Semi-supervised subspace clustering and applications to neuroscience

Machine learning techniques are used for extracting valuable knowledge from data. Nowa¬days, these techniques are becoming even more important due to the evolution in data ac¬quisition and storage, which is leading to data with different characteristics that must be exploited. Therefore, advances in data collection must be accompanied with advances in machine learning techniques to solve new challenges that might arise, on both academic and real applications. There are several machine learning techniques depending on both data characteristics and purpose. Unsupervised classification or clustering is one of the most known techniques when data lack of supervision (unlabeled data) and the aim is to discover data groups (clusters) according to their similarity. On the other hand, supervised classification needs data with supervision (labeled data) and its aim is to make predictions about labels of new data. The presence of data labels is a very important characteristic that guides not only the learning task but also other related tasks such as validation. When only some of the available data are labeled whereas the others remain unlabeled (partially labeled data), neither clustering nor supervised classification can be used. This scenario, which is becoming common nowadays because of labeling process ignorance or cost, is tackled with semi-supervised learning techniques. This thesis focuses on the branch of semi-supervised learning closest to clustering, i.e., to discover clusters using available labels as support to guide and improve the clustering process. Another important data characteristic, different from the presence of data labels, is the relevance or not of data features. Data are characterized by features, but it is possible that not all of them are relevant, or equally relevant, for the learning process. A recent clustering tendency, related to data relevance and called subspace clustering, claims that different clusters might be described by different feature subsets. This differs from traditional solutions to data relevance problem, where a single feature subset (usually the complete set of original features) is found and used to perform the clustering process. The proximity of this work to clustering leads to the first goal of this thesis. As commented above, clustering validation is a difficult task due to the absence of data labels. Although there are many indices that can be used to assess the quality of clustering solutions, these validations depend on clustering algorithms and data characteristics. Hence, in the first goal three known clustering algorithms are used to cluster data with outliers and noise, to critically study how some of the most known validation indices behave. The main goal of this work is however to combine semi-supervised clustering with subspace clustering to obtain clustering solutions that can be correctly validated by using either known indices or expert opinions. Two different algorithms are proposed from different points of view to discover clusters characterized by different subspaces. For the first algorithm, available data labels are used for searching for subspaces firstly, before searching for clusters. This algorithm assigns each instance to only one cluster (hard clustering) and is based on mapping known labels to subspaces using supervised classification techniques. Subspaces are then used to find clusters using traditional clustering techniques. The second algorithm uses available data labels to search for subspaces and clusters at the same time in an iterative process. This algorithm assigns each instance to each cluster based on a membership probability (soft clustering) and is based on integrating known labels and the search for subspaces into a model-based clustering approach. The different proposals are tested using different real and synthetic databases, and comparisons to other methods are also included when appropriate. Finally, as an example of real and current application, different machine learning tech¬niques, including one of the proposals of this work (the most sophisticated one) are applied to a task of one of the most challenging biological problems nowadays, the human brain model¬ing. Specifically, expert neuroscientists do not agree with a neuron classification for the brain cortex, which makes impossible not only any modeling attempt but also the day-to-day work without a common way to name neurons. Therefore, machine learning techniques may help to get an accepted solution to this problem, which can be an important milestone for future research in neuroscience. Resumen Las técnicas de aprendizaje automático se usan para extraer información valiosa de datos. Hoy en día, la importancia de estas técnicas está siendo incluso mayor, debido a que la evolución en la adquisición y almacenamiento de datos está llevando a datos con diferentes