Project management competence analysis in rural communities through territorial representation: application to Aymara women communities in Puno (Peru)

The acquisition of technical, contextual and behavioral competences is a prerequisite for sustainable development and strengthening of rural communities. Territorial display of the status of these skills helps to design the necessary learning, so its inclusion in planning processes is useful for decision making. The article discusses the application of visual representation of competences in a rural development project with Aymara women communities in Peru. The results show an improvement of transparency and dialogue, resulting in a more successful project management and strengthening of social organization.

Timed mind maps using MINDMANAGER & MS-PROJECT for educational innovation

The adaptation to the European Higher Education Area (EHEA) is becoming a great challenge for the University Community, especially for its teaching and research staff, which is involved actively in the teaching-learning process. It is also inducing a paradigm change for lecturers and students. Among the methodologies used for processes of teaching innovation, system thinking plays an important role when working mainly with mind maps, and is focused to highlighting the essence of the knowledge, allowing its visual representation. In this paper, a method for using these mind maps for organizing a particular subject is explained. This organization is completed with the definition of duration, precedence relationships and resources for each of these activities, as well as with their corresponding monitoring. Mind maps are generated by means of the MINDMANAGER package whilst Ms-PROJECT is used for establishing tasks relationships, durations, resources, and monitoring. Summarizing, a procedure and the necessary set of applications for self organizing and managing (timed) scheduled teaching tasks has been described in this paper.

Timed mind maps using mindmanager & msproject for educational innovation

The adaptation to the European Higher Education Area (EHEA) is becoming a great challenge for the University Community, especially for its teaching and research staff, which is involved actively in the teaching-learning process. It is also inducing a paradigm change for lecturers and students. Among the methodologies used for processes of teaching innovation, system thinking plays an important role when working mainly with mind maps, and is focused to highlighting the essence of the knowledge, allowing its visual representation. In this paper, a method for using these mind maps for organizing a particular subject is explained. This organization is completed with the definition of duration, precedence relationships and resources for each of these activities, as well as with their corresponding monitoring. Mind maps are generated by means of the MINDMANAGER package whilst Ms-PROJECT is used for establishing tasks relationships, durations, resources, and monitoring. Summarizing, a procedure and the necessary set of applications for self organizing and managing (timed) scheduled teaching tasks has been described in this paper

Optimización de los procesos de medida e interpretación de la tomografía geoeléctrica en la prospección superficial

Debido al carácter innovador de los objetivos científico-tecnológicos planteados al inicio de la presente Tesis doctoral, además de la primera recopilación bibliográfica, a lo largo del desarrollo de la misma se ha realizado una actualización bibliográfica continua centrada en los desarrollos relativos a la instrumentación, las aplicaciones y los procesos de interpretación de las técnicas de tomografía eléctrica. Durante el desarrollo del presente trabajo, se han realizado una serie de campañas diferenciadas, tanto por los ambientes geológicos y las condiciones antrópicas en los que se han efectuado los perfiles geoeléctricos, como por la profundidad y los objetivos de la prospección. En esas campañas se han obtenido, mediante el programa Res2DInv, las secciones tomográficas con la configuración de variables por defecto y se ha realizado una interpretación estructural de las mismas. Como parte central del desarrollo de esta investigación se han efectuado varios procesos de optimización: Comparación y optimización de los dispositivos empleados para la medición de perfiles de resistividad de cara a la obtención de secciones tomográficas que presenten la mayor resolución en distintos ambientes geológicos. Selección de los rangos de representación (lineales y logarítmicos) y de la gradación cromática que, pudiendo adoptarse de forma generalizada, permita la mejor interpretación gráfica para usuarios no avanzados. Diseño de criterios para la selección del factor de amortiguamiento, como parámetro crítico en los procesos de inversión tomográfica de perfiles geoeléctricos de superficie, de forma que los modelos resultantes alcancen la mejor relación entre fiabilidad y error respecto a los valores medidos. Paralelamente a los procesos anteriores se ha definido un índice de calidad de la inversión, que es directamente normalizado y que permite evaluar el grado en el que pueden considerarse fiables tanto los valores de resistividad obtenidos como su distribución espacial. El índice desarrollado (IRI) está basado en la influencia que tiene la resistividad inicial del modelo de inversión en los valores de cada una de las celdas de la malla de inversión. Tras un exhaustivo análisis estadístico se ha verificado que, a diferencia de otros índices utilizados hasta la fecha, dicho índice no está afectado ni por la profundidad de investigación y la resolución de los dispositivos, ni por la distribución de resistividades que presente el subsuelo. ABSTRACT Due to the innovative character of the scientific and technological objectives proposed at the beginning of this thesis, in addition to preparatory bibliographic reference, a constant bibliographic update on developments related to instrumentation, applications and interpretation processes for electric tomography has been performed all through the development of the work. Several measuring campaigns were performed during the development of the thesis. These campaigns, in which the geoelectric profiles were measured, varied in several aspects, both in the geological and anthropic conditions, and also in the depth and objectives of the prospection. Tomographic sections were obtained and interpretated by making use of the Res2DInv software configured with the default variables. As part of the core development in this research, several optimization processes have been done: Comparison and optimization of the devices used in the measurement of resistivity profiles. This optimization allows increasing the resolution of tomographic sections in different geological conditions. Selection of the best visual representation for the tomographic sections. This involves the selection of the range of values and type of scale (linear vs. logarithmic) as well as the chromatic graduation. This selection allows improving the interpretation of tomographic sections for the non-expert eye. Devising of criteria for the selection of the damping factor, as the critical parameter in processes of tomographic inversion of superficial geoelectrical profiles. The use of these criteria allows selecting the best factors to obtain the best ratio between reliability and error (in relation to the mean values) for the resulting model. In addition to the aforementioned processes, and as part of the work within this thesis, it has been defined a normalized quality index for inversion. This index allows evaluating the degree of reliability of the obtained resistivity values and spatial distribution. The developed index, termed IRI in the thesis, is based on the influence shown by the initial resistivity of the inversion model on the values of each of the cells of the inversion mesh. After an exhaustive statistical analysis it was verified that the IRI index is neither affected by the investigation depth, nor the resolution of the devices, nor the resistivity’s distribution of the sub soil. This independency is a unique characteristic of the IRI index, not present in other indexes developed and used till date.

