Accuracy of Parameter Estimation in Gibbs Sampling under the Two-Parameter Logistic Model.
Kim, Seock-Ho; Cohen, Allan S.
The accuracy of Gibbs sampling, a Markov chain Monte Carlo procedure, was considered for estimation of item and ability parameters under the two-parameter logistic model. Memory test data were analyzed to illustrate the Gibbs sampling procedure. Simulated data sets were analyzed using Gibbs sampling and the marginal Bayesian method. The marginal…
Vanfleteren, J R; De Vreese, A; Braeckman, B P
1998-11-01
We have fitted Gompertz, Weibull, and two- and three-parameter logistic equations to survival data obtained from 77 cohorts of Caenorhabditis elegans in axenic culture. Statistical analysis showed that the fitting ability was in the order: three-parameter logistic > two-parameter logistic = Weibull > Gompertz. Pooled data were better fit by the logistic equations, which tended to perform equally well as population size increased, suggesting that the third parameter is likely to be biologically irrelevant. Considering restraints imposed by the small population sizes used, we simply conclude that the two-parameter logistic and Weibull mortality models for axenically grown C. elegans generally provided good fits to the data, whereas the Gompertz model was inappropriate in many cases. The survival curves of several short- and long-lived mutant strains could be predicted by adjusting only the logistic curve parameter that defines mean life span. We conclude that life expectancy is genetically determined; the life span-altering mutations reported in this study define a novel mean life span, but do not appear to fundamentally alter the aging process.
An Introduction to the DA-T Gibbs Sampler for the Two-Parameter Logistic (2PL Model and Beyond
Directory of Open Access Journals (Sweden)
Gunter Maris
2005-01-01
Full Text Available The DA-T Gibbs sampler is proposed by Maris and Maris (2002 as a Bayesian estimation method for a wide variety of Item Response Theory (IRT models. The present paper provides an expository account of the DAT Gibbs sampler for the 2PL model. However, the scope is not limited to the 2PL model. It is demonstrated how the DA-T Gibbs sampler for the 2PL may be used to build, quite easily, Gibbs samplers for other IRT models. Furthermore, the paper contains a novel, intuitive derivation of the Gibbs sampler and could be read for a graduate course on sampling.
Directory of Open Access Journals (Sweden)
Ingo W Nader
Full Text Available Parameters of the two-parameter logistic model are generally estimated via the expectation-maximization algorithm, which improves initial values for all parameters iteratively until convergence is reached. Effects of initial values are rarely discussed in item response theory (IRT, but initial values were recently found to affect item parameters when estimating the latent distribution with full non-parametric maximum likelihood. However, this method is rarely used in practice. Hence, the present study investigated effects of initial values on item parameter bias and on recovery of item characteristic curves in BILOG-MG 3, a widely used IRT software package. Results showed notable effects of initial values on item parameters. For tighter convergence criteria, effects of initial values decreased, but item parameter bias increased, and the recovery of the latent distribution worsened. For practical application, it is advised to use the BILOG default convergence criterion with appropriate initial values when estimating the latent distribution from data.
Mirror symmetry for two-parameter models, 1
Candelas, Philip; Font, A; Katz, S; Morrison, Douglas Robert Ogston; Candelas, Philip; Ossa, Xenia de la; Font, Anamaria; Katz, Sheldon; Morrison, David R.
1994-01-01
We study, by means of mirror symmetry, the quantum geometry of the K\\"ahler-class parameters of a number of Calabi-Yau manifolds that have $b_{11}=2$. Our main interest lies in the structure of the moduli space and in the loci corresponding to singular models. This structure is considerably richer when there are two parameters than in the various one-parameter models that have been studied hitherto. We describe the intrinsic structure of the point in the (compactification of the) moduli space that corresponds to the large complex structure or classical limit. The instanton expansions are of interest owing to the fact that some of the instantons belong to families with continuous parameters. We compute the Yukawa couplings and their expansions in terms of instantons of genus zero. By making use of recent results of Bershadsky et al. we compute also the instanton numbers for instantons of genus one. For particular values of the parameters the models become birational to certain models with one parameter. The co...
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 n
Geo-Information Logistical Modeling
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Nikolaj I. Kovalenko
2014-11-01
Full Text Available This paper examines geo-information logistical modeling. The author illustrates the similarities between geo-informatics and logistics in the area of spatial objectives; illustrates that applying geo-data expands the potential of logistics; brings to light geo-information modeling as the basis of logistical modeling; describes the types of geo-information logistical modeling; describes situational geo-information modeling as a variety of geo-information logistical modeling.
Saturated logistic avalanche model
Aielli, G.; Camarri, P.; Cardarelli, R.; Di Ciaccio, A.; Liberti, B.; Paoloni, A.; Santonico, R.
2003-08-01
The search for an adequate avalanche RPC working model evidenced that the simple exponential growth can describe the electron multiplication phenomena in the gas with acceptable accuracy until the external electric field is not perturbed by the growing avalanche. We present here a model in which the saturated growth induced by the space charge effects is explained in a natural way by a constant coefficient non-linear differential equation, the Logistic equation, which was originally introduced to describe the evolution of a biological population in a limited resources environment. The RPCs, due to the uniform and intense field, proved to be an ideal device to test experimentally the presented model.
On modeling of lifetime data using two-parameter Gamma and Weibull distributions
Shanker, Rama; Shukla, Kamlesh Kumar; Shanker, Ravi; Leonida, Tekie Asehun
2016-01-01
The analysis and modeling of lifetime data are crucial in almost all applied sciences including medicine, insurance, engineering, behavioral sciences and finance, amongst others. The main objective of this paper is to have a comparative study of two-parameter gamma and Weibull distributions for mode
Codimension-Two Bifurcation Analysis in Hindmarsh-Rose Model with Two Parameters
Institute of Scientific and Technical Information of China (English)
DUAN Li-Xia; LU Qi-Shao
2005-01-01
@@ Bifurcation phenomena in a Hindmarsh-Rose neuron model are investigated. Special attention is paid to the bifurcation structures off two parameters, where codimension-two generalized-Hopf bifurcation and fold-Hopf bifurcation occur. The classification offiring patterns as well as the transition mechanism in different regions on the parameter plane are obtained.
An EOQ Model with Two-Parameter Weibull Distribution Deterioration and Price-Dependent Demand
Mukhopadhyay, Sushanta; Mukherjee, R. N.; Chaudhuri, K. S.
2005-01-01
An inventory replenishment policy is developed for a deteriorating item and price-dependent demand. The rate of deterioration is taken to be time-proportional and the time to deterioration is assumed to follow a two-parameter Weibull distribution. A power law form of the price dependence of demand is considered. The model is solved analytically…
An Alternative Three-Parameter Logistic Item Response Model.
Pashley, Peter J.
Birnbaum's three-parameter logistic function has become a common basis for item response theory modeling, especially within situations where significant guessing behavior is evident. This model is formed through a linear transformation of the two-parameter logistic function in order to facilitate a lower asymptote. This paper discusses an…
On Calculating the Hougaard Measure of Skewness in a Nonlinear Regression Model with Two Parameters
Directory of Open Access Journals (Sweden)
S. A. EL-Shehawy
2009-01-01
Full Text Available Problem statement: This study presented an alternative computational algorithm for determining the values of the Hougaard measure of skewness as a nonlinearity measure in a Nonlinear Regression model (NLR-model with two parameters. Approach: These values indicated a degree of a nonlinear behavior in the estimator of the parameter in a NLR-model. Results: We applied the suggested algorithm on an example of a NLR-model in which there is a conditionally linear parameter. The algorithm is mainly based on many earlier studies in measures of nonlinearity. The algorithm was suited for implementation using computer algebra systems such as MAPLE, MATLAB and MATHEMATICA. Conclusion/Recommendations: The results with the corresponding output the same considering example will be compared with the results in some earlier studies.
A two-parameter nondiffusive heat conduction model for data analysis in pump-probe experiments
Ma, Yanbao
2014-12-01
Nondiffusive heat transfer has attracted intensive research interests in last 50 years because of its importance in fundamental physics and engineering applications. It has unique features that cannot be described by the Fourier law. However, current studies of nondiffusive heat transfer still focus on studying the effective thermal conductivity within the framework of the Fourier law due to a lack of a well-accepted replacement. Here, we show that nondiffusive heat conduction can be characterized by two inherent material properties: a diffusive thermal conductivity and a ballistic transport length. We also present a two-parameter heat conduction model and demonstrate its validity in different pump-probe experiments. This model not only offers new insights of nondiffusive heat conduction but also opens up new avenues for the studies of nondiffusive heat transfer outside the framework of the Fourier law.
On two-parameter models of photon cross sections: application to dual-energy CT imaging.
Williamson, Jeffrey F; Li, Sicong; Devic, Slobodan; Whiting, Bruce R; Lerma, Fritz A
2006-11-01
The goal of this study is to evaluate the theoretically achievable accuracy in estimating photon cross sections at low energies (20-1000 keV) from idealized dual-energy x-ray computed tomography (CT) images. Cross-section estimation from dual-energy measurements requires a model that can accurately represent photon cross sections of any biological material as a function of energy by specifying only two characteristic parameters of the underlying material, e.g., effective atomic number and density. This paper evaluates the accuracy of two commonly used two-parameter cross-section models for postprocessing idealized measurements derived from dual-energy CT images. The parametric fit model (PFM) accounts for electron-binding effects and photoelectric absorption by power functions in atomic number and energy and scattering by the Klein-Nishina cross section. The basis-vector model (BVM) assumes that attenuation coefficients of any biological substance can be approximated by a linear combination of mass attenuation coefficients of two dissimilar basis substances. Both PFM and BVM were fit to a modern cross-section library for a range of elements and mixtures representative of naturally occurring biological materials (Z = 2-20). The PFM model, in conjunction with the effective atomic number approximation, yields estimated the total linear cross-section estimates with mean absolute and maximum error ranges of 0.6%-2.2% and 1%-6%, respectively. The corresponding error ranges for BVM estimates were 0.02%-0.15% and 0.1%-0.5%. However, for photoelectric absorption frequency, the PFM absolute mean and maximum errors were 10.8%-22.4% and 29%-50%, compared with corresponding BVM errors of 0.4%-11.3% and 0.5%-17.0%, respectively. Both models were found to exhibit similar sensitivities to image-intensity measurement uncertainties. Of the two models, BVM is the most promising approach for realizing dual-energy CT cross-section measurement.
Classifying hospitals as mortality outliers: logistic versus hierarchical logistic models.
Alexandrescu, Roxana; Bottle, Alex; Jarman, Brian; Aylin, Paul
2014-05-01
The use of hierarchical logistic regression for provider profiling has been recommended due to the clustering of patients within hospitals, but has some associated difficulties. We assess changes in hospital outlier status based on standard logistic versus hierarchical logistic modelling of mortality. The study population consisted of all patients admitted to acute, non-specialist hospitals in England between 2007 and 2011 with a primary diagnosis of acute myocardial infarction, acute cerebrovascular disease or fracture of neck of femur or a primary procedure of coronary artery bypass graft or repair of abdominal aortic aneurysm. We compared standardised mortality ratios (SMRs) from non-hierarchical models with SMRs from hierarchical models, without and with shrinkage estimates of the predicted probabilities (Model 1 and Model 2). The SMRs from standard logistic and hierarchical models were highly statistically significantly correlated (r > 0.91, p = 0.01). More outliers were recorded in the standard logistic regression than hierarchical modelling only when using shrinkage estimates (Model 2): 21 hospitals (out of a cumulative number of 565 pairs of hospitals under study) changed from a low outlier and 8 hospitals changed from a high outlier based on the logistic regression to a not-an-outlier based on shrinkage estimates. Both standard logistic and hierarchical modelling have identified nearly the same hospitals as mortality outliers. The choice of methodological approach should, however, also consider whether the modelling aim is judgment or improvement, as shrinkage may be more appropriate for the former than the latter.
Thermodynamic geometry, condensation and Debye model of two-parameter deformed statistics
Mohammadzadeh, Hosein; Azizian-Kalandaragh, Yashar; Cheraghpour, Narges; Adli, Fereshteh
2017-08-01
We consider the statistical distribution function of a two parameter deformed system, namely qp-deformed bosons and fermions. Using a thermodynamic geometry approach, we derive the thermodynamic curvature of an ideal gas with particles obeying qp-bosons and qp-fermions. We show that the intrinsic statistic interaction of qp-bosons is attractive in all physical ranges, while it is repulsive for qp-fermions. Also, the thermodynamic curvature of qp-boson gas is singular at a specified value of fugacity and therefore, a phase transition such as Bose-Einstein condensation can take place. In the following, we compare the experimental and theoretical results of temperature-dependent specific heat capacity of some metallic materials in the framework of q and qp-deformed algebras.
Comparing the Discrete and Continuous Logistic Models
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.)
Comparing the Discrete and Continuous Logistic Models
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.)
A Theoretic Model of Transport Logistics Demand
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Natalija Jolić
2006-01-01
Full Text Available 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 highly qualitative, differentiated and derived.While researching transport phenomenon the implementationof models is inevitable and demand models highly desirable. Asa contribution to transport modelling this paper improves decisionmaking and planning in the transport logistics field.
Two-Parameter Stochastic Resonance in a Model of Electrodissolution of Fe in H2SO4
Institute of Scientific and Technical Information of China (English)
无
2001-01-01
Stochastic resonance (SR) is shown in a two-parameter system, a model of electrodissolution of Fe in H2SO4. Modulation of two different parameters by a periodic signal in one parameter and noise in the other parameter is found to give rise to SR. The result indicates that the noise can enlarge a weak periodic signal and lead the system to order. The scenario and novel aspects of SR in this system are discussed.
Container Logistic Transport Planning Model
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Xin Zhang
2013-05-01
Full Text Available The study proposed a stochastic method of container logistic transport in order to solve the unreasonable transportation’s problem and overcome the traditional models’ two shortcomings. Container transport has rapidly developed into a modern means of transportation because of their significant advantages. With the development, it also exacerbated the flaws of transport in the original. One of the most important problems was that the invalid transport had not still reduced due to the congenital imbalances of transportation. Container transport exacerbated the invalid transport for the empty containers. To solve the problem, people made many efforts, but they did not make much progress. There had two theoretical flaws by analyzing the previous management methods in container transport. The first one was the default empty containers inevitability. The second one was that they did not overall consider how to solve the problem of empty containers allocation. In order to solve the unreasonable transportation’s problem and overcome the traditional models’ two shortcomings, the study re-built the container transport planning model-gravity model. It gave the general algorithm and has analyzed the final result of model.
Two-parameter Failure Model Improves Time-independent and Time-dependent Failure Predictions
Energy Technology Data Exchange (ETDEWEB)
Huddleston, R L
2004-01-27
A new analytical model for predicting failure under a generalized, triaxial stress state was developed by the author and initially reported in 1984. The model was validated for predicting failure under elevated-temperature creep-rupture conditions. Biaxial data for three alloy steels, Types 304 and 316 stainless steels and Inconel 600, demonstrated two to three orders of magnitude reduction in the scatter of predicted versus observed creep-rupture times as compared to the classical failure models of Mises, Tresca, and Rankine. In 1990, the new model was incorporated into American Society of Mechanical Engineers (ASME) Code Case N47-29 for design of components operating under creep-rupture conditions. The current report provides additional validation of the model for predicting failure under time-independent conditions and also outlines a methodology for predicting failure under cyclic, time-dependent, creep-fatigue conditions. The later extension of the methodology may have the potential to improve failure predictions there as well. These results are relevant to most design applications, but they have special relevance to high-performance design applications such as components for high-pressure equipment, nuclear reactors, and jet engines.
Two-parameter Failure Model Improves Time-independent and Time-dependent Failure Predictions
Energy Technology Data Exchange (ETDEWEB)
Huddleston, R L
2004-01-27
A new analytical model for predicting failure under a generalized, triaxial stress state was developed by the author and initially reported in 1984. The model was validated for predicting failure under elevated-temperature creep-rupture conditions. Biaxial data for three alloy steels, Types 304 and 316 stainless steels and Inconel 600, demonstrated two to three orders of magnitude reduction in the scatter of predicted versus observed creep-rupture times as compared to the classical failure models of Mises, Tresca, and Rankine. In 1990, the new model was incorporated into American Society of Mechanical Engineers (ASME) Code Case N47-29 for design of components operating under creep-rupture conditions. The current report provides additional validation of the model for predicting failure under time-independent conditions and also outlines a methodology for predicting failure under cyclic, time-dependent, creep-fatigue conditions. The later extension of the methodology may have the potential to improve failure predictions there as well. These results are relevant to most design applications, but they have special relevance to high-performance design applications such as components for high-pressure equipment, nuclear reactors, and jet engines.
Cook, Paul P
2016-01-01
We investigate two-parameter solutions of sigma-models on two dimensional symmetric spaces contained in E11. Embedding such sigma-model solutions in space-time gives solutions of M* and M'-theory where the metric depends on general travelling wave functions, as opposed to harmonic functions typical in general relativity, supergravity and M-theory. Weyl reflection allows such solutions to be mapped to M-theory solutions where the wave functions depend explicitly on extra coordinates contained in the fundamental representation of E11.
Quantitative Models for Reverse Logistics
M. Fleischmann (Moritz)
2000-01-01
textabstractEconomic, 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 flows o
Quantitative Models for Reverse Logistics
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
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...
Selected Logistics Models and Techniques.
1984-09-01
ACCESS PROCEDURE: On-Line System (OLS), UNINET . RCA maintains proprietary control of this model, and the model is available only through a lease...System (OLS), UNINET . RCA maintains proprietary control of this model, and the model is available only through a lease arrangement. • SPONSOR: ASD/ACCC
Logistics Modeling for Lunar Exploration Systems
Andraschko, Mark R.; Merrill, R. Gabe; Earle, Kevin D.
2008-01-01
The extensive logistics required to support extended crewed operations in space make effective modeling of logistics requirements and deployment critical to predicting the behavior of human lunar exploration systems. This paper discusses the software that has been developed as part of the Campaign Manifest Analysis Tool in support of strategic analysis activities under the Constellation Architecture Team - Lunar. The described logistics module enables definition of logistics requirements across multiple surface locations and allows for the transfer of logistics between those locations. A key feature of the module is the loading algorithm that is used to efficiently load logistics by type into carriers and then onto landers. Attention is given to the capabilities and limitations of this loading algorithm, particularly with regard to surface transfers. These capabilities are described within the context of the object-oriented software implementation, with details provided on the applicability of using this approach to model other human exploration scenarios. Some challenges of incorporating probabilistics into this type of logistics analysis model are discussed at a high level.
Cost Calculation Model for Logistics Service Providers
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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
Linear Logistic Test Modeling with R
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…
Directory of Open Access Journals (Sweden)
Shi Jack J
2012-10-01
the spatial and temporal evolution of the LV wall motion using a two-parameter formulation in conjunction with tMRI-based visualization of the LV wall in the transverse planes of the apex, mid-ventricle and base. In healthy hearts, the analytical model will potentially allow deriving biomechanical entities, such as strain, strain rate or torsion, which are typically used as diagnostic, prognostic or predictive markers of cardiovascular diseases including diabetes.
A dynamic distribution model for combat logistics
Gue, Kevin R.
1999-01-01
New warfare doctrine for the U.S. Marine Corps emphasizes small, highly mobile forces supported from the sea, rather than from large, land based supply points. The goal of logistics planners is to support these forces with as little inventory on land as possible. We show how to configure the land based distribution system over time to support a given battle plan with minimum inventory. Logistics planners could use the model to support tactical or operational decision making.
Energy Technology Data Exchange (ETDEWEB)
Han, Dong, E-mail: radon.han@gmail.com; Williamson, Jeffrey F. [Medical Physics Graduate Program, Department of Radiation Oncology, Virginia Commonwealth University, Richmond, Virginia 23298 (United States); Siebers, Jeffrey V. [Department of Radiation Oncology, University of Virginia, Charlottesville, Virginia 22908 (United States)
2016-01-15
Purpose: To evaluate the accuracy and robustness of a simple, linear, separable, two-parameter model (basis vector model, BVM) in mapping proton stopping powers via dual energy computed tomography (DECT) imaging. Methods: The BVM assumes that photon cross sections (attenuation coefficients) of unknown materials are linear combinations of the corresponding radiological quantities of dissimilar basis substances (i.e., polystyrene, CaCl{sub 2} aqueous solution, and water). The authors have extended this approach to the estimation of electron density and mean excitation energy, which are required parameters for computing proton stopping powers via the Bethe–Bloch equation. The authors compared the stopping power estimation accuracy of the BVM with that of a nonlinear, nonseparable photon cross section Torikoshi parametric fit model (VCU tPFM) as implemented by the authors and by Yang et al. [“Theoretical variance analysis of single- and dual-energy computed tomography methods for calculating proton stopping power ratios of biological tissues,” Phys. Med. Biol. 55, 1343–1362 (2010)]. Using an idealized monoenergetic DECT imaging model, proton ranges estimated by the BVM, VCU tPFM, and Yang tPFM were compared to International Commission on Radiation Units and Measurements (ICRU) published reference values. The robustness of the stopping power prediction accuracy of tissue composition variations was assessed for both of the BVM and VCU tPFM. The sensitivity of accuracy to CT image uncertainty was also evaluated. Results: Based on the authors’ idealized, error-free DECT imaging model, the root-mean-square error of BVM proton stopping power estimation for 175 MeV protons relative to ICRU reference values for 34 ICRU standard tissues is 0.20%, compared to 0.23% and 0.68% for the Yang and VCU tPFM models, respectively. The range estimation errors were less than 1 mm for the BVM and Yang tPFM models, respectively. The BVM estimation accuracy is not dependent on
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......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...
Applying waste logistics modeling to regional planning
Energy Technology Data Exchange (ETDEWEB)
Holter, G.M.; Khawaja, A.; Shaver, S.R.; Peterson, K.L.
1995-05-01
Waste logistics modeling is a powerful analytical technique that can be used for effective planning of future solid waste storage, treatment, and disposal activities. Proper waste management is essential for preventing unacceptable environmental degradation from ongoing operations, and is also a critical part of any environmental remediation activity. Logistics modeling allows for analysis of alternate scenarios for future waste flowrates and routings, facility schedules, and processing or handling capacities. Such analyses provide an increased understanding of the critical needs for waste storage, treatment, transport, and disposal while there is still adequate lead time to plan accordingly. They also provide a basis for determining the sensitivity of these critical needs to the various system parameters. This paper discusses the application of waste logistics modeling concepts to regional planning. In addition to ongoing efforts to aid in planning for a large industrial complex, the Pacific Northwest Laboratory (PNL) is currently involved in implementing waste logistics modeling as part of the planning process for material recovery and recycling within a multi-city region in the western US.
Logistics Chains in Freight Transport Modelling
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 estim
Logistics Chains in Freight Transport Modelling
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
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.
Linear Logistic Test Modeling with R
Directory of Open Access Journals (Sweden)
Purya Baghaei
2014-01-01
Full Text Available 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 applications of the model in test validation, hypothesis testing, cross-cultural studies of test bias, rule-based item generation, and investigating construct irrelevant factors which contribute to item difficulty are explained. The model is applied to an English as a foreign language reading comprehension test and the results are discussed.
Assessing change with the extended logistic model.
Cristante, Francesca; Robusto, Egidio
2007-11-01
The purpose of this article is to define a method for the assessment of change. A reinterpretation of the extended logistic model is proposed. The extended logistic model for the assessment of change (ELMAC) allows the definition of a time parameter which is supposed to identify whether change occurs during a period of time, given a specific event or phenomenon. The assessment of a trend of change through time, on the basis of the time parameter which is estimated at different successive occasions during a period of time, is also considered. In addition, a dispersion parameter is calculated which identifies whether change is consistent at each time point. The issue of independence is taken into account both in relation to the time parameter and the dispersion parameter. An application of the ELMAC in a learning process is presented. The interpretation of the model parameters and the model fit statistics is consistent with expectations.
Delivery Time Reliability Model of Logistics Network
Liusan Wu; Qingmei Tan; Yuehui Zhang
2013-01-01
Natural disasters like earthquake and flood will surely destroy the existing traffic network, usually accompanied by delivery delay or even network collapse. A logistics-network-related delivery time reliability model defined by a shortest-time entropy is proposed as a means to estimate the actual delivery time reliability. The less the entropy is, the stronger the delivery time reliability remains, and vice versa. The shortest delivery time is computed separately based on two different assum...
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.
Generalized Fiducial Inference for Binary Logistic Item Response Models.
Liu, Yang; Hannig, Jan
2016-06-01
Generalized fiducial inference (GFI) has been proposed as an alternative to likelihood-based and Bayesian inference in mainstream statistics. Confidence intervals (CIs) can be constructed from a fiducial distribution on the parameter space in a fashion similar to those used with a Bayesian posterior distribution. However, no prior distribution needs to be specified, which renders GFI more suitable when no a priori information about model parameters is available. In the current paper, we apply GFI to a family of binary logistic item response theory models, which includes the two-parameter logistic (2PL), bifactor and exploratory item factor models as special cases. Asymptotic properties of the resulting fiducial distribution are discussed. Random draws from the fiducial distribution can be obtained by the proposed Markov chain Monte Carlo sampling algorithm. We investigate the finite-sample performance of our fiducial percentile CI and two commonly used Wald-type CIs associated with maximum likelihood (ML) estimation via Monte Carlo simulation. The use of GFI in high-dimensional exploratory item factor analysis was illustrated by the analysis of a set of the Eysenck Personality Questionnaire data.
An Application on Multinomial Logistic Regression Model
Directory of Open Access Journals (Sweden)
Abdalla M El-Habil
2012-03-01
Full Text Available Normal 0 false false false EN-US X-NONE X-NONE This study aims to identify an application of Multinomial Logistic Regression model which is one of the important methods for categorical data analysis. This model deals with one nominal/ordinal response variable that has more than two categories, whether nominal or ordinal variable. This model has been applied in data analysis in many areas, for example health, social, behavioral, and educational.To identify the model by practical way, we used real data on physical violence against children, from a survey of Youth 2003 which was conducted by Palestinian Central Bureau of Statistics (PCBS. Segment of the population of children in the age group (10-14 years for residents in Gaza governorate, size of 66,935 had been selected, and the response variable consisted of four categories. Eighteen of explanatory variables were used for building the primary multinomial logistic regression model. Model had been tested through a set of statistical tests to ensure its appropriateness for the data. Also the model had been tested by selecting randomly of two observations of the data used to predict the position of each observation in any classified group it can be, by knowing the values of the explanatory variables used. We concluded by using the multinomial logistic regression model that we can able to define accurately the relationship between the group of explanatory variables and the response variable, identify the effect of each of the variables, and we can predict the classification of any individual case.
A Theoretic Model of Transport Logistics Demand
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 ...
Delivery Time Reliability Model of Logistics Network
Directory of Open Access Journals (Sweden)
Liusan Wu
2013-01-01
Full Text Available Natural disasters like earthquake and flood will surely destroy the existing traffic network, usually accompanied by delivery delay or even network collapse. A logistics-network-related delivery time reliability model defined by a shortest-time entropy is proposed as a means to estimate the actual delivery time reliability. The less the entropy is, the stronger the delivery time reliability remains, and vice versa. The shortest delivery time is computed separately based on two different assumptions. If a path is concerned without capacity restriction, the shortest delivery time is positively related to the length of the shortest path, and if a path is concerned with capacity restriction, a minimax programming model is built to figure up the shortest delivery time. Finally, an example is utilized to confirm the validity and practicality of the proposed approach.
Energy Technology Data Exchange (ETDEWEB)
Schulze-Halberg, Axel, E-mail: axgeschu@iun.edu, E-mail: xbataxel@gmail.com [Department of Mathematics and Actuarial Science and Department of Physics, Indiana University Northwest, 3400 Broadway, Gary, Indiana 46408 (United States); Wang, Jie, E-mail: wangjie@iun.edu [Department of Computer Information Systems, Indiana University Northwest, 3400 Broadway, Gary, Indiana 46408 (United States)
2015-07-15
We obtain series solutions, the discrete spectrum, and supersymmetric partners for a quantum double-oscillator system. Its potential features a superposition of the one-parameter Mathews-Lakshmanan interaction and a one-parameter harmonic or inverse harmonic oscillator contribution. Furthermore, our results are transferred to a generalized Pöschl-Teller model that is isospectral to the double-oscillator system.
Nowcasting sunshine number using logistic modeling
Brabec, Marek; Badescu, Viorel; Paulescu, Marius
2013-04-01
In this paper, we present a formalized approach to statistical modeling of the sunshine number, binary indicator of whether the Sun is covered by clouds introduced previously by Badescu (Theor Appl Climatol 72:127-136, 2002). Our statistical approach is based on Markov chain and logistic regression and yields fully specified probability models that are relatively easily identified (and their unknown parameters estimated) from a set of empirical data (observed sunshine number and sunshine stability number series). We discuss general structure of the model and its advantages, demonstrate its performance on real data and compare its results to classical ARIMA approach as to a competitor. Since the model parameters have clear interpretation, we also illustrate how, e.g., their inter-seasonal stability can be tested. We conclude with an outlook to future developments oriented to construction of models allowing for practically desirable smooth transition between data observed with different frequencies and with a short discussion of technical problems that such a goal brings.
Analysis of Jingdong Mall Logistics Distribution Model
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.
A Proposed Logistics Career Development Model.
1986-09-01
Both Professor Peppers and Professor Demidovich called for pioneers in logistics dynam- ics. They stated that it was part of every logistics manag- er’s...Force Institute of Technology (AU), Wright-Patterson AFB OH, August 1967 (AD-A824 956). 12. Demidovich , John W. and Jerome G. Peppers, Jr. "The
Characteristics of a Logistics-Based Business Model
Sandberg, Erik; Kihlén, Tobias; Abrahamsson, Mats
2011-01-01
In companies where excellence in logistics is decisive for the outperformance of competitors and logistics has an outspoken role for the strategy of the firm, there is present what we refer to here as a “logistics-based business model.” Based on a multiple case study of three Nordic retail companies, the purpose of this article is to explore the characteristics of such a logistics-based business model. As such, this research helps to provide structure to logistics-based business models and id...
Area Logistics System Based on System Dynamics Model
Institute of Scientific and Technical Information of China (English)
GUI Shouping; ZHU Qiang; LU Lifang
2005-01-01
At present, there are few effective ways to analyze area logistics systems. This paper uses system dynamics to analyze the area logistics system and establishes a system dynamics model for the area logistics system based on the characteristics of the area logistics system and system dynamics. Numerical simulations with the system dynamic model were used to analyze a logistic system. Analysis of the Guangzhou economy shows that the model can reflect the actual state of the system objectively and can be used to make policy and harmonize environment.
Logistics-based Competition : A Business Model Approach
Kihlén, Tobias
2007-01-01
Logistics is increasingly becoming recognised as a source of competitive advantage, both in practice and in academia. The possible strategic impact of logistics makes it important to gain deeper insight into the role of logistics in the strategy of the firm. There is however a considerable research gap between the quite abstract strategy theory and logistics research. A possible tool to use in bridging this gap is identified in business model research. Therefore, the purpose of this dissertat...
Logistic Regression Model on Antenna Control Unit Autotracking Mode
2015-10-20
412TW-PA-15240 Logistic Regression Model on Antenna Control Unit Autotracking Mode DANIEL T. LAIRD AIR FORCE TEST CENTER EDWARDS AFB, CA...OCT 15 4. TITLE AND SUBTITLE Logistic Regression Model on Antenna Control Unit Autotracking Mode 5a. CONTRACT NUMBER 5b. GRANT...alternative-hypothesis. This paper will present an Antenna Auto- tracking model using Logistic Regression modeling. This paper presents an example of
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.
Modeling of Robust Design of Remanufacturing Logistics Networks
Institute of Scientific and Technical Information of China (English)
XIA Shou-chang; XI Li-feng
2005-01-01
The uncertainty of time, quantity and quality of recycling products leads to the bad stability and flexibility of remanufacturing logistics networks, while general design only covers the minimizing logistics cost, so robust design is presented to solve it. The mathematical model of remanufacturing logistics networks is built on the stochastic distribution of uncontrollable factors, and robust objectives are presented. The basic elements of robust design of remanufacturing logistics are redefined, and each part of mathematical model is explained in detail as well. Robust design of remanufacturing logistics networks is a problem of multi-objective optimization in essence.
Combining logistic regression and neural networks to create predictive models.
Spackman, K. A.
