Utilización del cultivo plurianual de pataca (Helianthus tuberosus L.) para la producción de hidratos de carbono fermentables a partir de los tallos

La pataca (Helianthus tuberosus L.) es una especie de cultivo con un alto potencial en la producción de hidratos de carbono de reserva en forma de polifructanos, especialmente inulina, que se acumulan temporalmente en los tallos en forma de polisacáridos para translocarse posteriormente a los tubérculos, donde son almacenados. Aunque tradicionalmente el producto de interés del cultivo son los tubérculos, que acumulan gran cantidad de hidratos de carbono fermentables (HCF) cuando se recogen al final del ciclo de desarrollo, en este trabajo se pretende evaluar el potencial de la pataca como productor de HCF a partir de los tallos cosechados en el momento de máximo contenido en HCF, mediante un sistema de cultivo plurianual. Se han realizado los siguientes estudios: i) Determinación del momento óptimo de cosecha en ensayos con 12 clones ii) Potencial del cultivo plurianual de la pataca en términos de producción anual de biomasa aérea y de HCF en cosechas sucesivas, iii) Ensayos de conservación de la biomasa aérea, iv) Estimación de los costes de las dos modalidades de cultivo de pataca para producción de HCF y v) Estimación de la sostenibilidad energética de la producción de bioetanol mediante la utilización de los subproductos. Para la determinación del momento óptimo de la cosecha de la biomasa aérea se ensayaron 12 clones de diferente precocidad en Madrid; 4 tempranos (Huertos de Moya, C-17, Columbia y D-19) y 8 tardíos (Boniches, China, K-8, Salmantina, Nahodka, C-13, INIA y Violeta de Rennes). El máximo contenido en HCF tuvo lugar en el estado fenológico de botón floral-flor que además coincidió con la máxima producción de biomasa aérea. De acuerdo con los resultados obtenidos, la cosecha de los clones tempranos se debería realizar en el mes de julio y en los clones tardíos en septiembre, siendo éstos últimos más productivos. La producción media más representativa entre los 12 clones, obtenida en el estado fenológico de botón floral fue de 23,40 t ms/ha (clon INIA), con un contenido medio en HCF de 30,30 % lo que supondría una producción potencial media de 7,06 t HCF/ha. La producción máxima en HCF se obtuvo en el clon Boniches con 7,61 t/ha y 22,81 t ms/ha de biomasa aérea. En el sistema de cultivo plurianual la cantidad de tallos por unidad de superficie aumenta cada año debido a la cantidad de tubérculos que van quedando en el terreno, sobre todo a partir del 3er año, lo que produce la disminución del peso unitario de los tallos, con el consiguiente riesgo de encamado. El aclareo de los tallos nacidos a principios de primavera mediante herbicidas tipo Glifosato o mediante una labor de rotocultor rebaja la densidad final de tallos y mejora los rendimientos del cultivo. En las experiencias de conservación de la biomasa aérea se obtuvo una buena conservación por un período de 6 meses de los HCF contenidos en los tallos secos empacados y almacenados bajo cubierta. Considerando que el rendimiento práctico de la fermentación alcohólica es de 0,5 l de etanol por cada kg de azúcar, la producción potencial de etanol para una cosecha de tallos de 7,06 t de HCF/ha sería de 3.530 l/ha. El bagazo producido en la extracción de los HCF de la biomasa aérea supondría 11,91 t/ha lo que utilizado para fines térmicos supone más de 3 veces la energía primaria requerida en el proceso de producción de etanol, considerando un poder calorífico inferior de 3.832,6 kcal/kg. Para una producción de HCF a partir de la biomasa aérea de 7,06 t/ha y en tubérculos al final del ciclo de 12,11 t/ha, los costes de producción estimados para cada uno de ellos fueron de 184,69 €/t para los HCF procedentes de la biomasa aérea y 311,30 €/t para los de tubérculos. Como resultado de este trabajo se puede concluir que la producción de HCF a partir de la biomasa aérea de pataca en cultivo plurianual, es viable desde un punto de vista técnico, con reducción de los costes de producción respecto al sistema tradicional de cosecha de tubérculos. Entre las ventajas técnicas de esta modalidad de cultivo, cabe destacar: la reducción de operaciones de cultivo, la facilidad y menor coste de la cosecha, y la posibilidad de conservación de los HCF en la biomasa cosechada sin mermas durante varios meses. Estas ventajas, compensan con creces el menor rendimiento por unidad de superficie que se obtiene con este sistema de cultivo frente al de cosecha de los tubérculos. Jerusalem artichoke (Helianthus tuberosus L.) (JA) is a crop with a high potential for the production of carbohydrates in the form of polyfructans, especially inulin, which are temporarily accumulated in the stems in the form of polysaccharides. Subsequently they are translocated to the tubers, where they are finally accumulated. In this work the potential of Jerusalem artichoke for fermentable carbohydrates from stems that are harvested at their peak of carbohydrates accumulation is assessed as compared to the traditional cultivation system that aims at the production of tubers harvested at the end of the growth cycle. Tubers are storage organs of polyfructans, namely fermentable carbohydrates. Studies addressed in this work were: i) Determination of the optimum period of time for stem harvesting as a function of clone precocity in a 12-clone field experiment; ii) Study of the potential of JA poly-annual crop regarding the annual yield of aerial biomass and fermentable carbohydrates (HCF) over the years; iii) Tests of storage of the aerial biomass, iv) Comparative analysis of the two JA cultivation systems for HCF production: the poly-annual system for aerial biomass harvesting versus the annual cultivation system for tubers and v) Estimation of the energy sustainability of the bioethanol production by using by-products of the production chain. In order to determine the best period of time for aerial biomass harvesting twelve JA clones of different precocity were tested in Madrid: four early clones (Huertos de Moya, C-17, Columbia and D-19) and eight late clones (Boniches, China, K-8 , Salmantina, Nahodka, C-13, INIA and Violeta de Rennes). Best time was between the phenological stages of floral buds (closed capitula) and blossom (opened capitula), period in which the peak of biomass production coincides with the peak of HCF accumulation in the stems. According to the results, the early clones should be harvested in July and the late ones in September, being the late clones more productive. The clone named INIA was the one that exhibited more steady yields in biomass over the 12 clones experimented. The average potential biomass production of this clone was 23.40 t dm/ha when harvested at the floral buds phenological stage; mean HCF content is 30.30%, representing 7.06 t HCF/ha yield. However, the highest HCF production was obtained for the clone Boniches, 7.61 t HCF/ha from a production of 22.81 t aerial biomass/ha. In the poly-annual cultivation system the number of stems per unit area increases over the years due to the increase in the number of tubers that are left under ground; this effect is particularly important after the 3rd year of the poly-annual crop and results in a decrease of the stems unit weight and a risk of lodging. Thinning of JA shoots in early spring, by means of an herbicide treatment based on glyphosate or by means of one pass with a rotary tiller, results in a decrease of the crop stem density and in higher crop yields. Tests of biomass storing showed that the method of keeping dried stems packed and stored under cover results in a good preservation of HCF for a period of six months at least. Assuming that the fermentation yield is 0.5 L ethanol per kg sugars and a HCF stem production of 7.06 t HCF/ha, the potential for bioethanol is estimated at 3530 L/ha. The use of bagasse -by-product of the process of HCF extraction from the JA stems- for thermal purposes would represent over 3 times the primary energy required for the industrial ethanol production process, assuming 11.91 t/ha bagasse and 3832.6 kcal/kg heating value. HCF production costs of 7.06 t HCF/ha yield from aerial biomass and HCF production costs of 12.11 t HCF/ha from tubers were estimated at 184.69 €/t HCF and 311.30 €/t HCF, respectively. It can be concluded that the production of HCF from JA stems, following a poly-annual cultivation system, can be feasible from a technical standpoint and lead to lower production costs as compared to the traditional annual cultivation system for the production of HCF from tubers. Among the technical advantages of the poly-annual cultivation system it is worth mentioning the reduction in crop operations, the ease and efficiency of harvesting operations and the possibility of HCF preservation without incurring in HCF losses during the storage period, which can last several months. These advantages might compensate the lower yield of HCF per unit area that is obtained in the poly-annual crop system, which aims at stems harvesting, versus the annual one, which involves tubers harvesting.

