Temporal and Spatial Data Mining with Second-Order Hidden Models

In the frame of designing a knowledge discovery system, we have developed stochastic models based on high-order hidden Markov models. These models are capable to map sequences of data into a Markov chain in which the transitions between the states depend on the \texttt{n} previous states according to the order of the model. We study the process of achieving information extraction fromspatial and temporal data by means of an unsupervised classification. We use therefore a French national database related to the land use of a region, named Teruti, which describes the land use both in the spatial and temporal domain. Land-use categories (wheat, corn, forest, ...) are logged every year on each site regularly spaced in the region. They constitute a temporal sequence of images in which we look for spatial and temporal dependencies. The temporal segmentation of the data is done by means of a second-order Hidden Markov Model (\hmmd) that appears to have very good capabilities to locate stationary segments, as shown in our previous work in speech recognition. Thespatial classification is performed by defining a fractal scanning ofthe images with the help of a Hilbert-Peano curve that introduces atotal order on the sites, preserving the relation ofneighborhood between the sites. We show that the \hmmd performs aclassification that is meaningful for the agronomists.Spatial and temporal classification may be achieved simultaneously by means of a 2 levels \hmmd that measures the \aposteriori probability to map a temporal sequence of images onto a set of hidden classes

Mining Complex Hydrobiological Data with Galois Lattices

We have used Galois lattices for mining hydrobiological data. These data are about macrophytes, that are macroscopic plants living in water bodies. These plants are characterized by several biological traits, that own several modalities. Our aim is to cluster the plants according to their common traits and modalities and to find out the relations between traits. Galois lattices are efficient methods for such an aim, but apply on binary data. In this article, we detail a few approaches we used to transform complex hydrobiological data into binary data and compare the first results obtained thanks to Galois lattices

Load up the Woody: portable classroom leads to partnership

PosterThe Spencer S. Eccles Health Sciences Library and the University of Utah School of Medicine realize an oportunity to partner technology and teaching utilizing the library's portable wireless classroom

Case Adaptation with Qualitative Algebras

This paper proposes an approach for the adaptation of spatial or temporal cases in a case-based reasoning system. Qualitative algebras are used as spatial and temporal knowledge representation languages. The intuition behind this adaptation approach is to apply a substitution and then repair potential inconsistencies, thanks to belief revision on qualitative algebras. A temporal example from the cooking domain is given. (The paper on which this extended abstract is based was the recipient of the best paper award of the 2012 International Conference on Case-Based Reasoning.

Cross-Sector Models of Collaboration for Social Innovation

This dissertation consists of three studies that collectively examine the genesis and dynamics of collaborative cross-sector partnerships between nonprofit and for-profit organizations. The overarching question that frames the papers is how cross-sector partnerships organize across sectoral interfaces to advance social innovation. This thesis makes three contributions: 1) the standpoint of the beneficiaries needs to be explicitly discussed when exploring social innovation in cross-sector partnerships; 2) neither success nor failure are absolute but rather cross-sector partners deliberately and iteratively adjust their roles to sustain momentum towards success or rebound from temporary failure in pursuit of social innovation; and 3) despite largely non-overlapping sectoral frames, social innovation is possible when partners learn how to negotiate and fuse their value frames. In the first paper, we develop a critical theory of social innovation in cross-sector partnerships by recasting value creation from the standpoint of the beneficiary. We review and contrast the principles, relations and relational processes underpinning the Marxist, pragmatist and Frankfurt schools of thought to unpack the role the beneficiary may (or may not play) in value creation. Such critical theorizing enriches the conceptual foundation of the Resource Based View by reinstating the beneficiary as an essential contributor to value creation through voice-receiving, voice-making and/or voice-taking. This paper concludes that beneficiaries are essential to social innovation in cross-sector partnerships: they create and sustain generative tensions within each value creation cycle. In the second study, we explore the relational processes that underpin social innovation within cross-sector partnerships. Using four longitudinal narratives in healthcare, we explain how partners navigate the duality of success and failure: deliberate role (re)calibrations help the partners sustain the momentum for success and overcome temporary failure or crossover from failure to success. Three factors moderate the relationship between role recalibrations and the momentum for success or failure: relational attachment, partner complacency, and partner disillusionment. The third and last study uses the same four longitudinal narratives to explore how cross-sector partners come to recognize and reconcile their divergent value creation frames in order to co-construct social innovation. We argue and find that partners initially contrast their sector-embedded diagnostic frames and then work together to deliberately develop partnership-specific prognostic frames. The study develops a four-stage grounded model of frame negotiation, elasticity, plasticity and fusion which unpacks the relational process of value creation in cross sector partnerships. Taken together, the three studies advance the cross-sector partnership project by fleshing out the (largely neglected) role of relational processes in social innovation

Teaching teachers to teach with tablet PCs

PosterLibrary faculty met weekly to learn and teach one another how to use TabletPCs and how to train faculty in their use in the new health sciences education building. The new health sciences education building at the University of Utah provides a modern, state of the art, student focused, teaching and learning center that integrates the most recent advances in information technology to improve teaching and information dissemination. Health sciences faculty early adopters each received a Tablet PC for teaching in their classes and met monthly for sharing and instruction sessions. Feedback from the pilot was used to develop a one-hour faculty-focused Tablet PC course ensuring health sciences faculty familiarity with technology in the new building