Global macrozoobenthos production and energy budget data base V150731, with link to database

I developed a new model for estimating annual production-to-biomass ratio P/B and production P of macrobenthic populations in marine and freshwater habitats. Self-learning artificial neural networks (ANN) were used to model the relationships between P/B and twenty easy-to-measure abiotic and biotic parameters in 1252 data sets of population production. Based on log-transformed data, the final predictive model estimates log(P/B) with reasonable accuracy and precision (r2 = 0.801; residual mean square RMS = 0.083). Body mass and water temperature contributed most to the explanatory power of the model. However, as with all least squares models using nonlinearly transformed data, back-transformation to natural scale introduces a bias in the model predictions, i.e., an underestimation of P/B (and P). When estimating production of assemblages of populations by adding up population estimates, accuracy decreases but precision increases with the number of populations in the assemblage.

Distributed Fault Diagnosis Using Bayesian Reasoning in MAGNETO

Many of the emerging telecom services make use of Outer Edge Networks, in particular Home Area Networks. The configuration and maintenance of such services may not be under full control of the telecom operator which still needs to guarantee the service quality experienced by the consumer. Diagnosing service faults in these scenarios becomes especially difficult since there may be not full visibility between different domains. This paper describes the fault diagnosis solution developed in the MAGNETO project, based on the application of Bayesian Inference to deal with the uncertainty. It also takes advantage of a distributed framework to deploy diagnosis components in the different domains and network elements involved, spanning both the telecom operator and the Outer Edge networks. In addition, MAGNETO features self-learning capabilities to automatically improve diagnosis knowledge over time and a partition mechanism that allows breaking down the overall diagnosis knowledge into smaller subsets. The MAGNETO solution has been prototyped and adapted to a particular outer edge scenario, and has been further validated on a real testbed. Evaluation of the results shows the potential of our approach to deal with fault management of outer edge networks.

La visita a campo como metodología para el proceso de enseñanza-aprendizaje

Dentro de la enseñanza de la geotecnia los viajes a campo son una herramienta útil para superar las limitaciones asociadas a la enseñanza en el aula así como para promover el autoaprendizaje del alumno, el cual se enfrenta en primera persona a la información en estado bruto. Mediante esta comunicación compartimos la experiencia de la visita a las obras de construcción de los Túneles de Sorbas y El Almendral dentro del Máster de "Geología Aplicada a la Obra Civil y los Recursos Hídricos" ofertado por la Universidad de Granada, comentando, con un enfoque docente, la planificación de la actividad en función de los resultados de aprendizaje deseados. Fieldtrips are a good tool to overcome the inherent difficulties associated to teaching engineering geology at the classroom and to encourage student self-learning, when they face raw data. In this paper, we share our recent experience with the organization of a fieldtrip to two tunneling construction site (Sorbas Tunnel and El Almendral Tunnel) for the MSc program of “Applied Geology in Civil Engineering and Water Resources” offered by the University of Granada, discussing, with a educational point of view, the planning and learning outcomes.

Desarrollo de herramientas de autoevaluación de prácticas de procesado digital de la señal.

El objetivo de este proyecto es desarrollar un conjunto de herramientas de auto aprendizaje y autoevaluación del laboratorio de la asignatura "Procesado Digital de la Señal", perteneciente al plan de grado de la Escuela Técnica Superior de Ingeniería y Sistemas de Telecomunicación de la Universidad Politécnica de Madrid. Con ello se pretende de mejorar el rendimiento académico de los alumnos en dicha asignatura y en la materia "Señales y Sistemas" en general. Para la realización de las prácticas se emplea Matlab, de modo que es necesario integrar esta herramienta en el laboratorio con MOODLE, plataforma de e-learning utilizada para la gestión de las asignaturas a nivel docente, para proporcionar material de estudio y programar actividades de aprendizaje y evaluación. Será fundamental el análisis de la integración de Matlab con MOODLE, de modo que en función de los resultados de los alumnos, se les propongan repeticiones de apartados erróneos, revisiones de resultados y otros aspectos, como autoaprendizaje y autoevaluación que permitan la obtención de las competencias y alcanzar los resultados de aprendizaje, y a los profesores que imparten la asignatura, como herramienta para detectar las deficiencias más significativas en la programación y en las metodologías empleadas en la asignatura para corregir las carencias de los alumnos. ABSTRACT: The aim of this project will be the development of self-learning and self- assessment lab tools for the course "Procesado Digital de la Señal" in order to improve student’s performance in that subject and in the matter "Señales y Sistemas " for grades taught at the Escuela Universitaria de Ingeniería Técnica de Telecomunicación of the Universidad Politécnica de Madrid today. Matlab is used to perform laboratory practices of "Procesado Digital de la Señal “. Matlab is a numerical calculation program. A very powerful tool with a great mathematical processing performance level, so it is necessary to integrate this tool in the laboratory with MOODLE, the current e-learning platform used at the Universidad Politécnica de Madrid for the management of teaching subjects to provide material and to program learning and assessment activities for students. It is therefore essential the analysis of the Matlab integration with Moodle. Thus, depending on the results and grades that students get along the way in the various activities evaluators should conduct, they propose, for example, repetitions of erroneous exercises, reviews of some results and other aspects such as self-learning and self-assessment. This would allow students to obtain the skills and learning to achieve the results set as a target. For teachers who teach the subject will also be a preview of the notes as these tools will be used to identify the most significant shortcomings both in programming and in the methodologies used in "Procesado Digital de la Señal " to act accordingly and correcting shortcomings of the enrolled students.

