Application of the dynamic models to the detection of imperfections in plate Structures

This paper is part of a set of publications related with the development of mathematical models aimed to simulate the dynamic input and output of experimental nondestructive tests in order to detect structural imperfections. The structures to be considered are composed by steel plates of thin thickness. The imperfections in these cases are cracks and they can penetrate either a significant part of the plate thickness or be micro cracks or superficial imperfections. The first class of cracks is related with structural safety and the second one is more connected to the structural protection to the environment, particularly if protective paintings can be deteriorated. Two mathematical groups of models have been developed. The first group tries to locate the position and extension of the imperfection of the first class of imperfections, i.e. cracks and it is the object of the present paper. Bending Kirchoff thin plate models belong to this first group and they are used to this respect. The another group of models is dealt with membrane structures under the superficial Rayleigh waves excitation. With this group of models the micro cracks detection is intended. In the application of the first group of models to the detection of cracks, it has been observed that the differences between the natural frequencies of the non cracked and the cracked structures are very small. However, geometry and crack position can be identified quite accurately if this comparison is carried out between first derivatives (mode rotations) of the natural modes are used instead. Finally, in relation with the analysis of the superficial crack existence the use of Rayleigh waves is very promising. The geometry and the penetration of the micro crack can be detected very accurately. The mathematical and numerical treatment of the generation of these Rayleigh waves present and a numerical application has been shown.

Mulch materials in processing tomato: a multivariate approach.

Mulch materials of different origins have been introduced into the agricultural sector in recent years alternatively to the standard polyethylene due to its environmental impact. This study aimed to evaluate the multivariate response of mulch materials over three consecutive years in a processing tomato (Solanum lycopersicon L.) crop in Central Spain. Two biodegradable plastic mulches (BD1, BD2), one oxo-biodegradable material (OB), two types of paper (PP1, PP2), and one barley straw cover (BS) were compared using two control treatments (standard black polyethylene [PE] and manual weed control [MW]). A total of 17 variables relating to yield, fruit quality, and weed control were investigated. Several multivariate statistical techniques were applied, including principal component analysis, cluster analysis, and discriminant analysis. A group of mulch materials comprised of OB and BD2 was found to be comparable to black polyethylene regarding all the variables considered. The weed control variables were found to be an important source of discrimination. The two paper mulches tested did not share the same treatment group membership in any case: PP2 presented a multivariate response more similar to the biodegradable plastics, while PP1 was more similar to BS and MW. Based on our multivariate approach, the materials OB and BD2 can be used as an effective, more environmentally friendly alternative to polyethylene mulches.

Response threshold models, stochastic learning automata and ant colony optimization-based decentralized self-coordination algorithms for heterogeneous multi-tasks distribution in multi-robot systems

