Evaluación teórico experimental de la influencia de espumas de relleno metálicas como elementos de absorción de energía en perfiles tubulares de pequeño espesor. Su aplicación a vehículos para el transporte colectivo de personas

Los accidentes con implicación de autocares en los que se producen vuelcos ponen de manifiesto la especial agresividad de los mismos, como lo confirman las estadísticas. Como medida para mejorar la seguridad de los Vehículos de Grandes Dimensiones para el Transporte de Pasajeros (V.G.D.T.P.) frente a vuelco fue aprobado por las Naciones Unidas el Reglamento Nº 66 de Ginebra. Este reglamento establece los requisitos mínimos que las estructuras de los vehículos de grandes dimensiones deben cumplir con respecto a vuelco. El reglamento 66 ha supuesto un paso adelante muy importante en relación con la seguridad de los autocares, puesto que especifica por primera vez requerimientos estructurales a este tipo de vehículos, y en general ha supuesto una mejora del vehículo . Por otro lado, a consecuencia de la obligatoriedad de instalación de cinturones de seguridad, existe una unión entre pasajeros y vehículo, pero como no se trata de una unión rígida, hay que contemplar el porcentaje de la masa de los ocupantes que influye en la absorción de energía de la estructura. Además la retención de los ocupantes con cinturones de seguridad influye en la energía a absorber por la estructura del vehículo en dos aspectos, por un lado aumenta la masa del vehículo y en el otro se incrementa la altura el centro de gravedad. Esta situación a conducido a elaborar por parte de las Naciones Unidas la revisión 01 del Reglamento 66, en el que se considera que el 50 % de la masa total de los pasajeros posee una unión rígida con la estructura del vehículo, y por lo tanto debe ser tenida en cuenta si el vehículo posee sistemas de retención. En la situación actual, con limitaciones de peso del vehículo y peso por eje, los elementos de confort, seguridad y espacio para maleteros contribuyen a aumentar el peso del vehículo. Esto unido a la dificultad de introducción de cambios radicales en la concepción actual de fabricación de este tipo de vehículos por suponer unas pérdidas importantes para los fabricantes existentes, tanto en su conocimiento del producto como en su metodología de proceso, conlleva la necesidad cada vez más agobiante de analizar y evaluar otras alternativas estructurales que sin suponer grandes revoluciones a los productos actualmente en fabricación los complementen permitiendo adaptarse a los nuevos requerimientos en seguridad. Recientes desarrollos en la relación costo-beneficio de los procesos para la producción de materiales celulares metálicos de baja densidad, tales como las espumas metálicas, los posiciona como una alternativa de especial interés para la aplicación como elementos de absorción de energía para reforzar estructuras. El relleno con espumas metálicas puede ser más eficiente en términos de optimización de peso comparado con el aumento de espesor de los perfiles estructurales, dado que la absorción de energía se produce en una fracción relativamente pequeña de los perfiles, en las denominadas rótulas plásticas. La aplicación de espumas de relleno metálicas en estructuras de vehículos se está empezando a emplear en determinadas zonas de los vehículos de turismo, siendo totalmente novedosa cualquier intento de aplicación en estructuras de autobuses y autocares. Conforme a lo expuesto, y con el objeto de resolver estos problemas, se ha elaborado el presente trabajo de tesis doctoral, cuyos objetivos son: -Desarrollar un modelo matemático, que permita simular el ensayo de vuelco, considerando la influencia de los ocupantes retenidos con cinturones de seguridad para evaluar su influencia en la absorción de energía de la estructura. -Validar el modelo matemático de vuelco de la estructura mediante ensayos de secciones representativas de la estructura del vehículo y mediante el ensayo de un vehículo completo. -Realizar un estudio de las propiedades de las espumas metálicas que permitan incorporarlas como elemento de absorción de energía en el relleno de componentes de la superestructura de autobuses y autocares. -Desarrollar un modelo matemático para evaluar el aporte del relleno de espuma metálica en la absorción de energía ante solicitaciones por flexión estática y dinámica en componentes de la superestructura de autobuses o autocares. -Realizar un programa de ensayos a flexión estáticos y dinámicos para validar el modelo matemático del aporte del relleno de espuma metálica sobre componentes de la superestructura de autobuses y autocares. . -Incorporar al modelo matemático