Modélisation mathématique de la propagation de la malaria.

Un modèle mathématique de la propagation de la malaria en temps discret est élaboré en vue de déterminer l'influence qu'un déplacement des populations des zones rurales vers les zones urbaines aurait sur la persistance ou la diminution de l'incidence de la malaria. Ce modèle, sous la forme d'un système de quatorze équations aux différences finies, est ensuite comparé à un modèle analogue mais en temps continu, qui prend la forme d'équations différentielles ordinaires. Une étude comparative avec la littérature récente permet de déterminer les forces et les faiblesses de notre modèle.

A Study on the Kerridge's Inaccuracy Measure and Related Conceptss

Department of Statistics, Cochin University of Sciene ans Technology

Invariant density for a class of initial distributions under quadratic mapping

For the discrete-time quadratic map xt+1=4xt(1-xt) the evolution equation for a class of non-uniform initial densities is obtained. It is shown that in the t to infinity limit all of them approach the invariant density for the map.

Service quality and reliability assessment of mobile communication infrastructure

The service quality of any sector has two major aspects namely technical and functional. Technical quality can be attained by maintaining technical specification as decided by the organization. Functional quality refers to the manner which service is delivered to customer which can be assessed by the customer feed backs. A field survey was conducted based on the management tool SERVQUAL, by designing 28 constructs under 7 dimensions of service quality. Stratified sampling techniques were used to get 336 valid responses and the gap scores of expectations and perceptions are analyzed using statistical techniques to identify the weakest dimension. To assess the technical aspects of availability six months live outage data of base transceiver were collected. The statistical and exploratory techniques were used to model the network performance. The failure patterns have been modeled in competing risk models and probability distribution of service outage and restorations were parameterized. Since the availability of network is a function of the reliability and maintainability of the network elements, any service provider who wishes to keep up their service level agreements on availability should be aware of the variability of these elements and its effects on interactions. The availability variations were studied by designing a discrete time event simulation model with probabilistic input parameters. The probabilistic distribution parameters arrived from live data analysis was used to design experiments to define the availability domain of the network under consideration. The availability domain can be used as a reference for planning and implementing maintenance activities. A new metric is proposed which incorporates a consistency index along with key service parameters that can be used to compare the performance of different service providers. The developed tool can be used for reliability analysis of mobile communication systems and assumes greater significance in the wake of mobile portability facility. It is also possible to have a relative measure of the effectiveness of different service providers.

Räumliche Modellierung der Dynamik von Landnutzung in Hessen und ihrer Wirkung auf die biologische Kohlenstoffspeicherung - Entwicklung eines GIS-basierten Modellsystems

