Knowledge representation tool for cognitiveprocesses modeling

In the last decades, neuropsychological theories tend to consider cognitive functions as a result of the whole brainwork and not as individual local areas of its cortex. Studies based on neuroimaging techniques have increased in the last years, promoting an exponential growth of the body of knowledge about relations between cognitive functions and brain structures [1]. However, so fast evolution make complicated to integrate them in verifiable theories and, even more, translated in to cognitive rehabilitation. The aim of this research work is to develop a cognitive process-modeling tool. The purpose of this system is, in the first term, to represent multidimensional data, from structural and functional connectivity, neuroimaging, data from lesion studies and derived data from clinical intervention [2][3]. This will allow to identify consolidated knowledge, hypothesis, experimental designs, new data from ongoing studies and emerging results from clinical interventions. In the second term, we pursuit to use Artificial Intelligence to assist in decision making allowing to advance towards evidence based and personalized treatments in cognitive rehabilitation. This work presents the knowledge base design of the knowledge representation tool. It is compound of two different taxonomies (structure and function) and a set of tags linking both taxonomies at different levels of structural and functional organization. The remainder of the abstract is organized as follows: Section 2 presents the web application used for gathering necessary information for generating the knowledge base, Section 3 describes knowledge base structure and finally Section 4 expounds reached conclusions.

La Práctica del Desarrollo Local: Veinticinco Años de Experiencia del Instituto de Desarrollo Comunitario de Cuenca en Territorios Rurales

La investigación tiene como objetivo principal analizar la experiencia de la Asociación Instituto de Desarrollo Comunitario de Cuenca, en la práctica del desarrollo local en los territorios rurales de esta provincia. La necesidad de estimular a la población para que ésta forme parte de su propio desarrollo, pone de manifiesto la existencia de determinadas instituciones externas que a través de procesos como la facilitación, movilizan y crean capacidades en las personas y las empujan hacia la participación. Este es el caso del IDC de Cuenca que nace en 1985 como entidad privada —declarada de utilidad pública y sin ánimo de lucro—, con la voluntad de sus fundadores de trabajar en el desarrollo local de las zonas deprimidas de Cuenca. La labor desarrollada en estos más de 25 años tiene como centro la promoción de la persona como ser individual y como parte de su comunidad. Para la elaboración de la Tesis, se ha utilizado la metodología del caso de estudio centrado en el análisis de la experiencia del IDC respecto de las cuatro investigaciones realizadas centradas en el proceso de facilitación, las herramientas de formación e información, y la dinamización del tejido asociativo como resultado del proceso. La labor del IDC en la provincia de Cuenca se ha desarrollado a través de la ejecución de proyectos. Éstos se han llevado a cabo por medio de procesos de facilitación donde la creación de grupos de trabajo ha permitido mejorar la estructuración social de las zonas rurales. Los grupos de trabajo son creados y apoyados por el IDC a través de la utilización de las herramientas de información y formación, que deben estar adaptadas a las necesidades de los individuos y en este caso cuentan con una metodología de aplicación propia. La creación de diferentes entidades —asociaciones, cooperativas, clubes, etc.—, ha sido uno de los resultados del trabajo desarrollado por el IDC a través de los procesos de facilitación que han mejorado la estructuración de la sociedad rural. Pese a la complejidad tanto de los procesos de desarrollo como de la evaluación final de dichos procesos, la creación de grupos capaces de alcanzar determinados objetivos propuestos en su comunidad potenciando sus propios recursos, son el ejemplo de la dinamización social que se lleva produciendo en la provincia de Cuenca desde hace más de 25 años. The research's main objective is to analyze the experience of the Asociación Instituto de Desarrollo Comunitario de Cuenca, in the practice of local development in rural areas of this province. The need to encourage more people to take part of their own development, reveals the existence of certain external institutions which through processes such as facilitation, mobilize and create capacities in people to foster their participation. This is the case of the IDC of Cuenca that was born in 1985 as a private entity —declared of public utility and as non profit entity— with the intention, as stated by its founders, of working in the local development of the disadvantaged areas of Cuenca. The work carried out in these more than 25 years focused on promoting the person as an individual and as part of their community. In this research, the methodology of the case study has been used in the analysis of the experience of the IDC in four investigations carried out regarding the process of facilitation, training and information tools, and the improvement of social involvement as a result of the development process. The work of the IDC in the province of Cuenca has been developed through the implementation of projects. They have been carried out through processes of facilitation, where the creation of working groups has improved the social structuring of rural areas. The working groups are created and supported by the IDC through the use of tools of information and training, which must be adapted to the individual needs in each case, and even count with their own implementation methodology. The creation of different entities —associations, cooperatives, clubs, etc.— has been one of the results of the work carried out by the IDC through processes of facilitation which have improved the structure of rural society. Despite the complexity of development processes and the final assessment of these processes, the creation of groups able to reach certain objectives proposed in their community promoting its own resources, is an example of the social involvement that has been taking place in the province of Cuenca for more than 25 years.

