Building a decision support system with a knowledge modeling tool

Knowledge modeling tools are software tools that follow a modeling approach to help developers in building a knowledge-based system. The purpose of this article is to show the advantages of using this type of tools in the development of complex knowledge-based decision support systems. In order to do so, the article describes the development of a system called SAIDA in the domain of hydrology with the help of the KSM modeling tool. SAIDA operates on real-time receiving data recorded by sensors (rainfall, water levels, flows, etc.). It follows a multi-agent architecture to interpret the data, predict the future behavior and recommend control actions. The system includes an advanced knowledge based architecture with multiple symbolic representation. KSM was especially useful to design and implement the complex knowledge based architecture in an efficient way.

Author and title list of the most important accessions to the War Department Library : with subject entries in biography, military history, and military science, and index of periodicals received during the calendar year, 1904.

"Office of the Chief of Staff, Second (Military Information) Division."

Incunabula, including many famous woodcut books. With an appendix of some recent acquisitions including three distinguished illustrated Italian incunabula and with subject index and index of printers and places of printing. Offered for sale by H.P. Kraus.

Mode of access: Internet.

Data visualisation and exploration with prior knowledge

Visualising data for exploratory analysis is a major challenge in many applications. Visualisation allows scientists to gain insight into the structure and distribution of the data, for example finding common patterns and relationships between samples as well as variables. Typically, visualisation methods like principal component analysis and multi-dimensional scaling are employed. These methods are favoured because of their simplicity, but they cannot cope with missing data and it is difficult to incorporate prior knowledge about properties of the variable space into the analysis; this is particularly important in the high-dimensional, sparse datasets typical in geochemistry. In this paper we show how to utilise a block-structured correlation matrix using a modification of a well known non-linear probabilistic visualisation model, the Generative Topographic Mapping (GTM), which can cope with missing data. The block structure supports direct modelling of strongly correlated variables. We show that including prior structural information it is possible to improve both the data visualisation and the model fit. These benefits are demonstrated on artificial data as well as a real geochemical dataset used for oil exploration, where the proposed modifications improved the missing data imputation results by 3 to 13%.

Engaging with a world outside of ourselves:vistas of flatness, children's work and the urban informal economy

This paper considers the work and labour of children living on the streets of Accra, Ghana. It does so in two distinctive ways. First, it considers how the children's photographs of a day or two in their working lives, and the dialogues that go on in, through and around them, may contribute to the making of strong sociological arguments about children's work. In so doing, this paper elaborates the connections between visual sociology and realist traditions of photography, and argues that photographs can contribute distinctive and novel sources of insight into working children's lives and a powerful, humanising media of dissemination. Second, these arguments are then deployed to examine street children's experiences of work. Conceptualised in terms of its 'flatness', the paper explores the informal means of regulation through which the children are locked into types of working that prove difficult to escape. © Sociological Research Online, 1996-2012.

Engaging with the public in public engagement with research

Though there is now growing commitment to publicly engaged research, the role and definition of the public in such processes is wide-ranging, contested, and often rather vague. This article addresses this problem by showing that, although there is no single agreed upon theory or way of being public, it is still possible and very important to develop clear, public-centric, understandings of engaged research practice. The article introduces a multi-dimensional framework based on the theoretical literature on the ‘public’, and demonstrates – in the context of a recent engaged research project – how it possible to conceptualise, design and evaluate context-specific formations of the public. Starting from an understanding of publics as mediated and dynamic entities, the article seeks to illuminate some of the choices that researchers face and how the framework can help them navigate these. This article is for all those interested in what it means to address, support and account for an engaged public in contemporary settings.

Mapping of Submerged Aquatic Vegetation in Rivers From Very High Resolution Image Data, Using Object Based Image Analysis Combined with Expert Knowledge

The use of remote sensing for monitoring of submerged aquatic vegetation (SAV) in fluvial environments has been limited by the spatial and spectral resolution of available image data. The absorption of light in water also complicates the use of common image analysis methods. This paper presents the results of a study that uses very high resolution (VHR) image data, collected with a Near Infrared sensitive DSLR camera, to map the distribution of SAV species for three sites along the Desselse Nete, a lowland river in Flanders, Belgium. Plant species, including Ranunculus aquatilis L., Callitriche obtusangula Le Gall, Potamogeton natans L., Sparganium emersum L. and Potamogeton crispus L., were classified from the data using Object-Based Image Analysis (OBIA) and expert knowledge. A classification rule set based on a combination of both spectral and structural image variation (e.g. texture and shape) was developed for images from two sites. A comparison of the classifications with manually delineated ground truth maps resulted for both sites in 61% overall accuracy. Application of the rule set to a third validation image, resulted in 53% overall accuracy. These consistent results show promise for species level mapping in such biodiverse environments, but also prompt a discussion on assessment of classification accuracy.

“And yet we are still excluded”: reclaiming multicultural queer histories and engaging with contemporary multicultural queer realities

In this chapter, we contend that reclaiming multiculturalism entails engaging with and including sexual and gender diverse histories, heritages and contemporary realities. We explore the ongoing dilemmas, concerns and strategies in placing “multisexuality” and “multigender” on the “multicultural” agenda in Australia, particularly in relation to policy development and research. We discuss how “reclaiming multiculturalism” and the promotion of “global citizenship” requires a reclaiming of multicultural queer histories and heritages, achieved through decolonising research projects, postcolonising socio-political activist networks, and publications that engage with multiplicity in identities and communities, or “multiple lifeworlds”.