Combination of optical and on-destructivemechanicaltechniques for the measurement of maturity in peach

Increasing consumer dissatisfaction related with lack of ripeness in peach has been repeatedly reported since 1990 to the present day. There is thus, a great interest in improving the assessment of peach maturity, currently based on Magness Taylor firmness (destructive, highly variable, and time consuming) and colour (not reliable for highly coloured varieties). The present research studies as an alternative several non-destructive (ND) measurements, based on multispectral imaging, visible spectra, and low mass impact response. Their relationship with maturity, as well as the potential of their combination was studied. As a result, two rather independent (R2 = 0.3) groups of non-destructive measurements, chlorophyll related optical indexes and low mass impact (LMI) measurements, were identified. Optical measurements showed the best behaviour for assessing maturity at harvest, while LMI measurements reflected handling incidences, showing a promising potential to be used to control transport and postharvest handling.

Series combination of a switched dc-dc converter and a linear regulator for high frequency RF envelope amplifier

Classical linear amplifiers such as A, AB and B offer very good linearity suitable for RF power amplifiers. However, its inherent low efficiency limits its use especially in base-stations that manage tens or hundreds of Watts. The use of linearization techniques such as Envelope Elimination and Restoration (EER) allow an increase of efficiency keeping good linearity. This technique requires a very fast dc-dc power converter to provide variable voltage supply to the power amplifier. In this paper, several alternatives are analyzed to implement the envelope amplifier based on a cascade association of a switched dc-dc converter and a linear regulator. A simplified version of this approach is also suitable to operate with Envelope Tracking technique.

PSO and neural networks: Optimal combination to solve non linear complex problems

Swarm colonies reproduce social habits. Working together in a group to reach a predefined goal is a social behaviour occurring in nature. Linear optimization problems have been approached by different techniques based on natural models. In particular, Particles Swarm optimization is a meta-heuristic search technique that has proven to be effective when dealing with complex optimization problems. This paper presents and develops a new method based on different penalties strategies to solve complex problems. It focuses on the training process of the neural networks, the constraints and the election of the parameters to ensure successful results and to avoid the most common obstacles when searching optimal solutions.

Environmental variables modeling based on remote sensing data using time series analysis: forestry and agricultural applications