Characterization cement pastes degraded in lanoratory solutions and physiochemical parameters employed for modeling the process

Previously degradation studies carried out, over a number of different mortars by the research team, have shown that observed degradation does not exclusively depend on the solution equilibrium pH, nor the aggressive anions relative solubility. In our tests no reason was found that could allow us to explain, why same solubility anions with a lower pH are less aggressive than others. The aim of this paper is to study cement pastes behavior in aggressive environments. As observed in previous research, this cement pastes behaviors are not easily explained only taking into account only usual parameters, pH, solubility etc. Consequently the paper is about studying if solution physicochemical characteristics are more important in certain environments than specific pH values. The paper tries to obtain a degradation model, which starting from solution physicochemical parameters allows us to interpret the different behaviors shown by different composition cements. To that end, the rates of degradation of the solid phases were computed for each considered environment. Three cement have been studied: CEM I 42.5R/SR, CEM II/A-V 42.5R and CEM IV/B-(P-V) 32.5 N. The pastes have been exposed to five environments: sodium acetate/acetic acid 0.35 M, sodium sulfate solution 0.17 M, a solution representing natural water, saturated calcium hydroxide solution and laboratory environment. The attack mechanism was meant to be unidirectional, in order to achieve so; all sides of cylinders were sealed except from the attacked surface. The cylinders were taking out of the exposition environments after 2, 4, 7, 14, 30, 58 and 90 days. Both aggressive solution variations in solid phases and in different depths have been characterized. To each age and depth the calcium, magnesium and iron contents have been analyzed. Hydrated phases evolution studied, using thermal analysis, and crystalline compound changes, using X ray diffraction have been also analyzed. Sodium sulphate and water solutions stabilize an outer pH near to 8 in short time, however the stability of the most pH dependent phases is not the same. Although having similar pH and existing the possibility of forming a plaster layer near to the calcium leaching surface, this stability is greater than other sulphate solutions. Stability variations of solids formed by inverse diffusion, determine the rate of degradation.

Introducing usability in a conceptual modeling-based software development process.

Usability plays an important role to satisfy users? needs. There are many recommendations in the HCI literature on how to improve software usability. Our research focuses on such recommendations that affect the system architecture rather than just the interface. However, improving software usability in aspects that affect architecture increases the analyst?s workload and development complexity. This paper proposes a solution based on model-driven development. We propose representing functional usability mechanisms abstractly by means of conceptual primitives. The analyst will use these primitives to incorporate functional usability features at the early stages of the development process. Following the model-driven development paradigm, these features are then automatically transformed into subsequent steps of development, a practice that is hidden from the analyst.

