Bringing results to fruition through publication: An analysis of a peer-reviewed, open access and context-focused journal's editorial practice

When it comes to helping to shape sustainable development, research is most useful when it bridges the science–implementation/management gap and when it brings development specialists and researchers into a dialogue (Hurni et al. 2004); can a peer-reviewed journal contribute to this aim? In the classical system for validation and dissemination of scientific knowledge, journals focus on knowledge exchange within the academic community and do not specifically address a ‘life-world audience’. Within a North-South context, another knowledge divide is added: the peer review process excludes a large proportion of scientists from the South from participating in the production of scientific knowledge (Karlsson et al. 2007). Mountain Research and Development (MRD) is a journal whose mission is based on an editorial strategy to build the bridge between research and development and ensure that authors from the global South have access to knowledge production, ultimately with a view to supporting sustainable development in mountains. In doing so, MRD faces a number of challenges that we would like to discuss with the td-net community, after having presented our experience and strategy as editors of this journal. MRD was launched in 1981 by mountain researchers who wanted mountains to be included in the 1992 Rio process. In the late 1990s, MRD realized that the journal needed to go beyond addressing only the scientific community. It therefore launched a new section addressing a broader audience in 2000, with the aim of disseminating insights into, and recommendations for, the implementation of sustainable development in mountains. In 2006, we conducted a survey among MRD’s authors, reviewers, and readers (Wymann et al. 2007): respondents confirmed that MRD had succeeded in bridging the gap between research and development. But we realized that MRD could become an even more efficient tool for sustainability if development knowledge were validated: in 2009, we began submitting ‘development’ papers (‘transformation knowledge’) to external peer review of a kind different from the scientific-only peer review (for ‘systems knowledge’). At the same time, the journal became open access in order to increase the permeability between science and society, and ensure greater access for readers and authors in the South. We are currently rethinking our review process for development papers, with a view to creating more space for communication between science and society, and enhancing the co-production of knowledge (Roux 2008). Hopefully, these efforts will also contribute to the urgent debate on the ‘publication culture’ needed in transdisciplinary research (Kueffer et al. 2007).

Evaluating the Impact of the Number of Access Points in Mobile Robots Localization Using Artificial Neural Networks

Localization is information of fundamental importance to carry out various tasks in the mobile robotic area. The exact degree of precision required in the localization depends on the nature of the task. The GPS provides global position estimation but is restricted to outdoor environments and has an inherent imprecision of a few meters. In indoor spaces, other sensors like lasers and cameras are commonly used for position estimation, but these require landmarks (or maps) in the environment and a fair amount of computation to process complex algorithms. These sensors also have a limited field of vision. Currently, Wireless Networks (WN) are widely available in indoor environments and can allow efficient global localization that requires relatively low computing resources. However, the inherent instability in the wireless signal prevents it from being used for very accurate position estimation. The growth in the number of Access Points (AP) increases the overlap signals areas and this could be a useful means of improving the precision of the localization. In this paper we evaluate the impact of the number of Access Points in mobile nodes localization using Artificial Neural Networks (ANN). We use three to eight APs as a source signal and show how the ANNs learn and generalize the data. Added to this, we evaluate the robustness of the ANNs and evaluate a heuristic to try to decrease the error in the localization. In order to validate our approach several ANNs topologies have been evaluated in experimental tests that were conducted with a mobile node in an indoor space.

An Architecture to offer Cloud-Based Radio Access Network as a Service

This paper addresses the novel notion of offering a radio access network as a service. Its components may be instantiated on general purpose platforms with pooled resources (both radio and hardware ones) dimensioned on-demand, elastically and following the pay-per-use principle. A novel architecture is proposed that supports this concept. The architecture's success is in its modularity, well-defined functional elements and clean separation between operational and control functions. By moving much processing traditionally located in hardware for computation in the cloud, it allows the optimisation of hardware utilization and reduction of deployment and operation costs. It enables operators to upgrade their network as well as quickly deploy and adapt resources to demand. Also, new players may easily enter the market, permitting a virtual network operator to provide connectivity to its users.