procedures in place of the likelihood based inference for the polytomous logistic regression model. The validity of the theoretical results established in the article are further confirmed empirically through suitable simulation studies. Finally, an approach for the data-driven selection of the robustness tuning parameter is proposed with empirical justifications. © 2018, The International Biometric Society.

  12. Comparison of particular logistic models' adoption in the Czech Republic

    Science.gov (United States)

    Vrbová, Petra; Cempírek, Václav

    2016-12-01

    Managing inventory is considered as one of the most challenging tasks facing supply chain managers and specialists. Decisions related to inventory locations along with level of inventory kept throughout the supply chain have a fundamental impact on the response time, service level, delivery lead-time and the total cost of the supply chain. The main objective of this paper is to identify and analyse the share of a particular logistic model adopted in the Czech Republic (Consignment stock, Buffer stock, Safety stock) and also compare their usage and adoption according to different industries. This paper also aims to specify possible reasons of particular logistic model preferences in comparison to the others. The analysis is based on quantitative survey held in the Czech Republic.

  13. Accessibility to Nodes of Interest: Demographic Weighting the Logistic Model

    Directory of Open Access Journals (Sweden)

    Gioacchino DE CANDIA

    2015-11-01

    Full Text Available This research fits into the genre of spatial analysis, aimed at better understanding of population dynamics in relation to the presence and distribution of infrastructure and related services. Specifically, the analysis uses a model of the gravitational type, based on the assumption of the impedance (attractiveness territorial, based on a curve of type logistics to determine the accessibility of the same, to which to add a system of weights. In this sense, the model was weighted according to the population, to determine the level of “population served” in terms of infrastructure and related services included in the model.

  14. An optimal hierarchical decision model for a regional logistics network with environmental impact consideration.

    Science.gov (United States)

    Zhang, Dezhi; Li, Shuangyan; Qin, Jin

    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.

  15. An Optimal Hierarchical Decision Model for a Regional Logistics Network with Environmental Impact Consideration

    Directory of Open Access Journals (Sweden)

    Dezhi Zhang

    2014-01-01

    Full Text Available 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.

  16. An Optimal Hierarchical Decision Model for a Regional Logistics Network with Environmental Impact Consideration

    Science.gov (United States)

    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

  17. Interpreting parameters in the logistic regression model with random effects

    DEFF Research Database (Denmark)

    Larsen, Klaus; Petersen, Jørgen Holm; Budtz-Jørgensen, Esben

    2000-01-01

    interpretation, interval odds ratio, logistic regression, median odds ratio, normally distributed random effects......interpretation, interval odds ratio, logistic regression, median odds ratio, normally distributed random effects...

  18. Single-tier city logistics model for single product

    Science.gov (United States)

    Saragih, N. I.; Nur Bahagia, S.; Suprayogi; Syabri, I.

    2017-11-01

    This research develops single-tier city logistics model which consists of suppliers, UCCs, and retailers. The problem that will be answered in this research is how to determine the location of UCCs, to allocate retailers to opened UCCs, to assign suppliers to opened UCCs, to control inventory in the three entities involved, and to determine the route of the vehicles from opened UCCs to retailers. This model has never been developed before. All the decisions will be simultaneously optimized. Characteristic of the demand is probabilistic following a normal distribution, and the number of product is single.

  19. Models of Inter-Organizational Logistics Management in Slovenia

    Directory of Open Access Journals (Sweden)

    Sašo Murtič

    2015-03-01

    Full Text Available Throughout the history, the transportation of goods and related logistics have played an important role in human development and existence. This pertains to numerous interlinked processes, whose management is often linked to social system, international linkages, development of industry, market and market specifics. In modern times, the management of these processes is increasingly bound to globalization of production and market, moving of production to countries with cheaper labour force, environmental protection. The present Slovenian economy depends to a large extent on economies and corporate relations of the European Union and the world. Such inter-connectedness demands frequent transportation of semi-finished and finished goods. By providing timely delivery of goods, transportation consequently enables inter-organizational linkages and individual production, economic, market and other processes. Organizational and inter-organizational management of transport logistics demands profound understanding of transport flows, freight forwarding expertise and knowledge of transport, tax, environmental and other related regulations. Adequate knowledge and mastering of cultural, linguistic, national and other differences is important as well. The presented analysis and evaluation form the basis of the construction of inter-organizational model of logistics management in Slovenia.

  20. Decision support modeling for sustainable food logistics management

    NARCIS (Netherlands)

    Soysal, M.

    2015-01-01

    Summary

    For the last two decades, food logistics systems have seen the transition from traditional Logistics Management (LM) to Food Logistics Management (FLM), and successively, to Sustainable Food Logistics Management (SFLM). Accordingly, food industry has been subject to the recent

  1. Screening for ketosis using multiple logistic regression based on milk yield and composition.

    Science.gov (United States)

    Kayano, Mitsunori; Kataoka, Tomoko

    2015-11-01

    Multiple logistic regression was applied to milk yield and composition data for 632 records of healthy cows and 61 records of ketotic cows in Hokkaido, Japan. The purpose was to diagnose ketosis based on milk yield and composition, simultaneously. The cows were divided into two groups: (1) multiparous, including 314 healthy cows and 45 ketotic cows and (2) primiparous, including 318 healthy cows and 16 ketotic cows, since nutritional status, milk yield and composition are affected by parity. Multiple logistic regression was applied to these groups separately. For multiparous cows, milk yield (kg/day/cow) and protein-to-fat (P/F) ratio in milk were significant factors (Pketosis. For primiparous cows, lactose content (%), solid not fat (SNF) content (%) and milk urea nitrogen (MUN) content (mg/dl) were significantly associated with ketosis (Pketosis, provided the sensitivity, specificity and AUC values of (1) 0.711, 0.726 and 0.781; and (2) 0.678, 0.767 and 0.738, respectively.

  2. A general equation to obtain multiple cut-off scores on a test from multinomial logistic regression.

    Science.gov (United States)

    Bersabé, Rosa; Rivas, Teresa

    2010-05-01

    The authors derive a general equation to compute multiple cut-offs on a total test score in order to classify individuals into more than two ordinal categories. The equation is derived from the multinomial logistic regression (MLR) model, which is an extension of the binary logistic regression (BLR) model to accommodate polytomous outcome variables. From this analytical procedure, cut-off scores are established at the test score (the predictor variable) at which an individual is as likely to be in category j as in category j+1 of an ordinal outcome variable. The application of the complete procedure is illustrated by an example with data from an actual study on eating disorders. In this example, two cut-off scores on the Eating Attitudes Test (EAT-26) scores are obtained in order to classify individuals into three ordinal categories: asymptomatic, symptomatic and eating disorder. Diagnoses were made from the responses to a self-report (Q-EDD) that operationalises DSM-IV criteria for eating disorders. Alternatives to the MLR model to set multiple cut-off scores are discussed.

  3. Modeling risk and uncertainty in designing reverse logistics problem

    Directory of Open Access Journals (Sweden)

    Aida Nazari Gooran

    2018-01-01

    Full Text Available Increasing attention to environmental problems and social responsibility lead to appear reverse logistic (RL issues in designing supply chain which, in most recently, has received considerable attention from both academicians and practitioners. In this paper, a multi-product reverse logistic network design model is developed; then a hybrid method including Chance-constrained programming, Genetic algorithm and Monte Carlo simulation, are proposed to solve the developed model. The proposed model is solved for risk-averse and risk-seeking decision makers by conditional value at risk, sum of the excepted value and standard deviation, respectively. Comparisons of the results show that minimizing the costs had no direct relation with the kind of decision makers; however, in the most cases, risk-seeking decision maker gained more return products than risk-averse ones. It is clear that by increasing returned products to the chain, production costs of new products and material will be reduced and also by this act, environmental benefits will be created.

  4. A Cost Model for Integrated Logistic Support Activities

    Directory of Open Access Journals (Sweden)

    M. Elena Nenni

    2013-01-01

    Full Text Available An Integrated Logistic Support (ILS service has the objective of improving a system’s efficiency and availability for the life cycle. The system constructor offers the service to the customer, and she becomes the Contractor Logistic Support (CLS. The aim of this paper is to propose an approach to support the CLS in the budget formulation. Specific goals of the model are the provision of the annual cost of ILS activities through a specific cost model and a comprehensive examination of expected benefits, costs and savings under alternative ILS strategies. A simple example derived from an industrial application is also provided to illustrate the idea. Scientific literature is lacking in the topic and documents from the military are just dealing with the issue of performance measurement. Moreover, they are obviously focused on the customer’s perspective. Other scientific papers are general and focused only on maintenance or life cycle management. The model developed in this paper approaches the problem from the perspective of the CLS, and it is specifically tailored on the main issues of an ILS service.

  5. A logistics model for large space power systems

    Science.gov (United States)

    Koelle, H. H.

    Space Power Systems (SPS) have to overcome two hurdles: (1) to find an attractive design, manufacturing and assembly concept and (2) to have available a space transportation system that can provide economical logistic support during the construction and operational phases. An initial system feasibility study, some five years ago, was based on a reference system that used terrestrial resources only and was based partially on electric propulsion systems. The conclusion was: it is feasible but not yet economically competitive with other options. This study is based on terrestrial and extraterrestrial resources and on chemical (LH 2/LOX) propulsion systems. These engines are available from the Space Shuttle production line and require small changes only. Other so-called advanced propulsion systems investigated did not prove economically superior if lunar LOX is available! We assume that a Shuttle derived Heavy Lift Launch Vehicle (HLLV) will become available around the turn of the century and that this will be used to establish a research base on the lunar surface. This lunar base has the potential to grow into a lunar factory producing LOX and construction materials for supporting among other projects also the construction of space power systems in geostationary orbit. A model was developed to simulate the logistics support of such an operation for a 50-year life cycle. After 50 years 111 SPS units with 5 GW each and an availability of 90% will produce 100 × 5 = 500 GW. The model comprises 60 equations and requires 29 assumptions of the parameter involved. 60-state variables calculated with the 60 equations mentioned above are given on an annual basis and as averages for the 50-year life cycle. Recycling of defective parts in geostationary orbit is one of the features of the model. The state-of-the-art with respect to SPS technology is introduced as a variable Mg mass/MW electric power delivered. If the space manufacturing facility, a maintenance and repair facility

  6. Inverse estimation of multiple muscle activations based on linear logistic regression.

    Science.gov (United States)

    Sekiya, Masashi; Tsuji, Toshiaki

    2017-07-01

    This study deals with a technology to estimate the muscle activity from the movement data using a statistical model. A linear regression (LR) model and artificial neural networks (ANN) have been known as statistical models for such use. Although ANN has a high estimation capability, it is often in the clinical application that the lack of data amount leads to performance deterioration. On the other hand, the LR model has a limitation in generalization performance. We therefore propose a muscle activity estimation method to improve the generalization performance through the use of linear logistic regression model. The proposed method was compared with the LR model and ANN in the verification experiment with 7 participants. As a result, the proposed method showed better generalization performance than the conventional methods in various tasks.

  7. WASTES: a waste management logistics/economics model

    International Nuclear Information System (INIS)

    McNair, G.W.; Shay, M.R.; Fletcher, J.F.; Cashwell, J.W.

    1985-01-01

    The WASTES logistics model is a simulation language based model for analyzing the logistic flow of spent fuel/nuclear waste throughout the waste management system. The model tracks the movement of spent fuel/nuclear waste from point of generation to final destination. The model maintains inventories of spent fuel/nuclear waste at individual reactor sites as well as at various facilities within the waste management system. A maximum of 14 facilities may be utilized within a single run. These 14 facilities may include any combination of the following facilities: (1) federal interim storage (FIS), (2) reprocessing (REP), (3) monitored retrievable storage (MRS), (4) geological disposal facilities (GDF). The movement of spent fuel/nuclear waste between these facilities is controlled by the user specification of loading and unloading rates, annual and maximum capacities and commodity characteristics (minimum age or heat constraints) for each individual facility. In addition, the user may specify varying levels of priority on the spent fuel/nuclear waste that will be eligible for movement within a given year. These levels of priority allow the user to preferentially move spent fuel from reactor sites that are experiencing a loss of full-core-reserve (FCR) margin in a given year or from reactors that may be in the final stages of decommissioning. The WASTES model utilizes the reactor specific data available from the PNL spent fuel database. This database provides reactor specific information on items such as spent fuel basin size, reactor location, and transportation cask preference (i.e., rail or truck cask). In addition, detailed discharge data is maintained that provides the number of assemblies, metric tons, and exposure for both historic and projected discharges at each reactor site

  8. A model for logistics systems engineering management education in Europe

    NARCIS (Netherlands)

    Naim, M.; Lalwani, C.; Fortuin, L.; Schmidt, T.; Taylor, J.; Aronsson, H.

    2000-01-01

    This paper presents the need for a systems and process perspective of logistics. By defining logistics in this way a template for a logistics education course is developed. The template addresses functional, process and supply chain needs and has been developed by a number of university partners

  9. Effects of Perfectly Correlated and Anti-Correlated Noise in a Logistic Growth Model

    International Nuclear Information System (INIS)

    Zhang Li; Cao Li

    2011-01-01

    The logistic growth model with correlated additive and multiplicative Gaussian white noise is used to analyze tumor cell population. The effects of perfectly correlated and anti-correlated noise on the stationary properties of tumor cell population are studied. As in both cases the diffusion coefficient has zero point in real number field, some special features of the system are arisen. It is found that in both cases, the increase of the multiplicative noise intensity cause tumor cell extinction. In the perfectly anti-correlated case, the stationary probability distribution as a function of tumor cell population exhibit two extrema. (general)

  10. Identification of reverse logistics decision types from mathematical models

    Directory of Open Access Journals (Sweden)

    Pascual Cortés Pellicer

    2018-04-01

    Full Text Available Purpose: The increase in social awareness, politics and environmental regulation, the scarcity of raw materials and the desired “green” image, are some of the reasons that lead companies to decide for implement processes of Reverse Logistics (RL. At the time when incorporate new RL processes as key business processes, new and important decisions need to be made. Identification and knowledge of these decisions, including the information available and the implications for the company or supply chain, will be fundamental for decision-makers to achieve the best results. In the present work, the main types of RL decisions are identified. Design/methodology/approach: This paper is based on the analysis of mathematical models designed as tools to aid decision making in the field of RL. Once the types of interest work to be analyzed are defined, those studies that really deal about the object of study are searched and analyzed. The decision variables that are taken at work are identified and grouped according to the type of decision and, finally, are showed the main types of decisions used in mathematical models developed in the field of RL.     Findings: The principal conclusion of the research is that the most commonly addressed decisions with mathematical models in the field of RL are those related to the network’s configuration, followed by tactical/operative decisions such as the selections of product’s treatments to realize and the policy of returns or prices, among other decisions. Originality/value: The identification of the main decisions types of the reverse logistics will allow the managers of these processes to know and understand them better, while offer an integrated vision of them, favoring the achievement of better results.

  11. The Use of Logistic Model in RUL Assessment

    Science.gov (United States)

    Gumiński, R.; Radkowski, S.

    2017-12-01

    The paper takes on the issue of assessment of remaining useful life (RUL). The goal of the paper was to develop a method, which would enable use of diagnostic information in the task of reducing the uncertainty related to technical risk. Prediction of the remaining useful life (RUL) of the system is a very important task for maintenance strategy. In the literature RUL of an engineering system is defined as the first future time instant in which thresholds of conditions (safety, operational quality, maintenance cost, etc) are violated. Knowledge of RUL offers the possibility of planning the testing and repair activities. Building models of damage development is important in this task. In the presented work, logistic function will be used to model fatigue crack development. It should be remembered that modeling of every phase of damage development is very difficult, yet modeling of every phase of damage separately, especially including on-line diagnostic information is more effective. Particular attention was paid to the possibility of forecasting the occurrence of damage due to fatigue while relying on the analysis of the structure of a vibroacoustic signal.

  12. Optimizing Warehouse Logistics Operations Through Site Selection Models: Istanbul, Turkey

    National Research Council Canada - National Science Library

    Erdemir, Ugur

    2003-01-01

    .... Given the dynamic environment surrounding the military operations, logistic sustainability requirements, rapid information technology developments, and budget-constrained Turkish DoD acquisition...

  13. A Review on Quantitative Models for Sustainable Food Logistics Management

    NARCIS (Netherlands)

    Soysal, M.; Bloemhof, J.M.; Meuwissen, M.P.M.; Vorst, van der J.G.A.J.

    2012-01-01

    The last two decades food logistics systems have seen the transition from a focus on traditional supply chain management to food supply chain management, and successively, to sustainable food supply chain management. The main aim of this study is to identify key logistical aims in these three phases

  14. A Model for Logistics Systems Engineering Management Education in Europe.

    Science.gov (United States)

    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)

  15. Design logistics performance measurement model of automotive component industry for srengthening competitiveness of dealing AEC 2015

    Science.gov (United States)

    Amran, T. G.; Janitra Yose, Mindy

    2018-03-01

    As the free trade Asean Economic Community (AEC) causes the tougher competition, it is important that Indonesia’s automotive industry have high competitiveness as well. A model of logistics performance measurement was designed as an evaluation tool for automotive component companies to improve their logistics performance in order to compete in AEC. The design of logistics performance measurement model was based on the Logistics Scorecard perspectives, divided into two stages: identifying the logistics business strategy to get the KPI and arranging the model. 23 KPI was obtained. The measurement result can be taken into consideration of determining policies to improve the performance logistics competitiveness.

  16. Revenue-Sharing Contract Models for Logistics Service Supply Chains with Mass Customization Service

    Directory of Open Access Journals (Sweden)

    Weihua Liu

    2015-01-01

    Full Text Available The revenue-sharing contract is one of the most important supply chain coordination contracts; it has been applied in various supply chains. However, studies related to service supply chains with mass customization (MC are lacking. Considering the equity of benefit distribution between the members of service supply chains, in this paper, we designed two revenue-sharing contracts. The first contract for the maximum equity of a single logistics service integrator (LSI and single functional logistics service provider (FLSP in a two-echelon logistics service supply chain was designed by introducing the fair entropy function (“one to one” model. Furthermore, the method is extended to a more complex supply chain, which consists of a single LSI and multiple FLSPs. A new contract was designed not only for considering the equity of an LSI and each FLSP but also for the equity between each FLSP (“one to N” model. The “one to one” model in three-echelon LSSC is also provided. The result exemplifies that, whether in the “one to one” model or “one to N” model, there exists a best interval of customized level when the revenue-sharing coefficient reaches its maximum.

  17. Model-Independent Evaluation of Tumor Markers and a Logistic-Tree Approach to Diagnostic Decision Support

    Directory of Open Access Journals (Sweden)

    Weizeng Ni

    2014-01-01

    Full Text Available Sensitivity and specificity of using individual tumor markers hardly meet the clinical requirement. This challenge gave rise to many efforts, e.g., combing multiple tumor markers and employing machine learning algorithms. However, results from different studies are often inconsistent, which are partially attributed to the use of different evaluation criteria. Also, the wide use of model-dependent validation leads to high possibility of data overfitting when complex models are used for diagnosis. We propose two model-independent criteria, namely, area under the curve (AUC and Relief to evaluate the diagnostic values of individual and multiple tumor markers, respectively. For diagnostic decision support, we propose the use of logistic-tree which combines decision tree and logistic regression. Application on a colorectal cancer dataset shows that the proposed evaluation criteria produce results that are consistent with current knowledge. Furthermore, the simple and highly interpretable logistic-tree has diagnostic performance that is competitive with other complex models.

  18. Drought Patterns Forecasting using an Auto-Regressive Logistic Model

    Science.gov (United States)

    del Jesus, M.; Sheffield, J.; Méndez Incera, F. J.; Losada, I. J.; Espejo, A.

    2014-12-01

    Drought is characterized by a water deficit that may manifest across a large range of spatial and temporal scales. Drought may create important socio-economic consequences, many times of catastrophic dimensions. A quantifiable definition of drought is elusive because depending on its impacts, consequences and generation mechanism, different water deficit periods may be identified as a drought by virtue of some definitions but not by others. Droughts are linked to the water cycle and, although a climate change signal may not have emerged yet, they are also intimately linked to climate.In this work we develop an auto-regressive logistic model for drought prediction at different temporal scales that makes use of a spatially explicit framework. Our model allows to include covariates, continuous or categorical, to improve the performance of the auto-regressive component.Our approach makes use of dimensionality reduction (principal component analysis) and classification techniques (K-Means and maximum dissimilarity) to simplify the representation of complex climatic patterns, such as sea surface temperature (SST) and sea level pressure (SLP), while including information on their spatial structure, i.e. considering their spatial patterns. This procedure allows us to include in the analysis multivariate representation of complex climatic phenomena, as the El Niño-Southern Oscillation. We also explore the impact of other climate-related variables such as sun spots. The model allows to quantify the uncertainty of the forecasts and can be easily adapted to make predictions under future climatic scenarios. The framework herein presented may be extended to other applications such as flash flood analysis, or risk assessment of natural hazards.

  19. A Study on Logistics Cluster Competitiveness among Asia Main Countries using the Porter's Diamond Model

    Directory of Open Access Journals (Sweden)

    Tae Won Chung

    2016-12-01

    Full Text Available Measurement and discussions of logistics cluster competitiveness with a national approach are required to boost agglomeration effects and potentially create logistics efficiency and productivity. This study developed assessment criteria of logistics cluster competitiveness based on Porter's diamond model, calculated the weight of each criterion by the AHP method, and finally evaluated and discussed logistics cluster competitiveness among Asia main countries. The results indicate that there was a large difference in logistics cluster competitiveness among six countries. The logistics cluster competitiveness scores of Singapore (7.93, Japan (7.38, and Hong Kong (7.04 are observably different from those of China (5.40, Korea (5.08, and Malaysia (3.46. Singapore, with the highest competitiveness score, revealed its absolute advantage in logistics cluster indices. These research results intend to provide logistics policy makers with some strategic recommendations, and may serve as a baseline for further logistics cluster studies using Porter's diamond model.

  20. Outsourcing Wholesale Logistics, A Model for Future Systems

    National Research Council Canada - National Science Library

    McDaniels, Lloyd

    2002-01-01

    .... This paper outlines the method to reduce those costs by providing incentives to simultaneously increase operational readiness and reduce logistics requirements of the system at both the wholesale and retail levels...

  1. MODELING SNAKE MICROHABITAT FROM RADIOTELEMETRY STUDIES USING POLYTOMOUS LOGISTIC REGRESSION

    Science.gov (United States)

    Multivariate analysis of snake microhabitat has historically used techniques that were derived under assumptions of normality and common covariance structure (e.g., discriminant function analysis, MANOVA). In this study, polytomous logistic regression (PLR which does not require ...

  2. Collaborative autonomous systems in models of urban logistics

    OpenAIRE

    Arango Serna, Martín Darío; Serna Uran, Conrado Augusto; Alvarez Uribe, Karla Cristina; Arango Serna, Martín Darío

    2012-01-01

    Cities growth and along with them the exchange and distribution of goods and services has led in recent years to a greater increasing interest for the optimization of logistic processes carried out in urban areas. In this article, the main approaches and solutions which have been proposed from academic research will be described, focusing mainly on collaborative autonomic logistics, which is offered as an attractive solution to the urban goods distribution problems in complex cities.

  3. GREEN LOGISTICS – A DIFFERENT AND SUSTAINABLE BUSINESS GROWTH MODEL

    OpenAIRE

    BRĂDESCU Georgiana

    2014-01-01

    Built on the concepts of green logistics and green supply chain management (GrSCM), this paper presents the relationship between logistical activities and its related environmental effects and costs. By greening their supply chain, companies can better use their assets, optimize resources- do more with less, improve and create sustainable technology, ensure continuity and strategic, long-term alliances. Business ethics and social responsibility are important components of organisational effec...

  4. Logistics Systems Engineer – Interdisciplinary Competence Model for Modern Education

    OpenAIRE

    Tarvo Niine; Ott Koppel

    2015-01-01

    Logistics is an interdisciplinary field of study. Modern logisticians need to integrate business management and administration skills with technology design, IT systems and other engineering fields. However, based on research of university curricula and competence standards in logistics, the engineering aspect is not represented to full potential. There are some treatments of logistician competences which relate to engineering, but not a modernized one with wide-spread recognition. This paper...

  5. Design of a biomass-to-biorefinery logistics system through bio-inspired metaheuristic optimization considering multiple types of feedstocks

    Science.gov (United States)

    Trueba, Isidoro

    fossil fuels to biofuels. In many ways biomass is a unique renewable resource. It can be stored and transported relatively easily in contrast to renewable options such as wind and solar, which create intermittent electrical power that requires immediate consumption and a connection to the grid. This thesis presents two different models for the design optimization of a biomass-to-biorefinery logistics system through bio-inspired metaheuristic optimization considering multiple types of feedstocks. This work compares the performance and solutions obtained by two types of metaheuristic approaches; genetic algorithm and ant colony optimization. Compared to rigorous mathematical optimization methods or iterative algorithms, metaheuristics do not guarantee that a global optimal solution can be found on some class of problems. Problems with similar characteristics to the one presented in this thesis have been previously solved using linear programming, integer programming and mixed integer programming methods. However, depending on the type of problem, these mathematical or complete methods might need exponential computation time in the worst-case. This often leads to computation times too high for practical purposes. Therefore, this thesis develops two types of metaheuristic approaches for the design optimization of a biomass-to-biorefinery logistics system considering multiple types of feedstocks and shows that metaheuristics are highly suitable to solve hard combinatorial optimization problems such as the one addressed in this research work.

  6. Business Process Modeling for Domain Outbound Logistics System: Analytic Perspective with BPMN 2.0

    OpenAIRE

    Khabbazi, Mahmood Reza; Hasan, M.K; Sulaiman, R; Shapi’i, A

    2013-01-01

    This paper proposes a generic"to-be" business processes model for domain highest-level outbound logistics system representing the possible alternative structure and behaviour of the system in respect to x-party logistics services applicable in Small-to-medium sized enterprises. The generic framework of outbound logistics model consists of one main modular system named as the Shipping System including five internal sub-systems of the shipping core, shipping requirement, First Party Logistics (...

  7. Evolution Model and Simulation of Profit Model of Agricultural Products Logistics Financing

    Science.gov (United States)

    Yang, Bo; Wu, Yan

    2018-03-01

    Agricultural products logistics financial warehousing business mainly involves agricultural production and processing enterprises, third-party logistics enterprises and financial institutions tripartite, to enable the three parties to achieve win-win situation, the article first gives the replication dynamics and evolutionary stability strategy between the three parties in business participation, and then use NetLogo simulation platform, using the overall modeling and simulation method of Multi-Agent, established the evolutionary game simulation model, and run the model under different revenue parameters, finally, analyzed the simulation results. To achieve the agricultural products logistics financial financing warehouse business to participate in tripartite mutually beneficial win-win situation, thus promoting the smooth flow of agricultural products logistics business.

  8. Predictive ability of logistic regression, auto-logistic regression and neural network models in empirical land-use change modeling: a case study

    NARCIS (Netherlands)

    Lin, Y.P.; Chu, H.J.; Wu, C.F.; Verburg, P.H.

    2011-01-01

    The objective of this study is to compare the abilities of logistic, auto-logistic and artificial neural network (ANN) models for quantifying the relationships between land uses and their drivers. In addition, the application of the results obtained by the three techniques is tested in a dynamic

  9. Logistic regression modelling: procedures and pitfalls in developing and interpreting prediction models

    Directory of Open Access Journals (Sweden)

    Nataša Šarlija

    2017-01-01

    Full Text Available This study sheds light on the most common issues related to applying logistic regression in prediction models for company growth. The purpose of the paper is 1 to provide a detailed demonstration of the steps in developing a growth prediction model based on logistic regression analysis, 2 to discuss common pitfalls and methodological errors in developing a model, and 3 to provide solutions and possible ways of overcoming these issues. Special attention is devoted to the question of satisfying logistic regression assumptions, selecting and defining dependent and independent variables, using classification tables and ROC curves, for reporting model strength, interpreting odds ratios as effect measures and evaluating performance of the prediction model. Development of a logistic regression model in this paper focuses on a prediction model of company growth. The analysis is based on predominantly financial data from a sample of 1471 small and medium-sized Croatian companies active between 2009 and 2014. The financial data is presented in the form of financial ratios divided into nine main groups depicting following areas of business: liquidity, leverage, activity, profitability, research and development, investing and export. The growth prediction model indicates aspects of a business critical for achieving high growth. In that respect, the contribution of this paper is twofold. First, methodological, in terms of pointing out pitfalls and potential solutions in logistic regression modelling, and secondly, theoretical, in terms of identifying factors responsible for high growth of small and medium-sized companies.

  10. Grey-Theory-Based Optimization Model of Emergency Logistics Considering Time Uncertainty.

    Science.gov (United States)

    Qiu, Bao-Jian; Zhang, Jiang-Hua; Qi, Yuan-Tao; Liu, Yang

    2015-01-01

    Natural disasters occur frequently in recent years, causing huge casualties and property losses. Nowadays, people pay more and more attention to the emergency logistics problems. This paper studies the emergency logistics problem with multi-center, multi-commodity, and single-affected-point. Considering that the path near the disaster point may be damaged, the information of the state of the paths is not complete, and the travel time is uncertainty, we establish the nonlinear programming model that objective function is the maximization of time-satisfaction degree. To overcome these drawbacks: the incomplete information and uncertain time, this paper firstly evaluates the multiple roads of transportation network based on grey theory and selects the reliable and optimal path. Then simplify the original model under the scenario that the vehicle only follows the optimal path from the emergency logistics center to the affected point, and use Lingo software to solve it. The numerical experiments are presented to show the feasibility and effectiveness of the proposed method.

  11. The Overall Odds Ratio as an Intuitive Effect Size Index for Multiple Logistic Regression: Examination of Further Refinements

    Science.gov (United States)

    Le, Huy; Marcus, Justin

    2012-01-01

    This study used Monte Carlo simulation to examine the properties of the overall odds ratio (OOR), which was recently introduced as an index for overall effect size in multiple logistic regression. It was found that the OOR was relatively independent of study base rate and performed better than most commonly used R-square analogs in indexing model…

  12. A Cloud Computing Model for Optimization of Transport Logistics Process

    Directory of Open Access Journals (Sweden)

    Benotmane Zineb

    2017-09-01

    Full Text Available In any increasing competitive environment and even in companies; we must adopt a good logistic chain management policy which is the main objective to increase the overall gain by maximizing profits and minimizing costs, including manufacturing costs such as: transaction, transport, storage, etc. In this paper, we propose a cloud platform of this chain logistic for decision support; in fact, this decision must be made to adopt new strategy for cost optimization, besides, the decision-maker must have knowledge on the consequences of this new strategy. Our proposed cloud computing platform has a multilayer structure; this later is contained from a set of web services to provide a link between applications using different technologies; to enable sending; and receiving data through protocols, which should be understandable by everyone. The chain logistic is a process-oriented business; it’s used to evaluate logistics process costs, to propose optimal solutions and to evaluate these solutions before their application. As a scenario, we have formulated the problem for the delivery process, and we have proposed a modified Bin-packing algorithm to improve vehicles loading.

  13. Network Design in Reverse Logistics: A Quantitative Model

    NARCIS (Netherlands)

    Krikke, H.R.; Kooij, E.J.; Schuur, Peter; Speranza, M. Grazia; Stähly, Paul

    1999-01-01

    The introduction of (extended) producer responsibility forces Original Equipment Manufacturers to solve entirely new managerial problems. One of the issues concerns the physical design of the reverse logistic network, which is a problem that fits into the class of facility-location problems. Since

  14. Evaluation of city logistics solutions with business model analysis

    NARCIS (Netherlands)

    Quak, H.J.; Balm, S.H.; Posthumus, B.

    2014-01-01

    Small scale, local demonstrations of which the outcomes are considered to be only appropriate within a specific context occur quite often in the field of city logistics. Various local demonstrations usually show a solution’s technical and operational feasibility. These often subsidized

  15. A Study on Logistics Cluster Competitiveness among Asia Main Countries using the Porter's Diamond Model

    OpenAIRE

    Tae Won Chung

    2016-01-01

    Measurement and discussions of logistics cluster competitiveness with a national approach are required to boost agglomeration effects and potentially create logistics efficiency and productivity. This study developed assessment criteria of logistics cluster competitiveness based on Porter's diamond model, calculated the weight of each criterion by the AHP method, and finally evaluated and discussed logistics cluster competitiveness among Asia main countries. The results indicate that there wa...

  16. Understanding the cost of capital of logistics service providers: an empirical investigation of multiple contingency variables

    OpenAIRE

    Lampe, Kerstin; Hofmann, Erik

    2014-01-01

    The article analyzes the influence of company-, industry- and market-related variables on the cost of capital of logistics service providers, as well as on their systematic risk. Financial information has become more and more important in strategic decision making (especially in the international context); in addition of being a measure of performance, the cost of capital is an important variable for logistics service providers in decisions about investing capital and developing the appropria...

  17. Research on support effectiveness modeling and simulating of aviation materiel autonomic logistics system

    Science.gov (United States)

    Zhou, Yan; Zhou, Yang; Yuan, Kai; Jia, Zhiyu; Li, Shuo

    2018-05-01

    Aiming at the demonstration of autonomic logistics system to be used at the new generation of aviation materiel in our country, the modeling and simulating method of aviation materiel support effectiveness considering autonomic logistics are studied. Firstly, this paper introduced the idea of JSF autonomic logistics and analyzed the influence of autonomic logistics on support effectiveness from aspects of reliability, false alarm rate, troubleshooting time, and support delay time and maintenance level. On this basis, the paper studies the modeling and simulating methods of support effectiveness considering autonomic logistics, and puts forward the maintenance support simulation process considering autonomic logistics. Finally, taking the typical aviation materiel as an example, this paper analyzes and verifies the above-mentioned support effectiveness modeling and simulating method of aviation materiel considering autonomic logistics.

  18. MATHEMATICAL MODEL FOR CALCULATION OF INFORMATION RISKS FOR INFORMATION AND LOGISTICS SYSTEM

    Directory of Open Access Journals (Sweden)

    A. G. Korobeynikov

    2015-05-01

    Full Text Available Subject of research. The paper deals with mathematical model for assessment calculation of information risks arising during transporting and distribution of material resources in the conditions of uncertainty. Meanwhile information risks imply the danger of origin of losses or damage as a result of application of information technologies by the company. Method. The solution is based on ideology of the transport task solution in stochastic statement with mobilization of mathematical modeling theory methods, the theory of graphs, probability theory, Markov chains. Creation of mathematical model is performed through the several stages. At the initial stage, capacity on different sites depending on time is calculated, on the basis of information received from information and logistic system, the weight matrix is formed and the digraph is under construction. Then there is a search of the minimum route which covers all specified vertexes by means of Dejkstra algorithm. At the second stage, systems of differential Kolmogorov equations are formed using information about the calculated route. The received decisions show probabilities of resources location in concrete vertex depending on time. At the third stage, general probability of the whole route passing depending on time is calculated on the basis of multiplication theorem of probabilities. Information risk, as time function, is defined by multiplication of the greatest possible damage by the general probability of the whole route passing. In this case information risk is measured in units of damage which corresponds to that monetary unit which the information and logistic system operates with. Main results. Operability of the presented mathematical model is shown on a concrete example of transportation of material resources where places of shipment and delivery, routes and their capacity, the greatest possible damage and admissible risk are specified. The calculations presented on a diagram showed

  19. A Note on the Item Information Function of the Four-Parameter Logistic Model

    Science.gov (United States)

    Magis, David

    2013-01-01

    This article focuses on four-parameter logistic (4PL) model as an extension of the usual three-parameter logistic (3PL) model with an upper asymptote possibly different from 1. For a given item with fixed item parameters, Lord derived the value of the latent ability level that maximizes the item information function under the 3PL model. The…

  20. Resource Allocation Optimization Model of Collaborative Logistics Network Based on Bilevel Programming

    Directory of Open Access Journals (Sweden)

    Xiao-feng Xu

    2017-01-01

    Full Text Available Collaborative logistics network resource allocation can effectively meet the needs of customers. It can realize the overall benefit maximization of the logistics network and ensure that collaborative logistics network runs orderly at the time of creating value. Therefore, this article is based on the relationship of collaborative logistics network supplier, the transit warehouse, and sellers, and we consider the uncertainty of time to establish a bilevel programming model with random constraints and propose a genetic simulated annealing hybrid intelligent algorithm to solve it. Numerical example shows that the method has stronger robustness and convergence; it can achieve collaborative logistics network resource allocation rationalization and optimization.

  1. Biomarker Detection in Association Studies: Modeling SNPs Simultaneously via Logistic ANOVA

    KAUST Repository

    Jung, Yoonsuh; Huang, Jianhua Z.; Hu, Jianhua

    2014-01-01

    In genome-wide association studies, the primary task is to detect biomarkers in the form of Single Nucleotide Polymorphisms (SNPs) that have nontrivial associations with a disease phenotype and some other important clinical/environmental factors. However, the extremely large number of SNPs comparing to the sample size inhibits application of classical methods such as the multiple logistic regression. Currently the most commonly used approach is still to analyze one SNP at a time. In this paper, we propose to consider the genotypes of the SNPs simultaneously via a logistic analysis of variance (ANOVA) model, which expresses the logit transformed mean of SNP genotypes as the summation of the SNP effects, effects of the disease phenotype and/or other clinical variables, and the interaction effects. We use a reduced-rank representation of the interaction-effect matrix for dimensionality reduction, and employ the L 1-penalty in a penalized likelihood framework to filter out the SNPs that have no associations. We develop a Majorization-Minimization algorithm for computational implementation. In addition, we propose a modified BIC criterion to select the penalty parameters and determine the rank number. The proposed method is applied to a Multiple Sclerosis data set and simulated data sets and shows promise in biomarker detection.

  2. Biomarker Detection in Association Studies: Modeling SNPs Simultaneously via Logistic ANOVA

    KAUST Repository

    Jung, Yoonsuh

    2014-10-02

    In genome-wide association studies, the primary task is to detect biomarkers in the form of Single Nucleotide Polymorphisms (SNPs) that have nontrivial associations with a disease phenotype and some other important clinical/environmental factors. However, the extremely large number of SNPs comparing to the sample size inhibits application of classical methods such as the multiple logistic regression. Currently the most commonly used approach is still to analyze one SNP at a time. In this paper, we propose to consider the genotypes of the SNPs simultaneously via a logistic analysis of variance (ANOVA) model, which expresses the logit transformed mean of SNP genotypes as the summation of the SNP effects, effects of the disease phenotype and/or other clinical variables, and the interaction effects. We use a reduced-rank representation of the interaction-effect matrix for dimensionality reduction, and employ the L 1-penalty in a penalized likelihood framework to filter out the SNPs that have no associations. We develop a Majorization-Minimization algorithm for computational implementation. In addition, we propose a modified BIC criterion to select the penalty parameters and determine the rank number. The proposed method is applied to a Multiple Sclerosis data set and simulated data sets and shows promise in biomarker detection.

  3. Evolution dynamics modeling and simulation of logistics enterprise's core competence based on service innovation

    Science.gov (United States)

    Yang, Bo; Tong, Yuting

    2017-04-01

    With the rapid development of economy, the development of logistics enterprises in China is also facing a huge challenge, especially the logistics enterprises generally lack of core competitiveness, and service innovation awareness is not strong. Scholars in the process of studying the core competitiveness of logistics enterprises are mainly from the perspective of static stability, not from the perspective of dynamic evolution to explore. So the author analyzes the influencing factors and the evolution process of the core competence of logistics enterprises, using the method of system dynamics to study the cause and effect of the evolution of the core competence of logistics enterprises, construct a system dynamics model of evolution of core competence logistics enterprises, which can be simulated by vensim PLE. The analysis for the effectiveness and sensitivity of simulation model indicates the model can be used as the fitting of the evolution process of the core competence of logistics enterprises and reveal the process and mechanism of the evolution of the core competence of logistics enterprises, and provide management strategies for improving the core competence of logistics enterprises. The construction and operation of computer simulation model offers a kind of effective method for studying the evolution of logistics enterprise core competence.

  4. A Generalized Logistic Regression Procedure to Detect Differential Item Functioning among Multiple Groups

    Science.gov (United States)

    Magis, David; Raiche, Gilles; Beland, Sebastien; Gerard, Paul

    2011-01-01

    We present an extension of the logistic regression procedure to identify dichotomous differential item functioning (DIF) in the presence of more than two groups of respondents. Starting from the usual framework of a single focal group, we propose a general approach to estimate the item response functions in each group and to test for the presence…

  5. Logistical modelling of managerial decisions in social and marketing business systems

    Directory of Open Access Journals (Sweden)

    Oleksandr Velychko

    2017-10-01

    Full Text Available Logistical modelling of business systems within the context of mathematical logistics, logistical management, operational research as well as rationalistic provision of logistics at an enterprise have been considered in the article. The research was carried out on the methodological basis which included the authors’ developments and implied conveying familiar knowledge on new objects within the field of linear programming. Scientific novelty concerns the development of categorical toolkit as well as the existing methodical approaches of rationalistic logistics to managerial decisions. Rational areas of using terms “logistical model” and “model of logistics” in business environment have been determined. The authors’ methodology of constructing logistical models in management of separate social and marketing systems of enterprises according to minimization and maximization criteria is presented. Ways of using modelling at not conventional objects of logistical support for managerial decisions have been suggested in the context of studying the moral psychological climate of staff and complex estimation of socioeconomic measures of staff management improvement. The procedure of logistical optimization in the system of distributing and advertising activity of the enterprise has been developed. Approbation of the developed models has been carried out and possibilities for further model’s complication by output data, variables, and limitations under specific practical conditions have been grounded.

  6. SPD-based Logistics Management Model of Medical Consumables in Hospitals

    Science.gov (United States)

    LIU, Tongzhu; SHEN, Aizong; HU, Xiaojian; TONG, Guixian; GU, Wei; YANG, Shanlin

    2016-01-01

    Background: With the rapid development of health services, the progress of medical science and technology, and the improvement of materials research, the consumption of medical consumables (MCs) in medical activities has increased in recent years. However, owing to the lack of effective management methods and the complexity of MCs, there are several management problems including MC waste, low management efficiency, high management difficulty, and frequent medical accidents. Therefore, there is urgent need for an effective logistics management model to handle these problems and challenges in hospitals. Methods: We reviewed books and scientific literature (by searching the articles published from 2010 to 2015 in Engineering Village database) to understand supply chain related theories and methods and performed field investigations in hospitals across many cities to determine the actual state of MC logistics management of hospitals in China. Results: We describe the definition, physical model, construction, and logistics operation processes of the supply, processing, and distribution (SPD) of MC logistics because of the traditional SPD model. With the establishment of a supply-procurement platform and a logistics lean management system, we applied the model to the MC logistics management of Anhui Provincial Hospital with good effects. Conclusion: The SPD model plays a critical role in optimizing the logistics procedures of MCs, improving the management efficiency of logistics, and reducing the costs of logistics of hospitals in China. PMID:27957435

  7. SPD-based Logistics Management Model of Medical Consumables in Hospitals.

    Science.gov (United States)

    Liu, Tongzhu; Shen, Aizong; Hu, Xiaojian; Tong, Guixian; Gu, Wei; Yang, Shanlin

    2016-10-01

    With the rapid development of health services, the progress of medical science and technology, and the improvement of materials research, the consumption of medical consumables (MCs) in medical activities has increased in recent years. However, owing to the lack of effective management methods and the complexity of MCs, there are several management problems including MC waste, low management efficiency, high management difficulty, and frequent medical accidents. Therefore, there is urgent need for an effective logistics management model to handle these problems and challenges in hospitals. We reviewed books and scientific literature (by searching the articles published from 2010 to 2015 in Engineering Village database) to understand supply chain related theories and methods and performed field investigations in hospitals across many cities to determine the actual state of MC logistics management of hospitals in China. We describe the definition, physical model, construction, and logistics operation processes of the supply, processing, and distribution (SPD) of MC logistics because of the traditional SPD model. With the establishment of a supply-procurement platform and a logistics lean management system, we applied the model to the MC logistics management of Anhui Provincial Hospital with good effects. The SPD model plays a critical role in optimizing the logistics procedures of MCs, improving the management efficiency of logistics, and reducing the costs of logistics of hospitals in China.

  8. Forecast Model of Urban Stagnant Water Based on Logistic Regression

    Directory of Open Access Journals (Sweden)

    Liu Pan

    2017-01-01

    Full Text Available With the development of information technology, the construction of water resource system has been gradually carried out. In the background of big data, the work of water information needs to carry out the process of quantitative to qualitative change. Analyzing the correlation of data and exploring the deep value of data which are the key of water information’s research. On the basis of the research on the water big data and the traditional data warehouse architecture, we try to find out the connection of different data source. According to the temporal and spatial correlation of stagnant water and rainfall, we use spatial interpolation to integrate data of stagnant water and rainfall which are from different data source and different sensors, then use logistic regression to find out the relationship between them.

  9. Parental Vaccine Acceptance: A Logistic Regression Model Using Previsit Decisions.

    Science.gov (United States)

    Lee, Sara; Riley-Behringer, Maureen; Rose, Jeanmarie C; Meropol, Sharon B; Lazebnik, Rina

    2017-07-01

    This study explores how parents' intentions regarding vaccination prior to their children's visit were associated with actual vaccine acceptance. A convenience sample of parents accompanying 6-week-old to 17-year-old children completed a written survey at 2 pediatric practices. Using hierarchical logistic regression, for hospital-based participants (n = 216), vaccine refusal history ( P < .01) and vaccine decision made before the visit ( P < .05) explained 87% of vaccine refusals. In community-based participants (n = 100), vaccine refusal history ( P < .01) explained 81% of refusals. Over 1 in 5 parents changed their minds about vaccination during the visit. Thirty parents who were previous vaccine refusers accepted current vaccines, and 37 who had intended not to vaccinate choose vaccination. Twenty-nine parents without a refusal history declined vaccines, and 32 who did not intend to refuse before the visit declined vaccination. Future research should identify key factors to nudge parent decision making in favor of vaccination.

  10. An Agent Based Modelling Approach for Multi-Stakeholder Analysis of City Logistics Solutions

    NARCIS (Netherlands)

    Anand, N.

    2015-01-01

    This thesis presents a comprehensive framework for multi-stakeholder analysis of city logistics solutions using agent based modeling. The framework describes different stages for the systematic development of an agent based model for the city logistics domain. The framework includes a

  11. Logistic regression models of factors influencing the location of bioenergy and biofuels plants

    Science.gov (United States)

    T.M. Young; R.L. Zaretzki; J.H. Perdue; F.M. Guess; X. Liu

    2011-01-01

    Logistic regression models were developed to identify significant factors that influence the location of existing wood-using bioenergy/biofuels plants and traditional wood-using facilities. Logistic models provided quantitative insight for variables influencing the location of woody biomass-using facilities. Availability of "thinnings to a basal area of 31.7m2/ha...

  12. Integrating the augmented SCOR model and the ISO 15288 life cycle model into a single logistic model

    CSIR Research Space (South Africa)

    Schmitz, Peter MU

    2010-07-01

    Full Text Available using the Supply Chain Operations Reference (SCOR) model. The SANDF indicated that the augmented SCOR model (Bean, Schmitz and Engelbrecht, 2009) should be extended into a single logistics process which should include a life-cycle perspective...

  13. A Reverse Logistics Network Model for Handling Returned Products

    Directory of Open Access Journals (Sweden)

    Nizar Zaarour

    2014-07-01

    obtained the optimal solution at a fraction of the time used by the traditional nonlinear model and solution procedure, as well as the ability to handle up to 150 customers as compared to 30 in the conventional nonlinear model. As such, the proposed linear model is more suitable for actual industry applications than the existing models.

  14. Design, modeling, and analysis of a feedstock logistics system.

    Science.gov (United States)

    Judd, Jason D; Sarin, Subhash C; Cundiff, John S

    2012-01-01

    Given the location of a bio-energy plant for the conversion of biomass to bio-energy, a feedstock logistics system that relies on the use of satellite storage locations (SSLs) for temporary storage and loading of round bales is proposed. Three equipment systems are considered for handling biomass at the SSLs, and they are either placed permanently or are mobile and thereby travel from one SSL to another. A mathematical programming-based approach is utilized to determine SSLs and equipment routes in order to minimize the total cost. The use of a Side-loading Rack System results in average savings of 21.3% over a Densification System while a Rear-loading Rack System is more expensive to operate than either of the other equipment systems. The utilization of mobile equipment results in average savings of 14.8% over the equipment placed permanently. Furthermore, the Densification System is not justifiable for transportation distances less than 81 km. Copyright © 2011 Elsevier Ltd. All rights reserved.

  15. Comment on ``Correlated noise in a logistic growth model''

    Science.gov (United States)

    Behera, Anita; O'Rourke, S. Francesca C.

    2008-01-01

    We argue that the results published by Ai [Phys. Rev. E 67, 022903 (2003)] on “correlated noise in logistic growth” are not correct. Their conclusion that, for larger values of the correlation parameter λ , the cell population is peaked at x=0 , which denotes a high extinction rate, is also incorrect. We find the reverse behavior to their results, that increasing λ promotes the stable growth of tumor cells. In particular, their results for the steady-state probability, as a function of cell number, at different correlation strengths, presented in Figs. 1 and 2 of their paper show different behavior than one would expect from the simple mathematical expression for the steady-state probability. Additionally, their interpretation that at small values of cell number the steady-state probability increases as the correlation parameter is increased is also questionable. Another striking feature in their Figs. 1 and 3 is that, for the same values of the parameters λ and α , their simulation produces two different curves, both qualitatively and quantitatively.

