An Information-Centric Communication Infrastructure for Real-Time State Estimation of Active Distribution Networks

© 2010-2012 IEEE.The evolution toward emerging active distribution networks (ADNs) can be realized via a real-time state estimation (RTSE) application facilitated by the use of phasor measurement units (PMUs). A critical challenge in deploying PMU-based RTSE applications at large scale is the lack of a scalable and flexible communication infrastructure for the timely (i.e., sub-second) delivery of the high volume of synchronized and continuous synchrophasor measurements. We address this challenge by introducing a communication platform called C-DAX based on the information-centric networking (ICN) concept. With a topic-based publish-subscribe engine that decouples data producers and consumers in time and space, C-DAX enables efficient synchrophasor measurement delivery, as well as flexible and scalable (re)configuration of PMU data communication for seamless full observability of power conditions in complex and dynamic scenarios. Based on the derived set of requirements for supporting PMU-based RTSE in ADNs, we design the ICN-based C-DAX communication platform, together with a joint optimized physical network resource provisioning strategy, in order to enable the agile PMU data communications in near real-time. In this paper, C-DAX is validated via a field trial implementation deployed over a sample feeder in a real-distribution network; it is also evaluated through simulation-based experiments using a large set of real medium voltage grid topologies currently operating live in The Netherlands. This is the first work that applies emerging communication paradigms, such as ICN, to smart grids while maintaining the required hard real-time data delivery as demonstrated through field trials at national scale. As such, it aims to become a blueprint for the application of ICN-based general purpose communication platforms to ADNs

Constructing a national higher education brand for the UK: positional competition and promised capitals

This article examines national branding of UK higher education, a strategic intent and action to collectively brand UK higher education with the aim to attract prospective international students, using a Bourdieusian approach to understanding promises of capitals. We trace its development between 1999 and 2014 through a sociological study, one of the first of its kind, from the 'Education UK' and subsumed under the broader 'Britain is GREAT' campaign of the Coalition Government. The findings reveal how a national higher education brand is construed by connecting particular representations of the nation with those of prospective international students and the higher education sector, which combine in the brand with promises of capitals to convert into positional advantage in a competitive environment. The conceptual framework proposed here seeks to connect national higher education branding to the concept of the competitive state, branded as a nation and committed to the knowledge economy

Mining and Using Sets of Patterns through Compression

In this chapter we describe how to successfully apply the MDL principle to pattern mining. In particular, we discuss how pattern-based models can be designed and induced by means of compression, resulting in succinct and characteristic descriptions of the data. As motivation, we argue that traditional pattern mining asks the wrong question: instead of asking for all patterns satisfying some in-terestingness measure, one should ask for a small, non-redundant, and interesting set of patterns—which allows us to avoid the pattern explosion. Firmly rooted in algorithmic information theory, the approach we discuss in this chapter states that the best set of patterns is that set that compresses the data best. We formalize this problem using the Minimum Description Length (MDL) principle, describe useful model classes, and briefly discuss algorithmic approaches to inducing good models from data. Last but not least, we describe how the obtained models—in addition to showing the key patterns of the data—can be used for a wide range of data mining tasks; hence showing that MDL selects useful patterns

TNF promoter SNP variation in Amerindians and white-admixed women from Misiones, Argentina