Application of the Extended Kalman filter to fuzzy modeling: Algorithms and practical implementation

Modeling phase is fundamental both in the analysis process of a dynamic system and the design of a control system. If this phase is in-line is even more critical and the only information of the system comes from input/output data. Some adaptation algorithms for fuzzy system based on extended Kalman filter are presented in this paper, which allows obtaining accurate models without renounce the computational efficiency that characterizes the Kalman filter, and allows its implementation in-line with the process

HAZOP studies using a functional modeling framework

In this paper we present a tool to perform guided HAZOP studies using a functional modeling framework: D-higraphs. It is a formalism that gathers in a single model structural (ontological) and functional information about the process considered. In this paper it is applied to an industrial case showing that the proposed methodology fits its purposes and fulfills some of the gaps and drawbacks existing in previous reported HAZOP assistant tools.

Functional modeling applied to HAZOP automation

In this paper we present a new tool to perform guided HAZOP analyses. This tool uses a functional model of the process that merges its functional and its structural information in a natural way. The functional modeling technique used is called D-higraphs. This tool solves some of the problems and drawbacks of other existing methodologies for the automation of HAZOPs. The applicability and easy understanding of the proposed methodology is shown in an industrial case.

Hybrid incremental modeling based on least squares and fuzzy K-NN for monitoring tool wear in turning processes

There is now an emerging need for an efficient modeling strategy to develop a new generation of monitoring systems. One method of approaching the modeling of complex processes is to obtain a global model. It should be able to capture the basic or general behavior of the system, by means of a linear or quadratic regression, and then superimpose a local model on it that can capture the localized nonlinearities of the system. In this paper, a novel method based on a hybrid incremental modeling approach is designed and applied for tool wear detection in turning processes. It involves a two-step iterative process that combines a global model with a local model to take advantage of their underlying, complementary capacities. Thus, the first step constructs a global model using a least squares regression. A local model using the fuzzy k-nearest-neighbors smoothing algorithm is obtained in the second step. A comparative study then demonstrates that the hybrid incremental model provides better error-based performance indices for detecting tool wear than a transductive neurofuzzy model and an inductive neurofuzzy model.

A formalism and method for representing and reasoning with process models authored by subject matter experts

Enabling Subject Matter Experts (SMEs) to formulate knowledge without the intervention of Knowledge Engineers (KEs) requires providing SMEs with methods and tools that abstract the underlying knowledge representation and allow them to focus on modeling activities. Bridging the gap between SME-authored models and their representation is challenging, especially in the case of complex knowledge types like processes, where aspects like frame management, data, and control flow need to be addressed. In this paper, we describe how SME-authored process models can be provided with an operational semantics and grounded in a knowledge representation language like F-logic in order to support process-related reasoning. The main results of this work include a formalism for process representation and a mechanism for automatically translating process diagrams into executable code following such formalism. From all the process models authored by SMEs during evaluation 82% were well-formed, all of which executed correctly. Additionally, the two optimizations applied to the code generation mechanism produced a performance improvement at reasoning time of 25% and 30% with respect to the base case, respectively.

Modeling sub-threshold slope and DIBL mismatch of sub-22nm FinFet

A great challenge for future information technologies is building reliable systems on top of unreliable components. Parameters of modern and future technology devices are affected by severe levels of process variability and devices will degrade and even fail during the normal lifeDme of the chip due to aging mechanisms. These extreme levels of variability are caused by the high device miniaturizaDon and the random placement of individual atoms. Variability is considered a "red brick" by the InternaDonal Technology Roadmap for Semiconductors. The session is devoted to this topic presenDng research experiences from the Spanish Network on Variability called VARIABLES. In this session a talk entlited "Modeling sub-threshold slope and DIBL mismatch of sub-22nm FinFet" was presented.

