An empirical evaluation of the Random Forests classifier models for variable selection in a large-scale lung cancer case-control study

Random Forests™ is reported to be one of the most accurate classification algorithms in complex data analysis. It shows excellent performance even when most predictors are noisy and the number of variables is much larger than the number of observations. In this thesis Random Forests was applied to a large-scale lung cancer case-control study. A novel way of automatically selecting prognostic factors was proposed. Also, synthetic positive control was used to validate Random Forests method. Throughout this study we showed that Random Forests can deal with large number of weak input variables without overfitting. It can account for non-additive interactions between these input variables. Random Forests can also be used for variable selection without being adversely affected by collinearities. ^ Random Forests can deal with the large-scale data sets without rigorous data preprocessing. It has robust variable importance ranking measure. Proposed is a novel variable selection method in context of Random Forests that uses the data noise level as the cut-off value to determine the subset of the important predictors. This new approach enhanced the ability of the Random Forests algorithm to automatically identify important predictors for complex data. The cut-off value can also be adjusted based on the results of the synthetic positive control experiments. ^ When the data set had high variables to observations ratio, Random Forests complemented the established logistic regression. This study suggested that Random Forests is recommended for such high dimensionality data. One can use Random Forests to select the important variables and then use logistic regression or Random Forests itself to estimate the effect size of the predictors and to classify new observations. ^ We also found that the mean decrease of accuracy is a more reliable variable ranking measurement than mean decrease of Gini. ^

Analytical models for the power subsystem and the attitude control subsystem of a microsatellite

El trabajo realizado en la presente tesis doctoral se debe considerar parte del proyecto UPMSat-2, que se enmarca dentro del ámbito de la tecnología aeroespacial. El UPMSat-2 es un microsatélite (de bajo coste y pequeño tamaño) diseñado, construido, probado e integrado por la Universidad Politécnica de Madrid (España), para fines de demostración tecnológica y educación. El objetivo de la presente tesis doctoral es presentar nuevos modelos analíticos para estudiar la interdependencia energética entre los subsistemas de potencia y de control de actitud de un satélite. En primer lugar, se estudia la simulación del subsistema de potencia de un microsatélite, prestando especial atención a la simulación de la fuente de potencia, esto es, los paneles solares. En la tesis se presentan métodos sencillos pero precisos para simular la producción de energía de los paneles en condiciones ambientales variables a través de su circuito equivalente. Los métodos propuestos para el cálculo de los parámetros del circuito equivalente son explícitos (o al menos, con las variables desacopladas), no iterativos y directos; no se necesitan iteraciones o valores iniciales para calcular los parámetros. La precisión de este método se prueba y se compara con métodos similares de la literatura disponible, demostrando una precisión similar para mayor simplicidad. En segundo lugar, se presenta la simulación del subsistema de control de actitud de un microsatélite, prestando especial atención a la nueva ley de control propuesta. La tesis presenta un nuevo tipo de control magnético es aplicable a la órbita baja terrestre (LEO). La ley de control propuesta es capaz de ajustar la velocidad de rotación del satélite alrededor de su eje principal de inercia máximo o mínimo. Además, en el caso de órbitas de alta inclinación, la ley de control favorece la alineación del eje de rotación con la dirección normal al plano orbital. El algoritmo de control propuesto es simple, sólo se requieren magnetopares como actuadores; sólo se requieren magnetómetros como sensores; no hace falta estimar la velocidad angular; no incluye un modelo de campo magnético de la Tierra; no tiene por qué ser externamente activado con información sobre las características orbitales y permite el rearme automático después de un apagado total del subsistema de control de actitud. La viabilidad teórica de la citada ley de control se demuestra a través de análisis de Monte Carlo. Por último, en términos de producción de energía, se demuestra que la actitud propuesto (en eje principal perpendicular al plano de la órbita, y el satélite que gira alrededor de ella con una velocidad controlada) es muy adecuado para la misión UPMSat-2, ya que permite una área superior de los paneles apuntando hacia el sol cuando se compara con otras actitudes estudiadas. En comparación con el control de actitud anterior propuesto para el UPMSat-2 resulta en un incremento de 25% en la potencia disponible. Además, la actitud propuesto mostró mejoras significativas, en comparación con otros, en términos de control térmico, como la tasa de rotación angular por satélite puede seleccionarse para conseguir una homogeneización de la temperatura más alta que apunta satélite y la antena. ABSTRACT The work carried out in the present doctoral dissertation should be considered part of the UPMSat-2 project, falling within the scope of the aerospace technology. The UPMSat-2 is a microsatellite (low cost and small size) designed, constructed integrated and tested for educational and technology demonstration purposes at the Universidad Politécnica de Madrid (Spain). The aim of the present doctoral dissertation is to present new analytical models to study the energy interdependence between the power and the attitude control subsystems of a satellite. First, the simulation of the power subsystem of a microsatellite is studied, paying particular attention to the simulation of the power supply, i.e. the solar panels. Simple but accurate methods for simulate the power production under variable ambient conditions using its equivalent circuit are presented. The proposed methods for calculate the equivalent circuit parameters are explicit (or at least, with decoupled variables), non-iterative and straight forward; no iterations or initial values for the parameters are needed. The accuracy of this method is tested and compared with similar methods from the available literature demonstrating similar precision but higher simplicity. Second, the simulation of the control subsystem of a microsatellite is presented, paying particular attention to the new control law proposed. A new type of magnetic control applied to Low Earth Orbit (LEO) satellites has been presented. The proposed control law is able to set the satellite rotation speed around its maximum or minimum inertia principal axis. Besides, the proposed control law favors the alignment of this axis with the normal direction to the orbital plane for high inclination orbits. The proposed control algorithm is simples, only magnetorquers are required as actuators; only magnetometers are required as sensors; no estimation of the angular velocity is needed; it does not include an in-orbit Earth magnetic field model; it does not need to be externally activated with information about the orbital characteristics and it allows automatic reset after a total shutdown of attitude control subsystem. The theoretical viability of the control law is demonstrated through Monte Carlo analysis. Finally, in terms of power production, it is demonstrated that the proposed attitude (on principal axis perpendicular to the orbit plane, and the satellite rotating around it with a controlled rate) is quite suitable for the UPMSat-2 mission, as it allows a higher area of the panels pointing towards the sun when compared to other studied attitudes. Compared with the previous attitude control proposed for the UPMSat-2 it results in a 25% increment in available power. Besides, the proposed attitude showed significant improvements, when compared to others, in terms of thermal control, as the satellite angular rotation rate can be selected to achieve a higher temperature homogenization of the satellite and antenna pointing.