características que deben ser explotadas. Por lo tanto, los avances en la recolección de datos deben ir ligados a avances en las técnicas de aprendizaje automático para resolver nuevos retos que pueden aparecer, tanto en aplicaciones académicas como reales. Existen varias técnicas de aprendizaje automático dependiendo de las características de los datos y del propósito. La clasificación no supervisada o clustering es una de las técnicas más conocidas cuando los datos carecen de supervisión (datos sin etiqueta), siendo el objetivo descubrir nuevos grupos (agrupaciones) dependiendo de la similitud de los datos. Por otra parte, la clasificación supervisada necesita datos con supervisión (datos etiquetados) y su objetivo es realizar predicciones sobre las etiquetas de nuevos datos. La presencia de las etiquetas es una característica muy importante que guía no solo el aprendizaje sino también otras tareas relacionadas como la validación. Cuando solo algunos de los datos disponibles están etiquetados, mientras que el resto permanece sin etiqueta (datos parcialmente etiquetados), ni el clustering ni la clasificación supervisada se pueden utilizar. Este escenario, que está llegando a ser común hoy en día debido a la ignorancia o el coste del proceso de etiquetado, es abordado utilizando técnicas de aprendizaje semi-supervisadas. Esta tesis trata la rama del aprendizaje semi-supervisado más cercana al clustering, es decir, descubrir agrupaciones utilizando las etiquetas disponibles como apoyo para guiar y mejorar el proceso de clustering. Otra característica importante de los datos, distinta de la presencia de etiquetas, es la relevancia o no de los atributos de los datos. Los datos se caracterizan por atributos, pero es posible que no todos ellos sean relevantes, o igualmente relevantes, para el proceso de aprendizaje. Una tendencia reciente en clustering, relacionada con la relevancia de los datos y llamada clustering en subespacios, afirma que agrupaciones diferentes pueden estar descritas por subconjuntos de atributos diferentes. Esto difiere de las soluciones tradicionales para el problema de la relevancia de los datos, en las que se busca un único subconjunto de atributos (normalmente el conjunto original de atributos) y se utiliza para realizar el proceso de clustering. La cercanía de este trabajo con el clustering lleva al primer objetivo de la tesis. Como se ha comentado previamente, la validación en clustering es una tarea difícil debido a la ausencia de etiquetas. Aunque existen muchos índices que pueden usarse para evaluar la calidad de las soluciones de clustering, estas validaciones dependen de los algoritmos de clustering utilizados y de las características de los datos. Por lo tanto, en el primer objetivo tres conocidos algoritmos se usan para agrupar datos con valores atípicos y ruido para estudiar de forma crítica cómo se comportan algunos de los índices de validación más conocidos. El objetivo principal de este trabajo sin embargo es combinar clustering semi-supervisado con clustering en subespacios para obtener soluciones de clustering que puedan ser validadas de forma correcta utilizando índices conocidos u opiniones expertas. Se proponen dos algoritmos desde dos puntos de vista diferentes para descubrir agrupaciones caracterizadas por diferentes subespacios. Para el primer algoritmo, las etiquetas disponibles se usan para bus¬car en primer lugar los subespacios antes de buscar las agrupaciones. Este algoritmo asigna cada instancia a un único cluster (hard clustering) y se basa en mapear las etiquetas cono-cidas a subespacios utilizando técnicas de clasificación supervisada. El segundo algoritmo utiliza las etiquetas disponibles para buscar de forma simultánea los subespacios y las agru¬paciones en un proceso iterativo. Este algoritmo asigna cada instancia a cada cluster con una probabilidad de pertenencia (soft clustering) y se basa en integrar las etiquetas conocidas y la búsqueda en subespacios dentro de clustering basado en modelos. Las propuestas son probadas utilizando diferentes bases de datos reales y sintéticas, incluyendo comparaciones con otros métodos cuando resulten apropiadas. Finalmente, a modo de ejemplo de una aplicación real y actual, se aplican diferentes técnicas de aprendizaje automático, incluyendo una de las propuestas de este trabajo (la más sofisticada) a una tarea de uno de los problemas biológicos más desafiantes hoy en día, el modelado del cerebro humano. Específicamente, expertos neurocientíficos no se ponen de acuerdo en una clasificación de neuronas para la corteza cerebral, lo que imposibilita no sólo cualquier intento de modelado sino también el trabajo del día a día al no tener una forma estándar de llamar a las neuronas. Por lo tanto, las técnicas de aprendizaje automático pueden ayudar a conseguir una solución aceptada para este problema, lo cual puede ser un importante hito para investigaciones futuras en neurociencia.