de vuelco de la estructura, los resultados obtenidos sobre componentes con relleno de espuma metálica, para evaluar el aporte en la absorción de energía. -Validar el modelo de vuelco de la estructura del autobús o autocar con relleno de espuma metálica, mediante ensayos de secciones de carrocería. ABSTRACT Accidents involving buses in which rollovers occur reveal the special aggressiveness thereof, as the statistics prove. As a measure to improve the safety of large vehicles for the transport of passengers to rollover, Regulation 66 of Geneva was approved by the United Nations. This regulation establishes the minimum requirements that structures of large vehicles must comply with respect to rollovers. The regulation 66 has been a major step forward in relation to the safety of coaches, since it specifies structural requirements to such vehicles and has been an improvement for the vehicle. In turn, as a result of compulsory installation of safety belts, there is contact between passengers and vehicle, but as it is not a rigid connection we must contemplate the percentage of the mass of the occupants that impacts on the energy absorption of the structure. Thus, the passengers’ restraining modifies the energy to absorb by the vehicle in two different aspects: On the one hand, it increases the vehicle weight and on the other the height of the center of gravity. This circumstance has taken the United Nations to elaborate Revision 01 of Regulation 66, in which it is considered that the 50 percent of passengers’ mass has a rigid joint together with the vehicle structure and, therefore, the passengers’ mass mentioned above should be highly considered if the vehicle has seat belts. In the present situation, in which limitations in vehicle weight and weight in axles are stricter, elements of comfort, safety and space for baggage are contributing to increase the weight of the vehicle. This coupled with the difficulty of introducing radical changes in the current conception of manufacturing such vehicles pose significant losses for existing manufacturers, both in product knowledge and process methodology, entails the overwhelming need to analyze and evaluate other structural alternatives without assuming relevant modifications on the products manufactured currently allowing them to adapt to the new safety requirements. Recent developments in cost-benefit processes for the production of metallic foams of low density, such as metal foams, place them as an alternative of special interest to be used as energy absorbers to strengthen structures. The filling with metal foams can be more efficient in terms of weight optimization compared with increasing thickness of the structural beams, since the energy absorption occurs in a relatively small fraction of the beams, called plastic hinges. The application of metal filling foams in vehicle structures is beginning to be used in certain areas of passenger cars, being an innovative opportunity in structures for application in buses and coaches. According to the mentioned before, and in order to come forward with a solution, this doctoral thesis has been prepared and its objectives are: - Develop a mathematical model to simulate the rollover test, considering the influence of the occupants held with seat belts to assess their influence on energy absorption structure. - Validate the mathematical model of the structure rollover by testing representative sections of the vehicle structure and by testing a complete vehicle. - Conduct a study of the properties of metal foams as possible incorporation of energy absorbing element in the filler component of the superstructure of buses and coaches. - Elaborate a mathematical model to assess the contribution of the metal foam filling in absorbing energy for static and dynamic bending loads on the components of buses or coaches superstructure. - Conduct a static and dynamic bending test program to validate the mathematical model of contribution of metal foam filling on components of the superstructure of buses and coaches bending. - To incorporate into the mathematical model of structure rollover, the results obtained on components filled with metal foam, to evaluate the contribution to the energy absorption. - Validate the rollover model structure of the bus or coach filled with metal foam through tests of bay sections. The objectives in this thesis have been achieved successfully. The contribution calculation model with metal foam filling in the vehicle structure has revealed that the filling with metal foam is more efficient than increasing thickness of the beams, as demonstrated in the experimental validation of bay sections.

