Observation and Detection of Underground Cellars in the Duero Basin By GNSS, Lidar and Ground Penetrating Radar Techniques

The underground cellars that appear in different parts of Spain are part of an agricultural landscape dispersed, sometimes damaged, others at risk of disappearing. This paper studies the measurement and display of a group of wineries located in Atauta (Soria), in the Duero River corridor. It is a unique architectural complex, facing rising, built on a smooth hillock as shown in Fig. 1. These constructions are excavated in the ground. The access to the cave or underground cellar has a shape of a narrow tube or down gallery. Immediately after, this space gets wider. There, wine is produced and stored [1]. Observation and detection of the underground cellar, both on the outside and underground, it is essential to make an inventory of the rural patrimony [2]. The geodetection is a noninvasive technique, adequate to accurately locate buried structures in the ground. Works undertaken include topographic work with the LIDAR techniques and integration with data obtained by GNSS and GPR.

Efficient algorithms for dynamic probabilistic safety assessment. An application to convex damage domain.

The design of nuclear power plant has to follow a number of regulations aimed at limiting the risks inherent in this type of installation. The goal is to prevent and to limit the consequences of any possible incident that might threaten the public or the environment. To verify that the safety requirements are met a safety assessment process is followed. Safety analysis is as key component of a safety assessment, which incorporates both probabilistic and deterministic approaches. The deterministic approach attempts to ensure that the various situations, and in particular accidents, that are considered to be plausible, have been taken into account, and that the monitoring systems and engineered safety and safeguard systems will be capable of ensuring the safety goals. On the other hand, probabilistic safety analysis tries to demonstrate that the safety requirements are met for potential accidents both within and beyond the design basis, thus identifying vulnerabilities not necessarily accessible through deterministic safety analysis alone. Probabilistic safety assessment (PSA) methodology is widely used in the nuclear industry and is especially effective in comprehensive assessment of the measures needed to prevent accidents with small probability but severe consequences. Still, the trend towards a risk informed regulation (RIR) demanded a more extended use of risk assessment techniques with a significant need to further extend PSA’s scope and quality. Here is where the theory of stimulated dynamics (TSD) intervenes, as it is the mathematical foundation of the integrated safety assessment (ISA) methodology developed by the CSN(Consejo de Seguridad Nuclear) branch of Modelling and Simulation (MOSI). Such methodology attempts to extend classical PSA including accident dynamic analysis, an assessment of the damage associated to the transients and a computation of the damage frequency. The application of this ISA methodology requires a computational framework called SCAIS (Simulation Code System for Integrated Safety Assessment). SCAIS provides accident dynamic analysis support through simulation of nuclear accident sequences and operating procedures. Furthermore, it includes probabilistic quantification of fault trees and sequences; and integration and statistic treatment of risk metrics. SCAIS comprehensively implies an intensive use of code coupling techniques to join typical thermal hydraulic analysis, severe accident and probability calculation codes. The integration of accident simulation in the risk assessment process and thus requiring the use of complex nuclear plant models is what makes it so powerful, yet at the cost of an enormous increase in complexity. As the complexity of the process is primarily focused on such accident simulation codes, the question of whether it is possible to reduce the number of required simulation arises, which will be the focus of the present work. This document presents the work done on the investigation of more efficient techniques applied to the process of risk assessment inside the mentioned ISA methodology. Therefore such techniques will have the primary goal of decreasing the number of simulation needed for an adequate estimation of the damage probability. As the methodology and tools are relatively recent, there is not much work done inside this line of investigation, making it a quite difficult but necessary task, and because of time limitations the scope of the work had to be reduced. Therefore, some assumptions were made to work in simplified scenarios best suited for an initial approximation to the problem. The following section tries to explain in detail the process followed to design and test the developed techniques. Then, the next section introduces the general concepts and formulae of the TSD theory which are at the core of the risk assessment process. Afterwards a description of the simulation framework requirements and design is given. Followed by an introduction to the developed techniques, giving full detail of its mathematical background and its procedures. Later, the test case used is described and result from the application of the techniques is shown. Finally the conclusions are presented and future lines of work are exposed.

