Dissipative contact force models

"Series: Solid mechanics and its applications, vol. 226"

Contact force models for multibody dynamics

"Series: Solid mechanics and its applications, vol. 226"

An evolutionary approach to the use of Petri net based models: from parallel controllers to HW/SW co-design

"A workshop within the 19th International Conference on Applications and Theory of Petri Nets - ICATPN’1998"

Employment, turnover and career progress

The severe economic downturn that followed the Global Financial Crisis of 2007 was accompanied by major fluctuations in the labour market. During the Great Recession the rate of job destruction was such that, by 2013, active population was at levels of 1999; employment levels were at an historical minimum; and the unemployment rate soared to 17,5%. This chapter inspects the dynamics behind the aggregate fl uctuations in the labour market and studies the determinants of mobility within (promotions) and between fi rms, and whether these have changed during crisis, using Portuguese (LEED) data. During crisis women became more likely to make between- rm moves with short gaps of unemployment and less likely to find a new job after a long gap or to make a job-to-non-employment transition. More educated workers are less likely to experience between fi rm job mobility, both before and during crisis, and became less likely to make job-to-non-employment transitions during crisis. Young workers are the group that most suffered from crisis: they became less likely to make job-to-job transitions and their hazard of experiencing a transition into unemployment shoot up.

Real-Time models to predict the use of vasopressors in monitored patients

The needs of reducing human error has been growing in every field of study, and medicine is one of those. Through the implementation of technologies is possible to help in the decision making process of clinics, therefore to reduce the difficulties that are typically faced. This study focuses on easing some of those difficulties by presenting real-time data mining models capable of predicting if a monitored patient, typically admitted in intensive care, will need to take vasopressors. Data Mining models were induced using clinical variables such as vital signs, laboratory analysis, among others. The best model presented a sensitivity of 94.94%. With this model it is possible reducing the misuse of vasopressors acting as prevention. At same time it is offered a better care to patients by anticipating their treatment with vasopressors.

Modelos Mixtos-Aditivos Generalizados para el Estudio de Fenómenos Biológicos y Sociales Descriptos por Datos Agregados y/o Longitudinales. Generalized Mixed Additive Models for the Study of Biological and Social Phenomenons from Longitudinal and/or Aggregated Data.

Este proyecto propone extender y generalizar los procesos de estimación e inferencia de modelos aditivos generalizados multivariados para variables aleatorias no gaussianas, que describen comportamientos de fenómenos biológicos y sociales y cuyas representaciones originan series longitudinales y datos agregados (clusters). Se genera teniendo como objeto para las aplicaciones inmediatas, el desarrollo de metodología de modelación para la comprensión de procesos biológicos, ambientales y sociales de las áreas de Salud y las Ciencias Sociales, la condicionan la presencia de fenómenos específicos, como el de las enfermedades.Es así que el plan que se propone intenta estrechar la relación entre la Matemática Aplicada, desde un enfoque bajo incertidumbre y las Ciencias Biológicas y Sociales, en general, generando nuevas herramientas para poder analizar y explicar muchos problemas sobre los cuales tienen cada vez mas información experimental y/o observacional.Se propone, en forma secuencial, comenzando por variables aleatorias discretas (Yi, con función de varianza menor que una potencia par del valor esperado E(Y)) generar una clase unificada de modelos aditivos (paramétricos y no paramétricos) generalizados, la cual contenga como casos particulares a los modelos lineales generalizados, no lineales generalizados, los aditivos generalizados, los de media marginales generalizados (enfoques GEE1 -Liang y Zeger, 1986- y GEE2 -Zhao y Prentice, 1990; Zeger y Qaqish, 1992; Yan y Fine, 2004), iniciando una conexión con los modelos lineales mixtos generalizados para variables latentes (GLLAMM, Skrondal y Rabe-Hesketh, 2004), partiendo de estructuras de datos correlacionados. Esto permitirá definir distribuciones condicionales de las respuestas, dadas las covariables y las variables latentes y estimar ecuaciones estructurales para las VL, incluyendo regresiones de VL sobre las covariables y regresiones de VL sobre otras VL y modelos específicos para considerar jerarquías de variación ya reconocidas. Cómo definir modelos que consideren estructuras espaciales o temporales, de manera tal que permitan la presencia de factores jerárquicos, fijos o aleatorios, medidos con error como es el caso de las situaciones que se presentan en las Ciencias Sociales y en Epidemiología, es un desafío a nivel estadístico. Se proyecta esa forma secuencial para la construcción de metodología tanto de estimación como de inferencia, comenzando con variables aleatorias Poisson y Bernoulli, incluyendo los existentes MLG, hasta los actuales modelos generalizados jerárquicos, conextando con los GLLAMM, partiendo de estructuras de datos correlacionados. Esta familia de modelos se generará para estructuras de variables/vectores, covariables y componentes aleatorios jerárquicos que describan fenómenos de las Ciencias Sociales y la Epidemiología.