1992-01-01
Neural networks are being used widely in medicine and other areas to create predictive models from data. The statistical method that most closely parallels neural networks is logistic regression. This paper outlines some ways in which neural networks and logistic regression are similar, shows how a small modification of logistic regression can be used in the training of neural network models, and illustrates the use of this modification for variable selection and predictive model building wit...
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
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
Logistics chains in freight transport modelling
Davydenko, I.
2015-01-01
The research presented in this PhD thesis has been motivated by the fact that the Netherlands, and the Randstad region in particular, are affected by the large transport flows and extensive operations of the logistics sector. These operations create welfare for those people who work in the sector, w
Correlated noise in a logistic growth model
Ai, Bao-Quan; Wang, Xian-Ju; Liu, Guo-Tao; Liu, Liang-Gang
2003-02-01
The logistic differential equation is used to analyze cancer cell population, in the presence of a correlated Gaussian white noise. We study the steady state properties of tumor cell growth and discuss the effects of the correlated noise. It is found that the degree of correlation of the noise can cause tumor cell extinction.
Logistics chains in freight transport modelling
Davydenko, I.
2015-01-01
The research presented in this PhD thesis has been motivated by the fact that the Netherlands, and the Randstad region in particular, are affected by the large transport flows and extensive operations of the logistics sector. These operations create welfare for those people who work in the sector,
City Logistics Modeling Efforts: Trends and Gaps - A Review
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 se
Parameters Estimation of Geographically Weighted Ordinal Logistic Regression (GWOLR) Model
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.
A Time Scheduling Model of Logistics Service Supply Chain with Mass Customized Logistics Service
Directory of Open Access Journals (Sweden)
Weihua Liu
2012-01-01
Full Text Available With the increasing demand for customized logistics services in the manufacturing industry, the key factor in realizing the competitiveness of a logistics service supply chain (LSSC is whether it can meet specific requirements with the cost of mass service. In this case, in-depth research on the time-scheduling of LSSC is required. Setting the total cost, completion time, and the satisfaction of functional logistics service providers (FLSPs as optimal targets, this paper establishes a time scheduling model of LSSC, which is constrained by the service order time requirement. Numerical analysis is conducted by using Matlab 7.0 software. The effects of the relationship cost coefficient and the time delay coefficient on the comprehensive performance of LSSC are discussed. The results demonstrate that with the time scheduling model in mass-customized logistics services (MCLSs environment, the logistics service integrator (LSI can complete the order earlier or later than scheduled. With the increase of the relationship cost coefficient and the time delay coefficient, the comprehensive performance of LSSC also increases and tends towards stability. In addition, the time delay coefficient has a better effect in increasing the LSSC’s comprehensive performance than the relationship cost coefficient does.
The logistic model-generated carrying capacities for wild herbivores ...
African Journals Online (AJOL)
Jesse
Modelled as discrete-time logistic equations with fixed carrying capacities, it captures the wildlife herbivore population dynamics. Time series data, covering a period ..... Building Models for Conservation and. Wildlife Management. (New York ...
Model and Calculation of Container Port Logistics Enterprises Efficiency Indexes
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Xiao Hong
2013-04-01
Full Text Available The throughput of China’s container port is growing fast, but the earnings of inland port enterprises are not so good. Firstly ,the initial efficiency evaluation indexes of port logistics are reduced and screened by rough set model, and then logistics performance indexes weight are assigned by the rough totalitarian calculation method. As well, the rank of the indexes and the important indexes are picked up by combining with ABC management method. So the port logistics enterprises can monitor the key indexes to reduce cost and improve the efficiency of the logistics operations.
Multivariate Logistic Model to estimate Effective Rainfall for an Event
Singh, S. K.; Patil, Sachin; Bárdossy, A.
2009-04-01
Multivariate logistic models are widely used in biological, medical, and social sciences but logistic models are seldom applied to hydrological problems. A logistic function behaves linear in the mid range and tends to be non-linear as it approaches to the extremes, hence it is more flexible than a linear function and capable of dealing with skew-distributed variables. They seem to bear good potential to handle asymmetrically distributed hydrological variables of extreme occurrence. In this study, logistic regression approach is implemented to derive a multivariate logistic function for effective rainfall; in the process runoff coefficient is assumed to be a Bernoulli-distributed dependent variable. A backward stepwise logistic regression procedure was performed to derive the logistic transfer function between runoff coefficient and catchment as well as event variables (e.g. drainage density, soil moisture etc). The investigation was carried out using data base for 244 rainfall-runoff events from 42 mesoscale catchments located in south-west Germany. The performance of the derived logistic transfer function was compared with that of SCS method for estimation of effective rainfall.
Generalized multidirectional fuzzy map model of the logistics system networks
Ji, Chun-Rong; Liu, Ming-Yuan; Li, Yan; He, Yue M.
1997-07-01
By conducting [0, 1] treatment to time consuming of logistics system network key links, and regarding the time consumed by manufacture, inspection, storage, assembling, packing and market as a kind of existent extent of the joint and the time consumed by materials handling, transportation and logistics information as the connection strength between joints in a generalized multi-directional fuzzy map, a generalized multi-directional fuzzy map model of logistics system networks is built. The mutual flow among network joints and the special form of generalized fuzzy matrix is analyzed. Finally, an example of model building is given.
Modelling mortality of a stored grain insect pest with fumigation: probit, logistic or Cauchy model?
Shi, Mingren; Renton, Michael
2013-06-01
Computer simulation models can provide a relatively fast, safe and inexpensive means to judge and weigh the merits of various pest control management options. However, the usefulness of such simulation models relies on the accurate estimation of important model parameters, such as the pest mortality under different treatments and conditions. Recently, an individual-based simulation model of population dynamics and resistance evolution has been developed for the stored grain insect pest Rhyzopertha dominica, based on experimental results showing that alleles at two different loci are involved in resistance to the grain fumigant phosphine. In this paper, we describe how we used three generalized linear models, probit, logistic and Cauchy models, each employing two- and four-parameter sub-models, to fit experimental data sets for five genotypes for which detailed mortality data was already available. Instead of the usual statistical iterative maximum likelihood estimation, a direct algebraic approach, generalized inverse matrix technique, was used to estimate the mortality model parameters. As this technique needs to perturb the observed mortality proportions if the proportions include 0 or 1, a golden section search approach was used to find the optimal perturbation in terms of minimum least squares (L2) error. The results show that the estimates using the probit model were the most accurate in terms of L2 errors between observed and predicted mortality values. These errors with the probit model ranged from 0.049% to 5.3%, from 0.381% to 8.1% with the logistic model and from 8.3% to 48.2% with the Cauchy model. Meanwhile, the generalized inverse matrix technique achieved similar results to the maximum likelihood estimation ones, but is less time consuming and computationally demanding. We also describe how we constructed a two-parameter model to estimate the mortalities for each of the remaining four genotypes based on realistic genetic assumptions.
Logistics Systems Engineer – Interdisciplinary Competence Model for Modern Education
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Tarvo Niine
2015-05-01
Full Text Available 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 aims to explain the situation from the conceptual development point of view and suggests a competence profile for “logistics system engineer”, which introduces the viewpoint of systems engineering into logistics. For that purpose, the paper analyses requirements of various topical competence models and merges the introductory competences of systems engineering into logistics. In current interpretation, logistics systems engineering view integrates networks, technologies and ICT, process and service design and offers broader interdisciplinary approach. Another term suitable for this field would be intelligent logistics. The practical implication of such a competence profile is to utilize it in curriculum development and also present it as an occupational standard. The academic relevance of such concept is to offer a specific way to differentiate education in logistics.
The Logistic Maturity Model: Application to a Fashion Company
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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.
A Dynamic Distribution Model for Combat Logistics
1999-11-23
develop a heuristic algorithm for a similar problem, only capacity expansion can occur in any amount (modeled with continuous variables) while in...and Rutenberg (1977) solve it with a heuristic algorithm . Our problem is also related to the dynamic facility location problem. This problem seeks to
An Optimization Model for Aircraft Service Logistics
Institute of Scientific and Technical Information of China (English)
Angus; Cheung; W; H; Ip; Angel; Lai; Eva; Cheung
2002-01-01
Scheduling is one of the most difficult issues in t he planning and operations of the aircraft services industry. In this paper, t he various scheduling problems in ground support operation of an aircraft mainte nance service company are addressed. The authors developed a set of vehicle rout ings to cover each schedule flights; the objectives pursued are the maximization of vehicle and manpower utilization and minimization of operation time. To obta in the goals, an integer-programming model with geneti...
Credit Scoring Model Hybridizing Artificial Intelligence with Logistic Regression
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Han Lu
2013-01-01
Full Text Available Today the most commonly used techniques for credit scoring are artificial intelligence and statistics. In this paper, we started a new way to use these two kinds of models. Through logistic regression filters the variables with a high degree of correlation, artificial intelligence models reduce complexity and accelerate convergence, while these models hybridizing logistic regression have better explanations in statistically significance, thus improve the effect of artificial intelligence models. With experiments on German data set, we find an interesting phenomenon defined as ‘Dimensional interference’ with support vector machine and from cross validation it can be seen that the new method gives a lot of help with credit scoring.
Modeling urban expansion by using variable weights logistic cellular automata
Shu, Bangrong; Bakker, Martha M.; Zhang, Honghui; Li, Yongle; Qin, Wei; Carsjens, Gerrit J.
2017-01-01
Simulation models based on cellular automata (CA) are widely used for understanding and simulating complex urban expansion process. Among these models, logistic CA (LCA) is commonly adopted. However, the performance of LCA models is often limited because the fixed coefficients obtained from binary
Renormalizable two-parameter piecewise isometries.
Lowenstein, J H; Vivaldi, F
2016-06-01
We exhibit two distinct renormalization scenarios for two-parameter piecewise isometries, based on 2π/5 rotations of a rhombus and parameter-dependent translations. Both scenarios rely on the recently established renormalizability of a one-parameter triangle map, which takes place if and only if the parameter belongs to the algebraic number field K=Q(5) associated with the rotation matrix. With two parameters, features emerge which have no counterpart in the single-parameter model. In the first scenario, we show that renormalizability is no longer rigid: whereas one of the two parameters is restricted to K, the second parameter can vary continuously over a real interval without destroying self-similarity. The mechanism involves neighbouring atoms which recombine after traversing distinct return paths. We show that this phenomenon also occurs in the simpler context of Rauzy-Veech renormalization of interval exchange transformations, here regarded as parametric piecewise isometries on a real interval. We explore this analogy in some detail. In the second scenario, which involves two-parameter deformations of a three-parameter rhombus map, we exhibit a weak form of rigidity. The phase space splits into several (non-convex) invariant components, on each of which the renormalization still has a free parameter. However, the foliations of the different components are transversal in parameter space; as a result, simultaneous self-similarity of the component maps requires that both of the original parameters belong to the field K.
Data Logistics and the CMS Analysis Model
Managan, Julie E
2009-01-01
The Compact Muon Solenoid Experiment (CMS) at the Large Hadron Collider (LHC) at CERN has brilliant prospects for uncovering new information about the physical structure of our universe. Soon physicists around the world will participate together in analyzing CMS data in search of new physics phenomena and the Higgs Boson. However, they face a significant problem: with 5 Petabytes of data needing distribution each year, how will physicists get the data they need? How and where will they be able to analyze it? Computing resources and scientists are scattered around the world, while CMS data exists in localized chunks. The CMS computing model only allows analysis of locally stored data, “tethering” analysis to storage. The Vanderbilt CMS team is actively working to solve this problem with the Research and Education Data Depot Network (REDDnet), a program run by Vanderbilt’s Advanced Computing Center for Research and Education (ACCRE). The Compact Muon Solenoid Experiment (CMS) at the Large Hadron Collider ...
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.
Applications of the Linear Logistic Test Model in Psychometric Research
Kubinger, Klaus D.
2009-01-01
The linear logistic test model (LLTM) breaks down the item parameter of the Rasch model as a linear combination of some hypothesized elementary parameters. Although the original purpose of applying the LLTM was primarily to generate test items with specified item difficulty, there are still many other potential applications, which may be of use…
Modeling logistic performance in quantitative microbial risk assessment.
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.
General collision branching processes with two parameters
Institute of Scientific and Technical Information of China (English)
CHEN AnYue; LI JunPing
2009-01-01
A new class of branching models, the general collision branching processes with two parameters, is considered in this paper. For such models, it is necessary to evaluate the absorbing probabilities and mean extinction times for both absorbing states. Regularity and uniqueness criteria are firstly established. Explicit expressions are then obtained for the extinction probability vector, the mean extinction times and the conditional mean extinction times. The explosion behavior of these models is investigated and an explicit expression for mean explosion time is established. The mean global holding time is also obtained. It is revealed that these properties are substantially different between the super-explosive and sub-explosive cases.
Flower Power: Sunflowers as a Model for Logistic Growth
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,…
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.
An e-Procurement Model for Logistic Performance Increase
Toma, Cristina; Vasilescu, Bogdan; Popescu, Catalin; Soliman, KS
2009-01-01
This paper discusses the suitability of an e-procurement system in increasing logistic performance, given the growth in fast Internet availability,. In consequence, a model is derived and submitted for analysis. The scope of the research is limited at the intermediary goods importing sector for a be
Logistics Enterprise Evaluation Model Based On Fuzzy Clustering Analysis
Fu, Pei-hua; Yin, Hong-bo
In this thesis, we introduced an evaluation model based on fuzzy cluster algorithm of logistics enterprises. First of all,we present the evaluation index system which contains basic information, management level, technical strength, transport capacity,informatization level, market competition and customer service. We decided the index weight according to the grades, and evaluated integrate ability of the logistics enterprises using fuzzy cluster analysis method. In this thesis, we introduced the system evaluation module and cluster analysis module in detail and described how we achieved these two modules. At last, we gave the result of the system.
Logistic regression for risk factor modelling in stuttering research.
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.
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.
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.
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
On modified skew logistic regression model and its applications
Directory of Open Access Journals (Sweden)
C. Satheesh Kumar
2015-12-01
Full Text Available Here we consider a modiﬁed form of the logistic regression model useful for situations where the dependent variable is dichotomous in nature and the explanatory variables exhibit asymmetric and multimodal behaviour. The proposed model has been ﬁtted to some real life data set by using method of maximum likelihood estimation and illustrated its usefulness in certain medical applications.
Consumer Choice Prediction: Artificial Neural Networks versus Logistic Models
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Christopher Gan
2005-01-01
Full Text Available Conventional econometric models, such as discriminant analysis and logistic regression have been used to predict consumer choice. However, in recent years, there has been a growing interest in applying artificial neural networks (ANN to analyse consumer behaviour and to model the consumer decision-making process. The purpose of this paper is to empirically compare the predictive power of the probability neural network (PNN, a special class of neural networks and a MLFN with a logistic model on consumers choices between electronic banking and non-electronic banking. Data for this analysis was obtained through a mail survey sent to 1,960 New Zealand households. The questionnaire gathered information on the factors consumers use to decide between electronic banking versus non-electronic banking. The factors include service quality dimensions, perceived risk factors, user input factors, price factors, service product characteristics and individual factors. In addition, demographic variables including age, gender, marital status, ethnic background, educational qualification, employment, income and area of residence are considered in the analysis. Empirical results showed that both ANN models (MLFN and PNN exhibit a higher overall percentage correct on consumer choice predictions than the logistic model. Furthermore, the PNN demonstrates to be the best predictive model since it has the highest overall percentage correct and a very low percentage error on both Type I and Type II errors.
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.
Stochastic growth logistic model with aftereffect for batch fermentation process
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.
Short-Run Asset Selection using a Logistic Model
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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.
SpaceNet: Modeling and Simulating Space Logistics
Lee, Gene; Jordan, Elizabeth; Shishko, Robert; de Weck, Olivier; Armar, Nii; Siddiqi, Afreen
2008-01-01
This paper summarizes the current state of the art in interplanetary supply chain modeling and discusses SpaceNet as one particular method and tool to address space logistics modeling and simulation challenges. Fundamental upgrades to the interplanetary supply chain framework such as process groups, nested elements, and cargo sharing, enabled SpaceNet to model an integrated set of missions as a campaign. The capabilities and uses of SpaceNet are demonstrated by a step-by-step modeling and simulation of a lunar campaign.
SpaceNet: Modeling and Simulating Space Logistics
Lee, Gene; Jordan, Elizabeth; Shishko, Robert; de Weck, Olivier; Armar, Nii; Siddiqi, Afreen
2008-01-01
This paper summarizes the current state of the art in interplanetary supply chain modeling and discusses SpaceNet as one particular method and tool to address space logistics modeling and simulation challenges. Fundamental upgrades to the interplanetary supply chain framework such as process groups, nested elements, and cargo sharing, enabled SpaceNet to model an integrated set of missions as a campaign. The capabilities and uses of SpaceNet are demonstrated by a step-by-step modeling and simulation of a lunar campaign.
Sustainable Logistics Network Modeling for Enterprise Supply Chain
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Lan Zhu
2017-01-01
Full Text Available With the expansion of the study about green logistics, sustainable supply chain management (SSCM has appeared as a new concept in current economic circumstance. This paper studies the sustainability optimization of enterprise logistics network from a strategic perspective and proposes a multiobjective sustainable logistics optimization model considering three dimensions of sustainability: economy, environment, and society. In this model, the environment factor was measured with a Life Cycle Assessment (LCA method based on Chinese Life Cycle Database (CLCD, while for social factors, Sustainability Reporting Guidelines (GRI are utilized to quantify the social performance. Moreover, the model was solved with an adapted version of the ε-constraint method named augment constraint algorithm (AUGMENCON through GAMS software. The numerical experiment results of a computer manufacturer supply chain show that the proposed model is able to integrate all dimensions of sustainability and simultaneously prove the capability of AUGMENCON in providing a set of trade-off solutions for the decision makers to make different decisions under different environment and social requirements.
Comparison of particular logistic models' adoption in the Czech Republic
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.
带线性约束的新两参数估计%New Two Parameters Estimation for the Linear Model with Linear Restrictions
Institute of Scientific and Technical Information of China (English)
郭淑妹; 顾勇为; 郭杰
2013-01-01
针对带约束的最小二乘估计在参数估计中处理复共线性的不足，引入随机线性约束，提出了约束新两参数估计。并且得到在均方误差下，约束新两参数估计与约束最小二乘估计，约束岭估计和约束Liu估计相比的优良性。%In order to overcome the shortage of the multicollinearity in ordinary restricted least square estimation with parameter estimate based on the stochastic linear restrictions,a new estimation as restricted linear new two parameters estimation is proposed. In the mean squared error sense,compared with the properties the ordinary restricted least squares estimation,and the restricted ridge estimation,the method we proposed was superior.
The logistic, two-sex, age-structured population model.
Yang, Kai; Milner, Fabio
2009-03-01
In this paper, we introduce the logistic effect into the two-sex population model introduced by Hoppensteadt. We address the problem of existence and uniqueness of continuous and classical solutions. We first give sufficient conditions for a unique continuous solution to exist locally and also globally. Next, the existence of classical solutions is established under some mild assumptions on the vital rates. Finally, we study the existence of equilibria and give an upper bound for the total population at steady state.
APPLYING LOGISTIC REGRESSION MODEL TO THE EXAMINATION RESULTS DATA
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Goutam Saha
2011-01-01
Full Text Available The binary logistic regression model is used to analyze the school examination results(scores of 1002 students. The analysis is performed on the basis of the independent variables viz.gender, medium of instruction, type of schools, category of schools, board of examinations andlocation of schools, where scores or marks are assumed to be dependent variables. The odds ratioanalysis compares the scores obtained in two examinations viz. matriculation and highersecondary.
Accessibility to Nodes of Interest: Demographic Weighting the Logistic Model
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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.
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...
General collision branching processes with two parameters
Institute of Scientific and Technical Information of China (English)
2009-01-01
A new class of branching models,the general collision branching processes with two parameters,is considered in this paper.For such models,it is necessary to evaluate the absorbing probabilities and mean extinction times for both absorbing states.Regularity and uniqueness criteria are firstly established.Explicit expressions are then obtained for the extinction probability vector,the mean extinction times and the conditional mean extinction times.The explosion behavior of these models is investigated and an explicit expression for mean explosion time is established.The mean global holding time is also obtained.It is revealed that these properties are substantially different between the super-explosive and sub-explosive cases.
Sugarcane Land Classification with Satellite Imagery using Logistic Regression Model
Henry, F.; Herwindiati, D. E.; Mulyono, S.; Hendryli, J.
2017-03-01
This paper discusses the classification of sugarcane plantation area from Landsat-8 satellite imagery. The classification process uses binary logistic regression method with time series data of normalized difference vegetation index as input. The process is divided into two steps: training and classification. The purpose of training step is to identify the best parameter of the regression model using gradient descent algorithm. The best fit of the model can be utilized to classify sugarcane and non-sugarcane area. The experiment shows high accuracy and successfully maps the sugarcane plantation area which obtained best result of Cohen’s Kappa value 0.7833 (strong) with 89.167% accuracy.
Decision support modeling for sustainable food logistics management
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 challenges of
Decision support modeling for sustainable food logistics management
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 challenges of
Directory of Open Access Journals (Sweden)
Ying Qiu
2015-05-01
Full Text Available Purpose: We attempted to propose an approach to simulate the dynamics of Beijing’s logistics demand, which can do some help to find out the dynamics path of the needed storage and shipment, put forward with logistics policies and enhance logistics service. Design/methodology/approach: We present a paper with system dynamics (SD methodology, which was run by the software of Vensim®. Findings: With SD model, causal loop diagram and stock and flow diagram are constructed, as well as some experiments and policy analysis. The research findings revealed that the increase of average shipping capacity for a vehicle will bring a decrease in congestion and CO2 emission directly and the decrease of the average fuel use for a vehicle can help with the reduction of CO2 emission directly. Both the two parameters are the indirect causes of logistics demand dynamics in Beijing. Originality/value: Researches of this paper are aiming at handling logistics demand dynamics of Beijing, problems belonging to the area of complex systems, with SD model, where, to the best of our knowledge, no significant research has been done.
Decision support modeling for sustainable food logistics management
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 challenges of reducing the amount of food waste and raising energy efficiency to reduce greenhouse gas emissions. These additional challenges add to the complexity of logistics operations and require advanced de...
Modeling risk and uncertainty in designing reverse logistics problem
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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.
A Cost Model for Integrated Logistic Support Activities
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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.
A logistics model for large space power systems
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
Institute of Scientific and Technical Information of China (English)
Wenfeng; YANG
2015-01-01
Over the years,the logistics development in Tibet has fallen behind the transport. Since the opening of Qinghai-Tibet Railway in2006,the opportunity for development of modern logistics has been brought to Tibet. The logistics demand analysis and forecasting is a prerequisite for regional logistics planning. By establishing indicator system for logistics demand of agricultural products,agricultural product logistics principal component regression model,gray forecasting model,BP neural network forecasting model are built. Because of the single model’s limitations,quadratic-linear programming model is used to build combination forecasting model to predict the logistics demand scale of agricultural products in Tibet over the next five years. The empirical analysis results show that combination forecasting model is superior to single forecasting model,and it has higher precision,so combination forecasting model will have much wider application foreground and development potential in the field of logistics.
The formation models logistics management systems product distribution company
Palchyk, Ihor
2014-01-01
In the article describes the peculiarities of the management of the logistics systems, levels of logistic management. Formed scheme logistics-grid companies on the basis of different distribution channels and options sales - the sale of goods by the manufacturer (direct sales) and sales of goods intermediaries. The proposed direction (stages) management of the logistics system of the distribution system associated with the use of the individual management functions. Built client-oriented mode...
Two logistic models for the prediction of hypothyroidism in pregnancy.
Mbah, Anthony U; Ejim, Emmanuel C; Onodugo, Obinna D; Ezugwu, Francis O; Eze, Matthew I; Nkwo, Peter O; Ugbajah, Winston C
2011-06-18
The mounting evidence linking hypothyroidism during pregnancy with poor pregnancy outcome underscores the need for screening and, therefore, a search for more reliable and cheaper screening methods. The study was conducted in two phases. The phase one study comprised of healthy women in different stages of pregnancy who attended routine antenatal clinic at St Theresa's Maternity Hospital, Enugu, Nigeria from September 6 to October 18 1994. In this study the variables compared between the hypothyroid and non-hypothyroid pregnant women were maternal age, the number of the pregnancy or gravidity, gestational age, social class, body weight, height, the clinically assessed size of the thyroid gland, serum free thyroxin (FT4) and serum thyrotrophin (TSH). Based on the parameter differences between the two comparison groups of pregnant women two Logistic models, Model I and Model 11, were derived to differentiate the hypothyroid group from their non-hypothyroid counterparts. The two logistic models were then applied in a prospective validation study involving 197 pregnant women seen at presentation in Mother of Christ Specialist Hospital and Maternity, Ogui Road, Enugu from March 2002 to November 2007 The findings were that 82 (50.3%) of the 163 pregnant women had thyroid gland enlargement while 60 (36.8%) had hypothyroidism as defined by FT4 values below and/or TSH above their laboratory reference ranges. The pregnant subjects with hypothyroidism, compared with their non-hypothyroid counterparts, were characterized by a higher gravidity (p hypothyroidism during pregnancy. There is, however, a need for further independent confirmation of these findings.
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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.
Airport Logistics : Modeling and Optimizing the Turn-Around Process
Norin, Anna
2008-01-01
The focus of this licentiate thesis is air transportation and especially the logistics at an airport. The concept of airport logistics is investigated based on the following definition: Airport logistics is the planning and control of all resources and information that create a value for the customers utilizing the airport. As a part of the investigation, indicators for airport performance are considered. One of the most complex airport processes is the turn-around process. The turn-around is...
Research on Technological Process Control Model of Reverse Logistics in Manufacturing System
Institute of Scientific and Technical Information of China (English)
CHANG Jiane; LIU Chao
2006-01-01
This paper has found out some important input factors of reverse logistics in manufacturing system throuth analysis and summary, and established four kinds of technological process control models of reverse logistics in manufacturing system according to different processing methods. These models embed each other that form a cubic control system of reverse logistics.
Mirror symmetry for two parameter models, 2
Candelas, Philip; Katz, S; Morrison, Douglas Robert Ogston; Philip Candelas; Anamaria Font; Sheldon Katz; David R Morrison
1994-01-01
We describe in detail the space of the two K\\"ahler parameters of the Calabi--Yau manifold \\P_4^{(1,1,1,6,9)}[18] by exploiting mirror symmetry. The large complex structure limit of the mirror, which corresponds to the classical large radius limit, is found by studying the monodromy of the periods about the discriminant locus, the boundary of the moduli space corresponding to singular Calabi--Yau manifolds. A symplectic basis of periods is found and the action of the Sp(6,\\Z) generators of the modular group is determined. From the mirror map we compute the instanton expansion of the Yukawa couplings and the generalized N=2 index, arriving at the numbers of instantons of genus zero and genus one of each degree. We also investigate an SL(2,\\Z) symmetry that acts on a boundary of the moduli space.
A logistical model for performance evaluations of hybrid generation systems
Energy Technology Data Exchange (ETDEWEB)
Bonanno, F.; Consoli, A.; Raciti, A. [Univ. of Catania (Italy). Dept. of Electrical, Electronic, and Systems Engineering; Lombardo, S. [Schneider Electric SpA, Torino (Italy)
1998-11-01
In order to evaluate the fuel and energy savings, and to focus on the problems related to the exploitation of combined renewable and conventional energies, a logistical model for hybrid generation systems (HGS`s) has been prepared. A software package written in ACSL, allowing easy handling of the models and data of the HGS components, is presented. A special feature of the proposed model is that an auxiliary fictitious source is introduced in order to obtain the power electric balance at the busbars during the simulation state and, also, in the case of ill-sized components. The observed imbalance powers are then used to update the system design. As a case study, the simulation program is applied to evaluate the energetic performance of a power plant relative to a small isolated community, and island in the Mediterranean Sea, in order to establish the potential improvement achievable via an optimal integration of renewable energy sources in conventional plants. Evaluations and comparisons among different-sized wind, photovoltaic, and diesel groups, as well as of different management strategies have been performed using the simulation package and are reported and discussed in order to present the track followed to select the final design.
A Review on Quantitative Models for Sustainable Food Logistics Management
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
A Model for Logistics Systems Engineering Management Education in Europe.
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)
The Analysis of Several Models of Investment Value of Logistics Project Evaluation
Directory of Open Access Journals (Sweden)
Ke Qiu Cheng Zhou
2013-01-01
Full Text Available The study of the logistics project evaluation model features reviews the traditional value evaluation model. On the basis of this, using the fuzzy theory, we establish several logistics project evaluation models under fuzzy environment. The analysis of the respective characteristics and the comparison of the calculated results of the three models show that these models are important methods of investment value of logistics evaluation.
Sustainable theory of a logistic model - Fisher information approach.
Al-Saffar, Avan; Kim, Eun-Jin
2017-03-01
Information theory provides a useful tool to understand the evolution of complex nonlinear systems and their sustainability. In particular, Fisher information has been evoked as a useful measure of sustainability and the variability of dynamical systems including self-organising systems. By utilising Fisher information, we investigate the sustainability of the logistic model for different perturbations in the positive and/or negative feedback. Specifically, we consider different oscillatory modulations in the parameters for positive and negative feedback and investigate their effect on the evolution of the system and Probability Density Functions (PDFs). Depending on the relative time scale of the perturbation to the response time of the system (the linear growth rate), we demonstrate the maintenance of the initial condition for a long time, manifested by a broad bimodal PDF. We present the analysis of Fisher information in different cases and elucidate its implications for the sustainability of population dynamics. We also show that a purely oscillatory growth rate can lead to a finite amplitude solution while self-organisation of these systems can break down with an exponentially growing solution due to the periodic fluctuations in negative feedback. Copyright © 2017 Elsevier Inc. All rights reserved.
The Hamilton depression scale. Evaluation of objectivity using logistic models.
Bech, P; Allerup, P; Gram, L F; Reisby, N; Rosenberg, R; Jacobsen, O; Nagy, A
1981-03-01
The consistency of the Hamilton Depression Scale (HDS) as a measure of the severity of depressive states has been examined when the scale was used weekly during a trial when imipramine. By use of logistic models (Rasch) the consistency of the HDS has been considered across patient-variables as age, sex, plasma levels of imipramine, and diagnosis. The results showed that the original 17-item HDS was without adequate consistency, i.e. the total score of the sample of items was no one-dimensional measure of depressive states. However, a melancholia subscale of the HDS contained items the total of which can be used to compare patients quantitatively, although in some part of the analysis one of these items showed ceiling effect. It was concluded that the melancholia subscale (containing the items depressed mood, guilt, work and interests, retardation, psychic anxiety, and general somatic symptoms) can form the basis for further improvements in the field of quantitative rating scales for depressive states.
MODELING SNAKE MICROHABITAT FROM RADIOTELEMETRY STUDIES USING POLYTOMOUS LOGISTIC REGRESSION
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 ...
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.
Linear and logistic models with time dependent coefficients
Directory of Open Access Journals (Sweden)
Youness Mir
2016-01-01
Full Text Available We sutdy the effects of some properties of the carrying capacity on the solution of the linear and logistic differential equations. We present results concerning the behaviour and the asymptotic behaviour of their solutions. Special attention is paid when the carrying capacity is an increasing or a decreasing positive function. For more general carrying capacity, we obtain bounds for the corresponding solution by constructing appropriate subsolution and supersolution. We also present a decomposition of the solution of the linear, and logistic, differential equation as a product of the carrying capacity and the solution to the corresponding differential equation with a constant carrying capacity.
A Note on the Item Information Function of the Four-Parameter Logistic Model
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…
A Note on the Item Information Function of the Four-Parameter Logistic Model
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…
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.
Network Design in Reverse Logistics: A Quantitative Model
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
Evaluation of city logistics solutions with business model analysis
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 demonstration
A Cloud Computing Model for Optimization of Transport Logistics Process
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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.
Evaluation of city logistics solutions with business model analysis
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
DeAyala, R. J.; Koch, William R.
A nominal response model-based computerized adaptive testing procedure (nominal CAT) was implemented using simulated data. Ability estimates from the nominal CAT were compared to those from a CAT based upon the three-parameter logistic model (3PL CAT). Furthermore, estimates from both CAT procedures were compared with the known true abilities used…
Risk Evaluation on Logistics Finance of Agricultural Products Based on Fuzzy-AHP Model
Institute of Scientific and Technical Information of China (English)
Yan; PANG; Yangkun; XIA
2015-01-01
The development of logistics finance business for agricultural products is the best way to realize the common interests of logistics enterprises,small and medium-sized agricultural product enterprises and financial institutions,which will contribute to the development of China’s new socialist rural economy and the construction of " two-oriented society". As the agricultural products have some special attributes,it’s easy to create the risk in carrying out the logistics finance business. The paper constructs a risk evaluation indicator system for logistics finance of agricultural product,and uses the Fuzzy-AHP model to evaluate. The results show that the comprehensive risk level is normal risk,which shows that third-party logistics enterprises can carry out the logistics financial business of agricultural products,but the risks from logistics enterprises and agricultural collateral need to be prevented.
