DESARROLLO DE APLICACIONES ESTADÍSTICAS PARA LA AGRICULTURA DE PRECISIÓN. STATISTICAL APPLICATIONS FOR PRECISION AGRICULTURE

A partir de las últimas décadas se ha impulsado el desarrollo y la utilización de los Sistemas de Información Geográficos (SIG) y los Sistemas de Posicionamiento Satelital (GPS) orientados a mejorar la eficiencia productiva de distintos sistemas de cultivos extensivos en términos agronómicos, económicos y ambientales. Estas nuevas tecnologías permiten medir variabilidad espacial de propiedades del sitio como conductividad eléctrica aparente y otros atributos del terreno así como el efecto de las mismas sobre la distribución espacial de los rendimientos. Luego, es posible aplicar el manejo sitio-específico en los lotes para mejorar la eficiencia en el uso de los insumos agroquímicos, la protección del medio ambiente y la sustentabilidad de la vida rural. En la actualidad, existe una oferta amplia de recursos tecnológicos propios de la agricultura de precisión para capturar variación espacial a través de los sitios dentro del terreno. El óptimo uso del gran volumen de datos derivado de maquinarias de agricultura de precisión depende fuertemente de las capacidades para explorar la información relativa a las complejas interacciones que subyacen los resultados productivos. La covariación espacial de las propiedades del sitio y el rendimiento de los cultivos ha sido estudiada a través de modelos geoestadísticos clásicos que se basan en la teoría de variables regionalizadas. Nuevos desarrollos de modelos estadísticos contemporáneos, entre los que se destacan los modelos lineales mixtos, constituyen herramientas prometedoras para el tratamiento de datos correlacionados espacialmente. Más aún, debido a la naturaleza multivariada de las múltiples variables registradas en cada sitio, las técnicas de análisis multivariado podrían aportar valiosa información para la visualización y explotación de datos georreferenciados. La comprensión de las bases agronómicas de las complejas interacciones que se producen a la escala de lotes en producción, es hoy posible con el uso de éstas nuevas tecnologías. Los objetivos del presente proyecto son: (l) desarrollar estrategias metodológicas basadas en la complementación de técnicas de análisis multivariados y geoestadísticas, para la clasificación de sitios intralotes y el estudio de interdependencias entre variables de sitio y rendimiento; (ll) proponer modelos mixtos alternativos, basados en funciones de correlación espacial de los términos de error que permitan explorar patrones de correlación espacial de los rendimientos intralotes y las propiedades del suelo en los sitios delimitados. From the last decades the use and development of Geographical Information Systems (GIS) and Satellite Positioning Systems (GPS) is highly promoted in cropping systems. Such technologies allow measuring spatial variability of site properties including electrical conductivity and others soil features as well as their impact on the spatial variability of yields. Therefore, site-specific management could be applied to improve the efficiency in the use of agrochemicals, the environmental protection, and the sustainability of the rural life. Currently, there is a wide offer of technological resources to capture spatial variation across sites within field. However, the optimum use of data coming from the precision agriculture machineries strongly depends on the capabilities to explore the information about the complex interactions underlying the productive outputs. The covariation between spatial soil properties and yields from georeferenced data has been treated in a graphical manner or with standard geostatistical approaches. New statistical modeling capabilities from the Mixed Linear Model framework are promising to deal with correlated data such those produced by the precision agriculture. Moreover, rescuing the multivariate nature of the multiple data collected at each site, several multivariate statistical approaches could be crucial tools for data analysis with georeferenced data. Understanding the basis of complex interactions at the scale of production field is now within reach the use of these new techniques. Our main objectives are: (1) to develop new statistical strategies, based on the complementarities of geostatistics and multivariate methods, useful to classify sites within field grown with grain crops and analyze the interrelationships of several soil and yield variables, (2) to propose mixed linear models to predict yield according spatial soil variability and to build contour maps to promote a more sustainable agriculture.

Modelado multi-dominio de máquinas eléctricas. Multi-domain modeling of electric machines

El objetivo general de este proyecto es desarrollar nuevos modelos multi-dominio de máquinas eléctricas para aplicaciones al control y al diagnóstico de fallas. Se propone comenzar con el modelo electromagnético del motor de inducción en base a circuitos magnéticos equivalentes (MEC) validándolo por medio de simulación y de resultados experimentales. Como segundo paso se pretende desarrollas modelos térmicos y mecánicos con el objetivo que puedan ser acoplados al modelo electromagnético y de esta estudiar la interacción de los dominios y se validará mediante resultados de simulación y experimentales el modelo completo. Finalmente se pretende utilizar el modelo multi-dominio como una herramienta para la prueba de nuevas estrategias de control y diagnóstico de fallas. The main objective of this project is the development of new multi-domain models of electric machines for control and fault diagnosis applications. The electromagnetic modeling of the induction motor (IM) will be done using the magnetic equivalent circuits approach. This model will be validated by simulation and by experimental results. As a second step of this project, new mechanical and thermal models for the IM will be developed, with the objective of coupling these models with the electromagnetic one. With this multi-domain model it will be possible to study the interaction between each others. After that, the complete model will be validated by simulation and experimental results. Finally, the model will be used as a tool for testing new control and fault diagnosis strategies.

