Multibody dynamics of aircraft occupants seated behind interior walls

To improve aircraft crash safety, conditions critical to occupants survival during a crash must be known. In view of the importance of this problem, studies of post-crash dynamic behavior of victims are necessary in order to reduce severe injuries. In this study, crash dynamics program SOM-LA/TA, incorporating a dynamic model of the human body with a finite element model of the seat structure was used. Modifications were performed in the program for reconstruction of an occupant's head impact with the interior walls or bulkhead. A viscoelastic-type contact force model was used to represent the compliance characteristics of the bulkhead. Correlated studies of analytical simulations with impact sled test results were accomplished. A parametric study of the coefficients in the contact force model was then performed in order to obtain the correlations between the coefficients and the Head Injury Criteria. A measure of optimal values for the bulkhead compliance and displacement requirements was thus achieved in order to keep the possibility of a head injury as little as possible. This information could in turn be used in the selection of suitable materials for the bulkhead, instrument panel, or interior walls of an aircraft.     

M/G/1/N vacation model with varying E-limited service discipline

We define and analyze anM/G/1/N vacation model that uses a service discipline that we call theE-limited with limit variation discipline. According to this discipline, the server provides service until either the system is emptied (i.e. exhausted) or a randomly chosen limit ofl customers has been served. The server then goes on a vacation before returning to service the queue again. The queue length distribution and the Laplace-Stieltjes transforms of the waiting time, busy period and cycle time distributions are found. Further, an expression for the mean waiting time is developed. Several previously analyzed service disciplines, including Bernoulli scheduling, nonexhaustive service and limited service, are special cases of the general varying limit discipline that is analyzed in this paper.     

Improved customer choice predictions using ensemble methods

In this paper various ensemble learning methods from machine learning and statistics are considered and applied to the customer choice modeling problem. The application of ensemble learning usually improves the prediction quality of flexible models like decision trees and thus leads to improved predictions. We give experimental results for two real-life marketing datasets using decision trees, ensemble versions of decision trees and the logistic regression model, which is a standard approach for this problem. The ensemble models are found to improve upon individual decision trees and outperform logistic regression.     

Comparison of detection efficiencies of negatively charged gold-alkanethiolate-, gold-sulfur- and gold-clusters in ToF-SIMS

In order to improve quantification of high mass ions, the influence of cluster composition on detection efficiencies has been studied using a TOF-SIMS IV with the extended capability of postaccelerating ions up to 20 keV. In this experimental study, we focus on the comparison of detection efficiencies for three types of negatively charged secondary cluster ions: gold-alkanethiolate-clusters (Au_xM_y), gold-sulfur-clusters (Au_xS_y) and gold-clusters (Au_x). The clusters were sputtered from self-assembled monolayers of hexadecanethiols on gold substrates using 10 keV Ar⁺ primary ions. The detection efficiencies were derived on the basis of a function for the secondary electron yield and a fourth-order approximated Poisson probability distribution for electron propagation and amplification within the microchannel plate.In addition to the well-known dependence of detection efficiencies on ion mass and energy, which has already been studied for positively charged ions, we were able to show a similar behaviour for the investigated negatively charged secondary ions. We have observed major variations among the three types of clusters at similar mass and energy as predicted in a theoretical approach. The observed differences are due to the different composition of the investigated clusters which has a major influence on the kinetic ion induced electron emission within the microchannel plate. For the first time it was possible to experimentally verify these predictions for detection efficiencies.     

A Partial Differential Inequality in Geological Models

Sedimentation and erosion processes in sedimentary basins can be modeled by a parabolic equation with a limiter on the fluxes and a constraint on the time variation.This limiter happens to satisfy a stationary scalar hyperbolic inequality,within a constraint,for which the authors prove the existence and the uniqueness of the solution.Actually,this solution is shown to be the maximal element of a convenient convex set of functions.The existence proof is obtained thanks to the use of a numerical scheme.     

Practical aspects associated with location planning for maternal and perinatal assistance in Brazil

A study has been carried out aimed at reducing perinatal mortality in the municipality of Rio de Janeiro through a better distribution of health care facilities. The algorithmic aspects are detailed elsewhere and here the emphasis is on practical issues and difficulties encountered. A 3-level hierarchical model was developed. Both uncapacitated and capacitated versions are briefly described together with some results based on actual data. The project brought to light many contradictions between OR theory and practice in developing countries and, unfortunately, the models developed were not implemented by the municipality health authorities. Possible reasons for this outcome are analysed.     

Portfolio optimization in stochastic markets

We consider a multiperiod mean-variance model where the model parameters change according to a stochastic market. The mean vector and covariance matrix of the random returns of risky assets all depend on the state of the market during any period where the market process is assumed to follow a Markov chain. Dynamic programming is used to solve an auxiliary problem which, in turn, gives the efficient frontier of the mean-variance formulation. An explicit expression is obtained for the efficient frontier and an illustrative example is given to demonstrate the application of the procedure.     

An improved algorithm for computing topological entropy

A new algorithm is presented for computing the topological entropy of a unimodal map of the interval. The accuracy of the algorithm is discussed and some graphs of the topological entropy which are obtained using the algorithm are displayed.     

Dynamic Nonlinear Modelization of Operational Supply Chain Systems

Supply Chain Management (SCM) is an important activity in all producing facilities and in many organizations to enable vendors, manufacturers and suppliers to interact gainfully and plan optimally their flow of goods and services. To realize this, a dynamic modelling approach for characterizing supply chain activities is opportune, so as to plan efficiently the set of activities over a distributed network in a formal and scientific way. The dynamical system will result so complex that it is not generally possible to specify the functional forms and the parameters of interest, relating outputs to inputs, states and stochastic terms by experiential specification methods. Thus the algorithm that will presented is Data Driven, determining simultaneously the functional forms, the parameters and the optimal control policy from the data available for the supply chain. The aim of this paper is to present this methodology, by considering dynamical aspects of the system, the presence of nonlinear relationships and unbiased estimation procedures to quantify these relations, leading to a nonlinear and stochastic dynamical system representation of the SCM problem. Moreover, the convergence of the algorithm will be proved and the satisfaction of the required statistical conditions demonstrated. Thus SCM problems may be formulated as formal scientific procedures, with well defined algorithms and a precise calculation sequence to determine the best alternative to enact. A “Certainty equivalent principle” will be indicated to ensure that the effects of the inevitable uncertainties will not lead to indeterminate results, allowing the formulation of demonstrably asymptotically optimal management plans.