First-principle data-driven models for assessment of motor disorders in Parkinson’s disease

Parkinson’s disease (PD) is an increasing neurological disorder in an aging society. The motor and non-motor symptoms of PD advance with the disease progression and occur in varying frequency and duration. In order to affirm the full extent of a patient’s condition, repeated assessments are necessary to adjust medical prescription. In clinical studies, symptoms are assessed using the unified Parkinson’s disease rating scale (UPDRS). On one hand, the subjective rating using UPDRS relies on clinical expertise. On the other hand, it requires the physical presence of patients in clinics which implies high logistical costs. Another limitation of clinical assessment is that the observation in hospital may not accurately represent a patient’s situation at home. For such reasons, the practical frequency of tracking PD symptoms may under-represent the true time scale of PD fluctuations and may result in an overall inaccurate assessment. Current technologies for at-home PD treatment are based on data-driven approaches for which the interpretation and reproduction of results are problematic.  The overall objective of this thesis is to develop and evaluate unobtrusive computer methods for enabling remote monitoring of patients with PD. It investigates first-principle data-driven model based novel signal and image processing techniques for extraction of clinically useful information from audio recordings of speech (in texts read aloud) and video recordings of gait and finger-tapping motor examinations. The aim is to map between PD symptoms severities estimated using novel computer methods and the clinical ratings based on UPDRS part-III (motor examination). A web-based test battery system consisting of self-assessment of symptoms and motor function tests was previously constructed for a touch screen mobile device. A comprehensive speech framework has been developed for this device to analyze text-dependent running speech by: (1) extracting novel signal features that are able to represent PD deficits in each individual component of the speech system, (2) mapping between clinical ratings and feature estimates of speech symptom severity, and (3) classifying between UPDRS part-III severity levels using speech features and statistical machine learning tools. A novel speech processing method called cepstral separation difference showed stronger ability to classify between speech symptom severities as compared to existing features of PD speech. In the case of finger tapping, the recorded videos of rapid finger tapping examination were processed using a novel computer-vision (CV) algorithm that extracts symptom information from video-based tapping signals using motion analysis of the index-finger which incorporates a face detection module for signal calibration. This algorithm was able to discriminate between UPDRS part III severity levels of finger tapping with high classification rates. Further analysis was performed on novel CV based gait features constructed using a standard human model to discriminate between a healthy gait and a Parkinsonian gait. The findings of this study suggest that the symptom severity levels in PD can be discriminated with high accuracies by involving a combination of first-principle (features) and data-driven (classification) approaches. The processing of audio and video recordings on one hand allows remote monitoring of speech, gait and finger-tapping examinations by the clinical staff. On the other hand, the first-principles approach eases the understanding of symptom estimates for clinicians. We have demonstrated that the selected features of speech, gait and finger tapping were able to discriminate between symptom severity levels, as well as, between healthy controls and PD patients with high classification rates. The findings support suitability of these methods to be used as decision support tools in the context of PD assessment.

Quality assessment of a landslide inventory map and its application to land‐use planning. A case study in the Northern Apennines (Emilia‐Romagna region, Italy)

Landslide hazard and risk are growing as a consequence of climate change and demographic pressure. Land‐use planning represents a powerful tool to manage this socio‐economic problem and build sustainable and landslide resilient communities. Landslide inventory maps are a cornerstone of land‐use planning and, consequently, their quality assessment represents a burning issue. This work aimed to define the quality parameters of a landslide inventory and assess its spatial and temporal accuracy with regard to its possible applications to land‐use planning. In this sense, I proceeded according to a two‐steps approach. An overall assessment of the accuracy of data geographic positioning was performed on four case study sites located in the Italian Northern Apennines. The quantification of the overall spatial and temporal accuracy, instead, focused on the Dorgola Valley (Province of Reggio Emilia). The assessment of spatial accuracy involved a comparison between remotely sensed and field survey data, as well as an innovative fuzzylike analysis of a multi‐temporal landslide inventory map. Conversely, long‐ and short‐term landslide temporal persistence was appraised over a period of 60 years with the aid of 18 remotely sensed image sets. These results were eventually compared with the current Territorial Plan for Provincial Coordination (PTCP) of the Province of Reggio Emilia. The outcome of this work suggested that geomorphologically detected and mapped landslides are a significant approximation of a more complex reality. In order to convey to the end‐users this intrinsic uncertainty, a new form of cartographic representation is needed. In this sense, a fuzzy raster landslide map may be an option. With regard to land‐use planning, landslide inventory maps, if appropriately updated, confirmed to be essential decision‐support tools. This research, however, proved that their spatial and temporal uncertainty discourages any direct use as zoning maps, especially when zoning itself is associated to statutory or advisory regulations.

