Final year project: students and instructors perceptions as a competence-strengthening tool for engineering students

This work indicates the importance of the Final Year Project (FYP) in the strengthening of competences of engineering students. The study also shows which personal competences of students are reinforced most during the FYP process,including the preparation, elaboration, presentation and defence stages. In order to gather information on this subject, a survey was conducted at two different Spanish technical universities—one public and one private—and a comparative analysis was performed of the questionnaires collected. The competence model considered is that used by the Accreditation Board for Engineering and Technology (ABET), since the official title of the public university has been accredited by this model. The results indicate which personal and professional competences of students are reinforced well by undertaking the FYP. Any significant differences in response by university are explained in the study. For validation purposes, the results were contrasted with the instructor’s perspective using the triangulation methodology. Finally, the conclusions drawn will permit the design of new study plans to cope more effectively with the challenges of the FYP in the new Bologna framework.

Benchmarking for stability evaluation of computer systems

In this paper we propose a new benchmark to drive making decisions in maintenance of computer systems. This benchmark is made from load average sample data. The main goal is to improve reliability and performance of a set of devices or components. In particular, the stability of the system is measured in terms of variability of the load. A forecast of the behavior of this stability is also proposal as part of the reporting benchmark. At the final stage, a more stable system is obtained and its global reliability and performance can be then evaluated by means of appropriate specifications.

Brain injury MRI simulator based on theoretical models of neuroanatomic damage

In order to improve the body of knowledge about brain injury impairment is essential to develop image database with different types of injuries. This paper proposes a new methodology to model three types of brain injury: stroke, tumor and traumatic brain injury; and implements a system to navigate among simulated MRI studies. These studies can be used on research studies, to validate new processing methods and as an educational tool, to show different types of brain injury and how they affect to neuroanatomic structures.

Some developments on cup anemometer aerodynamics

In the present study the geometry of cups is experimentally studied through anemometer performance. This performance is analyzed in two different ways. On the one hand the anemometer transfer function between cases is compared. On the other hand the stationary rotation speed is decomposed into constant and harmonic terms, the comparison being established between the last ones. Results indicate that some cup shapes can improve the uniformity of anemometer rotation, this fact being important to reduce degradation due to ageing.

Active Learning and Dynamic Pricing Policies

In this paper, we address the problem of dynamic pricing to optimize the revenue coming from the sales of a limited inventory in a finite time-horizon. A priori, the demand is assumed to be unknown. The seller must learn on the fly. We first deal with the simplest case, involving only one class of product for sale. Furthermore the general situation is considered with a finite number of product classes for sale. In particular, a case in point is the sale of tickets for events related to culture and leisure; in this case, typically the tickets are sold months before the event, thus, uncertainty over actual demand levels is a very a common occurrence. We propose a heuristic strategy of adaptive dynamic pricing, based on experience gained from the past, taking into account, for each time period, the available inventory, the time remaining to reach the horizon, and the profit made in previous periods. In the computational simulations performed, the demand is updated dynamically based on the prices being offered, as well as on the remaining time and inventory. The simulations show a significant profit over the fixed-price strategy, confirming the practical usefulness of the proposed strategy. We develop a tool allowing us to test different dynamic pricing strategies designed to fit market conditions and seller s objectives, which will facilitate data analysis and decision-making in the face of the problem of dynamic pricing.

Win-win transport strategies: searching for sinergies

In order to achieve to minimize car-based trips, transport planners have been particularly interested in understanding the factors that explain modal choices. In the transport modelling literature there has been an increasing awareness 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 deal. In this paper, factorial and path analyses through a Multiple-Indicator Multiple-Cause (MIMIC) model are used to understand and describe the relationship between the different psychological and environmental constructs with social influence and socioeconomic variables. The MIMIC model generates Latent Variables (LVs) to be incorporated sequentially into Discrete Choice Models (DCM) where the levels of service and cost attributes of travel modes are also included directly to measure the effect of the transport policies that have been introduced in Madrid during the last three years in the context of the economic crisis. The data used for this paper are collected from a two panel smartphone-based survey (n=255 and 190 respondents, respectively) of Madrid.

