5 research outputs found
Educational Technology and Related Education Conferences for January to June 2011 - November 11, 2010
If you attend the same conferences each year, you don’t need to scan this list. This list is your opportunity to “push the envelope” by trying something new. There are hundreds of professional development events that may give you a different perspective or help you learn a new skill. Rather than attend the same event you always do, scan this list and investigate conferences, symposiums, or workshops you have never attended. The list below covers selected events focused primarily on the use of technology in educational settings and on teaching, learning, and educational administration. Only listings until June 2011 are complete as dates, locations, or URLs are not available for a number of events held after June 2011. A Word 2003 format is used to enable people who do not have access to Word 2007 or higher version and those with limited or high-cost Internet access to find a conference that is congruent with their interests or obtain conference proceedings. (If you are seeking a more interactive listing, refer to online conference sites.) Consider using the “Find” tool under Microsoft Word’s “Edit” tab or similar tab in OpenOffice to locate the name of a particular conference, association, city, or country. If you enter the country “United Kingdom” in the “Find” tool, all conferences that occur in the United Kingdom will be highlighted. Then, “cut and paste” a list of suitable events for yourself and your colleagues. Please note that events, dates, titles, and locations may change; thus, CHECK the specific conference website. Note also that some events will be cancelled at a later date. All Internet addresses were verified at the time of publication. No liability is assumed for any errors that may have been introduced inadvertently during the assembly of this conference list. If possible, please do not remove the contact information when you re-distribute the list as that is how I receive updates and corrections. If you publish the list on the web, please note its source
Mathematics in Software Reliability and Quality Assurance
This monograph concerns the mathematical aspects of software reliability and quality assurance and consists of 11 technical papers in this emerging area. Included are the latest research results related to formal methods and design, automatic software testing, software verification and validation, coalgebra theory, automata theory, hybrid system and software reliability modeling and assessment
A Novel Data-Driven Fault Tree Methodology for Fault Diagnosis and Prognosis
RÉSUMÉ : La thèse développe une nouvelle méthodologie de diagnostic et de pronostic de défauts dans un système complexe, nommée Interpretable logic tree analysis (ILTA), qui combine les techniques d’extraction de connaissances à partir des bases de données « knowledge discovery in database (KDD) » et l’analyse d’arbre de défaut « fault tree analysis (FTA) ». La méthodologie capitalise les avantages des deux techniques pour appréhender la problématique de diagnostic et de pronostic de défauts. Bien que les arbres de défauts offrent des modèles interprétables pour déterminer les causes possibles à l’origine d’un défaut, leur utilisation pour le diagnostic de défauts dans un système industriel est limitée, en raison de la nécessité de faire appel à des connaissances expertes pour décrire les relations de cause-à -effet entre les processus internes du système. Cependant, il sera intéressant d’exploiter la puissance d’analyse des arbres de défaut mais construit à partir des connaissances explicites et non biaisées extraites directement des bases de données sur la causalité des fautes. Par conséquent, la méthodologie ILTA fonctionne de manière analogue à la logique du modèle d'analyse d'arbre de défaut (FTA) mais avec une implication minimale des experts. Cette approche de modélisation doit rejoindre la logique des experts pour représenter la structure hiérarchique des défauts dans un système complexe. La méthodologie ILTA est appliquée à la gestion des risques de défaillance en fournissant deux modèles d'arborescence avancés interprétables à plusieurs niveaux (MILTA) et au cours du temps (ITCA). Le modèle MILTA est conçu pour accomplir la tâche de diagnostic de défaillance dans les systèmes complexes. Il est capable de décomposer un défaut complexe et de modéliser graphiquement sa structure de causalité dans un arbre à plusieurs niveaux. Par conséquent, un expert est en mesure de visualiser l’influence des relations hiérarchiques de cause à effet menant à la défaillance principale. De plus, quantifier ces causes en attribuant des probabilités aide à comprendre leur contribution dans l’occurrence de la défaillance du système. Le modèle ITCA est conçu pour réaliser la tâche de pronostic de défaillance dans les systèmes complexes. Basé sur une répartition des données au cours du temps, le modèle ITCA capture l’effet du vieillissement du système à travers de l’évolution de la structure de causalité des fautes. Ainsi, il décrit les changements de causalité résultant de la détérioration et du vieillissement au cours de la vie du système.