  16. Logistic regression model for detecting radon prone areas in Ireland.

    Science.gov (United States)

    Elío, J; Crowley, Q; Scanlon, R; Hodgson, J; Long, S

    2017-12-01

    A new high spatial resolution radon risk map of Ireland has been developed, based on a combination of indoor radon measurements (n=31,910) and relevant geological information (i.e. Bedrock Geology, Quaternary Geology, soil permeability and aquifer type). Logistic regression was used to predict the probability of having an indoor radon concentration above the national reference level of 200Bqm -3 in Ireland. The four geological datasets evaluated were found to be statistically significant, and, based on combinations of these four variables, the predicted probabilities ranged from 0.57% to 75.5%. Results show that the Republic of Ireland may be divided in three main radon risk categories: High (HR), Medium (MR) and Low (LR). The probability of having an indoor radon concentration above 200Bqm -3 in each area was found to be 19%, 8% and 3%; respectively. In the Republic of Ireland, the population affected by radon concentrations above 200Bqm -3 is estimated at ca. 460k (about 10% of the total population). Of these, 57% (265k), 35% (160k) and 8% (35k) are in High, Medium and Low Risk Areas, respectively. Our results provide a high spatial resolution utility which permit customised radon-awareness information to be targeted at specific geographic areas. Copyright © 2017 Elsevier B.V. All rights reserved.

  17. Impact of Disturbing Factors on Cooperation in Logistics Outsourcing Performance: The Empirical Model

    Directory of Open Access Journals (Sweden)

    Andreja Križman

    2010-05-01

    Full Text Available The purpose of this paper is to present the research results of a study conducted in the Slovene logistics market of conflicts and opportunism as disturbing factors while examining their impact on cooperation in logistics outsourcing performance. Relationship variables are proposed that directly or indirectly affect logistics performance and conceptualize the hypotheses based on causal linkages for the constructs. On the basis of extant literature and new argumentations that are derived from in-depth interviews of logistics experts, including providers and customers, the measurement and structural models are empirically analyzed. Existing measurement scales for the constructs are slightly modified for this analysis. Purification testing and measurement for validity and reliability are performed. Multivariate statistical methods are utilized and hypotheses are tested. The results show that conflicts have a significantly negative impact on cooperation between customers and logistics service providers (LSPs, while opportunism does not play an important role in these relationships. The observed antecedents of logistics outsourcing performance in the model account for 58.4% of the variance of the goal achievement and 36.5% of the variance of the exceeded goal. KEYWORDS: logistics outsourcing performance; logistics customer–provider relationships; conflicts and cooperation in logistics outsourcing; PLS path modelling

  18. Geometrical model of multiple production

    International Nuclear Information System (INIS)

    Chikovani, Z.E.; Jenkovszky, L.L.; Kvaratshelia, T.M.; Struminskij, B.V.

    1988-01-01

    The relation between geometrical and KNO-scaling and their violation is studied in a geometrical model of multiple production of hadrons. Predictions concerning the behaviour of correlation coefficients at future accelerators are given

  19. A development of logistics management models for the Space Transportation System

    Science.gov (United States)

    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.

  20. UML Modeling for Dynamic Logistics System Based on DEVS

    OpenAIRE

    Zhang Zhiyong; Liu Jie; Zhang Xinhui

    2013-01-01

    DEVS is a hierarchical and modular system descriptive method. However, it cannot describe dynamic process and relationship of system members. This article has proposed a way to extend UML using stereotype, making it suitable for simulation modeling. To build a modeling tool, we defined atomic model class and coupled model class, both of which are in line with not only DEVS’s hierarchical and modular requirements but also UML’s object-oriented characteristics. At last, we use the tool to analy...

  1. Incorporating Logistics in Freight Transport Demand Models: State-of-the-Art and Research Opportunities

    NARCIS (Netherlands)

    Tavasszy, L.A.; Ruijgrok, K.; Davydenko, I.

    2012-01-01

    Freight transport demand is a demand derived from all the activities needed to move goods between locations of production to locations of consumption, including trade, logistics and transportation. A good representation of logistics in freight transport demand models allows us to predict the effects

  2. Logistic Regression Modeling of Diminishing Manufacturing Sources for Integrated Circuits

    National Research Council Canada - National Science Library

    Gravier, Michael

    1999-01-01

    .... This thesis draws on available data from the electronics integrated circuit industry to attempt to assess whether statistical modeling offers a viable method for predicting the presence of DMSMS...

  3. WASTES: a waste management logistics/economics model

    International Nuclear Information System (INIS)

    McNair, G.W.; Shay, M.R.; Fletcher, J.F.; Cashwell, J.W.

    1985-02-01

    The WASTES model simulates a user defined system for nuclear waste transportation and storage at both temporary and long-term storage facilities. The model is written in FORTRAN 77 as an extension to the SLAM commercial simulation package (Pritsker and Pegden 1979). SLAM (Simulation Language for Alternative Modeling) is utilized in a discrete event mode to model the passage of spent fuel through the system. The system is initiated with individual reactor discharges of spent fuel as described in the reactor discharge data file or as supplied by the user. The reactor discharge file contains deterministic information on the date (year/month) and quantity of spent fuel discharges. From this point, the model is controlled by a combination of source originated and destination originated transfers. Source driven transfers occur when a reactor pool violates the full core reserve (FCR) storage margin or when the reactor is decommissioned. At these times, the source reactor checks destination facilities to see if they can accept material. A dry storage facility is assumed to exist for each reactor and is allowed to grow as necessary to contain spent fuel which cannot be shipped to any other facility. In this way the FCR margin is always maintained. Destination driven transfers occur when the annual capacity of a facility will not be met by full core reserve or decommissioning shipments. An attempt is made at the end of each calendar year to schedule enough shipments of spent fuel from facilities with non-critical storage capacity to fill the annual capacity of each destination facility. Allowable facility types are reprocessing plants, federal interim storage (FIS), monitored retrievable storage (MRS), and repositories. The number, capacities, location and priority for receipt of spent fuel is user specified. This report describes in detail the waste generating model, the waste facilities model, the transportation model and the basic transportation scheme

  4. LOGAM (Logistic Analysis Model). Volume 2. Users Manual.

    Science.gov (United States)

    1982-08-01

    as opposed to simulation models which represent a system’s behavior as a function of time. These latter classes of models are often complex. They...includes the cost of ammunition and missiles comsumed by the system being costed during unit training. Excluded is the cost of ammunition consumed during...data. The results obtained from sensitivity testing may be used to construct graphs which display the behavior of the maintenance concept over the range

  5. Model of the naval base logistic interoperability within the multinational operations

    Directory of Open Access Journals (Sweden)

    Bohdan Pac

    2011-12-01

    Full Text Available The paper concerns the model of the naval base logistics interoperability within the multinational operations conducted at sea by NATO or EU nations. The model includes the set of logistic requirements that NATO and EU expect from the contributing nations within the area of the logistic support provided to the forces operating out of the home bases. Model may reflect the scheme configuration, the set of requirements and its mathematical description for the naval base supporting multinational forces within maritime operations.

  6. Business Process Modeling for Domain Inbound Logistics System : Analytical Perspective with BPMN 2.0

    OpenAIRE

    Khabbazi, Mahmood Reza; Hasan, M. K; Sulaiman, R; Shapi’i, A

    2013-01-01

    Among different Business Process Management strategies and methodologies, one common feature is to captureexisting processes and representing the new processes adequately. Business Process Modelling (BPM) plays acrucial role on such an effort. This paper proposes a “to-be” inbound logistics business processes model usingBPMN 2.0 standard specifying the structure and behaviour of the system within the SME environment. Thegeneric framework of inbound logistics model consists of one main high-le...

  7. Application of Tecnomatix Plant Simulation for Modeling Production and Logistics Processes

    Directory of Open Access Journals (Sweden)

    Julia Siderska

    2016-06-01

    Full Text Available The main objective of the article was to present the possibilities and examples of using Tecnomatix Plant Simulation (by Siemens to simulate the production and logistics processes. This tool allows to simulate discrete events and create digital models of logistic systems (e.g. production, optimize the operation of production plants, production lines, as well as individual logistics processes. The review of implementations of Tecnomatix Plant Simulation for modeling processes in production engineering and logistics was conducted and a few selected examples of simulations were presented. The author’s future studies are going to focus on simulation of production and logistic processes and their optimization with the use of genetic algorithms and artificial neural networks.

  8. Gaussian Process Regression Model in Spatial Logistic Regression

    Science.gov (United States)

    Sofro, A.; Oktaviarina, A.

    2018-01-01

    Spatial analysis has developed very quickly in the last decade. One of the favorite approaches is based on the neighbourhood of the region. Unfortunately, there are some limitations such as difficulty in prediction. Therefore, we offer Gaussian process regression (GPR) to accommodate the issue. In this paper, we will focus on spatial modeling with GPR for binomial data with logit link function. The performance of the model will be investigated. We will discuss the inference of how to estimate the parameters and hyper-parameters and to predict as well. Furthermore, simulation studies will be explained in the last section.

  9. Variable selection in Logistic regression model with genetic algorithm.

    Science.gov (United States)

    Zhang, Zhongheng; Trevino, Victor; Hoseini, Sayed Shahabuddin; Belciug, Smaranda; Boopathi, Arumugam Manivanna; Zhang, Ping; Gorunescu, Florin; Subha, Velappan; Dai, Songshi

    2018-02-01

    Variable or feature selection is one of the most important steps in model specification. Especially in the case of medical-decision making, the direct use of a medical database, without a previous analysis and preprocessing step, is often counterproductive. In this way, the variable selection represents the method of choosing the most relevant attributes from the database in order to build a robust learning models and, thus, to improve the performance of the models used in the decision process. In biomedical research, the purpose of variable selection is to select clinically important and statistically significant variables, while excluding unrelated or noise variables. A variety of methods exist for variable selection, but none of them is without limitations. For example, the stepwise approach, which is highly used, adds the best variable in each cycle generally producing an acceptable set of variables. Nevertheless, it is limited by the fact that it commonly trapped in local optima. The best subset approach can systematically search the entire covariate pattern space, but the solution pool can be extremely large with tens to hundreds of variables, which is the case in nowadays clinical data. Genetic algorithms (GA) are heuristic optimization approaches and can be used for variable selection in multivariable regression models. This tutorial paper aims to provide a step-by-step approach to the use of GA in variable selection. The R code provided in the text can be extended and adapted to other data analysis needs.

  10. Modeling Logistic Performance in Quantitative Microbial Risk Assessment

    NARCIS (Netherlands)

    Rijgersberg, H.; Tromp, S.O.; Jacxsens, L.; Uyttendaele, M.

    2010-01-01

    In quantitative microbial risk assessment (QMRA), food safety in the food chain is modeled and simulated. In general, prevalences, concentrations, and numbers of microorganisms in media are investigated in the different steps from farm to fork. The underlying rates and conditions (such as storage

  11. The logistic model-generated carrying capacities for wild herbivores ...

    African Journals Online (AJOL)

    Jesse

    Under this formulation, both carrying capacity and exchange ratios are endogenously determined (Kinyua and Njoka, 2001), making it possible to empirically estimate the population growth models for Grant's gazelle, Thompson's gazelle and Zebra. (1) for i = 1,…,n-1 j = 1,…,2 and i ≠ j. Here Hit+1, measured in animal units, ...

  12. Determining factors influencing survival of breast cancer by fuzzy logistic regression model.

    Science.gov (United States)

    Nikbakht, Roya; Bahrampour, Abbas

    2017-01-01

    Fuzzy logistic regression model can be used for determining influential factors of disease. This study explores the important factors of actual predictive survival factors of breast cancer's patients. We used breast cancer data which collected by cancer registry of Kerman University of Medical Sciences during the period of 2000-2007. The variables such as morphology, grade, age, and treatments (surgery, radiotherapy, and chemotherapy) were applied in the fuzzy logistic regression model. Performance of model was determined in terms of mean degree of membership (MDM). The study results showed that almost 41% of patients were in neoplasm and malignant group and more than two-third of them were still alive after 5-year follow-up. Based on the fuzzy logistic model, the most important factors influencing survival were chemotherapy, morphology, and radiotherapy, respectively. Furthermore, the MDM criteria show that the fuzzy logistic regression have a good fit on the data (MDM = 0.86). Fuzzy logistic regression model showed that chemotherapy is more important than radiotherapy in survival of patients with breast cancer. In addition, another ability of this model is calculating possibilistic odds of survival in cancer patients. The results of this study can be applied in clinical research. Furthermore, there are few studies which applied the fuzzy logistic models. Furthermore, we recommend using this model in various research areas.

  13. A Log Logistic Survival Model Applied to Hypobaric Decompression Sickness

    Science.gov (United States)

    Conkin, Johnny

    2001-01-01

    Decompression sickness (DCS) is a complex, multivariable problem. A mathematical description or model of the likelihood of DCS requires a large amount of quality research data, ideas on how to define a decompression dose using physical and physiological variables, and an appropriate analytical approach. It also requires a high-performance computer with specialized software. I have used published DCS data to develop my decompression doses, which are variants of equilibrium expressions for evolved gas plus other explanatory variables. My analytical approach is survival analysis, where the time of DCS occurrence is modeled. My conclusions can be applied to simple hypobaric decompressions - ascents lasting from 5 to 30 minutes - and, after minutes to hours, to denitrogenation (prebreathing). They are also applicable to long or short exposures, and can be used whether the sufferer of DCS is at rest or exercising at altitude. Ultimately I would like my models to be applied to astronauts to reduce the risk of DCS during spacewalks, as well as to future spaceflight crews on the Moon and Mars.

  14. An appraisal of convergence failures in the application of logistic regression model in published manuscripts.

    Science.gov (United States)

    Yusuf, O B; Bamgboye, E A; Afolabi, R F; Shodimu, M A

    2014-09-01

    Logistic regression model is widely used in health research for description and predictive purposes. Unfortunately, most researchers are sometimes not aware that the underlying principles of the techniques have failed when the algorithm for maximum likelihood does not converge. Young researchers particularly postgraduate students may not know why separation problem whether quasi or complete occurs, how to identify it and how to fix it. This study was designed to critically evaluate convergence issues in articles that employed logistic regression analysis published in an African Journal of Medicine and medical sciences between 2004 and 2013. Problems of quasi or complete separation were described and were illustrated with the National Demographic and Health Survey dataset. A critical evaluation of articles that employed logistic regression was conducted. A total of 581 articles was reviewed, of which 40 (6.9%) used binary logistic regression. Twenty-four (60.0%) stated the use of logistic regression model in the methodology while none of the articles assessed model fit. Only 3 (12.5%) properly described the procedures. Of the 40 that used the logistic regression model, the problem of convergence occurred in 6 (15.0%) of the articles. Logistic regression tends to be poorly reported in studies published between 2004 and 2013. Our findings showed that the procedure may not be well understood by researchers since very few described the process in their reports and may be totally unaware of the problem of convergence or how to deal with it.

  15. The Application of Collaborative Business Intelligence Technology in the Hospital SPD Logistics Management Model

    Science.gov (United States)

    LIU, Tongzhu; SHEN, Aizong; HU, Xiaojian; TONG, Guixian; GU, Wei

    2017-01-01

    Background: We aimed to apply collaborative business intelligence (BI) system to hospital supply, processing and distribution (SPD) logistics management model. Methods: We searched Engineering Village database, China National Knowledge Infrastructure (CNKI) and Google for articles (Published from 2011 to 2016), books, Web pages, etc., to understand SPD and BI related theories and recent research status. For the application of collaborative BI technology in the hospital SPD logistics management model, we realized this by leveraging data mining techniques to discover knowledge from complex data and collaborative techniques to improve the theories of business process. Results: For the application of BI system, we: (i) proposed a layered structure of collaborative BI system for intelligent management in hospital logistics; (ii) built data warehouse for the collaborative BI system; (iii) improved data mining techniques such as supporting vector machines (SVM) and swarm intelligence firefly algorithm to solve key problems in hospital logistics collaborative BI system; (iv) researched the collaborative techniques oriented to data and business process optimization to improve the business processes of hospital logistics management. Conclusion: Proper combination of SPD model and BI system will improve the management of logistics in the hospitals. The successful implementation of the study requires: (i) to innovate and improve the traditional SPD model and make appropriate implement plans and schedules for the application of BI system according to the actual situations of hospitals; (ii) the collaborative participation of internal departments in hospital including the department of information, logistics, nursing, medical and financial; (iii) timely response of external suppliers. PMID:28828316

  16. The Application of Collaborative Business Intelligence Technology in the Hospital SPD Logistics Management Model.

    Science.gov (United States)

    Liu, Tongzhu; Shen, Aizong; Hu, Xiaojian; Tong, Guixian; Gu, Wei

    2017-06-01

    We aimed to apply collaborative business intelligence (BI) system to hospital supply, processing and distribution (SPD) logistics management model. We searched Engineering Village database, China National Knowledge Infrastructure (CNKI) and Google for articles (Published from 2011 to 2016), books, Web pages, etc., to understand SPD and BI related theories and recent research status. For the application of collaborative BI technology in the hospital SPD logistics management model, we realized this by leveraging data mining techniques to discover knowledge from complex data and collaborative techniques to improve the theories of business process. For the application of BI system, we: (i) proposed a layered structure of collaborative BI system for intelligent management in hospital logistics; (ii) built data warehouse for the collaborative BI system; (iii) improved data mining techniques such as supporting vector machines (SVM) and swarm intelligence firefly algorithm to solve key problems in hospital logistics collaborative BI system; (iv) researched the collaborative techniques oriented to data and business process optimization to improve the business processes of hospital logistics management. Proper combination of SPD model and BI system will improve the management of logistics in the hospitals. The successful implementation of the study requires: (i) to innovate and improve the traditional SPD model and make appropriate implement plans and schedules for the application of BI system according to the actual situations of hospitals; (ii) the collaborative participation of internal departments in hospital including the department of information, logistics, nursing, medical and financial; (iii) timely response of external suppliers.

  17. A Study on Intelligent User-Centric Logistics Service Model Using Ontology

    Directory of Open Access Journals (Sweden)

    Saraswathi Sivamani

    2014-01-01

    Full Text Available Much research has been undergone in the smart logistics environment for the prompt delivery of the product in the right place at the right time. Most of the services were based on time management, routing technique, and location based services. The services in the recent logistics environment aim for situation based logistics service centered around the user by utilizing various information technologies such as mobile devices, computer systems, and GPS. This paper proposes a smart logistics service model for providing user-centric intelligent logistics service by utilizing smartphones in a smart environment. We also develop an OWL based ontology model for the smart logistics for the better understanding among the context information. In addition to basic delivery information, the proposed service model makes use of the location and situation information of the delivery vehicle and user, to draw the route information according to the user’s requirement. With the increase of internet usage, the real-time situations are received which helps to create a more reliable relationship, owing to the Internet of Things. Through this service model, it is possible to engage in the development of various IT and logistics convergence services based on situation information between the deliverer and user which occurs in real time.

  18. Enterprise games: creating and implementing a model to simulate logistics operations

    Directory of Open Access Journals (Sweden)

    Alander Ornellas Ornellas

    2008-07-01

    Full Text Available This work proposes an enterprise game model to simulate the main logistics operations in a supply chain. The need of a simple tool, but well structured and able to create a dynamic learning environment without making it too complex motivated this study and development. The work begins with a comparative analysis between the main reference models about enterprise logistics, included in the bibliography related to best practices in logistics decision-making. Then, concepts of simulation and games are described, its interrelations, characteristics and importance as learning method. The definition of the best practices is, then, used to guide the construction of the main characteristics for the proposed model. The results obtained show the efficacy of the model as a tool capable of creating a dynamic environment for learning purposes to complement traditional teaching techniques. Key-words: Enterprise Games, Supply Chain, Logistics, Simulation, Learning.

  19. Application of the TDABC model in the logistics process using different capacity cost rates

    Directory of Open Access Journals (Sweden)

    Paulo Afonso

    2016-12-01

    Full Text Available Purpose: The understanding of logistics process in terms of costs and profitability is a complex task and there is a need of more research and applied work on these issues. In this research project, the concepts underlying Time-Driven Activity Based Costing (TDABC have been used in the context of logistics costs. Design/methodology/approach: A Distribution Centre of wood and carpentry related materials has been studied. A multidisciplinary team has been composed to support the project including the researchers and three employees of the company responsible for accounting, logistics and warehousing. The design and implementation of the costing model asked for a deep understanding of the different tasks and processes that should be considered. Accordingly, a TDABC model for the logistics function was developed. Findings: The cost model presented here is supported on a series of time equations designed for the logistics function which allow the analysis and discussion of costs and profitability of different cost objects namely, products, clients, distribution channels, processes and activities. The cost of unused capacity and the effectiveness of logistics processes are also highlighted in this model. Research limitations/implications: In a case study, results and implications cannot be directly or immediately generalized. Nevertheless, the proposed time equations and cost model can be easily adapted to explain other types of logistics functions and it gives the foundations or other TDABC models with more than one capacity cost rate. Practical implications: The TDABC model developed in this case study can be used in similar cases and as a basis for the analysis of logistics costs in other logistics processes. Furthermore, managers can rely on the proposed approach to analyze products’ profitability and logistics cost structure.  Originality/value: In this case, different capacity cost rates were computed in order to reflect appropriately the

  20. Application of the TDABC model in the logistics process using different capacity cost rates

    International Nuclear Information System (INIS)

    Afonso, Paulo; Santana, Alex

    2016-01-01

    Purpose: The understanding of logistics process in terms of costs and profitability is a complex task and there is a need of more research and applied work on these issues. In this research project, the concepts underlying Time-Driven Activity Based Costing (TDABC) have been used in the context of logistics costs. Design/methodology/approach: A Distribution Centre of wood and carpentry related materials has been studied. A multidisciplinary team has been composed to support the project including the researchers and three employees of the company responsible for accounting, logistics and warehousing. The design and implementation of the costing model asked for a deep understanding of the different tasks and processes that should be considered. Accordingly, a TDABC model for the logistics function was developed. Findings: The cost model presented here is supported on a series of time equations designed for the logistics function which allow the analysis and discussion of costs and profitability of different cost objects namely, products, clients, distribution channels, processes and activities. The cost of unused capacity and the effectiveness of logistics processes are also highlighted in this model. Research limitations/implications: In a case study, results and implications cannot be directly or immediately generalized. Nevertheless, the proposed time equations and cost model can be easily adapted to explain other types of logistics functions and it gives the foundations or other TDABC models with more than one capacity cost rate. Practical implications: The TDABC model developed in this case study can be used in similar cases and as a basis for the analysis of logistics costs in other logistics processes. Furthermore, managers can rely on the proposed approach to analyze products’ profitability and logistics cost structure. Originality/value: In this case, different capacity cost rates were computed in order to reflect appropriately the logistics function which

  1. Application of the TDABC model in the logistics process using different capacity cost rates

    Energy Technology Data Exchange (ETDEWEB)

    Afonso, Paulo; Santana, Alex

    2016-07-01

    Purpose: The understanding of logistics process in terms of costs and profitability is a complex task and there is a need of more research and applied work on these issues. In this research project, the concepts underlying Time-Driven Activity Based Costing (TDABC) have been used in the context of logistics costs. Design/methodology/approach: A Distribution Centre of wood and carpentry related materials has been studied. A multidisciplinary team has been composed to support the project including the researchers and three employees of the company responsible for accounting, logistics and warehousing. The design and implementation of the costing model asked for a deep understanding of the different tasks and processes that should be considered. Accordingly, a TDABC model for the logistics function was developed. Findings: The cost model presented here is supported on a series of time equations designed for the logistics function which allow the analysis and discussion of costs and profitability of different cost objects namely, products, clients, distribution channels, processes and activities. The cost of unused capacity and the effectiveness of logistics processes are also highlighted in this model. Research limitations/implications: In a case study, results and implications cannot be directly or immediately generalized. Nevertheless, the proposed time equations and cost model can be easily adapted to explain other types of logistics functions and it gives the foundations or other TDABC models with more than one capacity cost rate. Practical implications: The TDABC model developed in this case study can be used in similar cases and as a basis for the analysis of logistics costs in other logistics processes. Furthermore, managers can rely on the proposed approach to analyze products’ profitability and logistics cost structure. Originality/value: In this case, different capacity cost rates were computed in order to reflect appropriately the logistics function which

  2. Vehicle coordinated transportation dispatching model base on multiple crisis locations

    Science.gov (United States)

    Tian, Ran; Li, Shanwei; Yang, Guoying

    2018-05-01

    Many disastrous events are often caused after unconventional emergencies occur, and the requirements of disasters are often different. It is difficult for a single emergency resource center to satisfy such requirements at the same time. Therefore, how to coordinate the emergency resources stored by multiple emergency resource centers to various disaster sites requires the coordinated transportation of emergency vehicles. In this paper, according to the problem of emergency logistics coordination scheduling, based on the related constraints of emergency logistics transportation, an emergency resource scheduling model based on multiple disasters is established.

  3. Assessment of RFID Investment in the Military Logistics Systems Through The Life Cycle Cost (LCC) Model

    OpenAIRE

    Ozdemir, Ahmet; Bayrak, Mustafa

    2015-01-01

    Radio Frequency Identification (RFID) is an emerging technology that has been recently used in numerous business and public fields. Most military applications of RFID have focused on logistics systems. Since RFID investment requires high initial cost and its benefits are hard to see in the short term, it needs an appropriate investment decision model. The purpose of this research is to propose a Life Cycle Cost (LCC) model for RFID integration into the Military Logistics System (MLS). The stu...

  4. A logistic regression model for Ghana National Health Insurance claims

    Directory of Open Access Journals (Sweden)

    Samuel Antwi

    2013-07-01

    Full Text Available In August 2003, the Ghanaian Government made history by implementing the first National Health Insurance System (NHIS in Sub-Saharan Africa. Within three years, over half of the country’s population had voluntarily enrolled into the National Health Insurance Scheme. This study had three objectives: 1 To estimate the risk factors that influences the Ghana national health insurance claims. 2 To estimate the magnitude of each of the risk factors in relation to the Ghana national health insurance claims. In this work, data was collected from the policyholders of the Ghana National Health Insurance Scheme with the help of the National Health Insurance database and the patients’ attendance register of the Koforidua Regional Hospital, from 1st January to 31st December 2011. Quantitative analysis was done using the generalized linear regression (GLR models. The results indicate that risk factors such as sex, age, marital status, distance and length of stay at the hospital were important predictors of health insurance claims. However, it was found that the risk factors; health status, billed charges and income level are not good predictors of national health insurance claim. The outcome of the study shows that sex, age, marital status, distance and length of stay at the hospital are statistically significant in the determination of the Ghana National health insurance premiums since they considerably influence claims. We recommended, among other things that, the National Health Insurance Authority should facilitate the institutionalization of the collection of appropriate data on a continuous basis to help in the determination of future premiums.

  5. Predictive market segmentation model: An application of logistic regression model and CHAID procedure

    Directory of Open Access Journals (Sweden)

    Soldić-Aleksić Jasna

    2009-01-01

    Full Text Available Market segmentation presents one of the key concepts of the modern marketing. The main goal of market segmentation is focused on creating groups (segments of customers that have similar characteristics, needs, wishes and/or similar behavior regarding the purchase of concrete product/service. Companies can create specific marketing plan for each of these segments and therefore gain short or long term competitive advantage on the market. Depending on the concrete marketing goal, different segmentation schemes and techniques may be applied. This paper presents a predictive market segmentation model based on the application of logistic regression model and CHAID analysis. The logistic regression model was used for the purpose of variables selection (from the initial pool of eleven variables which are statistically significant for explaining the dependent variable. Selected variables were afterwards included in the CHAID procedure that generated the predictive market segmentation model. The model results are presented on the concrete empirical example in the following form: summary model results, CHAID tree, Gain chart, Index chart, risk and classification tables.

  6. A mathematical model for optimization of an integrated network logistic design

    Directory of Open Access Journals (Sweden)

    Lida Tafaghodi

    2011-10-01

    Full Text Available In this study, the integrated forward/reverse logistics network is investigated, and a capacitated multi-stage, multi-product logistics network design is proposed by formulating a generalized logistics network problem into a mixed-integer nonlinear programming model (MINLP for minimizing the total cost of the closed-loop supply chain network. Moreover, the proposed model is solved by using optimization solver, which provides the decisions related to the facility location problem, optimum quantity of shipped product, and facility capacity. Numerical results show the power of the proposed MINLP model to avoid th sub-optimality caused by separate design of forward and reverse logistics networks and to handle various transportation modes and periodic demand.

  7. Accounting for Slipping and Other False Negatives in Logistic Models of Student Learning

    Science.gov (United States)

    MacLellan, Christopher J.; Liu, Ran; Koedinger, Kenneth R.

    2015-01-01

    Additive Factors Model (AFM) and Performance Factors Analysis (PFA) are two popular models of student learning that employ logistic regression to estimate parameters and predict performance. This is in contrast to Bayesian Knowledge Tracing (BKT) which uses a Hidden Markov Model formalism. While all three models tend to make similar predictions,…

  8. Using the Logistic Regression model in supporting decisions of establishing marketing strategies

    Directory of Open Access Journals (Sweden)

    Cristinel CONSTANTIN

    2015-12-01

    Full Text Available This paper is about an instrumental research regarding the using of Logistic Regression model for data analysis in marketing research. The decision makers inside different organisation need relevant information to support their decisions regarding the marketing strategies. The data provided by marketing research could be computed in various ways but the multivariate data analysis models can enhance the utility of the information. Among these models we can find the Logistic Regression model, which is used for dichotomous variables. Our research is based on explanation the utility of this model and interpretation of the resulted information in order to help practitioners and researchers to use it in their future investigations

  9. The total cost of logistics in supplier selection, under conditions of multiple sourcing, multiple criteria and capacity constraint

    Directory of Open Access Journals (Sweden)

    Elnaz Bani

    2016-06-01

    Full Text Available This paper presents a mathematical model to solve a multi-objective decision making supplier selection problem. The proposed problem considers three objective functions: the first objective function minimizes the cost of purchasing the products while the second objective function minimizes the due dates and finally the third objective function maximizes the customer satisfaction. The resulted problem is formulated as mixed integer programming and, therefore, we use invasive weed optimization technique to solve the resulted problem. The performance of the proposed model is compared with NSGA II based on different criteria such as mean ideal distance and quality matrix. The preliminary results indicate that the proposed model performs relatively well compared with alternative method.

  10. Analysis of RIA standard curve by log-logistic and cubic log-logit models

    International Nuclear Information System (INIS)

    Yamada, Hideo; Kuroda, Akira; Yatabe, Tami; Inaba, Taeko; Chiba, Kazuo

    1981-01-01

    In order to improve goodness-of-fit in RIA standard analysis, programs for computing log-logistic and cubic log-logit were written in BASIC using personal computer P-6060 (Olivetti). Iterative least square method of Taylor series was applied for non-linear estimation of logistic and log-logistic. Hear ''log-logistic'' represents Y = (a - d)/(1 + (log(X)/c)sup(b)) + d As weights either 1, 1/var(Y) or 1/σ 2 were used in logistic or log-logistic and either Y 2 (1 - Y) 2 , Y 2 (1 - Y) 2 /var(Y), or Y 2 (1 - Y) 2 /σ 2 were used in quadratic or cubic log-logit. The term var(Y) represents squares of pure error and σ 2 represents estimated variance calculated using a following equation log(σ 2 + 1) = log(A) + J log(y). As indicators for goodness-of-fit, MSL/S sub(e)sup(2), CMD% and WRV (see text) were used. Better regression was obtained in case of alpha-fetoprotein by log-logistic than by logistic. Cortisol standard curve was much better fitted with cubic log-logit than quadratic log-logit. Predicted precision of AFP standard curve was below 5% in log-logistic in stead of 8% in logistic analysis. Predicted precision obtained using cubic log-logit was about five times lower than that with quadratic log-logit. Importance of selecting good models in RIA data processing was stressed in conjunction with intrinsic precision of radioimmunoassay system indicated by predicted precision. (author)

  11. The Research on Influencing Factors of Medical Logistics Cost Based on ISM Model

    Directory of Open Access Journals (Sweden)

    Zhai Yunkai

    2017-01-01

    Full Text Available The reason why medical logistics cost remains high is a system problem, this paper analyzes the system through the ISM model. The result presents that medical logistics cost factors have four levels of relationship, primary factor is the national policies, secondary factors are the talent construction and pharmaceutical enterprise scale, Intermediate factors are medical information management system and inventory cost, the key factors are transportation cost and distribution center location. Finally, according to the four levels of relationship, this paper put forward specific suggestions to reduce logistics cost.

  12. An integrative fuzzy Kansei engineering and Kano model for logistics services

    Science.gov (United States)

    Hartono, M.; Chuan, T. K.; Prayogo, D. N.; Santoso, A.

    2017-11-01

    Nowadays, customer emotional needs (known as Kansei) in product and especially in services become a major concern. One of the emerging services is the logistics services. In obtaining a global competitive advantage, logistics services should understand and satisfy their customer affective impressions (Kansei). How to capture, model and analyze the customer emotions has been well structured by Kansei Engineering, equipped with Kano model to strengthen its methodology. However, its methodology lacks of the dynamics of customer perception. More specifically, there is a criticism of perceived scores on user preferences, in both perceived service quality and Kansei response, whether they represent an exact numerical value. Thus, this paper is proposed to discuss an approach of fuzzy Kansei in logistics service experiences. A case study in IT-based logistics services involving 100 subjects has been conducted. Its findings including the service gaps accompanied with prioritized improvement initiatives are discussed.

  13. A decision support model for identification and prioritization of key performance indicators in the logistics industry

    OpenAIRE

    Kucukaltan, Berk; Irani, Zahir; Aktas, Emel

    2016-01-01

    Performance measurement of logistics companies is based upon various performance indicators. Yet, in the logistics industry, there are several vaguenesses, such as deciding on key indicators and determining interrelationships between performance indicators. In order to resolve these vaguenesses, this paper first presents the stakeholder-informed Balanced Scorecard (BSC) model, by incorporating financial (e.g. cost) and non-financial (e.g. social media) performance indicators, with a comprehen...

  14. Modeling e-logistics for urban B2C in Europe

    OpenAIRE

    Galván, Dante; Robusté Antón, Francesc; Estrada Romeu, Miguel Ángel; Campos Cacheda, Jose Magin

    2005-01-01

    Major cities need to carry out good delivery operations that coexist with the rest of urban functions. The efficiency in city organisation depends directly on the proper management of logistic networks. In this context, Urban Logistics is born to improve the efficiency in public facilities dealing with the organisation of supply networks, especially in urban freight transport networks. This paper quantitatively models supply chains in the vehicle routing problem with time windows, especially ...

  15. SUPPLIES COSTS: AN EXPLORATORY STUDY WITH APPLICATION OF MEASUREMENT MODEL OF LOGISTICS COSTS

    OpenAIRE

    Ana Paula Ferreira Alves; José Vanderlei Silva Borba; Gilberto Tavares dos Santos; Artur Roberto Gibbon

    2013-01-01

    One of the main reasons for the difficulty in adopting an integrated method of calculation of logistics costs is still a lack of adequate information about costs. The management of the supply chain and identify its costs can provide information for their managers, with regard to decision making, generating competitive advantage. Some models of calculating logistics costs are proposed by Uelze (1974), Dias (1996), Goldratt (2002), Christopher (2007), Castiglioni (2009) and Borba & Gibbon (2009...

  16. An Application of a Multidimensional Extension of the Two-Parameter Logistic Latent Trait Model.

    Science.gov (United States)

    McKinley, Robert L.; Reckase, Mark D.

    A latent trait model is described that is appropriate for use with tests that measure more than one dimension, and its application to both real and simulated test data is demonstrated. Procedures for estimating the parameters of the model are presented. The research objectives are to determine whether the two-parameter logistic model more…

  17. Modelling of binary logistic regression for obesity among secondary students in a rural area of Kedah

    Science.gov (United States)

    Kamaruddin, Ainur Amira; Ali, Zalila; Noor, Norlida Mohd.; Baharum, Adam; Ahmad, Wan Muhamad Amir W.

    2014-07-01

    Logistic regression analysis examines the influence of various factors on a dichotomous outcome by estimating the probability of the event's occurrence. Logistic regression, also called a logit model, is a statistical procedure used to model dichotomous outcomes. In the logit model the log odds of the dichotomous outcome is modeled as a linear combination of the predictor variables. The log odds ratio in logistic regression provides a description of the probabilistic relationship of the variables and the outcome. In conducting logistic regression, selection procedures are used in selecting important predictor variables, diagnostics are used to check that assumptions are valid which include independence of errors, linearity in the logit for continuous variables, absence of multicollinearity, and lack of strongly influential outliers and a test statistic is calculated to determine the aptness of the model. This study used the binary logistic regression model to investigate overweight and obesity among rural secondary school students on the basis of their demographics profile, medical history, diet and lifestyle. The results indicate that overweight and obesity of students are influenced by obesity in family and the interaction between a student's ethnicity and routine meals intake. The odds of a student being overweight and obese are higher for a student having a family history of obesity and for a non-Malay student who frequently takes routine meals as compared to a Malay student.

  18. MODELS AND METHODS FOR LOGISTICS HUB LOCATION: A REVIEW TOWARDS TRANSPORTATION NETWORKS DESIGN

    Directory of Open Access Journals (Sweden)

    Carolina Luisa dos Santos Vieira

    Full Text Available ABSTRACT Logistics hubs affect the distribution patterns in transportation networks since they are flow-concentrating structures. Indeed, the efficient moving of goods throughout supply chains depends on the design of such networks. This paper presents a literature review on the logistics hub location problem, providing an outline of modeling approaches, solving techniques, and their applicability to such context. Two categories of models were identified. While multi-criteria models may seem best suited to find optimal locations, they do not allow an assessment of the impact of new hubs on goods flow and on the transportation network. On the other hand, single-criterion models, which provide location and flow allocation information, adopt network simplifications that hinder an accurate representation of the relationshipbetween origins, destinations, and hubs. In view of these limitations we propose future research directions for addressing real challenges of logistics hubs location regarding transportation networks design.

  19. Carbon emissions, logistics volume and GDP in China: empirical analysis based on panel data model.

    Science.gov (United States)

    Guo, Xiaopeng; Ren, Dongfang; Shi, Jiaxing

    2016-12-01

    This paper studies the relationship among carbon emissions, GDP, and logistics by using a panel data model and a combination of statistics and econometrics theory. The model is based on the historical data of 10 typical provinces and cities in China during 2005-2014. The model in this paper adds the variability of logistics on the basis of previous studies, and this variable is replaced by the freight turnover of the provinces. Carbon emissions are calculated by using the annual consumption of coal, oil, and natural gas. GDP is the gross domestic product. The results showed that the amount of logistics and GDP have a contribution to carbon emissions and the long-term relationships are different between different cities in China, mainly influenced by the difference among development mode, economic structure, and level of logistic development. After the testing of panel model setting, this paper established a variable coefficient model of the panel. The influence of GDP and logistics on carbon emissions is obtained according to the influence factors among the variables. The paper concludes with main findings and provides recommendations toward rational planning of urban sustainable development and environmental protection for China.

  20. Organizational Learning, Strategic Flexibility and Business Model Innovation: An Empirical Research Based on Logistics Enterprises

    Science.gov (United States)

    Bao, Yaodong; Cheng, Lin; Zhang, Jian

    Using the data of 237 Jiangsu logistics firms, this paper empirically studies the relationship among organizational learning capability, business model innovation, strategic flexibility. The results show as follows; organizational learning capability has positive impacts on business model innovation performance; strategic flexibility plays mediating roles on the relationship between organizational learning capability and business model innovation; interaction among strategic flexibility, explorative learning and exploitative learning play significant roles in radical business model innovation and incremental business model innovation.

  1. New methods to measure and model logistics and goods effects by the use of the CLG-DSS Model

    DEFF Research Database (Denmark)

    Salling, Kim Bang; Jensen, Anders Vestergaard

    2004-01-01

    This paper concerns the assessment and modelling of so-called logistics and goods effects (LG-effects) as part of a wider economic analysis by use of the developed CLG-DSS model. The results presented are based an on-going study, Task 9 about evaluation modelling and decision support systems (DSS......) in the Centre for Logistics and Goods Transport (CLG) 2001-2005 funded by the Danish Council for Technical-Scientific Research (STVF). Within the area of research on logistics the interaction between logistics and transportation is of great relevance. Task 9 and other recent studies have found that several...... companies are taking account of logistics and transport by setting up, among other things, specific departments to improve their handling. Some aspects in the transport sector concerning goods movement and consequences have not so far got the attention they deserve. In CLG Task 9 four LG-effects have been...

  2. SUPPLIES COSTS: AN EXPLORATORY STUDY WITH APPLICATION OF MEASUREMENT MODEL OF LOGISTICS COSTS

    Directory of Open Access Journals (Sweden)

    Ana Paula Ferreira Alves

    2013-12-01

    Full Text Available One of the main reasons for the difficulty in adopting an integrated method of calculation of logistics costs is still a lack of adequate information about costs. The management of the supply chain and identify its costs can provide information for their managers, with regard to decision making, generating competitive advantage. Some models of calculating logistics costs are proposed by Uelze (1974, Dias (1996, Goldratt (2002, Christopher (2007, Castiglioni (2009 and Borba & Gibbon (2009, with little disclosure of the results. In this context, this study aims to evaluate the costs of supplies, applying a measurement model of logistics costs. Methodologically, the study characterized as exploratory. The model applied pointed, in original condition, that about R$ 2.5 million were being applied in the process of management of supplies, with replacement costs and storage imbalance. Upgrading the company's data, it is possible obtain a 52% reduction in costs to replace and store supplies. Thus, the cost model applied to logistical supplies showed feasibility of implementation, as well as providing information to assist in management and decision-making in logistics supply.

  3. Modelo de Gerenciamento da Logística Reversa Reverse Logistics Management Model

    Directory of Open Access Journals (Sweden)

    Cecilia Toledo Hernández

    2012-01-01

    in the companies to investigate how this relationship is established. As the main result, which is directly related to the objectives of this study, a conceptual model that contributes to a better understanding of the reverse logistic process was developed. This model includes performance indicators suitable for evaluating the activity. Another objective of this study is the use of the multiple-criteria decision making approach, a tool that simplifies the selection of indicators according the company strategies.

  4. A Predictive Logistic Regression Model of World Conflict Using Open Source Data

    Science.gov (United States)

    2015-03-26

    No correlation between the error terms and the independent variables 9. Absence of perfect multicollinearity (Menard, 2001) When assumptions are...some of the variables before initial model building. Multicollinearity , or near-linear dependence among the variables will cause problems in the...model. High multicollinearity tends to produce unreasonably high logistic regression coefficients and can result in coefficients that are not

  5. Sample size calculation to externally validate scoring systems based on logistic regression models.

    Directory of Open Access Journals (Sweden)

    Antonio Palazón-Bru

    Full Text Available A sample size containing at least 100 events and 100 non-events has been suggested to validate a predictive model, regardless of the model being validated and that certain factors can influence calibration of the predictive model (discrimination, parameterization and incidence. Scoring systems based on binary logistic regression models are a specific type of predictive model.The aim of this study was to develop an algorithm to determine the sample size for validating a scoring system based on a binary logistic regression model and to apply it to a case study.The algorithm was based on bootstrap samples in which the area under the ROC curve, the observed event probabilities through smooth curves, and a measure to determine the lack of calibration (estimated calibration index were calculated. To illustrate its use for interested researchers, the algorithm was applied to a scoring system, based on a binary logistic regression model, to determine mortality in intensive care units.In the case study provided, the algorithm obtained a sample size with 69 events, which is lower than the value suggested in the literature.An algorithm is provided for finding the appropriate sample size to validate scoring systems based on binary logistic regression models. This could be applied to determine the sample size in other similar cases.

  6. Fitting multistate transition models with autoregressive logistic regression : Supervised exercise in intermittent claudication

    NARCIS (Netherlands)

    de Vries, S O; Fidler, Vaclav; Kuipers, Wietze D; Hunink, Maria G M

    1998-01-01

    The purpose of this study was to develop a model that predicts the outcome of supervised exercise for intermittent claudication. The authors present an example of the use of autoregressive logistic regression for modeling observed longitudinal data. Data were collected from 329 participants in a

  7. The use of logistic regression in modelling the distributions of bird ...

    African Journals Online (AJOL)

    The method of logistic regression was used to model the observed geographical distribution patterns of bird species in Swaziland in relation to a set of environmental variables. Reporting rates derived from bird atlas data are used as an index of population densities. This is justified in part by the success of the modelling ...

  8. An Investigation of Invariance Properties of One, Two and Three Parameter Logistic Item Response Theory Models

    Directory of Open Access Journals (Sweden)

    O.A. Awopeju

    2017-12-01

    Full Text Available The study investigated the invariance properties of one, two and three parame-ter logistic item response theory models. It examined the best fit among one parameter logistic (1PL, two-parameter logistic (2PL and three-parameter logistic (3PL IRT models for SSCE, 2008 in Mathematics. It also investigated the degree of invariance of the IRT models based item difficulty parameter estimates in SSCE in Mathematics across different samples of examinees and examined the degree of invariance of the IRT models based item discrimination estimates in SSCE in Mathematics across different samples of examinees. In order to achieve the set objectives, 6000 students (3000 males and 3000 females were drawn from the population of 35262 who wrote the 2008 paper 1 Senior Secondary Certificate Examination (SSCE in Mathematics organized by National Examination Council (NECO. The item difficulty and item discrimination parameter estimates from CTT and IRT were tested for invariance using BLOG MG 3 and correlation analysis was achieved using SPSS version 20. The research findings were that two parameter model IRT item difficulty and discrimination parameter estimates exhibited invariance property consistently across different samples and that 2-parameter model was suitable for all samples of examinees unlike one-parameter model and 3-parameter model.

  9. The Limit Behavior of a Stochastic Logistic Model with Individual Time-Dependent Rates

    Directory of Open Access Journals (Sweden)

    Yilun Shang

    2013-01-01

    Full Text Available We investigate a variant of the stochastic logistic model that allows individual variation and time-dependent infection and recovery rates. The model is described as a heterogeneous density dependent Markov chain. We show that the process can be approximated by a deterministic process defined by an integral equation as the population size grows.

  10. Logistics flows and enterprise input-output models: aggregate and disaggregate analysis

    NARCIS (Netherlands)

    Albino, V.; Yazan, Devrim; Messeni Petruzzelli, A.; Okogbaa, O.G.

    2011-01-01

    In the present paper, we propose the use of enterprise input-output (EIO) models to describe and analyse the logistics flows considering spatial issues and related environmental effects associated with production and transportation processes. In particular, transportation is modelled as a specific

  11. Using Multiple and Logistic Regression to Estimate the Median WillCost and Probability of Cost and Schedule Overrun for Program Managers

    Science.gov (United States)

    2017-03-23

    Logistic Regression to Estimate the Median Will-Cost and Probability of Cost and Schedule Overrun for Program Managers Ryan C. Trudelle, B.S...not the other. We are able to give logistic regression models to program managers that identify several program characteristics for either...considered acceptable. We recommend the use of our logistic models as a tool to manage a portfolio of programs in order to gain potential elusive

  12. Conditional Poisson models: a flexible alternative to conditional logistic case cross-over analysis.

    Science.gov (United States)

    Armstrong, Ben G; Gasparrini, Antonio; Tobias, Aurelio

    2014-11-24

    The time stratified case cross-over approach is a popular alternative to conventional time series regression for analysing associations between time series of environmental exposures (air pollution, weather) and counts of health outcomes. These are almost always analyzed using conditional logistic regression on data expanded to case-control (case crossover) format, but this has some limitations. In particular adjusting for overdispersion and auto-correlation in the counts is not possible. It has been established that a Poisson model for counts with stratum indicators gives identical estimates to those from conditional logistic regression and does not have these limitations, but it is little used, probably because of the overheads in estimating many stratum parameters. The conditional Poisson model avoids estimating stratum parameters by conditioning on the total event count in each stratum, thus simplifying the computing and increasing the number of strata for which fitting is feasible compared with the standard unconditional Poisson model. Unlike the conditional logistic model, the conditional Poisson model does not require expanding the data, and can adjust for overdispersion and auto-correlation. It is available in Stata, R, and other packages. By applying to some real data and using simulations, we demonstrate that conditional Poisson models were simpler to code and shorter to run than are conditional logistic analyses and can be fitted to larger data sets than possible with standard Poisson models. Allowing for overdispersion or autocorrelation was possible with the conditional Poisson model but when not required this model gave identical estimates to those from conditional logistic regression. Conditional Poisson regression models provide an alternative to case crossover analysis of stratified time series data with some advantages. The conditional Poisson model can also be used in other contexts in which primary control for confounding is by fine

  13. A fuzzy mathematical model of West Java population with logistic growth model

    Science.gov (United States)

    Nurkholipah, N. S.; Amarti, Z.; Anggriani, N.; Supriatna, A. K.

    2018-03-01

    In this paper we develop a mathematics model of population growth in the West Java Province Indonesia. The model takes the form as a logistic differential equation. We parameterize the model using several triples of data, and choose the best triple which has the smallest Mean Absolute Percentage Error (MAPE). The resulting model is able to predict the historical data with a high accuracy and it also able to predict the future of population number. Predicting the future population is among the important factors that affect the consideration is preparing a good management for the population. Several experiment are done to look at the effect of impreciseness in the data. This is done by considering a fuzzy initial value to the crisp model assuming that the model propagates the fuzziness of the independent variable to the dependent variable. We assume here a triangle fuzzy number representing the impreciseness in the data. We found that the fuzziness may disappear in the long-term. Other scenarios also investigated, such as the effect of fuzzy parameters to the crisp initial value of the population. The solution of the model is obtained numerically using the fourth-order Runge-Kutta scheme.

  14. Analysis of Interactions of Logistics Elements of K-1 Tracked Vehicles in Republic Of Korea Army by Using Simulation Model

    National Research Council Canada - National Science Library

    Park, Si-Won

    2007-01-01

    ...: component failure rate, repair rate, inventory service level, and logistics delays. The model with these logistics elements is simulated for the acquirement of data and the results provide guidance...

