Test Data of Flow Field of Shuttle SRM Nozzle Joint with Bond Defects, Using Unheated Air

The nozzle-to-case joint on the Shuttle SRM (as redesigned after the Challenger accident) features an adhesive sealant filling and bonding the joint, with a wiper O-ring to prevent the adhesive from reaching and disabling the closure O-ring. Flawless implementation of that joint design would ensure that hot, corrosive propellant combustion gases never reach the closure O-ring. However, understanding the flow field related to bonding defects is prudent. A comprehensive test program was conducted to quantify such flow fields and associated heating environments. A two-dimensional, full-scale model represented 65 inches of the nozzle joint, using unheated air as the test medium, in a blowdown mode. Geometry variations modeled RSRM assembly tolerances, and two types of bonding defects: pullaways and blowholes. A range of the magnitude of each type defect was tested. Also a range of operational parameters was tested, representative of the RSRM flow environment, including duplication of RSRM Mach and Reynolds numbers. Extensive instrumentation was provided to quantify pressures, heat rates, and velocities. The resulting data established that larger geometric defects cause larger pressure and larger heating, at the closure O-ring region. Velocity trends were not so straight-forward. Variations in assembly tolerances did not generally affect flow fields or heating. Operational parameters affected flow fields and heating as might be expected, increasing density or velocity increased heating. Complete details of this test effort are presented

Interferon y Stimulation Modulates the Proteolytic Activity and Cleavage Site Preference of 20S Mouse Proteasomes

The proteasome is a 700-kD multisubunit enzyme complex with several proteolytically active sites. The enzyme complex is involved in both ubiquitin-dependent and -independent protein degradation and may contribute to the processing of antigens presented by major histocompatibility complex (MHC) class I molecules. Here we demonstrate that treatment of mouse fibroblast cells with 20 U interferon qr (IFN-y) for 3 d induces a change in the proteasome subunit composition and that the B-type subunit LMP2, which is encoded in the MHC class II region, is incorporated into the enzyme complex. This is paralleled by reduction of the homologous 6-subunit. IFN-3' stimulation results in a downregulation of the chymotrypsin-like Suc-LLVY-MCA peptide hydrolyzing activity of 20S proteasomes whereas the trypsin-like activity remains unaffected. When tested as a substrate a synthetic 25-mer polypeptide whose sequence covers the antigenic nonapeptide YPHFMPTNL of the MCMV pp89, 20S proteasomes of IFN-3'-induced cells exhibit altered chymotrypsin-like cleavage site preferences. In the absence of IFN-qr induction, the naturally processed nonamer peptide that is presented by MHC class.I molecules appears as a minor cleavage product. IFN-'y activation does not result in an increase of the final peptide but results in a different set of peptides. We hypothesize that these peptides represent precursor peptides that can be trimmed to final peptide size

Augmented particle filtering for efficient visual tracking

Copyright © 2005 IEEEVisual tracking is one of the key tasks in computer vision. The particle filter algorithm has been extensively used to tackle this problem due to its flexibility. However the conventional particle filter uses system transition as the proposal distribution, frequently resulting in poor priors for the filtering step. The main reason is that it is difficult, if not impossible, to accurately model the target's motion. Such a proposal distribution does not take into account the current observations. It is not a trivial task to devise a satisfactory proposal distribution for the particle filter. In this paper we advance a general augmented particle filtering framework for designing the optimal proposal distribution. The essential idea is to augment a second filter's estimate into the proposal distribution design. We then show that several existing improved particle filters can be rationalised within this general framework. Based on this framework we further propose variant algorithms for robust and efficient visual tracking. Experiments indicate that the augmented particle filters are more efficient and robust than the conventional particle filter.Chunhua Shen Brooks, M.J. van den Hengel, A

Fast global kernel density mode seeking with application to localisation and tracking

