Aerial Coverage Path Planning applied to Mapping

In the last decade we have seen how small and light weight aerial platforms - aka, Mini Unmanned Aerial Vehicles (MUAV) - shipped with heterogeneous sensors have become a 'most wanted' Remote Sensing (RS) tool. Most of the off-the-shelf aerial systems found in the market provide way-point navigation. However, they do not rely on a tool that compute the aerial trajectories considering all the aspects that allow optimizing the aerial missions. One of the most demanded RS applications of MUAV is image surveying. The images acquired are typically used to build a high-resolution image, i.e., a mosaic of the workspace surface. Although, it may be applied to any other application where a sensor-based map must be computed. This thesis provides a study of this application and a set of solutions and methods to address this kind of aerial mission by using a fleet of MUAVs. In particular, a set of algorithms are proposed for map-based sampling, and aerial coverage path planning (ACPP). Regarding to map-based sampling, the approaches proposed consider workspaces with different shapes and surface characteristics. The workspace is sampled considering the sensor characteristics and a set of mission requirements. The algorithm applies different computational geometry approaches, providing a unique way to deal with workspaces with different shape and surface characteristics in order to be surveyed by one or more MUAVs. This feature introduces a previous optimization step before path planning. After that, the ACPP problem is theorized and a set of ACPP algorithms to compute the MUAVs trajectories are proposed. The problem addressed herein is the problem to coverage a wide area by using MUAVs with limited autonomy. Therefore, the mission must be accomplished in the shortest amount of time. The aerial survey is usually subject to a set of workspace restrictions, such as the take-off and landing positions as well as a safety distance between elements of the fleet. Moreover, it has to avoid forbidden zones to y. Three different algorithms have been studied to address this problem. The approaches studied are based on graph searching, heuristic and meta-heuristic approaches, e.g., mimic, evolutionary. Finally, an extended survey of field experiments applying the previous methods, as well as the materials and methods adopted in outdoor missions is presented. The reported outcomes demonstrate that the findings attained from this thesis improve ACPP mission for mapping purpose in an efficient and safe manner.

SVD Applied to Voltage Sag State Estimation

The method presented in this paper addresses the problem of voltage sag state estimation (VSSE). The problem consists in estimating the voltage sags frequency at non-monitored buses from the number of sags measured at monitored sites. Usually, due to limitations on the number of available voltage sag monitors, this is an underdetermined problem. In this approach, the mathematical formulation presented is based on the fault positions concept and is solved by means of the Singular Value Decomposition (SVD) technique. The proposed estimation method has been validated by using the IEEE 118 test system and the results obtained have been very satisfactory.

Aerial Coverage Path Planning applied to Mapping

In the last decade we have seen how small and light weight aerial platforms - aka, Mini Unmanned Aerial Vehicles (MUAV) - shipped with heterogeneous sensors have become a 'most wanted' Remote Sensing (RS) tool. Most of the off-the-shelf aerial systems found in the market provide way-point navigation. However, they do not rely on a tool that compute the aerial trajectories considering all the aspects that allow optimizing the aerial missions. One of the most demanded RS applications of MUAV is image surveying. The images acquired are typically used to build a high-resolution image, i.e., a mosaic of the workspace surface. Although, it may be applied to any other application where a sensor-based map must be computed. This thesis provides a study of this application and a set of solutions and methods to address this kind of aerial mission by using a fleet of MUAVs. In particular, a set of algorithms are proposed for map-based sampling, and aerial coverage path planning (ACPP). Regarding to map-based sampling, the approaches proposed consider workspaces with different shapes and surface characteristics. The workspace is sampled considering the sensor characteristics and a set of mission requirements. The algorithm applies different computational geometry approaches, providing a unique way to deal with workspaces with different shape and surface characteristics in order to be surveyed by one or more MUAVs. This feature introduces a previous optimization step before path planning. After that, the ACPP problem is theorized and a set of ACPP algorithms to compute the MUAVs trajectories are proposed. The problem addressed herein is the problem to coverage a wide area by using MUAVs with limited autonomy. Therefore, the mission must be accomplished in the shortest amount of time. The aerial survey is usually subject to a set of workspace restrictions, such as the take-off and landing positions as well as a safety distance between elements of the fleet. Moreover, it has to avoid forbidden zones to y. Three different algorithms have been studied to address this problem. The approaches studied are based on graph searching, heuristic and meta-heuristic approaches, e.g., mimic, evolutionary. Finally, an extended survey of field experiments applying the previous methods, as well as the materials and methods adopted in outdoor missions is presented. The reported outcomes demonstrate that the findings attained from this thesis improve ACPP mission for mapping purpose in an efficient and safe manner.

