Slope estimation in a parametric measurement error model: A simulation study

In regression analysis, covariate measurement error occurs in many applications. The error-prone covariates are often referred to as latent variables. In this proposed study, we extended the study of Chan et al. (2008) on recovering latent slope in a simple regression model to that in a multiple regression model. We presented an approach that applied the Monte Carlo method in the Bayesian framework to the parametric regression model with the measurement error in an explanatory variable. The proposed estimator applied the conditional expectation of latent slope given the observed outcome and surrogate variables in the multiple regression models. A simulation study was presented showing that the method produces estimator that is efficient in the multiple regression model, especially when the measurement error variance of surrogate variable is large.^

Mixture modeling for joint analysis of survival, discrete, and continuous data

Mixture modeling is commonly used to model categorical latent variables that represent subpopulations in which population membership is unknown but can be inferred from the data. In relatively recent years, the potential of finite mixture models has been applied in time-to-event data. However, the commonly used survival mixture model assumes that the effects of the covariates involved in failure times differ across latent classes, but the covariate distribution is homogeneous. The aim of this dissertation is to develop a method to examine time-to-event data in the presence of unobserved heterogeneity under a framework of mixture modeling. A joint model is developed to incorporate the latent survival trajectory along with the observed information for the joint analysis of a time-to-event variable, its discrete and continuous covariates, and a latent class variable. It is assumed that the effects of covariates on survival times and the distribution of covariates vary across different latent classes. The unobservable survival trajectories are identified through estimating the probability that a subject belongs to a particular class based on observed information. We applied this method to a Hodgkin lymphoma study with long-term follow-up and observed four distinct latent classes in terms of long-term survival and distributions of prognostic factors. Our results from simulation studies and from the Hodgkin lymphoma study demonstrated the superiority of our joint model compared with the conventional survival model. This flexible inference method provides more accurate estimation and accommodates unobservable heterogeneity among individuals while taking involved interactions between covariates into consideration.^

Age models and foraminifer isotopes of four ODP Leg 202 sites

We present benthic isotope stratigraphies for Sites 1236, 1237, 1239, and 1241 that span the late Miocene-Pliocene time interval from 6 to 2.4 Ma. Orbitally tuned timescales were generated for Sites 1237 and 1241 by correlating the high-frequency variations in gamma ray attenuation density, percent sand of the carbonate fraction, and benthic d13C to variations in Earth's orbital parameters. The astronomical timescales for Sites 1237 and 1241 are in agreement with the one from Atlantic Site 925/926 (Ocean Drilling Program Leg 154). The comparison of benthic d18O and d13C records from the east Pacific sites and Atlantic Site 925/926 revealed a surprising clarity of the "41-k.y. signal" in d13C records and a remarkably good correlation between their d13C records. This suggests that the late Miocene-Pliocene amplitudes of obliquity-related d13C cycles reflect a magnitude of global response often larger than that provided by obliquity-related d18O cycles. At Site 1237, the orbitally derived ages of Pliocene magnetic reversal boundaries between the base of Réunion and the top of Thvera confirm astronomical datings of the generally accepted ATNTS2004 timescale, except for the top of Kaena and the base of Sidufjall. Our astronomical age for the top of Kaena is about one obliquity cycle older. The base of Sidufjall appears to be about one precession cycle younger. The age models of Sites 1236 and 1239 were established by correlating their benthic d18O and d13C records directly to the orbitally tuned isotope record of Site 1241.

Geographical simulation analysis for logistics enhancement in Asia

This paper presents a simulation of the reduction of several components in trade cost for Asia and examines its impact on the economy. Our simulation model based on the new economic geography embraces seven sectors, including manufacturing and non-manufacturing sectors, and 1,715 regions in 18 countries/economies in Asia, in addition to the two economies of the US and the European Union. The geographical course of transactions among regions is modeled as determined based on firms’ modal choice. The model also includes estimates of some border cost measures such as tariff rates, non-tariff barriers, other border clearance costs, transshipment costs and so on. Our simulation analysis for Asia includes several scenarios involving the improvement/development of routes and the reduction of the above-mentioned border cost. We have shown that the contribution of physical and non-physical infrastructure improvements conducted together is larger than the sum of the contribution by each when conducted independently.

