We present work to transfer decentralized neuromuscular control strategies of human locomotion to powered segmented robotic legs. State-of-the-art robotic locomotion control approaches, like centralized planning and tracking in fully robotic systems and predefined motion pattern replay in prosthetic systems, do not enable the dynamism and reactiveness of able-bodied humans. Animals largely realize dexterous segmented leg performance with leg-encoded biomechanics and local feedback controls that bypass central processing. A decentralized neuromuscular controller was recently developed that enables robust locomotion for a simulated multi-segmented planar humanoid. A portion of this controller was used in an active ankle-foot prosthesis to modulate ankle torque during stance, enabling level and inclined ground walking. While these results suggest that the neuromuscular controller is a promising alternative control method for both fully robotic systems and powered prostheses, it is unclear if the controller can be transferred to multi-segmented robotic legs. The goal of this thesis is to investigate the feasibility of controlling a multi-segmented robotic leg with the proposed neuromuscular control approach, which may enable robots and powered prostheses to react to locomotion disturbances dynamically and in a human-like way. Specifically, work in this thesis investigates two hypotheses. Hypothesis one posits that the proposed decentralized swing-leg controllers enable more robust foot placements into ground targets than state-of-the-art impedance controls. Hypothesis two posits that neuromuscular swing-leg control enables more human-like motion than state-of-the-art impedance control. To transfer neuromuscular controls to powered segmented robotic legs, we use a model-based design approach. The initial transfer is focused on neuromuscular swing-leg controls, important for maintaining dynamic stability of both fully robotic systems and powered prostheses in the presence of unexpected locomotion disturbances, such as trips and pushes. We first present the design of RNL, a three segment, cable-driven, antagonistically actuated robotic leg with joint compliance. The robot’s size, weight, and actuation capabilities correspond to dynamically scaled human values. Next, a highfidelity simulation of the robot is created to investigate the feasibility of transferring neuromuscular controls, pre-tune hardware gains via optimization, and serve as a benchmark for hardware experiments. An idealized version of the swing-leg controller with mono-articular actuation, as well as the neuromuscular interpretation of this controller with multi-articular actuation is then transferred to RNL and evaluated with foot placement experiments. The results suggest that the proposed swing-leg controllers can accurately regulate foot placement of robotic legs during undisturbed and disturbed motions. Compared to impedance control, the proposed controls achieve foot placements over a range of ground targets with a single set of gains, which make them attractive candidates for regulating the motion of legged robots and prostheses in the real-world. Furthermore, the ankle trajectory traced out by the robot under neuromuscular control is more human-like than the trajectories traced out under the proposed idealized control and impedance control. In parallel to this control transfer, a synthesis method for creating compact nonlinear springs with user-defined torque-deflection profiles is presented to explore methods for improving RNL’s series elastic actuators. The springs use rubber as their elastic element, which, while enabling a compact spring design, introduce viscoelastic behavior in the spring that needs to be accounted for with additional control. To accurately estimate force developed in the rubber, an empirically characterized constitutive rubber model is developed and integrated into the series elastic actuator controller used by the RNL test platforms. Benchtop experiments show that in conjunction with an observer, the nonlinear spring prototype achieves desired behavior at actuation frequencies up to 2 Hz, after which spring behavior degrades due to rubber hysteresis. These results show that while the presented methodology is capable of realizing compact nonlinear springs, careful rubber selection that mitigates viscoelastic behavior is necessary during the spring design process.