Operator, organizational, direct and general support, and depot maintenance manual : control, radio set C6118/FRC-93 (Collins models 312B-4 and 312B-5).

"June 1964."

Borrowing from models of motor control to translate cognitive processes: Evidence for hypokinetic-hyperkinetic linguistic homologues?

In relation to motor control, the basal ganglia have been implicated in both the scaling and focusing of movement. Hypokinetic and hyperkinetic movement disorders manifest as a consequence of overshooting and undershooting GPi (globus pallidus internus) activity thresholds, respectively. Recently, models of motor control have been borrowed to translate cognitive processes relating to the overshooting and undershooting of GPi activity, including attention and executive function. Linguistic correlates, however, are yet to be extrapolated in sufficient detail. The aims of the present investigation were to: (1) characterise cognitive-linguistic processes within hypokinetic and hyperkinetic neural systems, as defined by motor disturbances; (2) investigate the impact of surgically-induced GPi lesions upon language abilities. Two Parkinsonian cases with opposing motor symptoms (akinetic versus dystonic/dyskinetic) served as experimental subjects in this research. Assessments were conducted both prior to as well as 3 and 12 months following bilateral posteroventral pallidotomy (PVP). Reliable changes in performance (i.e. both improvements and decrements) were typically restricted to tasks demanding complex linguistic operations across subjects. Hyperkinetic motor symptoms were associated with an initial overall improvement in complex language function as a consequence of bilateral PVP, which diminished over time, suggesting a decrescendo effect relative to surgical beneficence. In contrast, hypokinetic symptoms were associated with a more stable longitudinal linguistic profile, albeit defined by higher proportions of reliable decline versus improvement in postoperative assessment scores. The above findings endorsed the integration of the GPi within cognitive mechanisms involved in the arbitration of complex language functions. In relation to models of motor control, 'focusing' was postulated to represent the neural processes underpinning lexical-semantic manipulation, and 'scaling' the potential allocation of cognitive resources during the mediation of high-level linguistic tasks. (c) 2005 Elsevier Ltd. All rights reserved.

Improving learning in undergraduate control engineering courses using context-based learning models

Control Engineering is an essential part of university electrical engineering education. Normally, a control course requires considerable mathematical as well as engineering knowledge and is consequently regarded as a difficult course by many undergraduate students. From the academic point of view, how to help the students to improve their learning of the control engineering knowledge is therefore an important task which requires careful planning and innovative teaching methods. Traditionally, the didactic teaching approach has been used to teach the students the concepts needed to solve control problems. This approach is commonly adopted in many mathematics intensive courses; however it generally lacks reflection from the students to improve their learning. This paper addresses the practice of action learning and context-based learning models in teaching university control courses. This context-based approach has been practised in teaching several control engineering courses in a university with promising results, particularly in view of student learning performances.

Improved robust control of nonlinear stochastic systems using uncertain models

We introduce a technique for quantifying and then exploiting uncertainty in nonlinear stochastic control systems. The approach is suboptimal though robust and relies upon the approximation of the forward and inverse plant models by neural networks, which also estimate the intrinsic uncertainty. Sampling from the resulting Gaussian distributions of the inversion based neurocontroller allows us to introduce a control law which is demonstrably more robust than traditional adaptive controllers.

Logical Models of Composite Dynamic Objects Control

The questions of designing multicriteria control systems on the basis of logic models of composite dynamic objects are considered.