A technique for recursive invariance detection and selective program specialization

This paper presents a technique for achieving a class of optimizations related to the reduction of checks within cycles. The technique uses both Program Transformation and Abstract Interpretation. After a ñrst pass of an abstract interpreter which detects simple invariants, program transformation is used to build a hypothetical situation that simpliñes some predicates that should be executed within the cycle. This transformation implements the heuristic hypothesis that once conditional tests hold they may continué doing so recursively. Specialized versions of predicates are generated to detect and exploit those cases in which the invariance may hold. Abstract interpretation is then used again to verify the truth of such hypotheses and conñrm the proposed simpliñcation. This allows optimizations that go beyond those possible with only one pass of the abstract interpreter over the original program, as is normally the case. It also allows selective program specialization using a standard abstract interpreter not speciñcally designed for this purpose, thus simplifying the design of this already complex module of the compiler. In the paper, a class of programs amenable to such optimization is presented, along with some examples and an evaluation of the proposed techniques in some application áreas such as floundering detection and reducing run-time tests in automatic logic program parallelization. The analysis of the examples presented has been performed automatically by an implementation of the technique using existing abstract interpretation and program transformation tools.

Una propuesta de modelado del estudiante basada en ontologías y diagnóstico pedagógico-cognitivo no monótono

Los recientes avances tecnológicos han encontrado un potencial campo de explotación en la educación asistida por computador. A finales de los años 90 surgió un nuevo campo de investigación denominado Entornos Virtuales Inteligentes para el Entrenamiento y/o Enseñanza (EVIEs), que combinan dos áreas de gran complejidad: Los Entornos Virtuales (EVs) y los Sistemas de Tutoría Inteligente (STIs). De este modo, los beneficios de los entornos 3D (simulación de entornos de alto riesgo o entornos de difícil uso, etc.) pueden combinarse con aquéllos de un STIs (personalización de materias y presentaciones, adaptación de la estrategia de tutoría a las necesidades del estudiante, etc.) para proporcionar soluciones educativas/de entrenamiento con valores añadidos. El Modelo del Estudiante, núcleo de un SIT, representa el conocimiento y características del estudiante, y refleja el proceso de razonamiento del estudiante. Su complejidad es incluso superior cuando los STIs se aplican a EVs porque las nuevas posibilidades de interacción proporcionadas por estos entornos deben considerarse como nuevos elementos de información clave para el modelado del estudiante, incidiendo en todo el proceso educativo: el camino seguido por el estudiante durante su navegación a través de escenarios 3D; el comportamiento no verbal tal como la dirección de la mirada; nuevos tipos de pistas e instrucciones que el módulo de tutoría puede proporcionar al estudiante; nuevos tipos de preguntas que el estudiante puede formular, etc. Por consiguiente, es necesario que la estructura de los STIs, embebida en el EVIE, se enriquezca con estos aspectos, mientras mantiene una estructura clara, estructurada, y bien definida. La mayoría de las aproximaciones al Modelo del Estudiante en STIs y en IVETs no consideran una taxonomía de posibles conocimientos acerca del estudiante suficientemente completa. Además, la mayoría de ellas sólo tienen validez en ciertos dominios o es difícil su adaptación a diferentes STIs. Para vencer estas limitaciones, hemos propuesto, en el marco de esta tesis doctoral, un nuevo mecanismo de Modelado del Estudiante basado en la Ingeniería Ontológica e inspirado en principios pedagógicos, con un modelo de datos sobre el estudiante amplio y flexible que facilita su adaptación y extensión para diferentes STIs y aplicaciones de aprendizaje, además de un método de diagnóstico con capacidades de razonamiento no monótono. El método de diagnóstico es capaz de inferir el estado de los objetivos de aprendizaje contenidos en el SIT y, a partir de él, el estado de los conocimientos del estudiante durante su proceso de aprendizaje. La aproximación almodelado del estudiante propuesta ha sido implementada e integrada en un agente software (el agente de modelado del estudiante) dentro de una plataforma software existente para el desarrollo de EVIEs denominadaMAEVIF. Esta plataforma ha sido diseñada para ser fácilmente configurable para diferentes aplicaciones de aprendizaje. El modelado del estudiante presentado ha sido implementado e instanciado para dos tipos de entornos de aprendizaje: uno para aprendizaje del uso de interfaces gráficas de usuario en una aplicación software y para un Entorno Virtual para entrenamiento procedimental. Además, se ha desarrollado una metodología para guiar en la aplicación del esta aproximación de modelado del estudiante a cada sistema concreto.