Bases metodológicas para un sistema de apoyo a la selección de especies en la restauración de la vegetación

RESUMEN El apoyo a la selección de especies a la restauración de la vegetación en España en los últimos 40 años se ha basado fundamentalmente en modelos de distribución de especies, también llamados modelos de nicho ecológico, que estiman la probabilidad de presencia de las especies en función de las condiciones del medio físico (clima, suelo, etc.). Con esta tesis se ha intentado contribuir a la mejora de la capacidad predictiva de los modelos introduciendo algunas propuestas metodológicas adaptadas a los datos disponibles actualmente en España y enfocadas al uso de los modelos en la selección de especies. No siempre se dispone de datos a una resolución espacial adecuada para la escala de los proyectos de restauración de la vegetación. Sin embrago es habitual contar con datos de baja resolución espacial para casi todas las especies vegetales presentes en España. Se propone un método de recalibración que actualiza un modelo de regresión logística de baja resolución espacial con una nueva muestra de alta resolución espacial. El método permite obtener predicciones de calidad aceptable con muestras relativamente pequeñas (25 presencias de la especie) frente a las muestras mucho mayores (más de 100 presencias) que requería una estrategia de modelización convencional que no usara el modelo previo. La selección del método estadístico puede influir decisivamente en la capacidad predictiva de los modelos y por esa razón la comparación de métodos ha recibido mucha atención en la última década. Los estudios previos consideraban a la regresión logística como un método inferior a técnicas más modernas como las de máxima entropía. Los resultados de la tesis demuestran que esa diferencia observada se debe a que los modelos de máxima entropía incluyen técnicas de regularización y la versión de la regresión logística usada en las comparaciones no. Una vez incorporada la regularización a la regresión logística usando penalización, las diferencias en cuanto a capacidad predictiva desaparecen. La regresión logística penalizada es, por tanto, una alternativa más para el ajuste de modelos de distribución de especies y está a la altura de los métodos modernos con mejor capacidad predictiva como los de máxima entropía. A menudo, los modelos de distribución de especies no incluyen variables relativas al suelo debido a que no es habitual que se disponga de mediciones directas de sus propiedades físicas o químicas. La incorporación de datos de baja resolución espacial proveniente de mapas de suelo nacionales o continentales podría ser una alternativa. Los resultados de esta tesis sugieren que los modelos de distribución de especies de alta resolución espacial mejoran de forma ligera pero estadísticamente significativa su capacidad predictiva cuando se incorporan variables relativas al suelo procedente de mapas de baja resolución espacial. La validación es una de las etapas fundamentales del desarrollo de cualquier modelo empírico como los modelos de distribución de especies. Lo habitual es validar los modelos evaluando su capacidad predictiva especie a especie, es decir, comparando en un conjunto de localidades la presencia o ausencia observada de la especie con las predicciones del modelo. Este tipo de evaluación no responde a una cuestión clave en la restauración de la vegetación ¿cuales son las n especies más idóneas para el lugar a restaurar? Se ha propuesto un método de evaluación de modelos adaptado a esta cuestión que consiste en estimar la capacidad de un conjunto de modelos para discriminar entre las especies presentes y ausentes de un lugar concreto. El método se ha aplicado con éxito a la validación de 188 modelos de distribución de especies leñosas orientados a la selección de especies para la restauración de la vegetación en España. Las mejoras metodológicas propuestas permiten mejorar la capacidad predictiva de los modelos de distribución de especies aplicados a la selección de especies en la restauración de la vegetación y también permiten ampliar el número de especies para las que se puede contar con un modelo que apoye la toma de decisiones. SUMMARY During the last 40 years, decision support tools for plant species selection in ecological restoration in Spain have been based on species distribution models (also called ecological niche models), that estimate the probability of occurrence of the species as a function of environmental predictors (e.g., climate, soil). In this Thesis some methodological improvements are proposed to contribute to a better predictive performance of such models, given the current data available in Spain and focusing in the application of the models to selection of species for ecological restoration. Fine grained species distribution data are required to train models to be used at the scale of the ecological restoration projects, but this kind of data are not always available for every species. On the other hand, coarse grained data are available for almost every species in Spain. A recalibration method is proposed that updates a coarse grained logistic regression model using a new fine grained updating sample. The method allows obtaining acceptable predictive performance with reasonably small updating sample (25 occurrences of the species), in contrast with the much larger samples (more than 100 occurrences) required for a conventional modeling approach that discards the coarse grained data. The choice of the statistical method may have a dramatic effect on model performance, therefore comparisons of methods have received much interest in the last decade. Previous studies have shown a poorer performance of the logistic regression compared to novel methods like maximum entropy models. The results of this Thesis show that the observed difference is caused by the fact that maximum entropy models include regularization techniques and the versions of logistic regression compared do not. Once regularization has been added to the logistic regression using a penalization procedure, the differences in model performance disappear. Therefore, penalized logistic regression may be considered one of the best performing methods to model species distributions. Usually, species distribution models do not consider soil related predictors because direct measurements of the chemical or physical properties are often lacking. The inclusion of coarse grained soil data from national or continental soil maps could be a reasonable alternative. The results of this Thesis suggest that the performance of the models slightly increase after including soil predictors form coarse grained soil maps. Model validation is a key stage of the development of empirical models, such as species distribution models. The usual way of validating is based on the evaluation of model performance for each species separately, i.e., comparing observed species presences or absence to predicted probabilities in a set of sites. This kind of evaluation is not informative for a common question in ecological restoration projects: which n species are the most suitable for the environment of the site to be restored? A method has been proposed to address this question that estimates the ability of a set of models to discriminate among present and absent species in a evaluation site. The method has been successfully applied to the validation of 188 species distribution models used to support decisions on species selection for ecological restoration in Spain. The proposed methodological approaches improve the predictive performance of the predictive models applied to species selection in ecological restoration and increase the number of species for which a model that supports decisions can be fitted.