Defining habitat characteristics influencing the distribution, density and growth of Plaice (Pleuronectes Platessa) and Dab (Limanda Limanda) on west of Ireland nursery grounds

Plaice (Pleuronectes platessa, L.) and dab (Limanda limanda, L.) are among the most abundant flatfishes in the north-eastern Atlantic region and the dominant species in shallow coastal nursery grounds. With increasing pressures on commercial flatfish stocks in combination with changing coastal environments, better knowledge of population dynamics during all life stages is needed to evaluate variability in year-class strength and recruitment to the fishery. The aim of this research was to investigate the complex interplay of biotic and abiotic habitat components influencing the distribution, density and growth of plaice and dab during the vulnerable juvenile life stage and to gain insight in spatial and temporal differences in nursery habitat quality along the west coast of Ireland. Intraspecific variability in plaice diet was observed at different spatial scales and showed a link with condition, recent growth and morphology. This highlights the effect of food availability on habitat quality and the need to consider small scale variation when attempting to link habitat quality to feeding, growth and condition of juvenile flatfish. There was evidence of trophic, spatial and temporal resource partitioning between juvenile plaice and dab allowing the co-existence of morphologically similar species in nursery grounds. In the limited survey years there was no evidence that the carrying capacity of the studied nursery grounds was reached but spatial and interannual variations in fish growth indicated fluctuating environments in terms of food availability, predator densities, sediment features and physico-chemical conditions. Predation was the most important factor affecting habitat quality for juvenile plaice and dab with crab densities negatively correlated to fish condition whereas shrimp densities were negatively associated with densities of small-sized juveniles in spring. A comparison of proxies for fish growth showed the advantage of Fulton’s K for routine use whereas RNA:DNA ratios proved less powerful when short-term environmental fluctuations are lacking. This study illustrated how distinct sets of habitat features can drive spatial variation in density and condition of juvenile flatfish highlighting the value of studying both variables when modeling habitat requirements. The habitat models generated in this study also provide a powerful tool to predict potential climate and anthropogenic impacts on the distribution and condition of juveniles in flatfish nurseries. The need for effective coastal zone management was emphasized to ensure a sustainable use of coastal resources and successful flatfish recruitment to the fishery.

Isothermal drying of pore networks : influence of pore structure on drying kinetics

Drying of porous media, pore network, pore structure, capillary forces, viscous forces, drying kinetics

Influence of pore size distribution on drying behaviour of porous media by a continuous model

Bundle of capillaries, drying kinetics, continuous model, relative permeability, capillary pressure, control volume method

Modeling, design, and optimization of radiofrequency micromechanical structures

Coupled Electromechanical Analysis, MEMS Modeling, MEMS, RF MEMS Switches, Defected Ground Structures, Reconfigurable Resonator

Modeling and simulation of population balances for particulate processes

This work focuses on the modeling and numerical approximations of population balance equations (PBEs) for the simulation of different phenomena occurring in process engineering. The population balance equation (PBE) is considered to be a statement of continuity. It tracks the change in particle size distribution as particles are born, die, grow or leave a given control volume. In the population balance models the one independent variable represents the time, the other(s) are property coordinate(s), e.g., the particle volume (size) in the present case. They typically describe the temporal evolution of the number density functions and have been used to model various processes such as granulation, crystallization, polymerization, emulsion and cell dynamics. The semi-discrete high resolution schemes are proposed for solving PBEs modeling one and two-dimensional batch crystallization models. The schemes are discrete in property coordinates but continuous in time. The resulting ordinary differential equations can be solved by any standard ODE solver. To improve the numerical accuracy of the schemes a moving mesh technique is introduced in both one and two-dimensional cases ...

Time- and frequency-domain modeling of passive interconncection structured in field and circuit analysis

PEEC, computational electromagnetics

Robust acoustic and semantic modeling in a telephone-based spoken dialog system

Magdeburg, Univ., Fak. für Elektrotechnik und Informationstechnik, Diss., 2009

Modulation of the activity of the mitochondrial BK-channel and the permeability transition pore by hypoxia and apoptotic factors

Magdeburg, Univ., Fak. für Naturwiss., Diss., 2010

Design, modeling and fabrication of radio-frequency microelectromechanical switches and coplanar filters

Magdeburg, Univ., Fak. für Elektrotechnik und Informationstechnik, Diss., 2010

Modeling of polythermal preferential crystallization

Magdeburg, Univ., Fak. für Verfahrens- und Systemtechnik, Diss., 2010

Modeling, evaluation and predicting of IT human resources performance

Magdeburg, Univ., Fak. für Informatik, Diss., 2012

Development of methodology for treating pressure waves from explosions accounting for modeling and data uncertainties

Magdeburg, Univ., Fak. für Verfahrens- und Systemtechnik, Diss., 2012

Modeling the AppA/PpsR signal transduction system of rhodobacter sphaeroides

Magdeburg, Univ., Fak. für Naturwiss., Diss., 2012