Accurate Simulation of MPPT Methods Performance When Applied to Commercial Photovoltaic Panels

Anew, simple, and quick-calculationmethodology to obtain a solar panel model, based on the manufacturers’ datasheet, to perform MPPT simulations, is described. The method takes into account variations on the ambient conditions (sun irradiation and solar cells temperature) and allows fast MPPT methods comparison or their performance prediction when applied to a particular solar panel. The feasibility of the described methodology is checked with four different MPPT methods applied to a commercial solar panel, within a day, and under realistic ambient conditions.

State Convergence Theory Applied to a Delayed Teleoperation System

State convergence is a control strategy that was proposed in the early 2000s to ensure stability and transparency in a teleoperation system under specific control gains values. This control strategy has been implemented for a linear system with or without time delay. This paper represents the first attempt at demonstrating, theoretically and experimentantally, that this control strategy can also be applied to a nonlinear teleoperation system with n degrees of freedom and delay in the communication channel. It is assumed that the human operator applies a constant force on the local manipulator during the teleoperation. In addition, the interaction between the remote manipulator and the environment is considered passive. Communication between the local and remote sites is made by means of a communication channel with variable time delay. In this article the theory of Lyapunov-Krasovskii was used to demonstrate that the local-remote teleoperation system is asymptotically stable.

Cities Futures: A critical assessment of how future studies are applied to cities

Análisis critic de la aplicación de los estudios de future al campo de la planificación urbana

Dust tracking techniques applied to the STARDUST facility: First results

An important issue related to future nuclear fusion reactors fueled with deuterium and tritium is the creation of large amounts of dust due to several mechanisms (disruptions, ELMs and VDEs). The dust size expected in nuclear fusion experiments (such as ITER) is in the order of microns (between 0.1 and 1000 μm). Almost the total amount of this dust remains in the vacuum vessel (VV). This radiological dust can re-suspend in case of LOVA (loss of vacuum accident) and these phenomena can cause explosions and serious damages to the health of the operators and to the integrity of the device. The authors have developed a facility, STARDUST, in order to reproduce the thermo fluid-dynamic conditions comparable to those expected inside the VV of the next generation of experiments such as ITER in case of LOVA. The dust used inside the STARDUST facility presents particle sizes and physical characteristics comparable with those that created inside the VV of nuclear fusion experiments. In this facility an experimental campaign has been conducted with the purpose of tracking the dust re-suspended at low pressurization rates (comparable to those expected in case of LOVA in ITER and suggested by the General Safety and Security Report ITER-GSSR) using a fast camera with a frame rate from 1000 to 10,000 images per second. The velocity fields of the mobilized dust are derived from the imaging of a two-dimensional slice of the flow illuminated by optically adapted laser beam. The aim of this work is to demonstrate the possibility of dust tracking by means of image processing with the objective of determining the velocity field values of dust re-suspended during a LOVA.

Assessment methodology applied to demand measures to change urban mobility behavior

In order to minimize car-based trips, transport planners have been particularly interested in understanding the factors that explain modal choices. Transport modelling literature has been increasingly aware that socioeconomic attributes and quantitative variables are not sufficient to characterize travelers and forecast their travel behavior. Recent studies have also recognized that users’ social interactions and land use patterns influence travel behavior, especially when changes to transport systems are introduced; but links between international and Spanish perspectives are rarely dealt with. The overall objective of the thesis is to develop a stepped methodology that integrate diverse perspectives to evaluate the willingness to change patterns of urban mobility in Madrid, based on four steps: (1st) analysis of causal relationships between both objective and subjective personal variables, and travel behavior to capture pro-car and pro-public transport intentions; (2nd) exploring the potential influence of individual trip characteristics and social influence variables on transport mode choice; (3rd) identifying built environment dimensions on travel behavior; and (4th) exploring the potential influence on transport mode choice of extrinsic characteristics of individual trip using panel data, land use variables using spatial characteristics and social influence variables. The data used for this thesis have been collected from a two panel smartphone-based survey (n=255 and 190 respondents, respectively) carried out in Madrid. Although the steps above are mainly methodological, the application to the area of Madrid allows deriving important results that can be directly used to forecast travel demand and to evaluate the benefits of specific policies that might be implemented in the area. The results demonstrated, respectively: (1st) transport policy actions are more likely to be effective when pro-car intention has been disrupted first; (2nd) the consideration of “helped” and “voluntary” users as tested here could have a positive and negative impact, respectively, on the use of public transport; (3rd) the importance of density, design, diversity and accessibility underlying dimensions responsible for land use variables; and (4th) there are clearly different types of combinations of social interactions, land use and time frame on travel behavior studies. Finally, with the objective to study the impact of demand measures to change urban mobility behavior, those previous results have been considered in a unique way, a hybrid discrete choice model has been used on a 5th step. Then it can be concluded that urban mobility behavior is not only ruled by the maximum utility criterion, but also by a strong psychological-environment concept, developed without the mediation of cognitive processes during choice, i.e., many people using public transport on their way to work do not do it for utilitarian reasons, but because no other choice is available. Regarding built environment dimensions, the more diversity place of residence, the more difficult the use of public transport or walking.