Contribución al diseño y modelado de plataformas de gestión e impartición de titulaciones conjuntas en ambientes de e-learning

Las Tecnologías de la Información y de las Comunicaciones, ofrecen una buena oportunidad para el desarrollo de comunidades virtuales de aprendizaje, especialmente en el caso de las titulaciones conjuntas entre organizaciones. Estas comunidades permiten a las organizaciones aprovechar mejor las oportunidades de aprendizaje que brindan las tecnologías de Internet, aportando mejores contenidos y experiencias de aprendizaje (Recursos de aprendizaje) tanto para los profesores como para los alumnos. Sin embargo, actualmente no existe una tecnología clara con la que poder federar plataformas de gestión e impartición de titulaciones virtuales (LMS), con la que dar un adecuado soporte a las titulaciones conjuntas. En este trabajo, se presenta una metodología y una arquitectura de federación de plataformas LMS para poder gestionar titulaciones conjuntas en ambiente de e-learning. Actualmente, existe escaso conocimiento acerca de los problemas que están imposibilitando la utilización de estos escenarios. Por ello, este trabajo se presenta como una solución para los miembros de la comunidad (directores, docentes, investigadores y estudiantes), ofreciendo un marco conceptual, que ayuda a entender estos escenarios e identifica los requisitos de diseño que son útiles para generar servicios de aprendizaje accesibles a los miembros de la comunidad (Grid de recursos de aprendizaje) y para integrar los LMS en una nube de titulaciones conjuntas en ambientes de e-learning. Así mismo, en el presente documento se presentan varias experiencias, en las que se han implementado comunidades virtuales de aprendizaje en la ciudad de Cartagena de Indias (Colombia), que han servido para inspirar y validar la solución propuesta en este trabajo. ABSTRACT Information and communication technologies offer a great opportunity for the development of virtual learning communities, like as joint degrees between Organizations. Virtual Learning Communities allow organizations to be more cooperative during training activities via the Internet, with the provision of their learning expertise (learning resource). Internet enables multiple organizations to share their learning expertise with others. In these cooperative knowledge spaces, each organization contributes with their partners providing learning resources that they offer to students and teachers. However, currently there is no clear technology with which to federate Learning Management Systems (LMS) to give adequate support to joint degrees. In this work, we present a description of the problems that would face the generation of the Joint degrees in e-learning environments. Currently little is known about the problems that prevent the formation of virtual learning communities generated from the experience contributed by multiple organizations, so, this work is important for community members (Directors, Teachers, Researchers and practitioners) because it offers a conceptual framework that helps understand these scenarios and can provide useful design requirements when generating learning services for the community (Grid of Learning Resources) and to integrate the LMS in a cloud of joint degrees in e-learning environments. We also propose various experiences in which virtual learning communities have been integrated in Cartagena de Indias (Colombia) which have served to inspire and validate the solution proposed in this paper.

Quantifying Reproducibility in Computational Biology: The Case of the Tuberculosis Drugome

How easy is it to reproduce the results found in a typical computational biology paper? Either through experience or intuition the reader will already know that the answer is with difficulty or not at all. In this paper we attempt to quantify this difficulty by reproducing a previously published paper for different classes of users (ranging from users with little expertise to domain experts) and suggest ways in which the situation might be improved. Quantification is achieved by estimating the time required to reproduce each of the steps in the method described in the original paper and make them part of an explicit workflow that reproduces the original results. Reproducing the method took several months of effort, and required using new versions and new software that posed challenges to reconstructing and validating the results. The quantification leads to “reproducibility maps” that reveal that novice researchers would only be able to reproduce a few of the steps in the method, and that only expert researchers with advance knowledge of the domain would be able to reproduce the method in its entirety. The workflow itself is published as an online resource together with supporting software and data. The paper concludes with a brief discussion of the complexities of requiring reproducibility in terms of cost versus benefit, and a desiderata with our observations and guidelines for improving reproducibility. This has implications not only in reproducing the work of others from published papers, but reproducing work from one’s own laboratory.

The Way of Significant Innovation: When Gutenberg Became Nonlinear

Nowadays, online learning is booming. Really "booming", actually: thousands of online courses, hundreds of researching groups, dozens of universities online. Eventually, Web Based Learning has left the labs, and begun a fruitful life in the "real world". However,quantity has little to do with "real innovation". In very rare occasions, online courses and teaching institutions are breaking with the rules of the Gutenberg Galaxy: the rules developed during five centuries of printing books. They are designed on a linear basis,and based on conventional text.

Establishing a new paradigm for teaching mathematics at engineering schools

This paper analyzes an ideal model of teaching, thinking after 5-10 years in Universities in the world. We propose the collaborative work for a fruitful learning. According with that, we expose some of our previous projects in this area and some ideas for the ?global education?, focused on the teaching and learning of mathematics to engineering students. Furthermore we explain some of our initiatives for implementing the "Bologna process?. Aspects related to the learning and assessments will be analyzed. The establishment of the new teaching paradigm has to change the learning process and we will suggest some possible initiatives for adapting the learning to the new model. The paper ends by collecting some conclusions.

Uso de un sistema para la gestión del aprendizaje (LMS) de código libre en la Universidad Tecnológica del Suroeste de Guanajuato (UTSOE)

The use of the Information and Communication Technologies (ICT) in Learning Environment allows achieving the maximum interaction between Teachers and Students.The Virtual Learning Environments are computer programs that benefit the learning facilitating the communication between users. Open Source software allow to create the own online modular learning environment with a fast placed in service. In the present paper the use of a Learning Management Systems (LMS) as continuous education tool is proposed.