Unification of the Two-Parameter Equation of State and the Principle of Corresponding States
DEFF Research Database (Denmark)
Mollerup, Jørgen
1998-01-01
A two-parameter equation of state is a two-parameter corresponding states model. A two-parameter corresponding states model is composed of two scale factor correlations and a reference fluid equation of state. In a two-parameter equation of state the reference equation of state is the two......-parameter equation of state itself. If we retain the scale factor correlations derived from a two-parameter equation of state, but replace the two-parameter equation of state with a more accurate pure component equation of state for the reference fluid, we can improve the existing models of equilibrium properties...... without refitting any model parameters, and without imposing other restrictions as regards to species and mixing rules as already imposed by the two-parameter equation of state. The theory and procedure is outlined in the paper....
An innovative business model based on the integration of finance and logistics operations
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Zhao Daozhi
2012-11-01
Full Text Available This article advances a new logistics financing model based on the notes receivable. This is a written promise to receive a stated amount of money in future. The article describes the structure and key processes of the model, and analyses the roles of the involved stakeholders. In order to enhance understanding, the article compares the model with a loan financing model, establishes a game model based on logistics enterprise financing, studies the strategies in the process of investment and financing, and concludes by defining its feasible region. This involves comparing the expected net revenues of different stakeholders in the two models. Based on the results, the paper analyses the financing process of a logistics enterprise in Shanghai and determines the optimal financing strategy. This paper is an attempt to improve business innovation in logistics financing and provides a sensible solution for the integrated logistics and finance services. This can effectively improve the stakeholders’ profit.
SPD-based Logistics Management Model of Medical Consumables in Hospitals.
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.
SPD-based Logistics Management Model of Medical Consumables in Hospitals
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Tongzhu LIU
2016-10-01
Full Text Available 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.
A Flexible Logistics Distribution Hub Model considering Cost Weighted Time
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Wenxue Ran
2017-01-01
Full Text Available The delivery time of order has become an important fact for customers to evaluate logistics services. Due to the diverse and large quantities of orders in the background of electronic commerce, how to improve the flexibility of distribution hub and reduce the waiting time of customers becomes one of the most challenging questions for logistics companies. With this in mind, this paper proposes a new method of flexibility assessment in distribution hub by introducing cost weighted time (CWT. The advantages of supply hub operation mode in delivery flexibility are verified by the approach: the mode has pooling effects and uniform distribution characteristics; these traits can reduce overlapping delivery time to improve the flexibility in the case of two suppliers. Numerical examples show that the supply hub operation mode is more flexible than decentralized distribution operation mode in multidelivery cycles.
Logistic regression models of factors influencing the location of bioenergy and biofuels plants
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...
The example of modeling of logistics processes using differential equations
Ryczyński, Jacek
2017-07-01
The article describes the use of differential calculus to determine the form of differential equations family of curves. Form of differential equations obtained by eliminating the parameters of the equations describing the different family of curves. Elimination of the parameters has been performed several times by differentiation starting equations. Received appropriate form of differential equations for the case of family circles, family of curves of the second degree and the families of the logistic function.
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A. Calzado
2013-04-01
Full Text Available Aim of study: The aim of this work was to model diameter distributions of Quercus suber stands. The ultimate goal was to construct models enabling the development of more affordable forest inventory methods. This is the first study of this type on cork oak forests in the area.Area of study: The area of study is “Los Alcornocales” Natural Park (Cádiz-Málaga, Spain.Material and methods: The diameter distributions of 100 permanent plots were modelled with the two-parameter Weibull function. Distribution parameters were fitted with the non-linear regression, maximum likelihood, moment and percentile-based methods. Goodness of fit with the different methods was compared in terms of number of plots rejected by the Kolmogorov-Smirnov test, bias, mean square error and mean absolute error. The scale and shape parameters in the Weibull function were related to the stand variables by using the parameter prediction model.Main results: The best fitting was obtained with the non-linear regression approach, using as initial values those obtained by maximum likelihood method, the percentage of rejections by the Kolmogorov-Smirnov test was 2% of the total number of cases. The scale parameter (b was successfully modelled in terms of the quadratic mean diameter under cork (R2 adj = 0.99. The shape parameter (c was modelled by using maximum diameter, minimum diameter and plot elevation (R2 adj = 0.40.Research highlights: The proposed model diameter distribution can be a highly useful tool for the inventorying and management of cork oak forests.Key words: maximum likelihood method; moment method; non linear regression approach; parameter prediction model; percentile method; scale parameter; shape parameter.
Logistic distributed activation energy model--Part 1: Derivation and numerical parametric study.
Cai, Junmeng; Jin, Chuan; Yang, Songyuan; Chen, Yong
2011-01-01
A new distributed activation energy model is presented using the logistic distribution to mathematically represent the pyrolysis kinetics of complex solid fuels. A numerical parametric study of the logistic distributed activation energy model is conducted to evaluate the influences of the model parameters on the numerical results of the model. The parameters studied include the heating rate, reaction order, frequency factor, mean of the logistic activation energy distribution, standard deviation of the logistic activation energy distribution. The parametric study addresses the dependence on the forms of the calculated α-T and dα/dT-T curves (α: reaction conversion, T: temperature). The study results would be very helpful to the application of the logistic distributed activation energy model, which is the main subject of the next part of this series.
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...
Understanding logistics-based competition in retail : a business model perspective
Sandberg, Erik
2013-01-01
Purpose – Logistics scholars, as well as strategic management scholars, have in recent years shown that capabilities in logistics and supply chain management may be the foundation for a company's sustainable competitive advantage. It can be argued that beside product-, production-, or market-oriented companies, there are also flow-oriented companies, in which the business models are based on superior logistics performance. The purpose of this study is to explore the characteristics of logisti...
Conceptual grounds of modelling and managing logistics risk of an enterprise
Vitlinskyy Valdemar V.; Skitsko Volodymyr I.
2013-01-01
The article considers theoretical and methodological problems on managing and modelling logistics risk of an enterprise. It shows that managerial decisions in logistics are made in situations, which are characterised with: uncertainty and randomness of results of the risky activity; conflict; counteraction; multi-variance of solution; when simultaneously not all alternative variants of solutions are similarly favourable. The article analyses existing approaches to definition of the "logistics...
A MULTI-PRODUCT AND MULTI-PERIOD FACILITY LOCATION MODEL FOR REVERSE LOGISTICS
Benaissa Mounir; Benabdelhafid Abdellatif
2010-01-01
Reverse logistics has become an important entity in the world economy. Businesses increasingly have to cope with product returns, mandated environmental regulations and increasing costs associated with product disposal. This study presents a cost-minimization model for a multi-time-step, multi-type product waste reverse logistics system. The facility location is a central issue of the logistics networks. In this article we are interested in optimizing of the sites facility location for a reve...
A development of logistics management models for the Space Transportation System
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.
Integral points in two-parameter orbits
Corvaja, Pietro; Tucker, Thomas J; Zannier, Umberto
2012-01-01
Let K be a number field, let f: P_1 --> P_1 be a nonconstant rational map of degree greater than 1, let S be a finite set of places of K, and suppose that u, w in P_1(K) are not preperiodic under f. We prove that the set of (m,n) in N^2 such that f^m(u) is S-integral relative to f^n(w) is finite and effectively computable. This may be thought of as a two-parameter analog of a result of Silverman on integral points in orbits of rational maps. This issue can be translated in terms of integral points on an open subset of P_1^2; then one can apply a modern version of the method of Runge, after increasing the number of components at infinity by iterating the rational map. Alternatively, an ineffective result comes from a well-known theorem of Vojta.
Directory of Open Access Journals (Sweden)
Fenling Feng
2013-06-01
Full Text Available Properly planning the modern railway logistics center is a necessary step for the railway logistics operation, which can effectively improve the railway freight service for a seamless connection between the internal and external logistic nodes. The study, from the medium level and depending on the existing railway freight stations with the railway logistics node city, focuses on the site-selection of modern railway logistics center to realize organic combination between newly built railway logistics center and existing resources. Considering the special features of modern railway logistics center, the study makes pre-selection of the existing freight stations with the DEA assessment model to get the alternative plan. And further builds a Bi-level plan model with the gross construction costs and total client expenses minimized. Finally, the example shows that the hybrid optimization algorithm combined with GA, TA, SA can solve the Bi-level programming which is a NP-hard problem and get the railway logistics center number and distribution. The result proves that our method has profound realistic significance to the development of China railway logistics.
2015-03-01
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...ARL-TR-7229•MAR 2015 US Army Research Laboratory Multicriteria Cost Assessment and Logistics Modeling for Military Humanitarian Assistance and...Cost Assessment and Logistics Modeling for Military Humanitarian Assistance and Disaster Relief Aerial Delivery Operations by Nathaniel Bastian
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...
Modeling and Optimization of Food Cold-chain Intelligent Logistics Distribution Network
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Wuxue Jiang
2015-03-01
Full Text Available Aiming at improving the efficiency of food cold-chain logistics network, shortening the logistic time of food and reducing the logistics cost of food, this study analyzes the optimization strategy and various cost factors of the supply network of food cold chain and establishes and expands a kind of logistics network model adapting to the food cold-chain logistics. We use an improved genetic algorithm to solve the model and design an effective coding scheme, through the modified adaptive crossover probability and mutation probability, we integrate them into the elitism strategy, which has effectively avoided the prematurity of the algorithm and improved the operation efficiency of the algorithm. In the same instance, compared with the simple genetic algorithm, this study puts forward that the average running time and the average iteration number of the improved genetic algorithm have reduced nearly 50%, which has proved the feasibility and the effectiveness of the model and the algorithm.
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
Analysis of Two-Parameter (△K and Kmax) Fatigue Crack Propagation Models%包含△K和Kmax二参数的疲劳裂纹扩展模型
Institute of Scientific and Technical Information of China (English)
钱怡; 崔维成
2011-01-01
除了材料自身特性和环境因素外,疲劳裂纹扩展的方式取决于裂纹尖端附近的应力场.而该应力场由外加应力和残余应力组成,受到引起循环塑性区的应力强度因子变化幅度△K和产生单调塑性区的最大应力强度因子Kmax的共同影响.因此,驱动裂纹扩展的外部驱动力应该是△K和Kmax.通过比较Vasudevan和Sadananda,Kuiawski、张嘉振等人提出的3种典型的二参数疲劳裂纹扩展模型的特点,提出了一个兼顾内、外应力,适合变幅载荷下疲劳裂纹扩展的新模型.%The fatigue crack growth is dominated by stress field around the crack-tip except for the material characteristics and the effect of environment. The stress around the crack-tip is the superimposition of the residual stress and the externally applied stress, which are affected by maximum stress intensity factor, Kmax, and stress intensity factor range, △K. The former can be associated with the monotonic plastic zone, while the latter with the cyclic plastic zone. Therefore, the fatigue crack driving force should include two parameters △K and Kmax. After comparing three kinds of fatigue crack growth rate models, which were derived by Vasudevan and Sadananda, Kujawski, and Zhang, a new fatigue crack growth rate model is proposed. The model can deal with the variable amplitude loading cases, and will take into account the residual stress and the externally applied stress.
Simulation Modeling and Statistical Network Tools for Improving Collaboration in Military Logistics
2008-10-01
AFRL-RH-WP-TR-2009-0110 Simulation Modeling and Statistical Network Tools for Improving Collaboration in Military Logistics...SUBTITLE Simulation Modeling and Statistical Network Tools for Improving Collaboration in Military Logistics 5a. CONTRACT NUMBER FA8650-07-1-6848...8 1 1.0 SUMMARY This final technical report describes the research findings of the project Simulation Modeling and Statistical Network
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.
Comment on ``Correlated noise in a logistic growth model''
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.
Design, modeling, and analysis of a feedstock logistics system.
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.
Logistic Regression Models to Forecast Travelling Behaviour in Tripoli City
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Amiruddin Ismail
2011-01-01
Full Text Available Transport modes are very important to Libyan’s Tripoli residents for their daily trips. However, the total number of own car and private transport namely taxi and micro buses on the road increases and causes many problems such as traffic congestion, accidents, air and noise pollution. These problems then causes other related phenomena to the travel activities such as delay in trips, stress and frustration to motorists which may affect their productivity and efficiency to both workers and students. Delay may also increase travel cost as well inefficiency in trips making if compare to other public transport users in some Arabs cities. Switching to public transport (PT modes alternatives such as buses, light rail transit and underground train could improve travel time and travel costs. A transport study has been carried out at Tripoli City Authority areas among own car users who live in areas with inadequate of private transport and poor public transportation services. Analyses about relation between factors such as travel time, travel cost, trip purpose and parking cost have been made to answer research questions. Logistic regression technique has been used to analyse these factors that influence users to switch their trips mode to public transport alternatives.
A Study on Intelligent User-Centric Logistics Service Model Using Ontology
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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.
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.
Beam Elements on Linear Variable Two-Parameter Elastic Foundation
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Iancu-Bogdan Teodoru
2008-01-01
Full Text Available The traditional way to overcome the shortcomings of the Winkler foundation model is to incorporate spring coupling by assemblages of mechanical elements such as springs, flexural elements (beams in one-dimension, 1-D, plates in 2-D, shear-only layers and deformed, pretensioned membranes. This is the class of two-parameter foundations ? named like this because they have the second parameter which introduces interactions between adjacent springs, in addition to the first parameter from the ordinary Winkler?s model. This class of models includes Wieghardt, Filonenko-Borodich, Hetényi and Pasternak foundations. Mathematically, the equations to describe the reaction of the two-parameter foundations are equilibrium, and the only difference is the definition of the parameters. In order to analyse the bending behavior of a Euler-Bernoulli beam resting on linear variable two-parameter elastic foundation a (displacement Finite Element (FE formulation, based on the cubic displacement function of the governing differential equation, is introduced.
Application of the TDABC model in the logistics process using different capacity cost rates
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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
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.
A hybrid model using logistic regression and wavelet transformation to detect traffic incidents
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Shaurya Agarwal
2016-07-01
Full Text Available This research paper investigates a hybrid model using logistic regression with a wavelet-based feature extraction for detecting traffic incidents. A logistic regression model is suitable when the outcome can take only a limited number of values. For traffic incident detection, the outcome is limited to only two values, the presence or absence of an incident. The logistic regression model used in this study is a generalized linear model (GLM with a binomial response and a logit link function. This paper presents a framework to use logistic regression and wavelet-based feature extraction for traffic incident detection. It investigates the effect of preprocessing data on the performance of incident detection models. Results of this study indicate that logistic regression along with wavelet based feature extraction can be used effectively for incident detection by balancing the incident detection rate and the false alarm rate according to need. Logistic regression on raw data resulted in a maximum detection rate of 95.4% at the cost of 14.5% false alarm rate. Whereas the hybrid model achieved a maximum detection rate of 98.78% at the expense of 6.5% false alarm rate. Results indicate that the proposed approach is practical and efficient; with future improvements in the proposed technique, it will make an effective tool for traffic incident detection.
A mathematical model for optimization of an integrated network logistic design
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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.
Accounting for Slipping and Other False Negatives in Logistic Models of Student Learning
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,…
Nonlinear Calibration Model Choice between the Four and Five Parameter Logistic Models
Cumberland, William N.; Fong, Youyi; Yu, Xuesong; Defawe, Olivier; Frahm, Nicole; De Rosa, Stephen
2014-01-01
Both the four-parameter logistic (4PL) and the five-parameter logistic (5PL) models are widely used in nonlinear calibration. In this paper, we study the choice between 5PL and 4PL both by the accuracy and precision of the estimated concentrations and by the power to detect an association between a binary disease outcome and the estimated concentrations. Our results show that when the true curve is symmetric around its inflection point, the efficiency loss from using 5PL is negligible under the prevalent experimental design. When the true curve is asymmetric, 4PL may sometimes offer better performance due to bias-variance trade-off. We provide a practical guideline for choosing between 5PL and 4PL and illustrate its application with a real dataset from the HIV Vaccine Trials Network laboratory. PMID:24918306
Logistics of Trainsets Creation with the Use of Simulation Models
Sedláček, Michal; Pavelka, Hynek
2016-12-01
This paper focuses on rail transport in following the train formation operational processes problem using computer simulations. The problem has been solved using SIMUL8 and applied to specific train formation station in the Czech Republic. The paper describes a proposal simulation model of the train formation work. Experimental modeling with an assessment of achievements and design solution for optimizing of the train formation operational process is also presented.
Using the Logistic Regression model in supporting decisions of establishing marketing strategies
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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
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Paulo H. Ferreira
2015-04-01
Full Text Available Statistical methods have been widely employed to assess the capabilities of credit scoring classification models in order to reduce the risk of wrong decisions when granting credit facilities to clients. The predictive quality of a classification model can be evaluated based on measures such as sensitivity, specificity, predictive values, accuracy, correlation coefficients and information theoretical measures, such as relative entropy and mutual information. In this paper we analyze the performance of a naive logistic regression model, a logistic regression with state-dependent sample selection model and a bounded logistic regression model via a large simulation study. Also, as a case study, the methodology is illustrated on a data set extracted from a Brazilian retail bank portfolio. Our simulation results so far revealed that there is nostatistically significant difference in terms of predictive capacity among the naive logistic regression models, the logistic regression with state-dependent sample selection models and the bounded logistic regression models. However, there is difference between the distributions of the estimated default probabilities from these three statistical modeling techniques, with the naive logistic regression models and the boundedlogistic regression models always underestimating such probabilities, particularly in the presence of balanced samples. Which are common in practice.
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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.
Logistics Distribution Center Location Optimizatio Model An Example Study
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Li Lingling
2017-01-01
Full Text Available This paper analyzes and investigates the situation of the today’s site of distribution centers .Then taking SF Express for an example ,In the light of minimize the total expense ,the location models for single distribution centers is established with the corresponding resolutions given .After that ,The location of the single distribution center of SF Express ,the starting point of which is Zhengzhou Railway Station ,can be determined with the help of distance-testing function of 360 map to conclude its coordinate and then determine its exact service spot .This paper will test the feasibility of above models by the chosen cases with the application of LINGO software.
2017-01-05
DISTRIBUTION STATEMENT A: Approved for public release; distribution is unlimited. TRAC-M-TM-17-010 January 2017 Enhancement of the Logistics ...17-010 January 2017 Enhancement of the Logistics Battle Command Model Architecture Upgrades and Attrition Module Development Nathan Parker... cost the Department of Defense approximately $191,000 expended by TRAC in Fiscal Years 15-17. Prepared on 20170106 TRAC Project Code # 060119 iii
SUPPLIES COSTS: AN EXPLORATORY STUDY WITH APPLICATION OF MEASUREMENT MODEL OF LOGISTICS COSTS
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...
Applying Hierarchy Model to Routing and Scheduling Operations in Postal Logistics
Institute of Scientific and Technical Information of China (English)
无
2001-01-01
Postal departments are actively taking part in e-commerce, of which logistics is a key joint. Computerized routing and scheduling of postal transportation operations offers significant potential for cost decreases and productivity gains. Routing and scheduling hierarchy model is initially built and demonstrated in detail on the basis of statements of specific requirements of postal logistics in this paper, and the realized software is proved to be practical and reliable.
Modeling Logistic Performance in Quantitative Microbial Risk Assessment
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 ti
Ramsay-Curve Item Response Theory for the Three-Parameter Logistic Item Response Model
Woods, Carol M.
2008-01-01
In Ramsay-curve item response theory (RC-IRT), the latent variable distribution is estimated simultaneously with the item parameters of a unidimensional item response model using marginal maximum likelihood estimation. This study evaluates RC-IRT for the three-parameter logistic (3PL) model with comparisons to the normal model and to the empirical…
Nick, Todd G; Campbell, Kathleen M
2007-01-01
The Medical Subject Headings (MeSH) thesaurus used by the National Library of Medicine defines logistic regression models as "statistical models which describe the relationship between a qualitative dependent variable (that is, one which can take only certain discrete values, such as the presence or absence of a disease) and an independent variable." Logistic regression models are used to study effects of predictor variables on categorical outcomes and normally the outcome is binary, such as presence or absence of disease (e.g., non-Hodgkin's lymphoma), in which case the model is called a binary logistic model. When there are multiple predictors (e.g., risk factors and treatments) the model is referred to as a multiple or multivariable logistic regression model and is one of the most frequently used statistical model in medical journals. In this chapter, we examine both simple and multiple binary logistic regression models and present related issues, including interaction, categorical predictor variables, continuous predictor variables, and goodness of fit.
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.
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...
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Siva Prasad Darla
2014-08-01
Full Text Available In this study, a multi level reverse logistics network is developed for a single product. Reverse logistics is a logistic activity beginning from intake of products returned by customers to selling of remanufactured or new products in market; so, it is considered that reverse flow of used products is from various sources like customers, dealers, retailers, manufacturers, etc., to remanufacturer and followed by transportation to secondary market. Due to uncertainties, any traditional supply chain approach to identify potential manufacturing facilities in this situation cannot be employed. Hence, Genetic Algorithm (GA is used for optimization and minimization of various costs involved in reverse logistics process. A sample numerical data is considered to test performance of the proposed model.
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Qunzhen Qu
2015-01-01
Full Text Available With the development of marine logistics industry to grow, the government and corporate more and more attach importance to the performance evaluation of innovation and technology professionals. Combine the characteristics of marine logistics industry and innovative technology professionals to design a performance evaluation index of marine logistics industry in innovation and technology professionals, with the Analytic Hierarchy Process (AHP to determine the weights of the various performance indicatorsf and through the establishment of fuzzy comprehensive evaluation model to make the problems of complex performance evaluation quantification and then come to their performance evaluation results, and provide reference methods and recommendations for innovation and technology professionals in performance evaluation theory and practice of marine logistics industry.
Carbon emissions, logistics volume and GDP in China: empirical analysis based on panel data model.
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.
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Chu-Liangyong
2013-06-01
Full Text Available The network of Chinese Waterborne Petroleum Logistics (CWPL is so complex that reasonably disposing and choosing Chinese Waterborne Petroleum Logistics Distribution Center (CWPLDC take on the important theory value and the practical significance. In the study, the network construct of CWPL distribution is provided and the corresponding mathematical model for locating CWPLDC is established, which is a nonlinear mixed interger model. In view of the nonlinerar programming characteristic of model, the genetic algorithm as the solution strategy is put forward here, the strategies of hybrid coding, constraint elimination , fitness function and genetic operator are given followed the algorithm. The result indicates that this model is effective and reliable. This method could also be applicable for other types of large-scale logistics distribution center optimization.
MODELS AND METHODS FOR LOGISTICS HUB LOCATION: A REVIEW TOWARDS TRANSPORTATION NETWORKS DESIGN
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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.
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
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......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...
Development of a new logistic model for microbial growth in foods.
Fujikawa, Hiroshi
2010-09-01
Mathematical models are essentially needed to quantitatively predict microbial growth in food products during their production and distribution. Recently we developed a new logistic model for microbial growth. The model is an extended logistic model, which shows a sigmoid curve on a semi-log plot. The model could precisely describe and predict bacterial growth at constant and dynamic temperatures in broth, on nutrient agar plates, and in pouched food. Prediction results with our model were very similar to those with the Baranyi model, which is well known worldwide. The model also predicted the amount of metabolites (toxins) that would be produced by a microorganism. Namely, with the growth model and the kinetics of staphylococcal enterotoxin A production, the amount of the toxins produced by Staphylococcus aureus in milk was successfully predicted. Our model could be a tool in the alert system and the quantitative risk assessment of harmful microbes in food.
SUPPLIES COSTS: AN EXPLORATORY STUDY WITH APPLICATION OF MEASUREMENT MODEL OF LOGISTICS COSTS
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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.
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.
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 six
Dynamics of a stochastic HIV-1 infection model with logistic growth
Jiang, Daqing; Liu, Qun; Shi, Ningzhong; Hayat, Tasawar; Alsaedi, Ahmed; Xia, Peiyan
2017-03-01
This paper is concerned with a stochastic HIV-1 infection model with logistic growth. Firstly, by constructing suitable stochastic Lyapunov functions, we establish sufficient conditions for the existence of ergodic stationary distribution of the solution to the HIV-1 infection model. Then we obtain sufficient conditions for extinction of the infection. The stationary distribution shows that the infection can become persistent in vivo.
The Limit Behavior of a Stochastic Logistic Model with Individual Time-Dependent Rates
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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.
Construction of risk prediction model of type 2 diabetes mellitus based on logistic regression
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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.
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Gang WU
2016-01-01
Full Text Available Objective To analyze the risk factors for prognosis in intracerebral hemorrhage using decision tree (classification and regression tree, CART model and logistic regression model. Methods CART model and logistic regression model were established according to the risk factors for prognosis of patients with cerebral hemorrhage. The differences in the results were compared between the two methods. Results Logistic regression analyses showed that hematoma volume (OR-value 0.953, initial Glasgow Coma Scale (GCS score (OR-value 1.210, pulmonary infection (OR-value 0.295, and basal ganglia hemorrhage (OR-value 0.336 were the risk factors for the prognosis of cerebral hemorrhage. The results of CART analysis showed that volume of hematoma and initial GCS score were the main factors affecting the prognosis of cerebral hemorrhage. The effects of two models on the prognosis of cerebral hemorrhage were similar (Z-value 0.402, P=0.688. Conclusions CART model has a similar value to that of logistic model in judging the prognosis of cerebral hemorrhage, and it is characterized by using transactional analysis between the risk factors, and it is more intuitive. DOI: 10.11855/j.issn.0577-7402.2015.12.13
Fitting Ranked Linguistic Data with Two-Parameter Functions
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Wentian Li
2010-07-01
Full Text Available It is well known that many ranked linguistic data can fit well with one-parameter models such as Zipf’s law for ranked word frequencies. However, in cases where discrepancies from the one-parameter model occur (these will come at the two extremes of the rank, it is natural to use one more parameter in the fitting model. In this paper, we compare several two-parameter models, including Beta function, Yule function, Weibull function—all can be framed as a multiple regression in the logarithmic scale—in their fitting performance of several ranked linguistic data, such as letter frequencies, word-spacings, and word frequencies. We observed that Beta function fits the ranked letter frequency the best, Yule function fits the ranked word-spacing distribution the best, and Altmann, Beta, Yule functions all slightly outperform the Zipf’s power-law function in word ranked- frequency distribution.
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Wun Wong
2003-01-01
Full Text Available The assessment of medical outcomes is important in the effort to contain costs, streamline patient management, and codify medical practices. As such, it is necessary to develop predictive models that will make accurate predictions of these outcomes. The neural network methodology has often been shown to perform as well, if not better, than the logistic regression methodology in terms of sample predictive performance. However, the logistic regression method is capable of providing an explanation regarding the relationship(s between variables. This explanation is often crucial to understanding the clinical underpinnings of the disease process. Given the respective strengths of the methodologies in question, the combined use of a statistical (i.e., logistic regression and machine learning (i.e., neural network technology in the classification of medical outcomes is warranted under appropriate conditions. The study discusses these conditions and describes an approach for combining the strengths of the models.
Logistics modelling: improving resource management and public information strategies in Florida.
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.
A coordination agents’ model for the Colombian shipbuilding industry’s logistics system
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Wilson Adarme Jaimes
2011-05-01
Full Text Available This paper presents the results of research carried out by the GICO and SEPRO research groups affiliated to the Universidad Nacional de Colombia regarding the Colombian shipbuilding industry to coordinate autonomous agents in a supply chain (SC, in a decentralised environment, where buyers (shipbuilders have a project system setting production. An exact multi-criteria linear programming model was developed for this purpose; it was aimed at reducing the deficit in meeting demand and minimising logistical costs incurred by all SC members, considering autonomy as being inherent to them, and the need to coordinate logistical operation through knowledge of customer demand and suppliers’ target planning ability. The proposed model was able to reduce total costs by 0,047% monetary units, and explicitly identify logistical costs as a chain complex.
Applying Fuzzy Multiobjective Integrated Logistics Model to Green Supply Chain Problems
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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.
Deriving Dynamic Subsidence of Coal Mining Areas Using InSAR and Logistic Model
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Zefa Yang
2017-02-01
Full Text Available The seasonal variation of land cover and the large deformation gradients in coal mining areas often give rise to severe temporal and geometrical decorrelation in interferometric synthetic aperture radar (InSAR interferograms. Consequently, it is common that the available InSAR pairs do not cover the entire time period of SAR acquisitions, i.e., temporal gaps exist in the multi-temporal InSAR observations. In this case, it is very difficult to accurately estimate mining-induced dynamic subsidence using the traditional time-series InSAR techniques. In this investigation, we employ a logistic model which has been widely applied to describe mining-related dynamic subsidence, to bridge the temporal gaps in multi-temporal InSAR observations. More specifically, we first construct a functional relationship between the InSAR observations and the logistic model, and we then develop a method to estimate the model parameters of the logistic model from the InSAR observations with temporal gaps. Having obtained these model parameters, the dynamic subsidence can be estimated with the logistic model. Simulated and real data experiments in the Datong coal mining area, China, were carried out in this study, in order to test the proposed method. The results show that the maximum subsidence in the Datong coal mining area reached about 1.26 m between 1 July 2007 and 28 February 2009, and the accuracy of the estimated dynamic subsidence is about 0.017 m. Compared with the linear and cubic polynomial models of the traditional time-series InSAR techniques, the accuracy of dynamic subsidence derived by the logistic model is increased by about 50.0% and 45.2%, respectively.
Logistic回归模型及其应用%Logistic regression model and its application
Institute of Scientific and Technical Information of China (English)
常振海; 刘薇
2012-01-01
为了利用Logistic模型提高多分类定性因变量的预测准确率,在二分类Logistic回归模型的基础上,对实际统计数据建立三类别的Logistic模型.采用似然比检验法对自变量的显著性进行检验,剔除了不显著的变量;对每个类别的因变量都确定了1个线性回归函数,并进行了模型检验.分析结果表明,在处理因变量为定性变量的回归分析中,Logistic模型具有很好的预测准确度和实用推广性.%To improve the forecasting accuracy of the multinomial qualitative dependent variable by using logistic model,ternary logistic model is established for actual statistical data based on binary logistic regression model.The significance of independent variables is tested by using the likelihood ratio test method to remove the non-significant variable.A linear regression function is determined for each category dependent variable,and the models are tested.The analysis results show that logistic regression model has good predictive accuracy and practical promotional value in handling regression analysis of qualitative dependent variable.
Development of the Integrated Biomass Supply Analysis and Logistics Model (IBSAL)
Energy Technology Data Exchange (ETDEWEB)
Sokhansanj, Shahabaddine [ORNL; Webb, Erin [ORNL; Turhollow Jr, Anthony F [ORNL
2008-06-01
The Integrated Biomass Supply & Logistics (IBSAL) model is a dynamic (time dependent) model of operations that involve collection, harvest, storage, preprocessing, and transportation of feedstock for use at a biorefinery. The model uses mathematical equations to represent individual unit operations. These unit operations can be assembled by the user to represent the working rate of equipment and queues to represent storage at facilities. The model calculates itemized costs, energy input, and carbon emissions. It estimates resource requirements and operational characteristics of the entire supply infrastructure. Weather plays an important role in biomass management and thus in IBSAL, dictating the moisture content of biomass and whether or not it can be harvested on a given day. The model calculates net biomass yield based on a soil conservation allowance (for crop residue) and dry matter losses during harvest and storage. This publication outlines the development of the model and provides examples of corn stover harvest and logistics.
