Generation of human computational models with machine learning

Services in smart environments pursue to increase the quality of people?s lives. The most important issues when developing this kind of environments is testing and validating such services. These tasks usually imply high costs and annoying or unfeasible real-world testing. In such cases, artificial societies may be used to simulate the smart environment (i.e. physical environment, equipment and humans). With this aim, the CHROMUBE methodology guides test engineers when modeling human beings. Such models reproduce behaviors which are highly similar to the real ones. Originally, these models are based on automata whose transitions are governed by random variables. Automaton?s structure and the probability distribution functions of each random variable are determined by a manual test and error process. In this paper, it is presented an alternative extension of this methodology which avoids the said manual process. It is based on learning human behavior patterns automatically from sensor data by using machine learning techniques. The presented approach has been tested on a real scenario, where this extension has given highly accurate human behavior models,

Modelo multifactorial para optimización de la productividad en el proceso de generación de energía eléctrica : aplicación al caso de las centrales hidroeléctricas venezolanas

Las organizaciones son sistemas o unidades sociales, compuestas por personas que interactúan entre sí, para lograr objetivos comunes. Uno de sus objetivos es la productividad. La productividad es un constructo multidimensional en la que influyen aspectos tecnológicos, económicos, organizacionales y humanos. Diversos estudios apoyan la influencia de la motivación de las personas, de las habilidades y destrezas de los individuos, de su talento para desempeñar el trabajo, así como también del ambiente de trabajo presente en la organización, en la productividad. Por esta razón, el objetivo general de la investigación, es analizar la influencia entre los factores humanos y la productividad. Se hará énfasis en la persona como factor productivo clave, para responder a las interrogantes de la investigación, referidas a cuáles son las variables humanas que inciden en la productividad, a la posibilidad de plantear un modelo de productividad que considere el impacto del factor humano y la posibilidad de encontrar un método para la medición de la productividad que contemple la percepción del factor humano. Para resolver estas interrogantes, en esta investigación se busca establecer las relaciones entre las variables humanas y la productividad, vistas desde la perspectiva de tres unidades de análisis diferentes: individuo, grupo y organización, para la formulación de un modelo de productividad humana y el diseño de un instrumento para su medida. Una de las principales fuente de investigación para la elección de las variables humanas, la formulación del modelo, y el método de medición de la productividad, fue la revisión de la literatura disponible sobre la productividad y el factor humano en las organizaciones, lo que facilitó el trazado del marco teórico y conceptual. Otra de las fuentes para la selección fue la opinión de expertos y de especialistas directamente involucrados en el sector eléctrico venezolano, lo cual facilitó la obtención de un modelo, cuyas variables reflejasen la realidad del ámbito en estudio. Para aportar una interpretación explicativa del fenómeno, se planteó el modelo de los Factores Humanos vs Productividad (MFHP), el cual se analizó desde la perspectiva del análisis causal y fue conformado por tres variables latentes exógenas denominadas: factores individuales, factores grupales y factores organizacionales, que estaban relacionadas con una variable latente endógena denominada productividad. El MFHP se formuló mediante la metodología de los modelos de ecuaciones estructurales (SEM). Las relaciones inicialmente propuestas entre las variables latentes fueron corroboradas por los ajustes globales del modelo, se constataron las relaciones entre las variables latentes planteadas y sus indicadores asociados, lo que facilitó el enunciado de 26 hipótesis, de las cuales se comprobaron 24. El modelo fue validado mediante la estrategia de modelos rivales, utilizada para comparar varios modelos SEM, y seleccionar el de mejor ajuste, con sustento teórico. La aceptación del modelo se realizó mediante la evaluación conjunta de los índices de bondad de ajuste