Systematic Approach for the selection of monitoring technologies in CO2 geological storage projects. Application of multicriteria decision making

Geologic storage of carbon dioxide (CO2) has been proposed as a viable means for reducing anthropogenic CO2 emissions. Once injection begins, a program for measurement, monitoring, and verification (MMV) of CO2 distribution is required in order to: a) research key features, effects and processes needed for risk assessment; b) manage the injection process; c) delineate and identify leakage risk and surface escape; d) provide early warnings of failure near the reservoir; and f) verify storage for accounting and crediting. The selection of the methodology of monitoring (characterization of site and control and verification in the post-injection phase) is influenced by economic and technological variables. Multiple Criteria Decision Making (MCDM) refers to a methodology developed for making decisions in the presence of multiple criteria. MCDM as a discipline has only a relatively short history of 40 years, and it has been closely related to advancements on computer technology. Evaluation methods and multicriteria decisions include the selection of a set of feasible alternatives, the simultaneous optimization of several objective functions, and a decision-making process and evaluation procedures that must be rational and consistent. The application of a mathematical model of decision-making will help to find the best solution, establishing the mechanisms to facilitate the management of information generated by number of disciplines of knowledge. Those problems in which decision alternatives are finite are called Discrete Multicriteria Decision problems. Such problems are most common in reality and this case scenario will be applied in solving the problem of site selection for storing CO2. Discrete MCDM is used to assess and decide on issues that by nature or design support a finite number of alternative solutions. Recently, Multicriteria Decision Analysis has been applied to hierarchy policy incentives for CCS, to assess the role of CCS, and to select potential areas which could be suitable to store. For those reasons, MCDM have been considered in the monitoring phase of CO2 storage, in order to select suitable technologies which could be techno-economical viable. In this paper, we identify techniques of gas measurements in subsurface which are currently applying in the phase of characterization (pre-injection); MCDM will help decision-makers to hierarchy the most suitable technique which fit the purpose to monitor the specific physic-chemical parameter.

Damage detection by using FBGs and strain field pattern recognition techniques

A novel methodology for damage detection and location in structures is proposed. The methodology is based on strain measurements and consists in the development of strain field pattern recognition techniques. The aforementioned are based on PCA (principal component analysis) and damage indices (T 2 and Q). We propose the use of fiber Bragg gratings (FBGs) as strain sensors

Dynamic Response Optimization of Vehicles through Efficient Multibody Formulations and Automatic Differentiation Techniques