Die gegenwärtige Entwicklung der internationalen Klimapolitik verlangt von Deutschland eine Reduktion seiner Treibhausgasemissionen. Wichtigstes Treibhausgas ist Kohlendioxid, das durch die Verbrennung fossiler Energieträger in die Atmosphäre freigesetzt wird. Die Reduktionsziele können prinzipiell durch eine Verminderung der Emissionen sowie durch die Schaffung von Kohlenstoffsenken erreicht werden. Senken beschreiben dabei die biologische Speicherung von Kohlenstoff in Böden und Wäldern. Eine wichtige Einflussgröße auf diese Prozesse stellt die räumliche Dynamik der Landnutzung einer Region dar. In dieser Arbeit wird das Modellsystem HILLS entwickelt und zur Simulation dieser komplexen Wirkbeziehungen im Bundesland Hessen genutzt. Ziel ist es, mit HILLS über eine Analyse des aktuellen Zustands hinaus auch Szenarien über Wege der zukünftigen regionalen Entwicklung von Landnutzung und ihrer Wirkung auf den Kohlenstoffhaushalt bis 2020 zu untersuchen. Für die Abbildung der räumlichen und zeitlichen Dynamik von Landnutzung in Hessen wird das Modell LUCHesse entwickelt. Seine Aufgabe ist die Simulation der relevanten Prozesse auf einem 1 km2 Raster, wobei die Raten der Änderung exogen als Flächentrends auf Ebene der hessischen Landkreise vorgegeben werden. LUCHesse besteht aus Teilmodellen für die Prozesse: (A) Ausbreitung von Siedlungs- und Gewerbefläche, (B) Strukturwandel im Agrarsektor sowie (C) Neuanlage von Waldflächen (Aufforstung). Jedes Teilmodell umfasst Methoden zur Bewertung der Standorteignung der Rasterzellen für unterschiedliche Landnutzungsklassen und zur Zuordnung der Trendvorgaben zu solchen Rasterzellen, die jeweils am besten für eine Landnutzungsklasse geeignet sind. Eine Validierung der Teilmodelle erfolgt anhand von statistischen Daten für den Zeitraum von 1990 bis 2000. Als Ergebnis eines Simulationslaufs werden für diskrete Zeitschritte digitale Karten der Landnutzugsverteilung in Hessen erzeugt. Zur Simulation der Kohlenstoffspeicherung wird eine modifizierte Version des Ökosystemmodells Century entwickelt (GIS-Century). Sie erlaubt einen gesteuerten Simulationslauf in Jahresschritten und unterstützt die Integration des Modells als Komponente in das HILLS Modellsystem. Es werden verschiedene Anwendungsschemata für GIS-Century entwickelt, mit denen die Wirkung der Stilllegung von Ackerflächen, der Aufforstung sowie der Bewirtschaftung bereits bestehender Wälder auf die Kohlenstoffspeicherung untersucht werden kann. Eine Validierung des Modells und der Anwendungsschemata erfolgt anhand von Feld- und Literaturdaten. HILLS implementiert eine sequentielle Kopplung von LUCHesse mit GIS-Century. Die räumliche Kopplung geschieht dabei auf dem 1 km2 Raster, die zeitliche Kopplung über die Einführung eines Landnutzungsvektors, der die Beschreibung der Landnutzungsänderung einer Rasterzelle während des Simulationszeitraums enthält. Außerdem integriert HILLS beide Modelle über ein dienste- und datenbankorientiertes Konzept in ein Geografisches Informationssystem (GIS). Auf diesem Wege können die GIS-Funktionen zur räumlichen Datenhaltung und Datenverarbeitung genutzt werden. Als Anwendung des Modellsystems wird ein Referenzszenario für Hessen mit dem Zeithorizont 2020 berechnet. Das Szenario setzt im Agrarsektor eine Umsetzung der AGENDA 2000 Politik voraus, die in großem Maße zu Stilllegung von Ackerflächen führt, während für den Bereich Siedlung und Gewerbe sowie Aufforstung die aktuellen Trends der Flächenausdehnung fortgeschrieben werden. Mit HILLS ist es nun möglich, die Wirkung dieser Landnutzungsänderungen auf die biologische Kohlenstoffspeicherung zu quantifizieren. Während die Ausdehnung von Siedlungsflächen als Kohlenstoffquelle identifiziert werden kann (37 kt C/a), findet sich die wichtigste Senke in der Bewirtschaftung bestehender Waldflächen (794 kt C/a). Weiterhin führen die Stilllegung von Ackerfläche (26 kt C/a) sowie Aufforstung (29 kt C/a) zu einer zusätzlichen Speicherung von Kohlenstoff. Für die Kohlenstoffspeicherung in Böden zeigen die Simulationsexperimente sehr klar, dass diese Senke nur von beschränkter Dauer ist.

Modeling of hybrid systems by piecewise decomposition

Piecewise linear models systems arise as mathematical models of systems in many practical applications, often from linearization for nonlinear systems. There are two main approaches of dealing with these systems according to their continuous or discrete-time aspects. We propose an approach which is based on the state transformation, more particularly the partition of the phase portrait in different regions where each subregion is modeled as a two-dimensional linear time invariant system. Then the Takagi-Sugeno model, which is a combination of local model is calculated. The simulation results show that the Alpha partition is well-suited for dealing with such a system

Determinantes de la deserción universitaria en la Facultad de Economía de la Universidad del Rosario

Este trabajo analiza el problema de la deserción estudiantil en la Facultad de Economía de la Universidad del Rosario, a través del estudio de los factores individuales, académicos y socioeconómicos que implican el riesgo de desertar. Con este objetivo, se utiliza el análisis de modelos de duración. Específi camente, se estima un modelo de riesgo proporcional de tiempo discreto con y sin heterogeneidad observada (Prentice- Gloeckler, 1978 y Meyer, 1980). Los resultados muestran que los estudiantes de sexo masculino, la vinculación de los estudiantes al mercado laboral y los estudiantes provenientes de otras regiones, tienen el mayor riesgo de deserción. Además, la edad del estudiante incrementa el riesgo, sin embargo, su efecto decrece marginalmente al aumentar la edad. Palabras clave: deserción estudiantil, modelos de duración, riesgo proporcional. Clasifi cación JEL: C41, C13, I21.