  15. Construction of risk prediction model of type 2 diabetes mellitus based on logistic regression

    Directory of Open Access Journals (Sweden)

    Li Jian

    2017-01-01

    Full Text Available Objective: to construct multi factor prediction model for the individual risk of T2DM, and to explore new ideas for early warning, prevention and personalized health services for T2DM. Methods: using logistic regression techniques to screen the risk factors for T2DM and construct the risk prediction model of T2DM. Results: Male’s risk prediction model logistic regression equation: logit(P=BMI × 0.735+ vegetables × (−0.671 + age × 0.838+ diastolic pressure × 0.296+ physical activity× (−2.287 + sleep ×(−0.009 +smoking ×0.214; Female’s risk prediction model logistic regression equation: logit(P=BMI ×1.979+ vegetables× (−0.292 + age × 1.355+ diastolic pressure× 0.522+ physical activity × (−2.287 + sleep × (−0.010.The area under the ROC curve of male was 0.83, the sensitivity was 0.72, the specificity was 0.86, the area under the ROC curve of female was 0.84, the sensitivity was 0.75, the specificity was 0.90. Conclusion: This study model data is from a compared study of nested case, the risk prediction model has been established by using the more mature logistic regression techniques, and the model is higher predictive sensitivity, specificity and stability.

  16. Persistence and extinction for stochastic logistic model with Levy noise and impulsive perturbation

    OpenAIRE

    Chun Lu; Qiang Ma; Xiaohua Ding

    2015-01-01

    This article investigates a stochastic logistic model with Levy noise and impulsive perturbation. In the model, the impulsive perturbation and Levy noise are taken into account simultaneously. This model is new and more feasible and more accordance with the actual. The definition of solution to a stochastic differential equation with Levy noise and impulsive perturbation is established. Based on this definition, we show that our model has a unique global positive solut...

  17. Applying Fuzzy Multiobjective Integrated Logistics Model to Green Supply Chain Problems

    Directory of Open Access Journals (Sweden)

    Chui-Yu Chiu

    2014-01-01

    Full Text Available The aim of this paper is attempting to explore the optimal way of supply chain management within the domain of environmental responsibility and concerns. The background of this research involves the issue of green supply chain management (GSCM and the concept of the multiobjective integrated logistics model. More specifically, in this paper, we suggest the fuzzy multiobjective integrated logistics model with the transportation cost and demand fuzziness to solve green supply chain problems in the uncertain environment which is illustrated via the detailed numerical example. Results and the sensitivity analysis of the numerical example indicate that when the governmental subsidy value increased the profits of the reverse chain also increased. The finding shows that the governmental subsidy policy could remain of significant influence for used-product reverse logistics chain.

  18. Logistics modelling: improving resource management and public information strategies in Florida.

    Science.gov (United States)

    Walsh, Daniel M; Van Groningen, Chuck; Craig, Brian

    2011-10-01

    One of the most time-sensitive and logistically-challenging emergency response operations today is to provide mass prophylaxis to every man, woman and child in a community within 48 hours of a bioterrorism attack. To meet this challenge, federal, state and local public health departments in the USA have joined forces to develop, test and execute large-scale bioterrorism response plans. This preparedness and response effort is funded through the US Centers for Disease Control and Prevention's Cities Readiness Initiative, a programme dedicated to providing oral antibiotics to an entire population within 48 hours of a weaponised inhalation anthrax attack. This paper will demonstrate how the State of Florida used a logistics modelling tool to improve its CRI mass prophylaxis plans. Special focus will be on how logistics modelling strengthened Florida's resource management policies and validated its public information strategies.

  19. Transport spatial model for the definition of green routes for city logistics centers

    International Nuclear Information System (INIS)

    Pamučar, Dragan; Gigović, Ljubomir; Ćirović, Goran; Regodić, Miodrag

    2016-01-01

    This paper presents a transport spatial decision support model (TSDSM) for carrying out the optimization of green routes for city logistics centers. The TSDSM model is based on the integration of the multi-criteria method of Weighted Linear Combination (WLC) and the modified Dijkstra algorithm within a geographic information system (GIS). The GIS is used for processing spatial data. The proposed model makes it possible to plan routes for green vehicles and maximize the positive effects on the environment, which can be seen in the reduction of harmful gas emissions and an increase in the air quality in highly populated areas. The scheduling of delivery vehicles is given as a problem of optimization in terms of the parameters of: the environment, health, use of space and logistics operating costs. Each of these input parameters was thoroughly examined and broken down in the GIS into criteria which further describe them. The model presented here takes into account the fact that logistics operators have a limited number of environmentally friendly (green) vehicles available. The TSDSM was tested on a network of roads with 127 links for the delivery of goods from the city logistics center to the user. The model supports any number of available environmentally friendly or environmentally unfriendly vehicles consistent with the size of the network and the transportation requirements. - Highlights: • Model for routing light delivery vehicles in urban areas. • Optimization of green routes for city logistics centers. • The proposed model maximizes the positive effects on the environment. • The model was tested on a real network.

  20. Transport spatial model for the definition of green routes for city logistics centers

    Energy Technology Data Exchange (ETDEWEB)

    Pamučar, Dragan, E-mail: dpamucar@gmail.com [University of Defence in Belgrade, Department of Logistics, Pavla Jurisica Sturma 33, 11000 Belgrade (Serbia); Gigović, Ljubomir, E-mail: gigoviclj@gmail.com [University of Defence in Belgrade, Department of Mathematics, Pavla Jurisica Sturma 33, 11000 Belgrade (Serbia); Ćirović, Goran, E-mail: cirovic@sezampro.rs [College of Civil Engineering and Geodesy, The Belgrade University, Hajduk Stankova 2, 11000 Belgrade (Serbia); Regodić, Miodrag, E-mail: mregodic62@gmail.com [University of Defence in Belgrade, Department of Mathematics, Pavla Jurisica Sturma 33, 11000 Belgrade (Serbia)

    2016-01-15

    This paper presents a transport spatial decision support model (TSDSM) for carrying out the optimization of green routes for city logistics centers. The TSDSM model is based on the integration of the multi-criteria method of Weighted Linear Combination (WLC) and the modified Dijkstra algorithm within a geographic information system (GIS). The GIS is used for processing spatial data. The proposed model makes it possible to plan routes for green vehicles and maximize the positive effects on the environment, which can be seen in the reduction of harmful gas emissions and an increase in the air quality in highly populated areas. The scheduling of delivery vehicles is given as a problem of optimization in terms of the parameters of: the environment, health, use of space and logistics operating costs. Each of these input parameters was thoroughly examined and broken down in the GIS into criteria which further describe them. The model presented here takes into account the fact that logistics operators have a limited number of environmentally friendly (green) vehicles available. The TSDSM was tested on a network of roads with 127 links for the delivery of goods from the city logistics center to the user. The model supports any number of available environmentally friendly or environmentally unfriendly vehicles consistent with the size of the network and the transportation requirements. - Highlights: • Model for routing light delivery vehicles in urban areas. • Optimization of green routes for city logistics centers. • The proposed model maximizes the positive effects on the environment. • The model was tested on a real network.

  1. Innovative Business Model for Realization of Sustainable Supply Chain at the Outsourcing Examination of Logistics Services

    Directory of Open Access Journals (Sweden)

    Péter Tamás

    2018-01-01

    Full Text Available The issue of sustainability is becoming more and more important because of the increase in the human population and the extraction of non-renewable natural resources. We can make decisive steps towards sustainability in the fields of logistics services by improvement of logistics processes and/or application of new environment-friendly technologies. These steps are very important for companies because they have a significant effect on competitiveness. Nowadays significant changes are taking place in applied methods and technologies in the fields of logistics services as part of the 4th Industrial Revolution. Most companies are not able to keep pace with these changes in addition to carrying out their main activities by using own resources; consequently, in many cases logistics services are outsourced in the interest of maintaining or increasing competitiveness. The currently applied outsourcing examination process contains numerous shortcomings. We have elaborated a new business model to eliminate these shortcomings, namely the basic concept for an outsourcing investigation system integrated in the electronic marketplace. The paper introduces the current process of logistics service outsourcing examination and the elaborated business model concept.

  2. Adjusting for Confounding in Early Postlaunch Settings: Going Beyond Logistic Regression Models.

    Science.gov (United States)

    Schmidt, Amand F; Klungel, Olaf H; Groenwold, Rolf H H

    2016-01-01

    Postlaunch data on medical treatments can be analyzed to explore adverse events or relative effectiveness in real-life settings. These analyses are often complicated by the number of potential confounders and the possibility of model misspecification. We conducted a simulation study to compare the performance of logistic regression, propensity score, disease risk score, and stabilized inverse probability weighting methods to adjust for confounding. Model misspecification was induced in the independent derivation dataset. We evaluated performance using relative bias confidence interval coverage of the true effect, among other metrics. At low events per coefficient (1.0 and 0.5), the logistic regression estimates had a large relative bias (greater than -100%). Bias of the disease risk score estimates was at most 13.48% and 18.83%. For the propensity score model, this was 8.74% and >100%, respectively. At events per coefficient of 1.0 and 0.5, inverse probability weighting frequently failed or reduced to a crude regression, resulting in biases of -8.49% and 24.55%. Coverage of logistic regression estimates became less than the nominal level at events per coefficient ≤5. For the disease risk score, inverse probability weighting, and propensity score, coverage became less than nominal at events per coefficient ≤2.5, ≤1.0, and ≤1.0, respectively. Bias of misspecified disease risk score models was 16.55%. In settings with low events/exposed subjects per coefficient, disease risk score methods can be useful alternatives to logistic regression models, especially when propensity score models cannot be used. Despite better performance of disease risk score methods than logistic regression and propensity score models in small events per coefficient settings, bias, and coverage still deviated from nominal.

  3. Predicting 30-day Hospital Readmission with Publicly Available Administrative Database. A Conditional Logistic Regression Modeling Approach.

    Science.gov (United States)

    Zhu, K; Lou, Z; Zhou, J; Ballester, N; Kong, N; Parikh, P

    2015-01-01

    This article is part of the Focus Theme of Methods of Information in Medicine on "Big Data and Analytics in Healthcare". Hospital readmissions raise healthcare costs and cause significant distress to providers and patients. It is, therefore, of great interest to healthcare organizations to predict what patients are at risk to be readmitted to their hospitals. However, current logistic regression based risk prediction models have limited prediction power when applied to hospital administrative data. Meanwhile, although decision trees and random forests have been applied, they tend to be too complex to understand among the hospital practitioners. Explore the use of conditional logistic regression to increase the prediction accuracy. We analyzed an HCUP statewide inpatient discharge record dataset, which includes patient demographics, clinical and care utilization data from California. We extracted records of heart failure Medicare beneficiaries who had inpatient experience during an 11-month period. We corrected the data imbalance issue with under-sampling. In our study, we first applied standard logistic regression and decision tree to obtain influential variables and derive practically meaning decision rules. We then stratified the original data set accordingly and applied logistic regression on each data stratum. We further explored the effect of interacting variables in the logistic regression modeling. We conducted cross validation to assess the overall prediction performance of conditional logistic regression (CLR) and compared it with standard classification models. The developed CLR models outperformed several standard classification models (e.g., straightforward logistic regression, stepwise logistic regression, random forest, support vector machine). For example, the best CLR model improved the classification accuracy by nearly 20% over the straightforward logistic regression model. Furthermore, the developed CLR models tend to achieve better sensitivity of

  4. Building interpretable predictive models for pediatric hospital readmission using Tree-Lasso logistic regression.

    Science.gov (United States)

    Jovanovic, Milos; Radovanovic, Sandro; Vukicevic, Milan; Van Poucke, Sven; Delibasic, Boris

    2016-09-01

    Quantification and early identification of unplanned readmission risk have the potential to improve the quality of care during hospitalization and after discharge. However, high dimensionality, sparsity, and class imbalance of electronic health data and the complexity of risk quantification, challenge the development of accurate predictive models. Predictive models require a certain level of interpretability in order to be applicable in real settings and create actionable insights. This paper aims to develop accurate and interpretable predictive models for readmission in a general pediatric patient population, by integrating a data-driven model (sparse logistic regression) and domain knowledge based on the international classification of diseases 9th-revision clinical modification (ICD-9-CM) hierarchy of diseases. Additionally, we propose a way to quantify the interpretability of a model and inspect the stability of alternative solutions. The analysis was conducted on >66,000 pediatric hospital discharge records from California, State Inpatient Databases, Healthcare Cost and Utilization Project between 2009 and 2011. We incorporated domain knowledge based on the ICD-9-CM hierarchy in a data driven, Tree-Lasso regularized logistic regression model, providing the framework for model interpretation. This approach was compared with traditional Lasso logistic regression resulting in models that are easier to interpret by fewer high-level diagnoses, with comparable prediction accuracy. The results revealed that the use of a Tree-Lasso model was as competitive in terms of accuracy (measured by area under the receiver operating characteristic curve-AUC) as the traditional Lasso logistic regression, but integration with the ICD-9-CM hierarchy of diseases provided more interpretable models in terms of high-level diagnoses. Additionally, interpretations of models are in accordance with existing medical understanding of pediatric readmission. Best performing models have

  5. Analysis Test of Understanding of Vectors with the Three-Parameter Logistic Model of Item Response Theory and Item Response Curves Technique

    Science.gov (United States)

    Rakkapao, Suttida; Prasitpong, Singha; Arayathanitkul, Kwan

    2016-01-01

    This study investigated the multiple-choice test of understanding of vectors (TUV), by applying item response theory (IRT). The difficulty, discriminatory, and guessing parameters of the TUV items were fit with the three-parameter logistic model of IRT, using the parscale program. The TUV ability is an ability parameter, here estimated assuming…

  6. Modeling Governance KB with CATPCA to Overcome Multicollinearity in the Logistic Regression

    Science.gov (United States)

    Khikmah, L.; Wijayanto, H.; Syafitri, U. D.

    2017-04-01

    The problem often encounters in logistic regression modeling are multicollinearity problems. Data that have multicollinearity between explanatory variables with the result in the estimation of parameters to be bias. Besides, the multicollinearity will result in error in the classification. In general, to overcome multicollinearity in regression used stepwise regression. They are also another method to overcome multicollinearity which involves all variable for prediction. That is Principal Component Analysis (PCA). However, classical PCA in only for numeric data. Its data are categorical, one method to solve the problems is Categorical Principal Component Analysis (CATPCA). Data were used in this research were a part of data Demographic and Population Survey Indonesia (IDHS) 2012. This research focuses on the characteristic of women of using the contraceptive methods. Classification results evaluated using Area Under Curve (AUC) values. The higher the AUC value, the better. Based on AUC values, the classification of the contraceptive method using stepwise method (58.66%) is better than the logistic regression model (57.39%) and CATPCA (57.39%). Evaluation of the results of logistic regression using sensitivity, shows the opposite where CATPCA method (99.79%) is better than logistic regression method (92.43%) and stepwise (92.05%). Therefore in this study focuses on major class classification (using a contraceptive method), then the selected model is CATPCA because it can raise the level of the major class model accuracy.

  7. Using ROC curves to compare neural networks and logistic regression for modeling individual noncatastrophic tree mortality

    Science.gov (United States)

    Susan L. King

    2003-01-01

    The performance of two classifiers, logistic regression and neural networks, are compared for modeling noncatastrophic individual tree mortality for 21 species of trees in West Virginia. The output of the classifier is usually a continuous number between 0 and 1. A threshold is selected between 0 and 1 and all of the trees below the threshold are classified as...

  8. Strategies for Testing Statistical and Practical Significance in Detecting DIF with Logistic Regression Models

    Science.gov (United States)

    Fidalgo, Angel M.; Alavi, Seyed Mohammad; Amirian, Seyed Mohammad Reza

    2014-01-01

    This study examines three controversial aspects in differential item functioning (DIF) detection by logistic regression (LR) models: first, the relative effectiveness of different analytical strategies for detecting DIF; second, the suitability of the Wald statistic for determining the statistical significance of the parameters of interest; and…

  9. Modelling the Cost Performance of a Given Logistics Network Operating Under Regular and Irregular Conditions

    NARCIS (Netherlands)

    Janic, M.

    2009-01-01

    This paper develops an analytical model for the assessment of the cost performance of a given logistics network operating under regular and irregular (disruptive) conditions. In addition, the paper aims to carry out a sensitivity analysis of this cost with respect to changes of the most influencing

  10. Semi-parametric estimation of random effects in a logistic regression model using conditional inference

    DEFF Research Database (Denmark)

    Petersen, Jørgen Holm

    2016-01-01

    This paper describes a new approach to the estimation in a logistic regression model with two crossed random effects where special interest is in estimating the variance of one of the effects while not making distributional assumptions about the other effect. A composite likelihood is studied...

  11. On the Relationships between Jeffreys Modal and Weighted Likelihood Estimation of Ability under Logistic IRT Models

    Science.gov (United States)

    Magis, David; Raiche, Gilles

    2012-01-01

    This paper focuses on two estimators of ability with logistic item response theory models: the Bayesian modal (BM) estimator and the weighted likelihood (WL) estimator. For the BM estimator, Jeffreys' prior distribution is considered, and the corresponding estimator is referred to as the Jeffreys modal (JM) estimator. It is established that under…

  12. Modeling CO2 emissions from fossil fuel combustion using the logistic equation

    International Nuclear Information System (INIS)

    Meng, Ming; Niu, Dongxiao

    2011-01-01

    CO 2 emissions from fossil fuel combustion have been known to contribute to the greenhouse effect. Research on emission trends and further forecasting their further values is important for adjusting energy policies, particularly those relative to low carbon. Except for a few countries, the main figures of CO 2 emission from fossil fuel combustion in other countries are S-shaped curves. The logistic function is selected to simulate the S-shaped curve, and to improve the goodness of fit, three algorithms were provided to estimate its parameters. Considering the different emission characteristics of different industries, the three algorithms estimated the parameters of CO 2 emission in each industry separately. The most suitable parameters for each industry are selected based on the criterion of Mean Absolute Percentage Error (MAPE). With the combined simulation values of the selected models, the estimate of total CO 2 emission from fossil fuel combustion is obtained. The empirical analysis of China shows that our method is better than the linear model in terms of goodness of fit and simulation risk. -- Highlights: → Figures of CO 2 emissions from fossil fuel combustion in most countries are S-shape curves. → Using the logistic function to model the S-shape curve. → Three algorithms are offered to estimate the parameters of the logistic function. → The empirical analysis from China shows that the logistic equation has satisfactory simulation results.

  13. An order insertion scheduling model of logistics service supply chain considering capacity and time factors.

    Science.gov (United States)

    Liu, Weihua; Yang, Yi; Wang, Shuqing; Liu, Yang

    2014-01-01

    Order insertion often occurs in the scheduling process of logistics service supply chain (LSSC), which disturbs normal time scheduling especially in the environment of mass customization logistics service. This study analyses order similarity coefficient and order insertion operation process and then establishes an order insertion scheduling model of LSSC with service capacity and time factors considered. This model aims to minimize the average unit volume operation cost of logistics service integrator and maximize the average satisfaction degree of functional logistics service providers. In order to verify the viability and effectiveness of our model, a specific example is numerically analyzed. Some interesting conclusions are obtained. First, along with the increase of completion time delay coefficient permitted by customers, the possible inserting order volume first increases and then trends to be stable. Second, supply chain performance reaches the best when the volume of inserting order is equal to the surplus volume of the normal operation capacity in mass service process. Third, the larger the normal operation capacity in mass service process is, the bigger the possible inserting order's volume will be. Moreover, compared to increasing the completion time delay coefficient, improving the normal operation capacity of mass service process is more useful.

  14. Integrated Modeling of Solutions in the System of Distributing Logistics of a Fruit and Vegetable Cooperative

    Directory of Open Access Journals (Sweden)

    Oleksandr Velychko

    2014-12-01

    Full Text Available A mechanism of preparing rationalistic solutions in the system of distributing logistics of a fruit and vegetable cooperative has been studied considering possible alternatives and existing limitations. Belonging of separate operations of the fruit and vegetable cooperative to technological, logistical or marketing business processes has been identified. Expediency of the integrated use of logistical concept DRP, decision tree method and linear programming in management of the cooperative has been grounded. The model for preparing decisions on organizing sales of vegetables and fruit which is focused on minimization of costs of cooperative services and maximization of profits for members of the cooperation has been developed. The necessity to consider integrated model of differentiation on levels of post gathering processing and logistical service has been revealed. Methodology of representation in the economical-mathematical model of probabilities in the tree of decisions concerning the expected amount of sales and margin for members of the cooperative using different channels has been processed. A formula which enables scientists to describe limitations in linear programming concerning critical duration of providing harvest of vegetables and fruit after gathering towards a customer has been suggested.

  15. The alarming problems of confounding equivalence using logistic regression models in the perspective of causal diagrams

    Directory of Open Access Journals (Sweden)

    Yuanyuan Yu

    2017-12-01

    Full Text Available Abstract Background Confounders can produce spurious associations between exposure and outcome in observational studies. For majority of epidemiologists, adjusting for confounders using logistic regression model is their habitual method, though it has some problems in accuracy and precision. It is, therefore, important to highlight the problems of logistic regression and search the alternative method. Methods Four causal diagram models were defined to summarize confounding equivalence. Both theoretical proofs and simulation studies were performed to verify whether conditioning on different confounding equivalence sets had the same bias-reducing potential and then to select the optimum adjusting strategy, in which logistic regression model and inverse probability weighting based marginal structural model (IPW-based-MSM were compared. The “do-calculus” was used to calculate the true causal effect of exposure on outcome, then the bias and standard error were used to evaluate the performances of different strategies. Results Adjusting for different sets of confounding equivalence, as judged by identical Markov boundaries, produced different bias-reducing potential in the logistic regression model. For the sets satisfied G-admissibility, adjusting for the set including all the confounders reduced the equivalent bias to the one containing the parent nodes of the outcome, while the bias after adjusting for the parent nodes of exposure was not equivalent to them. In addition, all causal effect estimations through logistic regression were biased, although the estimation after adjusting for the parent nodes of exposure was nearest to the true causal effect. However, conditioning on different confounding equivalence sets had the same bias-reducing potential under IPW-based-MSM. Compared with logistic regression, the IPW-based-MSM could obtain unbiased causal effect estimation when the adjusted confounders satisfied G-admissibility and the optimal

  16. The alarming problems of confounding equivalence using logistic regression models in the perspective of causal diagrams.

    Science.gov (United States)

    Yu, Yuanyuan; Li, Hongkai; Sun, Xiaoru; Su, Ping; Wang, Tingting; Liu, Yi; Yuan, Zhongshang; Liu, Yanxun; Xue, Fuzhong

    2017-12-28

    Confounders can produce spurious associations between exposure and outcome in observational studies. For majority of epidemiologists, adjusting for confounders using logistic regression model is their habitual method, though it has some problems in accuracy and precision. It is, therefore, important to highlight the problems of logistic regression and search the alternative method. Four causal diagram models were defined to summarize confounding equivalence. Both theoretical proofs and simulation studies were performed to verify whether conditioning on different confounding equivalence sets had the same bias-reducing potential and then to select the optimum adjusting strategy, in which logistic regression model and inverse probability weighting based marginal structural model (IPW-based-MSM) were compared. The "do-calculus" was used to calculate the true causal effect of exposure on outcome, then the bias and standard error were used to evaluate the performances of different strategies. Adjusting for different sets of confounding equivalence, as judged by identical Markov boundaries, produced different bias-reducing potential in the logistic regression model. For the sets satisfied G-admissibility, adjusting for the set including all the confounders reduced the equivalent bias to the one containing the parent nodes of the outcome, while the bias after adjusting for the parent nodes of exposure was not equivalent to them. In addition, all causal effect estimations through logistic regression were biased, although the estimation after adjusting for the parent nodes of exposure was nearest to the true causal effect. However, conditioning on different confounding equivalence sets had the same bias-reducing potential under IPW-based-MSM. Compared with logistic regression, the IPW-based-MSM could obtain unbiased causal effect estimation when the adjusted confounders satisfied G-admissibility and the optimal strategy was to adjust for the parent nodes of outcome, which

  17. Resource Symmetric Dispatch Model for Internet of Things on Advanced Logistics

    OpenAIRE

    Guofeng Qin; Lisheng Wang; Qiyan Li

    2016-01-01

    Business applications in advanced logistics service are highly concurrent. In this paper, we propose a resource symmetric dispatch model for the concurrent and cooperative tasks of the Internet of Things. In the model, the terminals receive and deliver commands, data, and information with mobile networks, wireless networks, and sensor networks. The data and information are classified and processed by the clustering servers in the cloud service platform. The cluster service, resource dispatch,...

  18. The Long Time Behavior of a Stochastic Logistic Model with Infinite Delay and Impulsive Perturbation

    OpenAIRE

    Lu, Chun; Wu, Kaining

    2016-01-01

    This paper considers a stochastic logistic model with infinite delay and impulsive perturbation. Firstly, with the space $C_{g}$ as phase space, the definition of solution to a stochastic functional differential equation with infinite delay and impulsive perturbation is established. According to this definition, we show that our model has an unique global positive solution. Then we establish the sufficient and necessary conditions for extinction and stochastic permanence of the...

  19. PATH ANALYSIS WITH LOGISTIC REGRESSION MODELS : EFFECT ANALYSIS OF FULLY RECURSIVE CAUSAL SYSTEMS OF CATEGORICAL VARIABLES

    OpenAIRE

    Nobuoki, Eshima; Minoru, Tabata; Geng, Zhi; Department of Medical Information Analysis, Faculty of Medicine, Oita Medical University; Department of Applied Mathematics, Faculty of Engineering, Kobe University; Department of Probability and Statistics, Peking University

    2001-01-01

    This paper discusses path analysis of categorical variables with logistic regression models. The total, direct and indirect effects in fully recursive causal systems are considered by using model parameters. These effects can be explained in terms of log odds ratios, uncertainty differences, and an inner product of explanatory variables and a response variable. A study on food choice of alligators as a numerical exampleis reanalysed to illustrate the present approach.

  20. Assessment of RFID investment in the military logistics systems through the Cost of Ownership Model (COO)

    OpenAIRE

    Ozdemir, Ahmet; Bayrak, Mustafa Ali

    2010-01-01

    MBA Professional Report Radio Frequency Identification (RFID) is an emerging technology that has been recently used in numerous business and public fields. Most military applications of RFID have focused on logistics systems. Since RFID investment requires high initial cost and its benefits are hard to see in the short term, it needs an appropriate investment decision model. The purpose of this research is to propose a Cost of Ownership (COO) model for RFID integration into the Military ...

  1. Regression modeling strategies with applications to linear models, logistic and ordinal regression, and survival analysis

    CERN Document Server

    Harrell , Jr , Frank E

    2015-01-01

    This highly anticipated second edition features new chapters and sections, 225 new references, and comprehensive R software. In keeping with the previous edition, this book is about the art and science of data analysis and predictive modeling, which entails choosing and using multiple tools. Instead of presenting isolated techniques, this text emphasizes problem solving strategies that address the many issues arising when developing multivariable models using real data and not standard textbook examples. It includes imputation methods for dealing with missing data effectively, methods for fitting nonlinear relationships and for making the estimation of transformations a formal part of the modeling process, methods for dealing with "too many variables to analyze and not enough observations," and powerful model validation techniques based on the bootstrap.  The reader will gain a keen understanding of predictive accuracy, and the harm of categorizing continuous predictors or outcomes.  This text realistically...

  2. Spatial Model for Determining the Optimum Placement of Logistics Centers in a Predefined Economic Area

    Directory of Open Access Journals (Sweden)

    Ramona Iulia Țarțavulea (Dieaconescu

    2016-08-01

    Full Text Available The process of globalization has stimulated the demand for logistics services at a level of speed and increased efficiency, which involves using of techniques, tools, technologies and modern models in supply chain management. The aim of this research paper is to present a model that can be used in order to achieve an optimized supply chain, associated with minimum transportation costs. The utilization of spatial modeling for determining the optimal locations for logistics centers in a predefined economic area is proposd in this paper. The principal methods used to design the model are mathematic optimization and linear programming. The output data of the model are the precise placement of one up to ten logistics centers, in terms of minimum operational costs for delivery from the optimum locations to consumer points. The results of the research indicate that by using the proposed model, an efficient supply chain that is consistent with optimization of transport can be designed, in order to streamline the delivery process and thus reduce operational costs

  3. Logistics models for the transportation of radioactive waste and spent fuel

    International Nuclear Information System (INIS)

    Joy, D.S.; Holcomb, B.D.

    1978-03-01

    Mathematical modeling of the logistics of waste shipment is an effective way to provide input to program planning and long-range waste management. Several logistics models have been developed for use in parametric studies, contingency planning, and management of transportation networks. These models allow the determination of shipping schedules, optimal routes, probable transportation modes, minimal costs, minimal personnel exposure, minimal transportation equipment, etc. Such information will permit OWI to specify waste-receiving rates at various repositories in order to balance work loads, evaluate surge capacity requirements, and estimate projected shipping cask fleets. The programs are tailored to utilize information on the types of wastes being received, location of repositories and waste-generating facilities, shipping distances, time required for a given shipment, availability of equipment, above-ground storage capabilities and locations, projected waste throughput rates, etc. Two basic models have been developed. The Low-Level Waste Model evaluates the optimal transportation policy for shipping waste directly from the source to a final destination without any intermediate stops. The Spent Fuel Logistics Model evaluates the optimal transportation policy for shipping unreprocessed spent fuel from nuclear power plants (1) indirectly, that is, to an Away-From-Reactor (AFR) storage facility, with subsequent transhipment to a repository, or (2) directly to a repository

  4. A fuzzy multi-objective optimization model for sustainable reverse logistics network design

    DEFF Research Database (Denmark)

    Govindan, Kannan; Paam, Parichehr; Abtahi, Amir Reza

    2016-01-01

    Decreasing the environmental impact, increasing the degree of social responsibility, and considering the economic motivations of organizations are three significant features in designing a reverse logistics network under sustainability respects. Developing a model, which can simultaneously consider...... a multi-echelon multi-period multi-objective model for a sustainable reverse logistics network. To reflect all aspects of sustainability, we try to minimize the present value of costs, as well as environmental impacts, and optimize the social responsibility as objective functions of the model. In order...... these environmental, social, and economic aspects and their indicators, is an important problem for both researchers and practitioners. In this paper, we try to address this comprehensive approach by using indicators for measurement of aforementioned aspects and by applying fuzzy mathematical programming to design...

  5. An inexact reverse logistics model for municipal solid waste management systems.

    Science.gov (United States)

    Zhang, Yi Mei; Huang, Guo He; He, Li

    2011-03-01

    This paper proposed an inexact reverse logistics model for municipal solid waste management systems (IRWM). Waste managers, suppliers, industries and distributors were involved in strategic planning and operational execution through reverse logistics management. All the parameters were assumed to be intervals to quantify the uncertainties in the optimization process and solutions in IRWM. To solve this model, a piecewise interval programming was developed to deal with Min-Min functions in both objectives and constraints. The application of the model was illustrated through a classical municipal solid waste management case. With different cost parameters for landfill and the WTE, two scenarios were analyzed. The IRWM could reflect the dynamic and uncertain characteristics of MSW management systems, and could facilitate the generation of desired management plans. The model could be further advanced through incorporating methods of stochastic or fuzzy parameters into its framework. Design of multi-waste, multi-echelon, multi-uncertainty reverse logistics model for waste management network would also be preferred. Copyright © 2010 Elsevier Ltd. All rights reserved.

  6. Persistence and extinction for stochastic logistic model with Levy noise and impulsive perturbation

    Directory of Open Access Journals (Sweden)

    Chun Lu

    2015-09-01

    Full Text Available This article investigates a stochastic logistic model with Levy noise and impulsive perturbation. In the model, the impulsive perturbation and Levy noise are taken into account simultaneously. This model is new and more feasible and more accordance with the actual. The definition of solution to a stochastic differential equation with Levy noise and impulsive perturbation is established. Based on this definition, we show that our model has a unique global positive solution and obtains its explicit expression. Sufficient conditions for extinction are established as well as nonpersistence in the mean, weak persistence and stochastic permanence. The threshold between weak persistence and extinction is obtained.

  7. One-dimensional map-based neuron model: A logistic modification

    International Nuclear Information System (INIS)

    Mesbah, Samineh; Moghtadaei, Motahareh; Hashemi Golpayegani, Mohammad Reza; Towhidkhah, Farzad

    2014-01-01

    A one-dimensional map is proposed for modeling some of the neuronal activities, including different spiking and bursting behaviors. The model is obtained by applying some modifications on the well-known Logistic map and is named the Modified and Confined Logistic (MCL) model. Map-based neuron models are known as phenomenological models and recently, they are widely applied in modeling tasks due to their computational efficacy. Most of discrete map-based models involve two variables representing the slow-fast prototype. There are also some one-dimensional maps, which can replicate some of the neuronal activities. However, the existence of four bifurcation parameters in the MCL model gives rise to reproduction of spiking behavior with control over the frequency of the spikes, and imitation of chaotic and regular bursting responses concurrently. It is also shown that the proposed model has the potential to reproduce more realistic bursting activity by adding a second variable. Moreover the MCL model is able to replicate considerable number of experimentally observed neuronal responses introduced in Izhikevich (2004) [23]. Some analytical and numerical analyses of the MCL model dynamics are presented to explain the emersion of complex dynamics from this one-dimensional map

  8. Logistic growth models of China pinks, cultivated on seven substrates, as a function of degree days

    Directory of Open Access Journals (Sweden)

    Marília Milani

    Full Text Available ABSTRACT: The objective of this study was to characterize the height (H and leaf number (LN of China pinks, grown in seven substrates, as a function of degree days, using the logistic growth model. H and LN were measured from 56 plants per substrate, for 392 plants in total. Plants that were grown on substrates formed of 50% soil with 50% rice husk ash (50% S + 50% RH and 80% rice husk ash with 20% worm castings (80% RH + 20% W had the longest vegetative growth period (74d, corresponding to 1317.9ºCd. The logistic growth model, adjusted for H, showed differences in the estimation of maximum expected height (α between the substrates, with values between 10.47cm for 50% S + 50% RH and 35.75cm for Mecplant(r. When α was estimated as LN, variation was also observed between the different substrates, from approximately 30 leaves on plants growing on 50% S + 50% RH to 34 leaves on the plants growing on the substrate formed of 80% RH + 20% W. Growth of China pinks can be characterized using H or LN in the logistic growth model as a function of degree days, being the provided plants adequately fertilized. The best substrates in terms of maximum height and leaf number were 80% soil + 20% worm castings and Mecplant(r. However, users must recalibrate the model with the estimated parameters before applying it to different growing conditions.

  9. Optimal Control of Production and Remanufacturing in a Reverse Logistics Model with Backlogging

    Directory of Open Access Journals (Sweden)

    I. Konstantaras

    2010-01-01

    Full Text Available Reverse logistics activities have received increasing attention within logistics and operations management during the last years, both from a theoretical and a practical point of view. The field of reverse logistics includes all logistics processes starting with the take-back of used products from customers up to the stage of making them reusable products or disposing them. In this paper, a single-product recovery system is studied. In such system, used products are collected from customers and are kept at the recoverable inventory warehouse in view to be recovered. The constant demand rate can be satisfied either by newly produced products or by recovered ones (serviceable inventory, which are regarded as perfectly as the new ones. Excess demand is completely backlogged. Following an exact analytical approach, the optimal set-up numbers and the optimal lot sizes for the production of new products and for the recovery of returned products are obtained. A numerical cost comparison of this model with the corresponding one without backordering is also performed.

  10. Resource Symmetric Dispatch Model for Internet of Things on Advanced Logistics

    Directory of Open Access Journals (Sweden)

    Guofeng Qin

    2016-04-01

    Full Text Available Business applications in advanced logistics service are highly concurrent. In this paper, we propose a resource symmetric dispatch model for the concurrent and cooperative tasks of the Internet of Things. In the model, the terminals receive and deliver commands, data, and information with mobile networks, wireless networks, and sensor networks. The data and information are classified and processed by the clustering servers in the cloud service platform. The cluster service, resource dispatch, and load balance are cooperative for management and monitoring of every application case during the logistics service lifecycle. In order to support the high performance of cloud service, resource symmetric dispatch algorithm among clustering servers and load balancing method among multi-cores in one server, including NIO (Non-blocking Input/Output and RMI (Remote Method Invocation are utilized to dispatch the cooperation of computation and service resources.

  11. Transportation system modeling and simulation in support of logistics and operations

    International Nuclear Information System (INIS)

    Yoshimura, R.H.; Kjeldgaard, E.A.; Turnquist, M.A.; List, G.F.

    1997-12-01

    Effective management of DOE's transportation operations requires better data than are currently available, a more integrated management structure for making transportation decisions, and decision support tools to provide needed analysis capabilities. This paper describes a vision of an advanced logistics management system for DOE, and the rationale for developing improved modeling and simulation capability as an integral part of that system. The authors illustrate useful types of models through four examples, addressing issues of transportation package allocation, fleet sizing, routing/scheduling, and emergency responder location. The overall vision for the advanced logistics management system, and the specific examples of potential capabilities, provide the basis for a conclusion that such a system would meet a critical DOE need in the area of radioactive material and waste transportation

  12. Transportation system modeling and simulation in support of logistics and operations

    International Nuclear Information System (INIS)

    Yoshimura, R.H.; Kjeldgaard, E.A.; Turnquist, M.A.; List, G.F.

    1998-01-01

    Effective management of DOE's transportation operations requires better data than are currently available, a more integrated management structure for making transportation decisions, and decision support tools to provide needed analysis capabilities. This paper describes a vision of an advanced logistics management system for DOE, and the rationale for developing improved modeling and simulation capability as an integral part of that system. We illustrate useful types of models through four examples, addressing issues of transportation package allocation, fleet sizing, routing/Scheduling, and emergency responder location. The overall vision for the advanced logistics management system, and the specific examples of potential capabilities, provide the basis for a conclusion that such a system would meet a critical DOE need in the area of radioactive material and waste transportation. (authors)

  13. Multilevel binomial logistic prediction model for malignant pulmonary nodules based on texture features of CT image

    International Nuclear Information System (INIS)

    Wang Huan; Guo Xiuhua; Jia Zhongwei; Li Hongkai; Liang Zhigang; Li Kuncheng; He Qian

    2010-01-01

    Purpose: To introduce multilevel binomial logistic prediction model-based computer-aided diagnostic (CAD) method of small solitary pulmonary nodules (SPNs) diagnosis by combining patient and image characteristics by textural features of CT image. Materials and methods: Describe fourteen gray level co-occurrence matrix textural features obtained from 2171 benign and malignant small solitary pulmonary nodules, which belongs to 185 patients. Multilevel binomial logistic model is applied to gain these initial insights. Results: Five texture features, including Inertia, Entropy, Correlation, Difference-mean, Sum-Entropy, and age of patients own aggregating character on patient-level, which are statistically different (P < 0.05) between benign and malignant small solitary pulmonary nodules. Conclusion: Some gray level co-occurrence matrix textural features are efficiently descriptive features of CT image of small solitary pulmonary nodules, which can profit diagnosis of earlier period lung cancer if combined patient-level characteristics to some extent.

  14. A novel robust chance constrained possibilistic programming model for disaster relief logistics under uncertainty

    Directory of Open Access Journals (Sweden)

    Maryam Rahafrooz

    2016-09-01

    Full Text Available In this paper, a novel multi-objective robust possibilistic programming model is proposed, which simultaneously considers maximizing the distributive justice in relief distribution, minimizing the risk of relief distribution, and minimizing the total logistics costs. To effectively cope with the uncertainties of the after-disaster environment, the uncertain parameters of the proposed model are considered in the form of fuzzy trapezoidal numbers. The proposed model not only considers relief commodities priority and demand points priority in relief distribution, but also considers the difference between the pre-disaster and post-disaster supply abilities of the suppliers. In order to solve the proposed model, the LP-metric and the improved augmented ε-constraint methods are used. Second, a set of test problems are designed to evaluate the effectiveness of the proposed robust model against its equivalent deterministic form, which reveales the capabilities of the robust model. Finally, to illustrate the performance of the proposed robust model, a seismic region of northwestern Iran (East Azerbaijan is selected as a case study to model its relief logistics in the face of future earthquakes. This investigation indicates the usefulness of the proposed model in the field of crisis.

  15. Persistence and extinction for a stochastic logistic model with infinite delay

    OpenAIRE

    Chun Lu; Xiaohua Ding

    2013-01-01

    This article, studies a stochastic logistic model with infinite delay. Using a phase space, we establish sufficient conditions for the extinction, nonpersistence in the mean, weak persistence, and stochastic permanence. A threshold between weak persistence and extinction is obtained. Our results state that different types of environmental noises have different effects on the persistence and extinction, and that the delay has no impact on the persistence and ext...

  16. Extinction and quasi-stationarity in the stochastic logistic SIS model

    CERN Document Server

    Nåsell, Ingemar

    2011-01-01

    This volume presents explicit approximations of the quasi-stationary distribution and of the expected time to extinction from the state one and from quasi-stationarity for the stochastic logistic SIS model. The approximations are derived separately in three different parameter regions, and then combined into a uniform approximation across all three regions. Subsequently, the results are used to derive thresholds as functions of the population size N.

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

    Czech Academy of Sciences Publication Activity Database

    Rijmen, F.; Vomlel, Jiří

    2008-01-01

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

  18. Detection of high GS risk group prostate tumors by diffusion tensor imaging and logistic regression modelling.

    Science.gov (United States)

    Ertas, Gokhan

    2018-07-01

    To assess the value of joint evaluation of diffusion tensor imaging (DTI) measures by using logistic regression modelling to detect high GS risk group prostate tumors. Fifty tumors imaged using DTI on a 3 T MRI device were analyzed. Regions of interests focusing on the center of tumor foci and noncancerous tissue on the maps of mean diffusivity (MD) and fractional anisotropy (FA) were used to extract the minimum, the maximum and the mean measures. Measure ratio was computed by dividing tumor measure by noncancerous tissue measure. Logistic regression models were fitted for all possible pair combinations of the measures using 5-fold cross validation. Systematic differences are present for all MD measures and also for all FA measures in distinguishing the high risk tumors [GS ≥ 7(4 + 3)] from the low risk tumors [GS ≤ 7(3 + 4)] (P Logistic regression modelling provides a favorable solution for the joint evaluations easily adoptable in clinical practice. Copyright © 2018 Elsevier Inc. All rights reserved.

  19. Challenges and models in supporting logistics system design for dedicated-biomass-based bioenergy industry.

    Science.gov (United States)

    Zhu, Xiaoyan; Li, Xueping; Yao, Qingzhu; Chen, Yuerong

    2011-01-01

    This paper analyzed the uniqueness and challenges in designing the logistics system for dedicated biomass-to-bioenergy industry, which differs from the other industries, due to the unique features of dedicated biomass (e.g., switchgrass) including its low bulk density, restrictions on harvesting season and frequency, content variation with time and circumambient conditions, weather effects, scattered distribution over a wide geographical area, and so on. To design it, this paper proposed a mixed integer linear programming model. It covered from planting and harvesting switchgrass to delivering to a biorefinery and included the residue handling, concentrating on integrating strategic decisions on the supply chain design and tactical decisions on the annual operation schedules. The present numerical examples verified the model and demonstrated its use in practice. This paper showed that the operations of the logistics system were significantly different for harvesting and non-harvesting seasons, and that under the well-designed biomass logistics system, the mass production with a steady and sufficient supply of biomass can increase the unit profit of bioenergy. The analytical model and practical methodology proposed in this paper will help realize the commercial production in biomass-to-bioenergy industry. Copyright © 2010 Elsevier Ltd. All rights reserved.

  20. Competition with Online and Offline Demands considering Logistics Costs Based on the Hotelling Model

    Directory of Open Access Journals (Sweden)

    Zhi-Hua Hu

    2014-01-01

    Full Text Available Through popular information technologies (e.g., call centers, web portal, ecommerce and social media, etc., traditional shops change their functions for servicing online demands while still providing offline sales and services, which expand the market and the service capacity. In the Hotelling model that formulates the demand effect by considering just offline demand, the shops in a line city will locate at the center as a the result of competition by games. The online demands are met by the delivery logistics services provided by the shops with additional cost; the consumers’ waiting time after their orders also affects their choices for shops. The main purpose is to study the effects of the following aspects on the shops’ location competition: two logistics costs (consumers’ travelling cost for offline demands and the shops’ delivery logistics cost for online demands, the consumers’ waiting cost for online orders, and the ratios of online demands to the whole demands. Therefore, this study primarily contributes to the literature on the formulation of these aspects by extending the Hotelling model. These features and effects are demonstrated by experiments using the extended Hotelling models.

  1. Modeling the dynamics of urban growth using multinomial logistic regression: a case study of Jiayu County, Hubei Province, China

    Science.gov (United States)

    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.

  2. Urban Growth Modelling with Artificial Neural Network and Logistic Regression. Case Study: Sanandaj City, Iran

    Directory of Open Access Journals (Sweden)

    SASSAN MOHAMMADY

    2013-01-01

    Full Text Available Cities have shown remarkable growth due to attraction, economic, social and facilities centralization in the past few decades. Population and urban expansion especially in developing countries, led to lack of resources, land use change from appropriate agricultural land to urban land use and marginalization. Under these circumstances, land use activity is a major issue and challenge for town and country planners. Different approaches have been attempted in urban expansion modelling. Artificial Neural network (ANN models are among knowledge-based models which have been used for urban growth modelling. ANNs are powerful tools that use a machine learning approach to quantify and model complex behaviour and patterns. In this research, ANN and logistic regression have been employed for interpreting urban growth modelling. Our case study is Sanandaj city and we used Landsat TM and ETM+ imageries acquired at 2000 and 2006. The dataset used includes distance to main roads, distance to the residence region, elevation, slope, and distance to green space. Percent Area Match (PAM obtained from modelling of these changes with ANN is equal to 90.47% and the accuracy achieved for urban growth modelling with Logistic Regression (LR is equal to 88.91%. Percent Correct Match (PCM and Figure of Merit for ANN method were 91.33% and 59.07% and then for LR were 90.84% and 57.07%, respectively.

  3. A simple approach to power and sample size calculations in logistic regression and Cox regression models.

    Science.gov (United States)

    Vaeth, Michael; Skovlund, Eva

    2004-06-15

    For a given regression problem it is possible to identify a suitably defined equivalent two-sample problem such that the power or sample size obtained for the two-sample problem also applies to the regression problem. For a standard linear regression model the equivalent two-sample problem is easily identified, but for generalized linear models and for Cox regression models the situation is more complicated. An approximately equivalent two-sample problem may, however, also be identified here. In particular, we show that for logistic regression and Cox regression models the equivalent two-sample problem is obtained by selecting two equally sized samples for which the parameters differ by a value equal to the slope times twice the standard deviation of the independent variable and further requiring that the overall expected number of events is unchanged. In a simulation study we examine the validity of this approach to power calculations in logistic regression and Cox regression models. Several different covariate distributions are considered for selected values of the overall response probability and a range of alternatives. For the Cox regression model we consider both constant and non-constant hazard rates. The results show that in general the approach is remarkably accurate even in relatively small samples. Some discrepancies are, however, found in small samples with few events and a highly skewed covariate distribution. Comparison with results based on alternative methods for logistic regression models with a single continuous covariate indicates that the proposed method is at least as good as its competitors. The method is easy to implement and therefore provides a simple way to extend the range of problems that can be covered by the usual formulas for power and sample size determination. Copyright 2004 John Wiley & Sons, Ltd.

  4. Model-based bootstrapping when correcting for measurement error with application to logistic regression.

    Science.gov (United States)

    Buonaccorsi, John P; Romeo, Giovanni; Thoresen, Magne

    2018-03-01

    When fitting regression models, measurement error in any of the predictors typically leads to biased coefficients and incorrect inferences. A plethora of methods have been proposed to correct for this. Obtaining standard errors and confidence intervals using the corrected estimators can be challenging and, in addition, there is concern about remaining bias in the corrected estimators. The bootstrap, which is one option to address these problems, has received limited attention in this context. It has usually been employed by simply resampling observations, which, while suitable in some situations, is not always formally justified. In addition, the simple bootstrap does not allow for estimating bias in non-linear models, including logistic regression. Model-based bootstrapping, which can potentially estimate bias in addition to being robust to the original sampling or whether the measurement error variance is constant or not, has received limited attention. However, it faces challenges that are not present in handling regression models with no measurement error. This article develops new methods for model-based bootstrapping when correcting for measurement error in logistic regression with replicate measures. The methodology is illustrated using two examples, and a series of simulations are carried out to assess and compare the simple and model-based bootstrap methods, as well as other standard methods. While not always perfect, the model-based approaches offer some distinct improvements over the other methods. © 2017, The International Biometric Society.

  5. Stakeholder engagement in quattro helix model for mobile phone reverse logistics in Indonesia: a conceptual framework

    Science.gov (United States)

    Maheswari, H.; Yudoko, G.; Adhiutama, A.

    2017-12-01

    The number of e-waste from mobile phone industry is still dominating until now. This is happened because there is no mutual commitment from all of parties i.e. businesses, government, and societies to reduce the use of mobile phone that has the shortest product life cycle. There are many researches study about firms’ motivation and government’s role, other discuss about actions of communities in supporting reverse logistics implementation. Unfortunately, research about engagement mechanism that involving all parties is still rare. Therefore, it is important to find the engagement model through this conceptual paper and it is expected useful to build the novel model. Through literature review, the results of this research are establishing the Quattro helix model as the appropriate structure to build the robust team by exploring stakeholder theories; mapping the engagement model either in form of collaboration or participation that consider stakeholders’ role and motivation and finding six types of engagement that consider their interest; and determining the novel model of engagement through Quattro helix model for implementing reverse logistics in handling e-waste by describing the linkage and the gaps among existing model.