In recent decades, there has been an increasing interest in systems comprised of several autonomous mobile robots, and as a result, there has been a substantial amount of development in the eld of Articial Intelligence, especially in Robotics. There are several studies in the literature by some researchers from the scientic community that focus on the creation of intelligent machines and devices capable to imitate the functions and movements of living beings. Multi-Robot Systems (MRS) can often deal with tasks that are dicult, if not impossible, to be accomplished by a single robot. In the context of MRS, one of the main challenges is the need to control, coordinate and synchronize the operation of multiple robots to perform a specic task. This requires the development of new strategies and methods which allow us to obtain the desired system behavior in a formal and concise way. This PhD thesis aims to study the coordination of multi-robot systems, in particular, addresses the problem of the distribution of heterogeneous multi-tasks. The main interest in these systems is to understand how from simple rules inspired by the division of labor in social insects, a group of robots can perform tasks in an organized and coordinated way. We are mainly interested on truly distributed or decentralized solutions in which the robots themselves, autonomously and in an individual manner, select a particular task so that all tasks are optimally distributed. In general, to perform the multi-tasks distribution among a team of robots, they have to synchronize their actions and exchange information. Under this approach we can speak of multi-tasks selection instead of multi-tasks assignment, which means, that the agents or robots select the tasks instead of being assigned a task by a central controller. The key element in these algorithms is the estimation ix of the stimuli and the adaptive update of the thresholds. This means that each robot performs this estimate locally depending on the load or the number of pending tasks to be performed. In addition, it is very interesting the evaluation of the results in function in each approach, comparing the results obtained by the introducing noise in the number of pending loads, with the purpose of simulate the robot's error in estimating the real number of pending tasks. The main contribution of this thesis can be found in the approach based on self-organization and division of labor in social insects. An experimental scenario for the coordination problem among multiple robots, the robustness of the approaches and the generation of dynamic tasks have been presented and discussed. The particular issues studied are: Threshold models: It presents the experiments conducted to test the response threshold model with the objective to analyze the system performance index, for the problem of the distribution of heterogeneous multitasks in multi-robot systems; also has been introduced additive noise in the number of pending loads and has been generated dynamic tasks over time. Learning automata methods: It describes the experiments to test the learning automata-based probabilistic algorithms. The approach was tested to evaluate the system performance index with additive noise and with dynamic tasks generation for the same problem of the distribution of heterogeneous multi-tasks in multi-robot systems. Ant colony optimization: The goal of the experiments presented is to test the ant colony optimization-based deterministic algorithms, to achieve the distribution of heterogeneous multi-tasks in multi-robot systems. In the experiments performed, the system performance index is evaluated by introducing additive noise and dynamic tasks generation over time.

On the dynamic adaptation of language models based on dialogue information

We present an approach to adapt dynamically the language models (LMs) used by a speech recognizer that is part of a spoken dialogue system. We have developed a grammar generation strategy that automatically adapts the LMs using the semantic information that the user provides (represented as dialogue concepts), together with the information regarding the intentions of the speaker (inferred by the dialogue manager, and represented as dialogue goals). We carry out the adaptation as a linear interpolation between a background LM, and one or more of the LMs associated to the dialogue elements (concepts or goals) addressed by the user. The interpolation weights between those models are automatically estimated on each dialogue turn, using measures such as the posterior probabilities of concepts and goals, estimated as part of the inference procedure to determine the actions to be carried out. We propose two approaches to handle the LMs related to concepts and goals. Whereas in the first one we estimate a LM for each one of them, in the second one we apply several clustering strategies to group together those elements that share some common properties, and estimate a LM for each cluster. Our evaluation shows how the system can estimate a dynamic model adapted to each dialogue turn, which helps to improve the performance of the speech recognition (up to a 14.82% of relative improvement), which leads to an improvement in both the language understanding and the dialogue management tasks.

A review of load models for the prediction of footfall-induced vibration in structures

Crowd induced dynamic loading in large structures, such as gymnasiums or stadium, is usually modelled as a series of harmonic loads which are defined in terms of their Fourier coefficients. Different values of these coefficients that were obtained from full scale measurements can be found in codes. Recently, an alternative has been proposed, based on random generation of load time histories that take into account phase lag among individuals inside the crowd. This paper presents the testing done on a structure designed to be a gymnasium. Two series of dynamic test were performed on the gym slab. For the first test an electrodynamic shaker was placed at several locations and during the second one people located inside a marked area bounced and jumped guided by different metronome rates. A finite element model (FEM) is presented and a comparison of numerically predicted and experimentally observed vibration modes and frequencies has been used to assess its validity. The second group of measurements will be compared with predictions made using the FEM model and three alternatives for crowd induced load modelling.