Grado de predicción del valor de las acciones ante nuevas emisiones en el sector de extracción de petróleo crudo y gas natural en Colombia, mediante modelos de caos y análisis recurrente

El presente trabajo se enfoca en el análisis de las acciones de Ecopetrol, empresa representativa del mercado de Extracción de Petróleo y Gas natural en Colombia (SP&G), durante el periodo, del 22 de mayo de 2012 al 30 de agosto de 2013. Durante este espacio de tiempo la acción sufrió una serie de variaciones en su precio las cuales se relacionaban a la nueva emisión de acciones que realizo la Compañía. Debido a este cambio en el comportamiento del activo se generaron una serie de interrogantes sobre, (i) la reacción del mercado ante diferentes sucesos ocurridos dentro de las firmas y en su entorno (ii) la capacidad de los modelos financieros de predecir y entender las posibles reacciones observadas de los activos (entendidos como deuda). Durante el desarrollo del presente trabajo se estudiará la pertinencia del mismo, en línea con los objetivos y desarrollos de la Escuela de Administración de la Universidad del Rosario. Puntualmente en temas de Perdurabilidad direccionados a la línea de Gerencia. Donde el entendimiento de la deuda como parte del funcionamiento actual y como variable determinante para el comportamiento futuro de las organizaciones tiene especial importancia. Una vez se clarifica la relación entre el presente trabajo y la Universidad, se desarrollan diferentes conceptos y teorías financieras que han permitido conocer y estudiar de manera más específica el mercado, con el objetivo de reducir los riesgos de las inversiones realizadas. Éste análisis se desarrolla en dos partes: (i) modelos de tiempo discreto y (ii) modelos de tiempo continúo. Una vez se tiene mayor claridad sobre los modelos estudiados hasta el momento se realiza el respectivo análisis de los datos mediante modelos de caos y análisis recurrente los cuales nos permiten entender que las acciones se comportan de manera caótica pero que establecen ciertas relaciones entre los precios actuales y los históricos, desarrollando comportamientos definidos entre los precios, las cantidades, el entorno macroeconómico y la organización. De otra parte, se realiza una descripción del mercado de petróleo en Colombia y se estudia a Ecopetrol como empresa y eje principal del mercado descrito en el país. La compañía Ecopetrol es representativa debido a que es uno de los mayores aportantes fiscales del país, pues sus ingresos se desprenden de bienes que se encuentran en el subsuelo por lo que la renta petrolera incluye impuestos a la producción transformación y consumo (Ecopetrol, 2003). Por último, se presentan los resultados del trabajo, así como el análisis que da lugar para presentar ciertas recomendaciones a partir de lo observado.

Designing flexible procurement systems

The systems used for the procurement of buildings are organizational systems. They involve people in a series of strategic decisions, and a pattern of roles, responsibilities and relationships that combine to form the organizational structure of the project. To ensure effectiveness of the building team, this organizational structure needs to be contingent upon the environment within which the construction project takes place. In addition, a changing environment means that the organizational structure within a project needs to be responsive, and dynamic. These needs are often not satisfied in the construction industry, due to the lack of analytical tools with which to analyse the environment and to design appropriate temporary organizations. This paper presents two techniques. First is the technique of "Environmental Complexity Analysis", which identifies the key variables in the environment of the construction project. These are classified as Financial, Legal, Technological, Aesthetic and Policy. It is proposed that their identification will set the parameters within which the project has to be managed. This provides a basis for the project managers to define the relevant set of decision points that will be required for the project. The Environmental Complexity Analysis also identifies the project's requirements for control systems concerning Budget, Contractual, Functional, Quality and Time control. The process of environmental scanning needs to be done at regular points during the procurement process to ensure that the organizational structure is adaptive to the changing environment. The second technique introduced is the technique of "3R analysis", being a graphical technique for describing and modelling Roles, Responsibilities and Relationships. A list of steps is introduced that explains the procedure recommended for setting up a flexible organizational structure that is responsive to the environment of the project. This is by contrast with the current trend towards predetermined procurement paths that may not always be in the best interests of the client.

Invasive neural prosthesis for neural signal detection and nerve stimulation

This paper specifically examines the implantation of a microelectrode array into the median nerve of the left arm of a healthy male volunteer. The objective was to establish a bi-directional link between the human nervous system and a computer, via a unique interface module. This is the first time that such a device has been used with a healthy human. The aim of the study was to assess the efficacy, compatibility, and long term operability of the neural implant in allowing the subject to perceive feedback stimulation and for neural activity to be detected and processed such that the subject could interact with remote technologies. A case study demonstrating real-time control of an instrumented prosthetic hand by means of the bi-directional link is given. The implantation did not result in infection, and scanning electron microscope images of the implant post extraction have not indicated significant rejection of the implant by the body. No perceivable loss of hand sensation or motion control was experienced by the subject while the implant was in place, and further testing of the subject following the removal of the implant has not indicated any measurable long term defects. The implant was extracted after 96 days. Copyright © 2004 John Wiley & Sons, Ltd.