La presente investigación trata sobre la creación y aplicación de una Metodología para solucionar problemas resolubles de manera determinista mediante técnicas sencillas y en un tiempo razonable, como puede ser, por ejemplo la resolución de ecuaciones lineales, la realización de pronósticos basados en la ecuación de la línea, pudiendo acortar el tiempo de resolución, más o menos largo, de una manera aceptable Se presenta una nueva metodología, que utiliza la clase Box-Jenkins, para la predicción de la demanda de llamadas, que efectúan los clientes a los centros de llamadas más conocidos como call-center. Se registró, en el trabajo de campo, los aportes y los modelos de solución de diversos autores: orientación del asesor, aporte de investigadores de la UNMSM, investigaciones desarrolladas en diversas organizaciones y las propuestas del autor. El propósito de la Tesis es generar un modelo de consenso con mayor eficiencia que las alternativas existentes y aplicar este modelo en la realidad administrativa. El estudio concluye que la propuesta metodológica para rediseñar procesos de atención al cliente, dentro del contexto de los modelos empresariales, empleando herramientas de serie de tiempos funciona de manera eficiente y reporta excelentes resultados en su aplicación, lo que ha de redundar en la mejora de la eficiencia y competitividad derivado de un uso racional de un recurso escaso clave, el humano. / --- This research is about creating and implementing a methodology to solve problems deterministically solvable through simple techniques and a reasonable time, as can be, for example, solving linear equations, the performance of forecasts based on the equation of the online and can shorten the resolution time, more or less long, in a manner acceptable We present a new methodology, which uses the Box-Jenkins class, for prediction of demand for calls, which make customers call centers known as call-center. Was recorded in the field, contributions and solution models from various authors: guidance counselor, contribution of researchers from San Marcos University, research conducted in various organizations and the author's proposals. The purpose of this thesis is to generate a consensus model more efficiently than existing alternatives and apply this model in the administrative reality. The study concludes that the proposed methodology to redesign customer processes within the context of business models, using time series tools works efficiently and provides excellent results in their application, which would be in improving efficiency and competitiveness from a rational use of a scarce resource key, the human.

La presente Tesis de Investigación Doctoral hace un análisis sistemático, sistémico y armónico del registro del potencial evocado hasta llegar a la codificación de esta señal bioeléctrica para su uso como registro individual específico mediante código de barras. El código nervioso de una señal sensorial, cuyos detalles falta descifrar, está conformado por un conjunto de señales eléctricas que procesan las redes neurales del sistema sensorial, los núcleos subcorticales y la corteza cerebral, el cual es posible analizar y decodificar. Las señales nerviosas sensoriales representan por sí solas el medio exterior, pero sus procesos esenciales son decodificados en la corteza cerebral, donde se activa la información psíquica correspondiente, el decodificar las señales neuronales y su significado. Estas señales se procesan en redes simétricas interconectadas en tiempo real, es decir, existen diferentes formas simétricas de señales en cualquier estructura del cerebro. Tomando al cerebro humano como sistema de emisión de señales bioelectromagnéticas, se crea una interfaz con el potencial evocado, lo que permite analizar las distintas latencias y amplitudes en forma de señales neuronales bioelectromágneticas, expresadas en minivoltios y hertzios, dentro de una longitud de onda que evoca el cerebro, utilizando modelos matemáticos como las series de Fourier, wavelets y fractales. En esta interfaz se introduce el código de barras que es un código basado en la representación mediante un conjunto de líneas paralelas verticales de distinto grosor y espaciado, que en su conjunto contienen una determinada información. De este modo, el código de barras permite reconocer rápidamente a una persona, en tanto permite generar un registro individual específico de esta persona. Con esta finalidad, se obtuvieron pruebas médicas del potencial evocado y se decodificaron mediante la trasformada de Fourier, lo que permitió la descomposición de la señal en componentes de frecuencias diferentes, g, que corresponde al espectro de frecuencias de la señal f. Luego, estas fueron procesadas mediante los modelos fractales, lográndose obtener una trasformada que se expresa en un código de barras personalizado. Es decir, el código nervioso es descifrado mediante la matematización con el uso de las series de Fourier y el procesamiento de la dimensión fractal y de su transformada, hacia un código de barras con múltiples aplicaciones en todas las ciencias. / -- The following Ph.D. thesis research presents a systematic, systemic and harmonic analysis from the evoked potential record until the encoding of this bioelectric signal; in order to use it as a specific individual record through barcode. The nervous code of a sensorial signal, which details need to be decoded, is formed by a group of electrical signal that processes the neural networks of the sensorial system, the sub cortical nuclei and the cerebral cortex. It is possible to analyze and decode. The sensorial nervous signals represent themselves the external mean, but their essential process is decoded at the cerebral cortex level, where it actives the respective psychic information. To decode the neural signals and their meaning. These signals are processed in real-time interconnected symmetrical networks, which mean there are different shapes of symmetrical signals within any brain structure. Taking the human brain as a bioelectromagnetic signal emission system, an interface is created with the evoked potential, which allows analyzing the different latencies and amplitudes through bioelectromagnetic neural signals, expressed on mini volts and hertz, within a wavelength that evokes the brain using mathematical models such as the Fourier series, wavelets and fractals. In this interface, a barcode is produced, which is a code based on the representation of a group of vertical parallel lines with different widths and spacings, storing specific information. In this manner, the barcode allows to recognize a person quickly, as it allows generating a specific individual record of this person. In this way, clinical tests of the evoked potential were obtained, they were decoded by the Fourier Transform, which allowed decomposing a signal into components of different frequency, g, represents the frequency spectrum of the signal f. Then, it was processed through fractal models obtaining a transform expressed by a personal barcode. In other words, the nervous code is decoded by mathematical means, using the Fourier series and the process fractal dimension and its transform, into a barcode with multiple applications to several sciences.