globales. Asimismo, para la elaboración del instrumento de medida de la productividad (IMPH), se realizó un análisis factorial exploratorio previo a la aplicación del análisis factorial confirmatorio, aplicando SEM. La revisión de los conceptos de productividad, la incidencia del factor humano, y sus métodos de medición, condujeron al planteamiento de métodos subjetivos que incorporaron la percepción de los principales actores del proceso productivo, tanto para la selección de las variables, como para la formulación de un modelo de productividad y el diseño de un instrumento de medición de la productividad. La contribución metodológica de este trabajo de investigación, ha sido el empleo de los SEM para relacionar variables que tienen que ver con el comportamiento humano en la organización y la productividad, lo cual abre nuevas posibilidades a la investigación en este ámbito. Organizations are social systems or units composed of people who interact with each other to achieve common goals. One objective is productivity, which is a multidimensional construct influenced by technological, economic, organizational and human aspects. Several studies support the influence on productivity of personal motivation, of the skills and abilities of individuals, of their talent for the job, as well as of the work environment present in the organization. Therefore, the overall objective of this research is to analyze the influence between human factors and productivity. The emphasis is on the individual as a productive factor which is key in order to answer the research questions concerning the human variables that affect productivity and to address the ability to propose a productivity model that considers the impact of the human factor and the possibility of finding a method for the measurement of productivity that includes the perception of the human factor. To consider these questions, this research seeks to establish the relationships between human and productivity variables, as seen from the perspective of three different units of analysis: the individual, the group and the organization, in order to formulate a model of human productivity and to design an instrument for its measurement. A major source of research for choosing the human variables, model formulation, and method of measuring productivity, was the review of the available literature on productivity and the human factor in organizations which facilitated the design of the theoretical and conceptual framework. Another source for the selection was the opinion of experts and specialists directly involved in the Venezuelan electricity sector which facilitated obtaining a model whose variables reflect the reality of the area under study. To provide an interpretation explaining the phenomenon, the model of the Human Factors vs. Productivity Model (HFPM) was proposed. This model has been analyzed from the perspective of causal analysis and was composed of three latent exogenous variables denominated: individual, group and organizational factors which are related to a latent variable denominated endogenous productivity. The HFPM was formulated using the methodology of Structural Equation Modeling (SEM). The initially proposed relationships between latent variables were confirmed by the global fits of the model, the relationships between the latent variables and their associated indicators enable the statement of 26 hypotheses, of which 24 were confirmed. The model was validated using the strategy of rival models, used for comparing various SEM models and to select the one that provides the best fit, with theoretical support. The acceptance of the model was performed through the joint evaluation of the adequacy of global fit indices. Additionally, for the development of an instrument to measure productivity, an exploratory factor analysis was performed prior to the application of a confirmatory factor analysis, using SEM. The review of the concepts of productivity, the impact of the human factor, and the measurement methods led to a subjective methods approach that incorporated the perception of the main actors of the production process, both for the selection of variables and for the formulation of a productivity model and the design of an instrument to measure productivity. The methodological contribution of this research has been the use of SEM to relate variables that have to do with human behavior in the organization and with productivity, opening new possibilities for research in this area.