Interfaz gráfica de usuario para la detección de microcalcificaciones mediante análisis de mamografía digitalizada

The graphical user interface (GUI) are all graphic elements that help to communicate with a system. The design of a GUI allow to land the central idea of a draft information technology. Today technology has become one of the largest and most useful tools to automate and facilitate processes for that reason fit into any kind of productive sectors, for example, in the health sector. The CAD systems (Systems Computer Aided Diagnosis) are the type of technology used in the health sector, in order to automate online modular learning environment with a fast placed in service. In the present paper the use of a Learning Management Systems (LMS) as continuous education tool is proposed.

Robust Real-time Vision-based Aircraft Tracking From Unmanned Aerial Vehicles.

Aircraft tracking plays a key and important role in the Sense-and-Avoid system of Unmanned Aerial Vehicles (UAVs). This paper presents a novel robust visual tracking algorithm for UAVs in the midair to track an arbitrary aircraft at real-time frame rates, together with a unique evaluation system. This visual algorithm mainly consists of adaptive discriminative visual tracking method, Multiple-Instance (MI) learning approach, Multiple-Classifier (MC) voting mechanism and Multiple-Resolution (MR) representation strategy, that is called Adaptive M3 tracker, i.e. AM3. In this tracker, the importance of test sample has been integrated to improve the tracking stability, accuracy and real-time performances. The experimental results show that this algorithm is more robust, efficient and accurate against the existing state-of-art trackers, overcoming the problems generated by the challenging situations such as obvious appearance change, variant surrounding illumination, partial aircraft occlusion, blur motion, rapid pose variation and onboard mechanical vibration, low computation capacity and delayed information communication between UAVs and Ground Station (GS). To our best knowledge, this is the first work to present this tracker for solving online learning and tracking freewill aircraft/intruder in the UAVs.

Real-Time Adaptive Multi-Classifier Multi-Resolution Visual Tracking Framework for Unmanned Aerial Vehicles

This paper presents a novel robust visual tracking framework, based on discriminative method, for Unmanned Aerial Vehicles (UAVs) to track an arbitrary 2D/3D target at real-time frame rates, that is called the Adaptive Multi-Classifier Multi-Resolution (AMCMR) framework. In this framework, adaptive Multiple Classifiers (MC) are updated in the (k-1)th frame-based Multiple Resolutions (MR) structure with compressed positive and negative samples, and then applied them in the kth frame-based Multiple Resolutions (MR) structure to detect the current target. The sample importance has been integrated into this framework to improve the tracking stability and accuracy. The performance of this framework was evaluated with the Ground Truth (GT) in different types of public image databases and real flight-based aerial image datasets firstly, then the framework has been applied in the UAV to inspect the Offshore Floating Platform (OFP). The evaluation and application results show that this framework is more robust, efficient and accurate against the existing state-of-art trackers, overcoming the problems generated by the challenging situations such as obvious appearance change, variant illumination, partial/full target occlusion, blur motion, rapid pose variation and onboard mechanical vibration, among others. To our best knowledge, this is the first work to present this framework for solving the online learning and tracking freewill 2D/3D target problems, and applied it in the UAVs.