Self-organizing cultured neural networks: Image analysis techniques for longitudinal tracking and modeling of the underlying network structure

Esta tesis estudia la evolución estructural de conjuntos de neuronas como la capacidad de auto-organización desde conjuntos de neuronas separadas hasta que forman una red (clusterizada) compleja. Esta tesis contribuye con el diseño e implementación de un algoritmo no supervisado de segmentación basado en grafos con un coste computacional muy bajo. Este algoritmo proporciona de forma automática la estructura completa de la red a partir de imágenes de cultivos neuronales tomadas con microscopios de fase con una resolución muy alta. La estructura de la red es representada mediante un objeto matemático (matriz) cuyos nodos representan a las neuronas o grupos de neuronas y los enlaces son las conexiones reconstruidas entre ellos. Este algoritmo extrae también otras medidas morfológicas importantes que caracterizan a las neuronas y a las neuritas. A diferencia de otros algoritmos hasta el momento, que necesitan de fluorescencia y técnicas inmunocitoquímicas, el algoritmo propuesto permite el estudio longitudinal de forma no invasiva posibilitando el estudio durante la formación de un cultivo. Además, esta tesis, estudia de forma sistemática un grupo de variables topológicas que garantizan la posibilidad de cuantificar e investigar la progresión de las características principales durante el proceso de auto-organización del cultivo. Nuestros resultados muestran la existencia de un estado concreto correspondiente a redes con configuracin small-world y la emergencia de propiedades a micro- y meso-escala de la estructura de la red. Finalmente, identificamos los procesos físicos principales que guían las transformaciones morfológicas de los cultivos y proponemos un modelo de crecimiento de red que reproduce el comportamiento cuantitativamente de las observaciones experimentales. ABSTRACT The thesis analyzes the morphological evolution of assemblies of living neurons, as they self-organize from collections of separated cells into elaborated, clustered, networks. In particular, it contributes with the design and implementation of a graph-based unsupervised segmentation algorithm, having an associated very low computational cost. The processing automatically retrieves the whole network structure from large scale phase-contrast images taken at high resolution throughout the entire life of a cultured neuronal network. The network structure is represented by a mathematical object (a matrix) in which nodes are identified neurons or neurons clusters, and links are the reconstructed connections between them. The algorithm is also able to extract any other relevant morphological information characterizing neurons and neurites. More importantly, and at variance with other segmentation methods that require fluorescence imaging from immunocyto- chemistry techniques, our measures are non invasive and entitle us to carry out a fully longitudinal analysis during the maturation of a single culture. In turn, a systematic statistical analysis of a group of topological observables grants us the possibility of quantifying and tracking the progression of the main networks characteristics during the self-organization process of the culture. Our results point to the existence of a particular state corresponding to a small-world network configuration, in which several relevant graphs micro- and meso-scale properties emerge. Finally, we identify the main physical processes taking place during the cultures morphological transformations, and embed them into a simplified growth model that quantitatively reproduces the overall set of experimental observations.

Self-organizing cultured neural networks: Image analysis techniques for longitudinal tracking and modeling of the underlying network structure (versión actualizada)