----------ABSTRACT : The thesis develops a new methodology for diagnosis and prognosis of faults in a complex system, called Interpretable logic tree analysis (ILTA), which combines knowledge extraction techniques from knowledge discovery in databases (KDD) and the fault tree analysis (FTA). The methodology combined the advantages of the both techniques for understanding the problem of diagnosis and prognosis of faults. Although fault trees provide interpretable models for determining the possible causes of a fault, its use for fault diagnosis in an industrial system is limited, due to the need for expert knowledge to describe cause-and-effect relationships between internal system processes. However, it will be interesting to exploit the analytical power of fault trees but built from explicit and unbiased knowledge extracted directly from databases on the causality of faults. Therefore, the ILTA methodology works analogously to the logic of the fault tree analysis model (FTA) but with minimal involvement of experts. This modeling approach joins the logic of experts to represent the hierarchical structure of faults in a complex system. The ILTA methodology is applied to failure risk management by providing two interpretable advanced logic models: a multi-level tree (MILTA) and a multilevel tree over time (ITCA). The MILTA model is designed to accomplish the task of diagnosing failure in complex systems. It is able to decompose a complex defect and graphically model its causal structure in a tree on several levels. As a result, an expert is able to visualize the influence of hierarchical cause and effect relationships leading to the main failure. In addition, quantifying these causes by assigning probabilities helps to understand their contribution to the occurrence of system failure. The second model is a logical tree interpretable in time (ITCA), designed to perform the task of prognosis of failure in complex systems. Based on a distribution of data over time, the ITCA model captures the effect of the aging of the system through the evolution of the fault causation structure. Thus, it describes the causal changes resulting from deterioration and aging over the life of the system
Model Predictive Control Applications to Spacecraft Rendezvous and Small Bodies Exploration
The overarching goal of this thesis is the design of model predictive control algorithms for
spacecraft proximity operations. These include, but it is not limited to, spacecraft rendezvous,
hovering phases or orbiting in the vicinity of small bodies. The main motivation
behind this research is the increasing demand of autonomy, understood as the spacecraft
capability to compute its own control plan, in current and future space operations. This
push for autonomy is fostered by the recent introduction of disruptive technologies changing
the traditional concept of space exploration and exploitation. The development of miniaturized
satellite platforms and the drastic cost reduction in orbital access have boosted space
activity to record levels. In the near future, it is envisioned that numerous artificial objects
will simultaneously operate across the Solar System. In that context, human operators will
be overwhelmed in the task of tracking and commanding each spacecraft in real time. As a
consequence, developing intelligent and robust autonomous systems has been identified by
several space agencies as a cornerstone technology.
Inspired by the previous facts, this work presents novel controllers to tackle several scenarios
related to spacecraft proximity operations. Mastering proximity operations enables
a wide variety of space missions such as active debris removal, astronauts transportation,
flight-formation applications, space stations resupply and the in-situ exploration of small
bodies. Future applications may also include satellite inspection and servicing. This thesis
has focused on four scenarios: six-degrees of freedom spacecraft rendezvous; near-rectilinear
halo orbits rendezvous; the hovering phase; orbit-attitude station-keeping in the vicinity of a
small body. The first problem aims to demonstrate rendezvous capabilities for a lightweight
satellite with few thrusters and a reaction wheels array. For near-rectilinear halo orbits
rendezvous, the goal is to achieve higher levels of constraints satisfaction than with a stateof-
the-art predictive controller. In the hovering phase, the objective is to augment the
control accuracy and computational efficiency of a recent global stable controller. The small
body exploration aims to demonstrate the positive impact of model-learning in the control
accuracy. Although based on model predictive control, the specific approach for each scenario differs.
In six-degrees of freedom rendezvous, the attitude flatness property and the transition
matrix for Keplerian-based relative are used to obtain a non-linear program. Then, the control
loop is closed by linearizing the system around the previous solution. For near-rectilinear
halo orbits rendezvous, the constraints are assured to be satisfied in the probabilistic sense by
a chance-constrained approach. The disturbances statistical properties are estimated on-line.
For the hovering phase problem, an aperiodic event-based predictive controller is designed.
