1,764 research outputs found
Yule, R J, 218491
No full textThis record was harvested from a previous catalogue system and will be withdrawn in 2025. Information in this record may be superseded or incomplete. Visit this record in UMA's new catalogue at: https://archives.library.unimelb.edu.au/nodes/view/427750Surname: YULE. Given Name(s) or Initials: R J. Military Service Number or Last Known Location: 218491. Missing, Wounded and Prisoner of War Enquiry Card Index Number: SEA-3825.253722
Item: [2016.0049.60011] "Yule, R J, 218491
The simulation of action disorganisation in complex activities of daily living
No full textAction selection in everyday goal-directed tasks of moderate complexity is known to be subject to breakdown following extensive frontal brain injury. A model of action selection in such tasks is presented and used to explore three hypotheses concerning the origins of action disorganisation: that it is a consequence of reduced top-down excitation within a hierarchical action schema network coupled with increased bottom-up triggering of schemas from environmental sources, that it is a more general disturbance of schema activation modelled by excessive noise in the schema network, and that it results from a general disturbance of the triggering of schemas by object representations. Results suggest that the action disorganisation syndrome is best accounted for by a general disturbance to schema activation, while altering the balance between top-down and bottom-up activation provides an account of a related disorder - utilisation behaviour. It is further suggested that ideational apraxia (which may result from lesions to left temporoparietal areas and which has similar behavioural consequences to action disorganisation syndrome on tasks of moderate complexity) is a consequence of a generalised disturbance of the triggering of schemas by object representations. Several predictions regarding differences between action disorganisation syndrome and ideational apraxia that follow from this interpretation are detailed
Yule Magic
No full textPhotograph used for a story in the Daily Oklahoman newspaper. Caption: "Yule Magic - L to R , Enthralled with magician are Betty Dunigan, 10-years-old and La Donna Smith, 9-years-old.
The origins of fixed X regression
No full textIn 1922 R. A. Fisher introduced the fixed X regression model, synthesising the regression theory of Pearson and Yule with the least squares theory of Gauss. The innovation was based on Fisher's realisation that the distribution associated with the regression coefficient was unaffected by the distribution of X. Subsequently Fisher interpreted the fixed X assumption in terms of his notion of ancillarity. This paper considers these developments against the background of early twentieth century statistical theory
The origins of fixed X regression
No full textIn 1922 R. A. Fisher introduced the fixed X regression model, synthesising the regression theory of Pearson and Yule with the least squares theory of Gauss. The innovation was based on Fisher's realisation that the distribution associated with the regression coefficient was unaffected by the distribution of X. Subsequently Fisher interpreted the fixed X assumption in terms of his notion of ancillarity. This paper considers these developments against the background of early twentieth century statistical theor
'I wear them every day, 365 days a year': children's perspectives on orthoses
No full textObjective: The aim of this small, mainly qualitative, study was to discover what a group of children with cerebral palsy (CP) think of their orthoses and the effect they have on their walking. The study complemented a biomechanical assessment of the children walking with, and without, their orthoses.Method: Fourteen children were recruited from physiotherapy departments located in a residential school and two child development centres. The children were aged between 5 and 16 years, and had a diagnosis of CP. Between them, the children wore a variety of orthoses and used a variety of walking aids, although the Kaye walker was the most frequently used. The children’s views and experiences were gathered by semi-structured interview. During the biomechanical assessment the children were also asked to rate four aspects of their walking – speed, ease, steadiness, and level of tiredness – by means of pictorial scales. The audiotaped interview data were transcribed and subjected to content analysis. The ratings from the scales were compared using the Wilcoxon signed ranks test.Results: Most children wore their orthoses for the majority of the time, found them comfortable, and some reported definite benefits to wearing them. Even when children did not identify specific benefits they seemed to accept wearing the orthoses. Children’s ratings of their walking with and without orthoses identified no clear preference. The difference in ratings was not statistically significant apart from level of tiredness which was significantly in favour of walking without orthoses (z=–1.983, p=0.047). There was a lack of consistency between the children’s ratings and the results from the biomechanical assessments, which were also inconclusive. However, one child, for whom definite improvements were seen in velocity and energy costs when wearing orthoses, consistently rated her own performance as better with orthoses.Conclusions: The children’s experiences of wearing orthoses were mainly positive or neutral. The children did not consistently identify a preference for walking with or without orthoses.This may have been due to their age, their expectations, or the fact that the findings of the biomechanical assessments were not consistent either. The experience of carrying out this study indicates that children are able to express their views about, and experiences of, a therapeutic intervention.Acknowledgements: The children who took part in the study and their families; the physiotherapists who helped with recruitment, and the charity HOPE, for funding
The Yule - Simon model in its limiting case as a pure migration process
No full textIn this paper the author offers an analytical solution to a problem first raised in 1973, namely, what is the equilibrium distribution of city sizes implied by the Yule - Simon model, when the total population of the urban system in question is stationary? Under the assumption that in-migration and out-migration rates are uncorrelated with city sizes, it is shown that Fisher's log-series distribution is that distribution. Fisher's log-series distribution yields a much less concentrated size distribution than does the Yule distribution, which is the equilibrium distribution associated with a pure growth process. Thus, we might expect a lower level of concentration or city size inequality when the overall urban system is stationary than when it is growing.
