786 research outputs found
Craft Education in the United Kingdom and the United States: A cross-cultural examination of ideals, approaches and solutions
At the conclusion of the Second World War both the United Kingdom and the United States experienced drastic changes in their building industries. As the construction industry progressed, the training systems for construction workers evolved to meet this new demand. This thesis argues that these changes have caused the UK and the US to face a perceived crisis in the training and supply of traditional craft workers. In both societies, different approaches have been taken to address these concerns, based on the evolving ethos of conservation theory in their respective cultures and their educational frameworks. The approaches taken can be seen as reflecting the evolution of conservation theory and practice in each society, which is often expressed through variations in perception of value, age, and methodology, as well as distinct differences in terminology. This thesis studies the progression of heritage craft training through the examination of historical evidence juxtaposed against ethnographic surveys of three generations of craft practitioners along with current educational providers. Using this evidence, this thesis examines the strengths and shortcomings of current heritage craft educational offerings in both networks through the opinions of both practitioners and educational providers using Actor-Network Theory methodology. It is from the triangulation of historical evidence, craft practitioner opinions, and educational provider experiences that this research proposes pathways to improve the educational offerings in both networks. This study argues that contrary to popular belief, the crisis in heritage craft training may be misdiagnosed, but significant improvements need to be made by both countries to enhance the visibility and delivery of the existing training opportunities. This thesis aims to inform our understanding of the progression of this under-studied sphere of the conservation industry in order to enrich future craft training practices
Frequency of Participation in an Employee Fitness Program and Health Care Expenditures
Regular physical activity is strongly linked to prevention of costly chronic health conditions. However, there has been limited examination of the impact that level of participation in physical activity promotion programs has on health care costs. This study examined a fitness reimbursement program (FRP) offered to small employers. FRP participants received 6.14 (2.6%) for low-moderate (P?=?0.60), 20.01 (8.4%) for high (P?=?0.08). With high-cost outliers included, significant monthly cost savings were observed for the moderate-high ($43.52, P?Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/140192/1/pop.2015.0102.pd
Non-Linear Temporal Subspace Representations for Activity Recognition
Representations that can compactly and effectively capture the temporal
evolution of semantic content are important to computer vision and machine
learning algorithms that operate on multi-variate time-series data. We
investigate such representations motivated by the task of human action
recognition. Here each data instance is encoded by a multivariate feature (such
as via a deep CNN) where action dynamics are characterized by their variations
in time. As these features are often non-linear, we propose a novel pooling
method, kernelized rank pooling, that represents a given sequence compactly as
the pre-image of the parameters of a hyperplane in a reproducing kernel Hilbert
space, projections of data onto which captures their temporal order. We develop
this idea further and show that such a pooling scheme can be cast as an
order-constrained kernelized PCA objective. We then propose to use the
parameters of a kernelized low-rank feature subspace as the representation of
the sequences. We cast our formulation as an optimization problem on
generalized Grassmann manifolds and then solve it efficiently using Riemannian
optimization techniques. We present experiments on several action recognition
datasets using diverse feature modalities and demonstrate state-of-the-art
results.Comment: Accepted at the IEEE International Conference on Computer Vision and
Pattern Recognition, CVPR, 2018. arXiv admin note: substantial text overlap
with arXiv:1705.0858
Self-Calibration of Cameras with Euclidean Image Plane in Case of Two Views and Known Relative Rotation Angle
The internal calibration of a pinhole camera is given by five parameters that
are combined into an upper-triangular calibration matrix. If the
skew parameter is zero and the aspect ratio is equal to one, then the camera is
said to have Euclidean image plane. In this paper, we propose a non-iterative
self-calibration algorithm for a camera with Euclidean image plane in case the
remaining three internal parameters --- the focal length and the principal
point coordinates --- are fixed but unknown. The algorithm requires a set of point correspondences in two views and also the measured relative
rotation angle between the views. We show that the problem generically has six
solutions (including complex ones).
The algorithm has been implemented and tested both on synthetic data and on
publicly available real dataset. The experiments demonstrate that the method is
correct, numerically stable and robust.Comment: 13 pages, 7 eps-figure
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