Data mining with graphical models

Data Mining, Learning from data, graphical models, possibility theory

Data-driven system identification via evolutionary retrieval of Takagi-Sugeno fuzzy models

Systemidentification, evolutionary automatic, data-driven model, fuzzy Takagi-Sugeno grammar, genotype interpretability, toxicity-prediction

Models and methods for supporting lot sizing decisions in product recovery systems

Magdeburg, Univ., Fak. für Wirtschaftswiss., Diss., 2011

Approximations of the Fisher information for the construction of efficient experimental designs in nonlinear mixed effects models

Magdeburg, Univ., Fak. für Mathematik, Diss., 2012

Experimental design for mixed models with application to population pharmacokinetic studies

experimental design, mixed model, random coefficient regression model, population pharmacokinetics, approximate design

One-year Mortality after an Acute Coronary Event and its Clinical Predictors: The ERICO Study

Background:Information about post-acute coronary syndrome (ACS) survival have been mostly short-term findings or based on specialized, cardiology referral centers.Objectives:To describe one-year case-fatality rates in the Strategy of Registry of Acute Coronary Syndrome (ERICO) cohort, and to study baseline characteristics as predictors.Methods:We analyzed data from 964 ERICO participants enrolled from February 2009 to December 2012. We assessed vital status by telephone contact and official death certificate searches. The cause of death was determined according to the official death certificates. We used log-rank tests to compare the probabilities of survival across subgroups. We built crude and adjusted (for age, sex and ACS subtype) Cox regression models to study if the ACS subtype or baseline characteristics were independent predictors of all-cause or cardiovascular mortality.Results:We identified 110 deaths in the cohort (case-fatality rate, 12.0%). Age [Hazard ratio (HR) = 2.04 per 10 year increase; 95% confidence interval (95%CI) = 1.75–2.38], non-ST elevation myocardial infarction (HR = 3.82 ; 95%CI = 2.21–6.60) or ST elevation myocardial infarction (HR = 2.59; 95%CI = 1.38–4.89) diagnoses, and diabetes (HR = 1.78; 95%CI = 1.20‑2.63) were significant risk factors for all-cause mortality in the adjusted models. We found similar results for cardiovascular mortality. A previous coronary artery disease diagnosis was also an independent predictor of all-cause mortality (HR = 1.61; 95%CI = 1.04–2.50), but not for cardiovascular mortality.Conclusion:We found an overall one-year mortality rate of 12.0% in a sample of post-ACS patients in a community, non-specialized hospital in São Paulo, Brazil. Age, ACS subtype, and diabetes were independent predictors of poor one‑year survival for overall and cardiovascular-related causes.

Optimal designs for mixed effects poisson regression models

Magdeburg, Univ., Fak. für Mathematik, Diss., 2010

Simulation of interacting populations in inhomogeneous flows using reduced models

Magdeburg, Univ., Fak. für Verfahrens- und Systemtechnik, Diss., 2010

Conversive Hidden non-Markovian models

Magdeburg, Univ., Fak. für Informatik, Diss., 2012