Simulation analysis of the EU ELV/RoHS directives based on an applied general equilibrium model with Melitz-type trade specification

This paper explores the potential usefulness of an AGE model with the Melitz-type trade specification to assess economic effects of technical regulations, taking the case of the EU ELV/RoHS directives as an example. Simulation experiments reveal that: (1) raising the fixed exporting cost to make sales in the EU market brings results that exports of the targeted commodities (motor vehicles and parts for ELV and electronic equipment for RoHS) to the EU from outside regions/countries expand while the domestic trade in the EU shrinks when the importer's preference for variety (PfV) is not strong; (2) if the PfV is not strong, policy changes that may bring reduction in the number of firms enable survived producers with high productivity to expand production to be large-scale mass producers fully enjoying the fruit of economies of scale; and (3) When the strength of the importer's PfV is changed from zero to unity, there is the value that totally changes simulation results and their interpretations.

Arquitectura cognitiva basada en el gradiente sensorial y su aplicación a la robótica móvil

El objetivo de esta tesis es el desarrollo de un sistema completo de navegación, aprendizaje y planificación para un robot móvil. Dentro de los innumerables problemas que este gran objetivo plantea, hemos dedicado especial atención al problema del conocimiento autónomo del mundo. Nuestra mayor preocupación ha sido la de establecer mecanismos que permitan, a partir de información sensorial cruda, el desarrollo incremental de un modelo topológico del entorno en el que se mueve el robot. Estos mecanismos se apoyan invariablemente en un nuevo concepto propuesto en esta tesis: el gradiente sensorial. El gradiente sensorial es un dispositivo matemático que funciona como un detector de sucesos interesantes para el sistema. Una vez detectado uno de estos sucesos, el robot puede identificar su situación en un mapa topológico y actuar en consecuencia. Hemos denominado a estas situaciones especiales lugares sensorialmente relevantes, ya que (a) captan la atención del sistema y (b) pueden ser identificadas utilizando la información sensorial. Para explotar convenientemente los modelos construidos, hemos desarrollado un algoritmo capaz de elaborar planes internalizados, estableciendo una red de sugerencias en los lugares sensorialmente relevantes, de modo que el robot encuentra en estos puntos una dirección recomendada de navegación. Finalmente, hemos implementado un sistema de navegación robusto con habilidades para interpretar y adecuar los planes internalizados a las circunstancias concretas del momento. Nuestro sistema de navegación está basado en la teoría de campos de potencial artificial, a la que hemos incorporado la posibilidad de añadir cargas ficticias como ayuda a la evitación de mínimos locales. Como aportación adicional de esta tesis al campo genérico de la ciencia cognitiva, todos estos elementos se integran en una arquitectura centrada en la memoria, lo que pretende resaltar la importancia de ésta en los procesos cognitivos de los seres vivos y aporta un giro conceptual al punto de vista tradicional, centrado en los procesos. The general objective of this thesis is the development of a global navigation system endowed with planning and learning features for a mobile robot. Within this general objective we have devoted a special effort to the autonomous learning problem. Our main concern has been to establish the necessary mechanisms for the incremental development of a topological model of the robot’s environment using the sensory information. These mechanisms are based on a new concept proposed in the thesis: the sensory gradient. The sensory gradient is a mathematical device which works like a detector of “interesting” environment’s events. Once a particular event has been detected the robot can identify its situation in the topological map and to react accordingly. We have called these special situations relevant sensory places because (a) they capture the system’s attention and (b) they can be identified using the sensory information. To conveniently exploit the built-in models we have developed an algorithm able to make internalized plans, establishing a suggestion network in the sensory relevant places in such way that the robot can find at those places a recommended navigation direction. It has been also developed a robust navigation system able to navigate by means of interpreting and adapting the internalized plans to the concrete circumstances at each instant, i.e. a reactive navigation system. This reactive system is based on the artificial potential field approach with the additional feature introduced in the thesis of what we call fictitious charges as an aid to avoid local minima. As a general contribution of the thesis to the cognitive science field all the above described elements are integrated in a memory-based architecture, emphasizing the important role played by the memory in the cognitive processes of living beings and giving a conceptual turn in the usual process-based approach.

MRI and Bidimensional relaxometry sequences for macro and microstructure assessment in food models.