Numerical simulation of group combustion of pulverized coal

A mathematical model for the group combustion of pulverized coal particles was developed in a previous work. It includes the Lagrangian description of the dehumidification, devolatilization and char gasification reactions of the coal particles in the homogenized gaseous environment resulting from the three fuels, CO, H2 and volatiles, supplied by the gasification of the particles and their simultaneous group combustion by the gas phase oxidation reactions, which are considered to be very fast. This model is complemented here with an analysis of the particle dynamics, determined principally by the effects of aerodynamic drag and gravity, and its dispersion based on a stochastic model. It is also extended to include two other simpler models for the gasification of the particles: the first one for particles small enough to extinguish the surrounding diffusion flames, and a second one for particles with small ash content when the porous shell of ashes remaining after gasification of the char, non structurally stable, is disrupted. As an example of the applicability of the models, they are used in the numerical simulation of an experiment of a non-swirling pulverized coal jet with a nearly stagnant air at ambient temperature, with an initial region of interaction with a small annular methane flame. Computational algorithms for solving the different stages undergone by a coal particle during its combustion are proposed. For the partial differential equations modeling the gas phase, a second order finite element method combined with a semi-Lagrangian characteristics method are used. The results obtained with the three versions of the model are compared among them and show how the first of the simpler models fits better the experimental results.

A multidisciplinary reference framework to support innovative design, implementation and assessment of chronic care models