Parallel workflows to personalize clinical guidelines recommendations: application to gestational diabetes mellitus

The MobiGuide system provides patients with personalized decision support tools, based on computerized clinical guidelines, in a mobile environment. The generic capabilities of the system will be demonstrated applied to the clinical domain of Gestational Diabetes (GD). This paper presents a methodology to identify personalized recommendations, obtained from the analysis of the GD guideline. We added a conceptual parallel part to the formalization of the GD guideline called "parallel workflow" that allows considering patient?s personal context and preferences. As a result of analysing the GD guideline and eliciting medical knowledge, we identified three different types of personalized advices (therapy, measurements and upcoming events) that will be implemented to perform patients? guiding at home, supported by the MobiGuide system. These results will be essential to determine the distribution of functionalities between mobile and server decision support capabilities.

Applications of Formal Languages to Management of Manned and Unmanned Aircraft

En el futuro, la gestión del tráfico aéreo (ATM, del inglés air traffic management) requerirá un cambio de paradigma, de la gestión principalmente táctica de hoy, a las denominadas operaciones basadas en trayectoria. Un incremento en el nivel de automatización liberará al personal de ATM —controladores, tripulación, etc.— de muchas de las tareas que realizan hoy. Las personas seguirán siendo el elemento central en la gestión del tráfico aéreo del futuro, pero lo serán mediante la gestión y toma de decisiones. Se espera que estas dos mejoras traigan un incremento en la eficiencia de la gestión del tráfico aéreo que permita hacer frente al incremento previsto en la demanda de transporte aéreo. Para aplicar el concepto de operaciones basadas en trayectoria, el usuario del espacio aéreo (la aerolínea, piloto, u operador) y el proveedor del servicio de navegación aérea deben negociar las trayectorias mediante un proceso de toma de decisiones colaborativo. En esta negociación, es necesaria una forma adecuada de compartir dichas trayectorias. Compartir la trayectoria completa requeriría un gran ancho de banda, y la trayectoria compartida podría invalidarse si cambiase la predicción meteorológica. En su lugar, podría compartirse una descripción de la trayectoria independiente de las condiciones meteorológicas, de manera que la trayectoria real se pudiese calcular a partir de dicha descripción. Esta descripción de la trayectoria debería ser fácil de procesar usando un programa de ordenador —ya que parte del proceso de toma de decisiones estará automatizado—, pero también fácil de entender para un operador humano —que será el que supervise el proceso y tome las decisiones oportunas—. Esta tesis presenta una serie de lenguajes formales que pueden usarse para este propósito. Estos lenguajes proporcionan los medios para describir trayectorias de aviones durante todas las fases de vuelo, desde la maniobra de push-back (remolcado hasta la calle de rodaje), hasta la llegada a la terminal del aeropuerto de destino. También permiten describir trayectorias tanto de aeronaves tripuladas como no tripuladas, incluyendo aviones de ala fija y cuadricópteros. Algunos de estos lenguajes están estrechamente relacionados entre sí, y organizados en una jerarquía. Uno de los lenguajes fundamentales de esta jerarquía, llamado aircraft intent description language (AIDL), ya había sido desarrollado con anterioridad a esta tesis. Este lenguaje fue derivado de las ecuaciones del movimiento de los aviones de ala fija, y puede utilizarse para describir sin ambigüedad trayectorias de este tipo de aeronaves. Una variante de este lenguaje, denominada quadrotor AIDL (QR-AIDL), ha sido desarrollada en esta tesis para permitir describir trayectorias de cuadricópteros con el mismo nivel de detalle. Seguidamente, otro lenguaje, denominado intent composite description language (ICDL), se apoya en los dos lenguajes anteriores, ofreciendo más flexibilidad para describir algunas partes de la trayectoria y dejar otras sin especificar. El ICDL se usa para proporcionar descripciones genéricas de maniobras comunes, que después se particularizan y combinan para formar descripciones complejas de un vuelo. Otro lenguaje puede construirse a partir del ICDL, denominado flight intent