---ABSTRACT---Recent technological advances have found a potential field of exploitation in computeraided education. At the end of the 90’s a new research field emerged, the so-called Intelligent Virtual Environments for Training and/or Education (IVETs), which combines two areas of great complexity: Virtual Environments (VE) and Intelligent Tutoring Systems (ITS). In this way, the benefits of 3D environments (simulation of high risk or difficult-to-use environments, etc.) may be combined with those of an ITS (content and presentation customization, adaptation of the tutoring strategy to the student requirements, etc.) in order to provide added value educational/training solutions. The StudentModel, core of an ITS, represents the student’s knowledge and characteristics, and reflects the student’s reasoning process. Its complexity is even higher when the ITSs are applied on VEs because the new interaction possibilities offered by these environments must be considered as new key information pieces for student modelling, impacting all the educational process: the path followed by the student during their navigation through 3D scenarios; non-verbal behavior such as gaze direction; new types of hints or instructions that the tutoring module can provide to the student; new question types that the student can ask, etc. Thus, it is necessary for the ITS structure, which is embedded in the IVET, to be enriched by these aspects, while keeping a clear, structured and well defined architecture. Most approaches to SM on ITSs and IVETs don’t consider a complete enough taxonomy of possible knowledge about the student. In addition, most of them have validity only in certain domains or they are hard to be adapted for different ITSs. In order to overcome these limitations, we have proposed, in the framework of this doctoral research project, a newStudentModeling mechanism that is based onOntological Engineering and inspired on pedagogical principles, with a wide and flexible data model about the student that facilitates its adaptation and extension to different ITSs and learning applications, as well as a rich diagnosis method with non-monotonic reasoning capacities. The diagnosis method is able to infer the state of the learning objectives encompassed by the ITS and, fromit, the student’s knowledge state during the student’s process of learning. The proposed student modelling approach has been implemented and integrated in a software agent (the student modeling agent) within an existing software platform for the development of IVETs called MAEVIF. This platform was designed to be easily configurable for different learning applications. The proposed student modeling has been implemented and it has been instantiated for two types of learning environments: one for learning to use the graphical user interface of a software application and a Virtual Environment for procedural training. In addition, a methodology to guide on the application of this student modeling approach to each specific system has been developed.

The educational learning lifecycle and the cloud computing

Currently, student dropout rates are a matter of concern among universities. Many research studies, aimed at discovering the causes, have been carried out. However, few solutions, that could serve all students and related problems, have been proposed so far. One such problem is caused by the lack of the "knowledge chain educational links" that occurs when students move onto higher studies without mastering their basic studies. Most regulated studies imparted at universities are designed so that some basic subjects serve as support for other, more complicated, subjects, thus forming a complicated knowledge network. When a link in this chain fails, student frustration occurs as it prevents him from fully understanding the following educational links. In this proposal we try to mitigate these disasters that stem, for the most part, the student?s frustration beyond his college stay. On one hand, we make a dissertation on the student?s learning process, which we divide into a series of phases that amount to what we call the "learning lifecycle." Also, we analyze at what stage the action by the stakeholders involved in this scenario: teachers and students; is most important. On the other hand, we consider that Information and Communication Technologies ICT, such as Cloud Computing, can help develop new ways, allowing for the teaching of higher education, while easing and facilitating the student?s learning process. But, methods and processes need to be defined as to direct the use of such technologies; in the teaching process in general, and within higher education in particular; in order to achieve optimum results. Our methodology integrates, as another actor, the ICT into the "Learning Lifecycle". We stimulate students to stop being merely spectators of their own education, and encourage them to take an active part in their training process. To do this, we offer a set of useful tools to determine not only academic failure causes, (for self assessment), but also to remedy these failures (with corrective actions); "discovered the causes it is easier to determine solutions?. We believe this study will be useful for both students and teachers. Students learn from their own experience and improve their learning process, while obtaining all of the "knowledge chain educational links? required in their studies. We stand by the motto "Studying to learn instead of studying to pass". Teachers will also be benefited by detecting where and how to strengthen their teaching proposals. All of this will also result in decreasing dropout rates.