Modeling the evolution of item rating networks using time-domain preferential attachment

The understanding of the structure and dynamics of the intricate network of connections among people that consumes products through Internet appears as an extremely useful asset in order to study emergent properties related to social behavior. This knowledge could be useful, for example, to improve the performance of personal recommendation algorithms. In this contribution, we analyzed five-year records of movie-rating transactions provided by Netflix, a movie rental platform where users rate movies from an online catalog. This dataset can be studied as a bipartite user-item network whose structure evolves in time. Even though several topological properties from subsets of this bipartite network have been reported with a model that combines random and preferential attachment mechanisms [Beguerisse Díaz et al., 2010], there are still many aspects worth to be explored, as they are connected to relevant phenomena underlying the evolution of the network. In this work, we test the hypothesis that bursty human behavior is essential in order to describe how a bipartite user-item network evolves in time. To that end, we propose a novel model that combines, for user nodes, a network growth prescription based on a preferential attachment mechanism acting not only in the topological domain (i.e. based on node degrees) but also in time domain. In the case of items, the model mixes degree preferential attachment and random selection. With these ingredients, the model is not only able to reproduce the asymptotic degree distribution, but also shows an excellent agreement with the Netflix data in several time-dependent topological properties.

Genetic fuzzy-based steering wheel controller using a mass-produced car

Intelligent Transportation Systems (ITS) cover a broad range of methods and technologies that provide answers to many problems of transportation. Unmanned control of the steering wheel 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 reproduce the steering of a human driver. To this end, information is recorded about the car's state while being driven by human drivers and used to obtain, via genetic algorithms, appropriate fuzzy controllers that can drive the car in the way that humans do. These controllers have satisfy two main objectives: to reproduce the human behavior, and to provide smooth actions to ensure comfortable driving. Finally, the results of automated driving on a test circuit are presented, showing both good route tracking (similar to the performance obtained by persons in the same task) and smooth driving.

Análisis de textos explicativos del significado de datos cuantitativos

En este Trabajo de Fin de Grado se ha realizado el análisis de textos explicativos de datos cuantitativos, con la finalidad de dar a conocer cuáles son las relaciones, basándose en la Teoría de la Estructura Retórica, entre las distintas frases de un texto de más común uso en documentos periodísticos relacionados con el comportamiento humano y el uso que hacen las personas de las redes sociales. Además de ello se han analizado un conjunto de 20 textos (alrededor de 1200 páginas) obteniendo frases típicas relacionadas con el mismo tema, que sirvieron como base para la construcción del modelo compuesto por un total de 101 patrones. En un futuro, este Trabajo puede ser continuado, si así se desea, para lo cual se plantean las siguientes posibilidades:  Ampliar el conjunto de patrones proporcionado.  Construir un Sistema Generador de Textos automáticos basados en los patrones creados.  Ampliar el estudio y extrapolarlo a diversos temas. ---ABSTRACT---In this Final Project has been performed an analysis of quantitative data explanatory texts, in order to make known what are the relationships, based on Rhetorical Structure Theory, between the different sentences of a text of most common use in journalistic texts related to human behavior and the use people make of social networking. Furthermore have been analyzed a set of 20 texts (about 1200 pages) obtaining typical sentences related to the same topic that served as the basis for construction of the model consists of a total of 101 patterns. In the future, this work can be continued, if so desired, for which the following possibilities are raised:  Extend the set of patterns provided.  Build an Automatic Text Generator System based on the patterns collected in this study.  Expand the study and extrapolate it to various topics.

Análisis y modelización de la dinámica emergente durante el proceso de difusión de información en las redes sociales de internet