  6. On the Inclusion of Short-distance Bystander Effects into a Logistic Tumor Control Probability Model.

    Science.gov (United States)

    Tempel, David G; Brodin, N Patrik; Tomé, Wolfgang A

    2018-01-01

    Currently, interactions between voxels are neglected in the tumor control probability (TCP) models used in biologically-driven intensity-modulated radiotherapy treatment planning. However, experimental data suggests that this may not always be justified when bystander effects are important. We propose a model inspired by the Ising model, a short-range interaction model, to investigate if and when it is important to include voxel to voxel interactions in biologically-driven treatment planning. This Ising-like model for TCP is derived by first showing that the logistic model of tumor control is mathematically equivalent to a non-interacting Ising model. Using this correspondence, the parameters of the logistic model are mapped to the parameters of an Ising-like model and bystander interactions are introduced as a short-range interaction as is the case for the Ising model. As an example, we apply the model to study the effect of bystander interactions in the case of radiation therapy for prostate cancer. The model shows that it is adequate to neglect bystander interactions for dose distributions that completely cover the treatment target and yield TCP estimates that lie in the shoulder of the dose response curve. However, for dose distributions that yield TCP estimates that lie on the steep part of the dose response curve or for inhomogeneous dose distributions having significant hot and/or cold regions, bystander effects may be important. Furthermore, the proposed model highlights a previously unexplored and potentially fruitful connection between the fields of statistical mechanics and tumor control probability/normal tissue complication probability modeling.

  7. Evaluating barriers for reverse logistics implementation under a multiple stakeholders' perspective analysis using grey decision making approach

    DEFF Research Database (Denmark)

    Bouzon, Marina; Govindan, Kannan; Rodriguez, Carlos Manuel Taboada

    2018-01-01

    In the past few decades, an interest in reverse logistics has attracted the attention of industries and also has become a subject of interest for researchers. However, while reverse logistics is becoming a mandatory element of the supply chain in developed countries particularly due to legislation...... issues, the subject is still in a state of infancy in emerging economies such as Brazil. In these connections, impediments to reverse logistics implementation must be considered and analyzed, as well as the many different perspectives from the key stakeholders for their development. The objective...... of this research is to evaluate the interrelationship among reverse logistics barriers from the perspectives of the most important stakeholders in the Brazilian context. For this purpose, a Multi-Criteria Decision Making tool named grey-based Decision Making Trial and Evaluation Laboratory (grey-DEMATEL) was used...

  8. Innovative and logistics development business model elaboration of the economy of Ukraine

    Directory of Open Access Journals (Sweden)

    Любов Олександрівна Кравченко

    2016-11-01

    Full Text Available The problematic position of export operations of the enterprises on foreign trade format are analyzed in the article. The variant of implementation of innovative and logistics elements in the enterprise management system is considered in order to increase the export potential of the enterprise. It is shown that combination of the innovative direction with the logistics is possible using enterprise management paradigm. Such approach would increase the competitiveness of the offered products on the international market. The conceptual model of innovative and investment development of the export potential of enterprises is proposed to determine the potential of the company to produce and promote competitive products on the external market and provide competitive services in the required quantity, the right quality in a timely manner with minimal costs.

  9. A review of logistic regression models used to predict post-fire tree mortality of western North American conifers

    Science.gov (United States)

    Travis Woolley; David C. Shaw; Lisa M. Ganio; Stephen. Fitzgerald

    2012-01-01

    Logistic regression models used to predict tree mortality are critical to post-fire management, planning prescribed bums and understanding disturbance ecology. We review literature concerning post-fire mortality prediction using logistic regression models for coniferous tree species in the western USA. We include synthesis and review of: methods to develop, evaluate...

  10. Comparison of nonstationary generalized logistic models based on Monte Carlo simulation

    Directory of Open Access Journals (Sweden)

    S. Kim

    2015-06-01

    Full Text Available Recently, the evidences of climate change have been observed in hydrologic data such as rainfall and flow data. The time-dependent characteristics of statistics in hydrologic data are widely defined as nonstationarity. Therefore, various nonstationary GEV and generalized Pareto models have been suggested for frequency analysis of nonstationary annual maximum and POT (peak-over-threshold data, respectively. However, the alternative models are required for nonstatinoary frequency analysis because of analyzing the complex characteristics of nonstationary data based on climate change. This study proposed the nonstationary generalized logistic model including time-dependent parameters. The parameters of proposed model are estimated using the method of maximum likelihood based on the Newton-Raphson method. In addition, the proposed model is compared by Monte Carlo simulation to investigate the characteristics of models and applicability.

  11. Redesigning fruit and vegetable distribution network in Tehran using a city logistics model

    Directory of Open Access Journals (Sweden)

    Farshad Saeedi

    2019-01-01

    Full Text Available Tehran, as one of the most populated capital cities worldwide, is categorized in the group of highly polluted cities in terms of the geographical location as well as increased number of industries, vehicles, domestic fuel consumption, intra-city trips, increased manufacturing units, and in general excessive increase in the consumption of fossil energies. City logistics models can be effectively helpful for solving the complicated problems of this city. In the present study, a queuing theory-based bi-objective mathematical model is presented, which aims to optimize the environmental and economic costs in city logistics operations. It also tries to reduce the response time in the network. The first objective is associated with all beneficiaries and the second one is applicable for perishable and necessary goods. The proposed model makes decisions on urban distribution centers location problem. Subsequently, as a case study, the fruit and vegetable distribution network of Tehran city is investigated and redesigned via the proposed modelling. The results of the implementation of the model through traditional and augmented ε-constraint methods indicate the efficiency of the proposed model in redesigning the given network.

  12. Persistence and extinction for a stochastic logistic model with infinite delay

    Directory of Open Access Journals (Sweden)

    Chun Lu

    2013-11-01

    Full Text Available This article, studies a stochastic logistic model with infinite delay. Using a phase space, we establish sufficient conditions for the extinction, nonpersistence in the mean, weak persistence, and stochastic permanence. A threshold between weak persistence and extinction is obtained. Our results state that different types of environmental noises have different effects on the persistence and extinction, and that the delay has no impact on the persistence and extinction for the stochastic model in the autonomous case. Numerical simulations illustrate the theoretical results.

  13. A logistic and cost model for the transport of radioactive waste to a repository

    International Nuclear Information System (INIS)

    Hutchinson, D.L.; Gray, I.L.S.; Manville, W.D.

    1997-01-01

    UK Nirex Ltd is planning a deep repository for intermediate level radioactive waste, and also some low level waste. Part of this work is to develop a transport system to bring the packaged waste to the repository from nuclear industry sites across the United Kingdom. To assess the logistics and costs of this transport system and to provide inputs to the repository specification and design, Nirex has commissioned the development of a flexible computer model which can be used on a desktop PC. The requirements for the LOGCOST model are explained, and the solutions adopted, and then examples shown of the graphical and tabular outputs that LOGCOST can provide. (Author)

  14. A multicriteria decision making model for assessment and selection of an ERP in a logistics context

    Science.gov (United States)

    Pereira, Teresa; Ferreira, Fernanda A.

    2017-07-01

    The aim of this work is to apply a methodology of decision support based on a multicriteria decision analyses (MCDA) model that allows the assessment and selection of an Enterprise Resource Planning (ERP) in a Portuguese logistics company by Group Decision Maker (GDM). A Decision Support system (DSS) that implements a MCDA - Multicriteria Methodology for the Assessment and Selection of Information Systems / Information Technologies (MMASSI / IT) is used based on its features and facility to change and adapt the model to a given scope. Using this DSS it was obtained the information system that best suited to the decisional context, being this result evaluated through a sensitivity and robustness analysis.

  15. Underwater Cylindrical Object Detection Using the Spectral Features of Active Sonar Signals with Logistic Regression Models

    Directory of Open Access Journals (Sweden)

    Yoojeong Seo

    2018-01-01

    Full Text Available The issue of detecting objects bottoming on the sea floor is significant in various fields including civilian and military areas. The objective of this study is to investigate the logistic regression model to discriminate the target from the clutter and to verify the possibility of applying the model trained by the simulated data generated by the mathematical model to the real experimental data because it is not easy to obtain sufficient data in the underwater field. In the first stage of this study, when the clutter signal energy is so strong that the detection of a target is difficult, the logistic regression model is employed to distinguish the strong clutter signal and the target signal. Previous studies have found that if the clutter energy is larger, false detection occurs even for the various existing detection schemes. For this reason, the discrete Fourier transform (DFT magnitude spectrum of acoustic signals received by active sonar is applied to train the model to distinguish whether the received signal contains a target signal or not. The goodness of fit of the model is verified in terms of receiver operation characteristic (ROC, area under ROC curve (AUC, and classification table. The detection performance of the proposed model is evaluated in terms of detection rate according to target to clutter ratio (TCR. Furthermore, the real experimental data are employed to test the proposed approach. When using the experimental data to test the model, the logistic regression model is trained by the simulated data that are generated based on the mathematical model for the backscattering of the cylindrical object. The mathematical model is developed according to the size of the cylinder used in the experiment. Since the information on the experimental environment including the sound speed, the sediment type and such is not available, once simulated data are generated under various conditions, valid simulated data are selected using 70% of the

  16. Application of Logistic Regression Tree Model in Determining Habitat Distribution of Astragalus verus

    Directory of Open Access Journals (Sweden)

    M. Saki

    2013-03-01

    Full Text Available The relationship between plant species and environmental factors has always been a central issue in plant ecology. With rising power of statistical techniques, geo-statistics and geographic information systems (GIS, the development of predictive habitat distribution models of organisms has rapidly increased in ecology. This study aimed to evaluate the ability of Logistic Regression Tree model to create potential habitat map of Astragalus verus. This species produces Tragacanth and has economic value. A stratified- random sampling was applied to 100 sites (50 presence- 50 absence of given species, and produced environmental and edaphic factors maps by using Kriging and Inverse Distance Weighting methods in the ArcGIS software for the whole study area. Relationships between species occurrence and environmental factors were determined by Logistic Regression Tree model and extended to the whole study area. The results indicated species occurrence has strong correlation with environmental factors such as mean daily temperature and clay, EC and organic carbon content of the soil. Species occurrence showed direct relationship with mean daily temperature and clay and organic carbon, and inverse relationship with EC. Model accuracy was evaluated both by Cohen’s kappa statistics (κ and by area under Receiver Operating Characteristics curve based on independent test data set. Their values (kappa=0.9, Auc of ROC=0.96 indicated the high power of LRT to create potential habitat map on local scales. This model, therefore, can be applied to recognize potential sites for rangeland reclamation projects.

  17. Multiple Indicator Stationary Time Series Models.

    Science.gov (United States)

    Sivo, Stephen A.

    2001-01-01

    Discusses the propriety and practical advantages of specifying multivariate time series models in the context of structural equation modeling for time series and longitudinal panel data. For time series data, the multiple indicator model specification improves on classical time series analysis. For panel data, the multiple indicator model…

  18. Going Mobile: An Empirical Model for Explaining Successful Information Logistics in Ward Rounds.

    Science.gov (United States)

    Esdar, Moritz; Liebe, Jan-David; Babitsch, Birgit; Hübner, Ursula

    2018-01-01

    Medical ward rounds are critical focal points of inpatient care that call for uniquely flexible solutions to provide clinical information at the bedside. While this fact is undoubted, adoption rates of mobile IT solutions remain rather low. Our goal was to investigate if and how mobile IT solutions influence successful information provision at the bedside, i.e. clinical information logistics, as well as to shed light at socio-organizational factors that facilitate adoption rates from a user-centered perspective. Survey data were collected from 373 medical and nursing directors of German, Austrian and Swiss hospitals and analyzed using variance-based Structural Equation Modelling (SEM). The adoption of mobile IT solutions explains large portions of clinical information logistics and is in itself associated with an organizational culture of innovation and end user participation. Results should encourage decision makers to understand mobility as a core constituent of information logistics and thus to promote close end-user participation as well as to work towards building a culture of innovation.

  19. A comparative study on entrepreneurial attitudes modeled with logistic regression and Bayes nets.

    Science.gov (United States)

    López Puga, Jorge; García García, Juan

    2012-11-01

    Entrepreneurship research is receiving increasing attention in our context, as entrepreneurs are key social agents involved in economic development. We compare the success of the dichotomic logistic regression model and the Bayes simple classifier to predict entrepreneurship, after manipulating the percentage of missing data and the level of categorization in predictors. A sample of undergraduate university students (N = 1230) completed five scales (motivation, attitude towards business creation, obstacles, deficiencies, and training needs) and we found that each of them predicted different aspects of the tendency to business creation. Additionally, our results show that the receiver operating characteristic (ROC) curve is affected by the rate of missing data in both techniques, but logistic regression seems to be more vulnerable when faced with missing data, whereas Bayes nets underperform slightly when categorization has been manipulated. Our study sheds light on the potential entrepreneur profile and we propose to use Bayesian networks as an additional alternative to overcome the weaknesses of logistic regression when missing data are present in applied research.

  20. Comprehensive Logistics

    CERN Document Server

    Gudehus, Timm

    2012-01-01

    Modern logistics comprises operative logistics, analytical logistics and management of logistic networks. Central task of operative logistics is the efficient supply of required goods at the right place within the right time. Tasks of analytical logistics are designing optimal networks and systems, developing strategies for planning, scheduling and operation, and organizing efficient order and performance processes. Logistic management plans, implements and operates logistic networks and schedules orders, stocks and resources. This reference-book offers a unique survey of modern logistics. It contains proven strategies, rules and tools for the solution of a multitude of logistic problems. The analytically derived algorithms and formulas can be used for the computer-based planning of logistic systems and for the dynamic scheduling of orders and resources in supply networks. They enable significant improvements of performance, quality and costs. Their application is demonstrated by several examples from industr...

  1. Modeling Multiple Causes of Carcinogenesis

    Energy Technology Data Exchange (ETDEWEB)

    Jones, T D

    1999-01-24

    An array of epidemiological results and databases on test animal indicate that risk of cancer and atherosclerosis can be up- or down-regulated by diet through a range of 200%. Other factors contribute incrementally and include the natural terrestrial environment and various human activities that jointly produce complex exposures to endotoxin-producing microorganisms, ionizing radiations, and chemicals. Ordinary personal habits and simple physical irritants have been demonstrated to affect the immune response and risk of disease. There tends to be poor statistical correlation of long-term risk with single agent exposures incurred throughout working careers. However, Agency recommendations for control of hazardous exposures to humans has been substance-specific instead of contextually realistic even though there is consistent evidence for common mechanisms of toxicological and carcinogenic action. That behavior seems to be best explained by molecular stresses from cellular oxygen metabolism and phagocytosis of antigenic invasion as well as breakdown of normal metabolic compounds associated with homeostatic- and injury-related renewal of cells. There is continually mounting evidence that marrow stroma, comprised largely of monocyte-macrophages and fibroblasts, is important to phagocytic and cytokinetic response, but the complex action of the immune process is difficult to infer from first-principle logic or biomarkers of toxic injury. The many diverse database studies all seem to implicate two important processes, i.e., the univalent reduction of molecular oxygen and breakdown of aginuine, an amino acid, by hydrolysis or digestion of protein which is attendant to normal antigen-antibody action. This behavior indicates that protection guidelines and risk coefficients should be context dependent to include reference considerations of the composite action of parameters that mediate oxygen metabolism. A logic of this type permits the realistic common-scale modeling of

  2. Modeling data for pancreatitis in presence of a duodenal diverticula using logistic regression

    Science.gov (United States)

    Dineva, S.; Prodanova, K.; Mlachkova, D.

    2013-12-01

    The presence of a periampullary duodenal diverticulum (PDD) is often observed during upper digestive tract barium meal studies and endoscopic retrograde cholangiopancreatography (ERCP). A few papers reported that the diverticulum had something to do with the incidence of pancreatitis. The aim of this study is to investigate if the presence of duodenal diverticula predisposes to the development of a pancreatic disease. A total 3966 patients who had undergone ERCP were studied retrospectively. They were divided into 2 groups-with and without PDD. Patients with a duodenal diverticula had a higher rate of acute pancreatitis. The duodenal diverticula is a risk factor for acute idiopathic pancreatitis. A multiple logistic regression to obtain adjusted estimate of odds and to identify if a PDD is a predictor of acute or chronic pancreatitis was performed. The software package STATISTICA 10.0 was used for analyzing the real data.

  3. Influence of Coloured Correlated Noises on Probability Distribution and Mean of Tumour Cell Number in the Logistic Growth Model

    Institute of Scientific and Technical Information of China (English)

    HAN Li-Bo; GONG Xiao-Long; CAO Li; WU Da-Jin

    2007-01-01

    An approximate Fokker-P1anck equation for the logistic growth model which is driven by coloured correlated noises is derived by applying the Novikov theorem and the Fox approximation. The steady-state probability distribution (SPD) and the mean of the tumour cell number are analysed. It is found that the SPD is the single extremum configuration when the degree of correlation between the multiplicative and additive noises, λ, is in -1<λ ≤ 0 and can be the double extrema in 0<λ<1. A configuration transition occurs because of the variation of noise parameters. A minimum appears in the curve of the mean of the steady-state tumour cell number, 〈x〉, versus λ. The position and the value of the minimum are controlled by the noise-correlated times.

  4. Efficient Design of Distribution Logistics by Using a Model-Based Decision Support System

    OpenAIRE

    J. Becker; R. Arnold

    2016-01-01

    The design of distribution logistics has a decisive impact on a company's logistics costs and performance. Hence, such solutions make an essential contribution to corporate success. This article describes a decision support system for analyzing the potential of distribution logistics in terms of logistics costs and performance. In contrast to previous procedures of business process re-engineering (BPR), this method maps distribution logistics holistically under variable distribution structure...

  5. A tactical supply chain planning model with multiple flexibility options

    DEFF Research Database (Denmark)

    Esmaeilikia, Masoud; Fahimnia, Behnam; Sarkis, Joeseph

    2016-01-01

    Supply chain flexibility is widely recognized as an approach to manage uncertainty. Uncertainty in the supply chain may arise from a number of sources such as demand and supply interruptions and lead time variability. A tactical supply chain planning model with multiple flexibility options...... incorporated in sourcing, manufacturing and logistics functions can be used for the analysis of flexibility adjustment in an existing supply chain. This paper develops such a tactical supply chain planning model incorporating a realistic range of flexibility options. A novel solution method is designed...

  6. Evaluating penalized logistic regression models to predict Heat-Related Electric grid stress days

    Energy Technology Data Exchange (ETDEWEB)

    Bramer, L. M.; Rounds, J.; Burleyson, C. D.; Fortin, D.; Hathaway, J.; Rice, J.; Kraucunas, I.

    2017-11-01

    Understanding the conditions associated with stress on the electricity grid is important in the development of contingency plans for maintaining reliability during periods when the grid is stressed. In this paper, heat-related grid stress and the relationship with weather conditions is examined using data from the eastern United States. Penalized logistic regression models were developed and applied to predict stress on the electric grid using weather data. The inclusion of other weather variables, such as precipitation, in addition to temperature improved model performance. Several candidate models and datasets were examined. A penalized logistic regression model fit at the operation-zone level was found to provide predictive value and interpretability. Additionally, the importance of different weather variables observed at different time scales were examined. Maximum temperature and precipitation were identified as important across all zones while the importance of other weather variables was zone specific. The methods presented in this work are extensible to other regions and can be used to aid in planning and development of the electrical grid.

  7. A Case Study Using Modeling and Simulation to Predict Logistics Supply Chain Issues

    Science.gov (United States)

    Tucker, David A.

    2007-01-01

    Optimization of critical supply chains to deliver thousands of parts, materials, sub-assemblies, and vehicle structures as needed is vital to the success of the Constellation Program. Thorough analysis needs to be performed on the integrated supply chain processes to plan, source, make, deliver, and return critical items efficiently. Process modeling provides simulation technology-based, predictive solutions for supply chain problems which enable decision makers to reduce costs, accelerate cycle time and improve business performance. For example, United Space Alliance, LLC utilized this approach in late 2006 to build simulation models that recreated shuttle orbiter thruster failures and predicted the potential impact of thruster removals on logistics spare assets. The main objective was the early identification of possible problems in providing thruster spares for the remainder of the Shuttle Flight Manifest. After extensive analysis the model results were used to quantify potential problems and led to improvement actions in the supply chain. Similarly the proper modeling and analysis of Constellation parts, materials, operations, and information flows will help ensure the efficiency of the critical logistics supply chains and the overall success of the program.

  8. Modeling Energy Efficiency As A Green Logistics Component In Vehicle Assembly Line

    Science.gov (United States)

    Oumer, Abduaziz; Mekbib Atnaw, Samson; Kie Cheng, Jack; Singh, Lakveer

    2016-11-01

    This paper uses System Dynamics (SD) simulation to investigate the concept green logistics in terms of energy efficiency in automotive industry. The car manufacturing industry is considered to be one of the highest energy consuming industries. An efficient decision making model is proposed that capture the impacts of strategic decisions on energy consumption and environmental sustainability. The sources of energy considered in this research are electricity and fuel; which are the two main types of energy sources used in a typical vehicle assembly plant. The model depicts the performance measurement for process- specific energy measures of painting, welding, and assembling processes. SD is the chosen simulation method and the main green logistics issues considered are Carbon Dioxide (CO2) emission and energy utilization. The model will assist decision makers acquire an in-depth understanding of relationship between high level planning and low level operation activities on production, environmental impacts and costs associated. The results of the SD model signify the existence of positive trade-offs between green practices of energy efficiency and the reduction of CO2 emission.

  9. Development and validation of logistic prognostic models by predefined SAS-macros

    Directory of Open Access Journals (Sweden)

    Ziegler, Christoph

    2006-02-01

    Full Text Available In medical decision making about therapies or diagnostic procedures in the treatment of patients the prognoses of the course or of the magnitude of diseases plays a relevant role. Beside of the subjective attitude of the clinician mathematical models can help in providing such prognoses. Such models are mostly multivariate regression models. In the case of a dichotomous outcome the logistic model will be applied as the standard model. In this paper we will describe SAS-macros for the development of such a model, for examination of the prognostic performance, and for model validation. The rational for this developmental approach of a prognostic modelling and the description of the macros can only given briefly in this paper. Much more details are given in. These 14 SAS-macros are a tool for setting up the whole process of deriving a prognostic model. Especially the possibility of validating the model by a standardized software tool gives an opportunity, which is not used in general in published prognostic models. Therefore, this can help to develop new models with good prognostic performance for use in medical applications.

  10. An Integrated Multiechelon Logistics Model with Uncertain Delivery Lead Time and Quality Unreliability

    Directory of Open Access Journals (Sweden)

    Ming-Feng Yang

    2016-01-01

    Full Text Available Nowadays, in order to achieve advantages in supply chain management, how to keep inventory in adequate level and how to enhance customer service level are two critical practices for decision makers. Generally, uncertain lead time and defective products have much to do with inventory and service level. Therefore, this study mainly aims at developing a multiechelon integrated just-in-time inventory model with uncertain lead time and imperfect quality to enhance the benefits of the logistics model. In addition, the Ant Colony Algorithm (ACA is established to determine the optimal solutions. Moreover, based on our proposed model and analysis, the ACA is more efficient than Particle Swarm Optimization (PSO and Lingo in SMEIJI model. An example is provided in this study to illustrate how production run and defective rate have an effect on system costs. Finally, the results of our research could provide some managerial insights which support decision makers in real-world operations.

  11. Research on vehicles and cargos matching model based on virtual logistics platform

    Science.gov (United States)

    Zhuang, Yufeng; Lu, Jiang; Su, Zhiyuan

    2018-04-01

    Highway less than truckload (LTL) transportation vehicles and cargos matching problem is a joint optimization problem of typical vehicle routing and loading, which is also a hot issue of operational research. This article based on the demand of virtual logistics platform, for the problem of the highway LTL transportation, the matching model of the idle vehicle and the transportation order is set up and the corresponding genetic algorithm is designed. Then the algorithm is implemented by Java. The simulation results show that the solution is satisfactory.

  12. VIRTUAL MODEL OF A ROLLER CONVEYOR INTEGRATED INTO A LOGISTIC FLOW

    Directory of Open Access Journals (Sweden)

    POPESCU Adrian

    2015-11-01

    Full Text Available In this article is presented, with the help of graphics, a logistic flow for palletizing and wrapping operations. The loaded pallets are transported by means of a roller conveyor. Creating the virtual model for the conveyer allows us to emphasize the compatibility elements between on the one hand the mechanical assemblies of the flow components and on the other hand the subassemblies of the conveyer structure. The paper has focused on the presentation of the conveyor specific assembly and how are placed the sensors on the mechanical structure of the conveyor. Finally, the main working phases are graphically presented within the flow, highlighting the loaded pallet positions in the flow.

  13. Warehouse Logistics

    OpenAIRE

    Panibratetc, Anastasiia

    2015-01-01

    This research is a review of warehouse logistics on the example of Kannustalo Oy, located in Kannus, Western region of Finland. Kannustalo is an international company of designing, manufacturing and assembling block and turn-key houses. The research subject is logistics process in warehouse system of industrial company. In my work I discussed about theoretical aspect of logistics, logistic functions and processes. Later I considered warehouse as a part of logistics system and provided inf...

  14. Nonlinear dynamics in a business-cycle model with logistic population growth

    International Nuclear Information System (INIS)

    Brianzoni, Serena; Mammana, Cristiana; Michetti, Elisabetta

    2009-01-01

    We consider a discrete-time growth model of the Solow type where workers and shareholders have different but constant saving rates and the population growth dynamics is described by the logistic equation able to exhibit complicated dynamics. We show conditions for the resulting system having a compact global attractor and we describe its structure. We also perform a mainly numerical analysis using the critical lines method able to describe the strange attractor and the absorbing area, in order to show how cyclical or complex fluctuations may be produced in a business-cycle model. We study the dynamic behaviour of the model under different ranges of the main parameters, i.e. the elasticity of substitution between the two production factors and the one in the logistic equation (namely μ). We prove the existence of complex dynamics when the elasticity of substitution between production factors drops below one (so that capital income declines) or μ increases (so that the amplitude of movements in the population growth rate increases).

  15. Effective factors contraceptive use by logistic regression model in Tehran, 1996

    Directory of Open Access Journals (Sweden)

    Ramezani F

    1999-07-01

    Full Text Available Despite unwillingness to fertility, about 30% of couples do not use any kind of contraception and this will lead to unwanted pregnancy. In this clinical trial study, 4177 subjects who had at least one alive child, and delivered in one of the 12 university hospitals in Tehran were recruited. This study was conducted in 1996. The questionnaire included some questions about contraceptive use, their attitudes about unwantedness or wantedness of their current pregnancies. Data were analysed using a Logistic Regrassion Model. Results showed that 20.3% of those who had no fertility intention, did not use any kind of contraception methods, 41.1% of the subjects who were using a contraception method before pregnancy, had got pregnant unwantedly. Based on Logistic Regression Model; age, education, previous familiarity of women with contraception methods and husband's education were the most significant factors in contraceptive use. Subjects who were 20 years old and less or 35 years old and more and illeterate subjects were at higher risk for unuse of contraception methods. This risk was not related to the gender of their children that suggests a positive change in their perspectives towards sex and the number of children. It is suggested that health politicians choose an appropriate model to enhance the literacy, education and counseling for the correct usage of contraceptives and prevention of unwanted pregnancy.

  16. A production inventory model with exponential demand rate and reverse logistics

    Directory of Open Access Journals (Sweden)

    Ritu Raj

    2014-08-01

    Full Text Available The objective of this paper is to develop an integrated production inventory model for reworkable items with exponential demand rate. This is a three-layer supply chain model with perspectives of supplier, producer and retailer. Supplier delivers raw material to the producer and finished goods to the retailer. We consider perfect and imperfect quality products, product reliability and reworking of imperfect items. After screening, defective items reworked at a cost just after the regular manufacturing schedule. At the beginning, the manufacturing system starts produce perfect items, after some time the manufacturing system can undergo into “out-of-control” situation from “in-control” situation, which is controlled by reverse logistic technique. This paper deliberates the effects of business strategies like optimum order size of raw material, exponential demand rate, production rate is demand dependent, idle times and reverse logistics for an integrated marketing system. Mathematica is used to develop the optimal solution of production rate and raw material order for maximum expected average profit. A numerical example and sensitivity analysis is illustrated to validate the model.

  17. A transport logistic and cost model for use in repository design specification

    International Nuclear Information System (INIS)

    Gray, L.S.; Manville, W.D.

    1998-01-01

    UK Nirex Ltd (Nirex) is responsible for developing a deep repository for the disposal of the United Kingdom's intermediate level waste and some low level waste. It also needs to be able to predict the total cost of the transport operations, and to compute the costs attributable to different combinations of sites and types of waste packages. This paper draws on work carried out as part of the assessment of Sellafield as a potential repository site, but will also show that many aspects of the transport system are independent of the actual repository location. To analyze the effects of all these possible scenarios and proposed operating practices on the costs and logistics of radioactive waste transport, Nirex commissioned the development of a flexible computer model from a software developer with the appropriate expertise. This paper describes how the LOGCOST model has been used to provide the information required for the repository design specification, and how it can readily be adapted to different potential repository locations and to changing requirements. In conclusion, it can be said that LOGCOST is a very effective transport and logistics model based on the Excel spread-sheet. The examples given have shown how LOGCOST can provide detailed predictions of radioactive waste transport costs, and how LOGCOST can be readily adapted to a new repository site or any other focal point for a transport network. (O.M.)

  18. A Comparison of the One-and Three-Parameter Logistic Models on Measures of Test Efficiency.

    Science.gov (United States)

    Benson, Jeri

    Two methods of item selection were used to select sets of 40 items from a 50-item verbal analogies test, and the resulting item sets were compared for relative efficiency. The BICAL program was used to select the 40 items having the best mean square fit to the one parameter logistic (Rasch) model. The LOGIST program was used to select the 40 items…

  19. Logistic regression model for diagnosis of transition zone prostate cancer on multi-parametric MRI.

    Science.gov (United States)

    Dikaios, Nikolaos; Alkalbani, Jokha; Sidhu, Harbir Singh; Fujiwara, Taiki; Abd-Alazeez, Mohamed; Kirkham, Alex; Allen, Clare; Ahmed, Hashim; Emberton, Mark; Freeman, Alex; Halligan, Steve; Taylor, Stuart; Atkinson, David; Punwani, Shonit

    2015-02-01

    We aimed to develop logistic regression (LR) models for classifying prostate cancer within the transition zone on multi-parametric magnetic resonance imaging (mp-MRI). One hundred and fifty-five patients (training cohort, 70 patients; temporal validation cohort, 85 patients) underwent mp-MRI and transperineal-template-prostate-mapping (TPM) biopsy. Positive cores were classified by cancer definitions: (1) any-cancer; (2) definition-1 [≥Gleason 4 + 3 or ≥ 6 mm cancer core length (CCL)] [high risk significant]; and (3) definition-2 (≥Gleason 3 + 4 or ≥ 4 mm CCL) cancer [intermediate-high risk significant]. For each, logistic-regression mp-MRI models were derived from the training cohort and validated internally and with the temporal cohort. Sensitivity/specificity and the area under the receiver operating characteristic (ROC-AUC) curve were calculated. LR model performance was compared to radiologists' performance. Twenty-eight of 70 patients from the training cohort, and 25/85 patients from the temporal validation cohort had significant cancer on TPM. The ROC-AUC of the LR model for classification of cancer was 0.73/0.67 at internal/temporal validation. The radiologist A/B ROC-AUC was 0.65/0.74 (temporal cohort). For patients scored by radiologists as Prostate Imaging Reporting and Data System (Pi-RADS) score 3, sensitivity/specificity of radiologist A 'best guess' and LR model was 0.14/0.54 and 0.71/0.61, respectively; and radiologist B 'best guess' and LR model was 0.40/0.34 and 0.50/0.76, respectively. LR models can improve classification of Pi-RADS score 3 lesions similar to experienced radiologists. • MRI helps find prostate cancer in the anterior of the gland • Logistic regression models based on mp-MRI can classify prostate cancer • Computers can help confirm cancer in areas doctors are uncertain about.

  20. Logistic regression model for diagnosis of transition zone prostate cancer on multi-parametric MRI

    Energy Technology Data Exchange (ETDEWEB)

    Dikaios, Nikolaos; Halligan, Steve; Taylor, Stuart; Atkinson, David; Punwani, Shonit [University College London, Centre for Medical Imaging, London (United Kingdom); University College London Hospital, Departments of Radiology, London (United Kingdom); Alkalbani, Jokha; Sidhu, Harbir Singh; Fujiwara, Taiki [University College London, Centre for Medical Imaging, London (United Kingdom); Abd-Alazeez, Mohamed; Ahmed, Hashim; Emberton, Mark [University College London, Research Department of Urology, London (United Kingdom); Kirkham, Alex; Allen, Clare [University College London Hospital, Departments of Radiology, London (United Kingdom); Freeman, Alex [University College London Hospital, Department of Histopathology, London (United Kingdom)

    2014-09-17

    We aimed to develop logistic regression (LR) models for classifying prostate cancer within the transition zone on multi-parametric magnetic resonance imaging (mp-MRI). One hundred and fifty-five patients (training cohort, 70 patients; temporal validation cohort, 85 patients) underwent mp-MRI and transperineal-template-prostate-mapping (TPM) biopsy. Positive cores were classified by cancer definitions: (1) any-cancer; (2) definition-1 [≥Gleason 4 + 3 or ≥ 6 mm cancer core length (CCL)] [high risk significant]; and (3) definition-2 (≥Gleason 3 + 4 or ≥ 4 mm CCL) cancer [intermediate-high risk significant]. For each, logistic-regression mp-MRI models were derived from the training cohort and validated internally and with the temporal cohort. Sensitivity/specificity and the area under the receiver operating characteristic (ROC-AUC) curve were calculated. LR model performance was compared to radiologists' performance. Twenty-eight of 70 patients from the training cohort, and 25/85 patients from the temporal validation cohort had significant cancer on TPM. The ROC-AUC of the LR model for classification of cancer was 0.73/0.67 at internal/temporal validation. The radiologist A/B ROC-AUC was 0.65/0.74 (temporal cohort). For patients scored by radiologists as Prostate Imaging Reporting and Data System (Pi-RADS) score 3, sensitivity/specificity of radiologist A 'best guess' and LR model was 0.14/0.54 and 0.71/0.61, respectively; and radiologist B 'best guess' and LR model was 0.40/0.34 and 0.50/0.76, respectively. LR models can improve classification of Pi-RADS score 3 lesions similar to experienced radiologists. (orig.)

  1. Logistic regression model for diagnosis of transition zone prostate cancer on multi-parametric MRI

    International Nuclear Information System (INIS)

    Dikaios, Nikolaos; Halligan, Steve; Taylor, Stuart; Atkinson, David; Punwani, Shonit; Alkalbani, Jokha; Sidhu, Harbir Singh; Fujiwara, Taiki; Abd-Alazeez, Mohamed; Ahmed, Hashim; Emberton, Mark; Kirkham, Alex; Allen, Clare; Freeman, Alex

    2015-01-01

    We aimed to develop logistic regression (LR) models for classifying prostate cancer within the transition zone on multi-parametric magnetic resonance imaging (mp-MRI). One hundred and fifty-five patients (training cohort, 70 patients; temporal validation cohort, 85 patients) underwent mp-MRI and transperineal-template-prostate-mapping (TPM) biopsy. Positive cores were classified by cancer definitions: (1) any-cancer; (2) definition-1 [≥Gleason 4 + 3 or ≥ 6 mm cancer core length (CCL)] [high risk significant]; and (3) definition-2 (≥Gleason 3 + 4 or ≥ 4 mm CCL) cancer [intermediate-high risk significant]. For each, logistic-regression mp-MRI models were derived from the training cohort and validated internally and with the temporal cohort. Sensitivity/specificity and the area under the receiver operating characteristic (ROC-AUC) curve were calculated. LR model performance was compared to radiologists' performance. Twenty-eight of 70 patients from the training cohort, and 25/85 patients from the temporal validation cohort had significant cancer on TPM. The ROC-AUC of the LR model for classification of cancer was 0.73/0.67 at internal/temporal validation. The radiologist A/B ROC-AUC was 0.65/0.74 (temporal cohort). For patients scored by radiologists as Prostate Imaging Reporting and Data System (Pi-RADS) score 3, sensitivity/specificity of radiologist A 'best guess' and LR model was 0.14/0.54 and 0.71/0.61, respectively; and radiologist B 'best guess' and LR model was 0.40/0.34 and 0.50/0.76, respectively. LR models can improve classification of Pi-RADS score 3 lesions similar to experienced radiologists. (orig.)

  2. Model Novaes for analysis of the productivity and efficiency of logistics operators in Brazil: a study of its applicability for the years 2005 and 2006

    Directory of Open Access Journals (Sweden)

    Emanuel Rodrigues Junqueira

    2008-07-01

    Full Text Available The study presents a proposal to upgrade the production function to evaluate the productivity and efficiency of Brazilians logistics operators, which was developed by Novaes in his study in 2000. The goal was identify if and how the variables used continued to explain the behavior of productivity of these companies. To achieve that goal, tests were performed with data of years for 2005 and 2006, provided by the Revista Tecnologística, and used the same statistical techniques developed in the previous study, the multiple regression. The previous study intended to help the competitive advantage of logistics operators attentive to the problem, through the methodology of analysis of competitors and to customers of this service along the supply chain management, interested in identifying companies with greater efficiency. The results indicate that the model developed by Novaes is not valid for the current reality of these companies. Key-words: productivity function; logistic operators; analysis of competitors and suppliers.

  3. A Selection Model to Logistic Centers Based on TOPSIS and MCGP Methods: The Case of Airline Industry

    Directory of Open Access Journals (Sweden)

    Kou-Huang Chen

    2014-01-01

    Full Text Available The location selection of a logistics center is a crucial decision relating to cost and benefit analysis in airline industry. However, it is difficult to be solved because there are many conflicting and multiple objectives in location problems. To solve the problem, this paper integrates fuzzy technique for order preference by similarity to an ideal solution (TOPSIS and multichoice goal programming (MCGP to obtain an appropriate logistics center from many alternative locations for airline industry. The proposed method in this paper will offer the decision makers (DMs to set multiple aspiration levels for the decision criteria. A numerical example of application is also presented.

  4. A fuzzy Bi-linear management model in reverse logistic chains

    Directory of Open Access Journals (Sweden)

    Tadić Danijela

    2016-01-01

    Full Text Available The management of the electrical and electronic waste (WEEE problem in the uncertain environment has a critical effect on the economy and environmental protection of each region. The considered problem can be stated as a fuzzy non-convex optimization problem with linear objective function and a set of linear and non-linear constraints. The original problem is reformulated by using linear relaxation into a fuzzy linear programming problem. The fuzzy rating of collecting point capacities and fix costs of recycling centers are modeled by triangular fuzzy numbers. The optimal solution of the reformulation model is found by using optimality concept. The proposed model is verified through an illustrative example with real-life data. The obtained results represent an input for future research which should include a good benchmark base for tested reverse logistic chains and their continuous improvement. [Projekat Ministarstva nauke Republike Srbije, br. 035033: Sustainable development technology and equipment for the recycling of motor vehicles

  5. A New Availability-Payment Model for Pricing Performance-Based Logistics Contracts

    Science.gov (United States)

    2014-05-01

    Grant number: N00244‐13‐1‐0009 A New “Availability‐ Payment ”  Model  for Pricing Performance‐ Based Logistics Contracts A. KashaniPour, X. Zhu, P...DATE MAY 2014 2. REPORT TYPE 3. DATES COVERED 00-00-2014 to 00-00-2014 4. TITLE AND SUBTITLE A New ’Availability‐ Payment ’ Model for...is how the  payment   model  in the contract  quantifies the contractor’s  performance for awarding incentives  or penalties Discrete‐Event Simulator ut

  6. Logistic regression analysis of multiple noninvasive tests for the prediction of the presence and extent of coronary artery disease in men

    International Nuclear Information System (INIS)

    Hung, J.; Chaitman, B.R.; Lam, J.; Lesperance, J.; Dupras, G.; Fines, P.; Cherkaoui, O.; Robert, P.; Bourassa, M.G.

    1985-01-01

    The incremental diagnostic yield of clinical data, exercise ECG, stress thallium scintigraphy, and cardiac fluoroscopy to predict coronary and multivessel disease was assessed in 171 symptomatic men by means of multiple logistic regression analyses. When clinical variables alone were analyzed, chest pain type and age were predictive of coronary disease, whereas chest pain type, age, a family history of premature coronary disease before age 55 years, and abnormal ST-T wave changes on the rest ECG were predictive of multivessel disease. The percentage of patients correctly classified by cardiac fluoroscopy (presence or absence of coronary artery calcification), exercise ECG, and thallium scintigraphy was 9%, 25%, and 50%, respectively, greater than for clinical variables, when the presence or absence of coronary disease was the outcome, and 13%, 25%, and 29%, respectively, when multivessel disease was studied; 5% of patients were misclassified. When the 37 clinical and noninvasive test variables were analyzed jointly, the most significant variable predictive of coronary disease was an abnormal thallium scan and for multivessel disease, the amount of exercise performed. The data from this study provide a quantitative model and confirm previous reports that optimal diagnostic efficacy is obtained when noninvasive tests are ordered sequentially. In symptomatic men, cardiac fluoroscopy is a relatively ineffective test when compared to exercise ECG and thallium scintigraphy

  7. Exploring the Use of Microworld Models to Train Army Logistics Management Skills

    National Research Council Canada - National Science Library

    Levy, Dina

    2001-01-01

    The Army faces new challenges in training its logistics managers. As the Army evolves into a force-projection Army, the design and management of large-scale logistics systems assume increasing importance...

  8. Quantitative analysis of the clinical data on leukemia, 5. Specificity of clinical features in acute myelocytic leukemia with 8; 21 translocation by multiple logistic discriminant analysis

    Energy Technology Data Exchange (ETDEWEB)

    Ueoka, Hiroshi; Kamada, Nanao; Yamamoto, Hisashi; Ohtaki, Megu; Takimoto, Yasuo; Kuramoto, Atsushi; Munaka, Masaki

    1984-11-01

    In order to determine the necessity of chromosome analysis required for the evaluation of 8;21 translocation, multiple logistic discriminant analysis was made on 124 patients with acute non-lymphocytic leukemia experienced in the authors' institution. Variables which showed positive correlation with the presence of 8;21 translocation were the presence of Auer body and granular abnormality of the cells, numbers of peripheral promyelocytes, myelocytes and metamyelocytes, and bone marrow promyelocytes, myelocytes, and the sum of rods and segments. Those which showed negative correlation with 8;21 translocation were peripheral platelet count, neutrocytealkaline phosphatase (N-AP) score, numbers of eosinocytes, monocytes and erythroblasts, and erythroblasts on myelogram. Auer body, four peripheral hematological features (platelet count, N-AP score, metamyelocytes and monocytes), and three myelogram features (myelocytes, reticular cells and granulocytes/eosionocytes) were used for the multiple logistic discriminant analysis. By the analysis, 2 of the 22 patients (9.1%) with translocation were judged not to have 8;21 translocation and 3 of the 102 patients (2.9%) without translocation were judged to have it. Therefore, this multiple logistic discriminant method has proved to be simple and useful in clinically evaluating acute non-lymphocytic leukemia. (Namekawa, K.).

  9. A Logistic Regression Based Auto Insurance Rate-Making Model Designed for the Insurance Rate Reform

    Directory of Open Access Journals (Sweden)

    Zhengmin Duan

    2018-02-01

    Full Text Available Using a generalized linear model to determine the claim frequency of auto insurance is a key ingredient in non-life insurance research. Among auto insurance rate-making models, there are very few considering auto types. Therefore, in this paper we are proposing a model that takes auto types into account by making an innovative use of the auto burden index. Based on this model and data from a Chinese insurance company, we built a clustering model that classifies auto insurance rates into three risk levels. The claim frequency and the claim costs are fitted to select a better loss distribution. Then the Logistic Regression model is employed to fit the claim frequency, with the auto burden index considered. Three key findings can be concluded from our study. First, more than 80% of the autos with an auto burden index of 20 or higher belong to the highest risk level. Secondly, the claim frequency is better fitted using the Poisson distribution, however the claim cost is better fitted using the Gamma distribution. Lastly, based on the AIC criterion, the claim frequency is more adequately represented by models that consider the auto burden index than those do not. It is believed that insurance policy recommendations that are based on Generalized linear models (GLM can benefit from our findings.

  10. Study on Maritime Logistics Warehousing Center Model and Precision Marketing Strategy Optimization Based on Fuzzy Method and Neural Network Model

    Directory of Open Access Journals (Sweden)

    Xiao Kefeng

    2017-08-01

    Full Text Available The bulk commodity, different with the retail goods, has a uniqueness in the location selection, the chosen of transportation program and the decision objectives. How to make optimal decisions in the facility location, requirement distribution, shipping methods and the route selection and establish an effective distribution system to reduce the cost has become a burning issue for the e-commerce logistics, which is worthy to be deeply and systematically solved. In this paper, Logistics warehousing center model and precision marketing strategy optimization based on fuzzy method and neural network model is proposed to solve this problem. In addition, we have designed principles of the fuzzy method and neural network model to solve the proposed model because of its complexity. Finally, we have solved numerous examples to compare the results of lingo and Matlab, we use Matlab and lingo just to check the result and to illustrate the numerical example, we can find from the result, the multi-objective model increases logistics costs and improves the efficiency of distribution time.

  11. AN APPLICATION OF THE LOGISTIC REGRESSION MODEL IN THE EXPERIMENTAL PHYSICAL CHEMISTRY

    Directory of Open Access Journals (Sweden)

    Elpidio Corral-López

    2015-06-01

    Full Text Available The calculation of intensive properties molar volumes of ethanol-water mixtures by experimental densities and tangent method in the Physical Chemistry Laboratory presents the problem of making manually the molar volume curve versus mole fraction and the trace of the tangent line trace. The advantage of using a statistical model the Logistic Regression on a Texas VOYAGE graphing calculator allowed trace the curve and the tangents in situ, and also evaluate the students work during the experimental session. The error percentage between the molar volumes calculated using literature data and those obtained with statistical method is minimal, which validates the model. It is advantageous use the calculator with this application as a teaching support tool, reducing the evaluation time of 3 weeks to 3 hours.

  12. Threshold Dynamics of a Huanglongbing Model with Logistic Growth in Periodic Environments

    Directory of Open Access Journals (Sweden)

    Jianping Wang

    2014-01-01

    Full Text Available We analyze the impact of seasonal activity of psyllid on the dynamics of Huanglongbing (HLB infection. A new model about HLB transmission with Logistic growth in psyllid insect vectors and periodic coefficients has been investigated. It is shown that the global dynamics are determined by the basic reproduction number R0 which is defined through the spectral radius of a linear integral operator. If R0 1, then the disease persists. Numerical values of parameters of the model are evaluated taken from the literatures. Furthermore, numerical simulations support our analytical conclusions and the sensitive analysis on the basic reproduction number to the changes of average and amplitude values of the recruitment function of citrus are shown. Finally, some useful comments on controlling the transmission of HLB are given.

  13. Q-Matrix Optimization Based on the Linear Logistic Test Model.

    Science.gov (United States)

    Ma, Lin; Green, Kelly E

    This study explored optimization of item-attribute matrices with the linear logistic test model (Fischer, 1973), with optimal models explaining more variance in item difficulty due to identified item attributes. Data were 8th-grade mathematics test item responses of two TIMSS 2007 booklets. The study investigated three categories of attributes (content, cognitive process, and comprehensive cognitive process) at two grain levels (larger, smaller) and also compared results with random attribute matrices. The proposed attributes accounted for most of the variance in item difficulty for two assessment booklets (81% and 65%). The variance explained by the content attributes was very small (13% to 31%), less than variance explained by the comprehensive cognitive process attributes which explained much more variance than the content and cognitive process attributes. The variances explained by the grain level were similar to each other. However, the attributes did not predict the item difficulties of two assessment booklets equally.

  14. Stability and bifurcation analysis of an SIR epidemic model with logistic growth and saturated treatment

    International Nuclear Information System (INIS)

    Li, Jinhui; Teng, Zhidong; Wang, Guangqing; Zhang, Long; Hu, Cheng

    2017-01-01

    In this paper, we introduce the saturated treatment and logistic growth rate into an SIR epidemic model with bilinear incidence. The treatment function is assumed to be a continuously differential function which describes the effect of delayed treatment when the medical condition is limited and the number of infected individuals is large enough. Sufficient conditions for the existence and local stability of the disease-free and positive equilibria are established. And the existence of the stable limit cycles also is obtained. Moreover, by using the theory of bifurcations, it is shown that the model exhibits backward bifurcation, Hopf bifurcation and Bogdanov–Takens bifurcations. Finally, the numerical examples are given to illustrate the theoretical results and obtain some additional interesting phenomena, involving double stable periodic solutions and stable limit cycles.

  15. A joint logistic regression and covariate-adjusted continuous-time Markov chain model.

    Science.gov (United States)

    Rubin, Maria Laura; Chan, Wenyaw; Yamal, Jose-Miguel; Robertson, Claudia Sue

    2017-12-10

    The use of longitudinal measurements to predict a categorical outcome is an increasingly common goal in research studies. Joint models are commonly used to describe two or more models simultaneously by considering the correlated nature of their outcomes and the random error present in the longitudinal measurements. However, there is limited research on joint models with longitudinal predictors and categorical cross-sectional outcomes. Perhaps the most challenging task is how to model the longitudinal predictor process such that it represents the true biological mechanism that dictates the association with the categorical response. We propose a joint logistic regression and Markov chain model to describe a binary cross-sectional response, where the unobserved transition rates of a two-state continuous-time Markov chain are included as covariates. We use the method of maximum likelihood to estimate the parameters of our model. In a simulation study, coverage probabilities of about 95%, standard deviations close to standard errors, and low biases for the parameter values show that our estimation method is adequate. We apply the proposed joint model to a dataset of patients with traumatic brain injury to describe and predict a 6-month outcome based on physiological data collected post-injury and admission characteristics. Our analysis indicates that the information provided by physiological changes over time may help improve prediction of long-term functional status of these severely ill subjects. Copyright © 2017 John Wiley & Sons, Ltd. Copyright © 2017 John Wiley & Sons, Ltd.