En la actualidad, el seguimiento de la dinámica de los procesos medio ambientales está considerado como un punto de gran interés en el campo medioambiental. La cobertura espacio temporal de los datos de teledetección proporciona información continua con una alta frecuencia temporal, permitiendo el análisis de la evolución de los ecosistemas desde diferentes escalas espacio-temporales. Aunque el valor de la teledetección ha sido ampliamente probado, en la actualidad solo existe un número reducido de metodologías que permiten su análisis de una forma cuantitativa. En la presente tesis se propone un esquema de trabajo para explotar las series temporales de datos de teledetección, basado en la combinación del análisis estadístico de series de tiempo y la fenometría. El objetivo principal es demostrar el uso de las series temporales de datos de teledetección para analizar la dinámica de variables medio ambientales de una forma cuantitativa. Los objetivos específicos son: (1) evaluar dichas variables medio ambientales y (2) desarrollar modelos empíricos para predecir su comportamiento futuro. Estos objetivos se materializan en cuatro aplicaciones cuyos objetivos específicos son: (1) evaluar y cartografiar estados fenológicos del cultivo del algodón mediante análisis espectral y fenometría, (2) evaluar y modelizar la estacionalidad de incendios forestales en dos regiones bioclimáticas mediante modelos dinámicos, (3) predecir el riesgo de incendios forestales a nivel pixel utilizando modelos dinámicos y (4) evaluar el funcionamiento de la vegetación en base a la autocorrelación temporal y la fenometría. Los resultados de esta tesis muestran la utilidad del ajuste de funciones para modelizar los índices espectrales AS1 y AS2. Los parámetros fenológicos derivados del ajuste de funciones permiten la identificación de distintos estados fenológicos del cultivo del algodón. El análisis espectral ha demostrado, de una forma cuantitativa, la presencia de un ciclo en el índice AS2 y de dos ciclos en el AS1 así como el comportamiento unimodal y bimodal de la estacionalidad de incendios en las regiones mediterránea y templada respectivamente. Modelos autorregresivos han sido utilizados para caracterizar la dinámica de la estacionalidad de incendios y para predecir de una forma muy precisa el riesgo de incendios forestales a nivel pixel. Ha sido demostrada la utilidad de la autocorrelación temporal para definir y caracterizar el funcionamiento de la vegetación a nivel pixel. Finalmente el concepto “Optical Functional Type” ha sido definido, donde se propone que los pixeles deberían ser considerados como unidades temporales y analizados en función de su dinámica temporal. ix SUMMARY A good understanding of land surface processes is considered as a key subject in environmental sciences. The spatial-temporal coverage of remote sensing data provides continuous observations with a high temporal frequency allowing the assessment of ecosystem evolution at different temporal and spatial scales. Although the value of remote sensing time series has been firmly proved, only few time series methods have been developed for analyzing this data in a quantitative and continuous manner. In the present dissertation a working framework to exploit Remote Sensing time series is proposed based on the combination of Time Series Analysis and phenometric approach. The main goal is to demonstrate the use of remote sensing time series to analyze quantitatively environmental variable dynamics. The specific objectives are (1) to assess environmental variables based on remote sensing time series and (2) to develop empirical models to forecast environmental variables. These objectives have been achieved in four applications which specific objectives are (1) assessing and mapping cotton crop phenological stages using spectral and phenometric analyses, (2) assessing and modeling fire seasonality in two different ecoregions by dynamic models, (3) forecasting forest fire risk on a pixel basis by dynamic models, and (4) assessing vegetation functioning based on temporal autocorrelation and phenometric analysis. The results of this dissertation show the usefulness of function fitting procedures to model AS1 and AS2. Phenometrics derived from function fitting procedure makes it possible to identify cotton crop phenological stages. Spectral analysis has demonstrated quantitatively the presence of one cycle in AS2 and two in AS1 and the unimodal and bimodal behaviour of fire seasonality in the Mediterranean and temperate ecoregions respectively. Autoregressive models has been used to characterize the dynamics of fire seasonality in two ecoregions and to forecasts accurately fire risk on a pixel basis. The usefulness of temporal autocorrelation to define and characterized land surface functioning has been demonstrated. And finally the “Optical Functional Types” concept has been proposed, in this approach pixels could be as temporal unities based on its temporal dynamics or functioning.

The Optimal combination: Grammatical Swarm, Particle Swarm Optimization and Neural Networks.

Social behaviour is mainly based on swarm colonies, in which each individual shares its knowledge about the environment with other individuals to get optimal solutions. Such co-operative model differs from competitive models in the way that individuals die and are born by combining information of alive ones. This paper presents the particle swarm optimization with differential evolution algorithm in order to train a neural network instead the classic back propagation algorithm. The performance of a neural network for particular problems is critically dependant on the choice of the processing elements, the net architecture and the learning algorithm. This work is focused in the development of methods for the evolutionary design of artificial neural networks. This paper focuses in optimizing the topology and structure of connectivity for these networks.

Brain structural and functional recovery following initiation of combination antiretroviral therapy

NeuroAIDS persists in the era of combination antiretroviral therapies. We describe here the recovery of brain structure and function following 6 months of therapy in a treatment-naive patient presenting with HIV-associated dementia. The patient’s neuropsychological test performance improved and his total brain volume increased by more than 5 %. Neuronal functional connectivity measured by magnetoencephalography changed from a pattern identical to that observed in other HIV-infected individuals to one that was indistinguishable from that of uninfected control subjects. These data suggest that at least some of the effects of HIV on the brain can be fully reversed with treatment.

