Project Management Learning in a Collaborative Distant Learning Context - An Actual On-going Experience

The goal of this paper is to show the results of an on-going experience on teaching project management to grade students by following a development scheme of management related competencies on an individual basis. In order to achieve that goal, the students are organized in teams that must solve a problem and manage the development of a feasible solution to satisfy the needs of a client. The innovative component advocated in this paper is the formal introduction of negotiating and virtual team management aspects, as different teams from different universities at different locations and comprising students with different backgrounds must collaborate and compete amongst them. The different learning aspects are identified and the improvement levels are reflected in a rubric that has been designed ad hoc for this experience. Finally, the effort frameworks for the student and instructor have been established according to the requirements of the Bologna paradigms. This experience is developed through a software-based support system allowing blended learning for the theoretical and individual?s work aspects, blogs, wikis, etc., as well as project management tools based on WWW that allow the monitoring of not only the expected deliverables and the achievement of the goals but also the progress made on learning as established in the defined rubri

PBL (Project Based Learning) en entornos colaborativos virtuales en el contexto del EEES (Espacio Europeo de Educación Superior)

Premio a la Innovación en la Enseñanza 2011[ES] En los últimos años se han producido una serie de vertiginosos cambios en las costumbres de las sociedades avanzadas que han provocado sin duda alguna una transformación sin precedentes de la vida diaria de las personas. La implantación del Espacio Europeo de Educación Superior es, asimismo, una transformación sin parangón que afectará a todos los miembros de la comunidad universitaria, así como a todas sus partes interesadas. Las oportunidades que surgen en consonancia con los procesos de cambios en los que nos encontramos inmersos son igualmente excepcionale

Adquisición de competencias en dirección de proyectos en un contexto colaborativo descentralizado

Se presenta una experiencia educativa en el ámbito de la adquisición de competencias relacionadas con la dirección de proyectos. Alumnos de tres universidades y tres titulaciones distintas colaboran en la realización de un proyecto conjunto como instrumento conductor del proceso de enseñanzaaprendizaje. El objetivo es valorar la idoneidad de un enfoque multidisciplinar de colaboración a distancia basado en la metodología Project Based Learning en el actual contexto de cambio de paradigma educativo. La experiencia resulta innovadora y es utilizada para definir una rúbrica que permita medir un determinado número de competencias relacionadas con la ingeniería de proyectos y la dirección de proyectos de ingeniería. Un sistema software facilita la integración de las métricas definidas y simplifica los procesos de supervisión de la adquisición de competencias

Análisis de resultados del uso de una plataforma Moodle utilizando algoritmos de clasificación jerárquica aglomerativa

5 p.En este trabajo se desarrolla un análisis del uso de una plataforma de enseñanza electronica (Moodle) utilizando una técnica de clasificación jerárquica aglomerativa. Aparecen tres perfiles de ususarios claramente diferenciados por sus respuestas. Se intenta llegar a unas conclusiones que son sirvan para entender los diversos tipos de usuarios y sus comportamientos ante una plataforma de este tip

Estimation of lamb weight using transfer learning and regression

Meat production needs of accurate measurement of livestock weight. In lambs, traditional scales are still used to weigh live animals, which is a tedious process for the operators and stressful for the animal. In this paper, we propose a method to estimate the weight of live lambs automatically, fast, non-invasive and affordably. The system only requires a camera like those that can be found in mobile phones. Our approach is based on the use of a known Convolutional Neural Network architecture (Xception) pre-trained on the ImageNet dataset. The acquired knowledge during training is used to estimate the weight, which is known as transfer learning. The best results are achieved with a model that receives the image, the sex of the lamb and the height from where the image is taken. A mean absolute error (MAE) of 0.58 kg and an R2 of 0.96 were obtained, improving on current techniques. Only one image and two values specified by the user (sex and height) allow to estimate with a minimum error the optimal weight of a lamb, maximising the economic profit

A fault detection system for a geothermal heat exchanger sensor based on intelligent techniques