description language (FIDL). El FIDL especifica requisitos de alto nivel sobre las trayectorias —incluyendo restricciones y objetivos—, pero puede utilizar características del ICDL para proporcionar niveles de detalle arbitrarios en las distintas partes de un vuelo. Tanto el ICDL como el FIDL han sido desarrollados en colaboración con Boeing Research & Technology Europe (BR&TE). También se ha desarrollado un lenguaje para definir misiones en las que interactúan varias aeronaves, el mission intent description language (MIDL). Este lenguaje se basa en el FIDL y mantiene todo su poder expresivo, a la vez que proporciona nuevas semánticas para describir tareas, restricciones y objetivos relacionados con la misión. En ATM, los movimientos de un avión en la superficie de aeropuerto también tienen que ser monitorizados y gestionados. Otro lenguaje formal ha sido diseñado con este propósito, llamado surface movement description language (SMDL). Este lenguaje no pertenece a la jerarquía de lenguajes descrita en el párrafo anterior, y se basa en las clearances (autorizaciones del controlador) utilizadas durante las operaciones en superficie de aeropuerto. También proporciona medios para expresar incertidumbre y posibilidad de cambios en las distintas partes de la trayectoria. Finalmente, esta tesis explora las aplicaciones de estos lenguajes a la predicción de trayectorias y a la planificación de misiones. El concepto de trajectory language processing engine (TLPE) se usa en ambas aplicaciones. Un TLPE es una función de ATM cuya principal entrada y salida se expresan en cualquiera de los lenguajes incluidos en la jerarquía descrita en esta tesis. El proceso de predicción de trayectorias puede definirse como una combinación de TLPEs, cada uno de los cuales realiza una pequeña sub-tarea. Se le ha dado especial importancia a uno de estos TLPEs, que se encarga de generar el perfil horizontal, vertical y de configuración de la trayectoria. En particular, esta tesis presenta un método novedoso para la generación del perfil vertical. El proceso de planificar una misión también se puede ver como un TLPE donde la entrada se expresa en MIDL y la salida consiste en cierto número de trayectorias —una por cada aeronave disponible— descritas utilizando FIDL. Se ha formulado este problema utilizando programación entera mixta. Además, dado que encontrar caminos óptimos entre distintos puntos es un problema fundamental en la planificación de misiones, también se propone un algoritmo de búsqueda de caminos. Este algoritmo permite calcular rápidamente caminos cuasi-óptimos que esquivan todos los obstáculos en un entorno urbano. Los diferentes lenguajes formales definidos en esta tesis pueden utilizarse como una especificación estándar para la difusión de información entre distintos actores de la gestión del tráfico aéreo. En conjunto, estos lenguajes permiten describir trayectorias con el nivel de detalle necesario en cada aplicación, y se pueden utilizar para aumentar el nivel de automatización explotando esta información utilizando sistemas de soporte a la toma de decisiones. La aplicación de estos lenguajes a algunas funciones básicas de estos sistemas, como la predicción de trayectorias, han sido analizadas. ABSTRACT Future air traffic management (ATM) will require a paradigm shift from today’s mainly tactical ATM to trajectory-based operations (TBOs). An increase in the level of automation will also relieve humans —air traffic control officers (ATCOs), flight crew, etc.— from many of the tasks they perform today. Humans will still be central in this future ATM, as decision-makers and managers. These two improvements (TBOs and increased automation) are expected to provide the increase in ATM performance that will allow coping with the expected increase in air transport demand. Under TBOs, trajectories are negotiated between the airspace user (an airline, pilot, or operator) and the air navigation service provider (ANSP) using a collaborative decision making (CDM) process. A suitable method for sharing aircraft trajectories is necessary for this negotiation. Sharing a whole trajectory would require a high amount of bandwidth, and the shared trajectory might become invalid if the weather forecast changed. Instead, a description of the trajectory, decoupled from the weather conditions, could be shared, so that the actual trajectory could be computed from this trajectory description. This trajectory description