El diseño y desarrollo de sistemas de suspensión para vehículos se basa cada día más en el diseño por ordenador y en herramientas de análisis por ordenador, las cuales permiten anticipar problemas y resolverlos por adelantado. El comportamiento y las características dinámicas se calculan con precisión, bajo coste, y recursos y tiempos de cálculo reducidos. Sin embargo, existe una componente iterativa en el proceso, que requiere la definición manual de diseños a través de técnicas “prueba y error”. Esta Tesis da un paso hacia el desarrollo de un entorno de simulación eficiente capaz de simular, analizar y evaluar diseños de suspensiones vehiculares, y de mejorarlos hacia la solución optima mediante la modificación de los parámetros de diseño. La modelización mediante sistemas multicuerpo se utiliza aquí para desarrollar un modelo de autocar con 18 grados de libertad, de manera detallada y eficiente. La geometría y demás características de la suspensión se ajustan a las del vehículo real, así como los demás parámetros del modelo. Para simular la dinámica vehicular, se utiliza una formulación multicuerpo moderna y eficiente basada en las ecuaciones de Maggi, a la que se ha incorporado un visor 3D. Así, se consigue simular maniobras vehiculares en tiempos inferiores al tiempo real. Una vez que la dinámica está disponible, los análisis de sensibilidad son cruciales para una optimización robusta y eficiente. Para ello, se presenta una técnica matemática que permite derivar las variables dinámicas dentro de la formulación, de forma algorítmica, general, con la precisión de la maquina, y razonablemente eficiente: la diferenciación automática. Este método propaga las derivadas con respecto a las variables de diseño a través del código informático y con poca intervención del usuario. En contraste con otros enfoques en la bibliografía, generalmente particulares y limitados, se realiza una comparación de librerías, se desarrolla una formulación híbrida directa-automática para el cálculo de sensibilidades, y se presentan varios ejemplos reales. Finalmente, se lleva a cabo la optimización de la respuesta dinámica del vehículo citado. Se analizan cuatro tipos distintos de optimización: identificación de parámetros, optimización de la maniobrabilidad, optimización del confort y optimización multi-objetivo, todos ellos aplicados al diseño del autocar. Además de resultados analíticos y gráficos, se incluyen algunas consideraciones acerca de la eficiencia. En resumen, se mejora el comportamiento dinámico de vehículos por medio de modelos multicuerpo y de técnicas de diferenciación automática y optimización avanzadas, posibilitando un ajuste automático, preciso y eficiente de los parámetros de diseño. ABSTRACT Each day, the design and development of vehicle suspension systems relies more on computer-aided design and computer-aided engineering tools, which allow anticipating the problems and solving them ahead of time. Dynamic behavior and characteristics are thus simulated accurately and inexpensively with moderate computational times and resources. There is, however, an iterative component in the process, which involves the manual definition of designs in a trialand-error manner. This Thesis takes a step towards the development of an efficient simulation framework capable of simulating, analyzing and evaluating vehicle suspension designs, and automatically improving them by varying the design parameters towards the optimal solution. The multibody systems approach is hereby used to model a three-dimensional 18-degrees-of-freedom coach in a comprehensive yet efficient way. The suspension geometry and characteristics resemble the ones from the real vehicle, as do the rest of vehicle parameters. In order to simulate vehicle dynamics, an efficient, state-of-the-art multibody formulation based on Maggi’s equations is employed, and a three-dimensional graphics viewer is developed. As a result, vehicle maneuvers can be simulated faster than real-time. Once the dynamics are ready, a sensitivity analysis is crucial for a robust optimization. To that end, a mathematical technique is introduced, which allows differentiating the dynamic variables within the multibody formulation in a general, algorithmic, accurate to machine precision, and reasonably efficient way: automatic differentiation. This method propagates the derivatives with respect to the design parameters throughout the computer code, with little user interaction. In contrast with other attempts in the literature, mostly not generalpurpose, a benchmarking of libraries is carried out, a hybrid direct-automatic differentiation approach for the computation of sensitivities is developed, and several real-life examples are analyzed. Finally, a design optimization process of the aforementioned vehicle is carried out. Four different types of dynamic response optimization are presented: parameter identification, handling optimization, ride comfort optimization and multi-objective optimization; all of which are applied to the design of the coach example. Together with analytical and visual proof of the results, efficiency considerations are made. In summary, the dynamic behavior of vehicles is improved by using the multibody systems approach, along with advanced differentiation and optimization techniques, enabling an automatic, accurate and efficient tuning of design parameters.

Functional and effective connectivity in MEG. Application to the study of epilepsy