Improving flexible databases searches using machine learning

El objetivo principal de este proyecto ha sido introducir aprendizaje automático en la aplicación FleSe. FleSe es una aplicación web que permite realizar consultas borrosas sobre bases de datos nítidos. Para llevar a cabo esta función la aplicación utiliza unos criterios para definir los conceptos borrosos usados para llevar a cabo las consultas. FleSe además permite que el usuario cambie estas personalizaciones. Es aquí donde introduciremos el aprendizaje automático, de tal manera que los criterios por defecto cambien y aprendan en función de las personalizaciones que van realizando los usuarios. Los objetivos secundarios han sido familiarizarse con el desarrollo y diseño web, al igual que recordar y ampliar el conocimiento sobre lógica borrosa y el lenguaje de programación lógica Ciao-Prolog. A lo largo de la realización del proyecto y sobre todo después del estudio de los resultados se demuestra que la agrupación de los usuarios marca la diferencia con la última versión de la aplicación. Esto se basa en la siguiente idea, podemos usar un algoritmo de aprendizaje automático sobre las personalizaciones de los criterios de todos los usuarios, pero la gran diversidad de opiniones de los usuarios puede llevar al algoritmo a concluir criterios erróneos o no representativos. Para solucionar este problema agrupamos a los usuarios intentando que cada grupo tengan la misma opinión o mismo criterio sobre el concepto. Y después de haber realizado las agrupaciones usar el algoritmo de aprendizaje automático para precisar el criterio por defecto de cada grupo de usuarios. Como posibles mejoras para futuras versiones de la aplicación FleSe sería un mejor control y manejo del ejecutable plserver. Este archivo se encarga de permitir a la aplicación web usar el lenguaje de programación lógica Ciao-Prolog para llevar a cabo la lógica borrosa relacionada con las consultas. Uno de los problemas más importantes que ofrece plserver es que bloquea el hilo de ejecución al intentar cargar un archivo con errores y en caso de ocurrir repetidas veces bloquea todas las peticiones siguientes bloqueando la aplicación. Pensando en los usuarios y posibles clientes, sería también importante permitir que FleSe trabajase con bases de datos de SQL en vez de almacenar la base de datos en los archivos de Prolog. Otra posible mejora basarse en distintas características a la hora de agrupar los usuarios dependiendo de los conceptos borrosos que se van ha utilizar en las consultas. Con esto se conseguiría que para cada concepto borroso, se generasen distintos grupos de usuarios, los cuales tendrían opiniones distintas sobre el concepto en cuestión. Así se generarían criterios por defecto más precisos para cada usuario y cada concepto borroso.---ABSTRACT---The main objective of this project has been to introduce machine learning in the application FleSe. FleSe is a web application that makes fuzzy queries over databases with precise information, using defined criteria to define the fuzzy concepts used by the queries. The application allows the users to change and custom these criteria. On this point is where the machine learning would be introduced, so FleSe learn from every new user customization of the criteria in order to generate a new default value of it. The secondary objectives of this project were get familiar with web development and web design in order to understand the how the application works, as well as refresh and improve the knowledge about fuzzy logic and logic programing. During the realization of the project and after the study of the results, I realized that clustering the users in different groups makes the difference between this new version of the application and the previous. This conclusion follows the next idea, we can use an algorithm to introduce machine learning over the criteria that people have, but the problem is the diversity of opinions and judgements that exists, making impossible to generate a unique correct criteria for all the users. In order to solve this problem, before using the machine learning methods, we cluster the users in order to make groups that have the same opinion, and afterwards, use the machine learning methods to precise the default criteria of each users group. The future improvements that could be important for the next versions of FleSe will be to control better the behaviour of the plserver file, that cost many troubles at the beginning of this project and it also generate important errors in the previous version. The file plserver allows the web application to use Ciao-Prolog, a logic programming language that control and manage all the fuzzy logic. One of the main problems with plserver is that when the user uploads a file with errors, it will block the thread and when this happens multiple times it will start blocking all the requests. Oriented to the customer, would be important as well to allow FleSe to manage and work with SQL databases instead of store the data in the Prolog files. Another possible improvement would that the cluster algorithm would be based on different criteria depending on the fuzzy concepts that the selected Prolog file have. This will generate more meaningful clusters, and therefore, the default criteria offered to the users will be more precise.

Un nuevo sistema de gobernanza para afrontar los retos del siglo XXI en la educación universitaria en Perú basado en el modelo de análisis de políticas