CAS: A tool for improving autonomous work

The EHEA proposes a student-centered teaching model. Therefore, it seems necessary to actively involve the students in the teaching-learning process. Increasing the active participation of the students is not always easy in mathematical topics, since, when the students just enter the University, their ability to carry out autonomous mathematical work is scarce. In this paper we present some experiences related with the use of Computer Algebra Systems (CAS). All the experiences are designed in order to develop some mathematical competencies and mainly self-learning, the use of technology and team-work. The experiences include some teachers? proposals including: small projects to be executed in small groups, participation in competitions, the design of different CAS-Toolboxes, etc. The results obtained in the experiences, carried out with different groups of students from different engineering studies at different universities, makes us slightly optimistic about the educational value of the model.

Experiences with free and open courses using on-line multimedia resources

This paper analyzes the learning experiences and opinions obtained from a group of undergraduate students in their interaction with several on-line multimedia resources included in a free on-line course about Computer Networks. These new educational resources employed are based on the Web2.0 approach such as blogs, videos and virtual labs which have been added in a web-site for distance self-learning.

Open educational resources: the role of OCW, blogs and videos in computer network classrooms

This paper analyzes the learning experiences and opinions obtained from a group of undergraduate students in their interaction with several on-line multimedia resources included in a free on-line course about Computer Networks. These new educational resources employed are based on the Web 2.0 approach such as blogs, videos and virtual labs which have been added in a web-site for distance self-learning.

Practical experiences on a real pumping system emulated by a hardware model and used as a remote laboratory

Paper submitted to ACE 2013, 10th IFAC Symposium on Advances in Control Education, University of Sheffield, UK, August 28-30, 2013.

New Approaches for Teaching Soil and Rock Mechanics Using Information and Communication Technologies

Soil and rock mechanics are disciplines with a strong conceptual and methodological basis. Initially, when engineering students study these subjects, they have to understand new theoretical phenomena, which are explained through mathematical and/or physical laws (e.g. consolidation process, water flow through a porous media). In addition to the study of these phenomena, students have to learn how to carry out estimations of soil and rock parameters in laboratories according to standard tests. Nowadays, information and communication technologies (ICTs) provide a unique opportunity to improve the learning process of students studying the aforementioned subjects. In this paper, we describe our experience of the incorporation of ICTs into the classical teaching-learning process of soil and rock mechanics and explain in detail how we have successfully developed various initiatives which, in summary, are: (a) implementation of an online social networking and microblogging service (using Twitter) for gradually sending key concepts to students throughout the semester (gradual learning); (b) detailed online virtual laboratory tests for a delocalized development of lab practices (self-learning); (c) integration of different complementary learning resources (e.g. videos, free software, technical regulations, etc.) using an open webpage. The complementary use to the classical teaching-learning process of these ICT resources has been highly satisfactory for students, who have positively evaluated this new approach.

Critical success factors for IS executive careers

This article qualitatively analyzes the Critical Success Factors (CSFs) for Information Systems (IS) executive careers based on evidence gathered from five case studies carried out in 1997. Typical IS executive career paths are presented within a time series style and the CSFs are interpreted within a descriptive framework by synthesising the case data based on Social Cognitive Theory. The descriptive framework suggests that successful IS executive careers would most likely be achieved by well educated and experienced IS employees who have the right attitude towards both their career and work, together with good performance. They would also exhibit an ability for self-learning and to anticipate future IT uses, as well as having proficient IS management knowledge and skills while working with an appropriate organizational environment. Moreover, the framework systematically indicates the interactions between the coupling factors in the typical career development processes. This provides a benchmark for employees that are aiming at a senior IS executive career against which they can compare their own achievements and aspirations. It also raises propositions for further research on theory building.