Nuestro cerebro contiene cerca de 1014 sinapsis neuronales. Esta enorme cantidad de conexiones proporciona un entorno ideal donde distintos grupos de neuronas se sincronizan transitoriamente para provocar la aparición de funciones cognitivas, como la percepción, el aprendizaje o el pensamiento. Comprender la organización de esta compleja red cerebral en base a datos neurofisiológicos, representa uno de los desafíos más importantes y emocionantes en el campo de la neurociencia. Se han propuesto recientemente varias medidas para evaluar cómo se comunican las diferentes partes del cerebro a diversas escalas (células individuales, columnas corticales, o áreas cerebrales). Podemos clasificarlos, según su simetría, en dos grupos: por una parte, la medidas simétricas, como la correlación, la coherencia o la sincronización de fase, que evalúan la conectividad funcional (FC); mientras que las medidas asimétricas, como la causalidad de Granger o transferencia de entropía, son capaces de detectar la dirección de la interacción, lo que denominamos conectividad efectiva (EC). En la neurociencia moderna ha aumentado el interés por el estudio de las redes funcionales cerebrales, en gran medida debido a la aparición de estos nuevos algoritmos que permiten analizar la interdependencia entre señales temporales, además de la emergente teoría de redes complejas y la introducción de técnicas novedosas, como la magnetoencefalografía (MEG), para registrar datos neurofisiológicos con gran resolución. Sin embargo, nos hallamos ante un campo novedoso que presenta aun varias cuestiones metodológicas sin resolver, algunas de las cuales trataran de abordarse en esta tesis. En primer lugar, el creciente número de aproximaciones para determinar la existencia de FC/EC entre dos o más señales temporales, junto con la complejidad matemática de las herramientas de análisis, hacen deseable organizarlas todas en un paquete software intuitivo y fácil de usar. Aquí presento HERMES (http://hermes.ctb.upm.es), una toolbox en MatlabR, diseñada precisamente con este fin. Creo que esta herramienta será de gran ayuda para todos aquellos investigadores que trabajen en el campo emergente del análisis de conectividad cerebral y supondrá un gran valor para la comunidad científica. La segunda cuestión practica que se aborda es el estudio de la sensibilidad a las fuentes cerebrales profundas a través de dos tipos de sensores MEG: gradiómetros planares y magnetómetros, esta aproximación además se combina con un enfoque metodológico, utilizando dos índices de sincronización de fase: phase locking value (PLV) y phase lag index (PLI), este ultimo menos sensible a efecto la conducción volumen. Por lo tanto, se compara su comportamiento al estudiar las redes cerebrales, obteniendo que magnetómetros y PLV presentan, respectivamente, redes más densamente conectadas que gradiómetros planares y PLI, por los valores artificiales que crea el problema de la conducción de volumen. Sin embargo, cuando se trata de caracterizar redes epilépticas, el PLV ofrece mejores resultados, debido a la gran dispersión de las redes obtenidas con PLI. El análisis de redes complejas ha proporcionado nuevos conceptos que mejoran caracterización de la interacción de sistemas dinámicos. Se considera que una red está compuesta por nodos, que simbolizan sistemas, cuyas interacciones se representan por enlaces, y su comportamiento y topología puede caracterizarse por un elevado número de medidas. Existe evidencia teórica y empírica de que muchas de ellas están fuertemente correlacionadas entre sí. Por lo tanto, se ha conseguido seleccionar un pequeño grupo que caracteriza eficazmente estas redes, y condensa la información redundante. Para el análisis de redes funcionales, la selección de un umbral adecuado para decidir si un determinado valor de conectividad de la matriz de FC es significativo y debe ser incluido para un análisis posterior, se convierte en un paso crucial. En esta tesis, se han obtenido resultados más precisos al utilizar un test de subrogadas, basado en los datos, para evaluar individualmente cada uno de los enlaces, que al establecer a priori un umbral fijo para la densidad de conexiones. Finalmente, todas estas cuestiones se han aplicado al estudio de la epilepsia, caso práctico en el que se analizan las redes funcionales MEG, en estado de reposo, de dos grupos de pacientes epilépticos (generalizada idiopática y focal frontal) en comparación con sujetos control sanos. La epilepsia es uno de los trastornos neurológicos más comunes, con más de 55 millones de afectados en el mundo. Esta enfermedad se caracteriza por la predisposición a generar ataques epilépticos de actividad neuronal anormal y excesiva o bien síncrona, y por tanto, es el escenario perfecto para este tipo de análisis al tiempo que presenta un gran interés tanto desde el punto de vista clínico como de investigación. Los resultados manifiestan alteraciones especificas en la conectividad y un cambio en la