Learning an L1-regularized Gaussian Bayesian Network in the Equivalence Class Space

Learning the structure of a graphical model from data is a common task in a wide range of practical applications. In this paper, we focus on Gaussian Bayesian networks, i.e., on continuous data and directed acyclic graphs with a joint probability density of all variables given by a Gaussian. We propose to work in an equivalence class search space, specifically using the k-greedy equivalence search algorithm. This, combined with regularization techniques to guide the structure search, can learn sparse networks close to the one that generated the data. We provide results on some synthetic networks and on modeling the gene network of the two biological pathways regulating the biosynthesis of isoprenoids for the Arabidopsis thaliana plant

Handy or practical student. Objective: to pass or to learn

With the introduction of the European Higher Education Area and the development of the "Bologna" method in learning certain technological subjects, a pilot assessment procedure was launched in the "old" plan to observe, monitor and analyze the acquiring knowledge of senior students in various academic courses. This paper is a reflection on culture and knowledge. Will students accommodate to get a lower score on tests because they know they have a lot of tooltips to achieve their objectives?. Are their skills lower for these reason?.

A policy-driven architecture for supporting joint degrees through e-learning services

En un mercado de educación superior cada vez más competitivo, la colaboración entre universidades es una efectiva estrategia para acceder al mercado global. El desarrollo de titulaciones conjuntas es un importante mecanismo para fortalecer las colaboraciones académicas y diversificar los conocimientos. Las titulaciones conjuntas están siendo cada vez más implementadas en las universidades de todo el mundo. En Europa, el proceso de Bolonia y el programa Erasmus, están fomentado el reconocimiento de titulaciones conjuntas y dobles y promoviendo la colaboración entre las instituciones académicas. En el imparable proceso de la globalización y convergencia educativa, el uso de sistemas de e-learning para soportar cursos tanto semipresencial como online es una tendencia en crecimiento. Dado que los sistemas de e-learning soportan una amplia variedad de cursos, es necesario encontrar una solución adecuada que permita a las universidades soportar y gestionar las titulaciones conjuntas a través de sus sistemas de e-learning en conformidad con los acuerdos de colaboración establecidos por las universidades participantes. Esta tesis doctoral abordará las siguientes preguntas de investigación: 1. ¿Qué factores deben tenerse en cuenta en la implementación y gestión de titulaciones conjuntas? 2. ¿Cómo pueden los sistemas actuales de e-learning soportar el desarrollo de titulaciones conjuntas? 3. ¿Qué otros servicios y sistemas necesitan ser adaptados por las universidades interesadas en participar en una titulación conjunta a través de sus sistemas de e-learning? La implementación de titulaciones conjuntas a través de sistemas de e-learning es compleja e implica retos técnicos, administrativos, culturales, financieros, jurídicos y de seguridad. Esta tesis doctoral propone una serie de contribuciones que pueden ayudar a resolver algunos de los retos identificados. En primer lugar se ha elaborado un modelo conceptual que incluye la información del contexto de las titulaciones conjuntas que es relevante para la implementación de estas titulaciones en los sistemas de e-learning. Después de definir el modelo conceptual, se ha propuesto una arquitectura basada en políticas para la implementación de titulaciones interinstitucionales a través de sistemas de e-learning de acuerdo a los términos estipulados en los acuerdos de colaboración que son firmados por las universidades participantes. El autor se ha centrado en el componente de gestión de flujos de trabajo de esta arquitectura. Por último y con el fin de permitir la interoperabilidad de repositorios de objetos educativos, los componentes básicos a implementar han sido identificados y validados. El uso de servicios multimedia en educación es una tendencia creciente, proporcionando servicios de e-learning que permiten mejorar la comunicación y la interacción entre profesores y alumnos. Dentro de estos servicios, nos hemos centrado en el uso de la videoconferencia y la grabación de clases como servicios adecuados para el desarrollo