should be easy to process using a computing program —as some of the CDM processes will be automated— but also easy to understand for a human operator —who will be supervising the process and making decisions. This thesis presents a series of formal languages that can be used for this purpose. These languages provide the means to describe aircraft trajectories during all phases of flight, from push back to arrival at the gate. They can also describe trajectories of both manned and unmanned aircraft, including fixedwing and some rotary-wing aircraft (quadrotors). Some of these languages are tightly interrelated and organized in a language hierarchy. One of the key languages in this hierarchy, the aircraft intent description language (AIDL), had already been developed prior to this thesis. This language was derived from the equations of motion of fixed-wing aircraft, and can provide an unambiguous description of fixed-wing aircraft trajectories. A variant of this language, the quadrotor AIDL (QR-AIDL), is developed in this thesis to allow describing a quadrotor aircraft trajectory with the same level of detail. Then, the intent composite description language (ICDL) is built on top of these two languages, providing more flexibility to describe some parts of the trajectory while leaving others unspecified. The ICDL is used to provide generic descriptions of common aircraft manoeuvres, which can be particularized and combined to form complex descriptions of flight. Another language is built on top of the ICDL, the flight intent description language (FIDL). The FIDL specifies high-level requirements on trajectories —including constraints and objectives—, but can use features of the ICDL to provide arbitrary levels of detail in different parts of the flight. The ICDL and FIDL have been developed in collaboration with Boeing Research & Technology Europe (BR&TE). Also, the mission intent description language (MIDL) has been developed to allow describing missions involving multiple aircraft. This language is based on the FIDL and keeps all its expressive power, while it also provides new semantics for describing mission tasks, mission objectives, and constraints involving several aircraft. In ATM, the movement of aircraft while on the airport surface also has to be monitored and managed. Another formal language has been designed for this purpose, denoted surface movement description language (SMDL). This language does not belong to the language hierarchy described above, and it is based on the clearances used in airport surface operations. Means to express uncertainty and mutability of different parts of the trajectory are also provided. Finally, the applications of these languages to trajectory prediction and mission planning are explored in this thesis. The concept of trajectory language processing engine (TLPE) is used in these two applications. A TLPE is an ATM function whose main input and output are expressed in any of the languages in the hierarchy described in this thesis. A modular trajectory predictor is defined as a combination of multiple TLPEs, each of them performing a small subtask. Special attention is given to the TLPE that builds the horizontal, vertical, and configuration profiles of the trajectory. In particular, a novel method for the generation of the vertical profile is presented. The process of planning a mission can also be seen as a TLPE, where the main input is expressed in the MIDL and the output consists of a number of trajectory descriptions —one for each aircraft available in the mission— expressed in the FIDL. A mixed integer linear programming (MILP) formulation for the problem of assigning mission tasks to the available aircraft is provided. In addition, since finding optimal paths between locations is a key problem to mission planning, a novel path finding algorithm is presented. This algorithm can compute near-shortest paths avoiding all obstacles in an urban environment in very short times. The several formal languages described in this thesis can serve as a standard specification to share trajectory information among different actors in ATM. In combination, these languages can describe trajectories with the necessary level of detail for any application, and can be used to increase automation by exploiting this information using decision support tools (DSTs). Their applications to some basic functions of DSTs, such as trajectory prediction, have been analized.