  16. Comparison of Prediction Model for Cardiovascular Autonomic Dysfunction Using Artificial Neural Network and Logistic Regression Analysis

    Science.gov (United States)

    Zeng, Fangfang; Li, Zhongtao; Yu, Xiaoling; Zhou, Linuo

    2013-01-01

    Background This study aimed to develop the artificial neural network (ANN) and multivariable logistic regression (LR) analyses for prediction modeling of cardiovascular autonomic (CA) dysfunction in the general population, and compare the prediction models using the two approaches. Methods and Materials We analyzed a previous dataset based on a Chinese population sample consisting of 2,092 individuals aged 30–80 years. The prediction models were derived from an exploratory set using ANN and LR analysis, and were tested in the validation set. Performances of these prediction models were then compared. Results Univariate analysis indicated that 14 risk factors showed statistically significant association with the prevalence of CA dysfunction (P<0.05). The mean area under the receiver-operating curve was 0.758 (95% CI 0.724–0.793) for LR and 0.762 (95% CI 0.732–0.793) for ANN analysis, but noninferiority result was found (P<0.001). The similar results were found in comparisons of sensitivity, specificity, and predictive values in the prediction models between the LR and ANN analyses. Conclusion The prediction models for CA dysfunction were developed using ANN and LR. ANN and LR are two effective tools for developing prediction models based on our dataset. PMID:23940593

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

    Science.gov (United States)

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

    2018-04-01

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

  18. Reverse Logistics

    OpenAIRE

    Kulikova, Olga

    2016-01-01

    This thesis was focused on the analysis of the concept of reverse logistics and actual reverse processes which are implemented in mining industry and finding solutions for the optimization of reverse logistics in this sphere. The objective of this paper was the assessment of the development of reverse logistics in mining industry on the example of potash production. The theoretical part was based on reverse logistics and mining waste related literature and provided foundations for further...

  19. Comparison of logistic regression and neural models in predicting the outcome of biopsy in breast cancer from MRI findings

    International Nuclear Information System (INIS)

    Abdolmaleki, P.; Yarmohammadi, M.; Gity, M.

    2004-01-01

    Background: We designed an algorithmic model based on regression analysis and a non-algorithmic model based on the Artificial Neural Network. Materials and methods: The ability of these models was compared together in clinical application to differentiate malignant from benign breast tumors in a study group of 161 patient's records. Each patient's record consisted of 6 subjective features extracted from MRI appearance. These findings were enclosed as features extracted for an Artificial Neural Network as well as a logistic regression model to predict biopsy outcome. After both models had been trained perfectly on samples (n=100), the validation samples (n=61) were presented to the trained network as well as the established logistic regression models. Finally, the diagnostic performance of models were compared to the that of the radiologist in terms of sensitivity, specificity and accuracy, using receiver operating characteristic curve analysis. Results: The average out put of the Artificial Neural Network yielded a perfect sensitivity (98%) and high accuracy (90%) similar to that one of an expert radiologist (96% and 92%) while specificity was smaller than that (67%) verses 80%). The output of the logistic regression model using significant features showed improvement in specificity from 60% for the logistic regression model using all features to 93% for the reduced logistic regression model, keeping the accuracy around 90%. Conclusion: Results show that Artificial Neural Network and logistic regression model prove the relationship between extracted morphological features and biopsy results. Using statistically significant variables reduced logistic regression model outperformed of Artificial Neural Network with remarkable specificity while keeping high sensitivity is achieved

  20. Zone-specific logistic regression models improve classification of prostate cancer on multi-parametric MRI

    Energy Technology Data Exchange (ETDEWEB)

    Dikaios, Nikolaos; Halligan, Steve; Taylor, Stuart; Atkinson, David; Punwani, Shonit [University College London, Centre for Medical Imaging, London (United Kingdom); University College London Hospital, Departments of Radiology, London (United Kingdom); Alkalbani, Jokha; Sidhu, Harbir Singh [University College London, Centre for Medical Imaging, London (United Kingdom); Abd-Alazeez, Mohamed; Ahmed, Hashim U.; Emberton, Mark [University College London, Research Department of Urology, Division of Surgery and Interventional Science, London (United Kingdom); Kirkham, Alex [University College London Hospital, Departments of Radiology, London (United Kingdom); Freeman, Alex [University College London Hospital, Department of Histopathology, London (United Kingdom)

    2015-09-15

    To assess the interchangeability of zone-specific (peripheral-zone (PZ) and transition-zone (TZ)) multiparametric-MRI (mp-MRI) logistic-regression (LR) models for classification of prostate cancer. Two hundred and thirty-one patients (70 TZ training-cohort; 76 PZ training-cohort; 85 TZ temporal validation-cohort) underwent mp-MRI and transperineal-template-prostate-mapping biopsy. PZ and TZ uni/multi-variate mp-MRI LR-models for classification of significant cancer (any cancer-core-length (CCL) with Gleason > 3 + 3 or any grade with CCL ≥ 4 mm) were derived from the respective cohorts and validated within the same zone by leave-one-out analysis. Inter-zonal performance was tested by applying TZ models to the PZ training-cohort and vice-versa. Classification performance of TZ models for TZ cancer was further assessed in the TZ validation-cohort. ROC area-under-curve (ROC-AUC) analysis was used to compare models. The univariate parameters with the best classification performance were the normalised T2 signal (T2nSI) within the TZ (ROC-AUC = 0.77) and normalized early contrast-enhanced T1 signal (DCE-nSI) within the PZ (ROC-AUC = 0.79). Performance was not significantly improved by bi-variate/tri-variate modelling. PZ models that contained DCE-nSI performed poorly in classification of TZ cancer. The TZ model based solely on maximum-enhancement poorly classified PZ cancer. LR-models dependent on DCE-MRI parameters alone are not interchangeable between prostatic zones; however, models based exclusively on T2 and/or ADC are more robust for inter-zonal application. (orig.)

  1. Testing a model of research intention among U.K. clinical psychologists: a logistic regression analysis.

    Science.gov (United States)

    Eke, Gemma; Holttum, Sue; Hayward, Mark

    2012-03-01

    Previous research highlights barriers to clinical psychologists conducting research, but has rarely examined U.K. clinical psychologists. The study investigated U.K. clinical psychologists' self-reported research output and tested part of a theoretical model of factors influencing their intention to conduct research. Questionnaires were mailed to 1,300 U.K. clinical psychologists. Three hundred and seventy-four questionnaires were returned (29% response-rate). This study replicated in a U.K. sample the finding that the modal number of publications was zero, highlighted in a number of U.K. and U.S. studies. Research intention was bimodally distributed, and logistic regression classified 78% of cases successfully. Outcome expectations, perceived behavioral control and normative beliefs mediated between research training environment and intention. Further research should explore how research is negotiated in clinical roles, and this issue should be incorporated into prequalification training. © 2012 Wiley Periodicals, Inc.

  2. Binary logistic regression modelling: Measuring the probability of relapse cases among drug addict

    Science.gov (United States)

    Ismail, Mohd Tahir; Alias, Siti Nor Shadila

    2014-07-01

    For many years Malaysia faced the drug addiction issues. The most serious case is relapse phenomenon among treated drug addict (drug addict who have under gone the rehabilitation programme at Narcotic Addiction Rehabilitation Centre, PUSPEN). Thus, the main objective of this study is to find the most significant factor that contributes to relapse to happen. The binary logistic regression analysis was employed to model the relationship between independent variables (predictors) and dependent variable. The dependent variable is the status of the drug addict either relapse, (Yes coded as 1) or not, (No coded as 0). Meanwhile the predictors involved are age, age at first taking drug, family history, education level, family crisis, community support and self motivation. The total of the sample is 200 which the data are provided by AADK (National Antidrug Agency). The finding of the study revealed that age and self motivation are statistically significant towards the relapse cases..

  3. Morphology of the cumulative logistic distribution when used as a model of radiologic film characteristic curves

    International Nuclear Information System (INIS)

    Prince, J.R.

    1988-01-01

    The cumulative logistic distribution (CLD) is an empiric model for film characteristic curves. Characterizing the shape parameters of the CLD in terms of contrast, latitude and speed is required. The CLD is written as Υ-F=D/[1+EXP-(Κ+κ 1 X)] where Υ is the optical density (OD) at log exposure X, F is fog level, D is a constant equal to Dm-F, Κ and κ 1 are shape parameters, and Dm is the maximum attainable OD. Further analysis demonstrates that when Κ is held constant, Κ 1 characterizes contrast (the larger κ 1 , the greater the contrast) and hence latitude; when κ 1 is held constant, Κ characterizes film speed (the larger Κ is, the faster the film). These equations and concepts are further illustrated with examples from radioscintigraphy, diagnostic radiology, and light sensitometry

  4. Mixture model-based clustering and logistic regression for automatic detection of microaneurysms in retinal images

    Science.gov (United States)

    Sánchez, Clara I.; Hornero, Roberto; Mayo, Agustín; García, María

    2009-02-01

    Diabetic Retinopathy is one of the leading causes of blindness and vision defects in developed countries. An early detection and diagnosis is crucial to avoid visual complication. Microaneurysms are the first ocular signs of the presence of this ocular disease. Their detection is of paramount importance for the development of a computer-aided diagnosis technique which permits a prompt diagnosis of the disease. However, the detection of microaneurysms in retinal images is a difficult task due to the wide variability that these images usually present in screening programs. We propose a statistical approach based on mixture model-based clustering and logistic regression which is robust to the changes in the appearance of retinal fundus images. The method is evaluated on the public database proposed by the Retinal Online Challenge in order to obtain an objective performance measure and to allow a comparative study with other proposed algorithms.

  5. Decoding and modelling of time series count data using Poisson hidden Markov model and Markov ordinal logistic regression models.

    Science.gov (United States)

    Sebastian, Tunny; Jeyaseelan, Visalakshi; Jeyaseelan, Lakshmanan; Anandan, Shalini; George, Sebastian; Bangdiwala, Shrikant I

    2018-01-01

    Hidden Markov models are stochastic models in which the observations are assumed to follow a mixture distribution, but the parameters of the components are governed by a Markov chain which is unobservable. The issues related to the estimation of Poisson-hidden Markov models in which the observations are coming from mixture of Poisson distributions and the parameters of the component Poisson distributions are governed by an m-state Markov chain with an unknown transition probability matrix are explained here. These methods were applied to the data on Vibrio cholerae counts reported every month for 11-year span at Christian Medical College, Vellore, India. Using Viterbi algorithm, the best estimate of the state sequence was obtained and hence the transition probability matrix. The mean passage time between the states were estimated. The 95% confidence interval for the mean passage time was estimated via Monte Carlo simulation. The three hidden states of the estimated Markov chain are labelled as 'Low', 'Moderate' and 'High' with the mean counts of 1.4, 6.6 and 20.2 and the estimated average duration of stay of 3, 3 and 4 months, respectively. Environmental risk factors were studied using Markov ordinal logistic regression analysis. No significant association was found between disease severity levels and climate components.

  6. Evaluating an Automated Number Series Item Generator Using Linear Logistic Test Models

    Directory of Open Access Journals (Sweden)

    Bao Sheng Loe

    2018-04-01

    Full Text Available This study investigates the item properties of a newly developed Automatic Number Series Item Generator (ANSIG. The foundation of the ANSIG is based on five hypothesised cognitive operators. Thirteen item models were developed using the numGen R package and eleven were evaluated in this study. The 16-item ICAR (International Cognitive Ability Resource1 short form ability test was used to evaluate construct validity. The Rasch Model and two Linear Logistic Test Model(s (LLTM were employed to estimate and predict the item parameters. Results indicate that a single factor determines the performance on tests composed of items generated by the ANSIG. Under the LLTM approach, all the cognitive operators were significant predictors of item difficulty. Moderate to high correlations were evident between the number series items and the ICAR test scores, with high correlation found for the ICAR Letter-Numeric-Series type items, suggesting adequate nomothetic span. Extended cognitive research is, nevertheless, essential for the automatic generation of an item pool with predictable psychometric properties.

  7. The Role of Cash Flow in Financial Early Warning of Agricultural Enterprises Based on Logistic Model

    Science.gov (United States)

    Sun, Fengru

    2018-01-01

    This paper chooses the agricultural listed companies as the research object, compares the financial situation of the enterprise and the theory of financial early warning, combines the financial status of the agricultural listed companies, selects the relevant cash flow indicators, discusses the application of the Logistic financial early warning model in the agricultural listed companies, Agricultural enterprises get better development. Research on financial early warning of agricultural listed companies will help the agricultural listed companies to predict the financial crisis. Financial early warning model is simple to establish, operational and strong, the use of financial early warning model, to help enterprises in the financial crisis before taking rapid and effective measures, which can avoid losses. Help enterprises to discover signs of deterioration of the financial situation in time to maintain the sustainable development of agricultural enterprises. In addition, through the financial early warning model, investors can correctly identify the financial situation of agricultural enterprises, and can evaluate the financial situation of agricultural enterprises and to help investors to invest in scientific and rational, beneficial to investors to analyze the safety of investment. But also help the relevant regulatory agencies to effectively monitor the market and promote the healthy and stable development of the market.

  8. Multiplicity Control in Structural Equation Modeling

    Science.gov (United States)

    Cribbie, Robert A.

    2007-01-01

    Researchers conducting structural equation modeling analyses rarely, if ever, control for the inflated probability of Type I errors when evaluating the statistical significance of multiple parameters in a model. In this study, the Type I error control, power and true model rates of famsilywise and false discovery rate controlling procedures were…

  9. Identification and validation of a logistic regression model for predicting serious injuries associated with motor vehicle crashes.

    Science.gov (United States)

    Kononen, Douglas W; Flannagan, Carol A C; Wang, Stewart C

    2011-01-01

    A multivariate logistic regression model, based upon National Automotive Sampling System Crashworthiness Data System (NASS-CDS) data for calendar years 1999-2008, was developed to predict the probability that a crash-involved vehicle will contain one or more occupants with serious or incapacitating injuries. These vehicles were defined as containing at least one occupant coded with an Injury Severity Score (ISS) of greater than or equal to 15, in planar, non-rollover crash events involving Model Year 2000 and newer cars, light trucks, and vans. The target injury outcome measure was developed by the Centers for Disease Control and Prevention (CDC)-led National Expert Panel on Field Triage in their recent revision of the Field Triage Decision Scheme (American College of Surgeons, 2006). The parameters to be used for crash injury prediction were subsequently specified by the National Expert Panel. Model input parameters included: crash direction (front, left, right, and rear), change in velocity (delta-V), multiple vs. single impacts, belt use, presence of at least one older occupant (≥ 55 years old), presence of at least one female in the vehicle, and vehicle type (car, pickup truck, van, and sport utility). The model was developed using predictor variables that may be readily available, post-crash, from OnStar-like telematics systems. Model sensitivity and specificity were 40% and 98%, respectively, using a probability cutpoint of 0.20. The area under the receiver operator characteristic (ROC) curve for the final model was 0.84. Delta-V (mph), seat belt use and crash direction were the most important predictors of serious injury. Due to the complexity of factors associated with rollover-related injuries, a separate screening algorithm is needed to model injuries associated with this crash mode. Copyright © 2010 Elsevier Ltd. All rights reserved.

  10. The systems integration operations/logistics model as a decision-support tool

    International Nuclear Information System (INIS)

    Miller, C.; Vogel, L.W.; Joy, D.S.

    1989-01-01

    Congress has enacted legislation specifying Yucca Mountain, Nevada, for characterization as the candidate site for the disposal of spent fuel and high-level wastes and has authorized a monitored retrievable storage (MRS) facility if one is warranted. Nevertheless, the exact configuration of the facilities making up the Federal Waste Management System (FWMS) was not specified. This has left the Office of Civilian Radioactive Waste Management (OCRWM) the responsibility for assuring the design of a safe and reliable disposal system. In order to assist in the analysis of potential configuration alternatives, operating strategies, and other factors for the FWMS and its various elements, a decision-support tool known as the systems integration operations/logistics model (SOLMOD) was developed. SOLMOD is a discrete event simulation model that emulates the movement and interaction of equipment and radioactive waste as it is processed through the FWMS - from pickup at reactor pools to emplacement. The model can be used to measure the impacts of different operating schedules and rules, system configurations, and equipment and other resource availabilities on the performance of processes comprising the FWMS and how these factors combine to determine overall system performance. SOLMOD can assist in identifying bottlenecks and can be used to assess capacity utilization of specific equipment and staff as well as overall system resilience

  11. Predictive occurrence models for coastal wetland plant communities: delineating hydrologic response surfaces with multinomial logistic regression

    Science.gov (United States)

    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.

  12. Predictive occurrence models for coastal wetland plant communities: Delineating hydrologic response surfaces with multinomial logistic regression

    Science.gov (United States)

    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.

  13. Forecasting inter-urban transport demand for a logistics company: A combined grey–periodic extension model with remnant correction

    Directory of Open Access Journals (Sweden)

    Donghui Wang

    2015-12-01

    Full Text Available Accurately predicting short-term transport demand for an individual logistics company involved in a competitive market is critical to make short-term operation decisions. This article proposes a combined grey–periodic extension model with remnant correction to forecast the short-term inter-urban transport demand of a logistics company involved in a nationwide competitive market, showing changes in trend and seasonal fluctuations with irregular periods different to the macroeconomic cycle. A basic grey–periodic extension model of an additive pattern, namely, the main combination model, is first constructed to fit the changing trends and the featured seasonal fluctuation periods. In order to improve prediction accuracy and model adaptability, the grey model is repeatedly modelled to fit the remnant tail time series of the main combination model until prediction accuracy is satisfied. The modelling approach is applied to a logistics company engaged in a nationwide less-than-truckload road transportation business in China. The results demonstrate that the proposed modelling approach produces good forecasting results and goodness of fit, also showing good model adaptability to the analysed object in a changing macro environment. This fact makes this modelling approach an option to analyse the short-term transportation demand of an individual logistics company.

  14. EIA model documentation: World oil refining logistics demand model,''WORLD'' reference manual

    International Nuclear Information System (INIS)

    1994-01-01

    This manual is intended primarily for use as a reference by analysts applying the WORLD model to regional studies. It also provides overview information on WORLD features of potential interest to managers and analysts. Broadly, the manual covers WORLD model features in progressively increasing detail. Section 2 provides an overview of the WORLD model, how it has evolved, what its design goals are, what it produces, and where it can be taken with further enhancements. Section 3 reviews model management covering data sources, managing over-optimization, calibration and seasonality, check-points for case construction and common errors. Section 4 describes in detail the WORLD system, including: data and program systems in overview; details of mainframe and PC program control and files;model generation, size management, debugging and error analysis; use with different optimizers; and reporting and results analysis. Section 5 provides a detailed description of every WORLD model data table, covering model controls, case and technology data. Section 6 goes into the details of WORLD matrix structure. It provides an overview, describes how regional definitions are controlled and defines the naming conventions for-all model rows, columns, right-hand sides, and bounds. It also includes a discussion of the formulation of product blending and specifications in WORLD. Several Appendices supplement the main sections

  15. Easy and low-cost identification of metabolic syndrome in patients treated with second-generation antipsychotics: artificial neural network and logistic regression models.

    Science.gov (United States)

    Lin, Chao-Cheng; Bai, Ya-Mei; Chen, Jen-Yeu; Hwang, Tzung-Jeng; Chen, Tzu-Ting; Chiu, Hung-Wen; Li, Yu-Chuan

    2010-03-01

    Metabolic syndrome (MetS) is an important side effect of second-generation antipsychotics (SGAs). However, many SGA-treated patients with MetS remain undetected. In this study, we trained and validated artificial neural network (ANN) and multiple logistic regression models without biochemical parameters to rapidly identify MetS in patients with SGA treatment. A total of 383 patients with a diagnosis of schizophrenia or schizoaffective disorder (DSM-IV criteria) with SGA treatment for more than 6 months were investigated to determine whether they met the MetS criteria according to the International Diabetes Federation. The data for these patients were collected between March 2005 and September 2005. The input variables of ANN and logistic regression were limited to demographic and anthropometric data only. All models were trained by randomly selecting two-thirds of the patient data and were internally validated with the remaining one-third of the data. The models were then externally validated with data from 69 patients from another hospital, collected between March 2008 and June 2008. The area under the receiver operating characteristic curve (AUC) was used to measure the performance of all models. Both the final ANN and logistic regression models had high accuracy (88.3% vs 83.6%), sensitivity (93.1% vs 86.2%), and specificity (86.9% vs 83.8%) to identify MetS in the internal validation set. The mean +/- SD AUC was high for both the ANN and logistic regression models (0.934 +/- 0.033 vs 0.922 +/- 0.035, P = .63). During external validation, high AUC was still obtained for both models. Waist circumference and diastolic blood pressure were the common variables that were left in the final ANN and logistic regression models. Our study developed accurate ANN and logistic regression models to detect MetS in patients with SGA treatment. The models are likely to provide a noninvasive tool for large-scale screening of MetS in this group of patients. (c) 2010 Physicians

  16. Demand analysis of flood insurance by using logistic regression model and genetic algorithm

    Science.gov (United States)

    Sidi, P.; Mamat, M. B.; Sukono; Supian, S.; Putra, A. S.

    2018-03-01

    Citarum River floods in the area of South Bandung Indonesia, often resulting damage to some buildings belonging to the people living in the vicinity. One effort to alleviate the risk of building damage is to have flood insurance. The main obstacle is not all people in the Citarum basin decide to buy flood insurance. In this paper, we intend to analyse the decision to buy flood insurance. It is assumed that there are eight variables that influence the decision of purchasing flood assurance, include: income level, education level, house distance with river, building election with road, flood frequency experience, flood prediction, perception on insurance company, and perception towards government effort in handling flood. The analysis was done by using logistic regression model, and to estimate model parameters, it is done with genetic algorithm. The results of the analysis shows that eight variables analysed significantly influence the demand of flood insurance. These results are expected to be considered for insurance companies, to influence the decision of the community to be willing to buy flood insurance.

  17. Predicting the "graduate on time (GOT)" of PhD students using binary logistics regression model

    Science.gov (United States)

    Shariff, S. Sarifah Radiah; Rodzi, Nur Atiqah Mohd; Rahman, Kahartini Abdul; Zahari, Siti Meriam; Deni, Sayang Mohd

    2016-10-01

    Malaysian government has recently set a new goal to produce 60,000 Malaysian PhD holders by the year 2023. As a Malaysia's largest institution of higher learning in terms of size and population which offers more than 500 academic programmes in a conducive and vibrant environment, UiTM has taken several initiatives to fill up the gap. Strategies to increase the numbers of graduates with PhD are a process that is challenging. In many occasions, many have already identified that the struggle to get into the target set is even more daunting, and that implementation is far too ideal. This has further being progressing slowly as the attrition rate increases. This study aims to apply the proposed models that incorporates several factors in predicting the number PhD students that will complete their PhD studies on time. Binary Logistic Regression model is proposed and used on the set of data to determine the number. The results show that only 6.8% of the 2014 PhD students are predicted to graduate on time and the results are compared wih the actual number for validation purpose.

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

    Science.gov (United States)

    Dai, Huanping; Micheyl, Christophe

    2012-11-01

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

  19. A Model of An Integration System for Operations and Cost Data Designed to Control Logistics Processes in Agricultural Enterprises

    Directory of Open Access Journals (Sweden)

    Karol Wajszczuk

    2011-03-01

    Full Text Available The paper presents a model of an integration system for operations and cost data designed for the needs of process controlling in agricultural enterprises, with special emphasis on logistics processes. The proposed model constituted the basis for the development of an IT tool to be used in the identification and analysis of logistics costs in agricultural enterprises in terms of the process based approach. As a result of research and programming efforts a model was developed, which made it possible in agricultural enterprises to determine the type-based relationship of cost dynamics and structure with realized actions, operating processes (including logistics processes and products, as well as the relationship of these costs with used resources, maintained stocks, applied materials and work methods. Moreover, this model facilitates cost allocation to products and processes as well as cost centers and points, and makes it possible to determine multidimensional dependencies of the result (divided into individual products on incurred costs.

  20. Smart logistics

    NARCIS (Netherlands)

    Woensel, van T.

    2012-01-01

    This lecture focuses on Smart Logistics referring to these intelligent managerial decisions related to the design, operations and control of the transportation chain processes in an efficient and cost-effective way. The starting point for Smart Logistics is the key observation that the real-life

  1. CONCURRENT ENGINEERING MODEL (CEM ANALYSIS ON LOGISTICS DESIGN PARAMETERS – A CASE STUDY

    Directory of Open Access Journals (Sweden)

    J.S. Gnanasekaran

    2012-01-01

    Full Text Available

    ENGLISH ABSTRACT: Logistics engineering can be divided into internal or in-plant logistics and external manufacturing logistics. Internal (in-plant logistics include material handling, warehousing, and storage systems, while external manufacturing logistics include transportation. Both must be integrated to minimise costs at a competitive level of service. For example, plant layout and production planning must consider internal logistics. The design decisions are made in the early phases of product design, and development will have a significant effect over future manufacturing and logistical activities. In this paper, a methodology is developed and presented to minimise the design cycle time of any manufacturing firm, including their suppliers, and to maximise the whole system’s effectiveness.

    AFRIKAANSE OPSOMMING: Logistieke ingenieurswese kan verdeel word in interne of binne-aanleg logistiek en eksterne vervaardigingslogistiek. Interne (binne-aanleg logistiek behels materiaalhantering, berging en voorraadhoudingsisteme, terwyl eksterne vervaardigingslogistiek vervoer insluit. Die fasette moet geintegreer wees om koste te minimiseer by ‘n mededingende diensvlak. So byvoorbeeld moet die uitleg van ‘n aanleg en produksiebeplanning interne logistiek in aanmerking neem. Die ontwerpbesluite word geneem in die beginstadium van die produkontwerp en ontwikkeling sal ‘n betekenisvolle invloed hê op toekomstige vervaardigings- en logistieke aktiwiteite. In hierdie artikel word ‘n metodologie ontwikkel en aangebied om die ontwerpsiklustyd van enige vervaardigingsonderneming te minimiseer met inagneming van die leweransiers om sodoende die totale sisteem se effektiwiteit te maksimiseer.

  2. Total Logistic Plant Solutions

    Directory of Open Access Journals (Sweden)

    Dusan Dorcak

    2016-02-01

    Full Text Available The Total Logistics Plant Solutions, plant logistics system - TLPS, based on the philosophy of advanced control processes enables complex coordination of business processes and flows and the management and scheduling of production in the appropriate production plans and planning periods. Main attributes of TLPS is to create a comprehensive, multi-level, enterprise logistics information system, with a certain degree of intelligence, which accepts the latest science and research results in the field of production technology and logistics. Logistic model of company understands as a system of mutually transforming flows of materials, energy, information, finance, which is realized by chain activities and operations

  3. Scheduling the Remediation of Port Hope: Logistical and Regulatory Challenges of a Multiple Site Urban Remediation Project - 13119

    International Nuclear Information System (INIS)

    Ferguson Jones, Andrea; Lee, Angela; Palmeter, Tim

    2013-01-01

    The Port Hope Project is part of the larger CAN$1.28 billion Port Hope Area Initiative (PHAI), a community-based program for the development and implementation of a safe, local, long-term management solution for historic Low-Level Radioactive Waste (LLRW) in the Municipalities of Port Hope and Clarington, Ontario, Canada. Atomic Energy of Canada (AECL) is the Project Proponent, Public Works and Government Services (PWGSC) is managing the procurement of services and the MMM Group Limited - Conestoga Rovers and Associates Joint Venture (MMM-CRA Joint Venture) is providing detailed design and construction oversight and administration services for the Project. The Port Hope Project includes the construction of a long-term waste management facility (LTWMF) in the Municipality of Port Hope and the remediation of 18 (eighteen) large-scale LLRW, numerous small-scale sites still being identified and industrial sites within the Municipality. The total volume to be remediated is over one million cubic metres and will come from sites that include temporary storage sites, ravines, beaches, parks, private commercial and residential properties and vacant industrial sites all within the urban area of Port Hope. Challenges that will need to be overcome during this 10 year project include: - Requirements stipulated by the Environmental Assessment (EA) that affect Project logistics and schedule. - Coordination of site remediation with the construction schedule at the LTWMF. - Physical constraints on transport routes and at sites affecting production rates. - Despite being an urban undertaking, seasonal constrains for birds and fish (i.e., nesting and spawning seasons). - Municipal considerations. - Site-specific constraints. - Site interdependencies exist requiring consideration in the schedule. Several sites require the use of an adjacent site for staging. (authors)

  4. Scheduling the Remediation of Port Hope: Logistical and Regulatory Challenges of a Multiple Site Urban Remediation Project - 13119

    Energy Technology Data Exchange (ETDEWEB)

    Ferguson Jones, Andrea; Lee, Angela [MMM Group Limited, 100 Commerce Valley Drive West, Thornhill, Ontario, L3T 0A1 (Canada); Palmeter, Tim [Public Works and Government Services Canada, 4900 Yonge Street, Toronto, Ontario, M2N 6A6 (Canada)

    2013-07-01

    The Port Hope Project is part of the larger CAN$1.28 billion Port Hope Area Initiative (PHAI), a community-based program for the development and implementation of a safe, local, long-term management solution for historic Low-Level Radioactive Waste (LLRW) in the Municipalities of Port Hope and Clarington, Ontario, Canada. Atomic Energy of Canada (AECL) is the Project Proponent, Public Works and Government Services (PWGSC) is managing the procurement of services and the MMM Group Limited - Conestoga Rovers and Associates Joint Venture (MMM-CRA Joint Venture) is providing detailed design and construction oversight and administration services for the Project. The Port Hope Project includes the construction of a long-term waste management facility (LTWMF) in the Municipality of Port Hope and the remediation of 18 (eighteen) large-scale LLRW, numerous small-scale sites still being identified and industrial sites within the Municipality. The total volume to be remediated is over one million cubic metres and will come from sites that include temporary storage sites, ravines, beaches, parks, private commercial and residential properties and vacant industrial sites all within the urban area of Port Hope. Challenges that will need to be overcome during this 10 year project include: - Requirements stipulated by the Environmental Assessment (EA) that affect Project logistics and schedule. - Coordination of site remediation with the construction schedule at the LTWMF. - Physical constraints on transport routes and at sites affecting production rates. - Despite being an urban undertaking, seasonal constrains for birds and fish (i.e., nesting and spawning seasons). - Municipal considerations. - Site-specific constraints. - Site interdependencies exist requiring consideration in the schedule. Several sites require the use of an adjacent site for staging. (authors)

  5. Stakeholders' roles for business modelling in a city logistics ecosystem: Towards a conceptual model

    NARCIS (Netherlands)

    Ir. G. Zenezini; dr. J.H.R. van Duin; Ir. L. Tavasszy; Ir. A. De Marco

    2017-01-01

    A major challenge associated with the implementation of CL initiatives lies with their economic and financial long-term success. In this context, the business model concept can support assessing the business side of stakeholders’ decision-making processes as major determinants for such success. The

  6. Stakeholders’ roles for business modelling in a city logistics ecosystem : Towards a conceptual model

    NARCIS (Netherlands)

    Zenezini, G.; van Duin, Ron; Tavasszy, L.A.; De Marco, Alberto

    2017-01-01

    A major challenge associated with the implementation of CL initiatives lies with their economic and financial long-term success. In this context, the business model concept can support assessing the business side of stakeholders’ decision-making processes as major determinants for such success. The

  7. proceedings of Stakeholders’ roles for business modelling in a city logistics ecosystem: Towards a conceptual model

    NARCIS (Netherlands)

    Zenezini, G.; van Duin, Ron; Tavasszy, L.A.

    2017-01-01

    A major challenge associated with the implementation of CL initiatives lies with their economic and financial long-term success. In this context, the business model concept can support assessing the business side of stakeholders’ decision-making processes as major determinants for such success. The

  8. Modelling landscape change in paddy fields using logistic regression and GIS

    Science.gov (United States)

    Franjaya, E. E.; Syartinilia; Setiawan, Y.

    2018-05-01

    Paddy field in karawang district, as an important agricultural land in west java, has been decreased since 1994. From previous study, paddy fields dominantly turned into built area. The changes were almost occured in the middle area of the district where roadways, industries, settlements, and commercial buildings were existed. These were estimated as driving forces. But, we still need to prove it. This study aimed to construct the paddy field probability change model, subsequently the driving forces will be obtained. GIS combined with logistic regression using environmental variables were used as main method in this study. Ten environmental variables were elevation 0–500 m, elevation>500 m, slope8%, CBD, build up area, river, irrigation, toll and national roadway, and collector and local roadway. The result indicated that four variables were significantly played as driving forces (slope>8%, CBD area, build up area, and collector and local roadway). Paddy field has high, medium, and low probability to change which covered about 27.8%, 7.8%, and 64.4% area in Karawang respectively. Based on landscape ecology, the recommendation that suitable with landscape change is adaptive management.

  9. The likelihood of achieving quantified road safety targets: a binary logistic regression model for possible factors.

    Science.gov (United States)

    Sze, N N; Wong, S C; Lee, C Y

    2014-12-01

    In past several decades, many countries have set quantified road safety targets to motivate transport authorities to develop systematic road safety strategies and measures and facilitate the achievement of continuous road safety improvement. Studies have been conducted to evaluate the association between the setting of quantified road safety targets and road fatality reduction, in both the short and long run, by comparing road fatalities before and after the implementation of a quantified road safety target. However, not much work has been done to evaluate whether the quantified road safety targets are actually achieved. In this study, we used a binary logistic regression model to examine the factors - including vehicle ownership, fatality rate, and national income, in addition to level of ambition and duration of target - that contribute to a target's success. We analyzed 55 quantified road safety targets set by 29 countries from 1981 to 2009, and the results indicate that targets that are in progress and with lower level of ambitions had a higher likelihood of eventually being achieved. Moreover, possible interaction effects on the association between level of ambition and the likelihood of success are also revealed. Copyright © 2014 Elsevier Ltd. All rights reserved.

  10. The reliable solution and computation time of variable parameters Logistic model

    OpenAIRE

    Pengfei, Wang; Xinnong, Pan

    2016-01-01

    The reliable computation time (RCT, marked as Tc) when applying a double precision computation of a variable parameters logistic map (VPLM) is studied. First, using the method proposed, the reliable solutions for the logistic map are obtained. Second, for a time-dependent non-stationary parameters VPLM, 10000 samples of reliable experiments are constructed, and the mean Tc is then computed. The results indicate that for each different initial value, the Tcs of the VPLM are generally different...

  11. [Logistic regression model of noninvasive prediction for portal hypertensive gastropathy in patients with hepatitis B associated cirrhosis].

    Science.gov (United States)

    Wang, Qingliang; Li, Xiaojie; Hu, Kunpeng; Zhao, Kun; Yang, Peisheng; Liu, Bo

    2015-05-12

    To explore the risk factors of portal hypertensive gastropathy (PHG) in patients with hepatitis B associated cirrhosis and establish a Logistic regression model of noninvasive prediction. The clinical data of 234 hospitalized patients with hepatitis B associated cirrhosis from March 2012 to March 2014 were analyzed retrospectively. The dependent variable was the occurrence of PHG while the independent variables were screened by binary Logistic analysis. Multivariate Logistic regression was used for further analysis of significant noninvasive independent variables. Logistic regression model was established and odds ratio was calculated for each factor. The accuracy, sensitivity and specificity of model were evaluated by the curve of receiver operating characteristic (ROC). According to univariate Logistic regression, the risk factors included hepatic dysfunction, albumin (ALB), bilirubin (TB), prothrombin time (PT), platelet (PLT), white blood cell (WBC), portal vein diameter, spleen index, splenic vein diameter, diameter ratio, PLT to spleen volume ratio, esophageal varices (EV) and gastric varices (GV). Multivariate analysis showed that hepatic dysfunction (X1), TB (X2), PLT (X3) and splenic vein diameter (X4) were the major occurring factors for PHG. The established regression model was Logit P=-2.667+2.186X1-2.167X2+0.725X3+0.976X4. The accuracy of model for PHG was 79.1% with a sensitivity of 77.2% and a specificity of 80.8%. Hepatic dysfunction, TB, PLT and splenic vein diameter are risk factors for PHG and the noninvasive predicted Logistic regression model was Logit P=-2.667+2.186X1-2.167X2+0.725X3+0.976X4.

  12. Multinomial logistic regression modelling of obesity and overweight among primary school students in a rural area of Negeri Sembilan

    Energy Technology Data Exchange (ETDEWEB)

    Ghazali, Amirul Syafiq Mohd; Ali, Zalila; Noor, Norlida Mohd; Baharum, Adam [Pusat Pengajian Sains Matematik, Universiti Sains Malaysia, 11800 USM, Pulau Pinang, Malaysia amirul@unisel.edu.my, zalila@cs.usm.my, norlida@usm.my, adam@usm.my (Malaysia)

    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.

  13. Multinomial logistic regression modelling of obesity and overweight among primary school students in a rural area of Negeri Sembilan

    International Nuclear Information System (INIS)

    Ghazali, Amirul Syafiq Mohd; Ali, Zalila; Noor, Norlida Mohd; Baharum, Adam

    2015-01-01

    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

  14. Computational Logistics

    DEFF Research Database (Denmark)

    Pacino, Dario; Voss, Stefan; Jensen, Rune Møller

    2013-01-01

    This book constitutes the refereed proceedings of the 4th International Conference on Computational Logistics, ICCL 2013, held in Copenhagen, Denmark, in September 2013. The 19 papers presented in this volume were carefully reviewed and selected for inclusion in the book. They are organized in to...... in topical sections named: maritime shipping, road transport, vehicle routing problems, aviation applications, and logistics and supply chain management.......This book constitutes the refereed proceedings of the 4th International Conference on Computational Logistics, ICCL 2013, held in Copenhagen, Denmark, in September 2013. The 19 papers presented in this volume were carefully reviewed and selected for inclusion in the book. They are organized...

  15. Computational Logistics

    DEFF Research Database (Denmark)

    This book constitutes the refereed proceedings of the 4th International Conference on Computational Logistics, ICCL 2013, held in Copenhagen, Denmark, in September 2013. The 19 papers presented in this volume were carefully reviewed and selected for inclusion in the book. They are organized in to...... in topical sections named: maritime shipping, road transport, vehicle routing problems, aviation applications, and logistics and supply chain management.......This book constitutes the refereed proceedings of the 4th International Conference on Computational Logistics, ICCL 2013, held in Copenhagen, Denmark, in September 2013. The 19 papers presented in this volume were carefully reviewed and selected for inclusion in the book. They are organized...

  16. Design of Xen Hybrid Multiple Police Model

    Science.gov (United States)

    Sun, Lei; Lin, Renhao; Zhu, Xianwei

    2017-10-01

    Virtualization Technology has attracted more and more attention. As a popular open-source virtualization tools, XEN is used more and more frequently. Xsm, XEN security model, has also been widespread concern. The safety status classification has not been established in the XSM, and it uses the virtual machine as a managed object to make Dom0 a unique administrative domain that does not meet the minimum privilege. According to these questions, we design a Hybrid multiple police model named SV_HMPMD that organically integrates multiple single security policy models include DTE,RBAC,BLP. It can fullfill the requirement of confidentiality and integrity for security model and use different particle size to different domain. In order to improve BLP’s practicability, the model introduce multi-level security labels. In order to divide the privilege in detail, we combine DTE with RBAC. In order to oversize privilege, we limit the privilege of domain0.

  17. Multiple Model Approaches to Modelling and Control,

    DEFF Research Database (Denmark)

    on the ease with which prior knowledge can be incorporated. It is interesting to note that researchers in Control Theory, Neural Networks,Statistics, Artificial Intelligence and Fuzzy Logic have more or less independently developed very similar modelling methods, calling them Local ModelNetworks, Operating......, and allows direct incorporation of high-level and qualitative plant knowledge into themodel. These advantages have proven to be very appealing for industrial applications, and the practical, intuitively appealing nature of the framework isdemonstrated in chapters describing applications of local methods...... to problems in the process industries, biomedical applications and autonomoussystems. The successful application of the ideas to demanding problems is already encouraging, but creative development of the basic framework isneeded to better allow the integration of human knowledge with automated learning...

  18. An epidemiological survey on road traffic crashes in Iran: application of the two logistic regression models.

    Science.gov (United States)

    Bakhtiyari, Mahmood; Mehmandar, Mohammad Reza; Mirbagheri, Babak; Hariri, Gholam Reza; Delpisheh, Ali; Soori, Hamid

    2014-01-01

    Risk factors of human-related traffic crashes are the most important and preventable challenges for community health due to their noteworthy burden in developing countries in particular. The present study aims to investigate the role of human risk factors of road traffic crashes in Iran. Through a cross-sectional study using the COM 114 data collection forms, the police records of almost 600,000 crashes occurred in 2010 are investigated. The binary logistic regression and proportional odds regression models are used. The odds ratio for each risk factor is calculated. These models are adjusted for known confounding factors including age, sex and driving time. The traffic crash reports of 537,688 men (90.8%) and 54,480 women (9.2%) are analysed. The mean age is 34.1 ± 14 years. Not maintaining eyes on the road (53.7%) and losing control of the vehicle (21.4%) are the main causes of drivers' deaths in traffic crashes within cities. Not maintaining eyes on the road is also the most frequent human risk factor for road traffic crashes out of cities. Sudden lane excursion (OR = 9.9, 95% CI: 8.2-11.9) and seat belt non-compliance (OR = 8.7, CI: 6.7-10.1), exceeding authorised speed (OR = 17.9, CI: 12.7-25.1) and exceeding safe speed (OR = 9.7, CI: 7.2-13.2) are the most significant human risk factors for traffic crashes in Iran. The high mortality rate of 39 people for every 100,000 population emphasises on the importance of traffic crashes in Iran. Considering the important role of human risk factors in traffic crashes, struggling efforts are required to control dangerous driving behaviours such as exceeding speed, illegal overtaking and not maintaining eyes on the road.

  19. Risk of Recurrence in Operated Parasagittal Meningiomas: A Logistic Binary Regression Model.

    Science.gov (United States)

    Escribano Mesa, José Alberto; Alonso Morillejo, Enrique; Parrón Carreño, Tesifón; Huete Allut, Antonio; Narro Donate, José María; Méndez Román, Paddy; Contreras Jiménez, Ascensión; Pedrero García, Francisco; Masegosa González, José

    2018-02-01

    Parasagittal meningiomas arise from the arachnoid cells of the angle formed between the superior sagittal sinus (SSS) and the brain convexity. In this retrospective study, we focused on factors that predict early recurrence and recurrence times. We reviewed 125 patients with parasagittal meningiomas operated from 1985 to 2014. We studied the following variables: age, sex, location, laterality, histology, surgeons, invasion of the SSS, Simpson removal grade, follow-up time, angiography, embolization, radiotherapy, recurrence and recurrence time, reoperation, neurologic deficit, degree of dependency, and patient status at the end of follow-up. Patients ranged in age from 26 to 81 years (mean 57.86 years; median 60 years). There were 44 men (35.2%) and 81 women (64.8%). There were 57 patients with neurologic deficits (45.2%). The most common presenting symptom was motor deficit. World Health Organization grade I tumors were identified in 104 patients (84.6%), and the majority were the meningothelial type. Recurrence was detected in 34 cases. Time of recurrence was 9 to 336 months (mean: 84.4 months; median: 79.5 months). Male sex was identified as an independent risk for recurrence with relative risk 2.7 (95% confidence interval 1.21-6.15), P = 0.014. Kaplan-Meier curves for recurrence had statistically significant differences depending on sex, age, histologic type, and World Health Organization histologic grade. A binary logistic regression was made with the Hosmer-Lemeshow test with P > 0.05; sex, tumor size, and histologic type were used in this model. Male sex is an independent risk factor for recurrence that, associated with other factors such tumor size and histologic type, explains 74.5% of all cases in a binary regression model. Copyright © 2017 Elsevier Inc. All rights reserved.

  20. Logistical Worlds

    Directory of Open Access Journals (Sweden)

    Ned Rossiter

    2014-03-01

    Full Text Available As the managerial art and science of coordinating the movement of people, finance and things, logistical operations are central to contemporary capital. Despite its materiality in the form of communications and transport infrastructure, logistics remains an abstract machine for many. This is largely due to the compartmental structure of global supply chains and the invisibility of code. In registering the mediating force of logistics, the essay considers parametric politics as an architecture of intervention for both game design and software development. There are implications here not only for gameplay, but also the invention of method and governance of labour. How, for instance, might game design facilitate the production of a political knowledge of logistics? This becomes a matter to address for labour power vis-à-vis collective research on infrastructure, software and global supply chains.

  1. Multiple model cardinalized probability hypothesis density filter

    Science.gov (United States)

    Georgescu, Ramona; Willett, Peter

    2011-09-01

    The Probability Hypothesis Density (PHD) filter propagates the first-moment approximation to the multi-target Bayesian posterior distribution while the Cardinalized PHD (CPHD) filter propagates both the posterior likelihood of (an unlabeled) target state and the posterior probability mass function of the number of targets. Extensions of the PHD filter to the multiple model (MM) framework have been published and were implemented either with a Sequential Monte Carlo or a Gaussian Mixture approach. In this work, we introduce the multiple model version of the more elaborate CPHD filter. We present the derivation of the prediction and update steps of the MMCPHD particularized for the case of two target motion models and proceed to show that in the case of a single model, the new MMCPHD equations reduce to the original CPHD equations.

  2. Modelling of diffuse solar fraction with multiple predictors

    Energy Technology Data Exchange (ETDEWEB)

    Ridley, Barbara; Boland, John [Centre for Industrial and Applied Mathematics, University of South Australia, Mawson Lakes Boulevard, Mawson Lakes, SA 5095 (Australia); Lauret, Philippe [Laboratoire de Physique du Batiment et des Systemes, University of La Reunion, Reunion (France)

    2010-02-15

    For some locations both global and diffuse solar radiation are measured. However, for many locations, only global radiation is measured, or inferred from satellite data. For modelling solar energy applications, the amount of radiation on a tilted surface is needed. Since only the direct component on a tilted surface can be calculated from direct on some other plane using trigonometry, we need to have diffuse radiation on the horizontal plane available. There are regression relationships for estimating the diffuse on a tilted surface from diffuse on the horizontal. Models for estimating the diffuse on the horizontal from horizontal global that have been developed in Europe or North America have proved to be inadequate for Australia. Boland et al. developed a validated model for Australian conditions. Boland et al. detailed our recent advances in developing the theoretical framework for the use of the logistic function instead of piecewise linear or simple nonlinear functions and was the first step in identifying the means for developing a generic model for estimating diffuse from global and other predictors. We have developed a multiple predictor model, which is much simpler than previous models, and uses hourly clearness index, daily clearness index, solar altitude, apparent solar time and a measure of persistence of global radiation level as predictors. This model performs marginally better than currently used models for locations in the Northern Hemisphere and substantially better for Southern Hemisphere locations. We suggest it can be used as a universal model. (author)

  3. Predictive performance models and multiple task performance

    Science.gov (United States)

    Wickens, Christopher D.; Larish, Inge; Contorer, Aaron

    1989-01-01

    Five models that predict how performance of multiple tasks will interact in complex task scenarios are discussed. The models are shown in terms of the assumptions they make about human operator divided attention. The different assumptions about attention are then empirically validated in a multitask helicopter flight simulation. It is concluded from this simulation that the most important assumption relates to the coding of demand level of different component tasks.