Durante la actividad diaria, la sociedad actual interactúa constantemente por medio de dispositivos electrónicos y servicios de telecomunicaciones, tales como el teléfono, correo electrónico, transacciones bancarias o redes sociales de Internet. Sin saberlo, masivamente dejamos rastros de nuestra actividad en las bases de datos de empresas proveedoras de servicios. Estas nuevas fuentes de datos tienen las dimensiones necesarias para que se puedan observar patrones de comportamiento humano a grandes escalas. Como resultado, ha surgido una reciente explosión sin precedentes de estudios de sistemas sociales, dirigidos por el análisis de datos y procesos computacionales. En esta tesis desarrollamos métodos computacionales y matemáticos para analizar sistemas sociales por medio del estudio combinado de datos derivados de la actividad humana y la teoría de redes complejas. Nuestro objetivo es caracterizar y entender los sistemas emergentes de interacciones sociales en los nuevos espacios tecnológicos, tales como la red social Twitter y la telefonía móvil. Analizamos los sistemas por medio de la construcción de redes complejas y series temporales, estudiando su estructura, funcionamiento y evolución en el tiempo. También, investigamos la naturaleza de los patrones observados por medio de los mecanismos que rigen las interacciones entre individuos, así como medimos el impacto de eventos críticos en el comportamiento del sistema. Para ello, hemos propuesto modelos que explican las estructuras globales y la dinámica emergente con que fluye la información en el sistema. Para los estudios de la red social Twitter, hemos basado nuestros análisis en conversaciones puntuales, tales como protestas políticas, grandes acontecimientos o procesos electorales. A partir de los mensajes de las conversaciones, identificamos a los usuarios que participan y construimos redes de interacciones entre los mismos. Específicamente, construimos una red para representar quién recibe los mensajes de quién y otra red para representar quién propaga los mensajes de quién. En general, hemos encontrado que estas estructuras tienen propiedades complejas, tales como crecimiento explosivo y distribuciones de grado libres de escala. En base a la topología de estas redes, hemos indentificado tres tipos de usuarios que determinan el flujo de información según su actividad e influencia. Para medir la influencia de los usuarios en las conversaciones, hemos introducido una nueva medida llamada eficiencia de usuario. La eficiencia se define como el número de retransmisiones obtenidas por mensaje enviado, y mide los efectos que tienen los esfuerzos individuales sobre la reacción colectiva. Hemos observado que la distribución de esta propiedad es ubicua en varias conversaciones de Twitter, sin importar sus dimensiones ni contextos. Con lo cual, sugerimos que existe universalidad en la relación entre esfuerzos individuales y reacciones colectivas en Twitter. Para explicar los factores que determinan la emergencia de la distribución de eficiencia, hemos desarrollado un modelo computacional que simula la propagación de mensajes en la red social de Twitter, basado en el mecanismo de cascadas independientes. Este modelo nos permite medir el efecto que tienen sobre la distribución de eficiencia, tanto la topología de la red social subyacente, como la forma en que los usuarios envían mensajes. Los resultados indican que la emergencia de un grupo selecto de usuarios altamente eficientes depende de la heterogeneidad de la red subyacente y no del comportamiento individual. Por otro lado, hemos desarrollado técnicas para inferir el grado de polarización política en redes sociales. Proponemos una metodología para estimar opiniones en redes sociales y medir el grado de polarización en las opiniones obtenidas. Hemos diseñado un modelo donde estudiamos el efecto que tiene la opinión de un pequeño grupo de usuarios influyentes, llamado élite, sobre las opiniones de la mayoría de usuarios. El modelo da como resultado una distribución de opiniones sobre la cual medimos el grado de polarización. Aplicamos nuestra metodología para medir la polarización en redes de difusión de mensajes, durante una conversación en Twitter de una sociedad políticamente polarizada. Los resultados obtenidos presentan una alta correspondencia con los datos offline. Con este estudio, hemos demostrado que la metodología propuesta es capaz de determinar diferentes grados de polarización dependiendo de la estructura de la red. Finalmente, hemos estudiado el comportamiento humano a partir de datos de telefonía móvil. Por una parte, hemos caracterizado el impacto que tienen desastres naturales, como innundaciones, sobre el comportamiento colectivo. Encontramos que los patrones de comunicación se alteran de forma abrupta en las áreas afectadas por la catástofre. Con lo cual, demostramos que se podría medir el impacto en la región casi en tiempo real y sin necesidad de desplegar esfuerzos en el terreno. Por otra parte, hemos estudiado los patrones de actividad y movilidad humana para caracterizar las interacciones entre regiones de un país en desarrollo. Encontramos que las redes de llamadas y trayectorias humanas tienen estructuras de comunidades asociadas a regiones y centros urbanos. En resumen, hemos mostrado que es posible entender procesos sociales complejos por medio del análisis de datos de actividad humana y la teoría de redes complejas. A lo largo de la tesis, hemos comprobado que fenómenos