Cálculo de pilas con aparatos de apoyo tipo POT y tablero con punto fijo

In recent years a great number of high speed railway bridges have been constructed within the Spanish borders. Due to the demanding high speed trains route's geometrical requirements, bridges frequently show remarkable lengths. This fact is the main reason why railway bridges are overall longer than roadway bridges. In the same line, it is also worth highlighting the importance of high speed trains braking forces compared to vehicles. While vehicles braking forces can be tackled easily, the railway braking forces demand the existence of a fixed-point. It is generally located at abutments where the no-displacements requirement can be more easily achieved. In some other cases the fixed-point is placed in one of the interior columns. As a consequence of these bridges' length and the need of a fixed-point, temperature, creep and shrinkage strains lead to fairly significant deck displacements, which become greater with the distance to the fixed-point. These displacements need to be accommodated by the piers and bearings deformation. Regular elastomeric bearings are not able to allow such displacements and therefore are not suitable for this task. For this reason, the use of sliding PTFE POT bearings has been an extensive practice mainly because they permit sliding with low friction. This is not the only reason of the extensive use of these bearings to high-speed railways bridges. The value of the vertical loads at each bent is significantly higher than in roadway bridges. This is so mainly because the live loads due to trains traffic are much greater than vehicles. Thus, gravel rails foundation represents a non-negligible permanent load at all. All this together increases the value of vertical loads to be withstood. This high vertical load demand discards the use of conventional bearings for excessive compressions. The PTFE POT bearings' higher technology allows to accommodate this level of compression thanks to their design. The previously explained high-speed railway bridge configuration leads to a key fact regarding longitudinal horizontal loads (such as breaking forces) which is the transmission of these loads entirely to the fixed-point alone. Piers do not receive these longitudinal horizontal loads since PTFE POT bearings displayed are longitudinally free-sliding. This means that longitudinal horizontal actions on top of piers will not be forces but imposed displacements. This feature leads to the need to approach these piers design in a different manner that when piers are elastically linked to superstructure, which is the case of elastomeric bearings. In response to the previous, the main goal of this Thesis is to present a Design Method for columns displaying either longitudinally fixed POT bearings or longitudinally free PTFE POT bearings within bridges with fixed-point deck configuration, applicable to railway and road vehicles bridges. The method was developed with the intention to account for all major parameters that play a role in these columns behavior. The long process that has finally led to the method's formulation is rooted in the understanding of these column's behavior. All the assumptions made to elaborate the formulations contained in this method have been made in benefit of conservatives results. The singularity of the analysis of columns with this configuration is due to a combination of different aspects. One of the first steps of this work was to study they of these design aspects and understand the role each plays in the column's response. Among these aspects, special attention was dedicated to the column's own creep due to permanent actions such us rheological deck displacements, and also to the longitudinally guided PTFE POT bearings implications in the design of the column. The result of this study is the Design Method presented in this Thesis, that allows to work out a compliant vertical reinforcement distribution along the column. The design of horizontal reinforcement due to shear forces is not addressed in this Thesis. The method's formulations are meant to be applicable to the greatest number of cases, leaving to the engineer judgement many of the different parameters values. In this regard, this method is a helpful tool for a wide range of cases. The widespread use of European standards in the more recent years, in particular the so-called Eurocodes, has been one of the reasons why this Thesis has been developed in accordance with Eurocodes. Same trend has been followed for the bearings design implications, which are covered by the rather recent European code EN-1337. One of the most relevant aspects that this work has taken from the Eurocodes is the non-linear calculations security format. The biaxial bending simplified approach that shows the Design Method presented in this work also lies on Eurocodes recommendations. The columns under analysis are governed by a set of dimensionless parameters that are presented in this work. The identification of these parameters is a helpful for design purposes for two columns with identical dimensionless parameters may be designed together. The first group of these parameters have to do with the cross-sectional behavior, represented in the bending-curvature diagrams. A second group of parameters define the columns response. Thanks to this identification of the governing dimensionless parameters, it has been possible what has been named as Dimensionless Design Curves, which basically allows to obtain in a reduced time a preliminary vertical reinforcement column distribution. These curves are of little use nowadays, firstly because each family of curves refer to specific values of many different parameters and secondly because the use of computers allows for extremely quick and accurate calculations.

Automatic design of Ant Colony Optimization for permutation problems

In this study, we present a framework based on ant colony optimization (ACO) for tackling combinatorial problems. ACO algorithms have been applied to many diferent problems, focusing on algorithmic variants that obtain high-quality solutions. Usually, the implementations are re-done for various problem even if they maintain the same details of the ACO algorithm. However, our goal is to generate a sustainable framework for applications on permutation problems. We concentrate on understanding the behavior of pheromone trails and specific methods that can be combined. Eventually, we will propose an automatic offline configuration tool to build an efective algorithm. ---RESUMEN---En este trabajo vamos a presentar un framework basado en la familia de algoritmos ant colony optimization (ACO), los cuales están dise~nados para enfrentarse a problemas combinacionales. Los algoritmos ACO han sido aplicados a diversos problemas, centrándose los investigadores en diversas variantes que obtienen buenas soluciones. Normalmente, las implementaciones se tienen que rehacer, inclusos si se mantienen los mismos detalles para los algoritmos ACO. Sin embargo, nuestro objetivo es generar un framework sostenible para aplicaciones sobre problemas de permutaciones. Nos centraremos en comprender el comportamiento de la sendas de feromonas y ciertos métodos con los que pueden ser combinados. Finalmente, propondremos una herramienta para la configuraron automática offline para construir algoritmos eficientes.