Physico-chemical and organoleptic characteristics of food depend largely on the microscopic level distribution of gases and water, and connectivity and mobility through the pores. Microstructural characterization of food can be accomplished by Magnetic Resonance Imaging (MRI) and Nuclear Magnetic Spectroscopy (NMR) combined with the application of methods of dissemination and multidimensional relaxometry. In this work, funded by the EC Project InsideFood, several artificial food models, based on foams and gels were studied using MRI and 2D relaxometry. Two different kinds of foams were used: a sugarless and a sugar foam. Then, a half of a syringe was filled with the sugarless foam and the other half with the sugar foam. Then, MRI and NMR experiments were performed and the sample evolution was observed along 3 days in order to quantify macrostructural changes through proton density images and microstructural ones using T1T2 maps, using an inversion CPMG sequence. On the proton density images it may be seen that after 16 hours it was possible to differentiate the macrostructural changes, as the apparition of free water due to a syneresis phenomenon. On the interface it can be seen a brighter area after 16 hours, due to the occurrence of free water. Moreover, thanks to the bidimensional relaxometry (T1-T2) it was possible to differentiate among microscopic changes. Differences between the pores size can be observed as well as the microstructure evolution after 30.5 hours, as a consequence differences are shown on free water redistribution through larger pores and capillarity phenomena between both foams.

A simplified model for evaluation of fatigue damage in frames

Many studies have been developed to analyze the structural seismic behavior through the damage index concept. The evaluation of this index has been employed to quantify the safety of new and existing structures and, also, to establish a framework for seismic retrofitting decision making of structures. Most proposed models are based in a posterthquake evaluation in such a way they uncouple the structural response from the damage evaluation. In this paper, a generalization of the model by Flórez-López (1995) is proposed. The formulation employs irreversible thermodynamics and internal state variable theory applied to the study of beams and frames and it allows and explicit coupling between the degradation and the structural mechanical behavior. A damage index es defined in order to model elastoplasticity coupled with damage and fatigue damage.

Evaluation and improvement of empirical models of global solar irradiation: Case study northern Spain

This paper presents a new methodology to build parametric models to estimate global solar irradiation adjusted to specific on-site characteristics based on the evaluation of variable im- portance. Thus, those variables higly correlated to solar irradiation on a site are implemented in the model and therefore, different models might be proposed under different climates. This methodology is applied in a study case in La Rioja region (northern Spain). A new model is proposed and evaluated on stability and accuracy against a review of twenty-two already exist- ing parametric models based on temperatures and rainfall in seventeen meteorological stations in La Rioja. The methodology of model evaluation is based on bootstrapping, which leads to achieve a high level of confidence in model calibration and validation from short time series (in this case five years, from 2007 to 2011). The model proposed improves the estimates of the other twenty-two models with average mean absolute error (MAE) of 2.195 MJ/m2 day and average confidence interval width (95% C.I., n=100) of 0.261 MJ/m2 day. 41.65% of the daily residuals in the case of SIAR and 20.12% in that of SOS Rioja fall within the uncertainty tolerance of the pyranometers of the two networks (10% and 5%, respectively). Relative differences between measured and estimated irradiation on an annual cumulative basis are below 4.82%. Thus, the proposed model might be useful to estimate annual sums of global solar irradiation, reaching insignificant differences between measurements from pyranometers.

Evaluation, energy optimization, and spectrum analysis of an artificial noise technique to improve CWSN security

This paper presents the security evaluation, energy consumption optimization, and spectrum scarcity analysis of artificial noise techniques to increase physical-layer security in Cognitive Wireless Sensor Networks (CWSNs). These techniques introduce noise into the spectrum in order to hide real information. Nevertheless, they directly affect two important parameters in Cognitive Wireless Sensor Networks (CWSNs), energy consumption and spectrum utilization. Both are affected because the number of packets transmitted by the network and the active period of the nodes increase. Security evaluation demonstrates that these techniques are effective against eavesdropper attacks, but also optimization allows for the implementation of these approaches in low-resource networks such as Cognitive Wireless Sensor Networks. In this work, the scenario is formally modeled and the optimization according to the simulation results and the impact analysis over the frequency spectrum are presented.