topología de las redes en cerebros epilépticos, desplazando la importancia del ‘foco’ a la ‘red’, enfoque que va adquiriendo relevancia en las investigaciones recientes sobre epilepsia. ABSTRACT There are about 1014 neuronal synapses in the human brain. This huge number of connections provides the substrate for neuronal ensembles to become transiently synchronized, producing the emergence of cognitive functions such as perception, learning or thinking. Understanding the complex brain network organization on the basis of neuroimaging data represents one of the most important and exciting challenges for systems neuroscience. Several measures have been recently proposed to evaluate at various scales (single cells, cortical columns, or brain areas) how the different parts of the brain communicate. We can classify them, according to their symmetry, into two groups: symmetric measures, such as correlation, coherence or phase synchronization indexes, evaluate functional connectivity (FC); and on the other hand, the asymmetric ones, such as Granger causality or transfer entropy, are able to detect effective connectivity (EC) revealing the direction of the interaction. In modern neurosciences, the interest in functional brain networks has increased strongly with the onset of new algorithms to study interdependence between time series, the advent of modern complex network theory and the introduction of powerful techniques to record neurophysiological data, such as magnetoencephalography (MEG). However, when analyzing neurophysiological data with this approach several questions arise. In this thesis, I intend to tackle some of the practical open problems in the field. First of all, the increase in the number of time series analysis algorithms to study brain FC/EC, along with their mathematical complexity, creates the necessity of arranging them into a single, unified toolbox that allow neuroscientists, neurophysiologists and researchers from related fields to easily access and make use of them. I developed such a toolbox for this aim, it is named HERMES (http://hermes.ctb.upm.es), and encompasses several of the most common indexes for the assessment of FC and EC running for MatlabR environment. I believe that this toolbox will be very helpful to all the researchers working in the emerging field of brain connectivity analysis and will entail a great value for the scientific community. The second important practical issue tackled in this thesis is the evaluation of the sensitivity to deep brain sources of two different MEG sensors: planar gradiometers and magnetometers, in combination with the related methodological approach, using two phase synchronization indexes: phase locking value (PLV) y phase lag index (PLI), the latter one being less sensitive to volume conduction effect. Thus, I compared their performance when studying brain networks, obtaining that magnetometer sensors and PLV presented higher artificial values as compared with planar gradiometers and PLI respectively. However, when it came to characterize epileptic networks it was the PLV which gives better results, as PLI FC networks where very sparse. Complex network analysis has provided new concepts which improved characterization of interacting dynamical systems. With this background, networks could be considered composed of nodes, symbolizing systems, whose interactions with each other are represented by edges. A growing number of network measures is been applied in network analysis. However, there is theoretical and empirical evidence that many of these indexes are strongly correlated with each other. Therefore, in this thesis I reduced them to a small set, which could more efficiently characterize networks. Within this framework, selecting an appropriate threshold to decide whether a certain connectivity value of the FC matrix is significant and should be included in the network analysis becomes a crucial step, in this thesis, I used the surrogate data tests to make an individual data-driven evaluation of each of the edges significance and confirmed more accurate results than when just setting to a fixed value the density of connections. All these methodologies were applied to the study of epilepsy, analysing resting state MEG functional networks, in two groups of epileptic patients (generalized and focal epilepsy) that were compared to matching control subjects. Epilepsy is one of the most common neurological disorders, with more than 55 million people affected worldwide, characterized by its predisposition to generate epileptic seizures of abnormal excessive or synchronous neuronal activity, and thus, this scenario and analysis, present a great interest from both the clinical and the research perspective. Results revealed specific disruptions in connectivity and network topology and evidenced that networks’ topology is changed in epileptic brains, supporting the shift from ‘focus’ to ‘networks’ which is gaining importance in modern epilepsy research.

