A fault identification and classification scheme for an automobile door assembly process

A process fault identification and classification scheme for an automobile door assembly process is presented based on multivariate in-line dimensional measurements and principal component factor analysis. First, the door assembly process and the dimensional measurement system are briefly introduced. Second, the technique of principal component factor analysis is presented for process fault identification. Process faults are summarized based on off-line identified case studies. Finally a machine classification scheme based on principal components and principal factors is presented and evaluated, using the pattern knowledge obtained off-line. This scheme is shown to be effective in classifying process faults using production data.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/45569/1/10696_2005_Article_BF01324797.pd

Некоторые вопросы моделирования центробежных насосов

This work presents a novel object tracking approach, where the motion model is learned from sets of frame-wise detections with unknown associations. We employ a higher-order Markov model on position space instead of a first-order Markov model on a high-dimensional state-space of object dynamics. Compared to the latter, our approach allows the use of marginal rather than joint distributions, which results in a significant reduction of computation complexity. Densities are represented using a grid-based approach, where the rectangular windows are replaced with estimated smooth Parzen windows sampled at the grid points. This method performs as accurately as particle filter methods with the additional advantage that the prediction and update steps can be learned from empirical data. Our method is compared against standard techniques on image sequences obtained from an RC car following scenario. We show that our approach performs best in most of the sequences. Other potential applications are surveillance from cheap or uncalibrated cameras and image sequence analysis.DIPLEC

The economic and accounting content of fixed assets

This book presents a mathematical methodology for image analysis tasks at the edge of current research, including anisotropic diffusion filtering of tensor fields. Instead of specific applications, it explores methodological structures on which they are built.DIPLECS, GARNICS, NACI

Sto(ry)chastics: a Bayesian Network Architecture for User Modeling and Computational Storytelling for Interactive Spaces

This paper presents sto(ry)chastics, a user-centered approach for computational storytelling for real-time sensor-driven multimedia audiovisual stories, such as those that are triggered by the body in motion in a sensor-instrumented interactive narrative space. With sto(ry)chastics the coarse and noisy sensor inputs are coupled to digital media outputs via a user model, which is estimated probabilistically by a Bayesian network. To illustrate sto(ry)chastics, this paper describes the museum wearable, a device which delivers an audiovisual narration interactively in time and space to the visitor as a function of the estimated visitor type. The wearable relies on a custom-designed long-range infrared locationidentification sensor to gather information on where and how long the visitor stops in the museum galleries and uses this information as input to, or observations of, a (dynamic) Bayesian network. The network has been tested and validated on observed visitor tracking data by parameter learning using the Expectation Maximization (EM) algorithm, and by performance analysis of the model with the learned parameters

Olfactory acuity in theropods: palaeobiological and evolutionary implications

This research presents the first quantitative evaluation of the olfactory acuity in extinct theropod dinosaurs. Olfactory ratios (i.e. the ratio of the greatest diameter of the olfactory bulb to the greatest diameter of the cerebral hemisphere) are analysed in order to infer the olfactory acuity and behavioural traits in theropods, as well as to identify phylogenetic trends in olfaction within Theropoda. A phylogenetically corrected regression of olfactory ratio to body mass reveals that, relative to predicted values, the olfactory bulbs of (i) tyrannosaurids and dromaeosaurids are significantly larger, (ii) ornithomimosaurs and oviraptorids are significantly smaller, and (iii) ceratosaurians, allosauroids, basal tyrannosauroids, troodontids and basal birds are within the 95% CI. Relative to other theropods, olfactory acuity was high in tyrannosaurids and dromaeosaurids and therefore olfaction would have played an important role in their ecology, possibly for activities in low-light conditions, locating food, or for navigation within large home ranges. Olfactory acuity was the lowest in ornithomimosaurs and oviraptorids, suggesting a reduced reliance on olfaction and perhaps an omnivorous diet in these theropods. Phylogenetic trends in olfaction among theropods reveal that olfactory acuity did not decrease in the ancestry of birds, as troodontids, dromaeosaurids and primitive birds possessed typical or high olfactory acuity. Thus, the sense of smell must have remained important in primitive birds and its presumed decrease associated with the increased importance of sight did not occur until later among more derived birds