Automatic Categorization for Improving Spanish into Spanish Sign Language Machine Translation

This paper describes a preprocessing module for improving the performance of a Spanish into Spanish Sign Language (Lengua de Signos Espanola: LSE) translation system when dealing with sparse training data. This preprocessing module replaces Spanish words with associated tags. The list with Spanish words (vocabulary) and associated tags used by this module is computed automatically considering those signs that show the highest probability of being the translation of every Spanish word. This automatic tag extraction has been compared to a manual strategy achieving almost the same improvement. In this analysis, several alternatives for dealing with non-relevant words have been studied. Non-relevant words are Spanish words not assigned to any sign. The preprocessing module has been incorporated into two well-known statistical translation architectures: a phrase-based system and a Statistical Finite State Transducer (SFST). This system has been developed for a specific application domain: the renewal of Identity Documents and Driver's License. In order to evaluate the system a parallel corpus made up of 4080 Spanish sentences and their LSE translation has been used. The evaluation results revealed a significant performance improvement when including this preprocessing module. In the phrase-based system, the proposed module has given rise to an increase in BLEU (Bilingual Evaluation Understudy) from 73.8% to 81.0% and an increase in the human evaluation score from 0.64 to 0.83. In the case of SFST, BLEU increased from 70.6% to 78.4% and the human evaluation score from 0.65 to 0.82.

Automatic Understanding of ATC Speech: Study of Prospectives and Field Experiments for Several Controller Positions

Although there has been a lot of interest in recognizing and understanding air traffic control (ATC) speech, none of the published works have obtained detailed field data results. We have developed a system able to identify the language spoken and recognize and understand sentences in both Spanish and English. We also present field results for several in-tower controller positions. To the best of our knowledge, this is the first time that field ATC speech (not simulated) is captured, processed, and analyzed. The use of stochastic grammars allows variations in the standard phraseology that appear in field data. The robust understanding algorithm developed has 95% concept accuracy from ATC text input. It also allows changes in the presentation order of the concepts and the correction of errors created by the speech recognition engine improving it by 17% and 25%, respectively, absolute in the percentage of fully correctly understood sentences for English and Spanish in relation to the percentages of fully correctly recognized sentences. The analysis of errors due to the spontaneity of the speech and its comparison to read speech is also carried out. A 96% word accuracy for read speech is reduced to 86% word accuracy for field ATC data for Spanish for the "clearances" task confirming that field data is needed to estimate the performance of a system. A literature review and a critical discussion on the possibilities of speech recognition and understanding technology applied to ATC speech are also given.

Exploring differences between phonetic classes in Sleep Apnoea Syndrome Patients using automatic speech processing techniques

This work is part of an on-going collaborative project between the medical and signal processing communities to promote new research efforts on automatic OSA (Obstructive Apnea Syndrome) diagnosis. In this paper, we explore the differences noted in phonetic classes (interphoneme) across groups (control/apnoea) and analyze their utility for OSA detection

Automatic Adaptation of Airport Surface Surveillance to Sensor Quality

This paper describes a novel method to enhance current airport surveillance systems used in Advanced Surveillance Monitoring Guidance and Control Systems (A-SMGCS). The proposed method allows for the automatic calibration of measurement models and enhanced detection of nonideal situations, increasing surveillance products integrity. It is based on the definition of a set of observables from the surveillance processing chain and a rule based expert system aimed to change the data processing methods

GLMP for automatic assessment of DFS algorithm learning

We describe how to use a Granular Linguistic Model of a Phenomenon (GLMP) to assess e-learning processes. We apply this technique to evaluate algorithm learning using the GRAPHs learning environment.