  4. Keep Calm and Learn Multilevel Logistic Modeling: A Simplified Three-Step Procedure Using Stata, R, Mplus, and SPSS

    Directory of Open Access Journals (Sweden)

    Nicolas Sommet

    2017-09-01

    Full Text Available This paper aims to introduce multilevel logistic regression analysis in a simple and practical way. First, we introduce the basic principles of logistic regression analysis (conditional probability, logit transformation, odds ratio. Second, we discuss the two fundamental implications of running this kind of analysis with a nested data structure: In multilevel logistic regression, the odds that the outcome variable equals one (rather than zero may vary from one cluster to another (i.e. the intercept may vary and the effect of a lower-level variable may also vary from one cluster to another (i.e. the slope may vary. Third and finally, we provide a simplified three-step “turnkey” procedure for multilevel logistic regression modeling: -Preliminary phase: Cluster- or grand-mean centering variables -Step #1: Running an empty model and calculating the intraclass correlation coefficient (ICC -Step #2: Running a constrained and an augmented intermediate model and performing a likelihood ratio test to determine whether considering the cluster-based variation of the effect of the lower-level variable improves the model fit -Step #3 Running a final model and interpreting the odds ratio and confidence intervals to determine whether data support your hypothesis Command syntax for Stata, R, Mplus, and SPSS are included. These steps will be applied to a study on Justin Bieber, because everybody likes Justin Bieber.1

  5. Logistic regression model for identification of right ventricular dysfunction in patients with acute pulmonary embolism by means of computed tomography

    International Nuclear Information System (INIS)

    Staskiewicz, Grzegorz; Czekajska-Chehab, Elżbieta; Uhlig, Sebastian; Przegalinski, Jerzy; Maciejewski, Ryszard; Drop, Andrzej

    2013-01-01

    Purpose: Diagnosis of right ventricular dysfunction in patients with acute pulmonary embolism (PE) is known to be associated with increased risk of mortality. The aim of the study was to calculate a logistic regression model for reliable identification of right ventricular dysfunction (RVD) in patients diagnosed with computed tomography pulmonary angiography. Material and methods: Ninety-seven consecutive patients with acute pulmonary embolism were divided into groups with and without RVD basing upon echocardiographic measurement of pulmonary artery systolic pressure (PASP). PE severity was graded with the pulmonary obstruction score. CT measurements of heart chambers and mediastinal vessels were performed; position of interventricular septum and presence of contrast reflux into the inferior vena cava were also recorded. The logistic regression model was prepared by means of stepwise logistic regression. Results: Among the used parameters, the final model consisted of pulmonary obstruction score, short axis diameter of right ventricle and diameter of inferior vena cava. The calculated model is characterized by 79% sensitivity and 81% specificity, and its performance was significantly better than single CT-based measurements. Conclusion: Logistic regression model identifies RVD significantly better, than single CT-based measurements

  6. Predictors of work injury in underground mines - an application of a logistic regression model

    Energy Technology Data Exchange (ETDEWEB)

    P.S. Paul [Indian School of Mines University, Dhanbad (India). Department of Mining Engineering

    2009-05-15

    Mine accidents and injuries are complex and generally characterized by several factors starting from personal to technical, and technical to social characteristics. In this study, an attempt has been made to identify the various factors responsible for work related injuries in mines and to estimate the risk of work injury to mine workers. The prediction of work injury in mines was done by a step-by-step multivariate logistic regression modeling with an application to case study mines in India. In total, 18 variables were considered in this study. Most of the variables are not directly quantifiable. Instruments were developed to quantify them through a questionnaire type survey. Underground mine workers were randomly selected for the survey. Responses from 300 participants were used for the analysis. Four variables, age, negative affectivity, job dissatisfaction, and physical hazards bear significant discriminating power for risk of injury to the workers, comparing between cases and controls in a multivariate situation while controlling all the personal and socio-technical variables. The analysis reveals that negatively affected workers are 2.54 times more prone to injuries than the less negatively affected workers and this factor is a more important risk factor for the case-study mines. Long term planning through identification of the negative individuals, proper counseling regarding the adverse effects of negative behaviors and special training is urgently required. Care should be taken for the aged and experienced workers in terms of their job responsibility and training requirements. Management should provide a friendly atmosphere during work to increase the confidence of the injury prone miners. 44 refs., 4 tabs.

  7. A Conceptual Model of Excellent Performance Mode of Port Enterprise Logistics Management

    Directory of Open Access Journals (Sweden)

    Jiang He

    2017-11-01

    Full Text Available Port as one of the key hubs of international logistics, which has become the main part and the base of global logistics management. The port enterprises, plays an important role in the global supply chain. However, due to the lack of understanding in port supply chain management, coordination between the port enterprises, the integration of business process is not perfect, the lack of information sharing between various organizations, ports enterprises usually failed to fully play its positive role. Based on this, the paper makes the port enterprises as the research object, and introduces the excellent performance mode into the port enterprises. In order to study the port enterprises how to carry out effective quality management, and formation the coordination and integration of upstream and downstream of enterprises, so as to realize the competitive advantage in port logistics.

  8. Tennis Elbow Diagnosis Using Equivalent Uniform Voltage to Fit the Logistic and the Probit Diseased Probability Models

    Directory of Open Access Journals (Sweden)

    Tsair-Fwu Lee

    2015-01-01

    Full Text Available To develop the logistic and the probit models to analyse electromyographic (EMG equivalent uniform voltage- (EUV- response for the tenderness of tennis elbow. In total, 78 hands from 39 subjects were enrolled. In this study, surface EMG (sEMG signal is obtained by an innovative device with electrodes over forearm region. The analytical endpoint was defined as Visual Analog Score (VAS 3+ tenderness of tennis elbow. The logistic and the probit diseased probability (DP models were established for the VAS score and EMG absolute voltage-time histograms (AVTH. TV50 is the threshold equivalent uniform voltage predicting a 50% risk of disease. Twenty-one out of 78 samples (27% developed VAS 3+ tenderness of tennis elbow reported by the subject and confirmed by the physician. The fitted DP parameters were TV50 = 153.0 mV (CI: 136.3–169.7 mV, γ50 = 0.84 (CI: 0.78–0.90 and TV50 = 155.6 mV (CI: 138.9–172.4 mV, m = 0.54 (CI: 0.49–0.59 for logistic and probit models, respectively. When the EUV ≥ 153 mV, the DP of the patient is greater than 50% and vice versa. The logistic and the probit models are valuable tools to predict the DP of VAS 3+ tenderness of tennis elbow.

  9. Tennis Elbow Diagnosis Using Equivalent Uniform Voltage to Fit the Logistic and the Probit Diseased Probability Models

    Science.gov (United States)

    Lin, Wei-Chun; Lin, Shu-Yuan; Wu, Li-Fu; Guo, Shih-Sian; Huang, Hsiang-Jui; Chao, Pei-Ju

    2015-01-01

    To develop the logistic and the probit models to analyse electromyographic (EMG) equivalent uniform voltage- (EUV-) response for the tenderness of tennis elbow. In total, 78 hands from 39 subjects were enrolled. In this study, surface EMG (sEMG) signal is obtained by an innovative device with electrodes over forearm region. The analytical endpoint was defined as Visual Analog Score (VAS) 3+ tenderness of tennis elbow. The logistic and the probit diseased probability (DP) models were established for the VAS score and EMG absolute voltage-time histograms (AVTH). TV50 is the threshold equivalent uniform voltage predicting a 50% risk of disease. Twenty-one out of 78 samples (27%) developed VAS 3+ tenderness of tennis elbow reported by the subject and confirmed by the physician. The fitted DP parameters were TV50 = 153.0 mV (CI: 136.3–169.7 mV), γ 50 = 0.84 (CI: 0.78–0.90) and TV50 = 155.6 mV (CI: 138.9–172.4 mV), m = 0.54 (CI: 0.49–0.59) for logistic and probit models, respectively. When the EUV ≥ 153 mV, the DP of the patient is greater than 50% and vice versa. The logistic and the probit models are valuable tools to predict the DP of VAS 3+ tenderness of tennis elbow. PMID:26380281

  10. Correction: Keep Calm and Learn Multilevel Logistic Modeling: A Simplified Three-Step Procedure Using Stata, R, Mplus, and SPSS

    Directory of Open Access Journals (Sweden)

    Nicolas Sommet

    2017-12-01

    Full Text Available This article details a correction to the article: Sommet, N. & Morselli, D., (2017. Keep Calm and Learn Multilevel Logistic Modeling: A Simplified Three-Step Procedure Using Stata, R, Mplus, and SPSS. 'International Review of Social Psychology'. 30(1, pp. 203–218. DOI: https://doi.org/10.5334/irsp.90

  11. Careful with Those Priors: A Note on Bayesian Estimation in Two-Parameter Logistic Item Response Theory Models

    Science.gov (United States)

    Marcoulides, Katerina M.

    2018-01-01

    This study examined the use of Bayesian analysis methods for the estimation of item parameters in a two-parameter logistic item response theory model. Using simulated data under various design conditions with both informative and non-informative priors, the parameter recovery of Bayesian analysis methods were examined. Overall results showed that…

  12. The Impact of Three Factors on the Recovery of Item Parameters for the Three-Parameter Logistic Model

    Science.gov (United States)

    Kim, Kyung Yong; Lee, Won-Chan

    2017-01-01

    This article provides a detailed description of three factors (specification of the ability distribution, numerical integration, and frame of reference for the item parameter estimates) that might affect the item parameter estimation of the three-parameter logistic model, and compares five item calibration methods, which are combinations of the…

  13. Multi-objective reverse logistics model for integrated computer waste management.

    Science.gov (United States)

    Ahluwalia, Poonam Khanijo; Nema, Arvind K

    2006-12-01

    This study aimed to address the issues involved in the planning and design of a computer waste management system in an integrated manner. A decision-support tool is presented for selecting an optimum configuration of computer waste management facilities (segregation, storage, treatment/processing, reuse/recycle and disposal) and allocation of waste to these facilities. The model is based on an integer linear programming method with the objectives of minimizing environmental risk as well as cost. The issue of uncertainty in the estimated waste quantities from multiple sources is addressed using the Monte Carlo simulation technique. An illustrated example of computer waste management in Delhi, India is presented to demonstrate the usefulness of the proposed model and to study tradeoffs between cost and risk. The results of the example problem show that it is possible to reduce the environmental risk significantly by a marginal increase in the available cost. The proposed model can serve as a powerful tool to address the environmental problems associated with exponentially growing quantities of computer waste which are presently being managed using rudimentary methods of reuse, recovery and disposal by various small-scale vendors.

  14. Understanding logistic regression analysis

    OpenAIRE

    Sperandei, Sandro

    2014-01-01

    Logistic regression is used to obtain odds ratio in the presence of more than one explanatory variable. The procedure is quite similar to multiple linear regression, with the exception that the response variable is binomial. The result is the impact of each variable on the odds ratio of the observed event of interest. The main advantage is to avoid confounding effects by analyzing the association of all variables together. In this article, we explain the logistic regression procedure using ex...

  15. APPLICATION OF METHODS OF LOGISTICS AND PROJECT MANAGEMENT FOR THE CONSTRUCTION OF MANAGEMENT MODEL OF BUSINESS PROCESSES IN THE NETWORK

    Directory of Open Access Journals (Sweden)

    Наталія Іванівна ЧУХРАЙ

    2016-02-01

    Full Text Available In terms of the dynamic development of network economy for effective decision-making managers of enterprises should be combined methods of logistics and project management to obtain the positive synergistic effect. It is shown that the basis of objective measures aimed at minimizing transaction costs. Solving this problem is associated with the development of the structural shell of business enterprises, which continue to evolve rapidly. Organization joint coordinated work in the same virtual information field together geographically separated users opens up entirely new possibilities for improving the mechanisms of project management and logistics. It was reviewed the evolution tool of business process and identified key business processes in networks. The analysis of support for business processes in logistics networks contains a list of basic management mechanisms. It was developed the model of economic and mathematical business process management in structural shell business. The semantic content of the objective function is to minimize transaction costs.

  16. An optimization model for sustainable solutions towards implementation of reverse logistics under collaborative framework

    DEFF Research Database (Denmark)

    Agarwal, Vernika; Govindan, Kannan; Darbari, Jyoti Dhingra

    2016-01-01

    Enforced Legislations, social image, corporate citizenship and market competence are forcing manufacturing enterprises (MEs) to incorporate reverse logistics (RL) into their supply chains. RL can be used as a strategic tool to gain customer loyalty and reduce operational costs by maximizing...

  17. Logistics Innovation Process Revisited

    DEFF Research Database (Denmark)

    Gammelgaard, Britta; Su, Shong-Iee Ivan; Yang, Su-Lan

    2011-01-01

    Purpose – The purpose of this paper is to learn more about logistics innovation processes and their implications for the focal organization as well as the supply chain, especially suppliers. Design/methodology/approach – The empirical basis of the study is a longitudinal action research project...... that was triggered by the practical needs of new ways of handling material flows of a hospital. This approach made it possible to revisit theory on logistics innovation process. Findings – Apart from the tangible benefits reported to the case hospital, five findings can be extracted from this study: the logistics...... innovation process model may include not just customers but also suppliers; logistics innovation in buyer-supplier relations may serve as an alternative to outsourcing; logistics innovation processes are dynamic and may improve supplier partnerships; logistics innovations in the supply chain are as dependent...

  18. The Bifurcation and Control of a Single-Species Fish Population Logistic Model with the Invasion of Alien Species

    OpenAIRE

    Zhang, Yi; Zhang, Qiaoling; Li, Jinghao; Zhang, Qingling

    2014-01-01

    The objective of this paper is to study systematically the bifurcation and control of a single-species fish population logistic model with the invasion of alien species based on the theory of singular system and bifurcation. It regards Spartina anglica as an invasive species, which invades the fisheries and aquaculture. Firstly, the stabilities of equilibria in this model are discussed. Moreover, the sufficient conditions for existence of the trans-critical bifurcation and the singularity ind...

  19. Pharmaceutical Logistics at the 121st General Hospital, Seoul, Korea

    National Research Council Canada - National Science Library

    Giraud, Roger S

    2004-01-01

    ...). The sample consists of 122 days of pharmaceutical requisitions. Pharmaceutical logistics data are used to estimate a multiple regression model of OST for demand satisfaction and accommodation, requisition cost and volume and source of supply...

  20. Design of an integrated forward and reverse logistics network optimi-zation model for commercial goods management

    Directory of Open Access Journals (Sweden)

    Eva Ponce-Cueto

    2015-01-01

    Full Text Available In this study, an optimization model is formulated for designing an integrated forward and reverse logistics network in the consumer goods industry. The resultant model is a mixed-integer linear programming model (MILP. Its purpose is to minimize the total costs of the closed-loop supply chain network. It is important to note that the design of the logistics network may involve a trade-off between the total costs and the optimality in commercial goods management. The model comprises a discrete set as potential locations of unlimited capacity warehouses and fixed locations of customers’ zones. It provides decisions related to the facility location and customers’ requirements satisfaction, all of this related with the inventory and shipment decisions of the supply chain. Finally, an application of this model is illustrated by a real-life case in the food and drinks industry. We can conclude that this model can significantly help companies to make decisions about problems associated with logistics network design.

  1. Logistics service management; differentiating the logistics service

    NARCIS (Netherlands)

    Veeken, van der D.J.M.; Rutten, W.G.M.M.

    1998-01-01

    In this article a model is described, which enables differentiation of the logistics service that a company offers to its customers. Differentiating this service is essential for businesses with a large variation within their customer and/or products portfolio. The model consists of four phases:

  2. An Optimization Model for Expired Drug Recycling Logistics Networks and Government Subsidy Policy Design Based on Tri-level Programming

    Directory of Open Access Journals (Sweden)

    Hui Huang

    2015-07-01

    Full Text Available In order to recycle and dispose of all people’s expired drugs, the government should design a subsidy policy to stimulate users to return their expired drugs, and drug-stores should take the responsibility of recycling expired drugs, in other words, to be recycling stations. For this purpose it is necessary for the government to select the right recycling stations and treatment stations to optimize the expired drug recycling logistics network and minimize the total costs of recycling and disposal. This paper establishes a tri-level programming model to study how the government can optimize an expired drug recycling logistics network and the appropriate subsidy policies. Furthermore, a Hybrid Genetic Simulated Annealing Algorithm (HGSAA is proposed to search for the optimal solution of the model. An experiment is discussed to illustrate the good quality of the recycling logistics network and government subsides obtained by the HGSAA. The HGSAA is proven to have the ability to converge on the global optimal solution, and to act as an effective algorithm for solving the optimization problem of expired drug recycling logistics network and government subsidies.

  3. An Optimization Model for Expired Drug Recycling Logistics Networks and Government Subsidy Policy Design Based on Tri-level Programming.

    Science.gov (United States)

    Huang, Hui; Li, Yuyu; Huang, Bo; Pi, Xing

    2015-07-09

    In order to recycle and dispose of all people's expired drugs, the government should design a subsidy policy to stimulate users to return their expired drugs, and drug-stores should take the responsibility of recycling expired drugs, in other words, to be recycling stations. For this purpose it is necessary for the government to select the right recycling stations and treatment stations to optimize the expired drug recycling logistics network and minimize the total costs of recycling and disposal. This paper establishes a tri-level programming model to study how the government can optimize an expired drug recycling logistics network and the appropriate subsidy policies. Furthermore, a Hybrid Genetic Simulated Annealing Algorithm (HGSAA) is proposed to search for the optimal solution of the model. An experiment is discussed to illustrate the good quality of the recycling logistics network and government subsides obtained by the HGSAA. The HGSAA is proven to have the ability to converge on the global optimal solution, and to act as an effective algorithm for solving the optimization problem of expired drug recycling logistics network and government subsidies.

  4. Mathematical modeling of project management in logistics systems based on two-dimensional random vector

    Science.gov (United States)

    Glushkova, Yu O.; Gordashnukova, O. Yu; Pahomova, A. V.; Shatohina, S. P.; Filippov, D. V.

    2018-05-01

    The modern markets are characterized by fierce competition, constantly changing demand, increasing demands of consumers, shortening of the life cycle of goods and services in connection with scientific and technological progress. Therefore, for survival, modern logistic systems of industrial enterprises must be constantly improved. Modern economic literature is represented by a large volume of publications on various aspects of the studied issues. They consider the issues of project management in the logistics system that inevitably encounter with triple Limited. It initially describes the balance between project content, cost, and time. Later it was suggested to either replace the content with quality or add a fourth criterion. Therefore it is possible to name such limitation as triple or four-criteria limitation.

  5. An integrated decision making model for the selection of sustainable forward and reverse logistic providers

    DEFF Research Database (Denmark)

    Govindan, Kannan; Agarwal, Vernika; Darbari, Jyoti Dhingra

    2017-01-01

    Due to rising concerns for environmental sustainability, the Indian electronic industry faces immense pressure to incorporate effective sustainable practices into the supply chain (SC) planning. Consequently, manufacturing enterprises (ME) are exploring the option of re-examining their SC...... strategies and taking a formalized approach towards a sustainable partnership with logistics providers. To begin with, it is imperative to associate with sustainable forward and reverse logistics providers to manage effectively the upward and downstream flows simultaneously. In this context, this paper...... improve the sustainable performance value of the SC network and secure reasonable profits. The managerial implications drawn from the result analysis provide a sustainable framework to the ME for enhancing its corporate image....

  6. Application of Multiple Evaluation Models in Brazil

    Directory of Open Access Journals (Sweden)

    Rafael Victal Saliba

    2008-07-01

    Full Text Available Based on two different samples, this article tests the performance of a number of Value Drivers commonly used for evaluating companies by finance practitioners, through simple regression models of cross-section type which estimate the parameters associated to each Value Driver, denominated Market Multiples. We are able to diagnose the behavior of several multiples in the period 1994-2004, with an outlook also on the particularities of the economic activities performed by the sample companies (and their impacts on the performance through a subsequent analysis with segregation of companies in the sample by sectors. Extrapolating simple multiples evaluation standards from analysts of the main financial institutions in Brazil, we find that adjusting the ratio formulation to allow for an intercept does not provide satisfactory results in terms of pricing errors reduction. Results found, in spite of evidencing certain relative and absolute superiority among the multiples, may not be generically representative, given samples limitation.

  7. The reliable solution and computation time of variable parameters logistic model

    Science.gov (United States)

    Wang, Pengfei; Pan, Xinnong

    2018-05-01

    The study investigates the reliable computation time (RCT, termed as T c) by applying a double-precision computation of a variable parameters logistic map (VPLM). Firstly, by using the proposed method, we obtain the reliable solutions for the logistic map. Secondly, we construct 10,000 samples of reliable experiments from a time-dependent non-stationary parameters VPLM and then calculate the mean T c. The results indicate that, for each different initial value, the T cs of the VPLM are generally different. However, the mean T c trends to a constant value when the sample number is large enough. The maximum, minimum, and probable distribution functions of T c are also obtained, which can help us to identify the robustness of applying a nonlinear time series theory to forecasting by using the VPLM output. In addition, the T c of the fixed parameter experiments of the logistic map is obtained, and the results suggest that this T c matches the theoretical formula-predicted value.

  8. Applied logistic regression

    CERN Document Server

    Hosmer, David W; Sturdivant, Rodney X

    2013-01-01

     A new edition of the definitive guide to logistic regression modeling for health science and other applications This thoroughly expanded Third Edition provides an easily accessible introduction to the logistic regression (LR) model and highlights the power of this model by examining the relationship between a dichotomous outcome and a set of covariables. Applied Logistic Regression, Third Edition emphasizes applications in the health sciences and handpicks topics that best suit the use of modern statistical software. The book provides readers with state-of-

  9. The spatial prediction of landslide susceptibility applying artificial neural network and logistic regression models: A case study of Inje, Korea

    Science.gov (United States)

    Saro, Lee; Woo, Jeon Seong; Kwan-Young, Oh; Moung-Jin, Lee

    2016-02-01

    The aim of this study is to predict landslide susceptibility caused using the spatial analysis by the application of a statistical methodology based on the GIS. Logistic regression models along with artificial neutral network were applied and validated to analyze landslide susceptibility in Inje, Korea. Landslide occurrence area in the study were identified based on interpretations of optical remote sensing data (Aerial photographs) followed by field surveys. A spatial database considering forest, geophysical, soil and topographic data, was built on the study area using the Geographical Information System (GIS). These factors were analysed using artificial neural network (ANN) and logistic regression models to generate a landslide susceptibility map. The study validates the landslide susceptibility map by comparing them with landslide occurrence areas. The locations of landslide occurrence were divided randomly into a training set (50%) and a test set (50%). A training set analyse the landslide susceptibility map using the artificial network along with logistic regression models, and a test set was retained to validate the prediction map. The validation results revealed that the artificial neural network model (with an accuracy of 80.10%) was better at predicting landslides than the logistic regression model (with an accuracy of 77.05%). Of the weights used in the artificial neural network model, `slope' yielded the highest weight value (1.330), and `aspect' yielded the lowest value (1.000). This research applied two statistical analysis methods in a GIS and compared their results. Based on the findings, we were able to derive a more effective method for analyzing landslide susceptibility.

  10. The spatial prediction of landslide susceptibility applying artificial neural network and logistic regression models: A case study of Inje, Korea

    Directory of Open Access Journals (Sweden)

    Saro Lee

    2016-02-01

    Full Text Available The aim of this study is to predict landslide susceptibility caused using the spatial analysis by the application of a statistical methodology based on the GIS. Logistic regression models along with artificial neutral network were applied and validated to analyze landslide susceptibility in Inje, Korea. Landslide occurrence area in the study were identified based on interpretations of optical remote sensing data (Aerial photographs followed by field surveys. A spatial database considering forest, geophysical, soil and topographic data, was built on the study area using the Geographical Information System (GIS. These factors were analysed using artificial neural network (ANN and logistic regression models to generate a landslide susceptibility map. The study validates the landslide susceptibility map by comparing them with landslide occurrence areas. The locations of landslide occurrence were divided randomly into a training set (50% and a test set (50%. A training set analyse the landslide susceptibility map using the artificial network along with logistic regression models, and a test set was retained to validate the prediction map. The validation results revealed that the artificial neural network model (with an accuracy of 80.10% was better at predicting landslides than the logistic regression model (with an accuracy of 77.05%. Of the weights used in the artificial neural network model, ‘slope’ yielded the highest weight value (1.330, and ‘aspect’ yielded the lowest value (1.000. This research applied two statistical analysis methods in a GIS and compared their results. Based on the findings, we were able to derive a more effective method for analyzing landslide susceptibility.

  11. Relative efficiency of joint-model and full-conditional-specification multiple imputation when conditional models are compatible: The general location model.

    Science.gov (United States)

    Seaman, Shaun R; Hughes, Rachael A

    2018-06-01

    Estimating the parameters of a regression model of interest is complicated by missing data on the variables in that model. Multiple imputation is commonly used to handle these missing data. Joint model multiple imputation and full-conditional specification multiple imputation are known to yield imputed data with the same asymptotic distribution when the conditional models of full-conditional specification are compatible with that joint model. We show that this asymptotic equivalence of imputation distributions does not imply that joint model multiple imputation and full-conditional specification multiple imputation will also yield asymptotically equally efficient inference about the parameters of the model of interest, nor that they will be equally robust to misspecification of the joint model. When the conditional models used by full-conditional specification multiple imputation are linear, logistic and multinomial regressions, these are compatible with a restricted general location joint model. We show that multiple imputation using the restricted general location joint model can be substantially more asymptotically efficient than full-conditional specification multiple imputation, but this typically requires very strong associations between variables. When associations are weaker, the efficiency gain is small. Moreover, full-conditional specification multiple imputation is shown to be potentially much more robust than joint model multiple imputation using the restricted general location model to mispecification of that model when there is substantial missingness in the outcome variable.

  12. SIMULATION OF LOGISTICS PROCESSES

    Directory of Open Access Journals (Sweden)

    Yu. Taranenko

    2016-08-01

    Full Text Available The article deals with the theoretical basis of the simulation. The study shows the simulation of logistic processes in industrial countries is an integral part of many economic projects aimed at the creation or improvement of logistics systems. The paper was used model Beer Game for management of logistics processes in the enterprise. The simulation model implements in AnyLogic package. AnyLogic product allows us to consider the logistics processes as an integrated system, which allows reaching better solutions. Logistics process management involves pooling the sales market, production and distribution to ensure the temporal level of customer service at the lowest cost overall. This made it possible to conduct experiments and to determine the optimal size of the warehouse at the lowest cost.

  13. LOGISTICS - EVOLUTION THROUGH INNOVATION

    Directory of Open Access Journals (Sweden)

    Petrache Alexandru Constantin

    2015-07-01

    Full Text Available The current economic conditions, the rapidity with which the exchange of information, resources and products in the market takes place makes the logistics seem appreciably less significant. However, the importance of logistics has been presented in the military field, through strategies that have led to wining of the great wars that mankind has seen, through the supply of troops with food or moving military equipment. The literature in the field of logistics has numerous works on this topic. But while most focuses on efficient ways of carrying out the component activities of logistics or the strategies of organizations with regard to logistics or its functions, research on dynamics of logistics is underdeveloped. To be able to propose new methods or strategies of logistic activities is necessary to understand the development of this concept, determinant factors and economic and social conditions that gave rise to such developments. Thus, after a presentation of the main landmarks of the historical development of logistics we highlight the importance of the innovation within an organization's value chain innovation, in particular, and how to conduct the business in general. Using generations of innovation identified in the literature, we determine the generation of logistics development, taking into account innovation and how to conduct business. In addition for a better highlight of the own vision over the logistics generations identified, we will present the graphical concept for each generation in part. Last but not least, for each generation identified we try to allocate the chronological landmarks featured in order to reinforce the importance played by innovation in the development of the logistics industry and to give future directions of research within this topic. The study took into account the information presented in articles, books and websites of the relevant specialty in logistics and innovation to be able to build and expose a

  14. Proposition of a modeling and an analysis methodology of integrated reverse logistics chain in the direct chain

    Energy Technology Data Exchange (ETDEWEB)

    Mimouni, F.; Abouabdellah, A.

    2016-07-01

    Propose a modeling and analysis methodology based on the combination of Bayesian networks and Petri networks of the reverse logistics integrated the direct supply chain. Network modeling by combining Petri and Bayesian network. Modeling with Bayesian network complimented with Petri network to break the cycle problem in the Bayesian network. Demands are independent from returns. Model can only be used on nonperishable products. Legislation aspects: Recycling laws; Protection of environment; Client satisfaction via after sale service. Bayesian network with a cycle combined with the Petri Network. (Author)

  15. Proposition of a modeling and an analysis methodology of integrated reverse logistics chain in the direct chain

    Directory of Open Access Journals (Sweden)

    Faycal Mimouni

    2016-04-01

    Full Text Available Purpose: Propose a modeling and analysis methodology based on the combination of Bayesian networks and Petri networks of the reverse logistics integrated the direct supply chain. Design/methodology/approach: Network modeling by combining Petri and Bayesian network. Findings: Modeling with Bayesian network complimented with Petri network to break the cycle problem in the Bayesian network. Research limitations/implications: Demands are independent from returns. Practical implications: Model can only be used on nonperishable products. Social implications: Legislation aspects: Recycling laws; Protection of environment; Client satisfaction via after sale service. Originality/value: Bayesian network with a cycle combined with the Petri Network.

  16. The Modeling of Logistics and Coordination of the Rate of Commodities Production with the Rate of their Disposal

    Directory of Open Access Journals (Sweden)

    Sherstennykov Yuriy V.

    2016-08-01

    Full Text Available The economic objective of the modern high-tech enterprise is the optimal expansion of its own market niche and bringing the production capacities in accordance with the current demand for the products. An important role in this respect is played by issues of optimal organization of the enterprise logistics, marketing analysis of the current demand and effective advertising campaign aimed at maximal use of the available production capacity and creation of proper conditions for developing, in particular for increasing the production capacities. The purpose of the article is the elaboration of economic and mathematical models of enterprise production activity taking into account the logistics and market demand; the use of the elaborated model to harmonize the rate of production of everyday commodities with the rate of their disposal. Two variants of the enterprise logistics schemes are analyzed. The influence of the advertising company on expanding the enterprise market niche is studied. A model that allows conducting a detailed study of the influence of market conditions on the pace of sales has been developed. It is appropriate to apply the model for the integrated coordination of the production rate of commodities of everyday demand with the dynamics of flows of commodities and services disposal.

  17. Multiple model adaptive control with mixing

    Science.gov (United States)

    Kuipers, Matthew

    Despite the remarkable theoretical accomplishments and successful applications of adaptive control, the field is not sufficiently mature to solve challenging control problems requiring strict performance and safety guarantees. Towards addressing these issues, a novel deterministic multiple-model adaptive control approach called adaptive mixing control is proposed. In this approach, adaptation comes from a high-level system called the supervisor that mixes into feedback a number of candidate controllers, each finely-tuned to a subset of the parameter space. The mixing signal, the supervisor's output, is generated by estimating the unknown parameters and, at every instant of time, calculating the contribution level of each candidate controller based on certainty equivalence. The proposed architecture provides two characteristics relevant to solving stringent, performance-driven applications. First, the full-suite of linear time invariant control tools is available. A disadvantage of conventional adaptive control is its restriction to utilizing only those control laws whose solutions can be feasibly computed in real-time, such as model reference and pole-placement type controllers. Because its candidate controllers are computed off line, the proposed approach suffers no such restriction. Second, the supervisor's output is smooth and does not necessarily depend on explicit a priori knowledge of the disturbance model. These characteristics can lead to improved performance by avoiding the unnecessary switching and chattering behaviors associated with some other multiple adaptive control approaches. The stability and robustness properties of the adaptive scheme are analyzed. It is shown that the mean-square regulation error is of the order of the modeling error. And when the parameter estimate converges to its true value, which is guaranteed if a persistence of excitation condition is satisfied, the adaptive closed-loop system converges exponentially fast to a closed

  18. Building of Reusable Reverse Logistics Model and its Optimization Considering the Decision of Backorder or Next Arrival of Goods

    Science.gov (United States)

    Lee, Jeong-Eun; Gen, Mitsuo; Rhee, Kyong-Gu; Lee, Hee-Hyol

    This paper deals with the building of the reusable reverse logistics model considering the decision of the backorder or the next arrival of goods. The optimization method to minimize the transportation cost and to minimize the volume of the backorder or the next arrival of goods occurred by the Just in Time delivery of the final delivery stage between the manufacturer and the processing center is proposed. Through the optimization algorithms using the priority-based genetic algorithm and the hybrid genetic algorithm, the sub-optimal delivery routes are determined. Based on the case study of a distilling and sale company in Busan in Korea, the new model of the reusable reverse logistics of empty bottles is built and the effectiveness of the proposed method is verified.

  19. Multinomial logistic models explaining income changes of migrants to high-amenity counties.

    Science.gov (United States)

    Von Reichert, C; Rudzitis, G

    1992-01-01

    "A survey of residents of and migrants to 15 fast-growing wilderness counties [in the United States] showed that only 25 percent of the migrants increased their income, while almost 50 percent accepted income losses upon their moves to high-amenity counties. Concomitantly, amenities and quality of life were more important factors in the migration decision than was employment, for instance. We focused on migrants in the labor force and employed multinomial logistic regression to identify the impact of migrants' characteristics, their satisfaction/dissatisfaction with previous location (push), and the importance of destination features (pull) on income change." excerpt

  20. Systemic Thinking and Requisite Holism in Mastering Logistics Risks: the Model for Identifying Risks in Organisations and Supply Chain

    OpenAIRE

    Borut Jereb; Teodora Ivanuša; Bojan Rosi

    2013-01-01

    Risks in logistic processes represent one of the major issues in supply chain management nowadays. Every organization strives for success, and uninterrupted operations are the key factors in achieving this goal, which cannot be achieved without efficient risk management. In the scope of supply chain risk research, we identified some key issues in the field, the major issue being the lack of standardization and models, which can make risk management in an organization easier and more efficient...

  1. Periodic and chaotic events in a discrete model of logistic type for the competitive interaction of two species

    International Nuclear Information System (INIS)

    Lopez-Ruiz, Ricardo; Fournier-Prunaret, Daniele

    2009-01-01

    Two symmetrically coupled logistic equations are proposed to mimic the competitive interaction between two species. The phenomena of coexistence, oscillations and chaos are present in this cubic discrete system. This work, together with two other similar ones recently published by the authors, completes a triptych dedicated to the two species relationships present in Nature, namely the symbiosis, the predator-prey and the competition. These models can be used as basic ingredients to build up more complex interactions in the ecological networks.

  2. The Relationships Among Leadership, Entrepreneurial Mindset, Innovation and Competitive Advantage (a Conceptual Model of Logistics Service Industry)

    OpenAIRE

    Sudrajat, Darjat

    2015-01-01

    Nowadays, improvement of competitive advantage is an important and urgent issue facing logistics service companies in Indonesia. Some previous researches showed that to improve the competitive advantage could be conducted through improvement of leadership, entrepreneurial mindset and innovation variables. This research intended to recognize relationships among the variables. The research used causal-explanatory method. The results of research encompass a conceptual model, status of each varia...

  3. Comparing Johnson’s SBB, Weibull and Logit-Logistic bivariate distributions for modeling tree diameters and heights using copulas

    Energy Technology Data Exchange (ETDEWEB)

    Cardil Forradellas, A.; Molina Terrén, D.M.; Oliveres, J.; Castellnou, M.

    2016-07-01

    Aim of study: In this study we compare the accuracy of three bivariate distributions: Johnson’s SBB, Weibull-2P and LL-2P functions for characterizing the joint distribution of tree diameters and heights. Area of study: North-West of Spain. Material and methods: Diameter and height measurements of 128 plots of pure and even-aged Tasmanian blue gum (Eucalyptus globulus Labill.) stands located in the North-west of Spain were considered in the present study. The SBB bivariate distribution was obtained from SB marginal distributions using a Normal Copula based on a four-parameter logistic transformation. The Plackett Copula was used to obtain the bivariate models from the Weibull and Logit-logistic univariate marginal distributions. The negative logarithm of the maximum likelihood function was used to compare the results and the Wilcoxon signed-rank test was used to compare the related samples of these logarithms calculated for each sample plot and each distribution. Main results: The best results were obtained by using the Plackett copula and the best marginal distribution was the Logit-logistic. Research highlights: The copulas used in this study have shown a good performance for modeling the joint distribution of tree diameters and heights. They could be easily extended for modelling multivariate distributions involving other tree variables, such as tree volume or biomass. (Author)

  4. Resolution of an uncertain closed-loop logistics model: an application to fuzzy linear programs with risk analysis.

    Science.gov (United States)

    Wang, Hsiao-Fan; Hsu, Hsin-Wei

    2010-11-01

    With the urgency of global warming, green supply chain management, logistics in particular, has drawn the attention of researchers. Although there are closed-loop green logistics models in the literature, most of them do not consider the uncertain environment in general terms. In this study, a generalized model is proposed where the uncertainty is expressed by fuzzy numbers. An interval programming model is proposed by the defined means and mean square imprecision index obtained from the integrated information of all the level cuts of fuzzy numbers. The resolution for interval programming is based on the decision maker (DM)'s preference. The resulting solution provides useful information on the expected solutions under a confidence level containing a degree of risk. The results suggest that the more optimistic the DM is, the better is the resulting solution. However, a higher risk of violation of the resource constraints is also present. By defining this probable risk, a solution procedure was developed with numerical illustrations. This provides a DM trade-off mechanism between logistic cost and the risk. Copyright 2010 Elsevier Ltd. All rights reserved.

  5. Predicting Factors of INSURE Failure in Low Birth Weight Neonates with RDS; A Logistic Regression Model

    Directory of Open Access Journals (Sweden)

    Bita Najafian

    2015-02-01

    Full Text Available Background:Respiratory Distress syndrome is the most common respiratory disease in premature neonate and the most important cause of death among them. We aimed to investigate factors to predict successful or failure of INSURE method as a therapeutic method of RDS.Methods:In a cohort study,45 neonates with diagnosed RDS and birth weight lower than 1500g were included and they underwent INSURE followed by NCPAP(Nasal Continuous Positive Airway Pressure. The patients were divided into failure or successful groups and factors which can predict success of INSURE were investigated by logistic regression in SPSS 16th version.Results:29 and16 neonates were observed in successful and failure groups, respectively. Birth weight was the only variable with significant difference between two groups (P=0.002. Finally logistic regression test showed that birth weight is only predicting factor for success (P: 0.001, EXP[β]: 0.009, CI [95%]: 1.003-0.014 and mortality (P: 0.029, EXP[β]: 0.993, CI [95%]: 0.987-0.999 of neonates treated with INSURE method.Conclusion:Predicting factors which affect on success rate of INSURE can be useful for treating and reducing charge of neonate with RDS and the birth weight is one of the effective factor on INSURE Success in this study.

  6. Predicting Factors of INSURE Failure in Low Birth Weight Neonates with RDS; A Logistic Regression Model

    Directory of Open Access Journals (Sweden)

    Bita Najafian

    2015-02-01

    Full Text Available Background:Respiratory Distress syndrome is the most common respiratory disease in premature neonate and the most important cause of death among them. We aimed to investigate factors to predict successful or failure of INSURE method as a therapeutic method of RDS. Methods:In a cohort study,45 neonates with diagnosed RDS and birth weight lower than 1500g were included and they underwent INSURE followed by NCPAP(Nasal Continuous Positive Airway Pressure. The patients were divided into failure or successful groups and factors which can predict success of INSURE were investigated by logistic regression in SPSS 16th version. Results:29 and16 neonates were observed in successful and failure groups, respectively. Birth weight was the only variable with significant difference between two groups (P=0.002. Finally logistic regression test showed that birth weight is only predicting factor for success (P: 0.001, EXP[β]: 0.009, CI [95%]: 1.003-0.014 and mortality (P: 0.029, EXP[β]: 0.993, CI [95%]: 0.987-0.999 of neonates treated with INSURE method. Conclusion:Predicting factors which affect on success rate of INSURE can be useful for treating and reducing charge of neonate with RDS and the birth weight is one of the effective factor on INSURE Success in this study.

  7. Evaluation of logistic regression models and effect of covariates for case-control study in RNA-Seq analysis.

    Science.gov (United States)

    Choi, Seung Hoan; Labadorf, Adam T; Myers, Richard H; Lunetta, Kathryn L; Dupuis, Josée; DeStefano, Anita L

    2017-02-06

    Next generation sequencing provides a count of RNA molecules in the form of short reads, yielding discrete, often highly non-normally distributed gene expression measurements. Although Negative Binomial (NB) regression has been generally accepted in the analysis of RNA sequencing (RNA-Seq) data, its appropriateness has not been exhaustively evaluated. We explore logistic regression as an alternative method for RNA-Seq studies designed to compare cases and controls, where disease status is modeled as a function of RNA-Seq reads using simulated and Huntington disease data. We evaluate the effect of adjusting for covariates that have an unknown relationship with gene expression. Finally, we incorporate the data adaptive method in order to compare false positive rates. When the sample size is small or the expression levels of a gene are highly dispersed, the NB regression shows inflated Type-I error rates but the Classical logistic and Bayes logistic (BL) regressions are conservative. Firth's logistic (FL) regression performs well or is slightly conservative. Large sample size and low dispersion generally make Type-I error rates of all methods close to nominal alpha levels of 0.05 and 0.01. However, Type-I error rates are controlled after applying the data adaptive method. The NB, BL, and FL regressions gain increased power with large sample size, large log2 fold-change, and low dispersion. The FL regression has comparable power to NB regression. We conclude that implementing the data adaptive method appropriately controls Type-I error rates in RNA-Seq analysis. Firth's logistic regression provides a concise statistical inference process and reduces spurious associations from inaccurately estimated dispersion parameters in the negative binomial framework.

  8. A Logistic Regression Model with a Hierarchical Random Error Term for Analyzing the Utilization of Public Transport

    Directory of Open Access Journals (Sweden)

    Chong Wei

    2015-01-01

    Full Text Available Logistic regression models have been widely used in previous studies to analyze public transport utilization. These studies have shown travel time to be an indispensable variable for such analysis and usually consider it to be a deterministic variable. This formulation does not allow us to capture travelers’ perception error regarding travel time, and recent studies have indicated that this error can have a significant effect on modal choice behavior. In this study, we propose a logistic regression model with a hierarchical random error term. The proposed model adds a new random error term for the travel time variable. This term structure enables us to investigate travelers’ perception error regarding travel time from a given choice behavior dataset. We also propose an extended model that allows constraining the sign of this error in the model. We develop two Gibbs samplers to estimate the basic hierarchical model and the extended model. The performance of the proposed models is examined using a well-known dataset.

  9. Influential factors of red-light running at signalized intersection and prediction using a rare events logistic regression model.

    Science.gov (United States)

    Ren, Yilong; Wang, Yunpeng; Wu, Xinkai; Yu, Guizhen; Ding, Chuan

    2016-10-01

    Red light running (RLR) has become a major safety concern at signalized intersection. To prevent RLR related crashes, it is critical to identify the factors that significantly impact the drivers' behaviors of RLR, and to predict potential RLR in real time. In this research, 9-month's RLR events extracted from high-resolution traffic data collected by loop detectors from three signalized intersections were applied to identify the factors that significantly affect RLR behaviors. The data analysis indicated that occupancy time, time gap, used yellow time, time left to yellow start, whether the preceding vehicle runs through the intersection during yellow, and whether there is a vehicle passing through the intersection on the adjacent lane were significantly factors for RLR behaviors. Furthermore, due to the rare events nature of RLR, a modified rare events logistic regression model was developed for RLR prediction. The rare events logistic regression method has been applied in many fields for rare events studies and shows impressive performance, but so far none of previous research has applied this method to study RLR. The results showed that the rare events logistic regression model performed significantly better than the standard logistic regression model. More importantly, the proposed RLR prediction method is purely based on loop detector data collected from a single advance loop detector located 400 feet away from stop-bar. This brings great potential for future field applications of the proposed method since loops have been widely implemented in many intersections and can collect data in real time. This research is expected to contribute to the improvement of intersection safety significantly. Copyright © 2016 Elsevier Ltd. All rights reserved.

  10. Measuring efficiency in logistics

    Directory of Open Access Journals (Sweden)

    Milan Milovan Andrejić

    2013-06-01

    Full Text Available Dynamic market and environmental changes greatly affect operating of logistics systems. Logistics systems have to realize their activities and processes in an efficient way. The main objective of this paper is to analyze different aspects of efficiency measurement in logistics and to propose appropriate models of measurement. Measuring efficiency in logistics is a complex process that requires consideration of all subsystems, processes and activities as well as the impact of various financial, operational, environmental, quality and other factors. The proposed models have a basis in the Data Envelopment Analysis method. They could help managers in decision making and corrective actions processes. The tests and results of the model show the importance of input and output variables selection.

  11. Study on Maritime Logistics Warehousing Center Model and Precision Marketing Strategy Optimization Based on Fuzzy Method and Neural Network Model

    OpenAIRE

    Xiao Kefeng; Hu Xiaolan

    2017-01-01

    The bulk commodity, different with the retail goods, has a uniqueness in the location selection, the chosen of transportation program and the decision objectives. How to make optimal decisions in the facility location, requirement distribution, shipping methods and the route selection and establish an effective distribution system to reduce the cost has become a burning issue for the e-commerce logistics, which is worthy to be deeply and systematically solved. In this paper, Logistics warehou...

  12. Modified generalized method of moments for a robust estimation of polytomous logistic model

    Directory of Open Access Journals (Sweden)

    Xiaoshan Wang

    2014-07-01

    Full Text Available The maximum likelihood estimation (MLE method, typically used for polytomous logistic regression, is prone to bias due to both misclassification in outcome and contamination in the design matrix. Hence, robust estimators are needed. In this study, we propose such a method for nominal response data with continuous covariates. A generalized method of weighted moments (GMWM approach is developed for dealing with contaminated polytomous response data. In this approach, distances are calculated based on individual sample moments. And Huber weights are applied to those observations with large distances. Mellow-type weights are also used to downplay leverage points. We describe theoretical properties of the proposed approach. Simulations suggest that the GMWM performs very well in correcting contamination-caused biases. An empirical application of the GMWM estimator on data from a survey demonstrates its usefulness.

  13. Model Pembelajaran Berbasis Penstimulasian Multiple Intelligences Siswa

    OpenAIRE

    Edy Legowo

    2017-01-01

    Tulisan ini membahas mengenai penerapan teori multiple intelligences dalam pembelajaran di sekolah. Pembahasan diawali dengan menguraikan perkembangan konsep inteligensi dan multiple intelligences. Diikuti dengan menjelaskan dampak teori multiple intelligences dalam bidang pendidikan dan pembelajaran di sekolah. Bagian selanjutnya menguraikan tentang implementasi teori multiple intelligences dalam praktik pembelajaran di kelas yaitu bagaimana pemberian pengalaman belajar siswa yang difasilita...

  14. Logistics model for the optimization of class III supplies (fuels, grease and lubricants of the National Navy

    Directory of Open Access Journals (Sweden)

    Giver Mora García

    2018-05-01

    Full Text Available The objective of this research was to propose a more sophisticated tool than the current logistic model provides to the needs of the National Navy, through a methodological analysis of internal and external factors (Eyring, 1970, its simulation in a specialized platform, its schematization and identification of the causes that led to its development; all of the above in order to promote through a restructuring, the basis for a process that satisfies the need for optimum form and constant innovation. The proposed model was developed through the application of public procurement tolos (Colombian Congress, 1993 and institutional management and technological innovation procedures (Presidencia de la Republica, 2015.

  15. The Relationships among Leadership, Entrepreneurial Mindset, Innovation and Competitive Advantage (A Conceptual Model of Logistics Service Industry

    Directory of Open Access Journals (Sweden)

    Darjat Sudrajat

    2015-11-01

    Full Text Available Nowadays, improvement of competitive advantage is an important and urgent issue facing logistics service companies in Indonesia. Some previous researches showed that to improve the competitive advantage could be conducted through improvement of leadership, entrepreneurial mindset and innovation variables. This research intended to recognize relationships among the variables. The research used causal-explanatory method. The results of research encompass a conceptual model, status of each variable and hypotheses. The conceptual model could be further verified through verification research. 

  16. Understanding logistic regression analysis.

    Science.gov (United States)

    Sperandei, Sandro

    2014-01-01

    Logistic regression is used to obtain odds ratio in the presence of more than one explanatory variable. The procedure is quite similar to multiple linear regression, with the exception that the response variable is binomial. The result is the impact of each variable on the odds ratio of the observed event of interest. The main advantage is to avoid confounding effects by analyzing the association of all variables together. In this article, we explain the logistic regression procedure using examples to make it as simple as possible. After definition of the technique, the basic interpretation of the results is highlighted and then some special issues are discussed.

  17. Numerical solution of a logistic growth model for a population with Allee effect considering fuzzy initial values and fuzzy parameters

    Science.gov (United States)

    Amarti, Z.; Nurkholipah, N. S.; Anggriani, N.; Supriatna, A. K.

    2018-03-01

    Predicting the future of population number is among the important factors that affect the consideration in preparing a good management for the population. This has been done by various known method, one among them is by developing a mathematical model describing the growth of the population. The model usually takes form in a differential equation or a system of differential equations, depending on the complexity of the underlying properties of the population. The most widely used growth models currently are those having a sigmoid solution of time series, including the Verhulst logistic equation and the Gompertz equation. In this paper we consider the Allee effect of the Verhulst’s logistic population model. The Allee effect is a phenomenon in biology showing a high correlation between population size or density and the mean individual fitness of the population. The method used to derive the solution is the Runge-Kutta numerical scheme, since it is in general regarded as one among the good numerical scheme which is relatively easy to implement. Further exploration is done via the fuzzy theoretical approach to accommodate the impreciseness of the initial values and parameters in the model.

  18. Model Pembelajaran Berbasis Penstimulasian Multiple Intelligences Siswa

    Directory of Open Access Journals (Sweden)

    Edy Legowo

    2017-03-01

    Full Text Available Tulisan ini membahas mengenai penerapan teori multiple intelligences dalam pembelajaran di sekolah. Pembahasan diawali dengan menguraikan perkembangan konsep inteligensi dan multiple intelligences. Diikuti dengan menjelaskan dampak teori multiple intelligences dalam bidang pendidikan dan pembelajaran di sekolah. Bagian selanjutnya menguraikan tentang implementasi teori multiple intelligences dalam praktik pembelajaran di kelas yaitu bagaimana pemberian pengalaman belajar siswa yang difasilitasi guru dapat menstimulasi multiple intelligences siswa. Evaluasi hasil belajar siswa dari pandangan penerapan teori multiple intelligences seharusnya dilakukan menggunakan authentic assessment dan portofolio yang lebih memfasilitasi para siswa mengungkapkan atau mengaktualisasikan hasil belajarnya melalui berbagai cara sesuai dengan kekuatan jenis inteligensinya.

  19. Transmission Risks of Schistosomiasis Japonica: Extraction from Back-propagation Artificial Neural Network and Logistic Regression Model

    Science.gov (United States)

    Xu, Jun-Fang; Xu, Jing; Li, Shi-Zhu; Jia, Tia-Wu; Huang, Xi-Bao; Zhang, Hua-Ming; Chen, Mei; Yang, Guo-Jing; Gao, Shu-Jing; Wang, Qing-Yun; Zhou, Xiao-Nong

    2013-01-01

    Background The transmission of schistosomiasis japonica in a local setting is still poorly understood in the lake regions of the People's Republic of China (P. R. China), and its transmission patterns are closely related to human, social and economic factors. Methodology/Principal Findings We aimed to apply the integrated approach of artificial neural network (ANN) and logistic regression model in assessment of transmission risks of Schistosoma japonicum with epidemiological data collected from 2339 villagers from 1247 households in six villages of Jiangling County, P.R. China. By using the back-propagation (BP) of the ANN model, 16 factors out of 27 factors were screened, and the top five factors ranked by the absolute value of mean impact value (MIV) were mainly related to human behavior, i.e. integration of water contact history and infection history, family with past infection, history of water contact, infection history, and infection times. The top five factors screened by the logistic regression model were mainly related to the social economics, i.e. village level, economic conditions of family, age group, education level, and infection times. The risk of human infection with S. japonicum is higher in the population who are at age 15 or younger, or with lower education, or with the higher infection rate of the village, or with poor family, and in the population with more than one time to be infected. Conclusion/Significance Both BP artificial neural network and logistic regression model established in a small scale suggested that individual behavior and socioeconomic status are the most important risk factors in the transmission of schistosomiasis japonica. It was reviewed that the young population (≤15) in higher-risk areas was the main target to be intervened for the disease transmission control. PMID:23556015

  20. A logistic regression approach to model the willingness of consumers to adopt renewable energy sources

    Science.gov (United States)

    Ulkhaq, M. M.; Widodo, A. K.; Yulianto, M. F. A.; Widhiyaningrum; Mustikasari, A.; Akshinta, P. Y.