Effect of gait cycle selection on EMG analysis during walking in adults and children with gait pathology
No full textThis paper presents the results of a project to evaluate different methods of gait cycle selection on the analysis of electromyography recorded during gait. Electromyography (EMG) describes the electrical activity associated with the muscle and is often interpreted in gait analysis using a simultaneously obtained signal to identify phases of the gait cycle. Phase transitions are often selected manually from reference signals derived from additional instrumentation, such as pressure platforms, footswitches and video cameras. We propose two methods (automatic and semi-automatic) as an alternative to the more traditional manual selection, and analyse how the gait cycle selection affects the EMG analysis. To quantify the differences between the gait cycles obtained using each method and to classify each cycle, three indices have been introduced. The effect of the gait cycle selection has been evaluated with respect to the EMG step profiles and temporal gait descriptors. An asymptomatic adult, an asymptomatic child and two children with cerebral palsy were examined using telemetric EMG devices and pressure footswitches. The results obtained showed that the method of gait cycle selection did not have a major influence for the adult, but it altered considerably the analysis in the case of the children with cerebral palsy
Superstars and Journeymen: An Analysis of National Football Team’s Allocation of the Salary Cap across Rosters, 2000-2005
No full textThe National Football League constrains teams’ payrolls via a “salary cap.” We analyze how teams allocate cap spending across rosters using a data set of over 10,000 player-season observations during 2000-2005. We find that a few players account for relatively high portions of teams’ caps, and that the players’ “cap values” are consistent with both “superstar” and Yule-Simon income distributions. A theoretical model based on a utility function convex with respect to winning is used to explain this result. We also find that the cap has been substantially effective in reducing teams’ ability to “spend their way to championships.”Sports, NFL, Draft, Quarterback, Productivity
EDICS category 1-SPEC On the Noise-Compensated Yule-Walker Equations
No full textRecently a method of estimating the parameters of an AR(p) random process based on measurements corrupted by additive white noise was described. The method involves solving a matrix pencil, called the Noise-Compensated Yule-Walker (NCYW) equations, for the AR parameters and the variance of the measurement noise. In this correspondence we give a necessary and su#cient condition for there to exist a unique solution to the NCYW equations. submitted to IEEE Transactions on Signal Processing April 20, 2001 I. Background The p th -order AR (AR(p)) Random Process is given by x(n) = -a(1)x(n - a(2)x(n - - a(p)x(n p) + w(n) (1) where w(n) is white noise having variance # w and a(k), k = 1, . . . , p are the AR parameters. We assume that x(n) is real. The autocorrelation function of the AR process, r x (k), also satisfies the autoregressive property, this leads to the well-known Yule-Walker equations for the AR parameters r x (k) = i=1 a(i)r x (k i), k 1 (2) Suppose the measurements used to estimate the AR parameters can be modeled as x(n) = x(n) + v(n) where v(n) is white noise having variance # v , then the parameter estimates derived from the Yule-Walker equations will be biased since, r x (k) = r x (k) + #(k)# v where #(k) is the Dirac delta function. It has been shown that the biased AR parameters produce a "flatter" AR spectrum since the estimated poles of the AR process are biased toward the center of the unit circle [1]. A number of methods have been described for estimating the AR parameters using noisy measurements, some of these methods are surveyed in [1, 5]. The Noise-Compensated Yule-Walker (NCYW) equations are defined as (R x #B)u = 0 p+q (3) where R x = # # # # # # # # # # # # # # # # # # # # # # # r x (1) r x (0) r x (-1) ..
- …