Automatic Inference of Determinacy and Mutual Exclusion for Logic Programs Using Mode and Type Analyses

We propose an analysis for detecting procedures and goals that are deterministic (i.e., that produce at most one solution at most once),or predicates whose clause tests are mutually exclusive (which implies that at most one of their clauses will succeed) even if they are not deterministic. The analysis takes advantage of the pruning operator in order to improve the detection of mutual exclusion and determinacy. It also supports arithmetic equations and disequations, as well as equations and disequations on terms,for which we give a complete satisfiability testing algorithm, w.r.t. available type information. Information about determinacy can be used for program debugging and optimization, resource consumption and granularity control, abstraction carrying code, etc. We have implemented the analysis and integrated it in the CiaoPP system, which also infers automatically the mode and type information that our analysis takes as input. Experiments performed on this implementation show that the analysis is fairly accurate and efficient.

An Efficient Multiple Object Detection and Tracking Framework for Automatic Counting and Video Surveillance Applications

Automatic visual object counting and video surveillance have important applications for home and business environments, such as security and management of access points. However, in order to obtain a satisfactory performance these technologies need professional and expensive hardware, complex installations and setups, and the supervision of qualified workers. In this paper, an efficient visual detection and tracking framework is proposed for the tasks of object counting and surveillance, which meets the requirements of the consumer electronics: off-the-shelf equipment, easy installation and configuration, and unsupervised working conditions. This is accomplished by a novel Bayesian tracking model that can manage multimodal distributions without explicitly computing the association between tracked objects and detections. In addition, it is robust to erroneous, distorted and missing detections. The proposed algorithm is compared with a recent work, also focused on consumer electronics, proving its superior performance.

Automatic Bandwidth Estimation Strategy for High-Quality Non-Parametric Modeling based Moving Object Detection

Here, a novel and efficient moving object detection strategy by non-parametric modeling is presented. Whereas the foreground is modeled by combining color and spatial information, the background model is constructed exclusively with color information, thus resulting in a great reduction of the computational and memory requirements. The estimation of the background and foreground covariance matrices, allows us to obtain compact moving regions while the number of false detections is reduced. Additionally, the application of a tracking strategy provides a priori knowledge about the spatial position of the moving objects, which improves the performance of the Bayesian classifier

Automatic segmentation of relevant textures in agricultural images

One important issue emerging strongly in agriculture is related with the automatization of tasks, where the optical sensors play an important role. They provide images that must be conveniently processed. The most relevantimage processing procedures require the identification of green plants, in our experiments they come from barley and corn crops including weeds, so that some types of action can be carried out, including site-specific treatments with chemical products or mechanical manipulations. Also the identification of textures belonging to the soil could be useful to know some variables, such as humidity, smoothness or any others. Finally, from the point of view of the autonomous robot navigation, where the robot is equipped with the imaging system, some times it is convenient to know not only the soil information and the plants growing in the soil but also additional information supplied by global references based on specific areas. This implies that the images to be processed contain textures of three main types to be identified: green plants, soil and sky if any. This paper proposes a new automatic approach for segmenting these main textures and also to refine the identification of sub-textures inside the main ones. Concerning the green identification, we propose a new approach that exploits the performance of existing strategies by combining them. The combination takes into account the relevance of the information provided by each strategy based on the intensity variability. This makes an important contribution. The combination of thresholding approaches, for segmenting the soil and the sky, makes the second contribution; finally the adjusting of the supervised fuzzy clustering approach for identifying sub-textures automatically, makes the third finding. The performance of the method allows to verify its viability for automatic tasks in agriculture based on image processing

Effectiveness of abstract interpretation in automatic parallelization: a case study in logic programming

We report on a detailed study of the application and effectiveness of program analysis based on abstract interpretation to automatic program parallelization. We study the case of parallelizing logic programs using the notion of strict independence. We first propose and prove correct a methodology for the application in the parallelization task of the information inferred by abstract interpretation, using a parametric domain. The methodology is generic in the sense of allowing the use of different analysis domains. A number of well-known approximation domains are then studied and the transformation into the parametric domain defined. The transformation directly illustrates the relevance and applicability of each abstract domain for the application. Both local and global analyzers are then built using these domains and embedded in a complete parallelizing compiler. Then, the performance of the domains in this context is assessed through a number of experiments. A comparatively wide range of aspects is studied, from the resources needed by the analyzers in terms of time and memory to the actual benefits obtained from the information inferred. Such benefits are evaluated both in terms of the characteristics of the parallelized code and of the actual speedups obtained from it. The results show that data flow analysis plays an important role in achieving efficient parallelizations, and that the cost of such analysis can be reasonable even for quite sophisticated abstract domains. Furthermore, the results also offer significant insight into the characteristics of the domains, the demands of the application, and the trade-offs involved.