Nuevos Esquemas de Visualizaciones para Mejorar la Comprensibilidad de Modelos de Data Mining

La gran cantidad de datos que se registran diariamente en los sistemas de base de datos de las organizaciones ha generado la necesidad de analizarla. Sin embargo, se enfrentan a la complejidad de procesar enormes volúmenes de datos a través de métodos tradicionales de análisis. Además, dentro de un contexto globalizado y competitivo las organizaciones se mantienen en la búsqueda constante de mejorar sus procesos, para lo cual requieren herramientas que les permitan tomar mejores decisiones. Esto implica estar mejor informado y conocer su historia digital para describir sus procesos y poder anticipar (predecir) eventos no previstos. Estos nuevos requerimientos de análisis de datos ha motivado el desarrollo creciente de proyectos de minería de datos. El proceso de minería de datos busca obtener desde un conjunto masivo de datos, modelos que permitan describir los datos o predecir nuevas instancias en el conjunto. Implica etapas de: preparación de los datos, procesamiento parcial o totalmente automatizado para identificar modelos en los datos, para luego obtener como salida patrones, relaciones o reglas. Esta salida debe significar un nuevo conocimiento para la organización, útil y comprensible para los usuarios finales, y que pueda ser integrado a los procesos para apoyar la toma de decisiones. Sin embargo, la mayor dificultad es justamente lograr que el analista de datos, que interviene en todo este proceso, pueda identificar modelos lo cual es una tarea compleja y muchas veces requiere de la experiencia, no sólo del analista de datos, sino que también del experto en el dominio del problema. Una forma de apoyar el análisis de datos, modelos y patrones es a través de su representación visual, utilizando las capacidades de percepción visual del ser humano, la cual puede detectar patrones con mayor facilidad. Bajo este enfoque, la visualización ha sido utilizada en minería datos, mayormente en el análisis descriptivo de los datos (entrada) y en la presentación de los patrones (salida), dejando limitado este paradigma para el análisis de modelos. El presente documento describe el desarrollo de la Tesis Doctoral denominada “Nuevos Esquemas de Visualizaciones para Mejorar la Comprensibilidad de Modelos de Data Mining”. Esta investigación busca aportar con un enfoque de visualización para apoyar la comprensión de modelos minería de datos, para esto propone la metáfora de modelos visualmente aumentados. ABSTRACT The large amount of data to be recorded daily in the systems database of organizations has generated the need to analyze it. However, faced with the complexity of processing huge volumes of data over traditional methods of analysis. Moreover, in a globalized and competitive environment organizations are kept constantly looking to improve their processes, which require tools that allow them to make better decisions. This involves being bettered informed and knows your digital story to describe its processes and to anticipate (predict) unanticipated events. These new requirements of data analysis, has led to the increasing development of data-mining projects. The data-mining process seeks to obtain from a massive data set, models to describe the data or predict new instances in the set. It involves steps of data preparation, partially or fully automated processing to identify patterns in the data, and then get output patterns, relationships or rules. This output must mean new knowledge for the organization, useful and understandable for end users, and can be integrated into the process to support decision-making. However, the biggest challenge is just getting the data analyst involved in this process, which can identify models is complex and often requires experience not only of the data analyst, but also the expert in the problem domain. One way to support the analysis of the data, models and patterns, is through its visual representation, i.e., using the capabilities of human visual perception, which can detect patterns easily in any context. Under this approach, the visualization has been used in data mining, mostly in exploratory data analysis (input) and the presentation of the patterns (output), leaving limited this paradigm for analyzing models. This document describes the development of the doctoral thesis entitled "New Visualizations Schemes to Improve Understandability of Data-Mining Models". This research aims to provide a visualization approach to support understanding of data mining models for this proposed metaphor visually enhanced models.

