CV - Chris Gatti
... Developed and validated a finite element model of the glenoid labrum to determine the effects of humeral head migration. Used simulated annealing to determine optimal musculoskeletal model parameters to best match experimental measurements and reduce model development time from days to minutes. ...
... Developed and validated a finite element model of the glenoid labrum to determine the effects of humeral head migration. Used simulated annealing to determine optimal musculoskeletal model parameters to best match experimental measurements and reduce model development time from days to minutes. ...
PowerPoint - people.csail.mit.edu
... • Fundamental task: given observations, make inferences about initially unknown objects • But most RPM languages assume set of objects is fixed and known (Herbrand models) • Bayesian logic (BLOG) lifts this assumption [Milch et al., IJCAI 2005. See also MEBN: Laskey & da Costa, UAI 2005; Dynamical G ...
... • Fundamental task: given observations, make inferences about initially unknown objects • But most RPM languages assume set of objects is fixed and known (Herbrand models) • Bayesian logic (BLOG) lifts this assumption [Milch et al., IJCAI 2005. See also MEBN: Laskey & da Costa, UAI 2005; Dynamical G ...
Introductory Guide
... All rights reserved. Produced in the United States of America. For a hard-copy book: No part of this publication may be reproduced, stored in a retrieval system, or transmitted, in any form or by any means, electronic, mechanical, photocopying, or otherwise, without the prior written permission of t ...
... All rights reserved. Produced in the United States of America. For a hard-copy book: No part of this publication may be reproduced, stored in a retrieval system, or transmitted, in any form or by any means, electronic, mechanical, photocopying, or otherwise, without the prior written permission of t ...
MINITAB/TI Calculator Reference Math 214 Contents 1 Chapter 1
... Compute the area under a normal curve with mean µ, standard deviation σ between two points a and b. (Use a = −1E99 for areas to the left of b and b = 1E99 for areas to the right of a.) ...
... Compute the area under a normal curve with mean µ, standard deviation σ between two points a and b. (Use a = −1E99 for areas to the left of b and b = 1E99 for areas to the right of a.) ...
Introduction to MIS
... Better and more efficient decisions if you know the original problems, discussions, and contingency plans ...
... Better and more efficient decisions if you know the original problems, discussions, and contingency plans ...
CSE 5290: Artificial Intelligence
... According to Allerhand [7], the use of simple models in speech recognition creates an inherent performance limitation. A plateau is reached, set by the assumptions implicit in the model, where further improvement cannot be made. Combination of evidence offers a possible means of overcoming the funda ...
... According to Allerhand [7], the use of simple models in speech recognition creates an inherent performance limitation. A plateau is reached, set by the assumptions implicit in the model, where further improvement cannot be made. Combination of evidence offers a possible means of overcoming the funda ...
WWW-newsgroup-document Clustering by Means of
... numbers of neurons in their networks (Figs. 1a and 2a) that finally are equal to 273 and 251, respectively, and the numbers of sub-chains (Figs. 1b and 2b) finally achieving the values equal to 11 in both cases; the number of sub-chains is equal to the number of clusters detected in a given numerica ...
... numbers of neurons in their networks (Figs. 1a and 2a) that finally are equal to 273 and 251, respectively, and the numbers of sub-chains (Figs. 1b and 2b) finally achieving the values equal to 11 in both cases; the number of sub-chains is equal to the number of clusters detected in a given numerica ...
Time series
A time series is a sequence of data points, typically consisting of successive measurements made over a time interval. Examples of time series are ocean tides, counts of sunspots, and the daily closing value of the Dow Jones Industrial Average. Time series are very frequently plotted via line charts. Time series are used in statistics, signal processing, pattern recognition, econometrics, mathematical finance, weather forecasting, intelligent transport and trajectory forecasting, earthquake prediction, electroencephalography, control engineering, astronomy, communications engineering, and largely in any domain of applied science and engineering which involves temporal measurements.Time series analysis comprises methods for analyzing time series data in order to extract meaningful statistics and other characteristics of the data. Time series forecasting is the use of a model to predict future values based on previously observed values. While regression analysis is often employed in such a way as to test theories that the current values of one or more independent time series affect the current value of another time series, this type of analysis of time series is not called ""time series analysis"", which focuses on comparing values of a single time series or multiple dependent time series at different points in time.Time series data have a natural temporal ordering. This makes time series analysis distinct from cross-sectional studies, in which there is no natural ordering of the observations (e.g. explaining people's wages by reference to their respective education levels, where the individuals' data could be entered in any order). Time series analysis is also distinct from spatial data analysis where the observations typically relate to geographical locations (e.g. accounting for house prices by the location as well as the intrinsic characteristics of the houses). A stochastic model for a time series will generally reflect the fact that observations close together in time will be more closely related than observations further apart. In addition, time series models will often make use of the natural one-way ordering of time so that values for a given period will be expressed as deriving in some way from past values, rather than from future values (see time reversibility.)Time series analysis can be applied to real-valued, continuous data, discrete numeric data, or discrete symbolic data (i.e. sequences of characters, such as letters and words in the English language.).