Using History to Study Information Seeking Behavior

has focused on approaches that provide a snapshot in time of what is going on in a household. This poster explores the use of history to examine changes over time in both information questions and information sources used in the prosecution of everyday life activities in America. The study is based on identifying endogenous and exogenous forces to the activity at hand, and seeing how these forces cause change. A secondary question raised in this poster is the largely unexamined belief that the Internet has played an exceptional role in changing the nature of everyday information seeking behavior in America. The case of 100 years of car buying in America is used as a particular example, drawn from a larger study of nine everyday American activities

Distributed intelligent control and management (DICAM) applications and support for semi-automated development

We have recently begun a 4-year effort to develop a new technology foundation and associated methodology for the rapid development of high-performance intelligent controllers. Our objective in this work is to enable system developers to create effective real-time systems for control of multiple, coordinated entities in much less time than is currently required. Our technical strategy for achieving this objective is like that in other domain-specific software efforts: analyze the domain and task underlying effective performance, construct parametric or model-based generic components and overall solutions to the task, and provide excellent means for specifying, selecting, tailoring or automatically generating the solution elements particularly appropriate for the problem at hand. In this paper, we first present our specific domain focus, briefly describe the methodology and environment we are developing to provide a more regular approach to software development, and then later describe the issues this raises for the research community and this specific workshop

Moving towards a model of professional identity formation in midwifery through conversations and positioning theory

The disciplines of nursing and midwifery both uphold a powerful oral tradition that can impact upon student learning. Students enrolled in a Graduate Diploma of Midwifery are supervised and assessed by midwives during their placements in midwifery practice settings by a program of \u27preceptorship\u27 support and where conversations are innate. Positioning theory, eveloped by Harre and others, is a metaphorical concept in which an individual \u27positions\u27 herself/himself within entities of encompassing people, institutions and societies where conversations are conducted either privately or publicly. As construction sites of professional learning, conversations are underpinned by reflective practices.In unravelling conversations, positioning may be applied as an analytical tool by educators to interpret the emerging meanings and themes in their discussions with students, reflective journals by students and in meetings with preceptors/midwives.<br /

Architecture for Adaptive Intelligent Systems

We identify a class of niches to be occupied by 'adaptive intelligent systems (AISs)'. In contrast with niches occupied by typical AI agents, AIS niches present situations that vary dynamically along several key dimensions: different combinations of required tasks, different configurations of available resources, contextual conditions ranging from benign to stressful, and different performance criteria. We present a small class hierarchy of AIS niches that exhibit these dimensions of variability and describe a particular AIS niche, ICU (intensive care unit) patient monitoring, which we use for illustration throughout the paper. We have designed and implemented an agent architecture that supports all of different kinds of adaptation by exploiting a single underlying theoretical concept: An agent dynamically constructs explicit control plans to guide its choices among situation-triggered behaviors. We illustrate the architecture and its support for adaptation with examples from Guardian, an experimental agent for ICU monitoring

Using action-based hierarchies for real-time diagnosis

AbstractAn intelligent agent diagnoses perceived problems so that it can respond to them appropriately. Basically, the agent performs a series of tests whose results discriminate among competing hypotheses. Given a specific diagnosis, the agent performs the associated action. Using the traditional information-theoretic heuristic to order diagnostic tests in a decision tree, the agent can maximize the information obtained from each successive test and thereby minimize the average time (number of tests) required to complete a diagnosis and perform the appropriate action. However, in real-time domains, even the optimal sequence of tests cannot always be performed in the time available. Nonetheless, the agent must respond. For agents operating in real-time domains, we propose an alternative action-based approach in which: (a) each node in the diagnosis tree is augmented to include an ordered set of actions, each of which has positive utility for all of its children in the tree; and (b) the tree is structured to maximize the expected utility of the action available at each node. Upon perceiving a problem, the agent works its way through the tree, performing tests that discriminate among successively smaller subsets of potential faults. When a deadline occurs, the agent performs the best available action associated with the most specific node it has reached so far. Although the action-based approach does not minimize the time required to complete a specific diagnosis, it provides positive utility responses, with step-wise improvements in expected utility, throughout the diagnosis process. We present theoretical and empirical results contrasting the advantages and disadvantages of the information-theoretic and action-based approaches

The accidental youth worker

Author's note: This is an informal, personal and reflective paper that contains my thoughts and feelings on being invited to participate in the European Outdoor Education Network Seminar, held near Keswick, in October 2012. It includes elements of an article submitted as partial requirements of my MA in Youth Work and Community Development. This, together with the research also conducted as part of the qualification, formed the basis for my workshop delivered at the seminar and provides the foundations for my doctoral research. I will begin by providing a summary of my background with an explanation of how I came to be at the conference. I will then reflect on my experiences and conclude with my future plans

Toxin–antitoxin regulation: bimodal interaction of YefM–YoeB with paired DNA palindromes exerts transcriptional autorepression

Toxin–antitoxin (TA) complexes function in programmed cell death or stress response mechanisms in bacteria. The YefM–YoeB TA complex of Escherichia coli consists of YoeB toxin that is counteracted by YefM antitoxin. When liberated from the complex, YoeB acts as an endoribonuclease, preferentially cleaving 3′ of purine nucleotides. Here we demonstrate that yefM-yoeB is transcriptionally autoregulated. YefM, a dimeric protein with extensive secondary structure revealed by circular dichroism (CD) and nuclear magnetic resonance (NMR) spectroscopy, is the primary repressor, whereas YoeB is a repression enhancer. The operator site 5′ of yefM-yoeB comprises adjacent long and short palindromes with core 5′-TGTACA-3′ motifs. YefM binds the long palindrome, followed sequentially by short palindrome recognition. In contrast, the repressor–corepressor complex recognizes both motifs more avidly, impyling that YefM within the complex has an enhanced DNA-binding affinity compared to free YefM. Operator interaction by YefM and YefM–YoeB is accompanied by structural transitions in the proteins. Paired 5′-TGTACA-3′ motifs are common in yefM-yoeB regulatory regions in diverse genomes suggesting that interaction of YefM–YoeB with these motifs is a conserved mechanism of operon autoregulation. Artificial perturbation of transcriptional autorepression could elicit inappropriate YoeB toxin production and induction of bacterial cell suicide, a potentially novel antibacterial strategy