    2018-03-01

    The implementation of renewable energy in this globalization era is inevitable since the non-renewable energy leads to climate change and global warming; hence, it does harm the environment and human life. However, in the developing countries, such as Indonesia, the implementation of the renewable energy sources does face technical and social problems. For the latter, renewable energy sources implementation is only effective if the public is aware of its benefits. This research tried to identify the determinants that influence consumers’ intention in adopting renewable energy sources. In addition, this research also tried to predict the consumers who are willing to apply the renewable energy sources in their houses using a logistic regression approach. A case study was conducted in Semarang, Indonesia. The result showed that only eight variables (from fifteen) that are significant statistically, i.e., educational background, employment status, income per month, average electricity cost per month, certainty about the efficiency of renewable energy project, relatives’ influence to adopt the renewable energy sources, energy tax deduction, and the condition of the price of the non-renewable energy sources. The finding of this study could be used as a basis for the government to set up a policy towards an implementation of the renewable energy sources.

  1. Planning woody biomass logistics for energy production: A strategic decision model

    International Nuclear Information System (INIS)

    Frombo, F.; Robba, M.; Minciardi, R.; Sacile, R.; Rosso, F.

    2009-01-01

    One of the key factors on which the sustainable development of modern society should be based is the possibility to take advantage of renewable energies. Biomass resources are one of the most common and widespread resources in the world. Their use to produce energy has many advantages, such as the reduction of greenhouse emissions. This paper describes a GIS-based Environmental Decision Support System (EDSS) to define planning and management strategies for the optimal logistics for energy production from woody biomass, such as forest biomass, agricultural scraps and industrial and urban untreated wood residues. The EDSS is characterized by three main levels: the GIS, the database, and the optimization. The optimization module is divided in three sub-modules to face different kinds of decision problems: strategic planning, tactical planning, and operational management. The aim of this article is to describe the strategic planning level in detail. The decision variables are represented by plant capacity and harvested biomass in a specific forest parcel for each slope class, while the objective function is the sum of the costs related to plant installation and maintenance, biomass transportation and collection, minus the benefits coming from the energy sales at the current market price, including the renewable energy certificates. Moreover, the optimization problem is structured through a set of parameters and equations that are able to encompass different energy conversion technologies (pyrolysis, gasification or combustion) in the system. A case study on the Liguria Region (Savona Province) is presented and results are discussed. (author)

  2. Multiple Temperature Model for Near Continuum Flows

    International Nuclear Information System (INIS)

    XU, Kun; Liu, Hongwei; Jiang, Jianzheng

    2007-01-01

    In the near continuum flow regime, the flow may have different translational temperatures in different directions. It is well known that for increasingly rarefied flow fields, the predictions from continuum formulation, such as the Navier-Stokes equations, lose accuracy. These inaccuracies may be partially due to the single temperature assumption in the Navier-Stokes equations. Here, based on the gas-kinetic Bhatnagar-Gross-Krook (BGK) equation, a multitranslational temperature model is proposed and used in the flow calculations. In order to fix all three translational temperatures, two constraints are additionally proposed to model the energy exchange in different directions. Based on the multiple temperature assumption, the Navier-Stokes relation between the stress and strain is replaced by the temperature relaxation term, and the Navier-Stokes assumption is recovered only in the limiting case when the flow is close to the equilibrium with the same temperature in different directions. In order to validate the current model, both the Couette and Poiseuille flows are studied in the transition flow regime

  3. Collapse susceptibility mapping in karstified gypsum terrain (Sivas basin - Turkey) by conditional probability, logistic regression, artificial neural network models

    Science.gov (United States)

    Yilmaz, Isik; Keskin, Inan; Marschalko, Marian; Bednarik, Martin

    2010-05-01

    This study compares the GIS based collapse susceptibility mapping methods such as; conditional probability (CP), logistic regression (LR) and artificial neural networks (ANN) applied in gypsum rock masses in Sivas basin (Turkey). Digital Elevation Model (DEM) was first constructed using GIS software. Collapse-related factors, directly or indirectly related to the causes of collapse occurrence, such as distance from faults, slope angle and aspect, topographical elevation, distance from drainage, topographic wetness index- TWI, stream power index- SPI, Normalized Difference Vegetation Index (NDVI) by means of vegetation cover, distance from roads and settlements were used in the collapse susceptibility analyses. In the last stage of the analyses, collapse susceptibility maps were produced from CP, LR and ANN models, and they were then compared by means of their validations. Area Under Curve (AUC) values obtained from all three methodologies showed that the map obtained from ANN model looks like more accurate than the other models, and the results also showed that the artificial neural networks is a usefull tool in preparation of collapse susceptibility map and highly compatible with GIS operating features. Key words: Collapse; doline; susceptibility map; gypsum; GIS; conditional probability; logistic regression; artificial neural networks.

  4. A Robust Programming Approach to Bi-objective Optimization Model in the Disaster Relief Logistics Response Phase

    Directory of Open Access Journals (Sweden)

    Mohsen Saffarian

    2015-05-01

    Full Text Available Accidents and natural disasters and crises coming out of them indicate the importance of an integrated planning to reduce their effected. Therefore, disaster relief logistics is one of the main activities in disaster management. In this paper, we study the response phase of the disaster management cycle and a bi-objective model has been developed for relief chain logistic in uncertainty condition including uncertainty in traveling time an also amount of demand in damaged areas. The proposed mathematical model has two objective functions. The first one is to minimize the sum of arrival times to damaged area multiplying by amount of demand and the second objective function is to maximize the minimum ratio of satisfied demands in total period in order to fairness in the distribution of goods. In the proposed model, the problem has been considered periodically and in order to solve the mathematical model, Global Criterion method has been used and a case study has been done at South Khorasan.

  5. Modeling Typhoon Event-Induced Landslides Using GIS-Based Logistic Regression: A Case Study of Alishan Forestry Railway, Taiwan

    Directory of Open Access Journals (Sweden)

    Sheng-Chuan Chen

    2013-01-01

    Full Text Available This study develops a model for evaluating the hazard level of landslides at Alishan Forestry Railway, Taiwan, by using logistic regression with the assistance of a geographical information system (GIS. A typhoon event-induced landslide inventory, independent variables, and a triggering factor were used to build the model. The environmental factors such as bedrock lithology from the geology database; topographic aspect, terrain roughness, profile curvature, and distance to river, from the topographic database; and the vegetation index value from SPOT 4 satellite images were used as variables that influence landslide occurrence. The area under curve (AUC of a receiver operator characteristic (ROC curve was used to validate the model. Effects of parameters on landslide occurrence were assessed from the corresponding coefficient that appears in the logistic regression function. Thereafter, the model was applied to predict the probability of landslides for rainfall data of different return periods. Using a predicted map of probability, the study area was classified into four ranks of landslide susceptibility: low, medium, high, and very high. As a result, most high susceptibility areas are located on the western portion of the study area. Several train stations and railways are located on sites with a high susceptibility ranking.

  6. Logistics innovation development

    DEFF Research Database (Denmark)

    Pedrosa, Alex; Blazevic, Vera; Jasmand, Claudia

    2014-01-01

    to investigate the role of boundary-spanning employees in deepening and broadening customer knowledge while developing logistics service innovations. Findings The results show that boundary-spanning employees’ engage sequentially in deepening and broadening customer knowledge throughout the logistics innovation...... development process. In particular it shows that deepening customer knowledge tends to occur in one-to-one interactions. When boundary-spanning employees engage in broadening customer knowledge, they develop a rich understanding of current customer. Research limitations/implications (if applicable) In general......Purpose This paper aims to investigate the microfoundations—boundary-spanning employees activities and behaviors—of deepening and broadening customer knowledge during logistics innovation development. Design/methodology/approach A multiple case study approach (six case studies) was adopted...

  7. A simulation-based robust biofuel facility location model for an integrated bio-energy logistics network

    Directory of Open Access Journals (Sweden)

    Jae-Dong Hong

    2014-10-01

    Full Text Available Purpose: The purpose of this paper is to propose a simulation-based robust biofuel facility location model for solving an integrated bio-energy logistics network (IBLN problem, where biomass yield is often uncertain or difficult to determine.Design/methodology/approach: The IBLN considered in this paper consists of four different facilities: farm or harvest site (HS, collection facility (CF, biorefinery (BR, and blending station (BS. Authors propose a mixed integer quadratic modeling approach to simultaneously determine the optimal CF and BR locations and corresponding biomass and bio-energy transportation plans. The authors randomly generate biomass yield of each HS and find the optimal locations of CFs and BRs for each generated biomass yield, and select the robust locations of CFs and BRs to show the effects of biomass yield uncertainty on the optimality of CF and BR locations. Case studies using data from the State of South Carolina in the United State are conducted to demonstrate the developed model’s capability to better handle the impact of uncertainty of biomass yield.Findings: The results illustrate that the robust location model for BRs and CFs works very well in terms of the total logistics costs. The proposed model would help decision-makers find the most robust locations for biorefineries and collection facilities, which usually require huge investments, and would assist potential investors in identifying the least cost or important facilities to invest in the biomass and bio-energy industry.Originality/value: An optimal biofuel facility location model is formulated for the case of deterministic biomass yield. To improve the robustness of the model for cases with probabilistic biomass yield, the model is evaluated by a simulation approach using case studies. The proposed model and robustness concept would be a very useful tool that helps potential biofuel investors minimize their investment risk.

  8. Model for Building a Distribution Network Based on the Multivariate Analysis of the Industrial and Logistical Potential of Regions

    Directory of Open Access Journals (Sweden)

    Alexander Vladimirovich Kirillov

    2015-12-01

    Full Text Available The international integration of the Russian economy is connected to the need of the realization of the competitive advantages of the geopolitical position of Russia, the industrial potential of regions, the logistic infrastructure of transport corridors. This article discusses the design model of the supply chain (distribution network based on the multivariate analysis and the methodology of the substantiation of its configuration based on the cost factors and the level of the logistics infrastructure development. For solving the problem of placing one or more logistics centers in the service area, a two-stage algorithm is used. At the first stage, the decisions on the reasonability of the choice of one or another version of the development are made with А. В. Кириллов, В. Е. Целин 345 ЭКОНОМИКА РЕГИОНА №4 (2015 the use of the “Make or Buy” standard model. The criterion of decision making is the guaranteed overcoming of the threshold of “indifference” taking into account the statistical characteristics of costs for options of “buy” and “make” depending on the volume of consumption of goods or services. At the second stage, the Ardalan’s heuristic method is used for the evaluation of the choice of placing one or more logistics centers in the service area. The model parameters are based on the assessment of the development prospects of the region and its investment potential (existence and composition of employment, production, natural resources, financial and consumer opportunities, institutional, innovation, infrastructure capacity. Furthermore, such criteria as a regional financial appeal, professionally trained specialists, the competitive advantages of the promoted company and others are analyzed. An additional criterion is the development of the priority matrix, which considers such factors as difficulties of customs registration and certification, a level of regional transport

  9. Rainfall induced landslide susceptibility mapping using weight-of-evidence, linear and quadratic discriminant and logistic model tree method

    Science.gov (United States)

    Hong, H.; Zhu, A. X.

    2017-12-01

    Climate change is a common phenomenon and it is very serious all over the world. The intensification of rainfall extremes with climate change is of key importance to society and then it may induce a large impact through landslides. This paper presents GIS-based new ensemble data mining techniques that weight-of-evidence, logistic model tree, linear and quadratic discriminant for landslide spatial modelling. This research was applied in Anfu County, which is a landslide-prone area in Jiangxi Province, China. According to a literature review and research the study area, we select the landslide influencing factor and their maps were digitized in a GIS environment. These landslide influencing factors are the altitude, plan curvature, profile curvature, slope degree, slope aspect, topographic wetness index (TWI), Stream Power Index (SPI), Topographic Wetness Index (SPI), distance to faults, distance to rivers, distance to roads, soil, lithology, normalized difference vegetation index and land use. According to historical information of individual landslide events, interpretation of the aerial photographs, and field surveys supported by the government of Jiangxi Meteorological Bureau of China, 367 landslides were identified in the study area. The landslide locations were divided into two subsets, namely, training and validating (70/30), based on a random selection scheme. In this research, Pearson's correlation was used for the evaluation of the relationship between the landslides and influencing factors. In the next step, three data mining techniques combined with the weight-of-evidence, logistic model tree, linear and quadratic discriminant, were used for the landslide spatial modelling and its zonation. Finally, the landslide susceptibility maps produced by the mentioned models were evaluated by the ROC curve. The results showed that the area under the curve (AUC) of all of the models was > 0.80. At the same time, the highest AUC value was for the linear and quadratic

  10. Information Exchange in Global Logistics Chains : An application for Model-based Auditing (abstract)

    NARCIS (Netherlands)

    Veenstra, A.W.; Hulstijn, J.; Christiaanse, R.; Tan, Y.

    2013-01-01

    An integrated data pipeline has been proposed to meet requirements for supply chain visibility and control. How can data integration be used for risk assessment, monitoring and control in global supply chains? We argue that concepts from model-based auditing can be used to model the ‘ideal’ flow of

  11. Logistic regression models for predicting physical and mental health-related quality of life in rheumatoid arthritis patients.

    Science.gov (United States)

    Alishiri, Gholam Hossein; Bayat, Noushin; Fathi Ashtiani, Ali; Tavallaii, Seyed Abbas; Assari, Shervin; Moharamzad, Yashar

    2008-01-01

    The aim of this work was to develop two logistic regression models capable of predicting physical and mental health related quality of life (HRQOL) among rheumatoid arthritis (RA) patients. In this cross-sectional study which was conducted during 2006 in the outpatient rheumatology clinic of our university hospital, Short Form 36 (SF-36) was used for HRQOL measurements in 411 RA patients. A cutoff point to define poor versus good HRQOL was calculated using the first quartiles of SF-36 physical and mental component scores (33.4 and 36.8, respectively). Two distinct logistic regression models were used to derive predictive variables including demographic, clinical, and psychological factors. The sensitivity, specificity, and accuracy of each model were calculated. Poor physical HRQOL was positively associated with pain score, disease duration, monthly family income below 300 US$, comorbidity, patient global assessment of disease activity or PGA, and depression (odds ratios: 1.1; 1.004; 15.5; 1.1; 1.02; 2.08, respectively). The variables that entered into the poor mental HRQOL prediction model were monthly family income below 300 US$, comorbidity, PGA, and bodily pain (odds ratios: 6.7; 1.1; 1.01; 1.01, respectively). Optimal sensitivity and specificity were achieved at a cutoff point of 0.39 for the estimated probability of poor physical HRQOL and 0.18 for mental HRQOL. Sensitivity, specificity, and accuracy of the physical and mental models were 73.8, 87, 83.7% and 90.38, 70.36, 75.43%, respectively. The results show that the suggested models can be used to predict poor physical and mental HRQOL separately among RA patients using simple variables with acceptable accuracy. These models can be of use in the clinical decision-making of RA patients and to recognize patients with poor physical or mental HRQOL in advance, for better management.

  12. Spatial prediction of Lactarius deliciosus and Lactarius salmonicolor mushroom distribution with logistic regression models in the Kızılcasu Planning Unit, Turkey.

    Science.gov (United States)

    Mumcu Kucuker, Derya; Baskent, Emin Zeki

    2015-01-01

    Integration of non-wood forest products (NWFPs) into forest management planning has become an increasingly important issue in forestry over the last decade. Among NWFPs, mushrooms are valued due to their medicinal, commercial, high nutritional and recreational importance. Commercial mushroom harvesting also provides important income to local dwellers and contributes to the economic value of regional forests. Sustainable management of these products at the regional scale requires information on their locations in diverse forest settings and the ability to predict and map their spatial distributions over the landscape. This study focuses on modeling the spatial distribution of commercially harvested Lactarius deliciosus and L. salmonicolor mushrooms in the Kızılcasu Forest Planning Unit, Turkey. The best models were developed based on topographic, climatic and stand characteristics, separately through logistic regression analysis using SPSS™. The best topographic model provided better classification success (69.3 %) than the best climatic (65.4 %) and stand (65 %) models. However, the overall best model, with 73 % overall classification success, used a mix of several variables. The best models were integrated into an Arc/Info GIS program to create spatial distribution maps of L. deliciosus and L. salmonicolor in the planning area. Our approach may be useful to predict the occurrence and distribution of other NWFPs and provide a valuable tool for designing silvicultural prescriptions and preparing multiple-use forest management plans.

  13. Optimizing landslide susceptibility zonation: Effects of DEM spatial resolution and slope unit delineation on logistic regression models

    Science.gov (United States)

    Schlögel, R.; Marchesini, I.; Alvioli, M.; Reichenbach, P.; Rossi, M.; Malet, J.-P.

    2018-01-01

    We perform landslide susceptibility zonation with slope units using three digital elevation models (DEMs) of varying spatial resolution of the Ubaye Valley (South French Alps). In so doing, we applied a recently developed algorithm automating slope unit delineation, given a number of parameters, in order to optimize simultaneously the partitioning of the terrain and the performance of a logistic regression susceptibility model. The method allowed us to obtain optimal slope units for each available DEM spatial resolution. For each resolution, we studied the susceptibility model performance by analyzing in detail the relevance of the conditioning variables. The analysis is based on landslide morphology data, considering either the whole landslide or only the source area outline as inputs. The procedure allowed us to select the most useful information, in terms of DEM spatial resolution, thematic variables and landslide inventory, in order to obtain the most reliable slope unit-based landslide susceptibility assessment.

  14. A probabilistic cellular automata model for the dynamics of a population driven by logistic growth and weak Allee effect

    Science.gov (United States)

    Mendonça, J. R. G.

    2018-04-01

    We propose and investigate a one-parameter probabilistic mixture of one-dimensional elementary cellular automata under the guise of a model for the dynamics of a single-species unstructured population with nonoverlapping generations in which individuals have smaller probability of reproducing and surviving in a crowded neighbourhood but also suffer from isolation and dispersal. Remarkably, the first-order mean field approximation to the dynamics of the model yields a cubic map containing terms representing both logistic and weak Allee effects. The model has a single absorbing state devoid of individuals, but depending on the reproduction and survival probabilities can achieve a stable population. We determine the critical probability separating these two phases and find that the phase transition between them is in the directed percolation universality class of critical behaviour.

  15. Spatial modeling of rat bites and prediction of rat infestation in Peshawar valley using binomial kriging with logistic regression.

    Science.gov (United States)

    Ali, Asad; Zaidi, Farrah; Fatima, Syeda Hira; Adnan, Muhammad; Ullah, Saleem

    2018-03-24

    In this study, we propose to develop a geostatistical computational framework to model the distribution of rat bite infestation of epidemic proportion in Peshawar valley, Pakistan. Two species Rattus norvegicus and Rattus rattus are suspected to spread the infestation. The framework combines strengths of maximum entropy algorithm and binomial kriging with logistic regression to spatially model the distribution of infestation and to determine the individual role of environmental predictors in modeling the distribution trends. Our results demonstrate the significance of a number of social and environmental factors in rat infestations such as (I) high human population density; (II) greater dispersal ability of rodents due to the availability of better connectivity routes such as roads, and (III) temperature and precipitation influencing rodent fecundity and life cycle.

  16. The Linear Logistic Test Model (LLTM as the methodological foundation of item generating rules for a new verbal reasoning test

    Directory of Open Access Journals (Sweden)

    HERBERT POINSTINGL

    2009-06-01

    Full Text Available Based on the demand for new verbal reasoning tests to enrich psychological test inventory, a pilot version of a new test was analysed: the 'Family Relation Reasoning Test' (FRRT; Poinstingl, Kubinger, Skoda & Schechtner, forthcoming, in which several basic cognitive operations (logical rules have been embedded/implemented. Given family relationships of varying complexity embedded in short stories, testees had to logically conclude the correct relationship between two individuals within a family. Using empirical data, the linear logistic test model (LLTM; Fischer, 1972, a special case of the Rasch model, was used to test the construct validity of the test: The hypothetically assumed basic cognitive operations had to explain the Rasch model's item difficulty parameters. After being shaped in LLTM's matrices of weights ((qij, none of these operations were corroborated by means of the Andersen's Likelihood Ratio Test.

  17. Simulation Model of Logistic Support to Isolated Airspace Smveillance Radar Stations

    Directory of Open Access Journals (Sweden)

    Tomislav Crnković

    2008-03-01

    Full Text Available A simulation model of the radar network operation of fivemilitary radar stations has been developed. Simulation waspeiformed in GPSS language and contains the time of operationof five radars through a period of one year, time of plannedpreventive maintenance, irregularities, time of corrective maintenanceand maintenance team(s. The simulation shows theinfluence of the number of maintenance teams on the availabilityof each radar and presents a good orienteering point fordefining the optimal model of preventive and corrective maintenanceof the radar network.

  18. Multicriteria Cost Assessment and Logistics Modeling for Military Humanitarian Assistance and Disaster Relief Aerial Delivery Operations

    Science.gov (United States)

    2015-03-01

    vulnerable people will have access to this airdropped consumable aid (since nobody 1 is necessarily coordinating the distribution on the ground... VBA ) platforms (see Appendix B). In particular, we used GAMS v.23.9.3 with IBM ILOG CPLEX 12.4.0.1 to solve the stochastic, mixed-integer weighted...goal programming model, and we used Excel/ VBA to create an auto- matic, user-friendly interface with the decision maker for model input and analysis of

  19. and Multinomial Logistic Regression

    African Journals Online (AJOL)

    This work presented the results of an experimental comparison of two models: Multinomial Logistic Regression (MLR) and Artificial Neural Network (ANN) for classifying students based on their academic performance. The predictive accuracy for each model was measured by their average Classification Correct Rate (CCR).

  20. Binary Logistic Regression Versus Boosted Regression Trees in Assessing Landslide Susceptibility for Multiple-Occurring Regional Landslide Events: Application to the 2009 Storm Event in Messina (Sicily, southern Italy).

    Science.gov (United States)

    Lombardo, L.; Cama, M.; Maerker, M.; Parisi, L.; Rotigliano, E.

    2014-12-01

    This study aims at comparing the performances of Binary Logistic Regression (BLR) and Boosted Regression Trees (BRT) methods in assessing landslide susceptibility for multiple-occurrence regional landslide events within the Mediterranean region. A test area was selected in the north-eastern sector of Sicily (southern Italy), corresponding to the catchments of the Briga and the Giampilieri streams both stretching for few kilometres from the Peloritan ridge (eastern Sicily, Italy) to the Ionian sea. This area was struck on the 1st October 2009 by an extreme climatic event resulting in thousands of rapid shallow landslides, mainly of debris flows and debris avalanches types involving the weathered layer of a low to high grade metamorphic bedrock. Exploiting the same set of predictors and the 2009 landslide archive, BLR- and BRT-based susceptibility models were obtained for the two catchments separately, adopting a random partition (RP) technique for validation; besides, the models trained in one of the two catchments (Briga) were tested in predicting the landslide distribution in the other (Giampilieri), adopting a spatial partition (SP) based validation procedure. All the validation procedures were based on multi-folds tests so to evaluate and compare the reliability of the fitting, the prediction skill, the coherence in the predictor selection and the precision of the susceptibility estimates. All the obtained models for the two methods produced very high predictive performances, with a general congruence between BLR and BRT in the predictor importance. In particular, the research highlighted that BRT-models reached a higher prediction performance with respect to BLR-models, for RP based modelling, whilst for the SP-based models the difference in predictive skills between the two methods dropped drastically, converging to an analogous excellent performance. However, when looking at the precision of the probability estimates, BLR demonstrated to produce more robust

  1. Planning the City Logistics Terminal Location by Applying the Green p-Median Model and Type-2 Neurofuzzy Network.

    Science.gov (United States)

    Pamučar, Dragan; Vasin, Ljubislav; Atanasković, Predrag; Miličić, Milica

    2016-01-01

    The paper herein presents green p-median problem (GMP) which uses the adaptive type-2 neural network for the processing of environmental and sociological parameters including costs of logistics operators and demonstrates the influence of these parameters on planning the location for the city logistics terminal (CLT) within the discrete network. CLT shows direct effects on increment of traffic volume especially in urban areas, which further results in negative environmental effects such as air pollution and noise as well as increased number of urban populations suffering from bronchitis, asthma, and similar respiratory infections. By applying the green p-median model (GMM), negative effects on environment and health in urban areas caused by delivery vehicles may be reduced to minimum. This model creates real possibilities for making the proper investment decisions so as profitable investments may be realized in the field of transport infrastructure. The paper herein also includes testing of GMM in real conditions on four CLT locations in Belgrade City zone.

  2. Planning the City Logistics Terminal Location by Applying the Green p-Median Model and Type-2 Neurofuzzy Network

    Directory of Open Access Journals (Sweden)

    Dragan Pamučar

    2016-01-01

    Full Text Available The paper herein presents green p-median problem (GMP which uses the adaptive type-2 neural network for the processing of environmental and sociological parameters including costs of logistics operators and demonstrates the influence of these parameters on planning the location for the city logistics terminal (CLT within the discrete network. CLT shows direct effects on increment of traffic volume especially in urban areas, which further results in negative environmental effects such as air pollution and noise as well as increased number of urban populations suffering from bronchitis, asthma, and similar respiratory infections. By applying the green p-median model (GMM, negative effects on environment and health in urban areas caused by delivery vehicles may be reduced to minimum. This model creates real possibilities for making the proper investment decisions so as profitable investments may be realized in the field of transport infrastructure. The paper herein also includes testing of GMM in real conditions on four CLT locations in Belgrade City zone.

  3. Logistics bottlenecks

    Energy Technology Data Exchange (ETDEWEB)

    NONE

    2010-09-15

    Many of the vulnerabilities to Energy Access, Energy Security, and Environmental Sustainability result from impediments to reaching a global demand-supply balance, as well as local balances, for various energy sources and carriers. Vulnerabilities result from multiple reasons: regional imbalances of energy production and consumption, the bulky character of the majority of energy fuels, the virtual necessity of electricity consumption following its production, among others. To detect and prioritize respective 'bottlenecks' across energy carriers, they have to be measured. In this report, production, consumption, exports, and imports were measured across all major energy carriers for seven key regions of the world for three time frames-2008, 2020, and 2050. Imbalances between production and consumption form bottlenecks in each region.

  4. Developing logistic regression models using purchase attributes and demographics to predict the probability of purchases of regular and specialty eggs.

    Science.gov (United States)

    Bejaei, M; Wiseman, K; Cheng, K M

    2015-01-01

    Consumers' interest in specialty eggs appears to be growing in Europe and North America. The objective of this research was to develop logistic regression models that utilise purchaser attributes and demographics to predict the probability of a consumer purchasing a specific type of table egg including regular (white and brown), non-caged (free-run, free-range and organic) or nutrient-enhanced eggs. These purchase prediction models, together with the purchasers' attributes, can be used to assess market opportunities of different egg types specifically in British Columbia (BC). An online survey was used to gather data for the models. A total of 702 completed questionnaires were submitted by BC residents. Selected independent variables included in the logistic regression to develop models for different egg types to predict the probability of a consumer purchasing a specific type of table egg. The variables used in the model accounted for 54% and 49% of variances in the purchase of regular and non-caged eggs, respectively. Research results indicate that consumers of different egg types exhibit a set of unique and statistically significant characteristics and/or demographics. For example, consumers of regular eggs were less educated, older, price sensitive, major chain store buyers, and store flyer users, and had lower awareness about different types of eggs and less concern regarding animal welfare issues. However, most of the non-caged egg consumers were less concerned about price, had higher awareness about different types of table eggs, purchased their eggs from local/organic grocery stores, farm gates or farmers markets, and they were more concerned about care and feeding of hens compared to consumers of other eggs types.

  5. Channel-dependent GMM and multi-class logistic: Regression models for language recognition

    NARCIS (Netherlands)

    Leeuwen, D.A. van; Brümmer, Niko

    2006-01-01

    This paper describes two new approaches to spoken language recognition. These were both successfully applied in the NIST 2005 Language Recognition Evaluation. The first approach extends the Gaussian Mixture Model technique with channel dependency, which results in actual detection costs (CDET) of

  6. Information exchange in global logistics chains : An application for model-based auditing,

    NARCIS (Netherlands)

    Veenstra, A.W.; Hulstijn, J.; Christiaanse, R.M.J.; Tan, Y.

    2013-01-01

    An integrated data pipeline has been proposed to meet requirements for visibility, supervision and control in global supply chains. How can data integration be used for risk assessment, monitoring and control in global supply chains? We argue that concepts from model-based auditing can be used to

  7. An economic production model for time dependent demand with rework and multiple production setups

    Directory of Open Access Journals (Sweden)

    S.R. Singh

    2014-04-01

    Full Text Available In this paper, we present a model for time dependent demand with multiple productions and rework setups. Production is demand dependent and greater than the demand rate. Production facility produces items in m production setups and one rework setup (m, 1 policy. The major reason of reverse logistic and green supply chain is rework, so it reduces the cost of production and other ecological problems. Most of the researchers developed a rework model without deteriorating items. A numerical example and sensitivity analysis is shown to describe the model.

  8. Multiple Scattering Model for Optical Coherence Tomography with Rytov Approximation

    KAUST Repository

    Li, Muxingzi

    2017-01-01

    of speckles due to multiple scatterers within the coherence length, and other random noise. Motivated by the above two challenges, a multiple scattering model based on Rytov approximation and Gaussian beam optics is proposed for the OCT setup. Some previous

  9. The Bifurcation and Control of a Single-Species Fish Population Logistic Model with the Invasion of Alien Species

    Directory of Open Access Journals (Sweden)

    Yi Zhang

    2014-01-01

    Full Text Available The objective of this paper is to study systematically the bifurcation and control of a single-species fish population logistic model with the invasion of alien species based on the theory of singular system and bifurcation. It regards Spartina anglica as an invasive species, which invades the fisheries and aquaculture. Firstly, the stabilities of equilibria in this model are discussed. Moreover, the sufficient conditions for existence of the trans-critical bifurcation and the singularity induced bifurcation are obtained. Secondly, the state feedback controller is designed to eliminate the unexpected singularity induced bifurcation by combining harvested effort with the purification capacity. It obviously inhibits the switch of population and makes the system stable. Finally, the numerical simulation is proposed to show the practical significance of the bifurcation and control from the biological point of view.

  10. Comparison of artificial neural network and logistic regression models for predicting in-hospital mortality after primary liver cancer surgery.

    Directory of Open Access Journals (Sweden)

    Hon-Yi Shi

    Full Text Available BACKGROUND: Since most published articles comparing the performance of artificial neural network (ANN models and logistic regression (LR models for predicting hepatocellular carcinoma (HCC outcomes used only a single dataset, the essential issue of internal validity (reproducibility of the models has not been addressed. The study purposes to validate the use of ANN model for predicting in-hospital mortality in HCC surgery patients in Taiwan and to compare the predictive accuracy of ANN with that of LR model. METHODOLOGY/PRINCIPAL FINDINGS: Patients who underwent a HCC surgery during the period from 1998 to 2009 were included in the study. This study retrospectively compared 1,000 pairs of LR and ANN models based on initial clinical data for 22,926 HCC surgery patients. For each pair of ANN and LR models, the area under the receiver operating characteristic (AUROC curves, Hosmer-Lemeshow (H-L statistics and accuracy rate were calculated and compared using paired T-tests. A global sensitivity analysis was also performed to assess the relative significance of input parameters in the system model and the relative importance of variables. Compared to the LR models, the ANN models had a better accuracy rate in 97.28% of cases, a better H-L statistic in 41.18% of cases, and a better AUROC curve in 84.67% of cases. Surgeon volume was the most influential (sensitive parameter affecting in-hospital mortality followed by age and lengths of stay. CONCLUSIONS/SIGNIFICANCE: In comparison with the conventional LR model, the ANN model in the study was more accurate in predicting in-hospital mortality and had higher overall performance indices. Further studies of this model may consider the effect of a more detailed database that includes complications and clinical examination findings as well as more detailed outcome data.

  11. Empirical Study of E-logistics System Based on Tibet Logistics Industry

    OpenAIRE

    Liu, Yu

    2013-01-01

    With the rapid growth of E-logistics in the global logistics industry, it is important to get insight into E-logistics system in Chinese logistics industry. Regarding the current situation of E-logistics of Chinese logistics industry, there are still many problems to be concerned and resolved. This paper will review the concepts and theoretical background of E-logistics System from previous researches. After acknowledging the essential issues on E-logistics System, a research model is designe...

  12. Testing the Logistics Model of Supplying Military Vehicles with Spare Parts

    Directory of Open Access Journals (Sweden)

    Robert Spudić

    2007-07-01

    Full Text Available The use of advanced transport means understands alsotheir supply by spare and consumable parts. In order to solvethe problem of the required quantities, costs of purchase andstorage of the parts, it is necessary to solve the problem of stocksmanagement. The wear of tyres for military vehicles in extremeexploitation conditions is of random character. How fast thetyres will wear on the all-ten·ain and heavy motor vehicle dependson the driver's skill and the external conditions (weather,terrain. All the conditions are of random character and in orderto determine as accurately as possible the wear of tyres it isnecessary to monitor the wear of tyres within a certain time period,and to find the approximate probability of tyre wear in thefuture period of time. When the probability of tyre wear is determined,stochastic supply management model is used to calculatethe value of the stocks which allows optimal planning ofstocks of spare parts at minimal costs. The stochastic model allowsoptimal calculation for the purchase of consumable partsof transport means whose consumption depends on the randomconditions and events.

  13. Evaluation of Logistic Regression and Multivariate Adaptive Regression Spline Models for Groundwater Potential Mapping Using R and GIS

    Directory of Open Access Journals (Sweden)

    Soyoung Park

    2017-07-01

    Full Text Available This study mapped and analyzed groundwater potential using two different models, logistic regression (LR and multivariate adaptive regression splines (MARS, and compared the results. A spatial database was constructed for groundwater well data and groundwater influence factors. Groundwater well data with a high potential yield of ≥70 m3/d were extracted, and 859 locations (70% were used for model training, whereas the other 365 locations (30% were used for model validation. We analyzed 16 groundwater influence factors including altitude, slope degree, slope aspect, plan curvature, profile curvature, topographic wetness index, stream power index, sediment transport index, distance from drainage, drainage density, lithology, distance from fault, fault density, distance from lineament, lineament density, and land cover. Groundwater potential maps (GPMs were constructed using LR and MARS models and tested using a receiver operating characteristics curve. Based on this analysis, the area under the curve (AUC for the success rate curve of GPMs created using the MARS and LR models was 0.867 and 0.838, and the AUC for the prediction rate curve was 0.836 and 0.801, respectively. This implies that the MARS model is useful and effective for groundwater potential analysis in the study area.

  14. Testing for Nonuniform Differential Item Functioning with Multiple Indicator Multiple Cause Models

    Science.gov (United States)

    Woods, Carol M.; Grimm, Kevin J.

    2011-01-01

    In extant literature, multiple indicator multiple cause (MIMIC) models have been presented for identifying items that display uniform differential item functioning (DIF) only, not nonuniform DIF. This article addresses, for apparently the first time, the use of MIMIC models for testing both uniform and nonuniform DIF with categorical indicators. A…

  15. Multiplicity distributions in the dual parton model

    International Nuclear Information System (INIS)

    Batunin, A.V.; Tolstenkov, A.N.

    1985-01-01

    Multiplicity distributions are calculated by means of a new mechanism of production of hadrons in a string, which was proposed previously by the authors and takes into account explicitly the valence character of the ends of the string. It is shown that allowance for this greatly improves the description of the low-energy multiplicity distributions. At superhigh energies, the contribution of the ends of the strings becomes negligibly small, but in this case multi-Pomeron contributions must be taken into account

  16. Logistical connections?

    DEFF Research Database (Denmark)

    Bjerg, Helle

    Paperet præsenterer et kvalitativt studie af lærerstuderendes oplevelser og opfattelser af forholdet mellem uddannelse og praktik, samt teori og praksis, således som det udspiller sig i forbindelse med den første praktik på læreruddannelsen. I paperet præsenteres en model for en række forskellige...

  17. Modeling and Optimization of Woody Biomass Harvest and Logistics in the Northeastern United States

    Science.gov (United States)

    Hartley, Damon S.

    World energy consumption is at an all-time high and is projected to continue growing for the foreseeable future. Currently, much of the energy that is produced comes from non-renewable fossil energy sources, which includes the burden of increased greenhouse gas emissions and the fear of energy insecurity. Woody biomass is being considered as a material that can be utilized to reduce the burden caused by fossil energy. While the technical capability to convert woody biomass to energy has been known for a long period of time, the cost of the feedstock has been considered too costly to be implemented in a large commercial scale. Increasing the use of woody biomass as an energy source requires that the supply chains are setup in a way that minimizes cost, the locational factors that lead to development are understood, the facilities are located in the most favorable locations and local resource assessments can be made. A mixed integer linear programming model to efficiently configure woody biomass supply chain configurations and optimize the harvest, extraction, transport, storage and preprocessing of the woody biomass resources to provide the lowest possible delivered price. The characteristics of woody biomass, such as spatial distribution and low bulk density, tend to make collection and transport difficult as compared to traditional energy sources. These factors, as well as others, have an adverse effect on the cost of the feedstock. The average delivered cost was found to be between 64.69-98.31 dry Mg for an annual demand of 180,000 dry Mg. The effect of resource availability and required demand was examined to determine the impact that each would have on the total cost. The use of woody biomass for energy has been suggested as a way to improve rural economies through job creation, reduction of energy costs and regional development. This study examined existing wood using bio-energy facilities in the northeastern United States to define the drivers of

  18. Remote sensing and GIS-based landslide hazard analysis and cross-validation using multivariate logistic regression model on three test areas in Malaysia

    Science.gov (United States)

    Pradhan, Biswajeet

    2010-05-01

    This paper presents the results of the cross-validation of a multivariate logistic regression model using remote sensing data and GIS for landslide hazard analysis on the Penang, Cameron, and Selangor areas in Malaysia. Landslide locations in the study areas were identified by interpreting aerial photographs and satellite images, supported by field surveys. SPOT 5 and Landsat TM satellite imagery were used to map landcover and vegetation index, respectively. Maps of topography, soil type, lineaments and land cover were constructed from the spatial datasets. Ten factors which influence landslide occurrence, i.e., slope, aspect, curvature, distance from drainage, lithology, distance from lineaments, soil type, landcover, rainfall precipitation, and normalized difference vegetation index (ndvi), were extracted from the spatial database and the logistic regression coefficient of each factor was computed. Then the landslide hazard was analysed using the multivariate logistic regression coefficients derived not only from the data for the respective area but also using the logistic regression coefficients calculated from each of the other two areas (nine hazard maps in all) as a cross-validation of the model. For verification of the model, the results of the analyses were then compared with the field-verified landslide locations. Among the three cases of the application of logistic regression coefficient in the same study area, the case of Selangor based on the Selangor logistic regression coefficients showed the highest accuracy (94%), where as Penang based on the Penang coefficients showed the lowest accuracy (86%). Similarly, among the six cases from the cross application of logistic regression coefficient in other two areas, the case of Selangor based on logistic coefficient of Cameron showed highest (90%) prediction accuracy where as the case of Penang based on the Selangor logistic regression coefficients showed the lowest accuracy (79%). Qualitatively, the cross

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

    Science.gov (United States)

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

    2016-01-01

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

  20. Evolving Four Part Harmony Using a Multiple Worlds Model

    DEFF Research Database (Denmark)

    Scirea, Marco; Brown, Joseph Alexander

    2015-01-01

    This application of the Multiple Worlds Model examines a collaborative fitness model for generating four part harmonies. In this model we have multiple populations and the fitness of the individuals is based on the ability of a member from each population to work with the members of other...

  1. COSTS FOR IMPLEMENTING LOGISTICS INTO THE COMPANY

    OpenAIRE

    Mariana Man; Maria Nowicka-Skowron

    2010-01-01

    The ways of approaching the logistic problems need the use of some varied techniques and means, and the elaboration of a logistic project – which would aim the entire company – mobilises multiple personnel for a period of a few months and claims the intervention of logisticians within the logistic consultancy office, whom shall also act after putting the logistic project into practice. The accomplishment of any logistic wide change within the company needs an array of activities that may be g...

  2. Explaining clinical behaviors using multiple theoretical models

    Directory of Open Access Journals (Sweden)

    Eccles Martin P

    2012-10-01

    the five surveys. For the predictor variables, the mean construct scores were above the mid-point on the scale with median values across the five behaviors generally being above four out of seven and the range being from 1.53 to 6.01. Across all of the theories, the highest proportion of the variance explained was always for intention and the lowest was for behavior. The Knowledge-Attitudes-Behavior Model performed poorly across all behaviors and dependent variables; CSSRM also performed poorly. For TPB, SCT, II, and LT across the five behaviors, we predicted median R2 of 25% to 42.6% for intention, 6.2% to 16% for behavioral simulation, and 2.4% to 6.3% for behavior. Conclusions We operationalized multiple theories measuring across five behaviors. Continuing challenges that emerge from our work are: better specification of behaviors, better operationalization of theories; how best to appropriately extend the range of theories; further assessment of the value of theories in different settings and groups; exploring the implications of these methods for the management of chronic diseases; and moving to experimental designs to allow an understanding of behavior change.

  3. Explaining clinical behaviors using multiple theoretical models.

    Science.gov (United States)

    Eccles, Martin P; Grimshaw, Jeremy M; MacLennan, Graeme; Bonetti, Debbie; Glidewell, Liz; Pitts, Nigel B; Steen, Nick; Thomas, Ruth; Walker, Anne; Johnston, Marie

    2012-10-17

    , the mean construct scores were above the mid-point on the scale with median values across the five behaviors generally being above four out of seven and the range being from 1.53 to 6.01. Across all of the theories, the highest proportion of the variance explained was always for intention and the lowest was for behavior. The Knowledge-Attitudes-Behavior Model performed poorly across all behaviors and dependent variables; CSSRM also performed poorly. For TPB, SCT, II, and LT across the five behaviors, we predicted median R2 of 25% to 42.6% for intention, 6.2% to 16% for behavioral simulation, and 2.4% to 6.3% for behavior. We operationalized multiple theories measuring across five behaviors. Continuing challenges that emerge from our work are: better specification of behaviors, better operationalization of theories; how best to appropriately extend the range of theories; further assessment of the value of theories in different settings and groups; exploring the implications of these methods for the management of chronic diseases; and moving to experimental designs to allow an understanding of behavior change.

  4. The energy logistic model for analyses of transportation- and energy systems; Energilogistikmodell foer systemberaekningar av transport- och energifoersoerjningssystem

    Energy Technology Data Exchange (ETDEWEB)

    Blinge, M

    1995-05-01

    The Energy Logistic Model has been improved to become a tool for analysis of all production processes, transportation systems and systems including several energy users and several fuels. Two cases were studied. The first case deals with terminal equipment for inter modal transport systems and the second case deals with diesel fuelled trucks, cranes and machines in the Goeteborg area. In both cases, the environmental improvements of the city air quality are analyzed when natural gas is substituted for diesel oil. The comparison between inter modal transport and road haulage shows that the environmental impacts from the operations at the terminal are limited, and that the potential for environmental benefits when using inter modal transport is improving with the transportation distance. The choice of electricity production system is of great importance when calculating the environmental impact from railway traffic in the total analysis of the transportation system. 13 refs, 27 tabs

  5. Landslide susceptibility mapping for a part of North Anatolian Fault Zone (Northeast Turkey) using logistic regression model

    Science.gov (United States)

    Demir, Gökhan; aytekin, mustafa; banu ikizler, sabriye; angın, zekai

    2013-04-01

    The North Anatolian Fault is know as one of the most active and destructive fault zone which produced many earthquakes with high magnitudes. Along this fault zone, the morphology and the lithological features are prone to landsliding. However, many earthquake induced landslides were recorded by several studies along this fault zone, and these landslides caused both injuiries and live losts. Therefore, a detailed landslide susceptibility assessment for this area is indispancable. In this context, a landslide susceptibility assessment for the 1445 km2 area in the Kelkit River valley a part of North Anatolian Fault zone (Eastern Black Sea region of Turkey) was intended with this study, and the results of this study are summarized here. For this purpose, geographical information system (GIS) and a bivariate statistical model were used. Initially, Landslide inventory maps are prepared by using landslide data determined by field surveys and landslide data taken from General Directorate of Mineral Research and Exploration. The landslide conditioning factors are considered to be lithology, slope gradient, slope aspect, topographical elevation, distance to streams, distance to roads and distance to faults, drainage density and fault density. ArcGIS package was used to manipulate and analyze all the collected data Logistic regression method was applied to create a landslide susceptibility map. Landslide susceptibility maps were divided into five susceptibility regions such as very low, low, moderate, high and very high. The result of the analysis was verified using the inventoried landslide locations and compared with the produced probability model. For this purpose, Area Under Curvature (AUC) approach was applied, and a AUC value was obtained. Based on this AUC value, the obtained landslide susceptibility map was concluded as satisfactory. Keywords: North Anatolian Fault Zone, Landslide susceptibility map, Geographical Information Systems, Logistic Regression Analysis.

  6. Systemic Thinking and Requisite Holism in Mastering Logistics Risks: the Model for Identifying Risks in Organisations and Supply Chain

    Directory of Open Access Journals (Sweden)

    Bojan Rosi

    2013-02-01

    Full Text Available Risks in logistic processes represent one of the major issues in supply chain management nowadays. Every organization strives for success, and uninterrupted operations are the key factors in achieving this goal, which cannot be achieved without efficient risk management. In the scope of supply chain risk research, we identified some key issues in the field, the major issue being the lack of standardization and models, which can make risk management in an organization easier and more efficient. Consequently, we developed a model, which captures and identifies risks in an organization and its supply chain. It is in accordance with the general risk management standard – ISO 31000, and incorporates some relevant recent findings from general and supply chain risk management, especially from the viewpoint of public segmentation. This experimental catalogue (which is also published online can serve as a checklist and a starting point of supply chain risk management in organizations. Its main idea is cooperation between experts from the area in order to compile an ever-growing list of possible risks and to provide an insight in the model and its value in practice, for which reason input and opinions of anyone who uses our model are greatly appreciated and included in the catalogue.

  7. Integration of multiple, excess, backup, and expected covering models

    OpenAIRE

    M S Daskin; K Hogan; C ReVelle

    1988-01-01

    The concepts of multiple, excess, backup, and expected coverage are defined. Model formulations using these constructs are reviewed and contrasted to illustrate the relationships between them. Several new formulations are presented as is a new derivation of the expected covering model which indicates more clearly the relationship of the model to other multi-state covering models. An expected covering model with multiple time standards is also presented.

  8. Keep Calm and Learn Multilevel Logistic Modeling: A Simplified Three-Step Procedure Using Stata, R, Mplus, and SPSS

    OpenAIRE

    Nicolas Sommet; Davide Morselli

    2017-01-01

    This paper aims to introduce multilevel logistic regression analysis in a simple and practical way. First, we introduce the basic principles of logistic regression analysis (conditional probability, logit transformation, odds ratio). Second, we discuss the two fundamental implications of running this kind of analysis with a nested data structure: In multilevel logistic regression, the odds that the outcome variable equals one (rather than zero) may vary from one cluster to another (i.e. the i...

  9. Digital soil mapping using multiple logistic regression on terrain parameters in southern Brazil Mapeamento digital de solos utilizando regressões logísticas múltiplas e parâmetros do terreno no sul do Brasil

    Directory of Open Access Journals (Sweden)

    Elvio Giasson

    2006-06-01

    Full Text Available Soil surveys are necessary sources of information for land use planning, but they are not always available. This study proposes the use of multiple logistic regressions on the prediction of occurrence of soil types based on reference areas. From a digitalized soil map and terrain parameters derived from the digital elevation model in ArcView environment, several sets of multiple logistic regressions were defined using statistical software Minitab, establishing relationship between explanatory terrain variables and soil types, using either the original legend or a simplified legend, and using or not stratification of the study area by drainage classes. Terrain parameters, such as elevation, distance to stream, flow accumulation, and topographic wetness index, were the variables that best explained soil distribution. Stratification by drainage classes did not have significant effect. Simplification of the original legend increased the accuracy of the method on predicting soil distribution.Os levantamentos de solos são fontes de informação necessárias para o planejamento de uso das terras, entretanto eles nem sempre estão disponíveis. Este estudo propõe o uso de regressões logísticas múltiplas na predição de ocorrência de classes de solos a partir de áreas de referência. Baseado no mapa original de solos em formato digital e parâmetros do terreno derivados do modelo numérico do terreno em ambiente ArcView, vários conjuntos de regressões logísticas múltiplas foram definidas usando o programa estatístico Minitab, estabelecendo relações entre as variáveis do terreno independentes e tipos de solos, usando tanto a legenda original como uma legenda simplificada, e usando ou não estratificação da área de estudo por classes de drenagem. Os parâmetros do terreno como elevação, distância dos rios, acúmulo de fluxo e índice de umidade topográfica foram as variáveis que melhor explicaram a distribuição das classes de

  10. GIS-based groundwater potential analysis using novel ensemble weights-of-evidence with logistic regression and functional tree models.