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
MULTIPLE LOGISTIC REGRESSION MODEL TO PREDICT RISK FACTORS OF ORAL HEALTH DISEASES
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Parameshwar V. Pandit
2012-06-01
Full Text Available Purpose: To analysis the dependence of oral health diseases i.e. dental caries and periodontal disease on considering the number of risk factors through the applications of logistic regression model. Method: The cross sectional study involves a systematic random sample of 1760 permanent dentition aged between 18-40 years in Dharwad, Karnataka, India. Dharwad is situated in North Karnataka. The mean age was 34.26±7.28. The risk factors of dental caries and periodontal disease were established by multiple logistic regression model using SPSS statistical software. Results: The factors like frequency of brushing, timings of cleaning teeth and type of toothpastes are significant persistent predictors of dental caries and periodontal disease. The log likelihood value of full model is –1013.1364 and Akaike’s Information Criterion (AIC is 1.1752 as compared to reduced regression model are -1019.8106 and 1.1748 respectively for dental caries. But, the log likelihood value of full model is –1085.7876 and AIC is 1.2577 followed by reduced regression model are -1019.8106 and 1.1748 respectively for periodontal disease. The area under Receiver Operating Characteristic (ROC curve for the dental caries is 0.7509 (full model and 0.7447 (reduced model; the ROC for the periodontal disease is 0.6128 (full model and 0.5821 (reduced model. Conclusions: The frequency of brushing, timings of cleaning teeth and type of toothpastes are main signifi cant risk factors of dental caries and periodontal disease. The fitting performance of reduced logistic regression model is slightly a better fit as compared to full logistic regression model in identifying the these risk factors for both dichotomous dental caries and periodontal disease.
Permanence and Global Attractivity of a Discrete Logistic Model with Impulses
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Chunyu Gao
2013-01-01
Full Text Available By piecewise Euler method, we construct a discrete logistic equation with impulses. The constructed model is more easily implemented at computer and is a better analogue of the continuous-time dynamic system. The dynamic behaviors of the constructed model are investigated. Sufficient conditions which guarantee the permanence and the global attractivity of positive solutions of the model are obtained. Numerical simulations show the feasibility of the main results.
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…
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
Analysis of Cognitive Structure Using the Linear Logistic Test Model and Quadratic Assignment.
Medina-Diaz, Maria
1993-01-01
The cognitive structure of an algebra test was defined and validated using the linear logistic test model (LLTM) and quadratic assignment (QA). A 29-item test was administered to 235 ninth graders. Results suggest the benefits of applying both LLTM and QA to test construction and analysis. (SLD)
Item Vector Plots for the Multidimensional Three-Parameter Logistic Model
Bryant, Damon; Davis, Larry
2011-01-01
This brief technical note describes how to construct item vector plots for dichotomously scored items fitting the multidimensional three-parameter logistic model (M3PLM). As multidimensional item response theory (MIRT) shows promise of being a very useful framework in the test development life cycle, graphical tools that facilitate understanding…
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...
Improved Weighted Shapley Value Model for the Fourth Party Logistics Supply Chain Coalition
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Na Xu
2013-01-01
Full Text Available How to make the individual get the reasonable and practical profit among the fourth party logistics supply chain coalition system is still a question for further study. Considering the characteristics of the fourth party logistics supply chain coalition, this paper combines Shapley Value with Distribution according to Contribution, two methods in the application, and then adjusts the profit allocated to each member reasonably based on the actual coalition situation named improved weighted Shapley Value model. In this paper, we first analyze the fourth party logistics supply chain coalition profit allocation models, the classical Shapley value method. Then, we analyze the weight of individual enterprise in the coalition by the analytic hierarchy process. To each enterprise, the weight is determined by the investment risks, information divulging risks, and failure risks. Finally, the numerical study shows that the profit allocation method improved weighted Shapley value model is relatively rational and practical. Thus, the proposed combined model is a useful profit allocation mechanism for the fourth party logistics supply chain coalition that the contribution and risks are fully considered.
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…
Modeling Governance KB with CATPCA to Overcome Multicollinearity in the Logistic Regression
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.
PERSISTENCE AND EXTINCTION OF A STOCHASTIC LOGISTIC MODEL WITH DELAYS AND IMPULSIVE PERTURBATION
Institute of Scientific and Technical Information of China (English)
Chun LU; Xiaohua DING
2014-01-01
A stochastic logistic model with delays and impulsive perturbation is proposed and investigated. 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. Furthermore, the theoretical analysis results are also derivated with the help of numerical simulations.
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
MODELING AND ROBUST DESIGN OF REMANUFACTURING LOGISTICS NETWORKS BASED ON DESIGN OF EXPERIMENT
Institute of Scientific and Technical Information of China (English)
Xia Shouchang; Xi Lifeng; Hu Zongwu
2004-01-01
The uncertainty of time, quantity and quality of recycling products leads to the bad stability and flexibility of remanufacturing logistics networks, and general design only covered the minimizing logistics cost, thus, robust design is presented here to solve the uncertainty. The mathematical model of remanufacturing logistics networks is built based on stochastic distribution of uncontrollable factors, and robust objectives are presented. The integration of mathematical simulation and design of experiment method is performed to do sensitive analysis. The influence of each factor and level on the system is investigated, and the main factors and optimum combination are studied. The numbers of factors, level of each factor and design process of experiment are investigated as well. Finally, the process of robust design based on design of experiment is demonstrated by a detailed example.
Institute of Scientific and Technical Information of China (English)
Sher Khan Panhwar; LIU Qun; Shabir Ali Amir; Muhsan Ali Kalhoro
2012-01-01
The catch and effort data of Sillago sihama fishery in Pakistani waters were used to investigate the performance of two closely related stock assessment models:logistic and generalized surplus-production models.Compared with the generalized production model,the logistic model produced more reasonable estimates for parameters such as maximum sustainable yield.The Akaike's Information Criterion values estimated at 4.265 and-51.152 respectively by the logistic and generalized models.Simulation analyses of the S.sihama fishery showed that the estimated and observed abundance indices for the logistic model were closer than those for the generalized production model.Standardized residuals were distributed closer for logistic model,but exhibited a slightly increasing trend for the generalized model.Statistical outliers were seen in 1989 and 1993 for the logistic model,and in 1981 and 1999 for the generalized model.Simulated results revealed that the logistic estimates were close to the true value for low CVs(coefficients of variation)but widely dispersed for high CVs.In contrast,the generalized model estimates were loose for all CV levels.The estimated production model curve parameter φ was not reasonable at all the tested levels of white noise.With the increase in white noise R2 for the catch per unit effort decreased.Therefore,we conclude that the logistic model performs more reasonably than the generalized production model.
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.
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Weihua Liu
2014-01-01
Full Text Available 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.
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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.
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. PMID:25276851
Comparison of a Bayesian Network with a Logistic Regression Model to Forecast IgA Nephropathy
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Michel Ducher
2013-01-01
Full Text Available Models are increasingly used in clinical practice to improve the accuracy of diagnosis. The aim of our work was to compare a Bayesian network to logistic regression to forecast IgA nephropathy (IgAN from simple clinical and biological criteria. Retrospectively, we pooled the results of all biopsies (n=155 performed by nephrologists in a specialist clinical facility between 2002 and 2009. Two groups were constituted at random. The first subgroup was used to determine the parameters of the models adjusted to data by logistic regression or Bayesian network, and the second was used to compare the performances of the models using receiver operating characteristics (ROC curves. IgAN was found (on pathology in 44 patients. Areas under the ROC curves provided by both methods were highly significant but not different from each other. Based on the highest Youden indices, sensitivity reached (100% versus 67% and specificity (73% versus 95% using the Bayesian network and logistic regression, respectively. A Bayesian network is at least as efficient as logistic regression to estimate the probability of a patient suffering IgAN, using simple clinical and biological data obtained during consultation.
Comparison of a Bayesian network with a logistic regression model to forecast IgA nephropathy.
Ducher, Michel; Kalbacher, Emilie; Combarnous, François; Finaz de Vilaine, Jérome; McGregor, Brigitte; Fouque, Denis; Fauvel, Jean Pierre
2013-01-01
Models are increasingly used in clinical practice to improve the accuracy of diagnosis. The aim of our work was to compare a Bayesian network to logistic regression to forecast IgA nephropathy (IgAN) from simple clinical and biological criteria. Retrospectively, we pooled the results of all biopsies (n = 155) performed by nephrologists in a specialist clinical facility between 2002 and 2009. Two groups were constituted at random. The first subgroup was used to determine the parameters of the models adjusted to data by logistic regression or Bayesian network, and the second was used to compare the performances of the models using receiver operating characteristics (ROC) curves. IgAN was found (on pathology) in 44 patients. Areas under the ROC curves provided by both methods were highly significant but not different from each other. Based on the highest Youden indices, sensitivity reached (100% versus 67%) and specificity (73% versus 95%) using the Bayesian network and logistic regression, respectively. A Bayesian network is at least as efficient as logistic regression to estimate the probability of a patient suffering IgAN, using simple clinical and biological data obtained during consultation.
Existence of limit cycles in the Solow model with delayed-logistic population growth.
Bianca, Carlo; Guerrini, Luca
2014-01-01
This paper is devoted to the existence and stability analysis of limit cycles in a delayed mathematical model for the economy growth. Specifically the Solow model is further improved by inserting the time delay into the logistic population growth rate. Moreover, by choosing the time delay as a bifurcation parameter, we prove that the system loses its stability and a Hopf bifurcation occurs when time delay passes through critical values. Finally, numerical simulations are carried out for supporting the analytical results.
Shen, Xing-Rong; Feng, Rui; Chai, Jing; Cheng, Jing; Wang, De-Bin
2014-01-01
Large scale secular registry or surveillance systems have been accumulating vast data that allow mathematical modeling of cancer incidence and mortality rates. Most contemporary models in this regard use time series and APC (age-period-cohort) methods and focus primarily on predicting or analyzing cancer epidemiology with little attention being paid to implications for designing cancer registry, surveillance or evaluation initiatives. This research models age-specific cancer incidence rates using logistic growth equations and explores their performance under different scenarios of data completeness in the hope of deriving clues for reshaping relevant data collection. The study used China Cancer Registry Report 2012 as the data source. It employed 3-parameter logistic growth equations and modeled the age-specific incidence rates of all and the top 10 cancers presented in the registry report. The study performed 3 types of modeling, namely full age-span by fitting, multiple 5-year- segment fitting and single-segment fitting. Measurement of model performance adopted adjusted goodness of fit that combines sum of squred residuals and relative errors. Both model simulation and performance evalation utilized self-developed algorithms programed using C# languade and MS Visual Studio 2008. For models built upon full age-span data, predicted age-specific cancer incidence rates fitted very well with observed values for most (except cervical and breast) cancers with estimated goodness of fit (Rs) being over 0.96. When a given cancer is concerned, the R valuae of the logistic growth model derived using observed data from urban residents was greater than or at least equal to that of the same model built on data from rural people. For models based on multiple-5-year-segment data, the Rs remained fairly high (over 0.89) until 3-fourths of the data segments were excluded. For models using a fixed length single-segment of observed data, the older the age covered by the corresponding
Logistic Models of Fractal Dimension Growth for Spatio-Temporal Dynamics of Urban Morphology
Chen, Yanguang
2016-01-01
Urban form and growth can be described with fractal dimension, which is a measurement of space filling of urban evolution. Based on empirical analyses, a discovery is made that the time series of fractal dimension of urban form can be treated as a sigmoid function of time. Among various sigmoid functions, the logistic function is the most probable selection. However, how to use the model of fractal dimension growth to explain and predict urban growth is a pending problem remaining to be solved. This paper is devoted to modeling fractal dimension evolution of different types of cities. A interesting discovery is as follows: for the cities in developed countries such as UK, USA and Israel, the comparable fractal dimension values of a city's morphology in different years can be fitted to the logistic function; while for the cities in developing countries such as China, the fractal dimension data of urban form can be fitted to a quadratic logistic function. A generalized logistic function is thus proposed to mode...
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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
Karabulut, Esra Mahsereci; Ibrikci, Turgay
2014-05-01
This study develops a logistic model tree based automation system based on for accurate recognition of types of vertebral column pathologies. Six biomechanical measures are used for this purpose: pelvic incidence, pelvic tilt, lumbar lordosis angle, sacral slope, pelvic radius and grade of spondylolisthesis. A two-phase classification model is employed in which the first step is preprocessing the data by use of Synthetic Minority Over-sampling Technique (SMOTE), and the second one is feeding the classifier Logistic Model Tree (LMT) with the preprocessed data. We have achieved an accuracy of 89.73 %, and 0.964 Area Under Curve (AUC) in computer based automatic detection of the pathology. This was validated via a 10-fold-cross-validation experiment conducted on clinical records of 310 patients. The study also presents a comparative analysis of the vertebral column data with the use of several machine learning algorithms.
Alumura, Sibel A.; Karab, Bahar Y.; Melo, M. Teresa
2013-01-01
Facility location decisions play a critical role in designing logistics networks. This article provides some guidelines on how location decisions and logistics functions can be integrated into a single mathematical model to optimize the configuration of a logistics network. This will be illustrated by two generic models, one supporting the design of a forward logistics network and the other addressing the specific requirements of a reverse logistics network. Several special cases and extensio...
Alumura, Sibel A.; Karab, Bahar Y.; Melo, M. Teresa
2013-01-01
Facility location decisions play a critical role in designing logistics networks. This article provides some guidelines on how location decisions and logistics functions can be integrated into a single mathematical model to optimize the configuration of a logistics network. This will be illustrated by two generic models, one supporting the design of a forward logistics network and the other addressing the specific requirements of a reverse logistics network. Several special cases and extensio...
Revenue-Sharing Contract Models for Logistics Service Supply Chains with Mass Customization Service
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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.
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Jiaqing Zhang
2012-07-01
Full Text Available Nodal staging in breast cancer is a key predictor of prognosis. This paper presents the results of potential clinicopathological predictors of axillary lymph node involvement and develops an efficient prediction model to assist in predicting axillary lymph node metastases. Seventy patients with primary early breast cancer who underwent axillary dissection were evaluated. Univariate and multivariate logistic regression were performed to evaluate the association between clinicopathological factors and lymph node metastatic status. A logistic regression predictive model was built from 50 randomly selected patients; the model was also applied to the remaining 20 patients to assess its validity. Univariate analysis showed a significant relationship between lymph node involvement and absence of nm-23 (p = 0.010 and Kiss-1 (p = 0.001 expression. Absence of Kiss-1 remained significantly associated with positive axillary node status in the multivariate analysis (p = 0.018. Seven clinicopathological factors were involved in the multivariate logistic regression model: menopausal status, tumor size, ER, PR, HER2, nm-23 and Kiss-1. The model was accurate and discriminating, with an area under the receiver operating characteristic curve of 0.702 when applied to the validation group. Moreover, there is a need discover more specific candidate proteins and molecular biology tools to select more variables which should improve predictive accuracy.
An inexact reverse logistics model for municipal solid waste management systems.
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.
Nahashon, S N; Aggrey, S E; Adefope, N A; Amenyenu, A; Wright, D
2006-02-01
This study was undertaken to describe the growth pattern of the pearl gray Guinea fowl. Using BW data from hatch to 22 wk, 3 nonlinear mathematical functions (Richards, Gompertz, and logistic) were used to estimate growth patterns of the pearl gray guinea fowl. The logistic and Gompertz models are a special case of the Richards model, which has a variable point of inflection defined by the shape or growth trajectory parameter, m. The shape parameter m was 1.08 and 0.98 in males and females, respectively, suggesting that the growth pattern of the pearl gray female guinea fowl is Gompertz. The pearl gray guinea fowl exhibited sexual dimorphism for their growth characteristics. From the Gompertz model, the asymptotic BW, growth rate, and age at maximum growth were 1.62 kg, 0.22 kg/wk, and 6.65 wk in males, respectively, and 1.70 kg, 0.19 kg/wk, and 6.70 wk in females, respectively. The ages at maximum growth were 6.65, 6.47, and 8.12 wk for the Richards, Gompertz, and logistic models, respectively. The pearl gray guinea fowl females have a higher asymptotic BW compared with the males. The average asymptotic BW of about 1.57 kg for both sexes predicted by the logistic model was below the average predicted BW from the Richards (1.66 kg) and Gompertz (1.67 kg) models, respectively, at 22 wk of age. The inverse relationship between the asymptotic weight and both relative growth and age at maximum growth of the pearl gray guinea fowl is similar to that of chickens, quail, and ducks. Success in studying the growth characteristics of guinea fowl will contribute to the efforts of genetically improving this least-studied avian species.
存在保护区域的 Logistic 模型的研究%The Research of Logistic Model with Delay and Reserve Area
Institute of Scientific and Technical Information of China (English)
曾春花
2013-01-01
建立了存在保护区域的时滞 Logistic 模型，通过分析得到了不存在时滞时模型中存在唯一正平衡解的一个充分条件和此模型的全局渐近稳定性，而存在时滞时此模型是绝对稳定的。% Logistic model with delay and reserve area was built in this paper , we obtained a sufficient condition for the existence of the unique positive solution , the global stability of this model without delay , and the absolute stability of this model with delay .
Optimal Control of Production and Remanufacturing in a Reverse Logistics Model with Backlogging
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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.
Institute of Scientific and Technical Information of China (English)
CHEN Yong; LIN Feilong; WANG Xiao; TANG Kefeng
2006-01-01
In this paper, the multi-agent model about shop logistics is set up. This model has 8 agents: raw materials stock agent, process agent, testing agent, transition agent, production information agent, scheduling agent, process agent and stock agent. The scheduling agent has three subagents: manager agent (MA), resource agent (RA) and part agent (PA). MA, PA and RA are communicating equally that guarantees agility of the whole MAS system. The part tasks pass between MA, RA and PA as an integer, which can guarantee the consistency of the data. We use a detailed example about shop logistics scheduling in a semiconductor company to explain the principle. In this example, we use two scheduling strategies:FCFS and SPT. The result data indicates that the average flow time and lingering ratio are changed using different strategy. It is proves that the multi-agent scheduling is useful.
Resource Symmetric Dispatch Model for Internet of Things on Advanced Logistics
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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.
A Support Vector Machine-based Evaluation Model of Customer Satisfaction Degree in Logistics
Institute of Scientific and Technical Information of China (English)
SUN Hua-li; XIE Jian-ying
2007-01-01
This paper pressnts a novel evaluation model of the customer satisfaction degree (CSD) in logistics based on support vector machine (SVM). Firstly, the relation between the suppliers and the customers is analyzed. Secondly, the evaluation index system and fuzzy quantitative methods are provided. Thirdly, the CSD evaluation system including eight indexes and three ranks rinsed on one-against-one mode of SVM is built. Last simulation experiment is presented to illustrate the theoretical results.
2008-01-01
This thesis is a study for analysing costs affected by packaging in a producing industry. The purpose is to develop a model that will calculate and present possible cost savings for the customer by using Volvo Logistics Corporations, VLC’s, returnable packaging instead of other packaging solutions. The thesis is based on qualitative data gained from both theoretical and empirical studies. The methodology for gaining information has been to study theoretical sources such as course literature a...
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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.
Competition with Online and Offline Demands considering Logistics Costs Based on the Hotelling Model
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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.
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VALENTINA SHEHU
2015-10-01
Full Text Available Correct forecasting is of a great importance for the business and economy of the country. To comprehend the market and the economic system, mathematical models are used to describe and predict the future of situation. Agriculture is the spinal column of Albania’s economic activity and the last 20 years free market experience has given a demonstration of the high correlation between agricultural progress and the economic development. Producing greenhouse-grown vegetables can result a beneficial activity, but it is a hard and complicated investment. The greenhouse technology is one of great innovation in agriculture. Agricultures methods must be combined with technical knowledge, marketing must be planned before harvest, and every phase of process should be well-managed. In this paper it is studied and applied the logistic growth model for forecasting the production of vegetables in greenhouse. The results of this paper show that the logistic S-shaped curve is a mathematical model to characterize the progress of innovation in agriculture. Also, the logistic equation can be used to describe and predict the production of vegetables in greenhouses in Albania.
Using a unit cost model to predict the impact of budget cuts on logistics products and services
Van Haasteren, Cleve J.
1992-01-01
Approved for Public Release; Distribution is Unlimited The Director of the Trident Integrated Logistics Support Division at the Naval Sea Systems Command manages a complex and dynamic budget that supports the provision of logistics products and services to the Trident submarine fleet. This thesis focuses on analyzing the Logistics Division budget and developing a model where the impact of a budget cut can be predicted by employing marginal cost. The thesis also explores ...
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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.
2008-01-01
Drawing on a new and comprehensive measure of logistics quality, our gravity model suggests logistics in the exporting and partner-country can have an important impact on bilateral exports. A one standard deviation improvement in the exporter’s logistics quality, which for example would improve Gabon to the level of Guinea, would raise exports by almost 60%. Landlocked countries’ exports depend on their neighbours’ logistics, but their own logistics quality is not as important as for other co...
Transformation of state space for two-parameter Markov processes
Institute of Scientific and Technical Information of China (English)
周健伟
1996-01-01
Let X=(X) be a two-parameter *-Markov process with a transition function (p1, p2, p), where X, takes values in the state space (Er,), T=[0,)2. For each r T, let f, be a measurable transformation of (E,) into the state space (E’r, ). Set Y,=f,(X,), r T. A sufficient condition is given for the process Y=(Yr) still to be a two-parameter *-Markov process with a transition function in terms of transition function (p1, p2, p) and fr. For *-Markov families of two-parameter processes with a transition function, a similar problem is also discussed.
Grey-Theory-Based Optimization Model of Emergency Logistics Considering Time Uncertainty.
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Bao-Jian Qiu
Full Text Available 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.
Grey-Theory-Based Optimization Model of Emergency Logistics Considering Time Uncertainty.
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.
Innovative and logistics development business model elaboration of the economy of Ukraine
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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.
A general framework for the use of logistic regression models in meta-analysis.
Simmonds, Mark C; Higgins, Julian Pt
2016-12-01
Where individual participant data are available for every randomised trial in a meta-analysis of dichotomous event outcomes, "one-stage" random-effects logistic regression models have been proposed as a way to analyse these data. Such models can also be used even when individual participant data are not available and we have only summary contingency table data. One benefit of this one-stage regression model over conventional meta-analysis methods is that it maximises the correct binomial likelihood for the data and so does not require the common assumption that effect estimates are normally distributed. A second benefit of using this model is that it may be applied, with only minor modification, in a range of meta-analytic scenarios, including meta-regression, network meta-analyses and meta-analyses of diagnostic test accuracy. This single model can potentially replace the variety of often complex methods used in these areas. This paper considers, with a range of meta-analysis examples, how random-effects logistic regression models may be used in a number of different types of meta-analyses. This one-stage approach is compared with widely used meta-analysis methods including Bayesian network meta-analysis and the bivariate and hierarchical summary receiver operating characteristic (ROC) models for meta-analyses of diagnostic test accuracy.
Cosmology on all scales: a two-parameter perturbation expansion
Goldberg, Sophia R; Malik, Karim A
2016-01-01
We propose and construct a two-parameter perturbative expansion around a Friedmann-Lema\\^{i}tre-Robertson-Walker geometry that can be used to model high-order gravitational effects in the presence of non-linear structure. This framework reduces to the weak-field and slow-motion post-Newtonian treatment of gravity in the appropriate limits, but also includes the low-amplitude large-scale fluctuations that are important for cosmological modelling. We derive a set of field equations that can be applied to the late Universe, where non-linear structure exists on supercluster scales, and perform a detailed investigation of the associated gauge problem. This allows us to identify a consistent set of perturbed quantities in both the gravitational and matter sectors, and to construct a set of gauge-invariant quantities that correspond to each of them. The field equations, written in terms of these quantities, take on a relatively simple form, and allow the effects of small-scale structure on the large-scale properties...
The Stochastic stability of a Logistic model with Poisson white noise
Institute of Scientific and Technical Information of China (English)
Duan Dong-Hai; Xu Wei; Su Jun; Zhou Bing-Chang
2011-01-01
The stochastic stability of a logistic model subjected to the effect of a random natural environment, modeled as Poisson white noise process, is investigated. The properties of the stochastic response are discussed for calculating the Lyapunov exponent, which had proven to be the most useful diagnostic tool for the stability of dynamical systems. The generalised It(o) differentiation formula is used to analyse the stochastic stability of the response. The results indicate that the stability of the response is related to the intensity and amplitude distribution of the environment noise and the growth rate of the species.
GLOBAL ANALYSIS OF HEPATITIS B AND C VIRUS MODEL WITH LOGISTIC HEPATOCYTE GROWTH
Institute of Scientific and Technical Information of China (English)
无
2012-01-01
In this paper,a hepatitis B and C virus model with logistic hepatocyte growth is investigated,where the type of incidence is standard.Both of the two thresholds of the model,determining whether the virus infection persists and whether the virus infection leads to the complete liver failure,are found.The complete dynamical behaviors are analyzed.The obtained results show that the existence of homoclinic orbits is possible,which implies that the outbreak of the virus infection may occur.
A logistic model for magnetic energy storage in solar active regions
Institute of Scientific and Technical Information of China (English)
Hua-Ning Wang; Yan-Mei Cui; Han He
2009-01-01
Previous statistical analyses of a large number of SOHO/MDI full disk longitu-dinal magnetograms provided a result that demonstrated how responses of solar flares to photospheric magnetic properties can be fitted with sigmoid functions. A logistic model reveals that these fitted sigmoid functions might be related to the free energy storage process in solar active regions. Although this suggested model is rather simple, the free energy level of active regions can be estimated and the probability of a solar flare with importance over a threshold can be forecast within a given time window.
The diffusive logistic model with a free boundary in a heterogeneous time-periodic environment
Ding, Weiwei; Peng, Rui; Wei, Lei
2017-09-01
This paper is concerned with a diffusive logistic model with advection and a free boundary in a spatially heterogeneous and time periodic environment. Such a model may be used to describe the spreading of a new or invasive species with the free boundary representing the expanding front. Under more general assumptions on the initial data and the function standing for the intrinsic growth rate of the species, sharp criteria for spreading and vanishing are established, and estimates for spreading speed when spreading occurs are also derived. The obtained results considerably improve and complement the existing ones, especially those of [11,25].
A multicriteria decision making model for assessment and selection of an ERP in a logistics context
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.
Optimal harvesting of a stochastic delay logistic model with Lévy jumps
Qiu, Hong; Deng, Wenmin
2016-10-01
The optimal harvesting problem of a stochastic time delay logistic model with Lévy jumps is considered in this article. We first show that the model has a unique global positive solution and discuss the uniform boundedness of its pth moment with harvesting. Then we prove that the system is globally attractive and asymptotically stable in distribution under our assumptions. Furthermore, we obtain the existence of the optimal harvesting effort by the ergodic method, and then we give the explicit expression of the optimal harvesting policy and maximum yield.
Scholz-Reiter, B.; Wirth, F.; Dashkovskiy, S.; Makuschewitz, T.; Schönlein, M.; Kosmykov, M.
2011-12-01
We investigate the problem of model reduction with a view to large-scale logistics networks, specifically supply chains. Such networks are modeled by means of graphs, which describe the structure of material flow. An aim of the proposed model reduction procedure is to preserve important features within the network. As a new methodology we introduce the LogRank as a measure for the importance of locations, which is based on the structure of the flows within the network. We argue that these properties reflect relative importance of locations. Based on the LogRank we identify subgraphs of the network that can be neglected or aggregated. The effect of this is discussed for a few motifs. Using this approach we present a meta algorithm for structure-preserving model reduction that can be adapted to different mathematical modeling frameworks. The capabilities of the approach are demonstrated with a test case, where a logistics network is modeled as a Jackson network, i.e., a particular type of queueing network.
2007-11-02
Models), contains the To-Be Retail Asset Sustainment Process Model displaying the activities and functions related to the improved processes for receipt...of a logistics process model for a more distant future asset sustainment scenario unconstrained by today’s logistics information systems limitations...It also contains a process model reflecting the Reengineering Team’s vision of the future asset sustainment process.
Modeling of geogenic radon in Switzerland based on ordered logistic regression.
Kropat, Georg; Bochud, François; Murith, Christophe; Palacios Gruson, Martha; Baechler, Sébastien
2017-01-01
The estimation of the radon hazard of a future construction site should ideally be based on the geogenic radon potential (GRP), since this estimate is free of anthropogenic influences and building characteristics. The goal of this study was to evaluate terrestrial gamma dose rate (TGD), geology, fault lines and topsoil permeability as predictors for the creation of a GRP map based on logistic regression. Soil gas radon measurements (SRC) are more suited for the estimation of GRP than indoor radon measurements (IRC) since the former do not depend on ventilation and heating habits or building characteristics. However, SRC have only been measured at a few locations in Switzerland. In former studies a good correlation between spatial aggregates of IRC and SRC has been observed. That's why we used IRC measurements aggregated on a 10 km × 10 km grid to calibrate an ordered logistic regression model for geogenic radon potential (GRP). As predictors we took into account terrestrial gamma doserate, regrouped geological units, fault line density and the permeability of the soil. The classification success rate of the model results to 56% in case of the inclusion of all 4 predictor variables. Our results suggest that terrestrial gamma doserate and regrouped geological units are more suited to model GRP than fault line density and soil permeability. Ordered logistic regression is a promising tool for the modeling of GRP maps due to its simplicity and fast computation time. Future studies should account for additional variables to improve the modeling of high radon hazard in the Jura Mountains of Switzerland. Copyright Â© 2016 The Authors. Published by Elsevier Ltd.. All rights reserved.
The null distribution of likelihood-ratio statistics in the conditional-logistic linkage model.
Song, Yeunjoo E; Elston, Robert C
2013-01-01
Olson's conditional-logistic model retains the nice property of the LOD score formulation and has advantages over other methods that make it an appropriate choice for complex trait linkage mapping. However, the asymptotic distribution of the conditional-logistic likelihood-ratio (CL-LR) statistic with genetic constraints on the model parameters is unknown for some analysis models, even in the case of samples comprising only independent sib pairs. We derive approximations to the asymptotic null distributions of the CL-LR statistics and compare them with the empirical null distributions by simulation using independent affected sib pairs. Generally, the empirical null distributions of the CL-LR statistics match well the known or approximated asymptotic distributions for all analysis models considered except for the covariate model with a minimum-adjusted binary covariate. This work will provide useful guidelines for linkage analysis of real data sets for the genetic analysis of complex traits, thereby contributing to the identification of genes for disease traits.
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Daniel Furtado Ferreira
2003-01-01
Full Text Available The evaluation of a culture medium for the in vitro culture of a species is performed using its physical and/or chemical properties. However, the analysis of the experimental results makes it possible to evaluate its quality. In this sense, this work presents an alternative using a logistic model to evaluate the culture medium to be used in vitro. The probabilities provided by this model will be used as a medium evaluator index. The importance of this index is based on the formalization of a statistical criterion for the selection of the adequate culture medium to be used on in vitro culture without excluding its physical and/or chemical properties. To demonstrate this procedure, an experiment determining the ideal medium for the in vitro culture of primary explants of Ipeca [Psychotria ipecacuanha (Brot. Stokes] was evaluated. The differentiation of the culture medium was based on the presence and absence of the growth regulator BAP (6-benzilaminopurine. A logistic model was adjusted as a function of the weight of fresh and dry matter. Minimum, medium and maximum probabilities obtained with this model showed that the culture medium containing BAP was the most adequate for the explant growth. Due to the high discriminative power of these mediums, detected by the model, their use is recommended as an alternative to select culture medium for similar experiments.
Analysis of schizophrenia data using a nonlinear threshold index logistic model.
Jiang, Zhenyu; Du, Chengan; Jablensky, Assen; Liang, Hua; Lu, Zudi; Ma, Yang; Teo, Kok Lay
2014-01-01
Genetic information, such as single nucleotide polymorphism (SNP) data, has been widely recognized as useful in prediction of disease risk. However, how to model the genetic data that is often categorical in disease class prediction is complex and challenging. In this paper, we propose a novel class of nonlinear threshold index logistic models to deal with the complex, nonlinear effects of categorical/discrete SNP covariates for Schizophrenia class prediction. A maximum likelihood methodology is suggested to estimate the unknown parameters in the models. Simulation studies demonstrate that the proposed methodology works viably well for moderate-size samples. The suggested approach is therefore applied to the analysis of the Schizophrenia classification by using a real set of SNP data from Western Australian Family Study of Schizophrenia (WAFSS). Our empirical findings provide evidence that the proposed nonlinear models well outperform the widely used linear and tree based logistic regression models in class prediction of schizophrenia risk with SNP data in terms of both Types I/II error rates and ROC curves.
Analysis of schizophrenia data using a nonlinear threshold index logistic model.
