Entropy reduction via simplified image contourization

The process of contourization is presented which converts a raster image into a set of plateaux or contours. These contours can be grouped into a hierarchical structure, defining total spatial inclusion, called a contour tree. A contour coder has been developed which fully describes these contours in a compact and efficient manner and is the basis for an image compression method. Simplification of the contour tree has been undertaken by merging contour tree nodes thus lowering the contour tree's entropy. This can be exploited by the contour coder to increase the image compression ratio. By applying general and simple rules derived from physiological experiments on the human vision system, lossy image compression can be achieved which minimizes noticeable artifacts in the simplified image

More than a Match: The Role of Football in Britain’s Deaf Community

The University of Central Lancashire has undertaken a major research project into the role of football within the deaf community in Britain. As well as reconstructing the long history of deaf involvement in football for the first time, the project has also focused on the way in which football has provided deaf people with a means of developing and maintaining social contacts within the community, and of expressing the community’s cultural values. This article will draw on primary data gathered from interviews conducted with people involved in deaf football in a variety of capacities. During the course of these interviews, a number of themes and issues emerged relating to the values and benefits those involved with deaf football place on the game, and it is these which are explored here

Cost benefit analysis vs. referenda

We consider a planner who chooses between two possible public policies and ask whether a referendum or a cost benefit analysis leads to higher welfare. We find that a referendum leads to higher welfare than a cost benefit analyses in "common value" environments. Cost benefit analysis is better in "private value" environments.Cost benefit analysis, elections, referenda, project evaluation

Understanding the Value of Backbone Organizations in Collective Impact

Effective backbone support is a critical condition for collective impact. In fact, it is the number one reason that collective impact initiatives fail. In this publication, we provide communities and organizations engaged in collective impact with guidance on the role of the backbone and how to understand and support its effectiveness.In the Greater Cincinnati region, collective impact has become the "new normal," and The Greater Cincinnati Foundation (GCF) has made a commitment to support the infrastructure of collective impact - the backbone organization itself - in an effort to sustain and scale long-term systemic change and impact in the community. However, the role of the backbone organization in collective impact is complex and can be difficult to explain.In early 2012, The Greater Cincinnati Foundation and FSG began a partnership to define the value of backbone organizations and better understand back-bone effectiveness by working with six local backbone organizations and collective impact initiatives

The effects of public funding on farmers' attitudes to farm diversification

The overall aim of this research is to provide the UK Government with an evidence base from which it may be established whether there is a rationale for continuing Government intervention to encourage farm diversification, in particular through making capital grant funding available to farm diversification projects. The project's findings will inform the future role of government support, including whether other forms of support (advice, guidance and training) may be appropriate.Agricultural and Food Policy, Agricultural Finance, Farm Management,

Maori in governance: The voices of Maori trustees

While the education reforms of 1989 promised much for Maori in education, Maori membership on Boards of Trustees continues to be disproportionately low against that of non-Maori members. The governance role is significant in influencing the provision and outcomes of education for Maori students, but there has been little research into the experiences of Maori in school governance, or the factors that impact on successful partnerships between Maori and Pakeha on school boards. This research project presents the governance stories of six Maori trustees from different mainstream primary schools. With reference to the Treaty of Waitangi, it explores Maori and Pakeha conceptions of partnership, and discusses the effectiveness of the education reforms in promoting and sustaining partnership with Maori at school governance level. Through interviews conducted as part of this research, Maori trustees' understandings of their role in governance, the board's obligations to the Treaty of Waitangi, and the expectations placed on them as Maori by the board, and by their own Maori community, are explored. This project highlights some of the complex issues Maori trustees face within a governance structure which is incongruous with traditional Maori principles of collectivism, and illuminates the duality of role many Maori negotiate as school trustees

Hyperspectral colon tissue cell classification

A novel algorithm to discriminate between normal and malignant tissue cells of the human colon is presented. The microscopic level images of human colon tissue cells were acquired using hyperspectral imaging technology at contiguous wavelength intervals of visible light. While hyperspectral imagery data provides a wealth of information, its large size normally means high computational processing complexity. Several methods exist to avoid the so-called curse of dimensionality and hence reduce the computational complexity. In this study, we experimented with Principal Component Analysis (PCA) and two modifications of Independent Component Analysis (ICA). In the first stage of the algorithm, the extracted components are used to separate four constituent parts of the colon tissue: nuclei, cytoplasm, lamina propria, and lumen. The segmentation is performed in an unsupervised fashion using the nearest centroid clustering algorithm. The segmented image is further used, in the second stage of the classification algorithm, to exploit the spatial relationship between the labeled constituent parts. Experimental results using supervised Support Vector Machines (SVM) classification based on multiscale morphological features reveal the discrimination between normal and malignant tissue cells with a reasonable degree of accuracy