    Science.gov (United States)

    Chen, Wei; Li, Hui; Hou, Enke; Wang, Shengquan; Wang, Guirong; Panahi, Mahdi; Li, Tao; Peng, Tao; Guo, Chen; Niu, Chao; Xiao, Lele; Wang, Jiale; Xie, Xiaoshen; Ahmad, Baharin Bin

    2018-09-01

    The aim of the current study was to produce groundwater spring potential maps using novel ensemble weights-of-evidence (WoE) with logistic regression (LR) and functional tree (FT) models. First, a total of 66 springs were identified by field surveys, out of which 70% of the spring locations were used for training the models and 30% of the spring locations were employed for the validation process. Second, a total of 14 affecting factors including aspect, altitude, slope, plan curvature, profile curvature, stream power index (SPI), topographic wetness index (TWI), sediment transport index (STI), lithology, normalized difference vegetation index (NDVI), land use, soil, distance to roads, and distance to streams was used to analyze the spatial relationship between these affecting factors and spring occurrences. Multicollinearity analysis and feature selection of the correlation attribute evaluation (CAE) method were employed to optimize the affecting factors. Subsequently, the novel ensembles of the WoE, LR, and FT models were constructed using the training dataset. Finally, the receiver operating characteristic (ROC) curves, standard error, confidence interval (CI) at 95%, and significance level P were employed to validate and compare the performance of three models. Overall, all three models performed well for groundwater spring potential evaluation. The prediction capability of the FT model, with the highest AUC values, the smallest standard errors, the narrowest CIs, and the smallest P values for the training and validation datasets, is better compared to those of other models. The groundwater spring potential maps can be adopted for the management of water resources and land use by planners and engineers. Copyright © 2018 Elsevier B.V. All rights reserved.

  11. Modeling the potential risk factors of bovine viral diarrhea prevalence in Egypt using univariable and multivariable logistic regression analyses

    Directory of Open Access Journals (Sweden)

    Abdelfattah M. Selim

    2018-03-01

    Full Text Available Aim: The present cross-sectional study was conducted to determine the seroprevalence and potential risk factors associated with Bovine viral diarrhea virus (BVDV disease in cattle and buffaloes in Egypt, to model the potential risk factors associated with the disease using logistic regression (LR models, and to fit the best predictive model for the current data. Materials and Methods: A total of 740 blood samples were collected within November 2012-March 2013 from animals aged between 6 months and 3 years. The potential risk factors studied were species, age, sex, and herd location. All serum samples were examined with indirect ELIZA test for antibody detection. Data were analyzed with different statistical approaches such as Chi-square test, odds ratios (OR, univariable, and multivariable LR models. Results: Results revealed a non-significant association between being seropositive with BVDV and all risk factors, except for species of animal. Seroprevalence percentages were 40% and 23% for cattle and buffaloes, respectively. OR for all categories were close to one with the highest OR for cattle relative to buffaloes, which was 2.237. Likelihood ratio tests showed a significant drop of the -2LL from univariable LR to multivariable LR models. Conclusion: There was an evidence of high seroprevalence of BVDV among cattle as compared with buffaloes with the possibility of infection in different age groups of animals. In addition, multivariable LR model was proved to provide more information for association and prediction purposes relative to univariable LR models and Chi-square tests if we have more than one predictor.

  12. INTERNATIONAL LOGISTICS SYSTEMS DESIGN AND EFFECTIVENESS EVALUATION

    Directory of Open Access Journals (Sweden)

    N. V. Khalipova

    2015-08-01

    Full Text Available Purpose. In the paper the question of the development of a methodological approach to the determination of logistics systems’ performance and grounding of the most effective goods’ delivery schemes, based on the theory of functions and sets of multiple objects, vector optimization approaches and discrete maximum principle for multi-stage processes (phase method is considered. Methodology. To achieve the goals of the research, the model of logistic system represented by multiple object that defined by the structure and content. The object is represented by hybrid superposition, composed of sets, multi-sets, ordered sets (lists and inhomogeneous sets (sequences, corteges, which at each stage of cargo delivery present sets of technological operations of their processing, choices and decisions algorithms. Multiple structure of objects is constructive three, consisting of the carrier, signatures and axiomatic. To determine the effective scheme of delivery, applied discrete maximum principle using vector optimization criterion. Findings. In this article, logistics system of delivery is presented in the form of a multi-stage (phase of the process. Each stage reviews a plurality of discrete activities sets, which includes the possible technology cycles of operations in goods handling. At each stage of a multi-phase delivery process from the supplier to the consumer, these sets are different. Considered a model example solving the problem of vector optimization options for delivery of goods by the road in the international logistics system for the five-step process. Optimization performed on the basis of three indicators. Originality. In this paper, the choice of the most effective way of delivery goods produced using the theory of functions and sets of multiple objects, using the discrete maximum principle for multi-stage processes, based on the vector optimization criterion. At each of its stages are formed a plurality of valid solutions as

  13. A test for the parameters of multiple linear regression models ...

    African Journals Online (AJOL)

    A test for the parameters of multiple linear regression models is developed for conducting tests simultaneously on all the parameters of multiple linear regression models. The test is robust relative to the assumptions of homogeneity of variances and absence of serial correlation of the classical F-test. Under certain null and ...

  14. Shaping the E-Commerce Logistics Strategy: a Decision Framework

    Directory of Open Access Journals (Sweden)

    Antonio Ghezzi

    2012-07-01

    In order to accomplish this task, the combination of a literature review and a multiple case‐study approach was used. In particular, 28 case studies of leading B2C e‐ commerce merchants in Italy ‐ with various business models ‐ in the main online industries that sell products were conducted in order to analyse the relationship between the features of the logistics problem and the logistics strategy adopted.

  15. A logistic model to predict early pregnancy loss following in vitro fertilization based on 2601 infertility patients.

    Science.gov (United States)

    Yi, Yan; Lu, Guangxiu; Ouyang, Yan; lin, Ge; Gong, Fei; Li, Xihong

    2016-03-31

    According to previous studies, even after embryonic cardiac activity is detected, the pregnancy loss rate remains 3-4 %. The objectives of this study were to investigate the differences in ultrasound parameters between a miscarriage group and an ongoing pregnancy group during the 1(st) trimester and to build a logistic model to predict early pregnancy loss (EPL) after the appearance of embryonic cardiac activity in patients who have undergone in vitro fertilization embryo transfer (IVF-ET) treatment. A total of 2601 patients with early singleton pregnancies with embryonic cardiac activity were retrospectively analyzed after IVF from January 2010 to June 2011. Transvaginal sonography (TVS) was performed at 6 to 10 weeks of gestational age (GA). The mean gestational sac diameter (MSD), crown-rump length (CRL), fetal heart rate (FHR), and yolk sac diameter (YSD) were measured by TVS. A total of 2400 patients had an ongoing pregnancy and an additional 201 (7.7 %) patients miscarried during the first trimester after fetal cardiac activity had been established. The maternal age (MA) and infertility duration were much greater, and the MSD, CRL, and FHR were much lower in the miscarriage group than in the ongoing pregnancy group after IVF (P model utilized the following equation: the possibility of EPL = exp(z)/(1 + exp(z)), where z = -21.456 + (0.114 × MA) + (4.305 × × GA) - (0.043 × MSD) - (0.359 × CRL) - (0.091 × FHR) + 2.243 (fluid collection present around the gestational sac (GS)) + 2.519 (when YSD  5.5). The MA, MSD, CRL, YSD, FHR, infertility duration, and fluid collection around the GS were each correlated with EPL after IVF in infertile patients. A logistic model is a useful tool for predicting EPL after the appearance of embryonic cardiac activity (area under the curve [AUC] = 0.909).

  16. SU-F-BRD-01: A Logistic Regression Model to Predict Objective Function Weights in Prostate Cancer IMRT

    International Nuclear Information System (INIS)

    Boutilier, J; Chan, T; Lee, T; Craig, T; Sharpe, M

    2014-01-01

    Purpose: To develop a statistical model that predicts optimization objective function weights from patient geometry for intensity-modulation radiotherapy (IMRT) of prostate cancer. Methods: A previously developed inverse optimization method (IOM) is applied retrospectively to determine optimal weights for 51 treated patients. We use an overlap volume ratio (OVR) of bladder and rectum for different PTV expansions in order to quantify patient geometry in explanatory variables. Using the optimal weights as ground truth, we develop and train a logistic regression (LR) model to predict the rectum weight and thus the bladder weight. Post hoc, we fix the weights of the left femoral head, right femoral head, and an artificial structure that encourages conformity to the population average while normalizing the bladder and rectum weights accordingly. The population average of objective function weights is used for comparison. Results: The OVR at 0.7cm was found to be the most predictive of the rectum weights. The LR model performance is statistically significant when compared to the population average over a range of clinical metrics including bladder/rectum V53Gy, bladder/rectum V70Gy, and mean voxel dose to the bladder, rectum, CTV, and PTV. On average, the LR model predicted bladder and rectum weights that are both 63% closer to the optimal weights compared to the population average. The treatment plans resulting from the LR weights have, on average, a rectum V70Gy that is 35% closer to the clinical plan and a bladder V70Gy that is 43% closer. Similar results are seen for bladder V54Gy and rectum V54Gy. Conclusion: Statistical modelling from patient anatomy can be used to determine objective function weights in IMRT for prostate cancer. Our method allows the treatment planners to begin the personalization process from an informed starting point, which may lead to more consistent clinical plans and reduce overall planning time

  17. SU-F-BRD-01: A Logistic Regression Model to Predict Objective Function Weights in Prostate Cancer IMRT

    Energy Technology Data Exchange (ETDEWEB)

    Boutilier, J; Chan, T; Lee, T [University of Toronto, Toronto, Ontario (Canada); Craig, T; Sharpe, M [University of Toronto, Toronto, Ontario (Canada); The Princess Margaret Cancer Centre - UHN, Toronto, ON (Canada)

    2014-06-15

    Purpose: To develop a statistical model that predicts optimization objective function weights from patient geometry for intensity-modulation radiotherapy (IMRT) of prostate cancer. Methods: A previously developed inverse optimization method (IOM) is applied retrospectively to determine optimal weights for 51 treated patients. We use an overlap volume ratio (OVR) of bladder and rectum for different PTV expansions in order to quantify patient geometry in explanatory variables. Using the optimal weights as ground truth, we develop and train a logistic regression (LR) model to predict the rectum weight and thus the bladder weight. Post hoc, we fix the weights of the left femoral head, right femoral head, and an artificial structure that encourages conformity to the population average while normalizing the bladder and rectum weights accordingly. The population average of objective function weights is used for comparison. Results: The OVR at 0.7cm was found to be the most predictive of the rectum weights. The LR model performance is statistically significant when compared to the population average over a range of clinical metrics including bladder/rectum V53Gy, bladder/rectum V70Gy, and mean voxel dose to the bladder, rectum, CTV, and PTV. On average, the LR model predicted bladder and rectum weights that are both 63% closer to the optimal weights compared to the population average. The treatment plans resulting from the LR weights have, on average, a rectum V70Gy that is 35% closer to the clinical plan and a bladder V70Gy that is 43% closer. Similar results are seen for bladder V54Gy and rectum V54Gy. Conclusion: Statistical modelling from patient anatomy can be used to determine objective function weights in IMRT for prostate cancer. Our method allows the treatment planners to begin the personalization process from an informed starting point, which may lead to more consistent clinical plans and reduce overall planning time.

  18. Medicare capitation model, functional status, and multiple comorbidities: model accuracy

    Science.gov (United States)

    Noyes, Katia; Liu, Hangsheng; Temkin-Greener, Helena

    2012-01-01

    Objective This study examined financial implications of CMS-Hierarchical Condition Categories (HCC) risk-adjustment model on Medicare payments for individuals with comorbid chronic conditions. Study Design The study used 1992-2000 data from the Medicare Current Beneficiary Survey and corresponding Medicare claims. The pairs of comorbidities were formed based on the prior evidence about possible synergy between these conditions and activities of daily living (ADL) deficiencies and included heart disease and cancer, lung disease and cancer, stroke and hypertension, stroke and arthritis, congestive heart failure (CHF) and osteoporosis, diabetes and coronary artery disease, CHF and dementia. Methods For each beneficiary, we calculated the actual Medicare cost ratio as the ratio of the individual’s annualized costs to the mean annual Medicare cost of all people in the study. The actual Medicare cost ratios, by ADLs, were compared to the HCC ratios under the CMS-HCC payment model. Using multivariate regression models, we tested whether having the identified pairs of comorbidities affects the accuracy of CMS-HCC model predictions. Results The CMS-HCC model underpredicted Medicare capitation payments for patients with hypertension, lung disease, congestive heart failure and dementia. The difference between the actual costs and predicted payments was partially explained by beneficiary functional status and less than optimal adjustment for these chronic conditions. Conclusions Information about beneficiary functional status should be incorporated in reimbursement models since underpaying providers for caring for population with multiple comorbidities may provide severe disincentives for managed care plans to enroll such individuals and to appropriately manage their complex and costly conditions. PMID:18837646

  19. Multiple Scenario Generation of Subsurface Models

    DEFF Research Database (Denmark)

    Cordua, Knud Skou

    of information is obeyed such that no unknown assumptions and biases influence the solution to the inverse problem. This involves a definition of the probabilistically formulated inverse problem, a discussion about how prior models can be established based on statistical information from sample models...... of the probabilistic formulation of the inverse problem. This function is based on an uncertainty model that describes the uncertainties related to the observed data. In a similar way, a formulation of the prior probability distribution that takes into account uncertainties related to the sample model statistics...... similar to observation uncertainties. We refer to the effect of these approximations as modeling errors. Examples that show how the modeling error is estimated are provided. Moreover, it is shown how these effects can be taken into account in the formulation of the posterior probability distribution...

  20. Multiple system modelling of waste management

    International Nuclear Information System (INIS)

    Eriksson, Ola; Bisaillon, Mattias

    2011-01-01

    Highlights: → Linking of models will provide a more complete, correct and credible picture of the systems. → The linking procedure is easy to perform and also leads to activation of project partners. → The simulation procedure is a bit more complicated and calls for the ability to run both models. - Abstract: Due to increased environmental awareness, planning and performance of waste management has become more and more complex. Therefore waste management has early been subject to different types of modelling. Another field with long experience of modelling and systems perspective is energy systems. The two modelling traditions have developed side by side, but so far there are very few attempts to combine them. Waste management systems can be linked together with energy systems through incineration plants. The models for waste management can be modelled on a quite detailed level whereas surrounding systems are modelled in a more simplistic way. This is a problem, as previous studies have shown that assumptions on the surrounding system often tend to be important for the conclusions. In this paper it is shown how two models, one for the district heating system (MARTES) and another one for the waste management system (ORWARE), can be linked together. The strengths and weaknesses with model linking are discussed when compared to simplistic assumptions on effects in the energy and waste management systems. It is concluded that the linking of models will provide a more complete, correct and credible picture of the consequences of different simultaneous changes in the systems. The linking procedure is easy to perform and also leads to activation of project partners. However, the simulation procedure is a bit more complicated and calls for the ability to run both models.

  1. Mean multiplicity in the Regge models with rising cross sections

    International Nuclear Information System (INIS)

    Chikovani, Z.E.; Kobylisky, N.A.; Martynov, E.S.

    1979-01-01

    Behaviour of the mean multiplicity and the total cross section σsub(t) of hadron-hadron interactions is considered in the framework of the Regge models at high energies. Generating function was plotted for models of dipole and froissaron, and the mean multiplicity and multiplicity moments were calculated. It is shown that approximately ln 2 S (energy square) in the dipole model, which is in good agreement with the experiment. It is also found that in various Regge models approximately σsub(t)lnS

  2. Uso de regressões logísticas múltiplas para mapeamento digital de solos no Planalto Médio do RS Multiple logistic regression applied to soil survey in rio grande do sul state, Brazil

    Directory of Open Access Journals (Sweden)

    Samuel Ribeiro Figueiredo

    2008-12-01

    Full Text Available Regressões nominais logísticas estabelecem relações matemáticas entre variáveis independentes contínuas ou discretas e variáveis dependentes discretas. Essas foram avaliadas quanto ao seu potencial em predizer a ocorrência e distribuição de classes de solos na região dos municípios de Ibirubá e Quinze de Novembro (RS. A partir de modelo numérico de terreno digital (MNT com 90 m de resolução, foram calculadas variáveis de terreno topográficas (elevação, declividade e curvatura e hidrográficas (distância dos rios, índice de umidade topográfica, comprimento de fluxo de escoamento e índice de poder de escoamento. Foram então estabelecidas regressões logísticas múltiplas entre as classes de solos da região com base em levantamento tradicional na escala 1:80.000 e as variáveis de terreno. As regressões serviram para calcular a probabilidade de ocorrência de cada classe de solo, e o mapa final de solos estimado foi produzido atribuindo-se a cada célula do mapa a denominação da classe de solo com maior probabilidade de ocorrência. Observou-se acurácia geral (AG de 58 % e acurácia pelo coeficiente Kappa de Cohen de 38 %, comparando-se o mapa original com o mapa estimado dentro da escala original. Uma simplificação de escala foi pouco significativa para o aumento da acurácia do mapa, sendo 61 % de AG e 39 % de Kappa. Concluiu-se que as regressões logísticas múltiplas apresentaram potencial preditivo para serem usadas como ferramentas no mapeamento supervisionado de solos.Logistic nominal regressions establish mathematical relations between continuous or discrete independent variables and discrete dependent variables. The prediction potential of the occurrence and distribution of soil classes in the region Ibirubá and Quinze de Novembro, RS, Brazil was evaluated. Using a digital elevation model (DEM with 90 m resolution, were calculated several topographic characteristics (elevation, slope, and curvature and

  3. Discrete choice models with multiplicative error terms

    DEFF Research Database (Denmark)

    Fosgerau, Mogens; Bierlaire, Michel

    2009-01-01

    The conditional indirect utility of many random utility maximization (RUM) discrete choice models is specified as a sum of an index V depending on observables and an independent random term ε. In general, the universe of RUM consistent models is much larger, even fixing some specification of V due...

  4. Structural model analysis of multiple quantitative traits.

    Directory of Open Access Journals (Sweden)

    Renhua Li

    2006-07-01

    Full Text Available We introduce a method for the analysis of multilocus, multitrait genetic data that provides an intuitive and precise characterization of genetic architecture. We show that it is possible to infer the magnitude and direction of causal relationships among multiple correlated phenotypes and illustrate the technique using body composition and bone density data from mouse intercross populations. Using these techniques we are able to distinguish genetic loci that affect adiposity from those that affect overall body size and thus reveal a shortcoming of standardized measures such as body mass index that are widely used in obesity research. The identification of causal networks sheds light on the nature of genetic heterogeneity and pleiotropy in complex genetic systems.

  5. Managing Reverse Logistics or Reversing Logistics Management?

    OpenAIRE

    Brito, Marisa

    2004-01-01

    textabstractIn the past, supply chains were busy fine-tuning the logistics from raw material to the end customer. Today an increasing flow of products is going back in the chain. Thus, companies have to manage reverse logistics as well.This thesis contributes to a better understanding of reverse logistics. The thesis brings insights on reverse logistics decision-making and it lays down theoretical principles for reverse logistics as a research field.In particular it puts together a framework ...

  6. Multiple-lesion track-structure model

    International Nuclear Information System (INIS)

    Wilson, J.W.; Cucinotta, F.A.; Shinn, J.L.

    1992-03-01

    A multilesion cell kinetic model is derived, and radiation kinetic coefficients are related to the Katz track structure model. The repair-related coefficients are determined from the delayed plating experiments of Yang et al. for the C3H10T1/2 cell system. The model agrees well with the x ray and heavy ion experiments of Yang et al. for the immediate plating, delaying plating, and fractionated exposure protocols employed by Yang. A study is made of the effects of target fragments in energetic proton exposures and of the repair-deficient target-fragment-induced lesions

  7. Study of risk factors affecting both hypertension and obesity outcome by using multivariate multilevel logistic regression models

    Directory of Open Access Journals (Sweden)

    Sepedeh Gholizadeh

    2016-07-01

    Full Text Available Background:Obesity and hypertension are the most important non-communicable diseases thatin many studies, the prevalence and their risk factors have been performedin each geographic region univariately.Study of factors affecting both obesity and hypertension may have an important role which to be adrressed in this study. Materials &Methods:This cross-sectional study was conducted on 1000 men aged 20-70 living in Bushehr province. Blood pressure was measured three times and the average of them was considered as one of the response variables. Hypertension was defined as systolic blood pressure ≥140 (and-or diastolic blood pressure ≥90 and obesity was defined as body mass index ≥25. Data was analyzed by using multilevel, multivariate logistic regression model by MlwiNsoftware. Results:Intra class correlations in cluster level obtained 33% for high blood pressure and 37% for obesity, so two level model was fitted to data. The prevalence of obesity and hypertension obtained 43.6% (0.95%CI; 40.6-46.5, 29.4% (0.95%CI; 26.6-32.1 respectively. Age, gender, smoking, hyperlipidemia, diabetes, fruit and vegetable consumption and physical activity were the factors affecting blood pressure (p≤0.05. Age, gender, hyperlipidemia, diabetes, fruit and vegetable consumption, physical activity and place of residence are effective on obesity (p≤0.05. Conclusion: The multilevel models with considering levels distribution provide more precise estimates. As regards obesity and hypertension are the major risk factors for cardiovascular disease, by knowing the high-risk groups we can d careful planning to prevention of non-communicable diseases and promotion of society health.

  8. Affine LIBOR Models with Multiple Curves

    DEFF Research Database (Denmark)

    Grbac, Zorana; Papapantoleon, Antonis; Schoenmakers, John

    2015-01-01

    are specified following the methodology of the affine LIBOR models and are driven by the wide and flexible class of affine processes. The affine property is preserved under forward measures, which allows us to derive Fourier pricing formulas for caps, swaptions, and basis swaptions. A model specification...... with dependent LIBOR rates is developed that allows for an efficient and accurate calibration to a system of caplet prices....

  9. Analysis test of understanding of vectors with the three-parameter logistic model of item response theory and item response curves technique

    Directory of Open Access Journals (Sweden)

    Suttida Rakkapao

    2016-10-01

    Full Text Available This study investigated the multiple-choice test of understanding of vectors (TUV, by applying item response theory (IRT. The difficulty, discriminatory, and guessing parameters of the TUV items were fit with the three-parameter logistic model of IRT, using the parscale program. The TUV ability is an ability parameter, here estimated assuming unidimensionality and local independence. Moreover, all distractors of the TUV were analyzed from item response curves (IRC that represent simplified IRT. Data were gathered on 2392 science and engineering freshmen, from three universities in Thailand. The results revealed IRT analysis to be useful in assessing the test since its item parameters are independent of the ability parameters. The IRT framework reveals item-level information, and indicates appropriate ability ranges for the test. Moreover, the IRC analysis can be used to assess the effectiveness of the test’s distractors. Both IRT and IRC approaches reveal test characteristics beyond those revealed by the classical analysis methods of tests. Test developers can apply these methods to diagnose and evaluate the features of items at various ability levels of test takers.

  10. Analysis test of understanding of vectors with the three-parameter logistic model of item response theory and item response curves technique

    Science.gov (United States)

    Rakkapao, Suttida; Prasitpong, Singha; Arayathanitkul, Kwan

    2016-12-01

    This study investigated the multiple-choice test of understanding of vectors (TUV), by applying item response theory (IRT). The difficulty, discriminatory, and guessing parameters of the TUV items were fit with the three-parameter logistic model of IRT, using the parscale program. The TUV ability is an ability parameter, here estimated assuming unidimensionality and local independence. Moreover, all distractors of the TUV were analyzed from item response curves (IRC) that represent simplified IRT. Data were gathered on 2392 science and engineering freshmen, from three universities in Thailand. The results revealed IRT analysis to be useful in assessing the test since its item parameters are independent of the ability parameters. The IRT framework reveals item-level information, and indicates appropriate ability ranges for the test. Moreover, the IRC analysis can be used to assess the effectiveness of the test's distractors. Both IRT and IRC approaches reveal test characteristics beyond those revealed by the classical analysis methods of tests. Test developers can apply these methods to diagnose and evaluate the features of items at various ability levels of test takers.

  11. Financial performance monitoring of the technical efficiency of critical access hospitals: a data envelopment analysis and logistic regression modeling approach.

    Science.gov (United States)

    Wilson, Asa B; Kerr, Bernard J; Bastian, Nathaniel D; Fulton, Lawrence V

    2012-01-01

    From 1980 to 1999, rural designated hospitals closed at a disproportionally high rate. In response to this emergent threat to healthcare access in rural settings, the Balanced Budget Act of 1997 made provisions for the creation of a new rural hospital--the critical access hospital (CAH). The conversion to CAH and the associated cost-based reimbursement scheme significantly slowed the closure rate of rural hospitals. This work investigates which methods can ensure the long-term viability of small hospitals. This article uses a two-step design to focus on a hypothesized relationship between technical efficiency of CAHs and a recently developed set of financial monitors for these entities. The goal is to identify the financial performance measures associated with efficiency. The first step uses data envelopment analysis (DEA) to differentiate efficient from inefficient facilities within a data set of 183 CAHs. Determining DEA efficiency is an a priori categorization of hospitals in the data set as efficient or inefficient. In the second step, DEA efficiency is the categorical dependent variable (efficient = 0, inefficient = 1) in the subsequent binary logistic regression (LR) model. A set of six financial monitors selected from the array of 20 measures were the LR independent variables. We use a binary LR to test the null hypothesis that recently developed CAH financial indicators had no predictive value for categorizing a CAH as efficient or inefficient, (i.e., there is no relationship between DEA efficiency and fiscal performance).

  12. Indirect Allee effect, bistability and chaotic oscillations in a predator-prey discrete model of logistic type

    International Nuclear Information System (INIS)

    Lopez-Ruiz, Ricardo; Fournier-Prunaret, Daniele

    2005-01-01

    A cubic discrete coupled logistic equation is proposed to model the predator-prey problem. The coupling depends on the population size of both species and on a positive constant λ, which could depend on the prey reproduction rate and on the predator hunting strategy. Different dynamical regimes are obtained when λ is modified. For small λ, the species become extinct. For a bigger λ, the preys survive but the predators extinguish. Only when the prey population reaches a critical value then predators can coexist with preys. For increasing λ, a bistable regime appears where the populations apart of being stabilized in fixed quantities can present periodic, quasiperiodic and chaotic oscillations. Finally, bistability is lost and the system settles down in a steady state, or, for the biggest permitted λ, in an invariant curve. We also present the basins for the different regimes. The use of the critical curves lets us determine the influence of the zones with different number of first rank preimages in the bifurcation mechanisms of those basins

  13. Analyses of non-fatal accidents in an opencast mine by logistic regression model - a case study.

    Science.gov (United States)

    Onder, Seyhan; Mutlu, Mert

    2017-09-01

    Accidents cause major damage for both workers and enterprises in the mining industry. To reduce the number of occupational accidents, these incidents should be properly registered and carefully analysed. This study efficiently examines the Aegean Lignite Enterprise (ELI) of Turkish Coal Enterprises (TKI) in Soma between 2006 and 2011, and opencast coal mine occupational accident records were used for statistical analyses. A total of 231 occupational accidents were analysed for this study. The accident records were categorized into seven groups: area, reason, occupation, part of body, age, shift hour and lost days. The SPSS package program was used in this study for logistic regression analyses, which predicted the probability of accidents resulting in greater or less than 3 lost workdays for non-fatal injuries. Social facilities-area of surface installations, workshops and opencast mining areas are the areas with the highest probability for accidents with greater than 3 lost workdays for non-fatal injuries, while the reasons with the highest probability for these types of accidents are transporting and manual handling. Additionally, the model was tested for such reported accidents that occurred in 2012 for the ELI in Soma and estimated the probability of exposure to accidents with lost workdays correctly by 70%.

  14. EIA model documentation: World oil refining logistics demand model,``WORLD`` reference manual. Version 1.1

    Energy Technology Data Exchange (ETDEWEB)

    1994-04-11

    This manual is intended primarily for use as a reference by analysts applying the WORLD model to regional studies. It also provides overview information on WORLD features of potential interest to managers and analysts. Broadly, the manual covers WORLD model features in progressively increasing detail. Section 2 provides an overview of the WORLD model, how it has evolved, what its design goals are, what it produces, and where it can be taken with further enhancements. Section 3 reviews model management covering data sources, managing over-optimization, calibration and seasonality, check-points for case construction and common errors. Section 4 describes in detail the WORLD system, including: data and program systems in overview; details of mainframe and PC program control and files;model generation, size management, debugging and error analysis; use with different optimizers; and reporting and results analysis. Section 5 provides a detailed description of every WORLD model data table, covering model controls, case and technology data. Section 6 goes into the details of WORLD matrix structure. It provides an overview, describes how regional definitions are controlled and defines the naming conventions for-all model rows, columns, right-hand sides, and bounds. It also includes a discussion of the formulation of product blending and specifications in WORLD. Several Appendices supplement the main sections.

  15. SDG and qualitative trend based model multiple scale validation

    Science.gov (United States)

    Gao, Dong; Xu, Xin; Yin, Jianjin; Zhang, Hongyu; Zhang, Beike

    2017-09-01

    Verification, Validation and Accreditation (VV&A) is key technology of simulation and modelling. For the traditional model validation methods, the completeness is weak; it is carried out in one scale; it depends on human experience. The SDG (Signed Directed Graph) and qualitative trend based multiple scale validation is proposed. First the SDG model is built and qualitative trends are added to the model. And then complete testing scenarios are produced by positive inference. The multiple scale validation is carried out by comparing the testing scenarios with outputs of simulation model in different scales. Finally, the effectiveness is proved by carrying out validation for a reactor model.

  16. USAF Logistics Process Optimization Study for the Aircraft Asset Sustainment Process. Volume 3. Future to be Asset Sustainment Process Model

    National Research Council Canada - National Science Library

    Adamson, Anthony

    1998-01-01

    .... It is published as three separate volumes. Volume I, USAF Logistics Process Optimization Study for the Aircraft Asset Sustainment Process -- Phase II Report, discusses the result and cost/benefit analysis of testing three initiatives...

  17. Modelling of rate effects at multiple scales

    DEFF Research Database (Denmark)

    Pedersen, R.R.; Simone, A.; Sluys, L. J.

    2008-01-01

    , the length scale in the meso-model and the macro-model can be coupled. In this fashion, a bridging of length scales can be established. A computational analysis of  a Split Hopkinson bar test at medium and high impact load is carried out at macro-scale and meso-scale including information from  the micro-scale.......At the macro- and meso-scales a rate dependent constitutive model is used in which visco-elasticity is coupled to visco-plasticity and damage. A viscous length scale effect is introduced to control the size of the fracture process zone. By comparison of the widths of the fracture process zone...

  18. Simulation Integrated Design for Logistics

    NARCIS (Netherlands)

    Veeke, H.P.M.

    2003-01-01

    The design of an innovative logistic system is a complex problem in the solution of which many disciplines are involved. Each discipline developed its own way of conceptual modeling for a logistic system based on a mono disciplinary perception. In essence this leads to a communication problem

  19. New experimental model of multiple myeloma.

    Science.gov (United States)

    Telegin, G B; Kalinina, A R; Ponomarenko, N A; Ovsepyan, A A; Smirnov, S V; Tsybenko, V V; Homeriki, S G

    2001-06-01

    NSO/1 (P3x63Ay 8Ut) and SP20 myeloma cells were inoculated to BALB/c OlaHsd mice. NSO/1 cells allowed adequate stage-by-stage monitoring of tumor development. The adequacy of this model was confirmed in experiments with conventional cytostatics: prospidium and cytarabine caused necrosis of tumor cells and reduced animal mortality.

  20. Animal model of human disease. Multiple myeloma

    NARCIS (Netherlands)

    Radl, J.; Croese, J.W.; Zurcher, C.; Enden-Vieveen, M.H.M. van den; Leeuw, A.M. de

    1988-01-01

    Animal models of spontaneous and induced plasmacytomas in some inbred strains of mice have proven to be useful tools for different studies on tumorigenesis and immunoregulation. Their wide applicability and the fact that after their intravenous transplantation, the recipient mice developed bone

  1. Multiple Social Networks, Data Models and Measures for

    DEFF Research Database (Denmark)

    Magnani, Matteo; Rossi, Luca

    2017-01-01

    Multiple Social Network Analysis is a discipline defining models, measures, methodologies, and algorithms to study multiple social networks together as a single social system. It is particularly valuable when the networks are interconnected, e.g., the same actors are present in more than one...

  2. Methodologies for the assessment of earthquake-triggered landslides hazard. A comparison of Logistic Regression and Artificial Neural Network models.

    Science.gov (United States)

    García-Rodríguez, M. J.; Malpica, J. A.; Benito, B.

    2009-04-01

    In recent years, interest in landslide hazard assessment studies has increased substantially. They are appropriate for evaluation and mitigation plan development in landslide-prone areas. There are several techniques available for landslide hazard research at a regional scale. Generally, they can be classified in two groups: qualitative and quantitative methods. Most of qualitative methods tend to be subjective, since they depend on expert opinions and represent hazard levels in descriptive terms. On the other hand, quantitative methods are objective and they are commonly used due to the correlation between the instability factors and the location of the landslides. Within this group, statistical approaches and new heuristic techniques based on artificial intelligence (artificial neural network (ANN), fuzzy logic, etc.) provide rigorous analysis to assess landslide hazard over large regions. However, they depend on qualitative and quantitative data, scale, types of movements and characteristic factors used. We analysed and compared an approach for assessing earthquake-triggered landslides hazard using logistic regression (LR) and artificial neural networks (ANN) with a back-propagation learning algorithm. One application has been developed in El Salvador, a country of Central America where the earthquake-triggered landslides are usual phenomena. In a first phase, we analysed the susceptibility and hazard associated to the seismic scenario of the 2001 January 13th earthquake. We calibrated the models using data from the landslide inventory for this scenario. These analyses require input variables representing physical parameters to contribute to the initiation of slope instability, for example, slope gradient, elevation, aspect, mean annual precipitation, lithology, land use, and terrain roughness, while the occurrence or non-occurrence of landslides is considered as dependent variable. The results of the landslide susceptibility analysis are checked using landslide

  3. Modeling Rabbit Responses to Single and Multiple Aerosol ...

    Science.gov (United States)

    Journal Article Survival models are developed here to predict response and time-to-response for mortality in rabbits following exposures to single or multiple aerosol doses of Bacillus anthracis spores. Hazard function models were developed for a multiple dose dataset to predict the probability of death through specifying dose-response functions and the time between exposure and the time-to-death (TTD). Among the models developed, the best-fitting survival model (baseline model) has an exponential dose-response model with a Weibull TTD distribution. Alternative models assessed employ different underlying dose-response functions and use the assumption that, in a multiple dose scenario, earlier doses affect the hazard functions of each subsequent dose. In addition, published mechanistic models are analyzed and compared with models developed in this paper. None of the alternative models that were assessed provided a statistically significant improvement in fit over the baseline model. The general approach utilizes simple empirical data analysis to develop parsimonious models with limited reliance on mechanistic assumptions. The baseline model predicts TTDs consistent with reported results from three independent high-dose rabbit datasets. More accurate survival models depend upon future development of dose-response datasets specifically designed to assess potential multiple dose effects on response and time-to-response. The process used in this paper to dev

  4. LOGISTICS OPTIMIZATION USING ONTOLOGIES

    OpenAIRE

    Hendi , Hayder; Ahmad , Adeel; Bouneffa , Mourad; Fonlupt , Cyril

    2014-01-01

    International audience; Logistics processes involve complex physical flows and integration of different elements. It is widely observed that the uncontrolled processes can decline the state of logistics. The optimization of logistic processes can support the desired growth and consistent continuity of logistics. In this paper, we present a software framework for logistic processes optimization. It primarily defines logistic ontologies and then optimize them. It intends to assist the design of...

  5. Management of Logistics Planning

    OpenAIRE

    Bjørnar Aas; Stein W. Wallace

    2010-01-01

    Logistics problems are gradually becoming more complex and a better understanding of logistics management as a subject is a key to deal with the new challenges. A core element of logistics management is logistics planning, which substitutes for low customer service levels, high waste, and the use of buffers and slacks in the execution of logistic activities. Furthermore, the availability of information and problem-solving capabilities are established as the core parts of logistics planning. B...

  6. A simple approximation of moments of the quasi-equilibrium distribution of an extended stochastic theta-logistic model with non-integer powers.

    Science.gov (United States)

    Bhowmick, Amiya Ranjan; Bandyopadhyay, Subhadip; Rana, Sourav; Bhattacharya, Sabyasachi

    2016-01-01

    The stochastic versions of the logistic and extended logistic growth models are applied successfully to explain many real-life population dynamics and share a central body of literature in stochastic modeling of ecological systems. To understand the randomness in the population dynamics of the underlying processes completely, it is important to have a clear idea about the quasi-equilibrium distribution and its moments. Bartlett et al. (1960) took a pioneering attempt for estimating the moments of the quasi-equilibrium distribution of the stochastic logistic model. Matis and Kiffe (1996) obtain a set of more accurate and elegant approximations for the mean, variance and skewness of the quasi-equilibrium distribution of the same model using cumulant truncation method. The method is extended for stochastic power law logistic family by the same and several other authors (Nasell, 2003; Singh and Hespanha, 2007). Cumulant truncation and some alternative methods e.g. saddle point approximation, derivative matching approach can be applied if the powers involved in the extended logistic set up are integers, although plenty of evidence is available for non-integer powers in many practical situations (Sibly et al., 2005). In this paper, we develop a set of new approximations for mean, variance and skewness of the quasi-equilibrium distribution under more general family of growth curves, which is applicable for both integer and non-integer powers. The deterministic counterpart of this family of models captures both monotonic and non-monotonic behavior of the per capita growth rate, of which theta-logistic is a special case. The approximations accurately estimate the first three order moments of the quasi-equilibrium distribution. The proposed method is illustrated with simulated data and real data from global population dynamics database. Copyright © 2015 Elsevier Inc. All rights reserved.

  7. Explaining clinical behaviors using multiple theoretical models

    OpenAIRE

    Eccles, Martin P; Grimshaw, Jeremy M; MacLennan, Graeme; Bonetti, Debbie; Glidewell, Liz; Pitts, Nigel B; Steen, Nick; Thomas, Ruth; Walker, Anne; Johnston, Marie

    2012-01-01

    Abstract Background In the field of implementation research, there is an increased interest in use of theory when designing implementation research studies involving behavior change. In 2003, we initiated a series of five studies to establish a scientific rationale for interventions to translate research findings into clinical practice by exploring the performance of a number of different, commonly used, overlapping behavioral theories and models. We reflect on the strengths and weaknesses of...

  8. Airport choice model in multiple airport regions

    Directory of Open Access Journals (Sweden)

    Claudia Muñoz

    2017-02-01

    Full Text Available Purpose: This study aims to analyze travel choices made by air transportation users in multi airport regions because it is a crucial component when planning passenger redistribution policies. The purpose of this study is to find a utility function which makes it possible to know the variables that influence users’ choice of the airports on routes to the main cities in the Colombian territory. Design/methodology/approach: This research generates a Multinomial Logit Model (MNL, which is based on the theory of maximizing utility, and it is based on the data obtained on revealed and stated preference surveys applied to users who reside in the metropolitan area of Aburrá Valley (Colombia. This zone is the only one in the Colombian territory which has two neighboring airports for domestic flights. The airports included in the modeling process were Enrique Olaya Herrera (EOH Airport and José María Córdova (JMC Airport. Several structure models were tested, and the MNL proved to be the most significant revealing the common variables that affect passenger airport choice include the airfare, the price to travel the airport, and the time to get to the airport. Findings and Originality/value: The airport choice model which was calibrated corresponds to a valid powerful tool used to calculate the probability of each analyzed airport of being chosen for domestic flights in the Colombian territory. This is done bearing in mind specific characteristic of each of the attributes contained in the utility function. In addition, these probabilities will be used to calculate future market shares of the two airports considered in this study, and this will be done generating a support tool for airport and airline marketing policies.

  9. Multiple simultaneous event model for radiation carcinogenesis

    International Nuclear Information System (INIS)

    Baum, J.W.

    1976-01-01

    A mathematical model is proposed which postulates that cancer induction is a multi-event process, that these events occur naturally, usually one at a time in any cell, and that radiation frequently causes two of these events to occur simultaneously. Microdosimetric considerations dictate that for high LET radiations the simultaneous events are associated with a single particle or track. The model predicts: (a) linear dose-effect relations for early times after irradiation with small doses, (b) approximate power functions of dose (i.e. Dsup(x)) having exponent less than one for populations of mixed age examined at short times after irradiation with small doses, (c) saturation of effect at either long times after irradiation with small doses or for all times after irradiation with large doses, and (d) a net increase in incidence which is dependent on age of observation but independent of age at irradiation. Data of Vogel, for neutron induced mammary tumors in rats, are used to illustrate the validity of the formulation. This model provides a quantitative framework to explain several unexpected results obtained by Vogel. It also provides a logical framework to explain the dose-effect relations observed in the Japanese survivors of the atomic bombs. (author)

  10. Predicting risk for portal vein thrombosis in acute pancreatitis patients: A comparison of radical basis function artificial neural network and logistic regression models.

    Science.gov (United States)

    Fei, Yang; Hu, Jian; Gao, Kun; Tu, Jianfeng; Li, Wei-Qin; Wang, Wei

    2017-06-01

    To construct a radical basis function (RBF) artificial neural networks (ANNs) model to predict the incidence of acute pancreatitis (AP)-induced portal vein thrombosis. The analysis included 353 patients with AP who had admitted between January 2011 and December 2015. RBF ANNs model and logistic regression model were constructed based on eleven factors relevant to AP respectively. Statistical indexes were used to evaluate the value of the prediction in two models. The predict sensitivity, specificity, positive predictive value, negative predictive value and accuracy by RBF ANNs model for PVT were 73.3%, 91.4%, 68.8%, 93.0% and 87.7%, respectively. There were significant differences between the RBF ANNs and logistic regression models in these parameters (Plogistic regression model. D-dimer, AMY, Hct and PT were important prediction factors of approval for AP-induced PVT. Copyright © 2017 Elsevier Inc. All rights reserved.

  11. Basic Diagnosis and Prediction of Persistent Contrail Occurrence using High-resolution Numerical Weather Analyses/Forecasts and Logistic Regression. Part II: Evaluation of Sample Models

    Science.gov (United States)

    Duda, David P.; Minnis, Patrick

    2009-01-01

    Previous studies have shown that probabilistic forecasting may be a useful method for predicting persistent contrail formation. A probabilistic forecast to accurately predict contrail formation over the contiguous United States (CONUS) is created by using meteorological data based on hourly meteorological analyses from the Advanced Regional Prediction System (ARPS) and from the Rapid Update Cycle (RUC) as well as GOES water vapor channel measurements, combined with surface and satellite observations of contrails. Two groups of logistic models were created. The first group of models (SURFACE models) is based on surface-based contrail observations supplemented with satellite observations of contrail occurrence. The second group of models (OUTBREAK models) is derived from a selected subgroup of satellite-based observations of widespread persistent contrails. The mean accuracies for both the SURFACE and OUTBREAK models typically exceeded 75 percent when based on the RUC or ARPS analysis data, but decreased when the logistic models were derived from ARPS forecast data.

  12. Customer satisfaction with the quality of the logistic services

    Directory of Open Access Journals (Sweden)

    Małgorzata Lisińska-Kuśnierz

    2014-03-01

    Full Text Available Background: Logistics services are evaluated mainly by measuring customer satisfaction. Measurement of the customer satisfaction provides the information about how organizations operate as well as how to effectively satisfy customer needs. The aim of this paper is to propose an evaluation model of the customer satisfaction of the quality of the logistic services provided. The research in this paper was focused on the evaluation of the level of customer satisfaction in the context of logistics service as well as on the analysis of importance of ten logistic services attributes influencing customer satisfaction. Methods: The research was conducted on the basis of the questionnaire designed for purchasers of logistic services. The subjects of the research were companies which are using refrigerated transport. Results: To define relation between level of customer satisfaction in the context of logistic service and logistic service attributes impacting this satisfaction Pearson's correlation method was used. In turn the model to evaluate the customer satisfaction in the context of logistic services in scope of refrigerated transport was built using multiple regression and stepwise regression methods.

  13. Complex logistics audit system

    Directory of Open Access Journals (Sweden)

    Zuzana Marková

    2010-02-01

    Full Text Available Complex logistics audit system is a tool for realization of logistical audit in the company. The current methods for logistics auditare based on “ad hok” analysis of logisticsl system. This paper describes system for complex logistics audit. It is a global diagnosticsof logistics processes and functions of enterprise. The goal of logistics audit is to provide comparative documentation for managementabout state of logistics in company and to show the potential of logistics changes in order to achieve more effective companyperformance.

  14. Cox proportional hazards models have more statistical power than logistic regression models in cross-sectional genetic association studies

    NARCIS (Netherlands)

    van der Net, Jeroen B.; Janssens, A. Cecile J. W.; Eijkemans, Marinus J. C.; Kastelein, John J. P.; Sijbrands, Eric J. G.; Steyerberg, Ewout W.

    2008-01-01

    Cross-sectional genetic association studies can be analyzed using Cox proportional hazards models with age as time scale, if age at onset of disease is known for the cases and age at data collection is known for the controls. We assessed to what degree and under what conditions Cox proportional

  15. Multiple Imputation of Predictor Variables Using Generalized Additive Models

    NARCIS (Netherlands)

    de Jong, Roel; van Buuren, Stef; Spiess, Martin

    2016-01-01

    The sensitivity of multiple imputation methods to deviations from their distributional assumptions is investigated using simulations, where the parameters of scientific interest are the coefficients of a linear regression model, and values in predictor variables are missing at random. The

  16. SEPARATION PHENOMENA LOGISTIC REGRESSION

    Directory of Open Access Journals (Sweden)

    Ikaro Daniel de Carvalho Barreto

    2014-03-01

    Full Text Available This paper proposes an application of concepts about the maximum likelihood estimation of the binomial logistic regression model to the separation phenomena. It generates bias in the estimation and provides different interpretations of the estimates on the different statistical tests (Wald, Likelihood Ratio and Score and provides different estimates on the different iterative methods (Newton-Raphson and Fisher Score. It also presents an example that demonstrates the direct implications for the validation of the model and validation of variables, the implications for estimates of odds ratios and confidence intervals, generated from the Wald statistics. Furthermore, we present, briefly, the Firth correction to circumvent the phenomena of separation.

  17. Entrepreneurial intention modeling using hierarchical multiple regression

    Directory of Open Access Journals (Sweden)

    Marina Jeger

    2014-12-01

    Full Text Available The goal of this study is to identify the contribution of effectuation dimensions to the predictive power of the entrepreneurial intention model over and above that which can be accounted for by other predictors selected and confirmed in previous studies. As is often the case in social and behavioral studies, some variables are likely to be highly correlated with each other. Therefore, the relative amount of variance in the criterion variable explained by each of the predictors depends on several factors such as the order of variable entry and sample specifics. The results show the modest predictive power of two dimensions of effectuation prior to the introduction of the theory of planned behavior elements. The article highlights the main advantages of applying hierarchical regression in social sciences as well as in the specific context of entrepreneurial intention formation, and addresses some of the potential pitfalls that this type of analysis entails.

  18. Multiple Time Series Ising Model for Financial Market Simulations

    International Nuclear Information System (INIS)

    Takaishi, Tetsuya

    2015-01-01

    In this paper we propose an Ising model which simulates multiple financial time series. Our model introduces the interaction which couples to spins of other systems. Simulations from our model show that time series exhibit the volatility clustering that is often observed in the real financial markets. Furthermore we also find non-zero cross correlations between the volatilities from our model. Thus our model can simulate stock markets where volatilities of stocks are mutually correlated

  19. Logistics planning and logistics planning factors for humanitarian operations

    OpenAIRE

    Sullivan, Donna Marie.

    1995-01-01

    Due to the increasing demand on the military to conduct humanitarian operations, the need for logistics planning factors that are applicable to these operations has arisen. This thesis develops a model for humanitarian operations and employs the model to develop logistics planning factors for material consumption and a computer-assisted planning aid relating to the support of the victim population. U.S. Navy (U.S.N.) author.

  20. Osiris: an object oriented software tool for modelling the logistics, economics and environmental impact of the nuclear fuel cycle

    International Nuclear Information System (INIS)

    Millington, D.N.

    2003-01-01

    Osiris is a general purpose software tool which has been developed for performing studies of material usage, economics and environmental impacts associated with the nuclear fuel cycle. It is particularly suited to the analysis of complex multiple recycling scenarios featuring combinations of both existing and new reactor systems. A discrete event model is used to represent the movement of material batches around the fuel cycle due to the operations and timings of process plants. Nuclear materials are represented by state vectors, which undergo compositional changes due to radioactive decay and irradiation. A library of generic plant types is provided, which are declared and configured in order to represent specific plants. Reactors, front-end and back-end process plants, buffers, stores and material sources can be modelled. Fuel cycle scenarios are then constructed by defining the material flow paths between the plants. The plant parameters and flow paths can be altered dynamically over the course of a scenario in order to represent changes in recycling strategies and retirement and replacement of process plants. Discounted electricity costs can be determined by assigning unit costs to all capital investments, processes and raw materials. Radiotoxicity levels of waste streams can also be evaluated. The software was developed in C++ using objected oriented analysis and design methods. The use of abstraction and inheritance have enabled an open-ended fuel cycle modelling environment to be established, into which new reactor or plant models can readily be integrated. An overview of the object model, numerical modelling assumptions and the design and implementation of the software is presented. (author)