Mealiness assessment in fruits using MRI techniques.

Mealiness is a sensory attribute that cannot be defined by a single parameter but through a combination of variables (multidimensional structure). Previous studies propose the definition of mealiness as the lack of crispiness, of hardness and of juiciness. Current aims are focused on establishing non destructive tests for mealiness assessment. MultiSliceMultiEcho Magnetic resonance images (MRI, 64*64pixels) have been taken corresponding to a 3ms of Echo time. Small samples of Top Red apples stored 6 months at controlled atmosphere (expected to be non mealy) and 2°C (expected to be mealy) have been used for MRI imaging. Three out of four apples corresponding to the sample maintained at controlled atmosphere did not develop mealiness while three out of four fruits corresponding to the sample stored at 2°C became mealy after 6 month of storage. The minimum T2 values/image obtained for the mealy apples shows to be significantly lower when compared with non mealy apples pointing that a more dis-aggregated structure leads to a quicker loss of signal Also, there is a significant linear correlation (r=-0.76) between the number of pixels with a T2 value below 35ms within a fruit image and the deformation parameter registered during the Magness-Taylor firmness test. Finally, all the T2 images of the mealy apples show a regional variation of contrast which is not shown for non mealy apples. This variation of contrast is similar to the MRI images of water-cored apples indicating that in these cases there is a differential water movement that may precede the internal browning.

Mealiness assessment in apples and peaches using MRI techniques.

Since Januarv 1946 a wade EC Project entitled "Mealiness in fruits Consumers perception and means for detection is being carried out. Mealiness is a sensory attribute that cannot be defined by a single parameter but through a combination of variables (multidimensional structure) Previous studies propose the definition of mealiness as the lack of crispiness of hardness and of juiciness. A destructive instrumental procedure combined with a integration technique has been already developed enabling to identify mealy fruits by destructive instrumental means use other contributions of Barreiro and Ortiz to this Ag Eng 98. Current aims .are focused on establishing non destructive tests for mealiness assessment. Magnetic resonance Imaging (MRI) makes use of the magnetic properties that some atomic nuclei have. especially hidrogen nuclei from water molecules to obtain high quality images in the field of internal quality evaluation the MRI has been used to assess internal injury due to conservation as o treatments as chilling injury un Persimmons Clark&Forbes (1994) and water-core in apples (Wang et al. 1998. In the case of persimmons the chilling injury is described as an initial tissue breakdown and lack of cohesion between cells followed by formation of a firm gel and by a lack of juiciness without changes in the total amount ol water content. Also a browning of the flesh is indicated (Clark&Forhes 1994). This definition fits into the previous description of mealiness.

Learning from the living bodies: New principles and techniques for photonic sensing

Signal processing in any living being is much more complex than the one performed in artificial systems. Cortex architecture, although only partly known, gives some useful ideas to be employed in sensing technology. To analyze some of these structures is the objective of this paper. Among the points to be analyzed are the parallel transfer of information, the similarity of the different systems and the massive amount of data analyzed by physical techniques. As an example of these concepts, the possibility to transmit images in a parallel way will be reported.