sociales como la influencia, polarización política o reacción a eventos críticos quedan reflejados en los patrones estructurales y dinámicos que presentan la redes construidas a partir de datos de conversaciones en redes sociales de Internet o telefonía móvil. ABSTRACT During daily routines, we are constantly interacting with electronic devices and telecommunication services. Unconsciously, we are massively leaving traces of our activity in the service providers’ databases. These new data sources have the dimensions required to enable the observation of human behavioral patterns at large scales. As a result, there has been an unprecedented explosion of data-driven social research. In this thesis, we develop computational and mathematical methods to analyze social systems by means of the combined study of human activity data and the theory of complex networks. Our goal is to characterize and understand the emergent systems from human interactions on the new technological spaces, such as the online social network Twitter and mobile phones. We analyze systems by means of the construction of complex networks and temporal series, studying their structure, functioning and temporal evolution. We also investigate on the nature of the observed patterns, by means of the mechanisms that rule the interactions among individuals, as well as on the impact of critical events on the system’s behavior. For this purpose, we have proposed models that explain the global structures and the emergent dynamics of information flow in the system. In the studies of the online social network Twitter, we have based our analysis on specific conversations, such as political protests, important announcements and electoral processes. From the messages related to the conversations, we identify the participant users and build networks of interactions with them. We specifically build one network to represent whoreceives- whose-messages and another to represent who-propagates-whose-messages. In general, we have found that these structures have complex properties, such as explosive growth and scale-free degree distributions. Based on the topological properties of these networks, we have identified three types of user behavior that determine the information flow dynamics due to their influence. In order to measure the users’ influence on the conversations, we have introduced a new measure called user efficiency. It is defined as the number of retransmissions obtained by message posted, and it measures the effects of the individual activity on the collective reacixtions. We have observed that the probability distribution of this property is ubiquitous across several Twitter conversation, regardlessly of their dimension or social context. Therefore, we suggest that there is a universal behavior in the relationship between individual efforts and collective reactions on Twitter. In order to explain the different factors that determine the user efficiency distribution, we have developed a computational model to simulate the diffusion of messages on Twitter, based on the mechanism of independent cascades. This model, allows us to measure the impact on the emergent efficiency distribution of the underlying network topology, as well as the way that users post messages. The results indicate that the emergence of an exclusive group of highly efficient users depends upon the heterogeneity of the underlying network instead of the individual behavior. Moreover, we have also developed techniques to infer the degree of polarization in social networks. We propose a methodology to estimate opinions in social networks and to measure the degree of polarization in the obtained opinions. We have designed a model to study the effects of the opinions of a small group of influential users, called elite, on the opinions of the majority of users. The model results in an opinions distribution to which we measure the degree of polarization. We apply our methodology to measure the polarization on graphs from the messages diffusion process, during a conversation on Twitter from a polarized society. The results are in very good agreement with offline and contextual data. With this study, we have shown that our methodology is capable of detecting several degrees of polarization depending on the structure of the networks. Finally, we have also inferred the human behavior from mobile phones’ data. On the one hand, we have characterized the impact of natural disasters, like flooding, on the collective behavior. We found that the communication patterns are abruptly altered in the areas affected by the catastrophe. Therefore, we demonstrate that we could measure the impact of the disaster on the region, almost in real-time and without needing to deploy further efforts. On the other hand, we have studied human activity and mobility patterns in order to characterize regional interactions on a developing country. We found that the calls and trajectories networks present community structure associated to regional and urban areas. In summary, we have shown that it is possible to understand complex social processes by means of analyzing human activity data and the theory of complex networks. Along the thesis, we have demonstrated that social phenomena, like influence, polarization and reaction to critical events, are reflected in the structural and dynamical patterns of the networks constructed from data regarding conversations on online social networks and mobile phones.