Modelling a biomass supply chain through discrete-event simulation

The organizational structure of the companies in the biomass energy sector, regarding the supply chain management services, can be greatly improved through the use of software decision support tools. These tools should be able to provide real-time alternative scenarios when deviations from the initial production plans are observed. To make this possible it is necessary to have representative production chain process models where several scenarios and solutions can be evaluated accurately. Due to its nature, this type of process is more adequately represented by means of event-based models. In particular, this work presents the modelling of a typical biomass production chain using the computing platform SIMEVENTS. Throughout the article details about the conceptual model, as well as simulation results, are provided

San Antonio Alcohol Safety Action Project - analytic study no. 5-6: analysis of PDE and rehabilitation. Final report.

National Highway Traffic Safety Administration, Washington, D.C.

Grasshopper integrated pest management handbook.

Title on disk: Hopper.

Healthy waterways: Healthy catchments - An integrated research/management program to understand and reduce impacts of sediments and nutrients on waterways in Queensland, Australia

The Moreton Bay Waterways and Catchments Partnership, now branded the Healthy Waterways Partnership, has built on the experience of the past 15 years here in South East Queensland (SEQ). It focuses on water quality and the ecosystem health of our freshwater, estuarine and marine systems through the implementation of actions by individual partners and the collective oversight of a regional work program that assists partners to prioritise their investments and address emerging issues. This regional program includes monitoring, reporting, marketing and communication, development of decision support tools, research that is directed to problem solving, and maintaining extensive consultative and engagement arrangements. The Partnership has produced information-based outcomes which have led to significant cost savings in the protection of water quality and ecosystem resources by its stakeholders. This has been achieved by: – providing a clear focus for management actions that has ownership of governments, industry and community; – targeted scientific research to address issues requiring appropriate management actions; – management actions based on a sound understanding of the waterways and rigorous public consultation; and, – development and implementation of a strategy that incorporates commitments from all levels of stakeholders. While focusing on our waterways, the Partnership’s approach includes addressing catchment management issues particularly relating to the management of diffuse pollution sources in both urban and rural landscapes as well as point source loads. We are now working with other stakeholders to develop a framework for integrated water management that will link water quality and water quantity goals and priorities.

To link or not to link: a test of the case linkage principles using serial car theft data

The purpose of the present study is to test the case linkage principles of behavioural consistency and behavioural distinctiveness using serial vehicle theft data. Data from 386 solved vehicle thefts committed by 193 offenders were analysed using Jaccard's, regression and Receiver Operating Characteristic analyses to determine whether objectively observable aspects of crime scene behaviour could be used to distinguish crimes committed by the same offender from those committed by different offenders. The findings indicate that spatial behaviour, specifically the distance between theft locations and between dump locations, is a highly consistent and distinctive aspect of vehicle theft behaviour; thus, intercrime and interdump distance represent the most useful aspects of vehicle theft for the purpose of case linkage analysis. The findings have theoretical and practical implications for understanding of criminal behaviour and for the development of decision-support tools to assist police investigation and apprehension of serial vehicle theft offenders.

Trajectory prediction uncertainty modelling for Air Traffic Management

The anticipated growth of air traffic worldwide requires enhanced Air Traffic Management (ATM) technologies and procedures to increase the system capacity, efficiency, and resilience, while reducing environmental impact and maintaining operational safety. To deal with these challenges, new automation and information exchange capabilities are being developed through different modernisation initiatives toward a new global operational concept called Trajectory Based Operations (TBO), in which aircraft trajectory information becomes the cornerstone of advanced ATM applications. This transformation will lead to higher levels of system complexity requiring enhanced Decision Support Tools (DST) to aid humans in the decision making processes. These will rely on accurate predicted aircraft trajectories, provided by advanced Trajectory Predictors (TP). The trajectory prediction process is subject to stochastic effects that introduce uncertainty into the predictions. Regardless of the assumptions that define the aircraft motion model underpinning the TP, deviations between predicted and actual trajectories are unavoidable. This thesis proposes an innovative method to characterise the uncertainty associated with a trajectory prediction based on the mathematical theory of Polynomial Chaos Expansions (PCE). Assuming univariate PCEs of the trajectory prediction inputs, the method describes how to generate multivariate PCEs of the prediction outputs that quantify their associated uncertainty. Arbitrary PCE (aPCE) was chosen because it allows a higher degree of flexibility to model input uncertainty. The obtained polynomial description can be used in subsequent prediction sensitivity analyses thanks to the relationship between polynomial coefficients and Sobol indices. The Sobol indices enable ranking the input parameters according to their influence on trajectory prediction uncertainty. The applicability of the aPCE-based uncertainty quantification detailed herein is analysed through a study case. This study case represents a typical aircraft trajectory prediction problem in ATM, in which uncertain parameters regarding aircraft performance, aircraft intent description, weather forecast, and initial conditions are considered simultaneously. Numerical results are compared to those obtained from a Monte Carlo simulation, demonstrating the advantages of the proposed method. The thesis includes two examples of DSTs (Demand and Capacity Balancing tool, and Arrival Manager) to illustrate the potential benefits of exploiting the proposed uncertainty quantification method.