Using array based techniques for noise source identification in cars

Una de las principales causas del ruido en nuestras ciudades es el tráfico rodado. El ruido generado por los vehículos no es sólo debido al motor, sino que existen diversas fuentes de ruido en los mismos, entre las que se puede destacar el ruido de rodadura. Para localizar las causas del ruido e identificar las principales fuentes del mismo se han utilizado en diversos estudios las técnicas de coherencia y las técnicas basadas en arrays. Sin embargo, en la bibliografía existente, no es habitual encontrar el uso de estas técnicas en el sector automovilístico. En esta tesis se parte de la premisa de la posibilidad de usar estas técnicas de medida en coches, para demostrar a la largo de la misma su factibilidad y su bondad para evaluar las fuentes de ruido en dos condiciones distintas: cuando el coche está parado y cuando está en movimiento. Como técnica de coherencia se elige la de Intensidad Selectiva, utilizándose la misma para evaluar la coherencia existente entre el ruido que llega a los oídos del conductor y la intensidad radiada por distintos puntos del motor. Para la localización de fuentes de ruido, las técnicas basadas en array son las que mejores resultados ofrecen. Statistically Optimized Near-field Acoustical Holography (SONAH) es la técnica elegida para la localización y caracterización de las fuentes de ruido en el motor a baja frecuencia. En cambio, Beamforming es la técnica seleccionada para el caso de media-alta frecuencia y para la evaluación de las fuentes de ruido cuando el coche se encuentra en movimiento. Las técnicas propuestas no sólo pueden utilizarse en medidas reales, sino que además proporcionan abundante información y frecen una gran versatilidad a la hora de caracterizar fuentes de ruido. ABSTRACT One of the most important noise causes in our cities is the traffic. The noise generated by the vehicles is not only due to the engine, but there are some other noise sources. Among them the tyre/road noise can be highlighted. Coherence and array based techniques have been used in some research to locate the noise causes and identify the main noise sources. Nevertheless, it is not usual in the literature to find the application of this kind of techniques in the car sector. This Thesis starts taking into account the possibility of using this kind of measurement techniques in cars, to demonstrate their feasability and their quality to evaluate the noise sources under two different conditions: when the car is stopped and when it is in movement. Selective Intensity was chosen as coherence technique, evaluating the coherence between the noise in the driver’s ears and the intensity radiated in different points of the engine. Array based techniques carry out the best results to noise source location. Statistically Optimized Near-field Acoustical Holography (SONAH) is the measurement technique chosen for noise source location and characterization in the engine at low frequency. On the other hand, Beamforming is the technique chosen in the case of medium-high frequency and to characterize the noise sources when the car is in movement. The proposed techniques not only can be used in actual measurements, but also provide a lot of information and are very versatile to noise source characterization.

Dominance intensity measure within fuzzy weight oriented MAUT: an application

We introduce a dominance intensity measuring method to derive a ranking of alternatives to deal with incomplete information in multi-criteria decision-making problems on the basis of multi-attribute utility theory (MAUT) and fuzzy sets theory. We consider the situation where there is imprecision concerning decision-makers’ preferences, and imprecise weights are represented by trapezoidal fuzzy weights.The proposed method is based on the dominance values between pairs of alternatives. These values can be computed by linear programming, as an additive multi-attribute utility model is used to rate the alternatives. Dominance values are then transformed into dominance intensity measures, used to rank the alternatives under consideration. Distances between fuzzy numbers based on the generalization of the left and right fuzzy numbers are utilized to account for fuzzy weights. An example concerning the selection of intervention strategies to restore an aquatic ecosystem contaminated by radionuclides illustrates the approach. Monte Carlo simulation techniques have been used to show that the proposed method performs well for different imprecision levels in terms of a hit ratio and a rank-order correlation measure.

Reduction of Nutrient Losses with Eroded Sediments by Post-Fire Soil Stabilisation Techniques

After an experimental fire in steep shrub land in a temperate–humid region (north-west Spain), the effects of two post-fire stabilisation treatments (grass seeding and straw mulching) on the chemical properties of eroded sediments,and the amount of nutrients lost with them, we reevaluated relative to control burnt soil, over a period of 13 months. Total C and N concentrations, and d 13 C, indicated that sediments were mainly contributed by charred plant and litter material. The highest concentrations of extractable base cations in the sediments occurred during the first 3 months following fire, especially for Na and K. As treatments had little or no effect on nutrient concentration in sediments, differences in nutrient losses were due to the 10-fold lower sediment production in mulching compared with other treatments. In control and seeding treatments, the accumulated amounts of nutrients lost with sediments were 989–1028kgha 1 (C), 77kgha 1 (N), 1.9–2.4kgha 1 (Ca), 0.9–1.1kgha 1 (Mg), 0.48–0.55kgha 1 (NH 4 þ –N), 0.39–0.56kgha 1 (K), 0.19–0.34kgha 1 (Na) and , 0.1kgha 1 (P and NO 3 –N) . These values accounted for 22–25% (total C and N) and 5–12% (NH 4 þ –N, Ca, P and Mg) of available nutrients in ash, and 1.0–2.4% of those in ash þ topsoil. As nutrient and sediment losses were strongly correlated, the reduction of the latter by mulching application leads to an effective decrease of post-fire nutrient losses.