Methodology proposal for the life cycle sustainability assessment applied to retrofitting in a local context

In the European context of upgrading the housing stock energy performance, multiple barriers hinder the wide uptake of sustainable retrofitting practices. Moreover, some of these may imply negative effects often disregarded. Policy makers need to identify how to increase and improve retrofitting practices from the comprehensive point of view of sustainability. None of the existing assessment tools addresses all the issues relevant for sustainable development in a local situation from a life cycle perspective. Life cycle sustainability assessment methodology, or LCSA, analyzes environmental and socioeconomic impacts. The environmental part is quite developed, but the socioeconomic aspect is still challenging. This work proposes socioeconomic criteria to be included in a LCSA to assess retrofitting works in the specific context of Brussels-Capital Region. LCSA feasibility and challenging methodology aspects are discussed.

Recent advances on dendrogeomorphological research applied to flood hazard analysis in Spain.

Estudios dendroecológicos para el análisis de regímentes torrenciales y avenidas

A group decision-making methodology with incomplete individual beliefs applied to e-Democracy

We consider the situation where there are several alternatives for investing a quantity of money to achieve a set of objectives. The choice of which alternative to apply depends on how citizens and political representatives perceive that such objectives should be achieved. All citizens with the right to vote can express their preferences in the decision-making process. These preferences may be incomplete. Political representatives represent the citizens who have not taken part in the decision-making process. The weight corresponding to political representatives depends on the number of citizens that have intervened in the decision-making process. The methodology we propose needs the participants to specify for each alternative how they rate the different attributes and the relative importance of attributes. On the basis of this information an expected utility interval is output for each alternative. To do this, an evidential reasoning approach is applied. This approach improves the insightfulness and rationality of the decision-making process using a belief decision matrix for problem modeling and the Dempster?Shafer theory of evidence for attribute aggregation. Finally, we propose using the distances of each expected utility interval from the maximum and the minimum utilities to rank the alternative set. The basic idea is that an alternative is ranked first if its distance to the maximum utility is the smallest, and its distance to the minimum utility is the greatest. If only one of these conditions is satisfied, a distance ratio is then used.

MedVir: an interactive representation system of multidimensional medical data applied to Traumatic Brain Injury's rehabilitation prediction

Clinicians could model the brain injury of a patient through his brain activity. However, how this model is defined and how it changes when the patient is recovering are questions yet unanswered. In this paper, the use of MedVir framework is proposed with the aim of answering these questions. Based on complex data mining techniques, this provides not only the differentiation between TBI patients and control subjects (with a 72% of accuracy using 0.632 Bootstrap validation), but also the ability to detect whether a patient may recover or not, and all of that in a quick and easy way through a visualization technique which allows interaction.

Two-dimensional direct rainfall hydraulic models applied to direct calculation of hydrologic events in dams to prevent overtopping

One of the main concerns when conducting a dam test is the acute determination of the hydrograph for a specific flood event. The use of 2D direct rainfall hydraulic mathematical models on a finite elements mesh, combined with the efficiency of vector calculus that provides CUDA (Compute Unified Device Architecture) technology, enables nowadays the simulation of complex hydrological models without the need for terrain subbasin and transit splitting (as in HEC-HMS). Both the Spanish PNOA (National Plan of Aereal Orthophotography) Digital Terrain Model GRID with a 5 x 5 m accuracy and the CORINE GIS Land Cover (Coordination of INformation of the Environment) that allows assessment of the ground roughness, provide enough data to easily build these kind of models

Proposal of a new indicator to define ductility applied to corroded steel reinforcement on concrete structures = Propuesta de un nuevo indicador para definir la ductilidad aplicada a la corrosión del acero de refuerzo en estructuras de hormigón

The carbonation of concrete or the chlorides ingress in such quantity to reach the level of bars is triggers of reinforcement corrosion. One of the most significant effects of reinforcing steel corrosion on reinforced concrete structures is the decline in the ductility-related properties of the steel. Reinforcement ductility has a decisive effect on the overall ductility of reinforced concrete structures. Different Codes classify the type of steel depending on their ductility defined by the minimum values of several parameters. Using indicators of ductility associating different properties can be advantageous on many occasions. It is considered necessary to define the ductility by means of a single parameter that considers strength values and deformation simultaneously. There are a number of criteria for defining steel ductility by a single parameter. The present experimental study addresses the variation in the ductility of concrete-embedded steel bars when exposed to accelerated corrosion. This paper analyzes the suitability of a new indicator of ductility used in corroded bars.