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Zhenyu Jiang
Full Text Available Genetic information, such as single nucleotide polymorphism (SNP data, has been widely recognized as useful in prediction of disease risk. However, how to model the genetic data that is often categorical in disease class prediction is complex and challenging. In this paper, we propose a novel class of nonlinear threshold index logistic models to deal with the complex, nonlinear effects of categorical/discrete SNP covariates for Schizophrenia class prediction. A maximum likelihood methodology is suggested to estimate the unknown parameters in the models. Simulation studies demonstrate that the proposed methodology works viably well for moderate-size samples. The suggested approach is therefore applied to the analysis of the Schizophrenia classification by using a real set of SNP data from Western Australian Family Study of Schizophrenia (WAFSS. Our empirical findings provide evidence that the proposed nonlinear models well outperform the widely used linear and tree based logistic regression models in class prediction of schizophrenia risk with SNP data in terms of both Types I/II error rates and ROC curves.
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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.
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Gregor Stiglic
Full Text Available Different studies have demonstrated the importance of comorbidities to better understand the origin and evolution of medical complications. This study focuses on improvement of the predictive model interpretability based on simple logical features representing comorbidities. We use group lasso based feature interaction discovery followed by a post-processing step, where simple logic terms are added. In the final step, we reduce the feature set by applying lasso logistic regression to obtain a compact set of non-zero coefficients that represent a more comprehensible predictive model. The effectiveness of the proposed approach was demonstrated on a pediatric hospital discharge dataset that was used to build a readmission risk estimation model. The evaluation of the proposed method demonstrates a reduction of the initial set of features in a regression model by 72%, with a slight improvement in the Area Under the ROC Curve metric from 0.763 (95% CI: 0.755-0.771 to 0.769 (95% CI: 0.761-0.777. Additionally, our results show improvement in comprehensibility of the final predictive model using simple comorbidity based terms for logistic regression.
Hu, Kai; Gan, Xiao-qing; Gao, Kuo
The speed of logistics infrastructures investment in Central China is still lower than other regions since the rise of the central region strategy was put forward. And the ration of freight turnover was also being down. The analysis with the relations among the central region of the logistics investment, logistics value-added and GDP, found that three variables exists co-integration relation. And found that the investment in logistics infrastructure was the Granger reason of the GDP, the investment in logistics infrastructure and logistics value-added was the Granger reason for each other. According to the analysis, some countermeasures be put forward as following: accelerate the speed of logistics investment, optimize logistics environment, promote the logistics capability, reduce logistics cost, and so on.
Fenling Feng; Feiran Li; Qingya Zhang
2013-01-01
Properly planning the modern railway logistics center is a necessary step for the railway logistics operation, which can effectively improve the railway freight service for a seamless connection between the internal and external logistic nodes. The study, from the medium level and depending on the existing railway freight stations with the railway logistics node city, focuses on the site-selection of modern railway logistics center to realize organic combination between newly built railway lo...
Institute of Scientific and Technical Information of China (English)
XU Jing; YANG Chi; ZHANG Guoping
2007-01-01
Information model is adopted to integrate factors of various geosciences to estimate the susceptibility of geological hazards. Further combining the dynamic rainfall observations, Logistic regression is used for modeling the probabilities of geological hazard occurrences, upon which hierarchical warnings for rainfall-induced geological hazards are produced. The forecasting and warning model takes numerical precipitation forecasts on grid points as its dynamic input, forecasts the probabilities of geological hazard occurrences on the same grid, and translates the results into likelihoods in the form of a 5-level hierarchy. Validation of the model with observational data for the year 2004 shows that 80% of the geological hazards of the year have been identified as "likely enough to release warning messages". The model can satisfy the requirements of an operational warning system, thus is an effective way to improve the meteorological warnings for geological hazards.
Sensitivity Analysis to Select the Most Influential Risk Factors in a Logistic Regression Model
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Jassim N. Hussain
2008-01-01
Full Text Available The traditional variable selection methods for survival data depend on iteration procedures, and control of this process assumes tuning parameters that are problematic and time consuming, especially if the models are complex and have a large number of risk factors. In this paper, we propose a new method based on the global sensitivity analysis (GSA to select the most influential risk factors. This contributes to simplification of the logistic regression model by excluding the irrelevant risk factors, thus eliminating the need to fit and evaluate a large number of models. Data from medical trials are suggested as a way to test the efficiency and capability of this method and as a way to simplify the model. This leads to construction of an appropriate model. The proposed method ranks the risk factors according to their importance.
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...
Kasprzyk, I; Walanus, A
2014-01-01
The characteristics of a pollen season, such as timing and magnitude, depend on a number of factors such as the biology of the plant and environmental conditions. The main aim of this study was to develop mathematical models that explain dynamics in atmospheric concentrations of pollen and fungal spores recorded in Rzeszów (SE Poland) in 2000-2002. Plant taxa with different characteristics in the timing, duration and curve of their pollen seasons, as well as several fungal taxa were selected for this analysis. Gaussian, gamma and logistic distribution models were examined, and their effectiveness in describing the occurrence of airborne pollen and fungal spores was compared. The Gaussian and differential logistic models were very good at describing pollen seasons with just one peak. These are typically for pollen types with just one dominant species in the flora and when the weather, in particular temperature, is stable during the pollination period. Based on s parameter of the Gaussian function, the dates of the main pollen season can be defined. In spite of the fact that seasonal curves are often characterised by positive skewness, the model based on the gamma distribution proved not to be very effective.
A Case Study Using Modeling and Simulation to Predict Logistics Supply Chain Issues
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.
Modeling Energy Efficiency As A Green Logistics Component In Vehicle Assembly Line
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.
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Weihua Liu
2013-07-01
Full Text Available In the actual order allocation process of Logistics Service Supply Chain (LSSC, Functional Logistics Service Providers (FLSPs are strategic: they will pre-estimate the order allocation results to decide whether or not to participate in order allocation. Considering a two-echelon Logistics Service Supply Chain (LSSC consisting of one Logistics Service Integrator (LSI and several competitive FLSPs, we establish an order allocation optimization model of LSSC based on the pre-estimate and competitive behavior of FLSPs. The model considers three objectives: to minimize the cost of LSI, to maximize the order satisfaction of FLSPs and to match the different logistics capacities of FLSPs as much as possible. Numerical analysis is performed to discuss the effects of the competition among FLSPs on the order allocation results. The results show that with the rational expectations equilibrium, competitions among FLSPs help improve the comprehensive performance of LSSC.
SIMULATION OF LOGISTICS PROCESSES
Yu. Taranenko; Fedorenko, I.
2016-01-01
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 reach...
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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.
Development and implementation of integrated biomass supply analysis and logistics model (IBSAL)
Energy Technology Data Exchange (ETDEWEB)
Sokhansanj, Shahab; Turhollow, Anthony F. [Oak Ridge National Laboratory, Oak Ridge, TN (United States). Environmental Sciences Division; Kumar, Amit [University of Alberta, Edmonton, AB (Canada). Department of Mechanical Engineering
2006-10-15
This paper describes the framework development of a dynamic integrated biomass supply analysis and logistics model (IBSAL) to simulate the collection, storage, and transport operations for supplying agricultural biomass to a biorefinery. The model consists of time dependent events representing the working rate of equipment and queues representing the capacity of storage structures. The discrete event and queues are inter-connected to represent the entire network of material flow from field to a biorefinery. Weather conditions including rain and snow influence the moisture content and the dry matter loss of biomass through the supply chain and are included in the model. The model is developed using an object oriented high level simulation language EXTEND(TM). A case of corn stover collection and transport scenario using baling system is described. (author)
THE EXISTENCE OF POSITIVE PERIODIC SOLUTIONS IN A LOGISTIC DIFFERENCE MODEL WITH A FEEDBACK CONTROL
Institute of Scientific and Technical Information of China (English)
刘智钢; 陈安平
2004-01-01
Consider the following nonautonomous delayed periodic logistic difference model with feedback control term N(k+1)=N(k)exp[r(k)-a1(k)N(k)-a2(k)N(k-τ(k))-c(k)u(k)],Δu(k)=-a(k)u(k)+b(k)N(k-τ(k)), which describes the evolution of a single species. The existence of a positive periodic solution is established by using the method of Mawhin's coincidence degree. This work has important significance in both theory and applications.
CONFIDENCE LOWER LIMITS FOR RESPONSE PROBABILITIES UNDER THE LOGISTIC RESPONSE MODEL
Institute of Scientific and Technical Information of China (English)
TIAN Yubin; LI Guoying; YANG Jie
2004-01-01
The lower confidence limits for response probabilities based on binary response data under the logistic response model are considered by saddlepoint approach. The high order approximation to the conditional distribution of a statistic for an interested parameter and then the lower confidence limits of response probabilities are derived. A simulation comparing these lower confidence limits with those obtained from the asymptotic normality is conducted. The proposed approximation is applied to two real data sets. Numerical results show that the saddlepoint approximations are much more accurate than the asymptotic normality approximations, especially for the cases of small or moderate sample sizes.
MATHEMATICAL MODEL FOR CALCULATION OF INFORMATION RISKS FOR INFORMATION AND LOGISTICS SYSTEM
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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
A maximum likelihood estimation framework for delay logistic differential equation model
Mahmoud, Ahmed Adly; Dass, Sarat Chandra; Muthuvalu, Mohana S.
2016-11-01
This paper will introduce the maximum likelihood method of estimation for delay differential equation model governed by unknown delay and other parameters of interest followed by a numerical solver approach. As an example we consider the delayed logistic differential equation. A grid based estimation framework is proposed. Our methodology estimates correctly the delay parameter as well as the initial starting value of the dynamical system based on simulation data. The computations have been carried out with help of mathematical software: MATLAB® 8.0 R2012b.
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.
DEFF Research Database (Denmark)
Petersen, Jørgen Holm
2016-01-01
. For each term in the composite likelihood, a conditional likelihood is used that eliminates the influence of the random effects, which results in a composite conditional likelihood consisting of only one-dimensional integrals that may be solved numerically. Good properties of the resulting estimator......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...
A logistic regression model of Coronary Artery Disease among Male Patients in Punjab
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Sohail Chand
2005-07-01
Full Text Available This is a cross-sectional retrospective study of 308 male patients, who were presented first time for coronary angiography at the Punjab Institute of Cardiology. The mean age was 50.97 + 9.9 among male patients. As the response variable coronary artery disease (CAD was a binary variable, logistic regression model was fitted to predict the Coronary Artery Disease with the help of significant risk factors. Age, Chest pain, Diabetes Mellitus, Smoking and Lipids are resulted as significant risk factors associated with CAD among male population.
Log-Logistic Proportional Odds Model for Analyzing Infant Mortality in Bangladesh.
Fatima-Tuz-Zahura, Most; Mohammad, Khandoker Akib; Bari, Wasimul
2017-01-01
Log-logistic parametric survival regression model has been used to find out the potential determinants of infant mortality in Bangladesh using the data extracted from Bangladesh Demographic and Health Survey, 2011. First, nonparametric product-limit approach has been used to examine the unadjusted association between infant mortality and covariate of interest. It is found that maternal education, membership of nongovernmental organizations, age of mother at birth, sex of child, size of child at birth, and place of delivery play an important role in reducing the infant mortality, adjusting relevant covariates.
Delay-induced periodic phenomenon in a diffusive regulated logistic model.
Zhuang, Kejun; Jia, Gao
2016-01-01
The diffusive logistic growth model with time delay and feedback control is considered. First, the well-posedness and permanence of solutions are discussed by using some comparison techniques. Then, the sufficient conditions for stability of nonnegative constant steady states are established, and the occurrence of Hopf bifurcation at positive steady state is performed. Next, the bifurcation properties are derived by computing the normal form on center manifold. Our results not only supplement but also generalized some existing ones. Finally, some numerical simulations show the feasibility of our theoretical analyses.
Non-asymptotic Oracle Inequalities for the Lasso and Group Lasso in high dimensional logistic model
Kwemou, Marius
2012-01-01
We consider the problem of estimating a function $f_{0}$ in logistic regression model. We propose to estimate this function $f_{0}$ by a sparse approximation build as a linear combinaison of elements of a given dictionary of $p$ functions. This sparse approximation is selected by the Lasso or Group Lasso procedure. In this context, we state non asymptotique oracle inequalities for Lasso and Group Lasso under restricted eigenvalues assumption as introduced in \\cite{BRT}. Those theoretical results are illustrated through a simulation study.
Transitions in a Logistic Growth Model Induced by Noise Coupling and Noise Color
Institute of Scientific and Technical Information of China (English)
SHI Jin; ZHU Shi-Qun
2006-01-01
With unified colored noise approximation, the logistic growth model is used to analyze cancer cell population when colored noise is included. It is found that both the coupling between noise terms and the noise color can induce continuous first-order-like and re-entrance-like phase transitions in the system. The coupling and the noise color can also increase tumor cell growth for small number of cell mass and repress tumor cell growth for large number of cell mass. It is shown that the approximate analytic expressions are consistent with the numerical simulations.
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.
A modelling on estimation of the carbon dioxide emission from vehicles using logistic equation
Chandra, E. W.; Andry, A.; Afra, F.; Sumarti, N.
2016-04-01
In this paper, the logistic differential equation is used in developing a model on carbon dioxide traces which potentially releases from a particular area. The improvement to a higher scale or scope is straightforward by considering the larger observed data or larger number of the potential CO2 sources. Let G(t) the total amount of the carbon dioxide emission from motorcycles and cars used by the resident of the area. G (t )=P (t )(r1(t )η (t )+r2(t )ξ (t )) where P(t) is the number of the resident of the observed area (population of Bandung Institute of Technology) at year t, r1(t) and r2(t) are the portion of the population who use motorcycles and cars respectively, η(t) and ξ(t) are the approximated total emission of the carbon dioxide from the related vehicles respectively. The number of resident is modeled by the logistic equation so the future number can be estimated. The model is implemented in a campus of Institut Teknologi Bandung (ITB) at Ganesha street, Indonesia. The results show that the amount of CO2 produced from the transport in Ganesha campus will reach the carrying capacity of the campus in the next 3 years, which will be at around 2.1 billion kilotons of CO2. Therefore, the need of reducing the usage of motorcycles and cars is inevitable in the near future.
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.
Effective factors contraceptive use by logistic regression model in Tehran, 1996
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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.
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.)
Melo, Raquel; Vieira, Gonçalo; Caselli, Alberto; Ramos, Miguel
2010-05-01
Field surveying during the austral summer of 2007/08 and the analysis of a QuickBird satellite image, resulted on the production of a detailed geomorphological map of the Irizar and Crater Lake area in Deception Island (South Shetlands, Maritime Antarctic - 1:10 000) and allowed its analysis and spatial modelling of the geomorphological phenomena. The present study focus on the analysis of the spatial distribution and characteristics of hummocky terrains, lag surfaces and nivation hollows, complemented by GIS spatial modelling intending to identify relevant controlling geographical factors. Models of the susceptibility of occurrence of these phenomena were created using two statistical methods: logistical regression, as a multivariate method; and the informative value as a bivariate method. Success and prediction rate curves were used for model validation. The Area Under the Curve (AUC) was used to quantify the level of performance and prediction of the models and to allow the comparison between the two methods. Regarding the logistic regression method, the AUC showed a success rate of 71% for the lag surfaces, 81% for the hummocky terrains and 78% for the nivation hollows. The prediction rate was 72%, 68% and 71%, respectively. Concerning the informative value method, the success rate was 69% for the lag surfaces, 84% for the hummocky terrains and 78% for the nivation hollows, and with a correspondingly prediction of 71%, 66% and 69%. The results were of very good quality and demonstrate the potential of the models to predict the influence of independent variables in the occurrence of the geomorphological phenomena and also the reliability of the data. Key-words: present-day geomorphological dynamics, detailed geomorphological mapping, GIS, spatial modelling, Deception Island, Antarctic.
National Research Council Canada - National Science Library
Shu Ling Lin
2010-01-01
This paper proposes a new approach of two-stage hybrid model of logistic regression-ANN for the construction of a financial distress warning system for banking industry in emerging market during 1998-2006...
A binary logistic regression model for discriminating real protein-protein interface
Institute of Scientific and Technical Information of China (English)
无
2003-01-01
The selection and study of descriptive variables of protein-protein complex interface is a major question that many biologists come across when the research of protein-protein recognition is concerned. Several variables have been proposed to understand the structural or energetic features of complex interfaces. Here a systematic study of some of these "traditional" variables, as well as a few new ones, is introduced. With the values of these variables extracted from 42 PDB samples with real or false complex interfaces, a binary logistic regression analysis is performed, which results in an effective empirical model for the evaluation of binding probabilities of protein-protein interfaces. The model is validated with 12 samples, and satisfactory results are obtained for both the training and validation sets. Meanwhile, three potential dimeric interfaces of staphylokinase have been investigated and one with the best suitability to our model is proposed.
A landscape and climate data logistic model of tsetse distribution in Kenya.
Directory of Open Access Journals (Sweden)
Nathan Moore
Full Text Available BACKGROUND: Trypanosoma spp, biologically transmitted by the tsetse fly in Africa, are a major cause of illness resulting in both high morbidity and mortality among humans, cattle, wild ungulates, and other species. However, tsetse fly distributions change rapidly due to environmental changes, and fine-scale distribution maps are few. Due to data scarcity, most presence/absence estimates in Kenya prior to 2000 are a combination of local reports, entomological knowledge, and topographic information. The availability of tsetse fly abundance data are limited, or at least have not been collected into aggregate, publicly available national datasets. Despite this limitation, other avenues exist for estimating tsetse distributions including remotely sensed data, climate information, and statistical tools. METHODOLOGY/PRINCIPAL FINDINGS: Here we present a logistic regression model of tsetse abundance. The goal of this model is to estimate the distribution of tsetse fly in Kenya in the year 2000, and to provide a method by which to anticipate their future distribution. Multiple predictor variables were tested for significance and for predictive power; ultimately, a parsimonious subset of variables was identified and used to construct the regression model with the 1973 tsetse map. These data were validated against year 2000 Food and Agriculture Organization (FAO estimates. Mapcurves Goodness-Of-Fit scores were used to evaluate the modeled fly distribution against FAO estimates and against 1973 presence/absence data, each driven by appropriate climate data. CONCLUSIONS/SIGNIFICANCE: Logistic regression can be effectively used to produce a model that projects fly abundance under elevated greenhouse gas scenarios. This model identifies potential areas for tsetse abandonment and expansion.
Modeling group size and scalar stress by logistic regression from an archaeological perspective.
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Gianmarco Alberti
Full Text Available Johnson's scalar stress theory, describing the mechanics of (and the remedies to the increase in in-group conflictuality that parallels the increase in groups' size, provides scholars with a useful theoretical framework for the understanding of different aspects of the material culture of past communities (i.e., social organization, communal food consumption, ceramic style, architecture and settlement layout. Due to its relevance in archaeology and anthropology, the article aims at proposing a predictive model of critical level of scalar stress on the basis of community size. Drawing upon Johnson's theory and on Dunbar's findings on the cognitive constrains to human group size, a model is built by means of Logistic Regression on the basis of the data on colony fissioning among the Hutterites of North America. On the grounds of the theoretical framework sketched in the first part of the article, the absence or presence of colony fissioning is considered expression of not critical vs. critical level of scalar stress for the sake of the model building. The model, which is also tested against a sample of archaeological and ethnographic cases: a confirms the existence of a significant relationship between critical scalar stress and group size, setting the issue on firmer statistical grounds; b allows calculating the intercept and slope of the logistic regression model, which can be used in any time to estimate the probability that a community experienced a critical level of scalar stress; c allows locating a critical scalar stress threshold at community size 127 (95% CI: 122-132, while the maximum probability of critical scale stress is predicted at size 158 (95% CI: 147-170. The model ultimately provides grounds to assess, for the sake of any further archaeological/anthropological interpretation, the probability that a group reached a hot spot of size development critical for its internal cohesion.
Diagnostic analysis of the logistic model for pedestrian injury severity in traffic crashes.
Sze, N N; Wong, S C
2007-11-01
This study attempts to evaluate the injury risk of pedestrian casualties in traffic crashes and to explore the factors that contribute to mortality and severe injury, using the comprehensive historical crash record that is maintained by the Hong Kong Transport Department. The injury, demographic, crash, environmental, geometric, and traffic characteristics of 73,746 pedestrian casualties that were involved in traffic crashes from 1991 to 2004 are considered. Binary logistic regression is used to determine the associations between the probability of fatality and severe injury and all contributory factors. A consideration of the influence of implicit attributes on the trend of pedestrian injury risk, temporal confounding, and interaction effects is progressively incorporated into the predictive model. To verify the goodness-of-fit of the proposed model, the Hosmer-Lemeshow test and logistic regression diagnostics are conducted. It is revealed that there is a decreasing trend in pedestrian injury risk, controlling for the influences of demographic, road environment, and other risk factors. In addition, the influences of pedestrian behavior, traffic congestion, and junction type on pedestrian injury risk are subject to temporal variation.
Application of a two-parameter quantum algebra to rotational spectroscopy of nuclei
Barbier, R.; Kibler, M.
1996-10-01
A two-parameter quantum algebra Uqp( u2) is briefly investigated in this paper. The basic ingredients of a model based on the Uqp( u2) symmetry, the qp-rotator model, are presented in detail. Some general tendencies arising from the application of this model to the description of rotational bands of various atomic nuclei are summarized.
Stata Modules for Calculating Novel Predictive Performance Indices for Logistic Models
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Barkhordari
2016-01-01
Full Text Available Background Prediction is a fundamental part of prevention of cardiovascular diseases (CVD. The development of prediction algorithms based on the multivariate regression models loomed several decades ago. Parallel with predictive models development, biomarker researches emerged in an impressively great scale. The key question is how best to assess and quantify the improvement in risk prediction offered by new biomarkers or more basically how to assess the performance of a risk prediction model. Discrimination, calibration, and added predictive value have been recently suggested to be used while comparing the predictive performances of the predictive models’ with and without novel biomarkers. Objectives Lack of user-friendly statistical software has restricted implementation of novel model assessment methods while examining novel biomarkers. We intended, thus, to develop a user-friendly software that could be used by researchers with few programming skills. Materials and Methods We have written a Stata command that is intended to help researchers obtain cut point-free and cut point-based net reclassification improvement index and (NRI and relative and absolute Integrated discriminatory improvement index (IDI for logistic-based regression analyses.We applied the commands to a real data on women participating the Tehran lipid and glucose study (TLGS to examine if information of a family history of premature CVD, waist circumference, and fasting plasma glucose can improve predictive performance of the Framingham’s “general CVD risk” algorithm. Results The command is addpred for logistic regression models. Conclusions The Stata package provided herein can encourage the use of novel methods in examining predictive capacity of ever-emerging plethora of novel biomarkers.
AN APPLICATION OF THE LOGISTIC REGRESSION MODEL IN THE EXPERIMENTAL PHYSICAL CHEMISTRY
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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.
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Steyerberg Ewout W
2011-05-01
Full Text Available Abstract Background Logistic random effects models are a popular tool to analyze multilevel also called hierarchical data with a binary or ordinal outcome. Here, we aim to compare different statistical software implementations of these models. Methods We used individual patient data from 8509 patients in 231 centers with moderate and severe Traumatic Brain Injury (TBI enrolled in eight Randomized Controlled Trials (RCTs and three observational studies. We fitted logistic random effects regression models with the 5-point Glasgow Outcome Scale (GOS as outcome, both dichotomized as well as ordinal, with center and/or trial as random effects, and as covariates age, motor score, pupil reactivity or trial. We then compared the implementations of frequentist and Bayesian methods to estimate the fixed and random effects. Frequentist approaches included R (lme4, Stata (GLLAMM, SAS (GLIMMIX and NLMIXED, MLwiN ([R]IGLS and MIXOR, Bayesian approaches included WinBUGS, MLwiN (MCMC, R package MCMCglmm and SAS experimental procedure MCMC. Three data sets (the full data set and two sub-datasets were analysed using basically two logistic random effects models with either one random effect for the center or two random effects for center and trial. For the ordinal outcome in the full data set also a proportional odds model with a random center effect was fitted. Results The packages gave similar parameter estimates for both the fixed and random effects and for the binary (and ordinal models for the main study and when based on a relatively large number of level-1 (patient level data compared to the number of level-2 (hospital level data. However, when based on relatively sparse data set, i.e. when the numbers of level-1 and level-2 data units were about the same, the frequentist and Bayesian approaches showed somewhat different results. The software implementations differ considerably in flexibility, computation time, and usability. There are also differences in
Threshold Dynamics of a Huanglongbing Model with Logistic Growth in Periodic Environments
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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.
Heckmann, Tobias; Gegg, Katharina; Becht, Michael
2013-04-01
Statistical approaches to landslide susceptibility modelling on the catchment and regional scale are used very frequently compared to heuristic and physically based approaches. In the present study, we deal with the problem of the optimal sample size for a logistic regression model. More specifically, a stepwise approach has been chosen in order to select those independent variables (from a number of derivatives of a digital elevation model and landcover data) that explain best the spatial distribution of debris flow initiation zones in two neighbouring central alpine catchments in Austria (used mutually for model calculation and validation). In order to minimise problems arising from spatial autocorrelation, we sample a single raster cell from each debris flow initiation zone within an inventory. In addition, as suggested by previous work using the "rare events logistic regression" approach, we take a sample of the remaining "non-event" raster cells. The recommendations given in the literature on the size of this sample appear to be motivated by practical considerations, e.g. the time and cost of acquiring data for non-event cases, which do not apply to the case of spatial data. In our study, we aim at finding empirically an "optimal" sample size in order to avoid two problems: First, a sample too large will violate the independent sample assumption as the independent variables are spatially autocorrelated; hence, a variogram analysis leads to a sample size threshold above which the average distance between sampled cells falls below the autocorrelation range of the independent variables. Second, if the sample is too small, repeated sampling will lead to very different results, i.e. the independent variables and hence the result of a single model calculation will be extremely dependent on the choice of non-event cells. Using a Monte-Carlo analysis with stepwise logistic regression, 1000 models are calculated for a wide range of sample sizes. For each sample size
Bubbling and bistability in two parameter discrete systems
Indian Academy of Sciences (India)
G Ambika; N V Sujatha
2000-05-01
We present a graphical analysis of the mechanisms underlying the occurrences of bubbling sequences and bistability regions in the bifurcation scenario of a special class of one dimensional two parameter maps. The main result of the analysis is that whether it is bubbling or bistability is decided by the sign of the third derivative at the inﬂection point of the map function.
Optimal Two Parameter Bounds for the Seiffert Mean
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Hui Sun
2013-01-01
Full Text Available We obtain sharp bounds for the Seiffert mean in terms of a two parameter family of means. Our results generalize and extend the recent bounds presented in the Journal of Inequalities and Applications (2012 and Abstract and Applied Analysis (2012.
Biomarker Detection in Association Studies: Modeling SNPs Simultaneously via Logistic ANOVA
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.
物流作业成本核算模型研究%Study on Logistics Activity Cost Accounting Model
Institute of Scientific and Technical Information of China (English)
李淼; 程国全
2011-01-01
通过对物流中心作业流程的标准化设计,基于作业成本法的思想,运用表格工具进行各项作业的成本参数设置,从而建立起物流作业成本核算模型.%Through designing the standard logistics center activity process and using the method of activity-based costing, the paper employs diagram and table drawing softwares to the setting of the cost parameters of various logistics activities which are then used to formulate the cost accounting model of logistics activities.
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...
Multiple logistic regression model of signalling practices of drivers on urban highways
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.
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.)
Directory of Open Access Journals (Sweden)
Futao Guo
2016-10-01
Full Text Available Frequent and intense anthropogenic fires present meaningful challenges to forest management in the boreal forest of China. Understanding the underlying drivers of human-caused fire occurrence is crucial for making effective and scientifically-based forest fire management plans. In this study, we applied logistic regression (LR and Random Forests (RF to identify important biophysical and anthropogenic factors that help to explain the likelihood of anthropogenic fires in the Chinese boreal forest. Results showed that the anthropogenic fires were more likely to occur at areas close to railways and were significantly influenced by forest types. In addition, distance to settlement and distance to road were identified as important predictors for anthropogenic fire occurrence. The model comparison indicated that RF had greater ability than LR to predict forest fires caused by human activity in the Chinese boreal forest. High fire risk zones in the study area were identified based on RF, where we recommend increasing allocation of fire management resources.
A semiparametric Wald statistic for testing logistic regression models based on case-control data
Institute of Scientific and Technical Information of China (English)
2008-01-01
We propose a semiparametric Wald statistic to test the validity of logistic regression models based on case-control data. The test statistic is constructed using a semiparametric ROC curve estimator and a nonparametric ROC curve estimator. The statistic has an asymptotic chi-squared distribution and is an alternative to the Kolmogorov-Smirnov-type statistic proposed by Qin and Zhang in 1997, the chi-squared-type statistic proposed by Zhang in 1999 and the information matrix test statistic proposed by Zhang in 2001. The statistic is easy to compute in the sense that it requires none of the following methods: using a bootstrap method to find its critical values, partitioning the sample data or inverting a high-dimensional matrix. We present some results on simulation and on analysis of two real examples. Moreover, we discuss how to extend our statistic to a family of statistics and how to construct its Kolmogorov-Smirnov counterpart.
Binary logistic regression modelling: Measuring the probability of relapse cases among drug addict
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..
Transport and supply logistics of biomass fuels: Vol. 2. Biomass and strategic modelling
Energy Technology Data Exchange (ETDEWEB)
Allen, J.; Browne, M.; Cook, A.; Wicks, N.; Palmer, H.; Hunter, A.; Boyd, J.
1996-10-01
This document forms part of the United Kingdom Department of Trade and Industry project ''Transport and Logistics of Biomass Fuels'', which aimed to describe the distribution of existing and potential biomass resources in terms of their supply potential for power stations. Fixed areas of supply, or catchments, have been identified on colour maps of Britain showing the distribution of forest fuel, short rotation coppices, and various types of straw and animal slurry, using a specially written strategic modelling program. Adequate supplies of biomass resources are shown to exist in Britain, but siting of power stations to exploit these resources, will depend on transport and economic considerations appropriate at the time of construction. Biomass power stations in the megawatt capacity range could be resourced. (UK)
elrm: Software Implementing Exact-Like Inference for Logistic Regression Models
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David Zamar
2007-09-01
Full Text Available Exact inference is based on the conditional distribution of the sufficient statistics for the parameters of interest given the observed values for the remaining sufficient statistics. Exact inference for logistic regression can be problematic when data sets are large and the support of the conditional distribution cannot be represented in memory. Additionally, these methods are not widely implemented except in commercial software packages such as LogXact and SAS. Therefore, we have developed elrm, software for R implementing (approximate exact inference for binomial regression models from large data sets. We provide a description of the underlying statistical methods and illustrate the use of elrm with examples. We also evaluate elrm by comparing results with those obtained using other methods.
Statistical modelling for thoracic surgery using a nomogram based on logistic regression.
Liu, Run-Zhong; Zhao, Ze-Rui; Ng, Calvin S H
2016-08-01
A well-developed clinical nomogram is a popular decision-tool, which can be used to predict the outcome of an individual, bringing benefits to both clinicians and patients. With just a few steps on a user-friendly interface, the approximate clinical outcome of patients can easily be estimated based on their clinical and laboratory characteristics. Therefore, nomograms have recently been developed to predict the different outcomes or even the survival rate at a specific time point for patients with different diseases. However, on the establishment and application of nomograms, there is still a lot of confusion that may mislead researchers. The objective of this paper is to provide a brief introduction on the history, definition, and application of nomograms and then to illustrate simple procedures to develop a nomogram with an example based on a multivariate logistic regression model in thoracic surgery. In addition, validation strategies and common pitfalls have been highlighted.
Qualitative analysis of stationary Keller-Segel chemotaxis models with logistic growth
Wang, Qi; Yan, Jingda; Gai, Chunyi
2016-06-01
We study the stationary Keller-Segel chemotaxis models with logistic cellular growth over a one-dimensional region subject to the Neumann boundary condition. We show that nonconstant solutions emerge in the sense of Turing's instability as the chemotaxis rate {χ} surpasses a threshold number. By taking the chemotaxis rate as the bifurcation parameter, we carry out bifurcation analysis on the system to obtain the explicit formulas of bifurcation values and small amplitude nonconstant positive solutions. Moreover, we show that solutions stay strictly positive in the continuum of each branch. The stabilities of these steady-state solutions are well studied when the creation and degradation rate of the chemical is assumed to be a linear function. Finally, we investigate the asymptotic behaviors of the monotone steady states. We construct solutions with interesting patterns such as a boundary spike when the chemotaxis rate is large enough and/or the cell motility is small.
