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363 results on '"Tim Oates"'

1. The Futures of Assessments: Navigating Uncertainties through the Lenses of Anticipatory Thinking

Author

Cambridge University Press & Assessment (United Kingdom), Fawaz Abu Sitta, Bryan Maddox, Imogen Casebourne, Sarah Hughes, Martina Kuvalja, Judith Hannam, and Tim Oates

Abstract

The multifaceted disruption of social and political processes during the most intense phases of the COVID crisis encouraged many groups and individuals to propose change and reform to education. This current report is a distinctive voice in the debate about 'assessment futures'. Not least, it outlines the nature of human construction of the future. It acknowledges that while the future might be constrained by current arrangements and the impact of past policy and practice, the future is not 'inevitable' or fixed, but is the product of human agency: a combination of thought, decisions, actions and reactions. The aim of this research, looking forward to 2050, was not to predict the future of assessment but to use Futures Thinking as an approach to anticipate plausible future directions. The research was carried out in collaboration with individuals and groups from various departments across the University of Cambridge and two external groups. The participants took part in three 3-hour long workshops, with many completing significant work in-between the first and the second workshop. This study highlighted fundamental distinctions between linear and nonlinear approaches to future forecasting. It emphasises the necessity for unconventional methodologies to anticipate discontinuities and surprises resulting from radical shifts and disruptive innovation.

Published
2023

2. Computer vision supported pedestrian tracking: A demonstration on trail bridges in rural Rwanda.

Author

Evan Thomas, Sally Gerster, Lambert Mugabo, Huguens Jean, and Tim Oates

Subjects
Medicine, Science
Abstract

Trail bridges can improve access to critical services such as health care, schools, and markets. In order to evaluate the impact of trail bridges in rural Rwanda, it is helpful to objectively know how and when they are being used. In this study, we deployed motion-activated digital cameras across several trail bridges installed by the non-profit Bridges to Prosperity. We conducted and validated manual counting of bridge use to establish a ground truth. We adapted an open source computer vision algorithm to identify and count bridge use reflected in the digital images. We found a reliable correlation with less than 3% error bias of bridge crossings per hour between manual counting and those sites at which the cameras logged short video clips. We applied this algorithm across 186 total days of observation at four sites in fall 2019, and observed a total of 33,800 daily bridge crossings ranging from about 20 to over 1,100 individual uses per day, with no apparent correlation between daily or total weekly rainfall and bridge use, potentially indicating that transportation behaviors, after a bridge is installed, are no longer impacted by rainfall conditions. Higher bridge use was observed in the late afternoons, on market and church days, and roughly equal use of the bridge crossings in each direction. These trends are consistent with the design-intent of these bridges.

Published
2020
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6. Discovering and Characterizing Hidden Variables Using a Novel Neural Network Architecture: LO-Net

Author

Soumi Ray and Tim Oates

Subjects
Mechanical engineering and machinery, TJ1-1570
Abstract

Theoretical entities are aspects of the world that cannot be sensed directly but that, nevertheless, are causally relevant. Scientific inquiry has uncovered many such entities, such as black holes and dark matter. We claim that theoretical entities, or hidden variables, are important for the development of concepts within the lifetime of an individual and present a novel neural network architecture that solves three problems related to theoretical entities: (1) discovering that they exist, (2) determining their number, and (3) computing their values. Experiments show the utility of the proposed approach using discrete time dynamical systems, in which some of the state variables are hidden, and sensor data obtained from the camera of a mobile robot, in which the sizes and locations of objects in the visual field are observed but their sizes and locations (distances) in the three-dimensional world are not. Two different regularization terms are explored that improve the network's ability to approximate the values of hidden variables, and the performance and capabilities of the network are compared to that of Hidden Markov Models.

Published
2011
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13. Lempel-Ziv Networks.

Author

Rebecca Saul, Mohammad Mahmudul Alam, John Hurwitz, Edward Raff, Tim Oates 0001, and James Holt

Published
2022

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