Since its development, the scanning transmission electron microscope has rapidly found uses right across the material sciences. Its use of a finely focussed electron probe rastered across samples offers the microscopist a variety of imaging and spectroscopy signals in parallel. These signals are individually intuitive to interpret, and collectively immensely powerful as a research tool. Unsurprisingly then, much attention is concentrated on the optical quality of the electron probes used. The introduction of multi-pole hardware to correct optical distortions has yielded a step-change in imaging performance; now with spherical and other remnant aberrations greatly reduced, larger probe forming apertures are suddenly available. Probes formed by such apertures exhibit a much improved and routinely sub-Angstrom diffraction-limited resolution, as well as a greatly increased probe current for spectroscopic work. The superb fineness of the electron beams and enormous magnifications now achievable make the STEM instrument one of the most sensitive scientific instruments developed by man, and this thesis will deal with two core issues that suddenly become important in this new aberration-corrected era. With this new found sensitivity comes the risk of imaging-distortion from outside influences such as acoustic or mechanical vibrations. These can corrupt the data in an unsatisfactory manner and counter the natural interpretability of the technique. Methods to identify and diagnose this distortion will be discussed, and a new technique developed to restore the corrupted data presented. Secondly, the subtleties of probe-shape in the multi-pole corrected STEM are extensively evaluated via simulation, with the contrast-transfer capabilities across defocus explored in detail. From this investigation a new technique of STEM focal-series reconstruction (FSR) is developed to compensate for the small remnant aberrations that still persist – recovering the sample object function free from any optical distortion. In both cases the methodologies were developed into automated computer codes and example restorations from the two techniques are shown (separately, although in principal the scan-corrected output is compatible with FSR). The performance of these results has been quantified with respect to several factors including; image resolution, signal-noise ratio, sample-drift, low frequency instability, and quantitative image intensity. The techniques developed are offered as practical tools for the microscopist wishing to push the performance of their instrument just that little bit further.

This thesis deals with stock modelling using ARCH and GARCH time series. Important aspect of stock modelling is to capture volatility correctly. Volatility in finance is usually defined as a standard deviation of asset returns. Many different models, which are summarized in the first part of this thesis, are used to model volatility. This thesis focus on multivariate volatility models including multivariate GARCH models. An approach to constructing a conditional maximum likelihood estimate to these methods is given. Discussed theory is applied on real financial data. In numeric application there is a construction of a volatility estimates for two specific stocks using models described in the first part of this thesis. Using the same financial data various bivariate models are compared. Based on comparison using maximum likelihood a specific model for these stocks is recommended. Powered by TCPDF (www.tcpdf.org)