Impact of fire and post-fire management techniques on soil chemical properties

The effects of fire ( Control burned soil) and two emergency stabilisation techniques (grass Seeding and straw Mulching ) on 20 chemical characteristics were evaluated on 0 – 5 cm top-soils sampled 1, 90, 180 and 365 days after an experimental fi re in a steep shrubland of a temperate-humid region (NW Spain). Most part of pH (in H 2 O and KCl) variance was explained by the sampling date. No clear temporal trends were identi fi able for total soil C and N content, likely due to the large SOM pool in these soils; however, changes on soil δ 13 C were explained by the deposition of 13 C-depleted ashes, followed by its progressive erosion, while those on soil δ 15 N were a consequence of fi re induced N outputs. After the fi re, NH 4 + – N, P, Na, K, Mg, Ca, Mn, Cu, Zn and B concentrations increased, while those of NO 3 − – N, Al, Fe and Co did not vary significantly. Despite a significant decline with time, concentrations of Mg, Ca and Mn at the end of the study were still higher than in unburned soil, while those of K, Cu, Zn and B were similar to the pre-fire levels and those of NH 4 + – N, P and Na were below pre-fire values. Mulching and Seeding treatments for burned soil emergency stabilisation had significant effects on soil δ 15 N and extractable K, Mg and Ca, while data were inconclusive for their possible effects on the extractable Al, Fe and Co

Clustering techniques for patients suffering acquired brain injury inneuro personal trainer

The study of the effectiveness of the cognitive rehabilitation processes and the identification of cognitive profiles, in order to define comparable populations, is a controversial area, but concurrently it is strongly needed in order to improve therapies. There is limited evidence about cognitive rehabilitation efficacy. Many of the trials conclude that in spite of an apparent clinical good response, differences do not show statistical significance. The common feature in all these trials is heterogeneity among populations. In this situation, observational studies on very well controlled cohort of studies, together with innovative methods in knowledge extraction, could provide methodological insights for the design of more accurate comparative trials. Some correlation studies between neuropsychological tests and patients capacities have been carried out -1---2- and also correlation between tests and morphological changes in the brain -3-. The procedures efficacy depends on three main factors: the affectation profile, the scheduled tasks and the execution results. The relationship between them makes up the cognitive rehabilitation as a discipline, but its structure is not properly defined. In this work we present a clustering method used in Neuro Personal Trainer (NPT) to group patients into cognitive profiles using data mining techniques. The system uses these clusters to personalize treatments, using the patients assigned cluster to select which tasks are more suitable for its concrete needs, by comparing the results obtained in the past by patients with the same profile.

Determining the effectiveness of three software evaluation techniques through informal aggregation

An accepted fact in software engineering is that software must undergo verification and validation process during development to ascertain and improve its quality level. But there are too many techniques than a single developer could master, yet, it is impossible to be certain that software is free of defects. So, it is crucial for developers to be able to choose from available evaluation techniques, the one most suitable and likely to yield optimum quality results for different products. Though, some knowledge is available on the strengths and weaknesses of the available software quality assurance techniques but not much is known yet on the relationship between different techniques and contextual behavior of the techniques. Objective: This research investigates the effectiveness of two testing techniques ? equivalence class partitioning and decision coverage and one review technique ? code review by abstraction, in terms of their fault detection capability. This will be used to strengthen the practical knowledge available on these techniques.