Institute of Scientific and Technical Information of China (English)
林金官; 韦博成
2004-01-01
In this paper, it is discussed that two tests for varying dispersion of binomial data in the framework of nonlinear logistic models with random effects, which are widely used in analyzing longitudinal binomial data. One is the individual test and power calculation for varying dispersion through testing the randomness of cluster effects, which is extensions of Dean(1992) and Commenges et al (1994). The second test is the composite test for varying dispersion through simultaneously testing the randomness of cluster effects and the equality of random-effect means. The score test statistics are constructed and expressed in simple, easy to use, matrix formulas. The authors illustrate their test methods using the insecticide data (Giltinan, Capizzi & Malani (1988)).
Application of the new logistic model to microbial growth prediction in food.
Fujikawa, Hiroshi
2011-06-01
Recently a microbial growth model, the new logistic model, which could precisely describe and predict microbial growth at various patterns of temperature, was developed by the author (Biocontrol Science, 15, 75-80, 2010). The author shows several software programs developed with the model in this review. First, a program that analyzes microbial growth data and generates growth curves fitted to the model was developed. Second, a growth prediction program for Escherichia coli, Staphylococcus aureus, and Vibrio paraheamolyticus [corrected] exposed at various patterns of temperature was made based on experimental data. For V. paraheamolyticus [corrected] a program for bacterial growth under environmental conditions including temperature, salt concentration, and pH was developed. These programs are available free at the Japan Food Industry Center. Furthermore, a method to estimate the temperature at various points on or inside a food exposed to a given temperature was developed by using the measured temperatures of two points on the surface of the food and the heat conduction law. Combining this method with the growth model, a system that predicts microbial growth in a food exposed to various temperature patterns was made. This system could be a prototype of an alert system for microbial food safety.
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...... The aim of this paper is to present these four LG-effects with a special emphasis on a possible way of modelling these and interpreting their importance. The calculations are carried out by using the CLG-DSS model and case studies concerning the fixed links across the Great Belt and Øresund....... It is proposed to model the effects in two ways. First the paper presents a combined method modelling the four effects into one aggregate effect characterized by the goods-related time benefits. Second the paper describes a more refined, disaggregate method approach that, however, at this stage only concerns...
A simulation study of sample size for multilevel logistic regression models
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Moineddin Rahim
2007-07-01
Full Text Available Abstract Background Many studies conducted in health and social sciences collect individual level data as outcome measures. Usually, such data have a hierarchical structure, with patients clustered within physicians, and physicians clustered within practices. Large survey data, including national surveys, have a hierarchical or clustered structure; respondents are naturally clustered in geographical units (e.g., health regions and may be grouped into smaller units. Outcomes of interest in many fields not only reflect continuous measures, but also binary outcomes such as depression, presence or absence of a disease, and self-reported general health. In the framework of multilevel studies an important problem is calculating an adequate sample size that generates unbiased and accurate estimates. Methods In this paper simulation studies are used to assess the effect of varying sample size at both the individual and group level on the accuracy of the estimates of the parameters and variance components of multilevel logistic regression models. In addition, the influence of prevalence of the outcome and the intra-class correlation coefficient (ICC is examined. Results The results show that the estimates of the fixed effect parameters are unbiased for 100 groups with group size of 50 or higher. The estimates of the variance covariance components are slightly biased even with 100 groups and group size of 50. The biases for both fixed and random effects are severe for group size of 5. The standard errors for fixed effect parameters are unbiased while for variance covariance components are underestimated. Results suggest that low prevalent events require larger sample sizes with at least a minimum of 100 groups and 50 individuals per group. Conclusion We recommend using a minimum group size of 50 with at least 50 groups to produce valid estimates for multi-level logistic regression models. Group size should be adjusted under conditions where the prevalence
Theory of two-parameter Markov chain with an application in warranty study
Calvache, Álvaro
2012-01-01
In this paper we present the classical results of Kolmogorov's backward and forward equations to the case of a two-parameter Markov process. These equations relates the infinitesimal transition matrix of the two-parameter Markov process. However, solving these equations is not possible and we require a numerical procedure. In this paper, we give an alternative method by use of double Laplace transform of the transition probability matrix and of the infinitesimal transition matrix of the process. An illustrative example is presented for the method proposed. In this example, we consider a two-parameter warranty model, in which a system can be any of these states: working, failure. We calculate the transition density matrix of these states and also the cost of the warranty for the proposed model.
To Use or Not to Use--(The One- or Three-Parameter Logistic Model) That Is the Question.
Reckase, Mark D.
Definition of the issues to the use of latent trait models, specifically one- and three-parameter logistic models, in conjunction with multi-level achievement batteries, forms the basis of this paper. Research results related to these issues are also documented in an attempt to provide a rational basis for model selection. The application of the…
Interval Estimations of the Two-Parameter Exponential Distribution
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Lai Jiang
2012-01-01
Full Text Available In applied work, the two-parameter exponential distribution gives useful representations of many physical situations. Confidence interval for the scale parameter and predictive interval for a future independent observation have been studied by many, including Petropoulos (2011 and Lawless (1977, respectively. However, interval estimates for the threshold parameter have not been widely examined in statistical literature. The aim of this paper is to, first, obtain the exact significance function of the scale parameter by renormalizing the p∗-formula. Then the approximate Studentization method is applied to obtain the significance function of the threshold parameter. Finally, a predictive density function of the two-parameter exponential distribution is derived. A real-life data set is used to show the implementation of the method. Simulation studies are then carried out to illustrate the accuracy of the proposed methods.
Model of Air Force Logistics War Fighting Experimentation%空军后勤作战实验模型
Institute of Scientific and Technical Information of China (English)
宗龙强; 罗兴永; 温继海
2016-01-01
为提高空军后勤作战实验模型构建的质量和效益，构建一种空军后勤作战实验5层结构模型体系。在深入分析空军后勤系统的基础上，通过分析空军后勤作战实验模型体系的构建要求，运用UML建立了飞行保障指挥控制模型。分析结果表明：该5层结构模型体系基本厘清了空军后勤作战实验模型构建需求，为模型构建工作提供了一个基本的架构。%In order to improve the quality and efficiency of model of air force logistics war fighting experimentation, establish a five-level architecture model system of air force logistics. By penetratingly analyzing the air force logistics system, through analyze air construction requirement force logistics war fighting experimentation model system, use UML to establish flight protection command control model. The analysis results show that, the five-level architecture model system meets the establishment requirement of air force logistics war fighting experimentation, and provides a basic architecture for the model establishment.
Two-parameter Levy processes along decreasing paths
Covo, Shai
2010-01-01
Let {X_{t_1,t_2}: t_1,t_2 >= 0} be a two-parameter L\\'evy process on R^d. We study basic properties of the one-parameter process {X_{x(t),y(t)}: t \\in T} where x and y are, respectively, nondecreasing and nonincreasing nonnegative continuous functions on the interval T. We focus on and characterize the case where the process has stationary increments.
Integrated logistics optimizing the USMC quadrant model using intelligent agent technologies
Morse, Louis J.
2002-01-01
Approved for public release; distribution is unlimited In 1998, the Marine Corps initiated the Integrated Logistics Capability (ILC) to specifically address issues related to Marine Corps logistics doctrine, policy, and processes. The purposes of ILC initiatives were to define, measure, and improve core logistics capabilities to meet the challenges of the new millennium and beyond. During a four-week Best Business Practices seminar hosted by Penn State, several key concepts were analyze...
Institute of Scientific and Technical Information of China (English)
Cheng-Wu CHEN; Hsien-Chueh Peter YANG; Chen-Yuan CHEN; Alex Kung-Hsiung CHANG; Tsung-Hao CHEN
2008-01-01
Internal solitary wave propagation over a submarine ridge results in energy dissipation, in which the hydrodynamic interaction between a wave and ridge affects marine environment. This study analyzes the effects of ridge height and potential energy during wave-ridge interaction with a binary and cumulative logistic regression model. In testing the Global Null Hypothesis, all values are p＜0.001, with three statistical methods, such as Likelihood Ratio, Score, and Wald. While comparing with two kinds of models, tests values obtained by cumulative logistic regression models are better than those by binary logistic regression models. Although this study employed cumulative logistic regression model, three probability functions 1, 2 and 3, are utilized for investigating the weighted influence of factors on wave reflection. Deviance and Pearson tests are applied to check the goodness-of-fit of the proposed model. The analytical results demonstrated that both ridge height (X1) and potential energy (X2) significantly impact (p＜0.0001) the amplitude-based reflected rate; the P-values for the deviance and Pearson are all ＞0.05 (0.2839, 0.3438, respectively). That is, the goodness-of-fit between ridge height (X1) and potential energy (X2) can further predict parameters under the scenario of the best parsimonious model.Investigation of 6 predictive powers (R2, Max-rescaled R2, Somers'D, Gamma, Tau-a, and c, respectively) indicate that these predictive estimates of the proposed model have better predictive ability than ridge height alone, and are very similar to the interaction of ridge height and potential energy. It can be concluded that the goodness-of-fit and prediction ability of the cumulative logistic regression model are better than that of the binary logistic regression model.
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.
Widyaningsih, Purnami; Retno Sari Saputro, Dewi; Nugrahani Putri, Aulia
2017-06-01
GWOLR model combines geographically weighted regression (GWR) and (ordinal logistic reression) OLR models. Its parameter estimation employs maximum likelihood estimation. Such parameter estimation, however, yields difficult-to-solve system of nonlinear equations, and therefore numerical approximation approach is required. The iterative approximation approach, in general, uses Newton-Raphson (NR) method. The NR method has a disadvantage—its Hessian matrix is always the second derivatives of each iteration so it does not always produce converging results. With regard to this matter, NR model is modified by substituting its Hessian matrix into Fisher information matrix, which is termed Fisher scoring (FS). The present research seeks to determine GWOLR model parameter estimation using Fisher scoring method and apply the estimation on data of the level of vulnerability to Dengue Hemorrhagic Fever (DHF) in Semarang. The research concludes that health facilities give the greatest contribution to the probability of the number of DHF sufferers in both villages. Based on the number of the sufferers, IR category of DHF in both villages can be determined.
Jochens, Arne; Caliebe, Amke; Rösler, Uwe; Krawczak, Michael
2011-12-01
The rate of microsatellite mutation is dependent upon both the allele length and the repeat motif, but the exact nature of this relationship is still unknown. We analyzed data on the inheritance of human Y-chromosomal microsatellites in father-son duos, taken from 24 published reports and comprising 15,285 directly observable meioses. At the six microsatellites analyzed (DYS19, DYS389I, DYS390, DYS391, DYS392, and DYS393), a total of 162 mutations were observed. For each locus, we employed a maximum-likelihood approach to evaluate one of several single-step mutation models on the basis of the data. For five of the six loci considered, a novel logistic mutation model was found to provide the best fit according to Akaike's information criterion. This implies that the mutation probability at the loci increases (nonlinearly) with allele length at a rate that differs between upward and downward mutations. For DYS392, the best fit was provided by a linear model in which upward and downward mutation probabilities increase equally with allele length. This is the first study to empirically compare different microsatellite mutation models in a locus-specific fashion.
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
Reeve, Russell; Turner, J Rick
2013-05-01
The Hill equation is often used in dose-response or exposure-response modeling. Aliases for the Hill model include the Emax model, and the Michaelis-Menten model. There is confusion about the appropriate parameterization, how to interpret the parameters, what the meaning is of the various parameterizations found in the literature, and which parameterization best approximates the statistical inferences produced when fitting the Hill equation to data. In this paper, we present several equivalent versions of the Hill model; show that they are equivalent in terms of yielding the same prediction for a given dose, and are equivalent to the four-parameter logistic model in this same sense; and deduce which parameterization is optimal in the sense of having the least statistical curvature and preferable multicollinearity.
Modelo de Gerenciamento da Logística Reversa Reverse Logistics Management Model
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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.
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.
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.
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.
Modeling Haze Problems in the North of Thailand using Logistic Regression
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Busayamas Pimpunchat
2014-07-01
Full Text Available At present, air pollution is a major problem in the upper northern region of Thailand. Air pollutants have an effect on human health, the economy and the traveling industry. The severity of this problem clearly appears every year during the dry season, from February to April. In particular it becomes very serious in March, especially in Chiang Mai province where smoke haze is a major issue. This study looked into related data from 2005-2010 covering eight principal parameters: PM10 (particulate matter with a diameter smaller than 10 micrometer, CO (carbon monoxide, NO2 (nitrogen dioxide, SO2 (sulphur dioxide, RH (relative humidity, NO (nitrogen oxide, pressure, and rainfall. Overall haze problem occurrence was calculated from a logistic regression model. Its dependence on the eight parameters stated above was determined for design conditions using the correlation coefficients with PM10. The proposed overall haze problem modeling can be used as a quantitative assessment criterion for supporting decision making to protect human health. This study proposed to predict haze problem occurrence in 2011. The agreement of the results from the mathematical model with actual measured PM10 concentration data from the Pollution Control Department was quite satisfactory.
[Clinical research XX. From clinical judgment to multiple logistic regression model].
Berea-Baltierra, Ricardo; Rivas-Ruiz, Rodolfo; Pérez-Rodríguez, Marcela; Palacios-Cruz, Lino; Moreno, Jorge; Talavera, Juan O
2014-01-01
The complexity of the causality phenomenon in clinical practice implies that the result of a maneuver is not solely caused by the maneuver, but by the interaction among the maneuver and other baseline factors or variables occurring during the maneuver. This requires methodological designs that allow the evaluation of these variables. When the outcome is a binary variable, we use the multiple logistic regression model (MLRM). This multivariate model is useful when we want to predict or explain, adjusting due to the effect of several risk factors, the effect of a maneuver or exposition over the outcome. In order to perform an MLRM, the outcome or dependent variable must be a binary variable and both categories must mutually exclude each other (i.e. live/death, healthy/ill); on the other hand, independent variables or risk factors may be either qualitative or quantitative. The effect measure obtained from this model is the odds ratio (OR) with 95 % confidence intervals (CI), from which we can estimate the proportion of the outcome's variability explained through the risk factors. For these reasons, the MLRM is used in clinical research, since one of the main objectives in clinical practice comprises the ability to predict or explain an event where different risk or prognostic factors are taken into account.
Li, Li; Brumback, Babette A; Weppelmann, Thomas A; Morris, J Glenn; Ali, Afsar
2016-08-15
Motivated by an investigation of the effect of surface water temperature on the presence of Vibrio cholerae in water samples collected from different fixed surface water monitoring sites in Haiti in different months, we investigated methods to adjust for unmeasured confounding due to either of the two crossed factors site and month. In the process, we extended previous methods that adjust for unmeasured confounding due to one nesting factor (such as site, which nests the water samples from different months) to the case of two crossed factors. First, we developed a conditional pseudolikelihood estimator that eliminates fixed effects for the levels of each of the crossed factors from the estimating equation. Using the theory of U-Statistics for independent but non-identically distributed vectors, we show that our estimator is consistent and asymptotically normal, but that its variance depends on the nuisance parameters and thus cannot be easily estimated. Consequently, we apply our estimator in conjunction with a permutation test, and we investigate use of the pigeonhole bootstrap and the jackknife for constructing confidence intervals. We also incorporate our estimator into a diagnostic test for a logistic mixed model with crossed random effects and no unmeasured confounding. For comparison, we investigate between-within models extended to two crossed factors. These generalized linear mixed models include covariate means for each level of each factor in order to adjust for the unmeasured confounding. We conduct simulation studies, and we apply the methods to the Haitian data. Copyright © 2016 John Wiley & Sons, Ltd.
Institute of Scientific and Technical Information of China (English)
L. Miranda-Aragón; E.J. Trevi(n)o-Garza; J. Jiménez-Pérez; O.A. Aguirre-Calderón; M.A. González-Tagle; M. Pompa-García; C.A. Aguirre-Salado
2012-01-01
Determining underlying factors that foster deforestation and delineating forest areas by levels of susceptibility are of the main challenges when defining policies for forest management and planning at regional scale.The susceptibility to deforestation of remaining forest ecosystems (shrubland,temperate forest and rainforest) was conducted in the state of San Luis Potosi,located in north central Mexico.Spatial analysis techniques were used to detect the deforested areas in the study area during 1993-2007.Logistic regression was used to relate explanatory variables (such as social,investment,forest production,biophysical and proximity factors) with susceptibility to deforestation to construct predictive models with two focuses:general and by biogeographical zone.In all models,deforestation has positive correlation with distance to rainfed agriculture,and negative correlation with slope,distance to roads and distance to towns.Other variables were significant in some cases,but in others they had dual relationships,which varied in each biogeographical zone.The results show that the remaining rainforest of Huasteca region is highly susceptible to deforestation.Both approaches show that more than 70％ of the current rainforest area has high and very high levels of susceptibility to deforestation.The values represent a serious concern with global warming whether tree carbon is released to atmosphere.However,after some considerations,encouraging forest environmental services appears to be the best alternative to achieve sustainabie forest management.
Predicting the "graduate on time (GOT)" of PhD students using binary logistics regression model
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.
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.
Ghazali, Amirul Syafiq Mohd; Ali, Zalila; Noor, Norlida Mohd; Baharum, Adam
2015-10-01
Multinomial logistic regression is widely used to model the outcomes of a polytomous response variable, a categorical dependent variable with more than two categories. The model assumes that the conditional mean of the dependent categorical variables is the logistic function of an affine combination of predictor variables. Its procedure gives a number of logistic regression models that make specific comparisons of the response categories. When there are q categories of the response variable, the model consists of q-1 logit equations which are fitted simultaneously. The model is validated by variable selection procedures, tests of regression coefficients, a significant test of the overall model, goodness-of-fit measures, and validation of predicted probabilities using odds ratio. This study used the multinomial logistic regression model to investigate obesity and overweight among primary school students in a rural area on the basis of their demographic profiles, lifestyles and on the diet and food intake. The results indicated that obesity and overweight of students are related to gender, religion, sleep duration, time spent on electronic games, breakfast intake in a week, with whom meals are taken, protein intake, and also, the interaction between breakfast intake in a week with sleep duration, and the interaction between gender and protein intake.
Pradhan, Biswajeet
Recently, in 2006 and 2007 heavy monsoons rainfall have triggered floods along Malaysia's east coast as well as in southern state of Johor. The hardest hit areas are along the east coast of peninsular Malaysia in the states of Kelantan, Terengganu and Pahang. The city of Johor was particularly hard hit in southern side. The flood cost nearly billion ringgit of property and many lives. The extent of damage could have been reduced or minimized if an early warning system would have been in place. This paper deals with flood susceptibility analysis using logistic regression model. We have evaluated the flood susceptibility and the effect of flood-related factors along the Kelantan river basin using the Geographic Information System (GIS) and remote sensing data. Previous flooded areas were extracted from archived radarsat images using image processing tools. Flood susceptibility mapping was conducted in the study area along the Kelantan River using radarsat imagery and then enlarged to 1:25,000 scales. Topographical, hydrological, geological data and satellite images were collected, processed, and constructed into a spatial database using GIS and image processing. The factors chosen that influence flood occurrence were: topographic slope, topographic aspect, topographic curvature, DEM and distance from river drainage, all from the topographic database; flow direction, flow accumulation, extracted from hydrological database; geology and distance from lineament, taken from the geologic database; land use from SPOT satellite images; soil texture from soil database; and the vegetation index value from SPOT satellite images. Flood susceptible areas were analyzed and mapped using the probability-logistic regression model. Results indicate that flood prone areas can be performed at 1:25,000 which is comparable to some conventional flood hazard map scales. The flood prone areas delineated on these maps correspond to areas that would be inundated by significant flooding
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.
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 topical sections named: maritime shipping, road transport, vehicle routing problems, aviation applications, and logistics and supply chain management....
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 topical sections named: maritime shipping, road transport, vehicle routing problems, aviation applications, and logistics and supply chain management....
M.P. de Brito (Marisa); S.D.P. Flapper; R. Dekker (Rommert)
2002-01-01
textabstractThis paper gives an overview of scientific literature that describes and discusses cases of reverse logistics activities in practice. Over sixty case studies are considered. Based on these studies we are able to indicate critical factors for the practice of reverse logistics. In addi
The Development Model of Yueyang Port Logistics%岳阳港口物流发展模式探讨
Institute of Scientific and Technical Information of China (English)
李申; 陶婷
2014-01-01
文中从岳阳港口物流发展现状出发，得出岳阳迫切需要发展港口物流的结论。通过结合岳阳港口实际，运用灰色综合评价法对目前岳阳港口物流发展模式进行分析并提出最优方案。%In this paper,the current situation of development of port logistics Yueyang,the urgent need for development of port logistics Yueyang conclusions.Yueyang port through the grey comprehensive evaluation method model.Yueyang port logistics of the current model analysis and put forward the best programs.
Zhou, Lim Yi; Shan, Fam Pei; Shimizu, Kunio; Imoto, Tomoaki; Lateh, Habibah; Peng, Koay Swee
2017-08-01
A comparative study of logistic regression, support vector machine (SVM) and least square support vector machine (LSSVM) models has been done to predict the slope failure (landslide) along East-West Highway (Gerik-Jeli). The effects of two monsoon seasons (southwest and northeast) that occur in Malaysia are considered in this study. Two related factors of occurrence of slope failure are included in this study: rainfall and underground water. For each method, two predictive models are constructed, namely SOUTHWEST and NORTHEAST models. Based on the results obtained from logistic regression models, two factors (rainfall and underground water level) contribute to the occurrence of slope failure. The accuracies of the three statistical models for two monsoon seasons are verified by using Relative Operating Characteristics curves. The validation results showed that all models produced prediction of high accuracy. For the results of SVM and LSSVM, the models using RBF kernel showed better prediction compared to the models using linear kernel. The comparative results showed that, for SOUTHWEST models, three statistical models have relatively similar performance. For NORTHEAST models, logistic regression has the best predictive efficiency whereas the SVM model has the second best predictive efficiency.
Examining item-position effects in large-scale assessment using the Linear Logistic Test Model
Directory of Open Access Journals (Sweden)
CHRISTINE HOHENSINN
2008-09-01
Full Text Available When administering large-scale assessments, item-position effects are of particular importance because the applied test designs very often contain several test booklets with the same items presented at different test positions. Establishing such position effects would be most critical; it would mean that the estimated item parameters do not depend exclusively on the items’ difficulties due to content but also on their presentation positions. As a consequence, item calibration would be biased. By means of the linear logistic test model (LLTM, item-position effects can be tested. In this paper, the results of a simulation study demonstrating how LLTM is indeed able to detect certain position effects in the framework of a large-scale assessment are presented first. Second, empirical item-position effects of a specific large-scale competence assessment in mathematics (4th grade students are analyzed using the LLTM. The results indicate that a small fatigue effect seems to take place. The most important consequence of the given paper is that it is advisable to try pertinent simulation studies before an analysis of empirical data takes place; the reason is, that for the given example, the suggested Likelihood-Ratio test neither holds the nominal type-I-risk, nor qualifies as “robust”, and furthermore occasionally shows very low power.
A semiparametric Wald statistic for testing logistic regression models based on case-control data
Institute of Scientific and Technical Information of China (English)
WAN ShuWen
2008-01-01
We propose a semiparametric Wald statistic to test the validity of logistic regression models based on case-control data.The test statistic is constructed using a semiparametric ROC curve estimator and a nonparametric ROC curve estimator.The statistic has an asymptotic chi-squared distribution and is an alternative to the Kolmogorov-Smirnov-type statistic proposed by Qin and Zhang in 1997,the chi-squared-type statistic proposed by Zhang in 1999 and the information matrix test statistic proposed by Zhang in 2001.The statistic is easy to compute in the sense that it requires none of the following methods:using a bootstrap method to find its critical values,partitioning the sample data or inverting a high-dimensional matrix.We present some results on simulation and on analysis of two real examples.Moreover,we discuss how to extend our statistic to a family of statistics and how to construct its Kolmogorov-Smirnov counterpart.
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.
CPAT: Coding-Potential Assessment Tool using an alignment-free logistic regression model.
Wang, Liguo; Park, Hyun Jung; Dasari, Surendra; Wang, Shengqin; Kocher, Jean-Pierre; Li, Wei
2013-04-01
Thousands of novel transcripts have been identified using deep transcriptome sequencing. This discovery of large and 'hidden' transcriptome rejuvenates the demand for methods that can rapidly distinguish between coding and noncoding RNA. Here, we present a novel alignment-free method, Coding Potential Assessment Tool (CPAT), which rapidly recognizes coding and noncoding transcripts from a large pool of candidates. To this end, CPAT uses a logistic regression model built with four sequence features: open reading frame size, open reading frame coverage, Fickett TESTCODE statistic and hexamer usage bias. CPAT software outperformed (sensitivity: 0.96, specificity: 0.97) other state-of-the-art alignment-based software such as Coding-Potential Calculator (sensitivity: 0.99, specificity: 0.74) and Phylo Codon Substitution Frequencies (sensitivity: 0.90, specificity: 0.63). In addition to high accuracy, CPAT is approximately four orders of magnitude faster than Coding-Potential Calculator and Phylo Codon Substitution Frequencies, enabling its users to process thousands of transcripts within seconds. The software accepts input sequences in either FASTA- or BED-formatted data files. We also developed a web interface for CPAT that allows users to submit sequences and receive the prediction results almost instantly.
Data sharing requirements of supply - And logistics innovations - Towards a maturity model
Hofman, W.J.
2016-01-01
Supply - and logistics innovations require data of different, heterogeneous sources. Supply chain resilience for instance requires visibility of goods flows and data of planned infrastructure maintenance and unforeseen accidents or incidents that may cause delays. Technically, there are different wa
Applicability of logistic model and integrated satellite data for rice crop phenology detection
Chen, Chi-Farn; Son, Nguyen-Thanh; Chen, Cheng-Ru; Chang, Ly-Yu; Chiang, Shou-Hao
2016-04-01
Changes in climate condition through global warming locally altered climatic and hydrological conditions and likely trigger the increase of insect populations and diseases, causing the potential loss of rice yields. Because the rice fields damaged by diseases or insects may affect neighbouring fields, monitoring the cropping progress was important to provide agronomic planners with valuable information that could be used to timely devise strategies to mitigate possible impacts on the potential yield. This study aimed to develop an approach to monitor rice sowing and harvesting progress from the integrated Moderate Resolution Imaging Spectroradiometer (MODIS)-Landsat satellite data. We processed for the 2007 winter-spring and summer-autumn cropping seasons in 2007, following four main steps: (1) constructing a set of MODIS-Landsat fusion data using the spatiotemporal adaptive reflectance fusion model (STARFM), (2) creating smooth time-series enhanced vegetation 2 (EVI2) data using the commonly-used empirical mode decomposition (EMD), (3) detecting key phenological stages of rice crops the double logistic algorithm, and (4) error verification of the detected sowing and harvesting dates using field data. The comparison results between the EVI2 data derived from the fusion data and that from the Landsat yielded close agreement between these two datasets (R2 > 0.9). The double logistic algorithm applied to the filtered time-series EVI2 data to estimate phenological events of rice crops indicated the validity of our approach for monitoring the progress of sowing and harvesting activities in the region. The results obtained by comparisons between the estimated sowing/ harvesting dates and the field survey data indicated that the root mean squared error (RMSE) values archived for the winter-spring crop were respectively 8.4 and 5.5 days, while those for the summer-autumn crop were 9.4 and 12.8 days, respectively. The results obtained from this study could provide decision
Application of the TDABC model in the logistics process using different capacity cost rates
Paulo Afonso; Alex Santana
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 in...
Application of the TDABC Model in the Logistics Process Using Different Capacity Cost Rates
Alfonso, 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...
Generalization of the logistic distribution in the dynamic model of wind direction
Kaplya, E. V.
2016-12-01
Statistical regularity in the dynamics of wind direction has been found. The density distribution of the increment of the wind-direction angle has been approximated using a generalized advanced logistic distribution. The advanced logistic distribution involves an additional power-law parameter. The parameters of the approximation function have been computed from experimental data using the method of least squares. The consistency of the proposed function with meteorological data has been tested using Pearson's chisquared test and the Kolmogorov test.
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...
Bizzotto, Roberto; zamuner, stefano; Mezzalana, Enrica; De Nicolao, Giuseppe; Gomeni, Roberto; Hooker, Andrew C; Karlsson, Mats O.
2011-01-01
Mixed-effect Markov chain models have been recently proposed to characterize the time course of transition probabilities between sleep stages in insomniac patients. The most recent one, based on multinomial logistic functions, was used as a base to develop a final model combining the strengths of the existing ones. This final model was validated on placebo data applying also new diagnostic methods and then used for the inclusion of potential age, gender, and BMI effects. Internal validation w...
Noce, Anthony A.; McKeown, Larry
2008-01-01
Internet diffusion is not homogeneous and depends on many factors. This study uses data from the Canadian Internet Use Survey (CIUS) to explore the extent demographic variables affect Internet use by individuals in Canada. A logistic model confirms that certain factors, educational attainment, and geography in particular influence Internet use in…
Gordovil-Merino, Amalia; Guardia-Olmos, Joan; Pero-Cebollero, Maribel
2012-01-01
In this paper, we used simulations to compare the performance of classical and Bayesian estimations in logistic regression models using small samples. In the performed simulations, conditions were varied, including the type of relationship between independent and dependent variable values (i.e., unrelated and related values), the type of variable…
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…
Institute of Scientific and Technical Information of China (English)
张占卿
2013-01-01
Objective To explore the efficacy of logistic regression modeling based on plasma amino acid profile and patient age,for diagnosing hepatic fibrosis in patients with chronic hepatitis B (CHB) .Methods One-hundredand-forty-eight patients (108 males;mean age:38.1±11.9 years,range:16—72 years) histologically
MacDonald, George T.
2014-01-01
A simulation study was conducted to explore the performance of the linear logistic test model (LLTM) when the relationships between items and cognitive components were misspecified. Factors manipulated included percent of misspecification (0%, 1%, 5%, 10%, and 15%), form of misspecification (under-specification, balanced misspecification, and…
Logistics Innovation Process Revisited
DEFF Research Database (Denmark)
Gammelgaard, Britta; Su, Shong-Iee Ivan; Yang, Su-Lan
2011-01-01
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...... into the process of a logistics innovation in an oriental healthcare supply chain context. The study is, however, still limited in disclosing end-to-end supply chain benefits including concrete performance improvements at the suppliers. Examining logistics innovation processes should result not only......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...
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.
Directory of Open Access Journals (Sweden)
Portnoy Diane L
2004-08-01
Full Text Available Abstract Background Previous smallpox ring vaccination models based on contact tracing over a network suggest that ring vaccination would be effective, but have not explicitly included response logistics and limited numbers of vaccinators. Methods We developed a continuous-time stochastic simulation of smallpox transmission, including network structure, post-exposure vaccination, vaccination of contacts of contacts, limited response capacity, heterogeneity in symptoms and infectiousness, vaccination prior to the discontinuation of routine vaccination, more rapid diagnosis due to public awareness, surveillance of asymptomatic contacts, and isolation of cases. Results We found that even in cases of very rapidly spreading smallpox, ring vaccination (when coupled with surveillance is sufficient in most cases to eliminate smallpox quickly, assuming that 95% of household contacts are traced, 80% of workplace or social contacts are traced, and no casual contacts are traced, and that in most cases the ability to trace 1–5 individuals per day per index case is sufficient. If smallpox is assumed to be transmitted very quickly to contacts, it may at times escape containment by ring vaccination, but could be controlled in these circumstances by mass vaccination. Conclusions Small introductions of smallpox are likely to be easily contained by ring vaccination, provided contact tracing is feasible. Uncertainties in the nature of bioterrorist smallpox (infectiousness, vaccine efficacy support continued planning for ring vaccination as well as mass vaccination. If initiated, ring vaccination should be conducted without delays in vaccination, should include contacts of contacts (whenever there is sufficient capacity and should be accompanied by increased public awareness and surveillance.
Predictors of work injury in underground mines——an application of a logistic regression model
Institute of Scientific and Technical Information of China (English)
E S. Pau
2009-01-01
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.
Institute of Scientific and Technical Information of China (English)
Tianqi; ZHANG
2013-01-01
Through an empirical analysis of the agricultural logistics model and agricultural products quality control system in Pinggu district of Beijing, a model was studied to control the agricultural quality by agricultural logistics. The model adopts modern logistics supply chain, which firstly, establishes a modern logistics distribution system for veterinary drugs by the means of suppliers control, chain management and cold chain distribution; secondly, organizes the veterinary experts and doctors to provide real-time technical services so as to control the abuse of drugs; thirdly, realizes the supervision of local veterinary drugs and diseases. Thus the quality of animal products is guaranteed, and the model is worthy to be popularized.