Esta tesis estudia la evolución estructural de conjuntos de neuronas como la capacidad de auto-organización desde conjuntos de neuronas separadas hasta que forman una red (clusterizada) compleja. Esta tesis contribuye con el diseño e implementación de un algoritmo no supervisado de segmentación basado en grafos con un coste computacional muy bajo. Este algoritmo proporciona de forma automática la estructura completa de la red a partir de imágenes de cultivos neuronales tomadas con microscopios de fase con una resolución muy alta. La estructura de la red es representada mediante un objeto matemático (matriz) cuyos nodos representan a las neuronas o grupos de neuronas y los enlaces son las conexiones reconstruidas entre ellos. Este algoritmo extrae también otras medidas morfológicas importantes que caracterizan a las neuronas y a las neuritas. A diferencia de otros algoritmos hasta el momento, que necesitan de fluorescencia y técnicas inmunocitoquímicas, el algoritmo propuesto permite el estudio longitudinal de forma no invasiva posibilitando el estudio durante la formación de un cultivo. Además, esta tesis, estudia de forma sistemática un grupo de variables topológicas que garantizan la posibilidad de cuantificar e investigar la progresión de las características principales durante el proceso de auto-organización del cultivo. Nuestros resultados muestran la existencia de un estado concreto correspondiente a redes con configuracin small-world y la emergencia de propiedades a micro- y meso-escala de la estructura de la red. Finalmente, identificamos los procesos físicos principales que guían las transformaciones morfológicas de los cultivos y proponemos un modelo de crecimiento de red que reproduce el comportamiento cuantitativamente de las observaciones experimentales. ABSTRACT The thesis analyzes the morphological evolution of assemblies of living neurons, as they self-organize from collections of separated cells into elaborated, clustered, networks. In particular, it contributes with the design and implementation of a graph-based unsupervised segmentation algorithm, having an associated very low computational cost. The processing automatically retrieves the whole network structure from large scale phase-contrast images taken at high resolution throughout the entire life of a cultured neuronal network. The network structure is represented by a mathematical object (a matrix) in which nodes are identified neurons or neurons clusters, and links are the reconstructed connections between them. The algorithm is also able to extract any other relevant morphological information characterizing neurons and neurites. More importantly, and at variance with other segmentation methods that require fluorescence imaging from immunocyto- chemistry techniques, our measures are non invasive and entitle us to carry out a fully longitudinal analysis during the maturation of a single culture. In turn, a systematic statistical analysis of a group of topological observables grants us the possibility of quantifying and tracking the progression of the main networks characteristics during the self-organization process of the culture. Our results point to the existence of a particular state corresponding to a small-world network configuration, in which several relevant graphs micro- and meso-scale properties emerge. Finally, we identify the main physical processes taking place during the cultures morphological transformations, and embed them into a simplified growth model that quantitatively reproduces the overall set of experimental observations.

Modelización de servicios ecosistémicos en una cuenca hidrológica del área mediterránea = Modeling ecosystem services in a mediterranean area river basin