Hoy en día, por primera vez en la historia, la mayor parte de la población podrá vivir hasta los sesenta años y más (United Nations, 2015). Sin embargo, todavía existe poca evidencia que demuestre que las personas mayores, estén viviendo con mejor salud que sus padres, a la misma edad, ya que la mayoría de los problemas de salud en edades avanzadas están asociados a las enfermedades crónicas (WHO, 2015). Los sistemas sanitarios de los países desarrollados funcionan adecuadamente cuando se trata del cuidado de enfermedades agudas, pero no son lo suficientemente eficaces en la gestión de las enfermedades crónicas. Durante la última década, se han realizado esfuerzos para mejorar esta gestión, por medio de la utilización de estrategias de prevención y de reenfoque de la provisión de los servicios de atención para la salud (Kane et al. 2005). Según una revisión sistemática de modelos de cuidado de salud, comisionada por el sistema nacional de salud Británico, pocos modelos han conceptualizado cuáles son los componentes que hay que utilizar para proporcionar un cuidado crónico efectivo, y estos componentes no han sido suficientemente estructurados y articulados. Por lo tanto, no hay suficiente evidencia sobre el impacto real de cualquier modelo existente en la actualidad (Ham, 2006). Las innovaciones podrían ayudar a conseguir mejores diagnósticos, tratamientos y gestión de pacientes crónicos, así como a dar soporte a los profesionales y a los pacientes en el cuidado. Sin embargo, la forma en las que estas innovaciones se proporcionan no es lo suficientemente eficiente, efectiva y amigable para el usuario. Para mejorar esto, hace falta crear equipos de trabajo y estrategias multidisciplinares. En conclusión, hacen falta actividades que permitan conseguir que las innovaciones sean utilizadas en los sistemas de salud que quieren mejorar la gestión del cuidado crónico, para que sea posible: 1) traducir la “atención sanitaria basada en la evidencia” en “conocimiento factible”; 2) hacer frente a la complejidad de la atención sanitaria a través de una investigación multidisciplinaria; 3) identificar una aproximación sistemática para que se establezcan intervenciones innovadoras en el cuidado de salud. El marco de referencia desarrollado en este trabajo de investigación es un intento de aportar estas mejoras. Las siguientes hipótesis han sido propuestas: Hipótesis 1: es posible definir un proceso de traducción que convierta un modelo de cuidado crónico en una descripción estructurada de objetivos, requisitos e indicadores clave de rendimiento. Hipótesis 2: el proceso de traducción, si se ejecuta a través de elementos basados en la evidencia, multidisciplinares y de orientación económica, puede convertir un modelo de cuidado crónico en un marco descriptivo, que define el ciclo de vida de soluciones innovadoras para el cuidado de enfermedades crónicas. Hipótesis 3: es posible definir un método para evaluar procesos, resultados y capacidad de desarrollar habilidades, y asistir equipos multidisciplinares en la creación de soluciones innovadoras para el cuidado crónico. Hipótesis 4: es posible dar soporte al desarrollo de soluciones innovadoras para el cuidado crónico a través de un marco de referencia y conseguir efectos positivos, medidos en indicadores clave de rendimiento. Para verificar las hipótesis, se ha definido una aproximación metodológica compuesta de cuatro Fases, cada una asociada a una hipótesis. Antes de esto, se ha llevado a cabo una “Fase 0”, donde se han analizado los antecedentes sobre el problema (i.e. adopción sistemática de la innovación en el cuidado crónico) desde una perspectiva multi-dominio y multi-disciplinar. Durante la fase 1, se ha desarrollado un Proceso de Traducción del Conocimiento, elaborado a partir del JBI Joanna Briggs Institute (JBI) model of evidence-based healthcare (Pearson, 2005), y sobre el cual se han definido cuatro Bloques de Innovación. Estos bloques consisten en una descripción de elementos innovadores, definidos en la fase 0, que han sido añadidos a los cuatros elementos que componen el modelo JBI. El trabajo llevado a cabo en esta fase ha servido también para definir los materiales que el proceso de traducción tiene que ejecutar. La traducción que se ha llevado a cabo en la fase 2, y que traduce la mejor evidencia disponible de cuidado crónico en acción: resultado de este proceso de traducción es la parte descriptiva del marco de referencia, que consiste en una descripción de un modelo de cuidado crónico (se ha elegido el Chronic Care Model, Wagner, 1996) en términos de objetivos, especificaciones e indicadores clave de rendimiento y organizada en tres ciclos de innovación (diseño, implementación y evaluación). Este resultado ha permitido verificar la segunda hipótesis. Durante la fase 3, para demostrar la tercera hipótesis, se ha desarrollado un método-mixto de evaluación de equipos multidisciplinares que trabajan en innovaciones para el cuidado crónico. Este método se ha creado a partir del método mixto usado para la evaluación de equipo multidisciplinares translacionales (Wooden, 2013). El método creado añade una dimensión procedural al marco. El resultado de esta fase consiste, por lo tanto, en una primera versión del marco de referencia, lista para ser experimentada. En la fase 4, se ha validado el marco a través de un caso de estudio multinivel y con técnicas de observación-participante como método de recolección de datos. Como caso de estudio se han elegido las actividades de investigación que el grupo de investigación LifeStech ha desarrollado desde el 2008 para mejorar la gestión de la diabetes, actividades realizadas en un contexto internacional. Los resultados demuestran que el marco ha permitido mejorar las actividades de trabajo en distintos niveles: 1) la calidad y cantidad de las publicaciones; 2) se han conseguido dos contratos de investigación sobre diabetes: el primero es un proyecto de investigación aplicada, el segundo es un proyecto financiado para acelerar las innovaciones en el mercado; 3) a través de los indicadores claves de rendimiento propuestos en el marco, una prueba de concepto de un prototipo desarrollado en un proyecto de investigación ha sido transformada en una evaluación temprana de una intervención eHealth para el manejo de la diabetes, que ha sido recientemente incluida en Repositorio de prácticas innovadoras del Partenariado de Innovación Europeo en Envejecimiento saludable y activo. La verificación de