The aim of this study is to describe genetic variation in the TNF promoter in the ethnically diverse population of Misiones, north-eastern Argentina. We analysed 210 women including 66 Amerindians of the Mbya-Guarani ethnic group and 144 white-admixed individuals from urban and rural areas of Misiones. Their DNA samples were surveyed for TNF polymorphisms -376 A/G, -308 A/G -244 A/G and -238 A/G by PCR amplification and direct sequencing and for the Amerindian marker -857 C/T by real-time PCR. Our main findings are as follows:(i) a distinctive pattern of Single Nucleotide Polymorphism (SNP) distribution among these groups, (ii) genetic differentiation between the Mbya-Guarani and the white-admixed populations (P < 0.05), (iii) lower gene diversity (~0.05) in Mbya-Guarani compared with the whiteadmixed group (~0.21); and (iv) linkage disequilibrium between the -376A and -238A SNPs in white-admixed populations. These data highlight the principal role of population history in establishing present-day genetic variation at the TNF locus and provide a framework for undertaking ethnographic and disease association studies in Misiones.Fil: Badano, Ines. Universidad Nacional de Misiones. Facultad de Ciencias Exactas, Químicas y Naturales. Laboratorio de Biología Molecular Aplicada; Argentina; Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Houssay; Argentina;Fil: Schurr, T. G.. University of Pennsylvania; Estados Unidos de América;Fil: Stietz, S. M.. Universidad Nacional de Misiones. Facultad de Ciencias Exactas, Químicas y Naturales. Laboratorio de Biología Molecular Aplicada; Argentina;Fil: Dulik, M. C.. University of Pennsylvania; Estados Unidos de América;Fil: Mampaey, M.. Provincia de Misiones. Ministerio de Salud Pública; Argentina;Fil: Quintero, I. M.. Universidad Nacional de Misiones. Facultad de Ciencias Exactas, Químicas y Naturales. Laboratorio de Biología Molecular Aplicada; Argentina;Fil: Zinovich, J. B.. Provincia de Misiones. Ministerio de Salud Pública; Argentina;Fil: Campos, Rodolfo Hector. Universidad de Buenos Aires. Facultad de Farmacia y Bioquímica. Departamento de Microbiología, Inmunología y Biotecnología. Cátedra de Virología; Argentina; Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Houssay; Argentina;Fil: Liotta, Domingo Javier. Universidad Nacional de Misiones. Facultad de Ciencias Exactas, Químicas y Naturales. Laboratorio de Biología Molecular Aplicada; Argentina; Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Houssay; Argentina

Segmentation of coronal features to understand the solar EUV and UV irradiance variability

International audienceContext. The study of solar irradiance variability is of great importance in heliophysics, the Earth’s climate, and space weather applications. These studies require careful identifying, tracking and monitoring of active regions (ARs), coronal holes (CHs), and the quiet Sun (QS).Aims. We studied the variability of solar irradiance for a period of two years (January 2011–December 2012) using the Large Yield Radiometer (LYRA), the Sun Watcher using APS and image Processing (SWAP) on board PROBA2, and the Atmospheric Imaging Assembly (AIA) on board the Solar Dynamics Observatory (SDO).Methods. We used the spatial possibilistic clustering algorithm (SPoCA) to identify and segment coronal features from the EUV observations of AIA. The AIA segmentation maps were then applied on SWAP images, and parameters such as the intensity, fractional area, and contribution of ARs/CHs/QS features were computed and compared with the full-disk integrated intensity and LYRA irradiance measurements.Results. We report the results obtained from SDO/AIA and PROBA2/SWAP images taken from January 2011 to December 2012 and compare the resulting integrated full-disk intensity with PROBA2/LYRA irradiance. We determine the contributions of the segmented features to EUV and UV irradiance variations. The variations of the parameters resulting from the segmentation, namely the area, integrated intensity, and relative contribution to the solar irradiance, are compared with LYRA irradiance. We find that the active regions have a great impact on the irradiance fluctuations. In the EUV passbands considered in this study, the QS is the greatest contributor to the solar irradiance, with up to 63% of total intensity values. Active regions, on the other hand, contribute to about 10%, and off-limb structures to about 24%. We also find that the area of the features is highly variable suggesting that their area has to be taken into account in irradiance models, in addition to their intensity variations.Conclusions. We successfully show that the feature extraction allows us to use EUV telescopes to measure irradiance fluctuations and to quantify the contribution of each part to the EUV spectral solar irradiance observed with a calibrated radiometer. This study also shows that SPoCA is viable, and that the segmentation of images can be a useful tool. We also provide the measurement correlation between SWAP and AIA during this analysis