Un nuevo sistema de gobernanza para afrontar los retos del siglo XXI en la educación universitaria en Perú basado en el modelo de análisis de políticas, surge de observar el efecto de la competencia en los mercados, de la distribución de los escasos recursos según productividad y rendimiento, y de la gestión ineficiente de las universidades ya que estos parámetros están cambiando los criterios de confianza y legitimidad del sistema universitario en Perú. Las universidades se perciben más como instituciones del sector público, mientras que los servicios que ofrecen deben más bien contribuir a la modernización de la sociedad emergente y a la economía del conocimiento. Las reformas universitarias- iniciadas en los años 80 - han estado inspiradas en las organizaciones universitarias exitosas que han logrado modificar su gobernanza y van dirigidas a transformar ciertas instituciones burocráticas en organizaciones capaces de desempeñar la función de actores en esta competición global por los recursos y los mejores talentos. En este contexto, la universidad peruana se enfrenta a dos grandes desafíos: el de adaptarse a las nuevas perspectivas mundiales, y el poder dar mejor respuesta a las demandas, necesidades y expectativas de la sociedad. Un cambio en el sistema de gobernanza para la educación superior universitaria dará una solución integral a estos desafíos permitiéndole enfrentar los problemas de la universidad para su desarrollo e inserción en las corrientes mundiales. La metodología planteada en la investigación es cualitativa parte del análisis de la realidad como un TODO, sin reducirlos a sus partes integrantes, con la interpretación de los hechos, buscando entender las variables que intervienen. Se propone una política para la educación universitaria en Perú que se permeabilice a la sociedad, cambiando el modelo de planificación de un modelo de reforma social a un modelo de análisis de políticas, donde el Estado Peruano actúe como único responsable de responder a la sociedad demandante como su representante legal, y con unos organismo externo e independiente que siente las bases de la práctica, como se está haciendo en muchos modelos universitarios del mundo. Esta investigación presenta una primera fase conceptual, que aborda la evolución histórica de las universidades en el Perú, analizando y clarificando las fuerzas impulsoras a través del tiempo y distinguir las principales líneas que le imprimen dirección y sentido a los cambios de una realidad educativa universitaria. Así mismo, en esta fase se hace un análisis de la situación actual de las universidades en el Perú para llegar a determinar en qué situación se encuentra y si está preparada para enfrentar los retos de la educación universitaria mundial, para esto se analizan los modelos universitarios de mayor prestigio en el mundo. El marco teórico anterior permite sentar, en una segunda fase de la investigación, las bases científicas del modelo que se propone: el modelo de planificación de análisis de políticas para el sistema universitario peruano. Este modelo de ámbito público propuesto para la educación universitaria peruana basa su estrategia en un modelo de planificación con un objetivo común: “Mejorar la calidad de la educación superior universitaria peruana con el fin de aumentar la empleabilidad y la movilidad de los ciudadanos así como la competitividad internacional de la educación universitaria en Perú”, y con unas líneas de acción concretadas en cuatro objetivos específicos: 1) competencias (genéricas y específicas de las áreas temáticas); 2) enfoques de enseñanza, aprendizaje y evaluación; 3) créditos académicos; 4) calidad de los programa. Así como los fundamentos metodológicos del modelo de análisis de políticas, utilizado como estructura política, teniendo en cuenta las características básicas del modelo: a) Planificación desde arriba; b) Se centra en la toma de decisiones; c) Separación entre conocimiento experto y decisión; d) El estudio de los resultados orienta el proceso decisor. Finalmente, se analiza una fase de validación del modelo propuesto para la educación superior universitaria peruana, con los avances ya realizados en Perú en temas de educación superior, como es, el actual contexto de la nueva Ley Universitaria N°30220 promulgada el 8 de julio de 2014, la creación del SUNEDU y la reorganización del SINEACE, que tienen como propósito atender la crisis universitaria centrada en tres ejes principales incluidos en la ley, considerados como bases para una reforma. Primero, el Estado asume la rectoría de las políticas educativas en todos los niveles educativos. El segundo aspecto consiste en instalar un mecanismo de regulación de la calidad que junto con la reestructuración de aquellos otros existentes debieran sentar las bases para que las familias y estudiantes tengan la garantía pública de que el servicio que se ofrece, sin importar sus características particulares, presenten un mínimo común de calidad y un tercer aspecto es que la ley se reafirma en que la universidad es un espacio de construcción de conocimiento basado en la investigación y la formación integral. Las finalidades, la estructura y organización, las formas de graduación, las características del cuerpo docente, la obligatoriedad por los estudios generales, etc., indican que la reflexión académica es el centro articulador de la vida universitaria. Esta validación también se ha confrontado con los resultados de las entrevistas cualitativas a juicio de experto que se han realizado a rectores de universidades públicas y privadas así como a rectores miembros de la ex ANR, miembros de organizaciones como CONCYTEC, IEP, CNE, CONEAU, ICACIT e investigadores en educación superior, con la finalidad de analizar la sostenibilidad del modelo propuesto en el tiempo. Los resultados evidencian, que en el sistema universitario peruano se puede implementar un cambio hacía un modelo de educación superior universitaria, con una política educativa que se base en un objetivo común claramente definido, un calendario para lograrlo y un conjunto objetivos específicos, con un cambio de estructura política de reforma social a un modelo de análisis de políticas. Así mismo se muestran los distintos aspectos que los interesados en la educación superior universitaria deben considerar, si se quiere ocupar un espacio en el futuro y si interesa que la universidad peruana pueda contribuir para que la sociedad se forje caminos posibles a través de una buena docencia que se refleje en su