Stock selection with full-scale optimization and differential evolution

When composing stock portfolios, managers frequently choose among hundreds of stocks. The stocks' risk properties are analyzed with statistical tools, and managers try to combine these to meet the investors' risk profiles. A recently developed tool for performing such optimization is called full-scale optimization (FSO). This methodology is very flexible for investor preferences, but because of computational limitations it has until now been infeasible to use when many stocks are considered. We apply the artificial intelligence technique of differential evolution to solve FSO-type stock selection problems of 97 assets. Differential evolution finds the optimal solutions by self-learning from randomly drawn candidate solutions. We show that this search technique makes large scale problem computationally feasible and that the solutions retrieved are stable. The study also gives further merit to the FSO technique, as it shows that the solutions suit investor risk profiles better than portfolios retrieved from traditional methods.

Data Mining for Browsing Patterns in Weblog Data by Art Neural Networks

Categorising visitors based on their interaction with a website is a key problem in Web content usage. The clickstreams generated by various users often follow distinct patterns, the knowledge of which may help in providing customised content. This paper proposes an approach to clustering weblog data, based on ART2 neural networks. Due to the characteristics of the ART2 neural network model, the proposed approach can be used for unsupervised and self-learning data mining, which makes it adaptable to dynamically changing websites.

Development, Annotation and Protection of Digital Archive “Bulgarian Folklore Heritage”

The key to prosperity in today's world is access to digital content and skills to create new content. Investigations of folklore artifacts is the topic of this article, presenting research related to the national program „Knowledge Technologies for Creation of Digital Presentation and Significant Repositories of Folklore Heritage” (FolkKnow). FolkKnow aims to build a digital multimedia archive "Bulgarian Folklore Heritage” (BFH) and virtual information portal with folk media library of digitized multimedia objects from a selected collection of the fund of Institute of Ethnology and Folklore Studies with Ethnographic Museum (IEFSEM) of the Bulgarian Academy of Science (BAS). The realization of the project FolkKnow gives opportunity for wide social applications of the multimedia collections, for the purposes of Interactive distance learning/self-learning, research activities in the field of Bulgarian traditional culture and for the cultural and ethno-tourism. We study, analyze and implement techniques and methods for digitization of multimedia objects and their annotation. In the paper are discussed specifics approaches used to building and protect a digital archive with multimedia content. Tasks can be systematized in the following guidelines: * Digitization of the selected samples * Analysis of the objects in order to determine the metadata of selected artifacts from selected collections and problem areas * Digital multimedia archive * Socially-oriented applications and virtual exhibitions artery * Frequency dictionary tool for texts with folklore themes * A method of modern technologies of protecting intellectual property and copyrights on digital content developed for use in digital exposures.

Structural Health Monitoring using Index Based Reasoning for Unmanned Aerial Vehicles

Unmanned Aerial Vehicles (UAVs) may develop cracks, erosion, delamination or other damages due to aging, fatigue or extreme loads. Identifying these damages is critical for the safe and reliable operation of the systems. ^ Structural Health Monitoring (SHM) is capable of determining the conditions of systems automatically and continually through processing and interpreting the data collected from a network of sensors embedded into the systems. With the desired awareness of the systems’ health conditions, SHM can greatly reduce operational cost and speed up maintenance processes. ^ The purpose of this study is to develop an effective, low-cost, flexible and fault tolerant structural health monitoring system. The proposed Index Based Reasoning (IBR) system started as a simple look-up-table based diagnostic system. Later, Fast Fourier Transformation analysis and neural network diagnosis with self-learning capabilities were added. The current version is capable of classifying different health conditions with the learned characteristic patterns, after training with the sensory data acquired from the operating system under different status. ^ The proposed IBR systems are hierarchy and distributed networks deployed into systems to monitor their health conditions. Each IBR node processes the sensory data to extract the features of the signal. Classifying tools are then used to evaluate the local conditions with health index (HI) values. The HI values will be carried to other IBR nodes in the next level of the structured network. The overall health condition of the system can be obtained by evaluating all the local health conditions. ^ The performance of IBR systems has been evaluated by both simulation and experimental studies. The IBR system has been proven successful on simulated cases of a turbojet engine, a high displacement actuator, and a quad rotor helicopter. For its application on experimental data of a four rotor helicopter, IBR also performed acceptably accurate. The proposed IBR system is a perfect fit for the low-cost UAVs to be the onboard structural health management system. It can also be a backup system for aircraft and advanced Space Utility Vehicles. ^

On the possible implementation of nondirective teaching for English class in post secondary public schools in China

The paper explores how Chinese English teachers assume appropriate roles in applying nondirective teaching model to classrooms. After reviewing the current situation of English teaching and learning in China, it introduces the nondirective teaching model and its characteristics. Then, it focuses on the implementation of nondirective teaching model at the public schools in China. Finally it discusses the essential role that nondirective teaching model plays in helping students become powerful learners on English learning.