Testing Delivery Systems in Transnational virtual learning: the vocational management training for the european tourism industry (VocMat) case study

This article discusses the lessons learned from developing and delivering the Vocational Management Training for the European Tourism Industry (VocMat) online training programme, which was aimed at providing flexible, online distance learning for the European tourism industry. The programme was designed to address managers ‘need for flexible, senior management level training which they could access at a time and place which fitted in with their working and non-work commitments. The authors present two main approaches to using the Virtual Learning Environment, the feedback from the participants, and the implications of online Technology in extending tourism training opportunities

WePreserve 2009: DPE/Planets/CASPAR/nestor Joint Training Event: The Preservation challenge: basic concepts and practical applications (Barcelona, 23-27 març 2009)

Reseña del congreso WePreserve 2009 que tuvo lugar los pasados 23 al 27 de marzo en Barcelona, organizadopor la Facultad de Biblioteconomía y Documentación de la Universitat de Barcelona, con la colaboración del Institut d'Estudis Catalans, la Biblioteca de Catalunya y el Consorci de Biblioteques de Barcelona. El seminario 2009 WePreserve se celebra anualmente desde el año 2007 y participan todas las figuras de referencia europeas en materia de investigación en sistemas y metodologías que garantizan la preservación digital de los documentos: Digital Preservation Europe (DPE), Preservation and Long-term Access Through Networked Services (Planets), Cultural Artistic and Scientific Knowledge for Preservation, Access and Retrieval (CASPAR), y Network of expertise in Digital long-term preservation (nestor).

Dialogic learning and interactive groups: an IMS LD template integrated in runtime systems

Dialogic learning and interactive groups have proved to be a useful methodological approach appliedin educational situations for lifelong adult learners. The principles of this approach stress theimportance of dialogue and equal participation also when designing the training activities. This paperadopts these principles as the basis for a configurable template that can be integrated in runtimesystems. The template is formulated as a meta-UoL which can be interpreted by IMS Learning Designplayers. This template serves as a guide to flexibly select and edit the activities at runtime (on the fly).The meta-UoL has been used successfully by a practitioner so as to create a real-life example, withpositive and encouraging results

Neural networks complemented with genetic algorithms and fuzzy systems for predicting nitrogenous effluent variables in wastewater treatment plants

This work focuses on the prediction of the two main nitrogenous variables that describe the water quality at the effluent of a Wastewater Treatment Plant. We have developed two kind of Neural Networks architectures based on considering only one output or, in the other hand, the usual five effluent variables that define the water quality: suspended solids, biochemical organic matter, chemical organic matter, total nitrogen and total Kjedhal nitrogen. Two learning techniques based on a classical adaptative gradient and a Kalman filter have been implemented. In order to try to improve generalization and performance we have selected variables by means genetic algorithms and fuzzy systems. The training, testing and validation sets show that the final networks are able to learn enough well the simulated available data specially for the total nitrogen

Spatial filtering for pilot-aided WCDMA systems: a semi-blind subspace approach

This paper proposes a spatial filtering technique forthe reception of pilot-aided multirate multicode direct-sequencecode division multiple access (DS/CDMA) systems such as widebandCDMA (WCDMA). These systems introduce a code-multiplexedpilot sequence that can be used for the estimation of thefilter weights, but the presence of the traffic signal (transmittedat the same time as the pilot sequence) corrupts that estimationand degrades the performance of the filter significantly. This iscaused by the fact that although the traffic and pilot signals areusually designed to be orthogonal, the frequency selectivity of thechannel degrades this orthogonality at hte receiving end. Here,we propose a semi-blind technique that eliminates the self-noisecaused by the code-multiplexing of the pilot. We derive analyticallythe asymptotic performance of both the training-only andthe semi-blind techniques and compare them with the actual simulatedperformance. It is shown, both analytically and via simulation,that high gains can be achieved with respect to training-onlybasedtechniques.

ML approaches to channel estimation for pilot-aided multi-rate DS/CDMA systems

This paper analyzes the asymptotic performance of maximum likelihood (ML) channel estimation algorithms in wideband code division multiple access (WCDMA) scenarios. We concentrate on systems with periodic spreading sequences (period larger than or equal to the symbol span) where the transmitted signal contains a code division multiplexed pilot for channel estimation purposes. First, the asymptotic covariances of the training-only, semi-blind conditional maximum likelihood (CML) and semi-blind Gaussian maximum likelihood (GML) channelestimators are derived. Then, these formulas are further simplified assuming randomized spreading and training sequences under the approximation of high spreading factors and high number of codes. The results provide a useful tool to describe the performance of the channel estimators as a function of basicsystem parameters such as number of codes, spreading factors, or traffic to training power ratio.

A systems biology approach identifies molecular networks defining skeletal muscle abnormalities in chronic obstructive pulmonary disease.

Chronic Obstructive Pulmonary Disease (COPD) is an inflammatory process of the lung inducing persistent airflow limitation. Extensive systemic effects, such as skeletal muscle dysfunction, often characterize these patients and severely limit life expectancy. Despite considerable research efforts, the molecular basis of muscle degeneration in COPD is still a matter of intense debate. In this study, we have applied a network biology approach to model the relationship between muscle molecular and physiological response to training and systemic inflammatory mediators. Our model shows that failure to co- ordinately activate expression of several tissue remodelling and bioenergetics pathways is a specific landmark of COPD diseased muscles. Our findings also suggest that this phenomenon may be linked to an abnormal expression of a number of histone modifiers, which we discovered correlate with oxygen utilization. These observations raised the interesting possibility that cell hypoxia may be a key factor driving skeletal muscle degeneration in COPD patients.

The process of basic training, applied training, maintaining the performance of an observer

In the field of observational methodology the observer is obviously a central figure, and close attention should be paid to the process through which he or she acquires, applies, and maintains the skills required. Basic training in how to apply the operational definitions of categories and the rules for coding, coupled with the opportunity to use the observation instrument in real-life situations, can have a positive effect in terms of the degree of agreement achieved when one evaluates intra- and inter-observer reliability. Several authors, including Arias, Argudo, & Alonso (2009) and Medina and Delgado (1999), have put forward proposals for the process of basic and applied training in this context. Reid y De Master (1982) focuses on the observer's performance and how to maintain the acquired skills, it being argued that periodic checks are needed after initial training because an observer may, over time, become less reliable due to the inherent complexity of category systems. The purpose of this subsequent training is to maintain acceptable levels of observer reliability. Various strategies can be used to this end, including providing feedback about those categories associated with a good reliability index, or offering re-training in how to apply those that yield lower indices. The aim of this study is to develop a performance-based index that is capable of assessing an observer's ability to produce reliable observations in conjunction with other observers.