de cursos impartidos en escenarios de educación colaborativos. Las contribuciones han sido validadas en proyectos de investigación de ámbito nacional y europeo en los que el autor ha participado. Abstract In an increasingly competitive higher education market, collaboration between universities is an effective strategy for gaining access to the global market. The development of joint degrees is an important mechanism for strengthening academic research collaborations and diversifying knowledge. Joint degrees are becoming increasingly implemented in universities around the world. In Europe, the Bologna process and the Erasmus programme have encouraged both the global recognition of joint and double degrees and promoted close collaboration between academic institutions. In the unstoppable process of globalization and educational convergence, the use of e-learning systems for supporting both blended and online courses is becoming a growing trend. Since e-learning systems covers a wide range of courses, it becomes necessary to find a suitable solution that enables universities to support and manage joint degrees through their e-learning systems in accordance with the collaboration agreements established by the universities involved. This dissertation will address the following research questions: 1. What factors need to be considered in the implementation and management of joint degrees? 2. How can the current e-learning systems support the development of joint degrees? 3. What other services and systems need to be adapted by universities interested in participating in a joint degree through their e-learning systems? The implementation of joint degrees using e-learning systems is complex and involves technical, administrative, security, cultural, financial and legal challenges. This dissertation proposes a series of contributions to help solve some of the identified challenges. One of the cornerstones of this proposal is a conceptual model of all the relevant issues related to the support of joint degrees by means of e-learning systems. After defining the conceptual model, this dissertation proposes a policy-driven architecture for implementing inter-institutional degree collaborations through e-learning systems as stipulated by a collaboration agreement signed by two universities. The author has focused on the workflow management component of this architecture. Finally, the building blocks for achieving interoperability of learning object repositories have been identified and validated. The use of multimedia services in education is a growing trend, providing rich e-learning services that improve the communication and interaction between teachers and students. Within these e-learning services, we have focused on the use of videoconferencing and lecture recording as the best-suited services to support collaborative learning scenarios. The contributions have been validated within national and European research projects that the author has been involved in.

Training project management complexity in postgraduate and continuing education programs: a learning strategy in the eshe (European Space of Higher Education) framework

The objective of this paper is to address the methodological process of a teaching strategy for training project management complexity in postgraduate programs. The proposal is made up of different methods —intuitive, comparative, deductive, case study, problem-solving Project-Based Learning— and different activities inside and outside the classroom. This integration of methods motivated the current use of the concept of “learning strategy”. The strategy has two phases: firstly, the integration of the competences —technical, behavioral and contextual—in real projects; and secondly, the learning activity was oriented in upper level of knowledge, the evaluating the complexity for projects management in real situations. Both the competences in the learning strategy and the Project Complexity Evaluation are based on the ICB of IPMA. The learning strategy is applied in an international Postgraduate Program —Erasmus Mundus Master of Science— with the participation of five Universities of the European Union. This master program is fruit of a cooperative experience from one Educative Innovation Group of the UPM -GIE-Project-, two Research Groups of the UPM and the collaboration with other external agents to the university. Some reflections on the experience and the main success factors in the learning strategy were presented in the paper