[Abstract ]:This paper proposes a methodology for dealing with an issue of crucial practical importance in real engineering systems such as fault detection and recovery of a sensor. The main goal is to define a strategy to identify a malfunctioning sensor and to establish the correct measurement value in those cases. As study case, we use the data collected from a geothermal heat exchanger installed as part of the heat pump installation in a bioclimatic house. The sensor behaviour is modeled by using six different machine learning techniques: Random decision forests, gradient boosting, extremely randomized trees, adaptive boosting, k-nearest neighbors, and shallow neural networks. The achieved results suggest that this methodology is a very satisfactory solution for this kind of systems.Junta de Castilla y León; LE078G18. UXXI2018/000149. U-220.Ministerio de Economía, Industria y Competitividad; DPI2016-79960-C3-2-

Segmentación autónoma y extracción de características geométricas en Diatomeas

En este trabajo se ha realizado una aplicación que extrae automáticamente las principales características geométricas de las algas diatomeas. Estas algas resultan de gran utilidad en la monitorización de la calidad de las aguas, de ahí la importancia que la automatización de los procesos de análisis conlleva. La aplicación extrae 15 descriptores geométricos de cada diatomea almacenando su valor tanto en píxeles como en micrómetros. Se obtiene también la presencia o no del estigma al ser éste un valor determinante en la clasificación. Para llegar a este resultado es necesario realizar con anterioridad una segmentación autónoma de las imágenes digitales obtenidas mediante fotografía digital. Dicha segmentación autónoma requirió del desarrollo de un método específico basado en la combinación de dos técnicas: binarización por umbralización y detección de bordes utilizando el filtro de Canny. La separación de objetos solapados se resolvió mediante un método que combina binarizaciones, filtrados, adelgazamientos, operaciones morfológicas y el detector de bordes de Canny. Los valores geométricos calculados se compararon con los resultados proporcionados por un experto, tras realizar las mediciones de forma manual. Los resultados son muy similares por lo que se considera correcto el desarrollo realizad

Information system for image classification based on frequency curve proximity

With the size digital collections are currently reaching, retrieving the best match of a document from large collections by comparing hundreds of tags is a task that involves considerable algorithm complexity, even more so if the number of tags in the collection is not fixed. For these cases, similarity search appears to be the best retrieval method, but there is a lack of techniques suited for these conditions. This work presents a combination of machine learning algorithms put together to find the most similar object of a given one in a set of pre-processed objects based only on their metadata tags. The algorithm represents objects as character frequency curves and is capable of finding relationships between objects without an apparent association. It can also be parallelized using MapReduce strategies to perform the search. This method can be applied to a wide variety of documents with metadata tags. The case-study used in this work to demonstrate the similarity search technique is that of a collection of image objects in JavaScript Object Notation (JSON) containing metadata tags.This work has been done in the context of the project “ASASEC (Advisory System Against Sexual Exploitation of Children)” (HOME/2010/ISEC/AG/043) supported by the European Union with the program “Prevention and fight against crime”.info:eu-repo/semantics/publishedVersio

A Framework for the Optimization of Complex Cyber-Physical Systems via Directed Acyclic Graph

Mathematical modeling and data-driven methodologies are frequently required to optimize industrial processes in the context of Cyber-Physical Systems (CPS). This paper introduces the PipeGraph software library, an open-source python toolbox for easing the creation of machine learning models by using Directed Acyclic Graph (DAG)-like implementations that can be used for CPS. scikit-learn’s Pipeline is a very useful tool to bind a sequence of transformers and a final estimator in a single unit capable of working itself as an estimator. It sequentially assembles several steps that can be cross-validated together while setting different parameters. Steps encapsulation secures the experiment from data leakage during the training phase. The scientific goal of PipeGraph is to extend the concept of Pipeline by using a graph structure that can handle scikit-learn’s objects in DAG layouts. It allows performing diverse operations, instead of only transformations, following the topological ordering of the steps in the graph; it provides access to all the data generated along the intermediate steps; and it is compatible with GridSearchCV function to tune the hyperparameters of the steps. It is also not limited to (X,y) entries. Moreover, it has been proposed as part of the scikit-learn-contrib supported project, and is fully compatible with scikit-learn. Documentation and unitary tests are publicly available together with the source code. Two case studies are analyzed in which PipeGraph proves to be essential in improving CPS modeling and optimization: the first is about the optimization of a heat exchange management system, and the second deals with the detection of anomalies in manufacturing processes