Overcoming Bandwidth Limitations in Wireless Sensor Networks by Exploitation of Cyclic Signal Patterns: An Event-triggered Learning Approach

Wireless sensor networks are used in a wide range of applications, many of which require real-time transmission of the measurements. Bandwidth limitations result in limitations on the sampling frequency and number of sensors. This problem can be addressed by reducing the communication load via data compression and event-based communication approaches. The present paper focuses on the class of applications in which the signals exhibit unknown and potentially time-varying cyclic patterns. We review recently proposed event-triggered learning (ETL) methods that identify and exploit these cyclic patterns, we show how these methods can be applied to the nonlinear multivariable dynamics of three-dimensional orientation data, and we propose a novel approach that uses Gaussian process models. In contrast to other approaches, all three ETL methods work in real time and assure a small upper bound on the reconstruction error. The proposed methods are compared to several conventional approaches in experimental data from human subjects walking with a wearable inertial sensor network. They are found to reduce the communication load by 60–70%, which implies that two to three times more sensor nodes could be used at the same bandwidth

Using Ontologies for the Design of Data Warehouses

Obtaining an implementation of a data warehouse is a complex task that forces designers to acquire wide knowledge of the domain, thus requiring a high level of expertise and becoming it a prone-to-fail task. Based on our experience, we have detected a set of situations we have faced up with in real-world projects in which we believe that the use of ontologies will improve several aspects of the design of data warehouses. The aim of this article is to describe several shortcomings of current data warehouse design approaches and discuss the benefit of using ontologies to overcome them. This work is a starting point for discussing the convenience of using ontologies in data warehouse design.Comment: 15 pages, 2 figure

A unified view of data-intensive flows in business intelligence systems : a survey

Data-intensive flows are central processes in today’s business intelligence (BI) systems, deploying different technologies to deliver data, from a multitude of data sources, in user-preferred and analysis-ready formats. To meet complex requirements of next generation BI systems, we often need an effective combination of the traditionally batched extract-transform-load (ETL) processes that populate a data warehouse (DW) from integrated data sources, and more real-time and operational data flows that integrate source data at runtime. Both academia and industry thus must have a clear understanding of the foundations of data-intensive flows and the challenges of moving towards next generation BI environments. In this paper we present a survey of today’s research on data-intensive flows and the related fundamental fields of database theory. The study is based on a proposed set of dimensions describing the important challenges of data-intensive flows in the next generation BI setting. As a result of this survey, we envision an architecture of a system for managing the lifecycle of data-intensive flows. The results further provide a comprehensive understanding of data-intensive flows, recognizing challenges that still are to be addressed, and how the current solutions can be applied for addressing these challenges.Peer ReviewedPostprint (author's final draft

Learning landscapes for universities: mapping the field [or] Beyond a seat in the lecture hall: a prolegemenon of learning landscapes in universities

This is the first in a series of project working papers. Its aim is to commence the development of a shared vocabulary so that visioning learning landscapes can be realised in the appropriate development of academic estate. The paper explores first, how the terminology of learning landscapes has been employed elsewhere. Secondly, its connections with university conceptualisations past and present are explored as this project aims to retain the strengths of traditional academic environments together with new designs. The impetus to its emergence is next reviewed , its constituent elements and any evidence of estates-related literature. Finally a definition is essayed. Includes an abbreviated version (p.11-14)

Photovoltaic research and development in Japan

The status of the Japanese photovoltaic (PV) R&D activities was surveyed through literature searches, private communications, and site visits in 1982. The results show that the Japanese photovoltaic technology is maturing rapidly, consistent with the steady government funding under the Sunshine Project. Two main thrusts of the Project are: (1) completion of the solar panel production pilot plants using cast ingot and sheet silicon materials, and (2) development of large area amorphous silicon solar cells with acceptable efficiency (10 to 12%). An experimental automated solar panel production plant rated at 500 kW/yr is currently under construction for the Sunshine Project for completion in March 1983. Efficiencies demonstrated by experimental large are amorphous silicon solar cells are approaching 8%. Small area amorphous silicon solar cells are, however, currently being mass produced and marketed by several companies at an equivalent annual rate of 2 MW/yr for consumer electronic applications. There is no evidence of an immediate move by the Japanese PV industry to enter extensively into the photovoltaic power market, domestic or otherwise. However, the photovoltaic technology itself could become ready for such an entry in the very near future, especially by making use of advanced process automation technologies