Integrated learning of computer applications for production engineering

A high productivity rate in Engineering is related to an efficient management of the flow of the large quantities of information and associated decision making activities that are consubstantial to the Engineering processes both in design and production contexts. Dealing with such problems from an integrated point of view and mimicking real scenarios is not given much attention in Engineering degrees. In the context of Engineering Education, there are a number of courses designed for developing specific competencies, as required by the academic curricula, but not that many in which integration competencies are the main target. In this paper, a course devoted to that aim is discussed. The course is taught in a Marine Engineering degree but the philosophy could be used in any Engineering field. All the lessons are given in a computer room in which every student can use each all the treated software applications. The first part of the course is dedicated to Project Management: the students acquire skills in defining, using Ms-PROJECT, the work breakdown structure (WBS), and the organization breakdown structure (OBS) in Engineering projects, through a series of examples of increasing complexity, ending up with the case of vessel construction. The second part of the course is dedicated to the use of a database manager, Ms-ACCESS, for managing production related information. A series of increasing complexity examples is treated ending up with the management of the pipe database of a real vessel. This database consists of a few thousand of pipes, for which a production timing frame is defined, which connects this part of the course with the first one. Finally, the third part of the course is devoted to the work with FORAN, an Engineering Production package of widespread use in the shipbuilding industry. With this package, the frames and plates where all the outfitting will be carried out are defined through cooperative work by the studens, working simultaneously in the same 3D model. In the paper, specific details about the learning process are given. Surveys have been posed to the students in order to get feed-back from their experience as well as to assess their satisfaction with the learning process. Results from these surveys are discussed in the paper

Training project management complexity in postgraduate and continuing education programs: a learning strategy in the eshe (European Space of Higher Education) framework

The objective of this paper is to address the methodological process of a teaching strategy for training project management complexity in postgraduate programs. The proposal is made up of different methods —intuitive, comparative, deductive, case study, problem-solving Project-Based Learning— and different activities inside and outside the classroom. This integration of methods motivated the current use of the concept of ―learning strategy‖. The strategy has two phases: firstly, the integration of the competences —technical, behavioral and contextual—in real projects; and secondly, the learning activity was oriented in upper level of knowledge, the evaluating the complexity for projects management in real situations. Both the competences in the learning strategy and the Project Complexity Evaluation are based on the ICB of IPMA. The learning strategy is applied in an international Postgraduate Program —Erasmus Mundus Master of Science— with the participation of five Universities of the European Union. This master program is fruit of a cooperative experience from one Educative Innovation Group of the UPM -GIE-Project-, two Research Groups of the UPM and the collaboration with other external agents to the university. Some reflections on the experience and the main success factors in the learning strategy were presented in the paper.

The Learning of the subject Biology in a Master in Biomedical Physics

BIOLOGY is a dynamic and fascinating science. The study of this subject is an amazing trip for all the students that have a first contact with this subject. Here, we present the development of the study and learning experience of this subject belonging to an area of knowledge that is different to the training curriculum of students who have studied Physics during their degree period. We have taken a real example, the “Elements of Biology” subject, which is taught as part of the Official Biomedical Physics Master, at the Physics Faculty, of the Complutense University of Madrid, since the course 2006/07. Its main objective is to give to the student an understanding how the Physics can have numerous applications in the Biomedical Sciences area, giving the basic training to develop a professional, academic or research career. The results obtained when we use new virtual tools combined with the classical learning show that there is a clear increase in the number of persons that take and pass the final exam. On the other hand, this new learning strategy is well received by the students and this is translated to a higher participation and a decrease of the giving the subject up

Probabilistic versus incremental presynaptic learning in biological plausible synapses

In this paper, the presynaptic rule, a classical rule for hebbian learning, is revisited. It is shown that the presynaptic rule exhibits relevant synaptic properties like synaptic directionality, and LTP metaplasticity (long-term potentiation threshold metaplasticity). With slight modifications, the presynaptic model also exhibits metaplasticity of the long-term depression threshold, being also consistent with Artola, Brocher and Singer’s (ABS) influential model. Two asymptotically equivalent versions of the presynaptic rule were adopted for this analysis: the first one uses an incremental equation while the second, conditional probabilities. Despite their simplicity, both types of presynaptic rules exhibit sophisticated biological properties, specially the probabilistic version

Student Reciprocal Peer Teaching as a Method for Active Learning: An Experience in an Electrotechnical Laboratory