investigación, con alumnos internacionales, sobre todo, en los postgrados; con un investigación que se traduzca en publicaciones, patentes, etc., de impacto mundial, con relevancia en la sociedad porque contribuye a su desarrollo, concretándose en trabajos de muy diversos tipos, promovidos junto con empresas, gobiernos en sus diversos niveles, instituciones públicas o privadas, etc., para que aporten financiación a la universidad. ABSTRACT A new system of governance to meet the challenges of the twenty-first century university education in Peru based on the model of policy analysis, comes to observe the effect of market competition, distribution of scarce resources according to productivity and performance, and inefficient management of universities as these parameters are changing the criteria of trust and legitimacy of the university system in Peru. Universities are perceived more as public sector institutions, while the services provided should rather contribute to the modernization of society and the emerging knowledge economy. The-university reforms initiated in the 80s - have been inspired by successful university organizations that have succeeded in changing its governance and as attempting to transform certain bureaucratic institutions into organizations that act as actors in this global competition for resources and top talent. In this context, the Peruvian university faces two major challenges: to adapt to the new global outlook, and to better respond to the demands, needs and expectations of society. A change in the system of governance for university education give a comprehensive solution to address these challenges by allowing the problems of the university development and integration into global flows. The methodology proposed in this research is qualitative part of the analysis of reality as a whole, without reducing them to their constituent parts, with the interpretation of the facts, seeking to understand the variables involved. a policy for university education in Peru that permeabilizes society is proposed changing the planning model of a model of social reform a model of policy analysis, where the Peruvian State to act as the sole responsible for responding to the applicant as its legal representative, and with external and independent body that provides the basis of practice, as is being done in many university models in the world. This research presents an initial conceptual phase, which deals with the historical development of universities in Peru, analyzing and clarifying the driving forces over time and distinguish the main lines that give direction and meaning to changes in university educational reality. Also, at this stage an analysis of the current situation of universities in Peru is done to be able to determine what the situation is and whether it is prepared to meet the challenges of the global higher education, for this university models are analyzed most prestigious in the world. The above theoretical framework allows to lay in a second phase of research, the scientific basis of the model proposed: the planning model of policy analysis for the Peruvian university system. This proposed model of public sphere for the Peruvian college bases its strategy on a planning model with a common goal: "To improve the quality of the Peruvian university education in order to enhance the employability and mobility of citizens and the international competitiveness of higher education in Peru ", and lines of action materialized in four specific objectives: 1) competences (generic and specific subject areas); 2) approaches to teaching, learning and assessment; 3) credits; 4) quality of the program. As well as the methodological foundations of policy analysis model, used as political structure, taking into account the basic characteristics of the model: a) Planning from above; b) focuses on decision making; c) Separation between expertise and decision; d) The study of the results process guides the decision maker. Finally, a validation phase of the proposed Peruvian university higher education, with the progress already made in Peru on issues of higher education model is analyzed, as is the current context of the new University Law No. 30220 promulgated on July 8 2014, the creation of SUNEDU and reorganization of SINEACE, which are intended to serve the university crisis centered on three main areas included in the law, considered as the basis for reform. First, the State assumes the stewardship of education policies at all educational levels. The second aspect is to install a mechanism for regulating the quality along with the restructuring of those existing ones should lay the foundation for families and students to guarantee that public service is offered, regardless of their individual characteristics, are of common minimum quality and a third aspect is that the law reaffirms that the university is building a space of research-based knowledge and comprehensive training. The aims, structure and organization, forms of graduation, faculty characteristics, the requirement for the general studies, etc., indicate that the academic reflection is the coordinating center of university life. This validation has also been confronted with the results of qualitative interviews with expert judgment that has been made to directors of public and private universities as well as leading members of the former ANR members of organizations like CONCYTEC, IEP, CNE, CONEAU, ICACIT and researchers in higher education, in order to analyze the sustainability of the proposed model in time. The results show, that the Peruvian university system can implement a change to a model of university education, an educational policy based on clearly defined common goal, a timetable for achieving specific objectives set and, with a change social policy structure to a model of reform policy analysis. It also shows the various aspects that those interested in university education should consider, if you want to occupy a space in the future and if interested in the Peruvian university can contribute to society possible paths is forged through research good teaching, international students, especially in graduate programs; with research that results in publications, patents, etc., global impact, relevance to society because it contributes to their development taking shape in very different types of jobs, promoted with businesses, governments at various levels, public institutions or private, etc., to provide funding to the university.