Advanced morphometric techniques applied to the study of human brain anatomy

El desarrollo de las técnicas de imágenes por resonancia magnética han permitido el estudio y cuantificación, in vivo, de los cambios que ocurren en la morfología cerebral ligados a procesos tales como el neurodesarrollo, el envejecimiento, el aprendizaje o la enfermedad. Un gran número de métodos de morfometría han sido desarrollados con el fin de extraer la información contenida en estas imágenes y traducirla en indicadores de forma o tamaño, tales como el volumen o el grosor cortical; marcadores que son posteriormente empleados para encontrar diferencias estadísticas entre poblaciones de sujetos o realizar correlaciones entre la morfología cerebral y, por ejemplo, la edad o la severidad de determinada enfermedad. A pesar de la amplia variedad de biomarcadores y metodologías de morfometría, muchos estudios sesgan sus hipótesis, y con ello los resultados experimentales, al empleo de un número reducido de biomarcadores o a al uso de una única metodología de procesamiento. Con el presente trabajo se pretende demostrar la importancia del empleo de diversos métodos de morfometría para lograr una mejor caracterización del proceso que se desea estudiar. En el mismo se emplea el análisis de forma para detectar diferencias, tanto globales como locales, en la morfología del tálamo entre pacientes adolescentes con episodios tempranos de psicosis y adolescentes sanos. Los resultados obtenidos demuestran que la diferencia de volumen talámico entre ambas poblaciones de sujetos, previamente descrita en la literatura, se debe a una reducción del volumen de la región anterior-mediodorsal y del núcleo pulvinar del tálamo de los pacientes respecto a los sujetos sanos. Además, se describe el desarrollo de un estudio longitudinal, en sujetos sanos, que emplea simultáneamente distintos biomarcadores para la caracterización y cuantificación de los cambios que ocurren en la morfología de la corteza cerebral durante la adolescencia. A través de este estudio se revela que el proceso de “alisado” que experimenta la corteza cerebral durante la adolescencia es consecuencia de una disminución de la profundidad, ligada a un incremento en el ancho, de los surcos corticales. Finalmente, esta metodología es aplicada, en un diseño transversal, para el estudio de las causas que provocan el decrecimiento tanto del grosor cortical como del índice de girificación en adolescentes con episodios tempranos de psicosis. ABSTRACT The ever evolving sophistication of magnetic resonance image techniques continue to provide new tools to characterize and quantify, in vivo, brain morphologic changes related to neurodevelopment, senescence, learning or disease. The majority of morphometric methods extract shape or size descriptors such as volume, surface area, and cortical thickness from the MRI image. These morphological measurements are commonly entered in statistical analytic approaches for testing between-group differences or for correlations between the morphological measurement and other variables such as age, sex, or disease severity. A wide variety of morphological biomarkers are reported in the literature. Despite this wide range of potentially useful biomarkers and available morphometric methods, the hypotheses and findings of the grand majority of morphological studies are biased because reports assess only one morphometric feature and usually use only one image processing method. Throughout this dissertation biomarkers and image processing strategies are combined to provide innovative and useful morphometric tools for examining brain changes during neurodevelopment. Specifically, a shape analysis technique allowing for a fine-grained assessment of regional thalamic volume in early-onset psychosis patients and healthy comparison subjects is implemented. Results show that disease-related reductions in global thalamic volume, as previously described by other authors, could be particularly driven by a deficit in the anterior-mediodorsal and pulvinar thalamic regions in patients relative to healthy subjects. Furthermore, in healthy adolescents different cortical features are extracted and combined and their interdependency is assessed over time. This study attempts to extend current knowledge of normal brain development, specifically the largely unexplored relationship between changes of distinct cortical morphological measurements during adolescence. This study demonstrates that cortical flattening, present during adolescence, is produced by a combination of age-related increase in sulcal width and decrease in sulcal depth. Finally, this methodology is applied to a cross-sectional study, investigating the mechanisms underlying the decrease in cortical thickness and gyrification observed in psychotic patients with a disease onset during adolescence.