La modelización es un proceso por el que se obtienen modelos de los procesos del ´mundo real´ mediante la utilización de simplificaciones. Sin embargo, las estimaciones obtenidas con el modelo llevan implícitas incertidumbre que se debe evaluar. Mediante un análisis de sensibilidad se puede mejorar la confianza en los resultados, sin embargo, este paso a veces no se realiza debido básicamente al trabajo que lleva consigo este tipo de análisis. Además, al crear un modelo, hay que mantener un equilibrio entre la obtención de resultados lo más exactos posible mediante un modelo lo más sencillo posible. Por ello, una vez creado un modelo, es imprescindible comprobar si es necesario o no incluir más procesos que en un principio no se habían incluido. Los servicios ecosistémicos son los procesos mediante los cuales los ecosistemas mantienen y satisfacen el bienestar humano. La importancia que los servicios ecosistémicos y sus beneficios asociados tienen, junto con la necesidad de realizar una buena gestión de los mismos, han estimulado la aparición de modelos y herramientas para cuantificarlos. InVEST (Integrated Valuation of Ecosystem Services and Tradoffs) es una de estas herramientas específicas para calcular servicios eco-sistémicos, desarrollada por Natural Capital Project (Universidad de Stanford, EEUU). Como resultado del creciente interés en calcular los servicios eco-sistémicos, se prevé un incremento en la aplicación del InVEST. La investigación desarrollada en esta Tesis pretende ayudar en esas otras importantes fases necesarias después de la creación de un modelo, abarcando los dos siguientes trabajos. El primero es la aplicación de un análisis de sensibilidad al modelo en una cuenca concreta mediante la metodología más adecuada. El segundo es relativo a los procesos dentro de la corriente fluvial que actualmente no se incluyen en el modelo mediante la creación y aplicación de una metodología que estudiara el papel que juegan estos procesos en el modelo InVEST de retención de nutrientes en el área de estudio. Los resultados de esta Tesis contribuirán a comprender la incertidumbre involucrada en el proceso de modelado. También pondrá de manifiesto la necesidad de comprobar el comportamiento de un modelo antes de utilizarlo y en el momento de interpretar los resultados obtenidos. El trabajo en esta Tesis contribuirá a mejorar la plataforma InVEST, que es una herramienta importante en el ámbito de los servicios de los ecosistemas. Dicho trabajo beneficiará a los futuros usuarios de la herramienta, ya sean investigadores (en investigaciones futuras), o técnicos (en futuros trabajos de toma de decisiones o gestión ecosistemas). ABSTRACT Modeling is the process to idealize real-world situations through simplifications in order to obtain a model. However, model estimations lead to uncertainties that have to be evaluated formally. The role of the sensitivity analysis (SA) is to assign model output uncertainty based on the inputs and can increase confidence in model, however, it is often omitted in modelling, usually as a result of the growing effort it involves. In addition, the balance between accuracy and simplicity is not easy to assess. For this reason, when a model is developed, it is necessary to test it in order to understand its behavior and to include, if necessary, more complexity to get a better response. Ecosystem services are the conditions and processes through which natural ecosystems, and their constituent species, sustain and fulfill human life. The relevance of ecosystem services and the need to better manage them and their associated benefits have stimulated the emergence of models and tools to measure them. InVEST, Integrated Valuation of Ecosystem Services and Tradoffs, is one of these ecosystem services-specific tools developed by the Natural Capital Project (Stanford University, USA). As a result of the growing interest in measuring ecosystem services, the use of InVEST is anticipated to grow exponentially in the coming years. However, apart from model development, making a model involves other crucial stages such as its evaluation and application in order to validate estimations. The work developed in this thesis tries to help in this relevant and imperative phase of the modeling process, and does so in two different ways. The first one is to conduct a sensitivity analysis of the model, which consists in choosing and applying a methodology in an area and analyzing the results obtained. The second is related to the in-stream processes that are not modeled in the current model, and consists in creating and applying a methodology for testing the streams role in the InVEST nutrient retention model in a case study, analyzing the results obtained. The results of this Thesis will contribute to the understanding of the uncertainties involved in the modeling process. It will also illustrate the need to check the behavior of every model developed before putting them in production and illustrate the importance of understanding their behavior in terms of correctly interpreting the results obtained in light of uncertainty. The work in this thesis will contribute to improve the InVEST platform, which is an important tool in the field of ecosystem services. Such work will benefit future users, whether they are researchers (in their future research), or technicians (in their future work in ecosystem conservation or management decisions).

Modeling GHG emissions, N and C dynamics in Spanish agricultural soils.

To date, only few initiatives have been carried out in Spain in order to use mathematical models (e.g. DNDC, DayCent, FASSET y SIMSNIC) to estimate nitrogen (N) and carbon (C) dynamics as well as greenhouse gases (GHG) in Spanish agrosystems. Modeling at this level may allow to gain insight on both the complex relationships between biological and physicochemical processes, controlling the processes leading to GHG production and consumption in soils (e.g. nitrification, denitrification, decomposing, etc.), and the interactions between C and N cycles within the different components of the continuum plant-soil-environment. Additionally, these models can simulate the processes behind production, consumition and transport of GHG (e.g. nitrous oxide, N2O, and carbon dioxide, CO2) in the short and medium term and at different scales. Other sources of potential pollution from soils can be identified and quantified using these process-based models (e.g. NO3 y NH3).

Modelización de servicios ecosistémicos en una cuenca hidrológica del área mediterránea = Modeling ecosystem services in a mediterranean area river basin

