Parsimonious Catchment and River Flow Modelling

It is increasingly the case that models are being developed as “evolving” products rather than\ud one-off application tools, such that auditable modelling versus ad hoc treatment of models becomes a\ud pivotal issue. Auditable modelling is particularly vital to “parsimonious modelling” aimed at meeting\ud specific modelling requirements. This paper outlines various contributory factors and aims to seed\ud proactively a research topic by inextricably linking value/risk management to parsimonious modelling.\ud Value management in modelling may be implemented in terms of incorporating “enough detail” into a\ud model so that the synergy among the constituent units of the model captures that of the real system. It is a\ud problem of diminishing returns, since further reductions in the constituent units will create an\ud unacceptable difference between the model and the real system; conversely, any further detail will add to\ud the cost of modelling without returning any significant benefit. The paper also defines risk management\ud in relation to modelling. It presents a qualitative framework for value/risk management towards\ud parsimonious modelling by the categorisation of “modelling techniques” in terms of “control volume.

Using ontology engineering for understanding needs and allocating resources in web-based industrial virtual collaboration systems

In many interactions in cross-industrial and inter-industrial collaboration, analysis and understanding of relative specialist and non-specialist language is one of the most pressing challenges when trying to build multi-party, multi-disciplinary collaboration system. Hence, identifying the scope of the language used and then understanding the relationships between the language entities are key problems. In computer science, ontologies are used to provide a common vocabulary for a domain of interest together with descriptions of the meaning of terms and relationships between them, like in an encyclopedia. These, however, often lack the fuzziness required for human orientated systems. This paper uses an engineering sector business collaboration system (www.wmccm.co.uk) as a case study to illustrate the issues. The purpose of this paper is to introduce a novel ontology engineering methodology, which generates structurally enriched cross domain ontologies economically, quickly and reliably. A semantic relationship analysis of the Google Search Engine Index was devised and evaluated. Using Semantic analysis seems to generate a viable list of subject terms. A social network analysis of the semantically derived terms was conducted to generate a decision support network with rich relationships between terms. The derived ontology was quicker to generate, provided richer internal relationships and relied far less on expert contribution. More importantly, it improved the collaboration matching capability of WMCCM

Building the interface between experts and linguists in the detection and characterisation of neology in the field of the neurosciences

[EN]The paper focuses on the building of a collaborative tool between experts and linguists in the detection, categorisation and creation of neology in Spanish in the field of neurosciences. The pro- / inter- active relationship between new knowledge and its cross-linguistic realisation, and the possibility of enhancing it by digital means, is the main goal of our research. Several tools and work methodologies that will be useful in the inception and development of experiments with experts in the field of the neurosciences are described, such as the upper classes of NIFSTD and wikis as a collaborative tool to carry out our prototype experimen

Participatory process management

Although the process of public and stakeholder participation continues to be intensively investigated and discussed in academic circles, the implementation of participatory methods in practice remains problematic. This can be attributed to the lack of knowledge transfer on the one hand, and the general underestimation of participatory approaches in planning processes on the other.\ud A possible solution - participatory processmanagement - is introduced in this article. Participatory process management means that all participatory activities are embedded in the overall planning activities of a project. The most significant criteria for a participatory process are identified as ’objectives’, ’constraints’ and ’process’which together forma framework for combining generally applicablemethodswith local constraints and the objectives of a project. Themain elements of the participatory management framework introduced here are levels and classes of participation and a generic process scheme includingmonitoring and evaluation of participatory processes. This work is based upon long-term experiences of consultants and scientists. However, the insights from the InterReg project TRUST are particularly valuable and confirm the hypotheses that different water management projects are comparable in terms of their participatory process performance. The participatory management framework is a step forward in closing the gap between scientific knowledge about participatory methods and their applicability in practice

Context Aware Computing for The Internet of Things: A Survey

As we are moving towards the Internet of Things (IoT), the number of sensors deployed around the world is growing at a rapid pace. Market research has shown a significant growth of sensor deployments over the past decade and has predicted a significant increment of the growth rate in the future. These sensors continuously generate enormous amounts of data. However, in order to add value to raw sensor data we need to understand it. Collection, modelling, reasoning, and distribution of context in relation to sensor data plays critical role in this challenge. Context-aware computing has proven to be successful in understanding sensor data. In this paper, we survey context awareness from an IoT perspective. We present the necessary background by introducing the IoT paradigm and context-aware fundamentals at the beginning. Then we provide an in-depth analysis of context life cycle. We evaluate a subset of projects (50) which represent the majority of research and commercial solutions proposed in the field of context-aware computing conducted over the last decade (2001-2011) based on our own taxonomy. Finally, based on our evaluation, we highlight the lessons to be learnt from the past and some possible directions for future research. The survey addresses a broad range of techniques, methods, models, functionalities, systems, applications, and middleware solutions related to context awareness and IoT. Our goal is not only to analyse, compare and consolidate past research work but also to appreciate their findings and discuss their applicability towards the IoT.Comment: IEEE Communications Surveys & Tutorials Journal, 201