An exercises editor for an e-learning environment

One of the most important tenets of e-learning is that it bridges work and learning. A great e-learning experience brings learning into the work environment. This is a key point, the capacity to construct a work environment when the student can develop proper tasks to complete the learning process. This paper describes a work environment based on the development of two tools, an exercises editor and an exercises viewer. Both tools are able to manage color images where, because of the implementation of basic steganographic techniques, it is possible to add information, exercises, questions, and so on. The exercises editor allows to decide which information must be visible or remain hidden to the user, when the image is loaded in the exercises viewer. Therefore, it is possible to hide the solutions of the proposed tasks; this is very useful to complete a self-evaluation learning process. These tools constitute a learning architecture with the final objective that learners can apply and practice new concepts or skills.

Entornos virtuales: predicción de la satisfacción en contexto universitario

El presente estudio persigue un doble objetivo: evaluar el grado de satisfacción de los estudiantes con la formación recibida en un entorno virtual y, analizar su capacidad predictiva sobre la satisfacción. Se ha utilizado la versión española del cuestionario Distance Education Learning Environments Survey (Sp-DELES). Los resultados ponen de manifiesto el significativo nivel de satisfacción de los estudiantes con la experiencia y revelan las variables más importantes a la hora de explicar la varianza en satisfacción.

Functional outcomes after stabilization with Dynesys in patients with spinal degenerative diseases

Objective: To know the impact of the Dynesys system on the functional outcomes in patients with spinal degenerative diseases. Summary of background data: Dynesys system has been proposed as an alternative to vertebral fusion for several spinal degenerative diseases. The fact that it has been used in people with different diagnosis criteria using different tools to measure clinical outcomes makes very difficult unifying the results available nowadays. Methods: The data base of Medlars Online International Literature (MEDLINE) via PubMed©, EMBASE©, and the Cochrane Library Plus were reviewed in search of all the studies published until November 2012 in which an operation with Dynesys in patients with spinal degenerative diseases and an evaluation of the results by an analysis of functional outcomes had taken place. No limits were used to article type, date of publication or language. Results: A total of 134 articles were found, 26 of which fulfilled the inclusion criteria after being assessed by two reviewers. All of them were case series, except for a multicenter randomized clinical trial (RCT) and a prospective case-control study. The selected articles made a total of 1507 cases. The most frequent diagnosis were lumbar spinal canal stenosis (LSCS), degenerative disc disease (DDD), degenerative spondylolisthesis (DS) and lumbar degenerative scoliosis (LDS). In cases of lumbar spinal canal stenosis Dynesys was associated to surgical decompression. Several tools to measure the functional disability and general health status were found. Oswestry Disability Index (ODI), the ODI Korean version (K-Odi), Prolo, Sf-36, Sf-12, Roland-Morris disability questionnaire (RMDQ), and the pain Visual Analogue Scale (VAS) were the most used. They showed positive results in all cases series reviewed. In most studies the ODI decreased about 25% (e.g. from a score of 85% to 60%). Better results when dynamic fusion was combined with nerve root decompression were found. Functional outcomes and leg pain scores with Dynesys were statistically non-inferior to posterolateral spinal fusion using autogenous bone. When Dynesys and decompression was compared with posterior interbody lumbar fixation (PLIF) and decompression, differences in ODI and VAS were not statistically significant. Conclusions: In patients with spinal degenerative diseases due to degenerative disc disorders, spinal canal stenosis and degenerative spondylolisthesis, surgery with Dynesys and decompression improves functional outcomes, decreases disability, and reduces back and leg pain. More studies are needed to conclude that dynamic stabilization is better than posterolateral and posterior interbody lumbar fusion. Studies comparing Dynesys with decompression against decompression alone should be done in order to isolate the effect of the dynamic stabilization.

GPGPU implementation of growing neural gas: application to 3D scene reconstruction

Self-organising neural models have the ability to provide a good representation of the input space. In particular the Growing Neural Gas (GNG) is a suitable model because of its flexibility, rapid adaptation and excellent quality of representation. However, this type of learning is time-consuming, especially for high-dimensional input data. Since real applications often work under time constraints, it is necessary to adapt the learning process in order to complete it in a predefined time. This paper proposes a Graphics Processing Unit (GPU) parallel implementation of the GNG with Compute Unified Device Architecture (CUDA). In contrast to existing algorithms, the proposed GPU implementation allows the acceleration of the learning process keeping a good quality of representation. Comparative experiments using iterative, parallel and hybrid implementations are carried out to demonstrate the effectiveness of CUDA implementation. The results show that GNG learning with the proposed implementation achieves a speed-up of 6× compared with the single-threaded CPU implementation. GPU implementation has also been applied to a real application with time constraints: acceleration of 3D scene reconstruction for egomotion, in order to validate the proposal.