Data based constructive identification - overcoming the curse of dimensionality

The modelling of a nonlinear stochastic dynamical processes from data involves solving the problems of data gathering, preprocessing, model architecture selection, learning or adaptation, parametric evaluation and model validation. For a given model architecture such as associative memory networks, a common problem in non-linear modelling is the problem of "the curse of dimensionality". A series of complementary data based constructive identification schemes, mainly based on but not limited to an operating point dependent fuzzy models, are introduced in this paper with the aim to overcome the curse of dimensionality. These include (i) a mixture of experts algorithm based on a forward constrained regression algorithm; (ii) an inherent parsimonious delaunay input space partition based piecewise local lineal modelling concept; (iii) a neurofuzzy model constructive approach based on forward orthogonal least squares and optimal experimental design and finally (iv) the neurofuzzy model construction algorithm based on basis functions that are Bézier Bernstein polynomial functions and the additive decomposition. Illustrative examples demonstrate their applicability, showing that the final major hurdle in data based modelling has almost been removed.

Bistability through triadic closure

We propose and analyse a class of evolving network models suitable for describing a dynamic topological structure. Applications include telecommunication, on-line social behaviour and information processing in neuroscience. We model the evolving network as a discrete time Markov chain, and study a very general framework where, conditioned on the current state, edges appear or disappear independently at the next timestep. We show how to exploit symmetries in the microscopic, localized rules in order to obtain conjugate classes of random graphs that simplify analysis and calibration of a model. Further, we develop a mean field theory for describing network evolution. For a simple but realistic scenario incorporating the triadic closure effect that has been empirically observed by social scientists (friends of friends tend to become friends), the mean field theory predicts bistable dynamics, and computational results confirm this prediction. We also discuss the calibration issue for a set of real cell phone data, and find support for a stratified model, where individuals are assigned to one of two distinct groups having different within-group and across-group dynamics.

A dynamical systems framework for intermittent data assimilation

We consider the problem of discrete time filtering (intermittent data assimilation) for differential equation models and discuss methods for its numerical approximation. The focus is on methods based on ensemble/particle techniques and on the ensemble Kalman filter technique in particular. We summarize as well as extend recent work on continuous ensemble Kalman filter formulations, which provide a concise dynamical systems formulation of the combined dynamics-assimilation problem. Possible extensions to fully nonlinear ensemble/particle based filters are also outlined using the framework of optimal transportation theory.

Estimation of magnet separation for magnetic suspension applications

This thesis describes a form of non-contact measurement using two dimensional hall effect sensing to resolve the location of a moving magnet which is part of a ‘magnetic spring’ type suspension system. This work was inspired by the field of Space Robotics, which currently relies on solid link suspension techniques for rover stability. This thesis details the design, development and testing of a novel magnetic suspension system with a possible application in space and terrestrial based robotics, especially when the robot needs to traverse rough terrain. A number of algorithms were developed, to utilize experimental data from testing, that can approximate the separation between magnets in the suspension module through observation of the magnetic fields. Experimental hardware was also developed to demonstrate how two dimensional hall effect sensor arrays could provide accurate feedback, with respects to the magnetic suspension modules operation, so that future work can include the sensor array in a real-time control system to produce dynamic ride control for space robots. The research performed has proven that two dimensional hall effect sensing with respects to magnetic suspension is accurate, effective and suitable for future testing.

Memory and burstiness in dynamic networks

A discrete-time random process is described, which can generate bursty sequences of events. A Bernoulli process, where the probability of an event occurring at time t is given by a fixed probability x, is modified to include a memory effect where the event probability is increased proportionally to the number of events that occurred within a given amount of time preceding t. For small values of x the interevent time distribution follows a power law with exponent −2−x. We consider a dynamic network where each node forms, and breaks connections according to this process. The value of x for each node depends on the fitness distribution, \rho(x), from which it is drawn; we find exact solutions for the expectation of the degree distribution for a variety of possible fitness distributions, and for both cases where the memory effect either is, or is not present. This work can potentially lead to methods to uncover hidden fitness distributions from fast changing, temporal network data, such as online social communications and fMRI scans.