Enhancing Small Group Teaching in Plant Sciences: A Research and Development Project in Higher Education

The Department of Plant Sciences at the University of Cambridge uses a range of learning and teaching environments including lectures, practical laboratories and small group tutorials'. Under the auspices of the Cambridge-MIT Institute's Pedagogy Programme, a two-year research and development project concerned with the development of small-group teaching is being undertaken. The research element of this project endeavours to illuminate current practice and identify areas in which evidence-based development might take place. The development element will include professional development activities and the production of curriculum resources including appropriate online material. This is a multi-method study including a series of student questionnaires; focus groups of students; semi-structured interviews with staff members; and the collection of video of small group teaching. In this paper we report selected findings from the 'student data' of the first year of this project.The questionnaire, conducted with two cohorts of students (2nd and 3rd year Undergraduates), used a double-scale questionnaire in which students were asked to report both on the prevalence of a range of teaching and learning practices and on how valuable these were in supporting their learning. This type of questionnaire instrument is particularly appropriate because the data it generates is suggestive of areas for changes in practice. The gaps between 'practices' and 'values' (across both cohorts) suggested that students valued activities which improved their understanding of how elements of the course were interrelated; which related course content to 'authentic' examples; and those in which teachers made explicit the characteristics of 'high quality' student work. Small group teaching, in the view of most students, was best used to extend and explore concepts introduced in lectures rather than simply reinforcing them or assessing student understanding.Data gathered through focus group activities illuminated the questionnaire data, providing detailed accounts of how students managed their own learning, and the roles played in this by lectures, small group teaching and other resources. Students identified the processes of planning and writing essays as key learning activities during which they integrated diverse course content and reflected on problematic knowledge. Questionnaire and focus group data suggested that students had less clear views regarding the value of collaborative learning, peer-assessment or activities such as making presentations to other students. When students talked in positive terms about these activities, they often referred to the learning benefits of preparation for the tasks rather than of the collaborative activities themselves. These views may provide indications of potential barriers to changes in learning and teaching environments, and suggest that any such changes may have to be carefully justified to students in terms of benefits to their own learning. Many of our findings are broadly in accord with other work on teaching and learning in Higher Education settings (such as the 'Oxford Learning Context Project' and the 'Enhancing Teaching-Learning Environments in Undergraduate Courses' Project) in that 'deep learning' and 'authenticity' in learning activities are valued by students, and that the introduction of specific formative practices (such as sharing notions of 'quality') would be welcomed. At the same time, amongst the students in our sample, a view of learning as an individual process of 'learning-as-acquisition' predominates over a view that it is a social process of 'learning-as-participation', and this will inform the planning of the 'development' aspect of the project. We conclude with a discussion of how the approach we have used might be more widely applied both within and beyond the Cambridge-MIT partnership. We also identify potential affordances of, and barriers to, the development of research-informed teaching in Higher Education

Engineering model transformations with transML

The final publication is available at Springer via http://dx.doi.org/10.1007%2Fs10270-011-0211-2Model transformation is one of the pillars of model-driven engineering (MDE). The increasing complexity of systems and modelling languages has dramatically raised the complexity and size of model transformations as well. Even though many transformation languages and tools have been proposed in the last few years, most of them are directed to the implementation phase of transformation development. In this way, even though transformations should be built using sound engineering principles—just like any other kind of software—there is currently a lack of cohesive support for the other phases of the transformation development, like requirements, analysis, design and testing. In this paper, we propose a unified family of languages to cover the life cycle of transformation development enabling the engineering of transformations. Moreover, following an MDE approach, we provide tools to partially automate the progressive refinement of models between the different phases and the generation of code for several transformation implementation languages.This work has been sponsored by the Spanish Ministry of Science and Innovation with project METEORIC (TIN2008-02081), and by the R&D program of the Community of Madrid with projects “e-Madrid" (S2009/TIC-1650). Parts of this work were done during the research stays of Esther and Juan at the University of York, with financial support from the Spanish Ministry of Science and Innovation (grant refs. JC2009-00015, PR2009-0019 and PR2008-0185)