117,617 research outputs found
The Open Graph Archive: A Community-Driven Effort
In order to evaluate, compare, and tune graph algorithms, experiments on well
designed benchmark sets have to be performed. Together with the goal of
reproducibility of experimental results, this creates a demand for a public
archive to gather and store graph instances. Such an archive would ideally
allow annotation of instances or sets of graphs with additional information
like graph properties and references to the respective experiments and results.
Here we examine the requirements, and introduce a new community project with
the aim of producing an easily accessible library of graphs. Through successful
community involvement, it is expected that the archive will contain a
representative selection of both real-world and generated graph instances,
covering significant application areas as well as interesting classes of
graphs.Comment: 10 page
Analysing and modelling train driver performance
Arguments for the importance of contextual factors in understanding human performance have been made extremely persuasive in the context of the process control industries. This paper puts these arguments into the context of the train driving task, drawing on an extensive analysis of driver performance with the Automatic Warning System (AWS). The paper summarises a number of constructs from applied psychological research which are thought to be important in understanding train driver performance. A “Situational Model” is offered as a framework for investigating driver performance. The model emphasises the importance of understanding the state of driver cognition at a specific time (“Now”) in a specific situation and a specific context
Design project 1968/9: management report
1. INTRODUCTION
The design of an automatic assembly machine with versatility in
application was undertaken as a group project by post-graduate
students attending a course in production technology. This
report summarises the work clone and conclusions reached during
the project. In addition there are available five other reports
which describe the designing of different areas of the machine in
full detail (refs. 1 to 6). There is also the report of a technical
survey which was carried out to investigate industrial requirements
for automatic assembly. In order that this report may serve as a
guide, a summary of the content of each of the other reports is
included
A Statistical Modeling Approach to Computer-Aided Quantification of Dental Biofilm
Biofilm is a formation of microbial material on tooth substrata. Several
methods to quantify dental biofilm coverage have recently been reported in the
literature, but at best they provide a semi-automated approach to
quantification with significant input from a human grader that comes with the
graders bias of what are foreground, background, biofilm, and tooth.
Additionally, human assessment indices limit the resolution of the
quantification scale; most commercial scales use five levels of quantification
for biofilm coverage (0%, 25%, 50%, 75%, and 100%). On the other hand, current
state-of-the-art techniques in automatic plaque quantification fail to make
their way into practical applications owing to their inability to incorporate
human input to handle misclassifications. This paper proposes a new interactive
method for biofilm quantification in Quantitative light-induced fluorescence
(QLF) images of canine teeth that is independent of the perceptual bias of the
grader. The method partitions a QLF image into segments of uniform texture and
intensity called superpixels; every superpixel is statistically modeled as a
realization of a single 2D Gaussian Markov random field (GMRF) whose parameters
are estimated; the superpixel is then assigned to one of three classes
(background, biofilm, tooth substratum) based on the training set of data. The
quantification results show a high degree of consistency and precision. At the
same time, the proposed method gives pathologists full control to post-process
the automatic quantification by flipping misclassified superpixels to a
different state (background, tooth, biofilm) with a single click, providing
greater usability than simply marking the boundaries of biofilm and tooth as
done by current state-of-the-art methods.Comment: 10 pages, 7 figures, Journal of Biomedical and Health Informatics
2014. keywords: {Biomedical imaging;Calibration;Dentistry;Estimation;Image
segmentation;Manuals;Teeth},
http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6758338&isnumber=636350
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