Institute of Scientific and Technical Information of China (English)
梁世贞
2012-01-01
Through the studies of the concept and the mode of operation of the fnurth party logistics, and the analysis of the characteristics and the development trend of modem port logistics, to point out the function of the fourth party logistics to the development of modem port logistics, and finally advances the port logistics development model based on fourth party logistics. This paper mainly discusses how to use the advanced fourth party logistics to improve the management and service level of the port, then to increase their competitiveness.%通过对第四方物流的概念和运作模式进行研究,并分析了现代港口物流的特点和发展趋势,指出了第四方物流对于现代港口物流的发展作用,最后提出引入第四方物流以后现代港口物流的发展模式,着重探讨如何利用第四方物流的先进性提高港口的管理和服务水平,增强其竞争力。
The reliable solution and computation time of variable parameters Logistic model
Pengfei, Wang
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. However, the mean Tc trends to a constant value once the sample number is large enough. The maximum, minimum and probable distribution function of Tc is also obtained, which can help us to identify the robustness of applying a nonlinear time series theory to forecasting while using the VPLM output. In addition, the Tc of the fixed parameter experiments of the logistic map was obtained, and the results suggested that this Tc matches the theoretical formula predicted value.
Chen, Han; Wang, Chaolong; Conomos, Matthew P.; Stilp, Adrienne M.; Li, Zilin; Sofer, Tamar; Szpiro, Adam A.; Chen, Wei; Brehm, John M.; Celedón, Juan C.; Redline, Susan; Papanicolaou, George J.; Thornton, Timothy A.; Laurie, Cathy C.; Rice, Kenneth; Lin, Xihong
2016-01-01
Linear mixed models (LMMs) are widely used in genome-wide association studies (GWASs) to account for population structure and relatedness, for both continuous and binary traits. Motivated by the failure of LMMs to control type I errors in a GWAS of asthma, a binary trait, we show that LMMs are generally inappropriate for analyzing binary traits when population stratification leads to violation of the LMM’s constant-residual variance assumption. To overcome this problem, we develop a computationally efficient logistic mixed model approach for genome-wide analysis of binary traits, the generalized linear mixed model association test (GMMAT). This approach fits a logistic mixed model once per GWAS and performs score tests under the null hypothesis of no association between a binary trait and individual genetic variants. We show in simulation studies and real data analysis that GMMAT effectively controls for population structure and relatedness when analyzing binary traits in a wide variety of study designs. PMID:27018471
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.
Research of Secondary Vocational Logistics Training Model%中职物流人才培养模式研究
Institute of Scientific and Technical Information of China (English)
欧才学
2012-01-01
As the global integration and regional development of today＇s economic, modern logistics industry is booming andhas become a new economic growth point. At the same time, China＇s logistics talent is very scarce in the 21st century, lo- gistics personnel is listed as one of 12 categories of personnel shortage. The key of speeding up skilled logistics personnel training is vocational education. This paper attempts to analyze the problems of logistics vocational skills training, determine the objectives of logistics vocational training, explore an actual right vocational training model for logistics personnel training, and provide some operational advice.%随着世界经济一体化和区域化的发展。现代物流产业正在蓬勃兴起，并已成为国民经济新的增长点。然而，目前我国物流人才却十分匮乏，21世纪，物流人才被列为12类紧缺人才之一。、加快物流技能人才的培养．关键在职业教育．文章试图分析中职物流技能人才培养中存在的问题．确定中职物流人才的培养目标，探索适合中职学校实际情况的人才培养模式，为物流技能人才的培养提供操作性建议。
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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.
Huang, Hui; Li, Yuyu; Huang, Bo; Pi, Xing
2015-07-01
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.
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-
LOGISTICS - EVOLUTION THROUGH INNOVATION
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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
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.
SIMULATION OF LOGISTICS PROCESSES
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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.
Two-parameter asymptotics in magnetic Weyl calculus
Lein, Max
2010-12-01
This paper is concerned with small parameter asymptotics of magnetic quantum systems. In addition to a semiclassical parameter ɛ, the case of small coupling λ to the magnetic vector potential naturally occurs in this context. Magnetic Weyl calculus is adapted to incorporate both parameters, at least one of which needs to be small. Of particular interest is the expansion of the Weyl product which can be used to expand the product of operators in a small parameter, a technique which is prominent to obtain perturbation expansions. Three asymptotic expansions for the magnetic Weyl product of two Hörmander class symbols are proven as (i) ɛ ≪ 1 and λ ≪ 1, (ii) ɛ ≪ 1 and λ = 1, as well as (iii) ɛ = 1 and λ ≪ 1. Expansions (i) and (iii) are impossible to obtain with ordinary Weyl calculus. Furthermore, I relate the results derived by ordinary Weyl calculus with those obtained with magnetic Weyl calculus by one- and two-parameter expansions. To show the power and versatility of magnetic Weyl calculus, I derive the semirelativistic Pauli equation as a scaling limit from the Dirac equation up to errors of fourth order in 1/c.
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...
Institute of Scientific and Technical Information of China (English)
WV Xiao-Bo; MO Juan; YANG Ming-Hao; ZHENG Qiao-Hua; GU Hua-Guang; HEN Wei
2008-01-01
@@ Two different bifurcation scenarios, one is novel and the other is relatively simpler, in the transition procedures of neural firing patterns are studied in biological experiments on a neural pacemaker by adjusting two parameters. The experimental observations are simulated with a relevant theoretical model neuron. The deterministic non-periodic firing pattern lying within the novel bifurcation scenario is suggested to be a new case of chaos, which has not been observed in previous neurodynamical experiments.
Hanson, Erin K; Mirza, Mohid; Rekab, Kamel; Ballantyne, Jack
2014-11-01
We report the identification of sensitive and specific miRNA biomarkers for menstrual blood, a tissue that might provide probative information in certain specialized instances. We incorporated these biomarkers into qPCR assays and developed a quantitative statistical model using logistic regression that permits the prediction of menstrual blood in a forensic sample with a high, and measurable, degree of accuracy. Using the developed model, we achieved 100% accuracy in determining the body fluid of interest for a set of test samples (i.e. samples not used in model development). The development, and details, of the logistic regression model are described. Testing and evaluation of the finalized logistic regression modeled assay using a small number of samples was carried out to preliminarily estimate the limit of detection (LOD), specificity in admixed samples and expression of the menstrual blood miRNA biomarkers throughout the menstrual cycle (25-28 days). The LOD was blood was identified only during the menses phase of the female reproductive cycle in two donors.
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.
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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.
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)
Zheng, Wei; Zhao, Yang; Lu, Yuefeng; Miao, Harry; Liu, Hengchang
2016-01-01
We introduce a three-parameter logistic model to analyze the dose limiting toxicity (DLT) as a time-to-event endpoint in oncology Phase I trials. In the proposed model, patients are allowed to stay on trial without the constraint of a maximum follow-up time. Our model accommodates late-onset DLT as well as early-onset DLT, by both of which the dose recommendation is informed. A Bayesian approach is used to incorporate prior knowledge of the test treatment into dose recommendation. Simulation examples show that our proposed model has good operating characteristics in assessing the maximum tolerated dose (MTD).
军事应急物流网络模型研究%Research on Military Emergency Logistics Network Model
Institute of Scientific and Technical Information of China (English)
陈军; 智军; 时光
2015-01-01
文中针对军事应急物流体系基础设施的基本特征，把军事应急物流中的专业设施和功能设施抽象为网络节点，按照连通性将网络节点之间的物流线路作为网络边，最终建立了多种运输方式联合运输条件下的物流保障网络模型，并对其基本特征进行了分析。%For the basic characteristics of the military infrastructure of emergency logistics system, the professional and functional facilities in the military emergency logistics are abstracted for the network node.According to the connectivity,logistics route between network nodes are set as network edge.Finally it establishes a logistics support network model and its basic characteristics are analyzed.
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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.
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.
The adaptive Lasso for Logistic regression models%Logistic模型中参数的自适应Lasso估计
Institute of Scientific and Technical Information of China (English)
王娉; 郭鹏江; 夏志明
2012-01-01
目的 研究Logistic模型的参数估计.方法 在L1罚中引用一个自适应的权,即自适应Lasso方法.结果 自适应Lasso方法对Logistic模型同时进行了模型选择和参数估计.结论 在一定的正则条件下,Logistic模型的自适应Lasso估计是满足Oracle性质的.%Aim To estimate the parameters in the Logistic model. Methods Adaptive weights are used in the L1 penalty, which is adaptive Lasso. Results The adaptive Lasso selects variables and estimates parameters simulta-neously for the Logistic model. Conclusion Under certain regular conditions, the adaptive Lasso enjoys the oracle properties.
Li, J.; Gray, B.R.; Bates, D.M.
2008-01-01
Partitioning the variance of a response by design levels is challenging for binomial and other discrete outcomes. Goldstein (2003) proposed four definitions for variance partitioning coefficients (VPC) under a two-level logistic regression model. In this study, we explicitly derived formulae for multi-level logistic regression model and subsequently studied the distributional properties of the calculated VPCs. Using simulations and a vegetation dataset, we demonstrated associations between different VPC definitions, the importance of methods for estimating VPCs (by comparing VPC obtained using Laplace and penalized quasilikehood methods), and bivariate dependence between VPCs calculated at different levels. Such an empirical study lends an immediate support to wider applications of VPC in scientific data analysis.
Paché, Gilles
2007-01-01
Abstract Works conducted in logistics management mostly emphasize the importance of a `time compression' strategy to develop a sustainable competitive advantage. At the level of the design, manufacturing or distribution of products to consumers, high-speed orientation is now considered to be a universal source of performance. Drawing from current developments in the French food retailing industry, the paper...
Analysing the forward premium anomaly using a Logistic Smooth Transition Regression model.
Sofiane Amri
2008-01-01
Several researchers have suggested that exchange rates may be characterized by nonlinear behaviour. This paper examines these nonlinearities and asymetries and estimates a Logistic Transition Regression (LSTR) of Fama Regression with the Risk Adjusted Forward Premia as transition variable. Results confirm the existence of nonlinear dynamics in the relationship between spot exchange rate differential and the forward premium for all the currencies of the sample and for all maturities (three and...
Resolving forward-reverse logistics multi-period model using evolutionary algorithms
Kumar, A.; Kumar, V.; Brady, M.; Garza-Reyes, J. A.; Simpson, M.
2016-01-01
In the changing competitive landscape and with growing environmental awareness, reverse logistics issues have become prominent in manufacturing organizations. As a result there is an increasing focus on green aspects of the supply chain to reduce environmental impacts and ensure environmental efficiency. This is largely driven by changes made in government rules and regulations with which organizations must comply in order to successfully operate in different regions of the world. Therefore, ...
1993-06-18
suspended from issue or use. table-of-allowance- minimun -quantity-required The minimum quantity necessary to accomplish the assigned mission. table-of...required supplies to compensate for this time, and considerable expenses are dedicated to the inventory process (i.e., wages , overtime, utilities...American act, and mandatory wage requirements. If the military medical logistics activity is to operate as current civilian practices dictate, relief
1994-09-01
Pipeline stock is calculated by forecasting the projected requirements due to transportation time and counting out the amount of stock needed to cover...the "lead time" delay. Time needed for the transportation of an order is referred to as the lead time. "Lead time is the amount of time between the...Defenae Logistica Agency The Defense Logistics Agency (DLA) is an agency of the Department of Defense. "The National Security Act (NSA) established
A New Availability-Payment Model for Pricing Performance-Based Logistics Contracts
2014-06-17
complex and it is unclear how to optimally apply PBL contract mechanisms. For example, a recent study of PBL effectiveness ( Boyce and Banghart...level (called system- level by Boyce and Banghart) PBL 6 out of 12 contracts resulted in either cost increases or indeterminable cost changes...School of Business & Public Policy - 16 - Naval Postgraduate School References Boyce , J., and Banghart, A. (2012). Performance based logistics and
A Decision Support Model Suggestion for Logistics Support Unit in Risky Environment
AĞDAŞ, Mustafa; Eroğlu, Özer
2016-01-01
Abstract. Storage facilities have an important role for uninterrupted product/service flow and ensuring continuity in supply chains. Criteria, which will be taken into account for the location of this facilities, and criteria values, can alter in accordance with private or public sector and risk environment as well. Besides logistics costs, transportation opportunities and proximity to the customers, risk based criteria such as terror, sabotage, air strikes, and natural disasters play an impo...
The reliable solution and computation time of variable parameters logistic model
Wang, Pengfei; Pan, Xinnong
2017-04-01
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.
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Anupam Pathak
2014-11-01
Full Text Available Abstract: Problem Statement: The two-parameter exponentiated Rayleigh distribution has been widely used especially in the modelling of life time event data. It provides a statistical model which has a wide variety of application in many areas and the main advantage is its ability in the context of life time event among other distributions. The uniformly minimum variance unbiased and maximum likelihood estimation methods are the way to estimate the parameters of the distribution. In this study we explore and compare the performance of the uniformly minimum variance unbiased and maximum likelihood estimators of the reliability function R(t=P(X>t and P=P(X>Y for the two-parameter exponentiated Rayleigh distribution. Approach: A new technique of obtaining these parametric functions is introduced in which major role is played by the powers of the parameter(s and the functional forms of the parametric functions to be estimated are not needed. We explore the performance of these estimators numerically under varying conditions. Through the simulation study a comparison are made on the performance of these estimators with respect to the Biasness, Mean Square Error (MSE, 95% confidence length and corresponding coverage percentage. Conclusion: Based on the results of simulation study the UMVUES of R(t and ‘P’ for the two-parameter exponentiated Rayleigh distribution found to be superior than MLES of R(t and ‘P’.
Phiri, Andrew
2015-01-01
This study contributes to the foregoing literature by investigating asymmetric behaviour within the South African short-run Phillips curve for three versions of the Phillips curve specification namely; the New Classical Phillips curve, the New Keynesian Phillips curve and the Hybrid New Keynesian Phillips curve. To this end, we employ a logistic smooth transition regression (LSTR) econometric model to each of the aforementioned versions of the Phillips curve specifications for quarterly data ...
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Jose Javier Gorgoso-Varela
2016-04-01
Full Text Available 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.
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.
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N.W. Surya Wardhani
2014-10-01
Full Text Available Modeling of food security based on the characteristics of the area will be affected by the geographical location which means that geographical location will affect the region’s potential. Therefore, we need a method of statistical modeling that takes into account the geographical location or the location factor observations. In this case, the research variables could be global means that the location affects the response variables significantly; when some of the predictor variables are global and the other variables are local, then Geographically Weighted Ordinal Logistic Regression Semiparametric (GWOLRS could be used to analyze the data. The data used is the resilience and food insecurity data in 2011 in East Java Province. The result showed that three predictor variables that influenced by the location are the percentage of poor (%, rice production per district (tons and life expectancy (%. Those three predictor variables are local because they have significant influence in some districts/cities but had no significant effect in other districts/cities, while other two variables that are clean water and good quality road length (km are assumed global because it is not a significant factor for the whole districts/towns in East Java .
Boghosian, Bruce M; Wang, Hongyan
2016-01-01
The addition of wealth-attained advantage (WAA) to the Yard-Sale Model (YSM) of asset exchange has been demonstrated to induce wealth condensation. In a model of WAA for which the bias is a continuous function of the wealth difference of the transacting agents, the condensation was shown to arise from a second-order phase transition to a coexistence regime. In this paper, we present the first analytic time-dependent results for this model, by showing that the condensed wealth obeys a logistic equation in time.
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.
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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.
Institute of Scientific and Technical Information of China (English)
张中强
2011-01-01
探讨了我国军事物流与民用物流的融合发展.首先,论述了军事物流与民用物流的相互关系,在此基础上解析了军民物流融合发展的影响要素,这些要素包括专业化的第三方物流、物流信息与技术、社会动员物流、第四方物流管理等.它们相互作用、相互促进,每一个要素的变化都将在整体上对军民物流的融合发展带来倍率效应.然后,探讨了保证与支撑这些要素有序健康发展的融合发展机制,把这种融合发展机制分为形成机制、成长机制和协调机制,并分别加以阐述.在这种机制的保证下,最后给出了各要素互动共生、协作发展的军民物流融合发展模式.%This article discusses the converging development of military logistics and the civilian logistics. First, the author discusses the relationship between military logistics and the civil logistics, then analysis the influence factors of the civilian and military logistics converging development, which including specialized third party logistics, logistics information and technology, social mobilization logistics, the fourth party logistics management, etc. The factors are mutual interactions and promotions. The change of each factors will bring the bring rate effect to the whole system. Second, the article discussed the mechanism to guarantee and support these factors fusion. The mechanism is divided into formation mechanism, growth mechanism and coordination mechanism, and explained respectively. Finally, the author suggests the model of interaction and mutualism, converging development between military and civilian logistics.
Schaeben, Helmut; Semmler, Georg
2016-09-01
The objective of prospectivity modeling is prediction of the conditional probability of the presence T = 1 or absence T = 0 of a target T given favorable or prohibitive predictors B, or construction of a two classes 0,1 classification of T. A special case of logistic regression called weights-of-evidence (WofE) is geologists' favorite method of prospectivity modeling due to its apparent simplicity. However, the numerical simplicity is deceiving as it is implied by the severe mathematical modeling assumption of joint conditional independence of all predictors given the target. General weights of evidence are explicitly introduced which are as simple to estimate as conventional weights, i.e., by counting, but do not require conditional independence. Complementary to the regression view is the classification view on prospectivity modeling. Boosting is the construction of a strong classifier from a set of weak classifiers. From the regression point of view it is closely related to logistic regression. Boost weights-of-evidence (BoostWofE) was introduced into prospectivity modeling to counterbalance violations of the assumption of conditional independence even though relaxation of modeling assumptions with respect to weak classifiers was not the (initial) purpose of boosting. In the original publication of BoostWofE a fabricated dataset was used to "validate" this approach. Using the same fabricated dataset it is shown that BoostWofE cannot generally compensate lacking conditional independence whatever the consecutively processing order of predictors. Thus the alleged features of BoostWofE are disproved by way of counterexamples, while theoretical findings are confirmed that logistic regression including interaction terms can exactly compensate violations of joint conditional independence if the predictors are indicators.
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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.
Prestack migration velocity analysis based on simplifi ed two-parameter moveout equation
Institute of Scientific and Technical Information of China (English)
Chen Hai-Feng; Li Xiang-Yang; Qian Zhong-Ping; Song Jian-Jun; Zhao Gui-Ling
2016-01-01
Stacking velocityVC2, vertical velocity ratioγ0, effective velocity ratioγef, and anisotropic parameterχef are correlated in the PS-converted-wave (PS-wave) anisotropic prestack Kirchhoff time migration (PKTM) velocity model and are thus difficult to independently determine. We extended the simplified two-parameter (stacking velocity VC2 and anisotropic parameterkef) moveout equation from stacking velocity analysis to PKTM velocity model updating and formed a new four-parameter (stacking velocityVC2, vertical velocity ratioγ0, effective velocity ratioγef, and anisotropic parameterkef) PS-wave anisotropic PKTM velocity model updating and processfl ow based on the simplifi ed two-parameter moveout equation. In the proposed method, first, the PS-wave two-parameter stacking velocity is analyzed to obtain the anisotropic PKTM initial velocity and anisotropic parameters; then, the velocity and anisotropic parameters are corrected by analyzing the residual moveout on common imaging point gathers after prestack time migration. The vertical velocity ratioγ0 of the prestack time migration velocity model is obtained with an appropriate method utilizing the P- and PS-wave stacked sections after level calibration. The initial effective velocity ratioγef is calculated using the Thomsen (1999) equation in combination with the P-wave velocity analysis; ultimately, the final velocity model of the effective velocity ratioγef is obtained by percentage scanning migration. This method simplifi es the PS-wave parameter estimation in high-quality imaging, reduces the uncertainty of multiparameter estimations, and obtains good imaging results in practice.
Battaglin, William A.; Ulery, Randy L.; Winterstein, Thomas; Welborn, Toby
2003-01-01
In the State of Texas, surface water (streams, canals, and reservoirs) and ground water are used as sources of public water supply. Surface-water sources of public water supply are susceptible to contamination from point and nonpoint sources. To help protect sources of drinking water and to aid water managers in designing protective yet cost-effective and risk-mitigated monitoring strategies, the Texas Commission on Environmental Quality and the U.S. Geological Survey developed procedures to assess the susceptibility of public water-supply source waters in Texas to the occurrence of 227 contaminants. One component of the assessments is the determination of susceptibility of surface-water sources to nonpoint-source contamination. To accomplish this, water-quality data at 323 monitoring sites were matched with geographic information system-derived watershed- characteristic data for the watersheds upstream from the sites. Logistic regression models then were developed to estimate the probability that a particular contaminant will exceed a threshold concentration specified by the Texas Commission on Environmental Quality. Logistic regression models were developed for 63 of the 227 contaminants. Of the remaining contaminants, 106 were not modeled because monitoring data were available at less than 10 percent of the monitoring sites; 29 were not modeled because there were less than 15 percent detections of the contaminant in the monitoring data; 27 were not modeled because of the lack of any monitoring data; and 2 were not modeled because threshold values were not specified.
Empirical Study of E-logistics System Based on Tibet Logistics Industry
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...
Empirical Study of E-logistics System Based on Tibet Logistics Industry
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...
Institute of Scientific and Technical Information of China (English)
黄吉; 蒋正祥
2012-01-01
In this article,the author selects 11 financial indices of 28 listed companies in Guangxi Zhuang Autonomous Region in Shanghai Stock Exchange and Shenzhen Stock Exchange in 2011.Among these financial indices,five indices are chosen as the major variables of explanation to establish the logistic regression model.After that,the logistic regression model is combined with the KMV Model.Through empirical analysis,the author finds that the logistic-KMV mixed model can attain better appraisal result.%文章选取沪深两市2011年28家广西上市公司的11个财务指标进行分析,选取5个为主要的解释变量,建立logistic回归模型。然后将logistic回归模型与KMV模型进行结合,通过实证分析发现,Logistic-KMV混合模型能取得更好的评价结果。
一种 Logistic 模型参数估计的新方法及应用%New Method of Logistic Model Parameter Estimation and Application
Institute of Scientific and Technical Information of China (English)
赵红; 王增辉
2014-01-01
介绍了 logistic 曲线参数估计的一种新方法,它是利用三次样条插值函数求导代替 logistic曲线在这一点的导数值,进而利用最小二乘法得出参数的估计值,通过实例分析表明本文提出的方法比一般的三点法估计的参数值 k 再用线性化方法估计的参数值 b ,c ,拟合精度更高。%This paper presened a new method of logistic growth curve for parameter estimation,which uses the cubic spline interpolation functions instead of growth curve in the derivative value,and then uses the least squares estimation method to derive the parameters.And the instance analysis and verification show that.the proposed approach can get the higher fitting precision.than the average of three point method to estimate the c and the linear regression estimate the parameter values of b and c .
Modeling data for pancreatitis in presence of a duodenal diverticula using logistic regression
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.
Using Logistic Regression to Model New York City Restaurant Grades Over a Two-Year Period
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David Nadler
2014-07-01
Full Text Available A knowledge gap exists in the role of restaurant type on the prediction of attaining the highest grade possible from the local health inspection agency. This study identified disparities using logistic regression between the issuance of a Grade A and restaurant type and location. This study tested the eight most inspected types of restaurants within the City of New York and calculated the odds ratios of their receiving the highest inspection grade by the New York City Department of Health and Mental Hygiene. A fitted equation has been proposed for the prediction of receiving the highest inspection grade based upon the citywide results of these eight restaurant types from calendar years 2011 and 2012. The results suggest that certain styles of restaurants have lower odds of receiving the highest grade in comparison to American-style restaurants.
A New ’Availability-Payment’ Model for Pricing Performance-Based Logistics Contracts
2014-04-30
effectiveness ( Boyce & Banghart, 2012), reported on the cost of 21 PBL ^Åèìáëáíáçå=oÉëÉ~êÅÜ=mêçÖê~ãW= `êÉ~íáåÖ=póåÉêÖó=Ñçê=fåÑçêãÉÇ=`Ü~åÖÉ= - 242...contracts where in 9 out of 9 component and subsystem-level PBL contracts the cost decreased, but for platform-level (called system-level by Boyce and...availability is measured for contract assessment purposes. References Boyce , J., & Banghart, A. (2012). Performance based logistics and project proof
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
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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.
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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.
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Reshani P. Liyanage
2016-08-01
Full Text Available This paper is focused on the growing need of integrating environmentally sound choices into supply-chain management. The concept of green economic practices driven by the environmental sustainability challenges posed the concept of green logistics, to evolve in the last few decades.To establish the field further, the purpose of this paper is twofold. First, it offers anextensive systematic review of literature on GL with a critical review of the studies that have been considered in the paper.Second, it offers a conceptual analytical model where the canonical capacitated vehicle routing problem is extended to add the measures of Carbon Dioxide (CO2 emissions. The proposed, multi objective optimization model tackles the conflicting objectives of CO2 emission reduction and cost minimization. The developed generic model integrates the traffic information in providing the user with opportunity to have more realistic solution. The model also enables strategic decision making to improve the GL operations while allowing greatercompetitive advantage
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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
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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.
Foraz, K; CERN. Geneva. TS Department
2005-01-01
More than 80’000 tons of materials have to be transported and installed down into the LHC tunnel. The magnet assemblies which represent about 50’000 tons, will be transported according to the master schedule between March 2005 and November 2006. Considering that these about 1’800 cryo-magnets will be transported at a maximum speed of 3 km/h in a narrow tube (where installation works and hardware commissioning activities are ongoing) this duration of 21 months is a real challenge. This paper aims at describing: - the information flows between the different people involved in the logistics attached to the cryo-magnets, - the organization chosen within the Installation Coordination group, - the problems encountered so far and the solutions adopted. The coordination process with other underground transport and activities, mainly for the QRL will also be presented.
Two-parameter Rankine Heat Pumps’ COP Equations
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Samuel Sunday Adefila
2012-05-01
Full Text Available Equations for ideal vapour compression heat pump coefficient of performance (COPR which contain two fit-parameters are reported in this work. These equations contain either temperature term alone or temperature and pressure terms as the only thermodynamic variable(s. The best equation gave error ≥5% over wide range of temperature-lift and for different working fluid types that include fluorocarbons, hydrocarbons and inorganic fluids. In these respects the equation performs better than the one-parameter models reported earlier.
Planning woody biomass logistics for energy production: A strategic decision model
Energy Technology Data Exchange (ETDEWEB)
Frombo, F.; Robba, M. [DIST, Department of Communication, Computer and System Sciences, University of Genova, Via Opera Pia 13, 16145 Genova (Italy)]|[CIMA, Interuniversity Center of research in Environmental Monitoring, Via A. Magliotto 2, 17100 Savona (Italy)]|[Renewable Energy Laboratory, Modelling and Optimization, Via A. Magliotto 2, 17100 Savona (Italy); Minciardi, R.; Sacile, R. [DIST, Department of Communication, Computer and System Sciences, University of Genova, Via Opera Pia 13, 16145 Genova (Italy)]|[CIMA, Interuniversity Center of research in Environmental Monitoring, Via A. Magliotto 2, 17100 Savona (Italy); Rosso, F. [CIMA, Interuniversity Center of research in Environmental Monitoring, Via A. Magliotto 2, 17100 Savona (Italy)]|[Renewable Energy Laboratory, Modelling and Optimization, Via A. Magliotto 2, 17100 Savona (Italy)
2009-03-15
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)
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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.
Bennema, S C; Molento, M B; Scholte, R G; Carvalho, O S; Pritsch, I
2017-11-01
Fascioliasis is a condition caused by the trematode Fasciola hepatica. In this paper, the spatial distribution of F. hepatica in bovines in Brazil was modelled using a decision tree approach and a logistic regression, combined with a geographic information system (GIS) query. In the decision tree and the logistic model, isothermality had the strongest influence on disease prevalence. Also, the 50-year average precipitation in the warmest quarter of the year was included as a risk factor, having a negative influence on the parasite prevalence. The risk maps developed using both techniques, showed a predicted higher prevalence mainly in the South of Brazil. The prediction performance seemed to be high, but both techniques failed to reach a high accuracy in predicting the medium and high prevalence classes to the entire country. The GIS query map, based on the range of isothermality, minimum temperature of coldest month, precipitation of warmest quarter of the year, altitude and the average dailyland surface temperature, showed a possibility of presence of F. hepatica in a very large area. The risk maps produced using these methods can be used to focus activities of animal and public health programmes, even on non-evaluated F. hepatica areas.
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.
2001-01-01
textabstractReverse logistics, that is, all operations related to the reuse of used products, excess inventory and packaging materials, gain increasing attention globally both for their promising financial potentials, the sustainable growth alternative they offer and the environmental positive impact they have. In this paper, we introduce reverse logistics and we explain how the adoption of e-commerce provides new possibilities to existing business models and what are the new e-business model...
Liu, Xing
2008-01-01
The proportional odds (PO) model, which is also called cumulative odds model (Agresti, 1996, 2002 ; Armstrong & Sloan, 1989; Long, 1997, Long & Freese, 2006; McCullagh, 1980; McCullagh & Nelder, 1989; Powers & Xie, 2000; O'Connell, 2006), is one of the most commonly used models for the analysis of ordinal categorical data and comes from the class…
Bizzotto, Roberto; Zamuner, Stefano; Mezzalana, Enrica; De Nicolao, Giuseppe; Gomeni, Roberto; Hooker, Andrew C; Karlsson, Mats O
2011-09-01
Mixed-effect Markov chain models have been recently proposed to characterize the time course of transition probabilities between sleep stages in insomniac patients. The most recent one, based on multinomial logistic functions, was used as a base to develop a final model combining the strengths of the existing ones. This final model was validated on placebo data applying also new diagnostic methods and then used for the inclusion of potential age, gender, and BMI effects. Internal validation was performed through simplified posterior predictive check (sPPC), visual predictive check (VPC) for categorical data, and new visual methods based on stochastic simulation and estimation and called visual estimation check (VEC). External validation mainly relied on the evaluation of the objective function value and sPPC. Covariate effects were identified through stepwise covariate modeling within NONMEM VI. New model features were introduced in the model, providing significant sPPC improvements. Outcomes from VPC, VEC, and external validation were generally very good. Age, gender, and BMI were found to be statistically significant covariates, but their inclusion did not improve substantially the model's predictive performance. In summary, an improved model for sleep internal architecture has been developed and suitably validated in insomniac patients treated with placebo. Thereafter, covariate effects have been included into the final model.
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
An architecture and common data model for open data-based cargo-tracking in synchromodal logistics
Bol Raap, Wouter; Iacob, Maria-Eugenia; Sinderen, van Marten; Piest, Sebastian; Debruyne, Christophe; Panetto, Hervé; Meersman, Robert; Dillon, Tharam; Kuehn, Eva; O'Sullivan, Declan; Agostino Ardagna, Claudio
2016-01-01
In logistics, questions as “Where is my container?” and “When does my container arrive?” can often not be answered with sufficient precision, which restricts the ability of logistics service providers to be efficient. Since logistics is complex and often involves multiple transportation modes and ca
Efficient, uninformative sampling of limb darkening coefficients for two-parameter laws
Kipping, David M
2013-01-01
Stellar limb darkening affects a wide range of astronomical measurements and is frequently modeled with a parametric model using polynomials in the cosine of the angle between the line of sight and the emergent intensity. Two-parameter laws are particularly popular for cases where one wishes to fit freely for the limb darkening coefficients (i.e. an uninformative prior) due to the compact prior volume and the fact more complex models rarely obtain unique solutions with present data. In such cases, we show that the two limb darkening coefficients are constrained by three physical boundary conditions, describing a triangular region in the two-dimensional parameter space. We show that uniformly distributed samples may be drawn from this region with optimal efficiency by a technique developed by computer graphical programming: triangular sampling. Alternatively, one can use make draws using a uniform, bivariate Dirichlet distribution. We provide simple expressions for these parametrizations for both techniques ap...
A Cost Model of Item Migration in the Air Force Logistics Command Consumable Item Inventory
1986-12-01
Long Supply . . . 65 XT. Reduced Model ANOVA Table for Long Supply . , 66 XII . Mean Responses for Long Supply . . . . . . 68 vii This i•wt nvestigates...Reduced Model ANOUA Tabla for Backarders Cl5:439) DEPENDENT VARIABLE: AVERAGE DOLLAR-WEIGHTED BACKORDERS SOURCE DF SUM OF SQUARES MEAN SQUARE MODEL 5...supply for constant and varying lead time is shown in Table XII . Both the mean difference and the 95 percent confidence interval show a considerable
Development of a program to fit data to a new logistic model for microbial growth.