The history of technology in education. A comparative study and forecast

Area, launched in 1999 with the Bologna Declaration, has bestowed such a magnitude and unprecedented agility to the transformation process undertaken by European universities. However, the change has been more profound and drastic with regards to the use of new technologies both inside and outside the classroom. This article focuses on the study and analysis of the technology’s history within the university education and its impact on teachers, students and teaching methods. All the elements that have been significant and innovative throughout the history inside the teaching process have been analyzed, from the use of blackboard and chalk during lectures, the use of slide projectors and transparent slides, to the use of electronic whiteboards and Internet nowadays. The study is complemented with two types of surveys that have been performed among teachers and students during the school years 1999 - 2011 in the School of Civil Engineering at the Polytechnic University of Madrid. The pros and cons of each of the techniques and methodologies used in the learning process over the last decades are described, unfolding how they have affected the teacher, who has evolved from writing on a whiteboard to project onto a screen, the student, who has evolved from taking handwritten notes to download information or search the Internet, and the educational process, that has evolved from the lecture to acollaborative learning and project-based learning. It is unknown how the process of learning will evolve in the future, but we do know the consequences that some of the multimedia technologies are having on teachers, students and the learning process. It is our goal as teachers to keep ourselves up to date, in order to offer the student adequate technical content, while providing proper motivation through the use of new technologies. The study provides a forecast in the evolution of multimedia within the classroom and the renewal of the education process, which in our view, will set the basis for future learning process within the context of this new interactive era.

Economics and forecast of energy consumption in NGN networks: the case of Spain

Reducing energy consumption is one of the main goals of sustainability planning in most countries. For instance in Europe, the EC established the objectives in the Communication “20 20 by 2020 Europe's climate change opportunity”.

Energy Consumption Forecast in 4G Networks: The Case of Spain

Reducing energy consumption is one of the main goals of sustainability planning in most countries. For instance in Europe, the EC established the objectives in the Communication “20 20 by 2020 Europe's climate change opportunity”. • Next Generation Networks (NGN)  One of the most relevant upcoming ICT development • The role of energy consumption seems mostly absent from the main analysis and the debate on NGN deployment.

Contribution to energy consumption modelling and forecast in next generation access networks

La contribución del sector de las tecnologías de la información y las comunicaciones (TICs) al consumo de energía a nivel global se ha visto incrementada considerablemente en la última década al mismo tiempo que su relevancia dentro de la economía global. Se prevé que esta tendencia continúe debido al uso cada vez más intensivo de estas tecnologías. Una de las principales causas es el tráfico de datos de banda ancha generado por el uso de las redes de telecomunicaciones. De hecho como respuesta a esta demanda de recursos por parte de los usuarios, de la industria de las telecomunicaciones está iniciando el despliegue de las redes de nueva generación. En cualquier caso, el consumo de energía es un factor generalmente ausente del debate sobre el despliegue de estas tecnologías, a pesar de la posible repercusión que pueda llegar a tener en los costes y la sostenibilidad de estos proyectos. A lo largo de este trabajo se desarrollan modelos para evaluar el consumo energético de las redes de acceso de nueva generación (NGAN). Estos servirán tanto para llevar a cabo cálculos en un escenario global estático, como en cualquiera otro que determine la potencial evolución de la red de acceso a lo largo de su despliegue. Estos modelos combinan tres factores: la penetración prospectiva de cada una de las tecnologías de banda ancha analizadas, el tráfico generado por usuario y su futura evolución, y el perfil de consumo de energía de cada uno de los dispositivos de red desplegados. Tras evaluar los resultados derivados de la aplicación de los modelos en el caso demográfico específico de España, se obtienen conclusiones acerca de las diferencias tecnológicas en cuanto al consumo energético, sus implicaciones económicas, y la sensibilidad de los cálculos atendiendo a posibles modificaciones en los valores de referencia de diferentes parámetros de diseño. Se destaca por tanto el efecto en el consumo energético de los desarrollos tecnológicos, tecno-económicos, y de las decisiones en el ámbito regulatorio. Aunque como se ha dicho, se ha ejemplificado el cálculo para un caso particular, tanto los modelos como las conclusiones extraídas se pueden extrapolar a otros países similares.

Phytostabilization of metals in mine soils using Brassica juncea in combination with organic amendments