In this diploma thesis we explain the main principles and properties of bootstrap methods, that can be used to conduct the statistical inference in linear and nonlinear financial time series. We will introduce basic ideas of bootstrap methods for the case when observations can be considered as independent random variables, and afterwards we will describe more advanced methods, that can be successfully used when we are dealing with time series. Thesis deals with both parametric bootstrap methods, that we can use when the underlying parametric model of observations is available, as well as with nonparametric bootstrap methods that are used when more general nonparametric model of time series data is considered. The main objective is to compare particular bootstrap methods and show the usage of these methods on real world data. There is also a basic time series theory included in the work. 1

This thesis first describes the Lasso method and its adaptive improvement. Then the basic theoretical properties are shown and different algorithms are introduced. The main part of this thesis is application of the Lasso method to AR, MA and ARCH time series and to REGAR, REGMA and REGARCH models. An algorithm of the adaptive Lasso in a more general time series model, which includes all above mentioned models and series, is developed. The properties of methods and algorithms are shown on simulations and on a practical example. Powered by TCPDF (www.tcpdf.org)

En esta investigación se propone una metodológica alternativa a la metodología de Box y Jenkins, donde se podrá evidenciar el modelamiento de series temporales no lineales, mediante el enfoque paramétrico y el enfoque No paramétrico. En el enfoque paramétrico me inclinaré por la extensión de los métodos de Box y Jenkins, es decir, los modelos ARCH, GARCH, TGARCH entre otros, para el modelado de series temporales no lineales, en la cual obtendré los pronósticos del año 2012 para la serie temporal:  Número de peruanos retornantes según año de regreso mediante medio de transporte aéreo. En el enfoque No paramétrico presentaré el método de la red neural de retropropagación resiliente para el modelado de series temporales no lineales, en la cual obtendré los pronósticos del año 2012 para la serie temporal:  Número de peruanos retornantes según año de regreso mediante medio de transporte aéreo. La serie de tiempo estudiada para esta investigación presenta un cambio estructural durante los años del 2000-2003, lo que induce a la no linealidad de la serie. La estimación de los dos enfoques serán comparados y se elegirá el enfoque que otorgue mejores pronósticos, la cual escogeré mediante indicadores de validación como por ejemplo el MAD (Desviación Media Residual) y SSE (Suma de los Cuadrados de los Residuos). / In this research an alternative to Box and Jenkins methodology, where you can demonstrate the modeling of nonlinear time series, using parametric and nonparametric approach is proposed methodological approach. In the parametric approach, we prefer the extension of the methods of Box and Jenkins, ie ARCH, GARCH, TGARCH models among others, for modeling nonlinear time series, in which we obtain forecasts for 2012 for the series time:  Number of returnees back Peruvians by year by means of air transport. In the parametric approach not present the method of the Resilient Backpropagation Neural Network for modeling nonlinear time series, in which we obtain forecasts of 2012 to the time series:  Number of returnees back Peruvians by year by means of air transport. The time series studied for this research presents a structural change during the years of 2000-2003, which leads to the nonlinearity of the series. The estimation of the two approaches will be compared and approach that gives better predictions will be chosen, which will choose validation using indicators such as MAD (mean deviation residual) and SSE (sum of the squares of the waste)

Call number: LD2668 .T4 1957 R58 / Master of Science

The Polarizer-Sample-Analyzer (PSA) arrangement with the optical components P and A rotating with a fixed speed ratio (3:1) was originally introduced to determine nine Mueller matrix elements from Fourier analysis of the output signal of a photodetector. The arrangement is modified to the P'PSAA' arrangement where P' and A' represent fixed polarizers that are added at both ends with the speed ratio of the rotating components (P and A) remaining the same as before. After determination of the partial Mueller matrix in the ideal case, azimuthal offsets and imperfection parameters are introduced in the straight-through configuration and the imperfection parameters are determined from the Fourier coefficients. Finally, the sample is reintroduced and the full Mueller matrix elements are calculated to show the deviation from the ideal case and their dependency on the offsets and imperfection parameters.