Automatic lateral control for unmanned vehicles via genetic algorithms

It is known that the techniques under the topic of Soft Computing have a strong capability of learning and cognition, as well as a good tolerance to uncertainty and imprecision. Due to these properties they can be applied successfully to Intelligent Vehicle Systems; ITS is a broad range of technologies and techniques that hold answers to many transportation problems. The unmannedcontrol of the steering wheel of a vehicle is one of the most important challenges facing researchers in this area. This paper presents a method to adjust automatically a fuzzy controller to manage the steering wheel of a mass-produced vehicle; to reach it, information about the car state while a human driver is handling the car is taken and used to adjust, via iterative geneticalgorithms an appropriated fuzzy controller. To evaluate the obtained controllers, it will be considered the performance obtained in the track following task, as well as the smoothness of the driving carried out.

An Automatic Quantification and Registration Strategy to Create a Gene Expression Atlas of Zebrafish Embryogenesis

In order to properly understand and model the gene regulatory networks in animals development, it is crucial to obtain detailed measurements, both in time and space, about their gene expression domains. In this paper, we propose a complete computational framework to fulfill this task and create a 3D Atlas of the early zebrafish embryogenesis annotated with both the cellular localizations and the level of expression of different genes at different developmental stages. The strategy to construct such an Atlas is described here with the expression pattern of 5 different genes at 6 hours of development post fertilization.

Statistical Machine Learning for Automatic Assessment of Physical Activity Intensity Using Multi-axial Accelerometry and Heart Rate

This work explores the automatic recognition of physical activity intensity patterns from multi-axial accelerometry and heart rate signals. Data collection was carried out in free-living conditions and in three controlled gymnasium circuits, for a total amount of 179.80 h of data divided into: sedentary situations (65.5%), light-to-moderate activity (17.6%) and vigorous exercise (16.9%). The proposed machine learning algorithms comprise the following steps: time-domain feature definition, standardization and PCA projection, unsupervised clustering (by k-means and GMM) and a HMM to account for long-term temporal trends. Performance was evaluated by 30 runs of a 10-fold cross-validation. Both k-means and GMM-based approaches yielded high overall accuracy (86.97% and 85.03%, respectively) and, given the imbalance of the dataset, meritorious F-measures (up to 77.88%) for non-sedentary cases. Classification errors tended to be concentrated around transients, what constrains their practical impact. Hence, we consider our proposal to be suitable for 24 h-based monitoring of physical activity in ambulatory scenarios and a first step towards intensity-specific energy expenditure estimators

Automatic compile-time parallelization of logic programs for restricted, goal-level, independent and-parallelism.

A framework for the automatic parallelization of (constraint) logic programs is proposed and proved correct. Intuitively, the parallelization process replaces conjunctions of literals with parallel expressions. Such expressions trigger at run-time the exploitation of restricted, goal-level, independent and-parallelism. The parallelization process performs two steps. The first one builds a conditional dependency graph (which can be implified using compile-time analysis information), while the second transforms the resulting graph into linear conditional expressions, the parallel expressions of the &-Prolog language. Several heuristic algorithms for the latter ("annotation") process are proposed and proved correct. Algorithms are also given which determine if there is any loss of parallelism in the linearization process with respect to a proposed notion of maximal parallelism. Finally, a system is presented which implements the proposed approach. The performance of the different annotation algorithms is compared experimentally in this system by studying the time spent in parallelization and the effectiveness of the results in terms of speedups.