Background and aims The high metal bioavailability and the poor conditions of mine soils yield a low plant biomass, limiting the application of phytoremediation techniques. A greenhouse experiment was performed to evaluate the effects of organic amendments on metal stabilization and the potential of Brassica juncea L. for phytostabilization in mine soils. Methods Plants were grown in pots filled with soils collected from two mine sites located in Central Spain mixed with 0, 30 and 60 tha?1 of pine bark compost and horse- and sheep-manure compost. Plant biomass and metal concentrations in roots and shoots were measured. Metal bioavailability was assessed using a rhizosphere-based method (rhizo), which consists of a mixture of low-molecular-weight organic acids to simulate root exudates. Results Manure reduced metal concentrations in shoots (10?50 % reduction of Cu and 40?80 % of Zn in comparison with non-amended soils), bioconcentration factor (10?50 % of Cu and 40?80 % of Zn) and metal bioavailability in soil (40?50 % of Cu and 10?30 % of Zn) due to the high pH and the contribution of organic matter. Manure improved soil fertility and was also able to increase plant biomass (5?20 times in shoots and 3?30 times in roots), which resulted in a greater amount of metals removed from soil and accumulated in roots (increase of 2?7 times of Cu and Zn). Plants grown in pine bark treatments and in non-amended soils showed a limited biomass and high metal concentrations in shoots. Conclusions The addition of manure could be effective for the stabilization of metals and for enhancing the phytostabilization ability of B. juncea in mine soils. In this study, this species resulted to be a potential candidate for phytostabilization in combination with manure, differing from previous results, in which B. juncea had been recognized as a phytoextraction plant.

Estrategia de desarrollo de negocio para el producto Atos RTTF (Real Time Traffic Forecast)

El objetivo del presente proyecto de fin de máster es desplegar la estrategia de negocio completa, desde las declaraciones y premisas hasta la implantación y ejecución, para una solución novedosa de la compañía AtoS. Esta solución se denomina RTTF (Real Time Traffic Forecast), y sus objetivos principales, a alto nivel, son los siguientes: a) Conseguir unas mejores ciudades en la que vivir y trabajar. b) Realizar una gestión de tráfico proactiva para un uso de recursos de las ciudades optimizado. Nuestro planteamiento en este trabajo es, basado en las el módulo de estrategia del máster, diseñar un plan de negocio para desarrollar y potenciar la anterior solución. Para ello también necesitaremos herramientas de otros módulos del máster, como el de marketing, operaciones, o finanzas. Para ello, comenzaremos analizando el entorno desde el punto de vista de la posible receptividad al producto, así como de los posibles competidores, con objeto de posicionar de manera inicial nuestra solución, y reflexionar sobre si ese posicionamiento es el adecuado. Añadiendo también el estudio interno de la compañía y de la propia solución sobre la que versa el proyecto. El principal entregable del presente trabajo será un plan de negocio, con fechas, objetivos y un listado de clientes por orden de prioridad, con el objetivo final de desarrollar la solución.

PV power forecast using a nonparametric PV model

Forecasting the AC power output of a PV plant accurately is important both for plant owners and electric system operators. Two main categories of PV modeling are available: the parametric and the nonparametric. In this paper, a methodology using a nonparametric PV model is proposed, using as inputs several forecasts of meteorological variables from a Numerical Weather Forecast model, and actual AC power measurements of PV plants. The methodology was built upon the R environment and uses Quantile Regression Forests as machine learning tool to forecast AC power with a confidence interval. Real data from five PV plants was used to validate the methodology, and results show that daily production is predicted with an absolute cvMBE lower than 1.3%.

Advanced background modeling with RGB-D sensors through classifiers combination and inter-frame foreground prediction

An innovative background modeling technique that is able to accurately segment foreground regions in RGB-D imagery (RGB plus depth) has been presented in this paper. The technique is based on a Bayesian framework that efficiently fuses different sources of information to segment the foreground. In particular, the final segmentation is obtained by considering a prediction of the foreground regions, carried out by a novel Bayesian Network with a depth-based dynamic model, and, by considering two independent depth and color-based mixture of Gaussians background models. The efficient Bayesian combination of all these data reduces the noise and uncertainties introduced by the color and depth features and the corresponding models. As a result, more compact segmentations, and refined foreground object silhouettes are obtained. Experimental results with different databases suggest that the proposed technique outperforms existing state-of-the-art algorithms.

Scalable UWB photonic generator based on the combination of doublet pulses

We propose and experimentally demonstrate a scalable and reconfigurable optical scheme to generate high order UWB pulses. Firstly, various ultra wideband doublets are created through a process of phase-tointensity conversion by means of a phase modulation and a dispersive media. In a second stage, doublets are combined in an optical processing unit that allows the reconfiguration of UWB high order pulses. Experimental results both in time and frequency domains are presented showing good performance related to the fractional bandwidth and spectral efficiency parameters.