Herramienta de medida y visualización de prestaciones basada en eventos para especificaciones RVC-CAL

Este proyecto fin de grado presenta dos herramientas, Papify y Papify-Viewer, para medir y visualizar, respectivamente, las prestaciones a bajo nivel de especificaciones RVC-CAL basándose en eventos hardware. RVC-CAL es un lenguaje de flujo de datos estandarizado por MPEG y utilizado para definir herramientas relacionadas con la codificación de vídeo. La estructura de los programas descritos en RVC-CAL se basa en unidades funcionales llamadas actores, que a su vez se subdividen en funciones o procedimientos llamados acciones. ORCC (Open RVC-CAL Compiler) es un compilador de código abierto que utiliza como entrada descripciones RVC-CAL y genera a partir de ellas código fuente en un lenguaje dado, como por ejemplo C. Internamente, el compilador ORCC se divide en tres etapas distinguibles: front-end, middle-end y back-end. La implementación de Papify consiste en modificar la etapa del back-end del compilador, encargada de la generación de código, de modo tal que los actores, al ser traducidos a lenguaje C, queden instrumentados con PAPI (Performance Application Programing Interface), una herramienta utilizada como interfaz a los registros contadores de rendimiento (PMC) de los procesadores. Además, también se modifica el front-end para permitir identificar cierto tipo de anotaciones en las descripciones RVC-CAL, utilizadas para que el diseñador pueda indicar qué actores o acciones en particular se desean analizar. Los actores instrumentados, además de conservar su funcionalidad original, generan una serie de ficheros que contienen datos sobre los distintos eventos hardware que suceden a lo largo de su ejecución. Los eventos incluidos en estos ficheros son configurables dentro de las anotaciones previamente mencionadas. La segunda herramienta, Papify-Viewer, utiliza los datos generados por Papify y los procesa, obteniendo una representación visual de la información a dos niveles: por un lado, representa cronológicamente la ejecución de la aplicación, distinguiendo cada uno de los actores a lo largo de la misma. Por otro lado, genera estadísticas sobre la cantidad de eventos disparados por acción, actor o núcleo de ejecución y las representa mediante gráficos de barra. Ambas herramientas pueden ser utilizadas en conjunto para verificar el funcionamiento del programa, balancear la carga de los actores o la distribución por núcleos de los mismos, mejorar el rendimiento y diagnosticar problemas. ABSTRACT. This diploma project presents two tools, Papify and Papify-Viewer, used to measure and visualize the low level performance of RVC-CAL specifications based on hardware events. RVC-CAL is a dataflow language standardized by MPEG which is used to define video codec tools. The structure of the applications described in RVC-CAL is based on functional units called actors, which are in turn divided into smaller procedures called actions. ORCC (Open RVC-CAL Compiler) is an open-source compiler capable of transforming RVC-CAL descriptions into source code in a given language, such as C. Internally, the compiler is divided into three distinguishable stages: front-end, middle-end and back-end. Papify’s implementation consists of modifying the compiler’s back-end stage, which is responsible for generating the final source code, so that translated actors in C code are now instrumented with PAPI (Performance Application Programming Interface), a tool that provides an interface to the microprocessor’s performance monitoring counters (PMC). In addition, the front-end is also modified in such a way that allows identification of a certain type of annotations in the RVC-CAL descriptions, allowing the designer to set the actors or actions to be included in the measurement. Besides preserving their initial behavior, the instrumented actors will also generate a set of files containing data about the different events triggered throughout the program’s execution. The events included in these files can be configured inside the previously mentioned annotations. The second tool, Papify-Viewer, makes use of the files generated by Papify to process them and provide a visual representation of the information in two different ways: on one hand, a chronological representation of the application’s execution where each actor has its own timeline. On the other hand, statistical information is generated about the amount of triggered events per action, actor or core. Both tools can be used together to assert the normal functioning of the program, balance the load between actors or cores, improve performance and identify problems.