Fujikawa, Hiroshi; Kano, Yoshihiro
2009-06-01
Recently we developed a mathematical model for microbial growth in food. The model successfully predicted microbial growth at various patterns of temperature. In this study, we developed a program to fit data to the model with a spread sheet program, Microsoft Excel. Users can instantly get curves fitted to the model by inputting growth data and choosing the slope portion of a curve. The program also could estimate growth parameters including the rate constant of growth and the lag period. This program would be a useful tool for analyzing growth data and further predicting microbial growth.
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You Zhu
2016-05-01
Full Text Available Based on logistic regression (LR and artificial neural network (ANN methods, we construct an LR model, an ANN model and three types of a two-stage hybrid model. The two-stage hybrid model is integrated by the LR and ANN approaches. We predict the credit risk of China’s small and medium-sized enterprises (SMEs for financial institutions (FIs in the supply chain financing (SCF by applying the above models. In the empirical analysis, the quarterly financial and non-financial data of 77 listed SMEs and 11 listed core enterprises (CEs in the period of 2012–2013 are chosen as the samples. The empirical results show that: (i the “negative signal” prediction accuracy ratio of the ANN model is better than that of LR model; (ii the two-stage hybrid model type I has a better performance of predicting “positive signals” than that of the ANN model; (iii the two-stage hybrid model type II has a stronger ability both in aspects of predicting “positive signals” and “negative signals” than that of the two-stage hybrid model type I; and (iv “negative signal” predictive power of the two-stage hybrid model type III is stronger than that of the two-stage hybrid model type II. In summary, the two-stage hybrid model III has the best classification capability to forecast SMEs credit risk in SCF, which can be a useful prediction tool for China’s FIs.
Pommier, S; Chenu, D; Quintard, M; Lefebvre, X
2007-06-15
This article deals with the impact of water content of solid waste on biogas production kinetics in landfills. This impact has been proved in the laboratory thanks to anaerobic biodegradation experiments on paper/cardboard waste samples. A strong dependence with the moisture level was observed for both kinetic rates and maximum methane production. In this article, a logistic model is proposed to simulate the biogas production rate. It is chosen as simple as possible in order to allow for a correct identification of the model parameters given the experimental data available. The moisture dependency is introduced through a linear weighing of the biomass specific growth rate and of the amount of accessible organic substrate. It is directly linked to physical properties of the waste: the holding capacity and the minimal moisture level allowing the presence of free water.
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L.A. Moncayo-Martínez
2014-06-01
Full Text Available The aim of this paper is to solve the problem of placing safety stock over a Logistic Network (LN that is represented by a Generic Bill of Materials (GBOM. Thus the LN encompasses supplying, assembling, and delivering stages. We describe, in detail, the recursive algorithm based on Dynamic Programming (DP to solve the placing safety stock problem under guaranteed-service time models. We also develop a java-based application (JbA that both models the LN and runs the recursive DP algorithm. We solved a real case of a company that manufactures fixed brake and clutch pedal modules of cars’ brake system. After running JbA, the levels of inventory decreased by zero in 55 out of 65 stages.
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Juniarti Juniarti
2013-01-01
Full Text Available The study aims to prove whether good corporate governance (GCG is able to predict the probability of companies experiencing financial difficulties. Financial ratios that traditionally used for predicting bankruptcy remains used in this study. Besides, this study also compares logit and probit regression models, which are widely used in research related accounting bankruptcy prediction. Both models will be compared to determine which model is more superior. The sample in this study is the infrastructure, transportation, utilities & trade, services and hotels companies experiencing financial distress in the period 2008-2011. The results show that GCG and other three variables control i.e DTA, CR and company category do not prove significantly to predict the probability of companies experiencing financial difficulties. NPM, the only variable that proved significantly distinguishing healthy firms and distress. In general, logit and probit models do not result in different conclusions. Both of the models confirm the goodness of fit of models and the results of hypothesis testing. In terms of classification accuracy, logit model proves more accurate predictions than the probit models.
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Daichi Narushima
2016-03-01
Full Text Available Background: Spontaneous Reporting Systems (SRSs are passive systems composed of reports of suspected Adverse Drug Events (ADEs, and are used for Pharmacovigilance (PhV, namely, drug safety surveillance. Exploration of analytical methodologies to enhance SRS-based discovery will contribute to more effective PhV. In this study, we proposed a statistical modeling approach for SRS data to address heterogeneity by a reporting time point. Furthermore, we applied this approach to analyze ADEs of incretin-based drugs such as DPP-4 inhibitors and GLP-1 receptor agonists, which are widely used to treat type 2 diabetes. Methods: SRS data were obtained from the Japanese Adverse Drug Event Report (JADER database. Reported adverse events were classified according to the MedDRA High Level Terms (HLTs. A mixed effects logistic regression model was used to analyze the occurrence of each HLT. The model treated DPP-4 inhibitors, GLP-1 receptor agonists, hypoglycemic drugs, concomitant suspected drugs, age, and sex as fixed effects, while the quarterly period of reporting was treated as a random effect. Before application of the model, Fisher’s exact tests were performed for all drug-HLT combinations. Mixed effects logistic regressions were performed for the HLTs that were found to be associated with incretin-based drugs. Statistical significance was determined by a two-sided p-value <0.01 or a 99% two-sided confidence interval. Finally, the models with and without the random effect were compared based on Akaike’s Information Criteria (AIC, in which a model with a smaller AIC was considered satisfactory. Results: The analysis included 187,181 cases reported from January 2010 to March 2015. It showed that 33 HLTs, including pancreatic, gastrointestinal, and cholecystic events, were significantly associated with DPP-4 inhibitors or GLP-1 receptor agonists. In the AIC comparison, half of the HLTs reported with incretin-based drugs favored the random effect
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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.
Institute of Scientific and Technical Information of China (English)
石丽忠; 陈金良
2014-01-01
Through grey estimation of the parameters of Logistic equation ,Logistic equation of grey forecasting model is established . The effective irrigation area of Liaoning Province is simulated by the model .The simulation results have good agreement with the a‐vailable data ,with a correlation of 0 .95 .The model predicts that the upper limit of the effective irrigation area is 1 ,587 ,700 hec‐tares ,and the effective irrigation area in 2018 will be 1583000 hectares ,which is very close to the upper limit .Thus ,there is little potential for the development of effective irrigation area ,and the structural adjustment of agricultural resources is very necessary .%应用灰色系统理论，对 Logistic 方程参数进行灰色估计，建立 Logistic 方程灰色预测模型，并对辽宁省有效灌溉面积进行了模拟和预测，模拟结果与原始资料吻合很好，相关性达到0．95。辽宁省有效灌溉面积预测模型显示：有效灌溉面积的上限是158．8万 hm2，2018年预测值为158．3万 hm2，已经非常接近界限值，有效灌溉面积的发展不大，进行农业资源的结构调整非常必要。
U.S. Geological Survey, Department of the Interior — This is a surface showing relative favorability for the presence of geothermal systems in the western United States. It is an average of 12 models that correlates...
Simulation Model of Logistic Support to Isolated Airspace Smveillance Radar Stations
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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.
2012-03-22
95% of the country with low reliability requirements ( Weibel and Hansman 2005). While the primary calculations of these models are in terms of...quantified. For example, the model for ground impact by Weibel and Hansman (2005) was used to calculate a necessary mean time between failures (MTBF) to...Success in Independent Trials." Statistica Sinica 3 (1993): 295-312. Weibel , Ronald, and John Hansman. Safety Considerations for Operation of Unmanned
Maslov, Lev A.; Chebotarev, Vladimir I.
2017-02-01
The generalized logistic equation is proposed to model kinetics and statistics of natural processes such as earthquakes, forest fires, floods, landslides, and many others. This equation has the form dN(A)/dA = s dot (1-N(A)) dot N(A)q dot A-α, q>0q>0 and A>0A>0 is the size of an element of a structure, and α≥0. The equation contains two exponents α and q taking into account two important properties of elements of a system: their fractal geometry, and their ability to interact either to enhance or to damp the process of aggregation. The function N(A)N(A) can be understood as an approximation to the number of elements the size of which is less than AA. The function dN(A)/dAdN(A)/dA where N(A)N(A) is the general solution of this equation for q=1 is a product of an increasing bounded function and power-law function with stretched exponential cut-off. The relation with Tsallis non-extensive statistics is demonstrated by solving the generalized logistic equation for q>0q>0. In the case 01q>1 it models sub-additive structures. The Gutenberg-Richter (G-R) formula results from interpretation of empirical data as a straight line in the area of stretched exponent with small α. The solution is applied for modeling distribution of foreshocks and aftershocks in the regions of Napa Valley 2014, and Sumatra 2004 earthquakes fitting the observed data well, both qualitatively and quantitatively.
Espino, Natalia V.
Foreign Object Debris/Damage (FOD) is a costly and high-risk problem that aeronautics industries such as Boeing, Lockheed Martin, among others are facing at their production lines every day. They spend an average of $350 thousand dollars per year fixing FOD problems. FOD can put pilots, passengers and other crews' lives into high-risk. FOD refers to any type of foreign object, particle, debris or agent in the manufacturing environment, which could contaminate/damage the product or otherwise undermine quality control standards. FOD can be in the form of any of the following categories: panstock, manufacturing debris, tools/shop aids, consumables and trash. Although aeronautics industries have put many prevention plans in place such as housekeeping and "clean as you go" philosophies, trainings, use of RFID for tooling control, etc. none of them has been able to completely eradicate the problem. This research presents a logistic regression statistical model approach to predict probability of FOD type under given specific circumstances such as workstation, month and aircraft/jet being built. FOD Quality Assurance Reports of the last three years were provided by an aeronautical industry for this study. By predicting type of FOD, custom reduction/elimination plans can be put in place and by such means being able to diminish the problem. Different aircrafts were analyzed and so different models developed through same methodology. Results of the study presented are predictions of FOD type for each aircraft and workstation throughout the year, which were obtained by applying proposed logistic regression models. This research would help aeronautic industries to address the FOD problem correctly, to be able to identify root causes and establish actual reduction/elimination plans.
Sufficient Sample Size and Power in Multilevel Ordinal Logistic Regression Models
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Sabz Ali
2016-01-01
Full Text Available For most of the time, biomedical researchers have been dealing with ordinal outcome variable in multilevel models where patients are nested in doctors. We can justifiably apply multilevel cumulative logit model, where the outcome variable represents the mild, severe, and extremely severe intensity of diseases like malaria and typhoid in the form of ordered categories. Based on our simulation conditions, Maximum Likelihood (ML method is better than Penalized Quasilikelihood (PQL method in three-category ordinal outcome variable. PQL method, however, performs equally well as ML method where five-category ordinal outcome variable is used. Further, to achieve power more than 0.80, at least 50 groups are required for both ML and PQL methods of estimation. It may be pointed out that, for five-category ordinal response variable model, the power of PQL method is slightly higher than the power of ML method.
Sufficient Sample Size and Power in Multilevel Ordinal Logistic Regression Models
Ali, Amjad; Khan, Sajjad Ahmad; Hussain, Sundas
2016-01-01
For most of the time, biomedical researchers have been dealing with ordinal outcome variable in multilevel models where patients are nested in doctors. We can justifiably apply multilevel cumulative logit model, where the outcome variable represents the mild, severe, and extremely severe intensity of diseases like malaria and typhoid in the form of ordered categories. Based on our simulation conditions, Maximum Likelihood (ML) method is better than Penalized Quasilikelihood (PQL) method in three-category ordinal outcome variable. PQL method, however, performs equally well as ML method where five-category ordinal outcome variable is used. Further, to achieve power more than 0.80, at least 50 groups are required for both ML and PQL methods of estimation. It may be pointed out that, for five-category ordinal response variable model, the power of PQL method is slightly higher than the power of ML method.
Comparing Three Estimation Methods for the Three-Parameter Logistic IRT Model
Lamsal, Sunil
2015-01-01
Different estimation procedures have been developed for the unidimensional three-parameter item response theory (IRT) model. These techniques include the marginal maximum likelihood estimation, the fully Bayesian estimation using Markov chain Monte Carlo simulation techniques, and the Metropolis-Hastings Robbin-Monro estimation. With each…
Information exchange in global logistics chains : an application for model-based auditing,
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 mo
An application of the logistic density on a stochastic continuous review stock control model
Beek, van P.
1978-01-01
We consider a so-called (R, Q) stock control system with stochastic lead time in which a quantity Q is ordered as soon as stock on hand plus on order is lower than a fixed reorder point R. In literature an abundance of models is encountered in which the parameters R and Q are optimized
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Farnaz Barzinpour
2014-01-01
Full Text Available Thousands of victims and millions of affected people are hurt by natural disasters every year. Therefore, it is essential to prepare proper response programs that consider early activities of disaster management. In this paper, a multiobjective model for distribution centers which are located and allocated periodically to the damaged areas in order to distribute relief commodities is offered. The main objectives of this model are minimizing the total costs and maximizing the least rate of the satisfaction in the sense of being fair while distributing the items. The model simultaneously determines the location of relief distribution centers and the allocation of affected areas to relief distribution centers. Furthermore, an efficient solution approach based on genetic algorithm has been developed in order to solve the proposed mathematical model. The results of genetic algorithm are compared with the results provided by simulated annealing algorithm and LINGO software. The computational results show that the proposed genetic algorithm provides relatively good solutions in a reasonable time.
Institute of Scientific and Technical Information of China (English)
过晓芳; 王宇平
2012-01-01
To improve the customer satisfaction on the service of logistics distribution, a multi-objective optimization model for logistics distribution programming under the three-level supply chain was developed. In this model, minimization of total expenses and maximization of logistics service level were optimization objectives, and the influence of both the commodity processing ability and distribution time on the logistics service level was taken into account. Given that there is no single optimal solution for multi-objective optimization problems, a preference-based multi-objective evolutionary algorithm for solving the model was proposed with a pre-defined preference area and randomly generated weight vector used to establish the fitness function. The results show that by solving the model, ten non-inferior solutions are obtained, each of which represents a distribution program. The ten solutions without exception lie in the subjective preference area of the decision maker and reflect the conflict relationship between total expenses and logistics service level.%为了提高顾客对物流服务的满意度,以最小化物流系统总费用和最大化物流服务水平为优化目标,考虑配送中心现有货物周转能力和产品配送时间对物流服务水平的影响,构建了三级供应链模式下物流配送规划的多目标优化模型.针对多目标优化问题不存在单一最优解的特点,利用预先设定的偏好区域和随机生成的权向量构造了适应度函数,提出了基于偏好的多目标进化算法求解模型.算例结果表明:通过求解多目标优化模型,得到10组非劣解,即10种物流配送方案均处于决策者的主观偏好范围内;各方案的物流系统总费用与服务水平成反比关系.
Research on Development Model of Fourth Party Logistics%我国第四方物流的发展模式研究
Institute of Scientific and Technical Information of China (English)
李健
2011-01-01
第四方物流是国际先进物流发展理念,它集成物流需求企业、第三方物流供应商、信息技术提供商以及管理咨询公司的能力,站在供应链的高度集成各方资源,使物流运作效率达到最优.发达国家已经率先实践了几种模式来发展第四方物流,面对还未成熟的物流市场,我国可以利用政府高度统筹的优势,走出自己的第四方物流发展模式.%The Fourth Party Logistics is advanced logistics concepts in the world, and it integrates the ability of logistics demand enterprise, Third Party Logistics providers, information technology providers and management consulting firm, stands at a high degree of supply chain to integrate all resources, to make the efficiency of logistics operations optimal. The developed countries have practiced several models to develop Fourth Party Logistics firstly. In the face of the not mature logistics market, we can take the goxernment's advantage of our high degree of co-ordinating to find out the development mode of Fourth Party Logisties.
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
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.
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Branimir Milosavljević
2015-01-01
Full Text Available This paper determines, by experiments, the CO emissions at idle running with 1,785 vehicles powered by spark ignition engine, in order to verify the correctness of emissions values with a representative sample of vehicles in Serbia. The permissible emissions limits were considered for three (3 fitted binary logistic regression (BLR models, and the key reason for such analysis is finding the predictors that can have a crucial influence on the accuracy of the estimation whether such vehicles have correct emissions or not. Having summarized the research results, we found out that vehicles produced in Serbia (hereinafter referred to as “domestic vehicles” cause more pollution than imported cars (hereinafter referred to as “foreign vehicles”, although domestic vehicles are of lower average age and mileage. Another trend was observed: low-power vehicles and vehicles produced before 1992 are potentially more serious polluters.
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 flavors (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
Liu, Hongjie; Li, Tianhao; Chen, Lingxiu; Zhan, Sha; Pan, Meilan; Ma, Zhiguo; Li, Chenghua; Zhang, Zhe
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.
Lin, Q.; Wang, Y.; Song, C.
2016-12-01
The Newmark displacement model has been used to predict earthquake-triggered landslides. Logistic regression (LR) is also a common landslide hazard assessment method. We combined the Newmark displacement model and LR and applied them to Wenchuan County and Beichuan County in China, which were affected by the Ms.8.0 Wenchuan earthquake on May 12th, 2008, to develop a mechanism-based landslide occurrence probability model and improve the predictive accuracy. A total of 1904 landslide sites in Wenchuan County and 3800 random non-landslide sites were selected as the training dataset. We applied the Newmark model and obtained the distribution of permanent displacement (Dn) for a 30 × 30 m grid. Four factors (Dn, topographic relief, and distances to drainages and roads) were used as independent variables for LR. Then, a combined model was obtained, with an AUC (area under the curve) value of 0.797 for Wenchuan County. A total of 617 landslide sites and non-landslide sites in Beichuan County were used as a validation dataset with AUC = 0.753. The proposed method may also be applied to earthquake-induced landslides in other regions.
Use of Robust z in Detecting Unstable Items in Item Response Theory Models
Huynh, Huynh; Meyer, Patrick
2010-01-01
The first part of this paper describes the use of the robust z[subscript R] statistic to link test forms using the Rasch (or one-parameter logistic) model. The procedure is then extended to the two-parameter and three-parameter logistic and two-parameter partial credit (2PPC) models. A real set of data was used to illustrate the extension. The…
Röthig, Andreas; Chiarella, Carl
2006-01-01
This article explores nonlinearities in the response of speculators' trading activity to price changes in live cattle, corn, and lean hog futures markets. Analyzing weekly data from March 4, 1997 to December 27, 2005, we reject linearity in all of these markets. Using smooth transition regression models, we find a similar structure of nonlinearities with regard to the number of different regimes, the choice of the transition variable, and the value at which the transition occurs.
Positive Almost Periodic Solution on a Nonlinear Logistic Biological Model with Grazing Rates
Institute of Scientific and Technical Information of China (English)
NI Hua; TIAN Li-xin
2013-01-01
In this paper,we study the following nonlinear biological model dx(t)/dt =x(t)[a(t)-b(t)xα(t)] + f(t,xt),by using fixed pointed theorem,the sufficient conditions of the existence of unique positive almost periodic solution for the above system are obtained,by using the theories of stability,the sufficient conditions which guarantee the stability of the positive almost periodic solution are derived.
Multi-objective reverse logistics model for integrated computer waste management.
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.
Wang, M; Sun, X Z; Tang, S X; Tan, Z L; Pacheco, D
2013-06-01
Water-soluble components of feedstuffs are mainly utilized during the early phase of microbial fermentation, which could be deemed an important determinant of gas production behavior in vitro. Many studies proposed that the fractional rate of degradation (FRD) estimated by fitting gas production curves to mathematical models might be used to characterize the early incubation for in vitro systems. In this study, the mathematical concept of FRD was developed on the basis of the Logistic-Exponential (LE) model, with initial gas volume being zero (LE0). The FRD of the LE0 model exhibits a continuous increase from initial (FRD 0) toward final asymptotic value (FRD F) with longer incubation time. The relationships between the FRD and gas production at incubation times 2, 4, 6, 8, 12 and 24 h were compared for four models, in addition to LE0, Generalization of the Mitscherlich (GM), c th order Michaelis-Menten (MM) and Exponential with a discrete LAG (EXPLAG). A total of 94 in vitro gas curves from four subsets with a wide range of feedstuffs from different laboratories and incubation periods were used for model testing. Results indicated that compared with the GM, MM and EXPLAG models, the FRD of LE0 model consistently had stronger correlations with gas production across the four subsets, especially at incubation times 2, 4, 6, 8 and 12 h. Thus, the LE0 model was deemed to provide a better representation of the early fermentation rates. Furthermore, the FRD 0 also exhibited strong correlations (P < 0.05) with gas production at early incubation times 2, 4, 6 and 8 h across all four subsets. In summary, the FRD of LE0 model provides an alternative to quantify the rate of early stage incubation, and its initial value could be an important starting parameter of rate.
Son, Dae-Soon; Lee, DongHyuk; Lee, Kyusang; Jung, Sin-Ho; Ahn, Taejin; Lee, Eunjin; Sohn, Insuk; Chung, Jongsuk; Park, Woongyang; Huh, Nam; Lee, Jae Won
2015-02-01
An empirical method of sample size determination for building prediction models was proposed recently. Permutation method which is used in this procedure is a commonly used method to address the problem of overfitting during cross-validation while evaluating the performance of prediction models constructed from microarray data. But major drawback of such methods which include bootstrapping and full permutations is prohibitively high cost of computation required for calculating the sample size. In this paper, we propose that a single representative null distribution can be used instead of a full permutation by using both simulated and real data sets. During simulation, we have used a dataset with zero effect size and confirmed that the empirical type I error approaches to 0.05. Hence this method can be confidently applied to reduce overfitting problem during cross-validation. We have observed that pilot data set generated by random sampling from real data could be successfully used for sample size determination. We present our results using an experiment that was repeated for 300 times while producing results comparable to that of full permutation method. Since we eliminate full permutation, sample size estimation time is not a function of pilot data size. In our experiment we have observed that this process takes around 30min. With the increasing number of clinical studies, developing efficient sample size determination methods for building prediction models is critical. But empirical methods using bootstrap and permutation usually involve high computing costs. In this study, we propose a method that can reduce required computing time drastically by using representative null distribution of permutations. We use data from pilot experiments to apply this method for designing clinical studies efficiently for high throughput data.
A Multi-industry Default Prediction Model using Logistic Regression and Decision Tree
Directory of Open Access Journals (Sweden)
Suresh Ramakrishnan
2015-04-01
Full Text Available The accurate prediction of corporate bankruptcy for the firms in different industries is of a great concern to investors and creditors, as the reduction of creditors’ risk and a considerable amount of saving for an industry economy can be possible. Financial statements vary between industries. Therefore, economic intuition suggests that industry effects should be an important component in bankruptcy prediction. This study attempts to detail the characteristics of each industry using sector indicators. The results show significant relationship between probability of default and sector indicators. The results of this study may improve the default prediction models performance and reduce the costs of risk management.
Asymptotic Results for the Two-parameter Poisson-Dirichlet Distribution
Feng, Shui
2009-01-01
The two-parameter Poisson-Dirichlet distribution is the law of a sequence of decreasing nonnegative random variables with total sum one. It can be constructed from stable and Gamma subordinators with the two-parameters, $\\alpha$ and $\\theta$, corresponding to the stable component and Gamma component respectively. The moderate deviation principles are established for the two-parameter Poisson-Dirichlet distribution and the corresponding homozygosity when $\\theta$ approaches infinity, and the large deviation principle is established for the two-parameter Poisson-Dirichlet distribution when both $\\alpha$ and $\\theta$ approach zero.
Model for determining logistic distribution center: case study of Mount Merapi eruption disaster
Ai, T. J.; Wigati, S. S.
2017-01-01
As one of the most active volcano in the earth, Mount Merapi is periodically erupted and it is considered as a natural disaster for the surrounding area. Kabupaten Sleman as one of the nearest location to this mount has to be always prepared to this disaster. The local government already set three different groups of region, in which potentially affected by Mount Merapi eruption, called KRB I, KRB II, and KRB III. Region KRB III is the closest area to the mount crater and most often affected by the eruption disaster. Whenever KRB III is affected, people live in that area usually being transfer to the next region set that is KRB II. The case presented in this paper is located at the KRB II region, which is the second closest region to the mount crater. A humanitarian distribution system has to be set in this region, since usually this region is became the location of shelters for KRB III population whenever a ‘big’ eruption is happened. A mathematical model is proposed in this paper, for determining the location of distribution center, vehicle route, and the amount of goods delivered to each customer. Some numerical illustration are presented in order to know the behavior of the proposed model.
Directory of Open Access Journals (Sweden)
Jennifer Somali Angeyo
2014-09-01
Full Text Available Applicability of artificial intelligence techniques, in evaluating the influence of the environmental factors in legislative data was found amenable in an earlier study - SVM performed to satisfying results with a 21.5 percent error rate for passage of legislation as compared to the performance of ANN at 28 percent error rate and K-NN at 29 percent error rate. These techniques reported both collective influence (ANN, K-NN and SVM and respective influence (SVM one-against-all classifier. Determining the environmental influences - individually or in combination with other factors, could only be measurably achieved using other modeling techniques, despite SVM with probabilistic output of 76 percent outperforming PNN with 71 percent out. A triangulation of both statistical and artificial intelligence modeling techniques in classification is thus proposed for decision making support in legislative drafting, given that computations involving statistical approach correctly predicted up to 98.20 percent and placed economic considerations as the most important factor for the passing of a bill with economic connotations. Other predictions involving political, social, cultural factors did not however, perform as well as the PNN and SVM with probabilistic output.
Energy Technology Data Exchange (ETDEWEB)
Narumalani, S. [Nebraska Univ., Lincoln, NE (United States). Dept. of Geography; Jensen, J.R.; Althausen, J.D.; Burkhalter, S. [South Carolina Univ., Columbia, SC (United States). Dept. of Geography; Mackey, H.E. Jr. [Westinghouse Savannah River Co., Aiken, SC (United States)
1994-06-01
Since aquatic macrophytes have an important influence on the physical and chemical processes of an ecosystem while simultaneously affecting human activity, it is imperative that they be inventoried and managed wisely. However, mapping wetlands can be a major challenge because they are found in diverse geographic areas ranging from small tributary streams, to shrub or scrub and marsh communities, to open water lacustrian environments. In addition, the type and spatial distribution of wetlands can change dramatically from season to season, especially when nonpersistent species are present. This research, focuses on developing a model for predicting the future growth and distribution of aquatic macrophytes. This model will use a geographic information system (GIS) to analyze some of the biophysical variables that affect aquatic macrophyte growth and distribution. The data will provide scientists information on the future spatial growth and distribution of aquatic macrophytes. This study focuses on the Savannah River Site Par Pond (1,000 ha) and L Lake (400 ha) these are two cooling ponds that have received thermal effluent from nuclear reactor operations. Par Pond was constructed in 1958, and natural invasion of wetland has occurred over its 35-year history, with much of the shoreline having developed extensive beds of persistent and non-persistent aquatic macrophytes.
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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.
物流园区配送模式选择研究%A Research on the Selection of Logistics Park Distribution Model
Institute of Scientific and Technical Information of China (English)
何金海
2014-01-01
基于物流园区基本的物流配送模式，构建了企业物流配送成本模型，并利用量本利分析方法给出了物流园区物流配送模式的选择模型，为物流园区规划建设及企业选择配送模式提供理论指导和建议。%The author of this article discusses the current logistics park distribution,finds out the existing problems and provides some theoretical guidance and suggestions for the design and con-struction of logistics park distribution modes,such as constructing a logistics park distribution cost model,and selecting the logistics park distribution mode based on Break-even analysis.
Study on Logistics Cost Control Model Based on ERP Logic%基于ERP逻辑的物流成本控制模型研究
Institute of Scientific and Technical Information of China (English)
郝雅静; 郑燕
2013-01-01
首先对企业物流成本的相关研究进行了文献综述,接着重点探讨了传统物流成本管理的缺陷,研究了物流成本控制逻辑,创新性地提出了采用EVA管理模型进行物流成本的控制,构建了基于ERP逻辑的物流成本控制模型.将ERP现代管理理念和物流EVA业绩评价模型融入到物流成本核算领域中,利用ERP逻辑思想探讨二者结合的可行性,以此为物流成本的现代化管理提供借鉴.%In this paper,we first reviewed literatures on enterprise logistics cost,then in view of the inadequacy of the traditional logistics cost management practice,studied the logic of logistics cost control and proposed innovatively to use the EVA management model for the purpose,thus establishing the logistics cost control mdoel based on ERP logic.By incorporating the ideology of ERP and the logistics EVA performance evaluation model into logistics cost accounting,we used the ERP logic to discuss the possibility of combining the two.
Trans-theta logistics: a new family of population growth sigmoid functions.
Kozusko, F; Bourdeau, M
2011-12-01
Sigmoid functions have been applied in many areas to model self limited population growth. The most popular functions; General Logistic (GL), General von Bertalanffy (GV), and Gompertz (G), comprise a family of functions called Theta Logistic ([Formula: see text] L). Previously, we introduced a simple model of tumor cell population dynamics which provided a unifying foundation for these functions. In the model the total population (N) is divided into reproducing (P) and non-reproducing/quiescent (Q) sub-populations. The modes of the rate of change of ratio P/N was shown to produce GL, GV or G growth. We now generalize the population dynamics model and extend the possible modes of the P/N rate of change. We produce a new family of sigmoid growth functions, Trans-General Logistic (TGL), Trans-General von Bertalanffy (TGV) and Trans-Gompertz (TG)), which as a group we have named Trans-Theta Logistic (T [Formula: see text] L) since they exist when the [Formula: see text] L are translated from a two parameter into a three parameter phase space. Additionally, the model produces a new trigonometric based sigmoid (TS). The [Formula: see text] L sigmoids have an inflection point size fixed by a single parameter and an inflection age fixed by both of the defining parameters. T [Formula: see text] L and TS sigmoids have an inflection point size defined by two parameters in bounding relationships and inflection point age defined by three parameters (two bounded). While the Theta Logistic sigmoids provided flexibility in defining the inflection point size, the Trans-Theta Logistic sigmoids provide flexibility in defining the inflection point size and age. By matching the slopes at the inflection points we compare the range of values of inflection point age for T [Formula: see text] L versus [Formula: see text] L for model growth curves.
A modified Logistic model for forecasting petroleum consumption in China%采用改进Logistic模型预测中国石油消费量
Institute of Scientific and Technical Information of China (English)
纪利群
2011-01-01
Based on the Logistic model, a new modified Logistic model was developed by adding two curvature parameters. In general, the new model can't be analytically solved. It is difficult to estimate the model parameters by using some conventional optimization methods. Pattern search method, which is an advanced direct search method, was proposed to determine the parameter values of the new model. The Logistic model and its modification were applied to describe the evolution of petroleum consumption in China. The results show that the new modified Logistic model has performed better than the Logistic model. Based on the fitted modified Logistic model, the forecasted future values of petroleum consumption in China were obtained , which are very important for the future petroleum plan in China.%在原有Logistic模型的基础上,增加两个影响模型曲线曲率的参数,得到新的改进Logistic模型.为克服采用常规的优化方法求解模型参数难的问题,采用先进的直接搜索算法——模式搜索法进行模型参数的优化求解,并用Logistic模型和改进的Logistic模型描述中国历年石油消费量数据.结果表明:与原有的Logistic模型相比,改进的Logistic模型描述精度要高得多；基于拟合后改进的Logistic模型预测的中国未来石油消费量可为中国未来石油规划提供可靠的基础数据支持.
Modeling and Optimization of Woody Biomass Harvest and Logistics in the Northeastern 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
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Jihong Chen
2016-01-01
Full Text Available Operational efficiency is significant for the comprehensive competitiveness of a port. In this study, we use a principal component analysis-data envelopment analysis (PCA-DEA integrated model to evaluate the operational efficiency of iron ore logistics at the ports of Bohai Bay, China. The key indicators and systematic framework are established for logistics efficiency research. We consider the PCA-DEA integrated model as a practical tool for evaluating and analyzing the relative efficiency of the iron ore logistics of each port in that area. The proposed method consists of a two-stage research and analysis that begins with PCA. In the first stage, we use PCA to obtain 6 synthetic indicators, including 4 input indicators and 2 output indicators, from 15 original indicators. In the second stage, the standard DEA approach is used with the specific synthetic indicators. The evaluation results of the selected ports from the integrated PCA-DEA model are compared and discussed. The comparison of the evaluation results indicates that the PCA-DEA model provides a practical and powerful tool for the investigation of the port logistics problem. With this integrated model, a comparison analysis and further research into the iron ore logistics efficiency of different ports in the area are presented. Finally, discussions and suggestions are provided.