Active learning is one of the most efficient mechanisms for learning, according to the psychology of learning. When students act as teachers for other students, the communication is more fluent and knowledge is transferred easier than in a traditional classroom. This teaching method is referred to in the literature as reciprocal peer teaching. In this study, the method is applied to laboratory sessions of a higher education institution course, and the students who act as teachers are referred to as ‘‘laboratory monitors.’’ A particular way to select the monitors and its impact in the final marks is proposed. A total of 181 students participated in the experiment, experiences with laboratory monitors are discussed, and methods for motivating and training laboratory monitors and regular students are proposed. The types of laboratory sessions that can be led by classmates are discussed. This work is related to the changes in teaching methods in the Spanish higher education system, prompted by the Bologna Process for the construction of the European Higher Education Area

Regularization for sparsity in statistical analysis and machine learning

Pragmatism is the leading motivation of regularization. We can understand regularization as a modification of the maximum-likelihood estimator so that a reasonable answer could be given in an unstable or ill-posed situation. To mention some typical examples, this happens when fitting parametric or non-parametric models with more parameters than data or when estimating large covariance matrices. Regularization is usually used, in addition, to improve the bias-variance tradeoff of an estimation. Then, the definition of regularization is quite general, and, although the introduction of a penalty is probably the most popular type, it is just one out of multiple forms of regularization. In this dissertation, we focus on the applications of regularization for obtaining sparse or parsimonious representations, where only a subset of the inputs is used. A particular form of regularization, L1-regularization, plays a key role for reaching sparsity. Most of the contributions presented here revolve around L1-regularization, although other forms of regularization are explored (also pursuing sparsity in some sense). In addition to present a compact review of L1-regularization and its applications in statistical and machine learning, we devise methodology for regression, supervised classification and structure induction of graphical models. Within the regression paradigm, we focus on kernel smoothing learning, proposing techniques for kernel design that are suitable for high dimensional settings and sparse regression functions. We also present an application of regularized regression techniques for modeling the response of biological neurons. Supervised classification advances deal, on the one hand, with the application of regularization for obtaining a na¨ıve Bayes classifier and, on the other hand, with a novel algorithm for brain-computer interface design that uses group regularization in an efficient manner. Finally, we present a heuristic for inducing structures of Gaussian Bayesian networks using L1-regularization as a filter. El pragmatismo es la principal motivación de la regularización. Podemos entender la regularización como una modificación del estimador de máxima verosimilitud, de tal manera que se pueda dar una respuesta cuando la configuración del problema es inestable. A modo de ejemplo, podemos mencionar el ajuste de modelos paramétricos o no paramétricos cuando hay más parámetros que casos en el conjunto de datos, o la estimación de grandes matrices de covarianzas. Se suele recurrir a la regularización, además, para mejorar el compromiso sesgo-varianza en una estimación. Por tanto, la definición de regularización es muy general y, aunque la introducción de una función de penalización es probablemente el método más popular, éste es sólo uno de entre varias posibilidades. En esta tesis se ha trabajado en aplicaciones de regularización para obtener representaciones dispersas, donde sólo se usa un subconjunto de las entradas. En particular, la regularización L1 juega un papel clave en la búsqueda de dicha dispersión. La mayor parte de las contribuciones presentadas en la tesis giran alrededor de la regularización L1, aunque también se exploran otras formas de regularización (que igualmente persiguen un modelo disperso). Además de presentar una revisión de la regularización L1 y sus aplicaciones en estadística y aprendizaje de máquina, se ha desarrollado metodología para regresión, clasificación supervisada y aprendizaje de estructura en modelos gráficos. Dentro de la regresión, se ha trabajado principalmente en métodos de regresión local, proponiendo técnicas de diseño del kernel que sean adecuadas a configuraciones de alta dimensionalidad y funciones de regresión dispersas. También se presenta una aplicación de las técnicas de regresión regularizada para modelar la respuesta de neuronas reales. Los avances en clasificación supervisada tratan, por una parte, con el uso de regularización para obtener un clasificador naive Bayes y, por otra parte, con el desarrollo de un algoritmo que usa regularización por grupos de una manera eficiente y que se ha aplicado al diseño de interfaces cerebromáquina. Finalmente, se presenta una heurística para inducir la estructura de redes Bayesianas Gaussianas usando regularización L1 a modo de filtro.

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.