Multiple feature points representation in target localization of wireless visual sensor networks

This paper discusses the target localization problem in wireless visual sensor networks. Additive noises and measurement errors will affect the accuracy of target localization when the visual nodes are equipped with low-resolution cameras. In the goal of improving the accuracy of target localization without prior knowledge of the target, each node extracts multiple feature points from images to represent the target at the sensor node level. A statistical method is presented to match the most correlated feature point pair for merging the position information of different sensor nodes at the base station. Besides, in the case that more than one target exists in the field of interest, a scheme for locating multiple targets is provided. Simulation results show that, our proposed method has desirable performance in improving the accuracy of locating single target or multiple targets. Results also show that the proposed method has a better trade-off between camera node usage and localization accuracy.

MEDVIR: 3D visual interface applied to gene profile analisys.

The origins for this work arise in response to the increasing need for biologists and doctors to obtain tools for visual analysis of data. When dealing with multidimensional data, such as medical data, the traditional data mining techniques can be a tedious and complex task, even to some medical experts. Therefore, it is necessary to develop useful visualization techniques that can complement the expert’s criterion, and at the same time visually stimulate and make easier the process of obtaining knowledge from a dataset. Thus, the process of interpretation and understanding of the data can be greatly enriched. Multidimensionality is inherent to any medical data, requiring a time-consuming effort to get a clinical useful outcome. Unfortunately, both clinicians and biologists are not trained in managing more than four dimensions. Specifically, we were aimed to design a 3D visual interface for gene profile analysis easy in order to be used both by medical and biologist experts. In this way, a new analysis method is proposed: MedVir. This is a simple and intuitive analysis mechanism based on the visualization of any multidimensional medical data in a three dimensional space that allows interaction with experts in order to collaborate and enrich this representation. In other words, MedVir makes a powerful reduction in data dimensionality in order to represent the original information into a three dimensional environment. The experts can interact with the data and draw conclusions in a visual and quickly way.

An approach to a model of the visual cortex: disorders of vision

One of the most challenging problems that must be solved by any theoretical model purporting to explain the competence of the human brain for relational tasks is the one related with the analysis and representation of the internal structure in an extended spatial layout of múltiple objects. In this way, some of the problems are related with specific aims as how can we extract and represent spatial relationships among objects, how can we represent the movement of a selected object and so on. The main objective of this paper is the study of some plausible brain structures that can provide answers in these problems. Moreover, in order to achieve a more concrete knowledge, our study will be focused on the response of the retinal layers for optical information processing and how this information can be processed in the first cortex layers. The model to be reported is just a first trial and some major additions are needed to complete the whole vision process.

Online Learning-based Robust Visual Tracking for Autonomous Landing of Unmanned Aerial Vehicles

Autonomous landing is a challenging and important technology for both military and civilian applications of Unmanned Aerial Vehicles (UAVs). In this paper, we present a novel online adaptive visual tracking algorithm for UAVs to land on an arbitrary field (that can be used as the helipad) autonomously at real-time frame rates of more than twenty frames per second. The integration of low-dimensional subspace representation method, online incremental learning approach and hierarchical tracking strategy allows the autolanding task to overcome the problems generated by the challenging situations such as significant appearance change, variant surrounding illumination, partial helipad occlusion, rapid pose variation, onboard mechanical vibration (no video stabilization), low computational capacity and delayed information communication between UAV and Ground Control Station (GCS). The tracking performance of this presented algorithm is evaluated with aerial images from real autolanding flights using manually- labelled ground truth database. The evaluation results show that this new algorithm is highly robust to track the helipad and accurate enough for closing the vision-based control loop.

Online Learning-based Robust Visual Tracking for Autonomous Landing of Unmanned Aerial Vehicles

Autonomous landing is a challenging and important technology for both military and civilian applications of Unmanned Aerial Vehicles (UAVs). In this paper, we present a novel online adaptive visual tracking algorithm for UAVs to land on an arbitrary field (that can be used as the helipad) autonomously at real-time frame rates of more than twenty frames per second. The integration of low-dimensional subspace representation method, online incremental learning approach and hierarchical tracking strategy allows the autolanding task to overcome the problems generated by the challenging situations such as significant appearance change, variant surrounding illumination, partial helipad occlusion, rapid pose variation, onboard mechanical vibration (no video stabilization), low computational capacity and delayed information communication between UAV and Ground Control Station (GCS). The tracking performance of this presented algorithm is evaluated with aerial images from real autolanding flights using manually- labelled ground truth database. The evaluation results show that this new algorithm is highly robust to track the helipad and accurate enough for closing the vision-based control loop.