La modelización es un proceso por el que se obtienen modelos de los procesos del ´mundo real´ mediante la utilización de simplificaciones. Sin embargo, las estimaciones obtenidas con el modelo llevan implícitas incertidumbre que se debe evaluar. Mediante un análisis de sensibilidad se puede mejorar la confianza en los resultados, sin embargo, este paso a veces no se realiza debido básicamente al trabajo que lleva consigo este tipo de análisis. Además, al crear un modelo, hay que mantener un equilibrio entre la obtención de resultados lo más exactos posible mediante un modelo lo más sencillo posible. Por ello, una vez creado un modelo, es imprescindible comprobar si es necesario o no incluir más procesos que en un principio no se habían incluido. Los servicios ecosistémicos son los procesos mediante los cuales los ecosistemas mantienen y satisfacen el bienestar humano. La importancia que los servicios ecosistémicos y sus beneficios asociados tienen, junto con la necesidad de realizar una buena gestión de los mismos, han estimulado la aparición de modelos y herramientas para cuantificarlos. InVEST (Integrated Valuation of Ecosystem Services and Tradoffs) es una de estas herramientas específicas para calcular servicios eco-sistémicos, desarrollada por Natural Capital Project (Universidad de Stanford, EEUU). Como resultado del creciente interés en calcular los servicios eco-sistémicos, se prevé un incremento en la aplicación del InVEST. La investigación desarrollada en esta Tesis pretende ayudar en esas otras importantes fases necesarias después de la creación de un modelo, abarcando los dos siguientes trabajos. El primero es la aplicación de un análisis de sensibilidad al modelo en una cuenca concreta mediante la metodología más adecuada. El segundo es relativo a los procesos dentro de la corriente fluvial que actualmente no se incluyen en el modelo mediante la creación y aplicación de una metodología que estudiara el papel que juegan estos procesos en el modelo InVEST de retención de nutrientes en el área de estudio. Los resultados de esta Tesis contribuirán a comprender la incertidumbre involucrada en el proceso de modelado. También pondrá de manifiesto la necesidad de comprobar el comportamiento de un modelo antes de utilizarlo y en el momento de interpretar los resultados obtenidos. El trabajo en esta Tesis contribuirá a mejorar la plataforma InVEST, que es una herramienta importante en el ámbito de los servicios de los ecosistemas. Dicho trabajo beneficiará a los futuros usuarios de la herramienta, ya sean investigadores (en investigaciones futuras), o técnicos (en futuros trabajos de toma de decisiones o gestión ecosistemas). ABSTRACT Modeling is the process to idealize real-world situations through simplifications in order to obtain a model. However, model estimations lead to uncertainties that have to be evaluated formally. The role of the sensitivity analysis (SA) is to assign model output uncertainty based on the inputs and can increase confidence in model, however, it is often omitted in modelling, usually as a result of the growing effort it involves. In addition, the balance between accuracy and simplicity is not easy to assess. For this reason, when a model is developed, it is necessary to test it in order to understand its behavior and to include, if necessary, more complexity to get a better response. Ecosystem services are the conditions and processes through which natural ecosystems, and their constituent species, sustain and fulfill human life. The relevance of ecosystem services and the need to better manage them and their associated benefits have stimulated the emergence of models and tools to measure them. InVEST, Integrated Valuation of Ecosystem Services and Tradoffs, is one of these ecosystem services-specific tools developed by the Natural Capital Project (Stanford University, USA). As a result of the growing interest in measuring ecosystem services, the use of InVEST is anticipated to grow exponentially in the coming years. However, apart from model development, making a model involves other crucial stages such as its evaluation and application in order to validate estimations. The work developed in this thesis tries to help in this relevant and imperative phase of the modeling process, and does so in two different ways. The first one is to conduct a sensitivity analysis of the model, which consists in choosing and applying a methodology in an area and analyzing the results obtained. The second is related to the in-stream processes that are not modeled in the current model, and consists in creating and applying a methodology for testing the streams role in the InVEST nutrient retention model in a case study, analyzing the results obtained. The results of this Thesis will contribute to the understanding of the uncertainties involved in the modeling process. It will also illustrate the need to check the behavior of every model developed before putting them in production and illustrate the importance of understanding their behavior in terms of correctly interpreting the results obtained in light of uncertainty. The work in this thesis will contribute to improve the InVEST platform, which is an important tool in the field of ecosystem services. Such work will benefit future users, whether they are researchers (in their future research), or technicians (in their future work in ecosystem conservation or management decisions).