Auto-Emergencia de Comunicación Sintáctica en Entornos Estáticos y Dinámicos para Grupos de Robots mediante Evolución Gramatical y Aprendizaje por Refuerzo

La idea de dotar a un grupo de robots o agentes artificiales de un lenguaje ha sido objeto de intenso estudio en las ultimas décadas. Como no podía ser de otra forma los primeros intentos se enfocaron hacia el estudio de la emergencia de vocabularios compartidos convencionalmente por el grupo de robots. Las ventajas que puede ofrecer un léxico común son evidentes, como también lo es que un lenguaje con una estructura más compleja, en la que se pudieran combinar palabras, sería todavía más beneficioso. Surgen así algunas propuestas enfocadas hacia la emergencia de un lenguaje consensuado que muestre una estructura sintáctica similar al lenguaje humano, entre las que se encuentra este trabajo. Tomar el lenguaje humano como modelo supone adoptar algunas de las hipótesis y teorías que disciplinas como la filosofía, la psicología o la lingüística entre otras se han encargado de proponer. Según estas aproximaciones teóricas el lenguaje presenta una doble dimension formal y funcional. En base a su dimensión formal parece claro que el lenguaje sigue unas reglas, por lo que el uso de una gramática se ha considerado esencial para su representación, pero también porque las gramáticas son un dispositivo muy sencillo y potente que permite generar fácilmente estructuras simbólicas. En cuanto a la dimension funcional se ha tenido en cuenta la teoría quizá más influyente de los últimos tiempos, que no es otra que la Teoría de los Actos del Habla. Esta teoría se basa en la idea de Wittgenstein por la que el significado reside en el uso del lenguaje, hasta el punto de que éste se entiende como una manera de actuar y de comportarse, en definitiva como una forma de vida. Teniendo presentes estas premisas en esta tesis se pretende experimentar con modelos computacionales que permitan a un grupo de robots alcanzar un lenguaje común de manera autónoma, simplemente mediante interacciones individuales entre los robots, en forma de juegos de lenguaje. Para ello se proponen tres modelos distintos de lenguaje: • Un modelo basado en gramáticas probabilísticas y aprendizaje por refuerzo en el que las interacciones y el uso del lenguaje son claves para su emergencia y que emplea una gramática generativa estática y diseñada de antemano. Este modelo se aplica a dos grupos distintos: uno formado exclusivamente por robots y otro que combina robots y un humano, de manera que en este segundo caso se plantea un aprendizaje supervisado por humanos. • Un modelo basado en evolución gramatical que permite estudiar no solo el consenso sintáctico, sino también cuestiones relativas a la génesis del lenguaje y que emplea una gramática universal a partir de la cual los robots pueden evolucionar por sí mismos la gramática más apropiada según la situación lingüística que traten en cada momento. • Un modelo basado en evolución gramatical y aprendizaje por refuerzo que toma aspectos de los anteriores y amplia las posibilidades de los robots al permitir desarrollar un lenguaje que se adapta a situaciones lingüísticas dinámicas que pueden cambiar en el tiempo y también posibilita la imposición de restricciones de orden muy frecuentes en las estructuras sintácticas complejas. Todos los modelos implican un planteamiento descentralizado y auto-organizado, de manera que ninguno de los robots es el dueño del lenguaje y todos deben cooperar y colaborar de forma coordinada para lograr el consenso sintáctico. En cada caso se plantean experimentos que tienen como objetivo validar los modelos propuestos, tanto en lo relativo al éxito en la emergencia del lenguaje como en lo relacionado con cuestiones paralelas de importancia, como la interacción hombre-máquina o la propia génesis del lenguaje. ABSTRACT The idea of giving a language to a group of robots or artificial agents has been the subject of intense study in recent decades. The first attempts have focused on the development and emergence of a conventionally shared vocabulary. The advantages that can provide a common vocabulary are evident and therefore a more complex language that combines words would be even more beneficial. Thus some proposals are put forward towards the emergence of a consensual language with a sintactical structure in similar terms to the human language. This work follows this trend. Taking the human language as a model means taking some of the assumptions and theories that disciplines such as philosophy, psychology or linguistics among others have provided. According to these theoretical positions language has a double formal and functional dimension. Based on its formal dimension it seems clear that language follows rules, so that the use of a grammar has been considered essential for representation, but also because grammars are a very simple and powerful device that easily generates these symbolic structures. As for the functional dimension perhaps the most influential theory of recent times, the Theory of Speech Acts has been taken into account. This theory is based on the Wittgenstein’s idea about that the meaning lies in the use of language, to the extent that it is understood as a way of acting and behaving. Having into account these issues this work implements some computational models in order to test if they allow a group of robots to reach in an autonomous way a shared language by means of individual interaction among them, that is by means of language games. Specifically, three different models of language for robots are proposed: • A reinforcement learning based model in which interactions and language use are key to its emergence. This model uses a static probabilistic generative grammar which is designed beforehand. The model is applied to two different groups: one formed exclusively by robots and other combining robots and a human. Therefore, in the second case the learning process is supervised by the human. • A model based on grammatical evolution that allows us to study not only the syntactic consensus, but also the very genesis of language. This model uses a universal grammar that allows robots to evolve for themselves the most appropriate grammar according to the current linguistic situation they deal with. • A model based on grammatical evolution and reinforcement learning that takes aspects of the previous models and increases their possibilities. This model allows robots to develop a language in order to adapt to dynamic language situations that can change over time and also allows the imposition of syntactical order restrictions which are very common in complex syntactic structures. All models involve a decentralized and self-organized approach so that none of the robots is the language’s owner and everyone must cooperate and work together in a coordinated manner to achieve syntactic consensus. In each case experiments are presented in order to validate the proposed models, both in terms of success about the emergence of language and it relates to the study of important parallel issues, such as human-computer interaction or the very genesis of language.