Metodología de análisis acústico de sitios arqueológicos de Mesoamérica

El presente trabajo busca llenar un vacío existente en cuanto a una metodología general en los estudios Arqueoacústicos para la zona Mesoamericana. El resultado mas importante de ésta tesis es la propuesta de un procedimiento y método para los cuales se detalla el conjunto de operaciones utilizadas en las mediciones particulares involucradas, parámetros y análisis relevantes (de los cuales destacan el decaimiento de energía, tiempos de reverberación, intensidades de sonido directo y total, claridad e inteligibilidad), tipos de simulaciones e incertidumbres y actividades técnicas propias de la Ingeniería Acústica que se proponen para la efectiva y útil integración de la dimensión sonora en el quehacer arqueológico. Una importante consideración de la propuesta metodológica aquí presentada, es la consideración, por un lado, de los resultados obtenidos experimentalmente del trabajo in situ en cada uno de los sitios arqueológicos de interés, y por otro los resultados obtenidos de las simulaciones y modelaciones por computadora de los mismos para su comparación y contraste. La propuesta de sistematización está dividida en tres momentos investigativos, como son la coordinación y trabajo logístico en sitios arqueológicos, su reconocimiento y prospección acústica; el trabajo de campo; y el análisis de los resultados obtenidos. Asimismo, dicha propuesta metodológica, se presenta dividida en tres objetos de estudio fundamentales en el quehacer arqueoacústico: los Fenómenos Sonoros encontrados en sitios arqueológicos; los objetos de generación de sonido, tengan éstos aplicaciones musicales o de otra índole; y finalmente los espacios y recintos arquitectónicos, ya sean cerrados o abiertos, y el estudio de su funcionalidad. El acercamiento a la descripción de cada una de dichas ramas, se realiza mediante la presentación de casos de estudio, para los que se contrastan dos áreas culturales representativas e interrelacionadas de Mesoamérica, la zona del Bajío y la zona Maya. Dicho contraste es llevado a cabo mediante el análisis acústico de 4 zonas arqueológicas que son Plazuelas, Peralta y Cañada de la Virgen, pertenecientes a la zona del Bajio, y Chichen Itzá perteneciente a la zona Maya. De particular importancia para el presente trabajo, es la funcionalidad de los espacios estudiados, específicamente de la de los patios hundidos, característicos de la arquitectura del Bajío, y las plazas públicas que constituyen una estructura integral en muchos sitios arqueológicos, centrales para la comprensión de las conexiones entre el fenómeno sonoro y el comportamiento de una cultura en particular. Asimismo, el análisis de los instrumentos de generación sonora ha permitido realizar inferencias sobre papel del sonido en el comportamiento humano de las culturas en cuestión, completando los modelos acústicos y posibilitando el situar las características de las fuentes sonoras en los espacios resonantes. Los resultados particulares de ésta tesis, han permitido establecer las características acústicas de dichos espacios e instrumentos, así como formular y validar las hipótesis sobre su usos y funciones como espacios para eventos públicos y sociales, así como para representaciones culturales multitudinarios. ABSTRACT The present work, aims to fill a void existing in terms of a general methodology in Archaeoacoustic studies for the Mesoamerican region. The most important result of this thesis is the proposal of a procedure and method for archaeoacoustical studies and its relevant analysis and parameters (of which stand out the energy decay, reverberation times, intensities, clarity and intelligibility), simulations and uncertainty considerations for the effective and useful integration of the sound dimension in the archaeological realm. An important methodological consideration in the present work is the comparison and contrast of the results obtained experimentally on site, and the results of simulations and computer modeling. The proposed systematization is divided into three distinct moments: logistics; fieldwork; and result analysis. Likewise, the presented methodological proposal is divided into three fundamental objects of study: Sound phenomena found in archaeological sites; sound generation objects and instruments; and architectural enclosures and the study of their functionality. Presenting case studies is the approach to the description of each of these branches. Two interrelated Mesoamerican cultural areas are considered, the Bajío and the Mayan. Their contrast is carried out by the acoustic analysis of four archaeological sites: Plazuelas, Peralta and Cañada de la Virgen, belonging to the area of the Bajío, and Chichen Itza belonging to the Maya area. Of particular relevance to this paper, is the acoustic functionality of the public spaces present in many archaeological sites, specifically that of the sunken patios, characteristic of the architecture of the Bajío. The analysis of the sound generation instruments has allowed certain inferences about the role of sound in human behavior of the cultures in question, thus completing the acoustic models. It has also enable the contrast of the characteristics of the sound sources and those of the resonant spaces. The results of this thesis have made it possible to develop and validate certain hypotheses about the uses and functions of certain spaces for public and social events as well as for mass cultural representations.