las 4 hipótesis ha permitido demonstrar la hipótesis principal de este trabajo de investigación: es posible contribuir a crear un puente entre la atención sanitaria y la innovación y, por lo tanto, mejorar la manera en que el cuidado crónico sea procurado en los sistemas sanitarios. ABSTRACT Nowadays, for the first time in history, most people can expect to live into their sixties and beyond (United Nations, 2015). However, little evidence suggests that older people are experiencing better health than their parents, and most of the health problems of older age are linked to Chronic Diseases (WHO, 2015). The established health care systems in developed countries are well suited to the treatment of acute diseases but are mostly inadequate for dealing with CDs. Healthcare systems are challenging the burden of chronic diseases by putting more emphasis on the prevention of disease and by looking for new ways to reorient the provision of care (Kane et al., 2005). According to an evidence-based review commissioned by the British NHS Institute, few models have conceptualized effective components of care for CDs and these components have been not structured and articulated. “Consequently, there is limited evidence about the real impact of any of the existing models” (Ham, 2006). Innovations could support to achieve better diagnosis, treatment and management for patients across the continuum of care, by supporting health professionals and empowering patients to take responsibility. However, the way they are delivered is not sufficiently efficient, effective and consumer friendly. The improvement of innovation delivery, involves the creation of multidisciplinary research teams and taskforces, rather than just working teams. There are several actions to improve the adoption of innovations from healthcare systems that are tackling the epidemics of CDs: 1) Translate Evidence-Based Healthcare (EBH) into actionable knowledge; 2) Face the complexity of healthcare through multidisciplinary research; 3) Identify a systematic approach to support effective implementation of healthcare interventions through innovation. The framework proposed in this research work is an attempt to provide these improvements. The following hypotheses have been drafted: Hypothesis 1: it is possible to define a translation process to convert a model of chronic care into a structured description of goals, requirements and key performance indicators. Hypothesis 2: a translation process, if executed through evidence-based, multidisciplinary, holistic and business-oriented elements, can convert a model of chronic care in a descriptive framework, which defines the whole development cycle of innovative solutions for chronic disease management. Hypothesis 3: it is possible to design a method to evaluate processes, outcomes and skill acquisition capacities, and assist multidisciplinary research teams in the creation of innovative solutions for chronic disease management. Hypothesis 4: it is possible to assist the development of innovative solutions for chronic disease management through a reference framework and produce positive effects, measured through key performance indicators. In order to verify the hypotheses, a methodological approach, composed of four Phases that correspond to each one of the stated hypothesis, was defined. Prior to this, a “Phase 0”, consisting in a multi-domain and multi-disciplinary background analysis of the problem (i.e.: systematic adoption of innovation to chronic care), was carried out. During phase 1, in order to verify the first hypothesis, a Knowledge Translation Process (KTP) was developed, starting from the JBI Joanna Briggs Institute (JBI) model of evidence-based healthcare was used (Pearson, 2005) and adding Four Innovation Blocks. These blocks represent an enriched description, added to the JBI model, to accelerate the transformation of evidence-healthcare through innovation; the innovation blocks are built on top of the conclusions drawn after Phase 0. The background analysis gave also indication on the materials and methods to be used for the execution of the KTP, carried out during phase 2, that translates the actual best available evidence for chronic care into action: this resulted in a descriptive Framework, which is a description of a model of chronic care (the Chronic Care Model was chosen, Wagner, 1996) in terms of goals, specified requirements and Key Performance Indicators, and articulated in the three development cycles of innovation (i.e. design, implementation and evaluation). Thanks to this result the second hypothesis was verified. During phase 3, in order to verify the third hypothesis, a mixed-method to evaluate multidisciplinary teams working on innovations for chronic care, was created, based on a mixed-method used for the evaluation of Multidisciplinary Translational Teams (Wooden, 2013). This method adds a procedural dimension to the descriptive component of the Framework, The result of this phase consisted in a draft version of the framework, ready to be tested in a real scenario. During phase 4, a single and multilevel case study, with participant-observation data collection, was carried out, in order to have a complete but at the same time multi-sectorial evaluation of the framework. The activities that the LifeStech research group carried out since 2008 to improve the management of diabetes have been selected as case study. The results achieved showed that the framework allowed to improve the research activities in different directions: the quality and quantity of the research publications that LifeStech has issued, have increased substantially; 2 project grants to improve the management of diabetes, have been assigned: the first is a grant funding applied research while the second is about accelerating innovations into the market; by using the assessment KPIs of the framework, the proof of concept validation of a prototype developed in a research project was transformed into an early stage assessment of innovative eHealth intervention for Diabetes Management, which has been recently included in the repository of innovative practice of the European Innovation Partnership on Active and Health Ageing initiative. The verification of the 4 hypotheses lead to verify the main hypothesis of this research work: it is possible to contribute to bridge the gap between healthcare and innovation and, in turn, improve the way chronic care is delivered by healthcare systems.