It uses a set of trigger rules, defined using reachability concepts, deciding when to execute a
single-impulse control. In the small body exploration scenario, a novel learning-based model
predictive controller is developed. This works by integrating unscented Kalman filtering and
model predictive control. By doing so, the initially unknown small body inhomogeneous
gravity field is estimated over time which augments the model predictive control accuracy.El objeto de esta tesis es el diseËśno de algoritmos de control predictivo basado en modelo
para operaciones de veh´ıculos espaciales en proximidad. Esto incluye, pero no se limita, a
la maniobra de rendezvous, las fases de hovering u orbitar alrededor de cuerpos menores.
Esta tesis est´a motivada por la creciente demanda en la autonom´ıa, entendida como la capacidad
de un veh´ıculo para calcular su propio plan de control, de las actuales y futuras
misiones espaciales. Este inter´es en incrementar la autonom´ıa est´a relacionado con las actuales
tecnolog´ıas disruptivas que est´an cambiando el concepto tradicional de exploraci´on y
explotaci´on espacial. Estas son el desarrollo de plataformas satelitales miniaturizadas y la
dr´astica reducci´on de los costes de puesta en ´orbita. Dichas tecnolog´ıas han impulsado la
actividad espacial a niveles de record. En un futuro cercano, se prev´e que un gran n´umero de
objetos artificiales operen de manera simult´anea a lo largo del Sistema Solar. Bajo dicho escenario,
los operadores terrestres se ver´an desbordados en la tarea de monitorizar y controlar
cada sat´elite en tiempo real. Es por ello que el desarrollo de sistemas aut´onomos inteligentes
y robustos es considerado una tecnolog´ıa fundamental por diversas agencias espaciales.
Debido a lo anterior, este trabajo presenta nuevos resultados en el control de operaciones
de veh´ıculos espaciales en proximidad. Dominar dichas operaciones permite llevar a cabo
una gran variedad de misiones espaciales como la retirada de basura espacial, transferir
astronautas, aplicaciones de vuelo en formaci´on, reabastecer estaciones espaciales y la exploraci
´on de cuerpos menores. Futuras aplicaciones podr´ıan incluir operaciones de inspecci´on y
mantenimiento de sat´elites. Esta tesis se centra en cuatro escenarios: rendezvous de sat´elites
con seis grados de libertad; rendezvous en ´orbitas halo cuasi-rectil´ıneas; la fase de hovering;
el mantenimiento de ´orbita y actitud en las inmendiaciones de un cuerpo menor. El primer
caso trata de proveer capacidades de rendezvous para un sat´elite ligero con pocos propulsores
y un conjunto de ruedas de reacci´on. Para el rendezvous en ´orbitas halo cuasi-rectil´ıneas, se
intenta aumentar el grado de cumplimiento de restricciones con respecto a un controlador
predictivo actual. Para la fase de hovering, se mejora la precisi´on y eficiencia computacional
de un controlador globalmente estable. En la exploraci´on de un cuerpo menor, se pretende
demostrar el mayor grado de precisi´on que se obtiene al aprender el modelo.
Siendo la base el control predictivo basado en modelo, el enfoque espec´ıfico difiere para
cada escenario. En el rendezvous con seis grados de libertad, se obtiene un programa no-lineal
con el uso de la propiedad flatness de la actitud y la matriz de transici´on del movimiento
relativo Kepleriano. El bucle de control se cierra linealizando en torno a la soluci´on anterior.
Para el rendezvous en ´orbitas halo cuasi-rectil´ıneas, el cumplimiento de restricciones
se garantiza probabil´ısticamente mediante la t´ecnica chance-constrained. Las propiedades
estad´ısticas de las perturbaciones son estimadas on-line. En la fase de hovering, se usa el
control predictivo basado en eventos. Ello consiste en unas reglas de activaci´on, definidas
con conceptos de accesibilidad, que deciden la ejecuci´on de un ´unico impulso de control.
En la exploraci´on de cuerpos menores, se desarrolla un controlador predictivo basado en el
aprendizaje del modelo. Funciona integrando un filtro de Kalman con control predictivo
basado en modelo. Con ello, se consigue estimar las inomogeneidades del campo gravitario
lo que repercute en una mayor precisi´on del controlador predictivo basado en modelo