Flooding through the lens of mobile phone activity

Natural disasters affect hundreds of millions of people worldwide every year. Emergency response efforts depend upon the availability of timely information, such as information concerning the movements of affected populations. The analysis of aggregated and anonymized Call Detail Records (CDR) captured from the mobile phone infrastructure provides new possibilities to characterize human behavior during critical events. In this work, we investigate the viability of using CDR data combined with other sources of information to characterize the floods that occurred in Tabasco, Mexico in 2009. An impact map has been reconstructed using Landsat-7 images to identify the floods. Within this frame, the underlying communication activity signals in the CDR data have been analyzed and compared against rainfall levels extracted from data of the NASA-TRMM project. The variations in the number of active phones connected to each cell tower reveal abnormal activity patterns in the most affected locations during and after the floods that could be used as signatures of the floods - both in terms of infrastructure impact assessment and population information awareness. The epresentativeness of the analysis has been assessed using census data and civil protection records. While a more extensive validation is required, these early results suggest high potential in using cell tower activity information to improve early warning and emergency management mechanisms.

Flooding through the lens of mobile phone activity

Natural disasters affect hundreds of millions of people worldwide every year. Emergency response efforts depend upon the availability of timely information, such as information concerning the movements of affected populations. The analysis of aggregated and anonymized Call Detail Records (CDR) captured from the mobile phone infrastructure provides new possibilities to characterize human behavior during critical events. In this work, we investigate the viability of using CDR data combined with other sources of information to characterize the floods that occurred in Tabasco, Mexico in 2009. An impact map has been reconstructed using Landsat-7 images to identify the floods. Within this frame, the underlying communication activity signals in the CDR data have been analyzed and compared against rainfall levels extracted from data of the NASA-TRMM project. The variations in the number of active phones connected to each cell tower reveal abnormal activity patterns in the most affected locations during and after the floods that could be used as signatures of the floods - both in terms of infrastructure impact assessment and population information awareness. The representativeness of the analysis has been assessed using census data and civil protection records. While a more extensive validation is required, these early results suggest high potential in using cell tower activity information to improve early warning and emergency management mechanisms.

Assessing the suitability of student interactions from Moodle data logs as predictors of cross-curricular competencies

In the past decades, online learning has transformed the educational landscape with the emergence of new ways to learn. This fact, together with recent changes in educational policy in Europe aiming to facilitate the incorporation of graduate students to the labor market, has provoked a shift on the delivery of instruction and on the role played by teachers and students, stressing the need for development of both basic and cross-curricular competencies. In parallel, the last years have witnessed the emergence of new educational disciplines that can take advantage of the information retrieved by technology-based online education in order to improve instruction, such as learning analytics. This study explores the applicability of learning analytics for prediction of development of two cross-curricular competencies – teamwork and commitment – based on the analysis of Moodle interaction data logs in a Master’s Degree program at Universidad a Distancia de Madrid (UDIMA) where the students were education professionals. The results from the study question the suitability of a general interaction-based approach and show no relation between online activity indicators and teamwork and commitment acquisition. The discussion of results includes multiple recommendations for further research on this topic.

Post-fracture behavior of laminated plates after human impact test

For safety barriers the load bearing capacity of the glass when subjected to the soft body impact should be verified. The soft body pendulum test became a testing standard to classify safety glass plates. The classification of the safety glass do not consider the structural behavior when one sheet of a laminated glass is broken; in situations when the replacement of the plate could not be very urgent, structural behavior should be evaluated. The main objective of this paper is to present the structural behavior o laminated glass plates, though modal test and human impact test, including the post fracture behavior for the laminated cases. A god reproducibility and repeatability is obtained. Two main aspects of the structural behavior can be observed: the increment of the rupture load for laminated plates after the failure of the first sheet, and some similarities with a tempered monolithic behavior of equivalent thickness.

Failure and impact behavior of facade panels made of glass fiber reinforced cement(GRC)