How varies optimal welfare pricing with income distribution? The case of the untolled alternative.

In some countries, such as Spain, it is very common that in the same corridor there are two roads with the same origin and destination but with some differences. The most important contrast is that one is a toll highway which offers a better quality than the parallel road in exchange of a price. The users decide if the price of the toll is worth to pay for the advantages offered. This problem is known as the untolled alternative and it has been largely studied in the academic literature, particularly related to economic efficiency and the optimal welfare toll. However, there is a gap in the literature academic regarding how it affects income distribution to the optimal toll. The main objective of the paper is to fill this gap. In this paper a theoretical model in order to obtain the optimal welfare price in a toll highway that competes for capturing the traffic with a conventional road is developed. This model is done for non-usual users who decide over the expectation of free flow conditions. This model is finally applied to the variables we want to focus on: average value of travel time (VTT) which is strongly related with income, dispersion of this VTT and traffic levels, from free flow to congestion. Derived from the results, we conclude that the higher the average VTT the higher the optimal price, the higher the dispersion of this VTT the lower the optimal price and finally, the more the traffic the higher the optimal toll.

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.

On a two species chemotaxis model with slow chemical diffucion.

In this paper we consider a system of three parabolic equations modeling the behavior of two biological species moving attracted by a chemical factor. The chemical substance verifies a parabolic equation with slow diffusion. The system contains second order terms in the first two equations modeling the chemotactic effects. We apply an iterative method to obtain the global existence of solutions using that the total mass of the biological species is conserved. The stability of the homogeneous steady states is studied by using an energy method. A final example is presented to illustrate the theoretical results.

Bayesian model selection of structural explanatory models.

In this study we are proposing a Bayesian model selection methodology, where the best model from the list of candidate structural explanatory models is selected. The model structure is based on the Zellner's (1971)explanatory model with autoregressive errors. For the selection technique we are using a parsimonious model, where the model variables are transformed using Box and Cox (1964) class of transformations.

Structures subjected to Human Actions

In this paper we present the tests on a structure designed to be a gymnasium, which has natural frequencies within that range. In these tests the gym slab was instrumented with acceleration sensors and different people jumped on a force plate installed on the floor. The test results have been compared with predictions based on the two existing load modelling alternatives (Sim and SCI Guide) and two new methodologies for modelling jumping loads has been proposed. The results of the force plate trials were analysed in an attempt to better characterize the profile of the jump force and determine how best to approximate it. In the first proposed methodology the study is carried out in the frequency domain using an average power spectral density of the jumps. In the second proposed methodology, the jump force is decomposed into the summation of one peak with a large period and a number of peaks with smaller periods. Utilizing a similar model to that of the Sim model, the approximation will still be comprised of the summation of two quadratic cosine functions.

Analysis of Meshfree Methods for Lagrangian Fluid-Structure Interaction

In this dissertation a new numerical method for solving Fluid-Structure Interaction (FSI) problems in a Lagrangian framework is developed, where solids of different constitutive laws can suffer very large deformations and fluids are considered to be newtonian and incompressible. For that, we first introduce a meshless discretization based on local maximum-entropy interpolants. This allows to discretize a spatial domain with no need of tessellation, avoiding the mesh limitations. Later, the Stokes flow problem is studied. The Galerkin meshless method based on a max-ent scheme for this problem suffers from instabilities, and therefore stabilization techniques are discussed and analyzed. An unconditionally stable method is finally formulated based on a Douglas-Wang stabilization. Then, a Langrangian expression for fluid mechanics is derived. This allows us to establish a common framework for fluid and solid domains, such that interaction can be naturally accounted. The resulting equations are also in the need of stabilization, what is corrected with an analogous technique as for the Stokes problem. The fully Lagrangian framework for fluid/solid interaction is completed with simple point-to-point and point-to-surface contact algorithms. The method is finally validated, and some numerical examples show the potential scope of applications.

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.