Proposal for a semantic hierarchy of terminological metaphors in science and technology

Cognitive linguistics is considered as one of the most appropriate approaches to the study of scientific and technical language formation and development, where metaphor is accepted to play an essential role. This paper, based on the Cognitive Theory of Metaphor, takes as the starting point the terminological metaphors established in the research project METACITEC(Note 1), which was developed with the purpose of unfolding constitutive metaphors and their function in the language of science and technology. After the analysis of metaphorical terms and using a mixed corpus from the fields of Agriculture, Geology, Mining, Metallurgy, and other related technical fields, this study presents a proposal for a hierarchy of the selected metaphors underlying the scientific conceptual system, based on the semantic distance found in the projection from the source domain to the target domain. We argue that this semantic distance can be considered as an important parameter to take into account in order to establish the metaphoricity of science and technology metaphorical terms. The findings contribute to expand on the CTM stance that metaphor is a matter of cognition by reviewing the abstract-concrete conceptual relationship between the target and source domains, and to determine the role of human creativity and imagination in the language of science and technology configuration

An introduction to flow and transport in fractal models of porous media: Part I

This special issue gathers together a number of recent papers on fractal geometry and its applications to the modeling of flow and transport in porous media. The aim is to provide a systematic approach for analyzing the statics and dynamics of fluids in fractal porous media by means of theory, modeling and experimentation. The topics covered include lacunarity analyses of multifractal and natural grayscale patterns, random packing's of self-similar pore/particle size distributions, Darcian and non-Darcian hydraulic flows, diffusion within fractals, models for the permeability and thermal conductivity of fractal porous media and hydrophobicity and surface erosion properties of fractal structures.

Neuronanatomy, neurology and Bayesian networks

Bayesian networks are data mining models with clear semantics and a sound theoretical foundation. In this keynote talk we will pinpoint a number of neuroscience problems that can be addressed using Bayesian networks. In neuroanatomy, we will show computer simulation models of dendritic trees and classification of neuron types, both based on morphological features. In neurology, we will present the search for genetic biomarkers in Alzheimer's disease and the prediction of health-related quality of life in Parkinson's disease. Most of these challenging problems posed by neuroscience involve new Bayesian network designs that can cope with multiple class variables, small sample sizes, or labels annotated by several experts.

Lateral Dynamic Models for High-Speed Railway Bridges and Vehicles

The analysis of the running safety of railway vehicles on viaducts subject to strong lateral actions such as cross winds requires coupled nonlinear vehicle-bridge interaction models, capable to study extreme events. In this paper original models developed by the authors are described, based on finite elements for the structure, multibody and finite element models for the vehicle, and specially developed interaction elements for the interface between wheel and rail. The models have been implemented within ABAQUS and have full nonlinear capabilities for the structure, the vehicle and the contact interface. An application is developed for the Ulla Viaduct, a 105 m tall arch in the Spanish high-speed railway network. The dynamic analyses allow obtaining critical wind curves, which define the running safety conditions for a given train in terms of speed of circulation and wind speed