GRC is a cementitious composite material made up of a cement mortar matrix and chopped glass fibers. Due to its outstanding mechanical properties, GRC has been widely used to produce cladding panels and some civil engineering elements. Impact failure of cladding panels made of GRC may occur during production if some tool falls onto the panel, due to stone or other objects impacting at low velocities or caused by debris projected after a blast. Impact failure of a front panel of a building may have not only an important economic value but also human lives may be at risk if broken pieces of the panel fall from the building to the pavement. Therefore, knowing GRC impact strength is necessary to prevent economic costs and putting human lives at risk. One-stage light gas gun is an impact test machine capable of testing different materials subjected to impact loads. An experimental program was carried out, testing GRC samples of five different formulations, commonly used in building industry. Steel spheres were shot at different velocities on square GRC samples. The residual velocity of the projectiles was obtained both using a high speed camera with multiframe exposure and measuring the projectile’s penetration depth in molding clay blocks. Tests were performed on young and artificially aged GRC samples to compare GRC’s behavior when subjected to high strain rates. Numerical simulations using a hydrocode were made to analyze which parameters are most important during an impact event. GRC impact strength was obtained from test results. Also, GRC’s embrittlement, caused by GRC aging, has no influence on GRC impact behavior due to the small size of the projectile. Also, glass fibers used in GRC production only maintain GRC panels’ integrity but have no influence on GRC’s impact strength. Numerical models have reproduced accurately impact tests.

Survey and brain storming studies about machines, constructions, human and environmental risk consideration in the careers of the Universidad Politécnica of Madrid

The Universidad Politécnica of Madrid (UPM) includes schools and faculties that were for engineering degrees, architecture and computer science, that are now in a quick EEES Bolonia Plan metamorphosis getting into degrees, masters and doctorate structures. They are focused towards action in machines, constructions, enterprises, that are subjected to machines, human and environment created risks. These are present in actions such as use loads, wind, snow, waves, flows, earthquakes, forces and effects in machines, vehicles behavior, chemical effects, and other environmental factors including effects of crops, cattle and beasts, forests, and varied essential economic and social disturbances. Emphasis is for authors in this session more about risks of natural origin, such as for hail, winds, snow or waves that are not exactly known a priori, but that are often considered with statistical expected distributions giving extreme values for convenient return periods. These distributions are known from measures in time, statistic of extremes and models about hazard scenarios and about responses of man made constructions or devices. In each engineering field theories were built about hazards scenarios and how to cover for important risks. Engineers must get that the systems they handle, such as vehicles, machines, firms or agro lands or forests, obtain production with enough safety for persons and with decent economic results in spite of risks. For that risks must be considered in planning, in realization and in operation, and safety margins must be taken but at a reasonable cost. That is a small level of risks will often remain, due to limitations in costs or because of due to strange hazards, and maybe they will be covered by insurance in cases such as in transport with cars, ships or aircrafts, in agro for hail, or for fire in houses or in forests. These and other decisions about quality, security for men or about business financial risks are sometimes considered with Decision Theories models, using often tools from Statistics or operational Research. The authors have done and are following field surveys about risk consideration in the careers in UPM, making deep analysis of curricula taking into account the new structures of degrees in the EEES Bolonia Plan, and they have considered the risk structures offered by diverse schools of Decision theories. That gives an aspect of the needs and uses, and recommendations about improving in the teaching about risk, that may include special subjects especially oriented for each career, school or faculty, so as to be recommended to be included into the curricula, including an elaboration and presentation format using a multi-criteria decision model.

OMNIWORKS: Omnidirectional vision for human-UAV co-working

The OMNIWORKS project objective is to develop an autonomous and modular aerial inspection system for an off-shore meteorological mast up to 90m in length. The UAV was equipped with an omni-directional camera and vertical take-off/landing capabilities that should be simple enough to operate as to not need the interventions of a professional pilot under challenging situations. Therefore the tests included different aspects used to evaluate both the technical performance of the UAV behavior as well as the operators? point of view.

A Knowledge-based Approach for Automatic Generation of Summaries of Behavior

Effective automatic summarization usually requires simulating human reasoning such as abstraction or relevance reasoning. In this paper we describe a solution for this type of reasoning in the particular case of surveillance of the behavior of a dynamic system using sensor data. The paper first presents the approach describing the required type of knowledge with a possible representation. This includes knowledge about the system structure, behavior, interpretation and saliency. Then, the paper shows the inference algorithm to produce a summarization tree based on the exploitation of the physical characteristics of the system. The paper illustrates how the method is used in the context of automatic generation of summaries of behavior in an application for basin surveillance in the presence of river floods.