Introduction of African Swine Fever into the European Union through Illegal Importation of Pork and Pork Products

Transboundary animal diseases can have very severe socio-economic impacts when introduced into new regions. The history of disease incursions into the European Union suggests that initial outbreaks were often initiated by illegal importation of meat and derived products. The European Union would benefit from decision-support tools to evaluate the risk of disease introduction caused by illegal imports in order to inform its surveillance strategy. However, due to the difficulty in quantifying illegal movements of animal products, very few studies of this type have been conducted. Using African swine fever as an example, this work presents a novel risk assessment framework for disease introduction into the European Union through illegal importation of meat and products. It uses a semi-quantitative approach based on factors that likely influence the likelihood of release of contaminated smuggled meat and products, and subsequent exposure of the susceptible population. The results suggest that the European Union is at non-negligible risk of African swine fever.

SADA and DESYRE DSSs descriptive classification criteria (main issues related to DSS's)

Brownfield rehabilitation is an essential step for sustainable land-use planning and management in the European Union. In brownfield regeneration processes, the legacy contamination plays a significant role, firstly because of the persistent contaminants in soil or groundwater which extends the existing hazards and risks well into the future; and secondly, problems from historical contamination are often more difficult to manage than contamination caused by new activities. Due to the complexity associated with the management of brownfield site rehabilitation, Decision Support Systems (DSSs) have been developed to support problem holders and stakeholders in the decision-making process encompassing all phases of the rehabilitation. This paper presents a comparative study between two DSSs, namely SADA (Spatial Analysis and Decision Assistance) and DESYRE (Decision Support System for the Requalification of Contaminated Sites), with the main objective of showing the benefits of using DSSs to introduce and process data and then to disseminate results to different stakeholders involved in the decision-making process. For this purpose, a former car manufacturing plant located in the Brasov area, Central Romania, contaminated chiefly by heavy metals and total petroleum hydrocarbons, has been selected as a case study to apply the two examined DSSs. Major results presented here concern the analysis of the functionalities of the two DSSs in order to identify similarities, differences and complementarities and, thus, to provide an indication of the most suitable integration options.

Organizational maintenance repair parts and special tools lists : concrete - mobile mixer, body M919, model 8CM - 24/F, NSN 3895-01-028-4391.

Includes index.

Sustainable urban metabolism as a link between bio-physical sciences and urban planning: the BRIDGE project

Urban metabolism considers a city as a system with flows of energy and material between it and the environment. Recent advances in bio-physical sciences provide methods and models to estimate local scale energy, water, carbon and pollutant fluxes. However, good communication is required to provide this new knowledge and its implications to endusers (such as urban planners, architects and engineers). The FP7 project BRIDGE (sustainaBle uRban plannIng Decision support accountinG for urban mEtabolism) aimed to address this gap by illustrating the advantages of considering these issues in urban planning. The BRIDGE Decision Support System (DSS) aids the evaluation of the sustainability of urban planning interventions. The Multi Criteria Analysis approach adopted provides a method to cope with the complexity of urban metabolism. In consultation with targeted end-users, objectives were defined in relation to the interactions between the environmental elements (fluxes of energy, water, carbon and pollutants) and socioeconomic components (investment costs, housing, employment, etc.) of urban sustainability. The tool was tested in five case study cities: Helsinki, Athens, London, Florence and Gliwice; and sub-models were evaluated using flux data selected. This overview of the BRIDGE project covers the methods and tools used to measure and model the physical flows, the selected set of sustainability indicators, the methodological framework for evaluating urban planning alternatives and the resulting DSS prototype.