Copyright © 2005 IEEE.We address the problem of seeking the global mode of a density function using the mean shift algorithm. Mean shift, like other gradient ascent optimisation methods, is susceptible to local maxima, and hence often fails to find the desired global maximum. In this work, we propose a multi-bandwidth mean shift procedure that alleviates this problem, which we term annealed mean shift, as it shares similarities with the annealed importance sampling procedure. The bandwidth of the algorithm plays the same role as the temperature in annealing. We observe that the over-smoothed density function with a sufficiently large bandwidth is uni-modal. Using a continuation principle, the influence of the global peak in the density function is introduced gradually. In this way the global maximum is more reliably located. Generally, the price of this annealing-like procedure is that more iterations are required. Since it is imperative that the computation complexity is minimal in real-time applications such as visual tracking. We propose an accelerated version of the mean shift algorithm. Compared with the conventional mean shift algorithm, the accelerated mean shift can significantly decrease the number of iterations required for convergence. The proposed algorithm is applied to the problems of visual tracking and object localisation. We empirically show on various data sets that the proposed algorithm can reliably find the true object location when the starting position of mean shift is far away from the global maximum, in contrast with the conventional mean shift algorithm that will usually get trapped in a spurious local maximum.Chunhua Shen, Michael J. Brooks and Anton van den Henge

The prevalence and incidence of musculoskeletal symptoms among hospital physicians: a systematic review

Physicians are exposed to a range of work-related risk factors that may result in occupational diseases. This systematic review aims at shedding light on the prevalence and incidence of musculoskeletal complaints among hospital physicians. A systematic literature search was performed in Pubmed and EMBASE (1990-2010), and methodological quality criteria were applied. A search was done for musculoskeletal complaints. Five medium-quality studies and three high-quality studies were included in this review. The definitions and assessment used in the studies for musculoskeletal complaints were different. In short, the frequently reported prevalence for hand and wrist pain was 8-33 and 0%, 17% for shoulder pain, and 9-28% for neck pain. Moreover, the annual prevalence of low back pain was between 33 and 68%. The limited number of studies makes it difficult to draw conclusions, and the results should be intepreted with care. In conclusion, musculoskeletal complaints may be work-related complaints in hospital physicians, which need future attentio

From FNS to HEIV: A link between two vision parameter estimation methods

Copyright © 2004 IEEEProblems requiring accurate determination of parameters from imagebased quantities arise often in computer vision. Two recent, independently developed frameworks for estimating such parameters are the FNS and HEIV schemes. Here, it is shown that FNS and a core version of HEIV are essentially equivalent, solving a common underlying equation via different means. The analysis is driven by the search for a nondegenerate form of a certain generalized eigenvalue problem and effectively leads to a new derivation of the relevant case of the HEIV algorithm. This work may be seen as an extension of previous efforts to rationalize and interrelate a spectrum of estimators, including the renormalization method of Kanatani and the normalized eight-point method of Hartley.Wojciech Chojnacki, Michael J. Brooks, Anton van den Hengel, and Darren Gawle

2D articulated tracking with dynamic Bayesian networks

©2004 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.We present a novel method for tracking the motion of an articulated structure in a video sequence. The analysis of articulated motion is challenging because of the potentially large number of degrees of freedom (DOFs) of an articulated body. For particle filter based algorithms, the number of samples required with high dimensional problems can be computationally prohibitive. To alleviate this problem, we represent the articulated object as an undirected graphical model (or Markov Random Field, MRF) in which soft constraints between adjacent subparts are captured by conditional probability distributions. The graphical model is extended across time frames to implement a tracker. The tracking algorithm can be interpreted as a belief inference procedure on a dynamic Bayesian network. The discretisation of the state vectors makes it possible to utilise the efficient belief propagation (BP) and mean field (MF) algorithms to reason in this network. Experiments on real video sequences demonstrate that the proposed method is computationally efficient and performs well in tracking the human body.Chunhua Shen, Anton van den Hengel, Anthony Dick, Michael J. Brook

FNS and HEIV: relating two vision parameter estimation frameworks

©2003 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.Problems requiring accurate determination of parameters from image-based quantities arise often in computer vision. Two recent, independently developed frameworks for estimating such parameters are the FNS and HEIV schemes. Here it is shown that FNS and a core version of HEIV are essentially equivalent, solving a common underlying equation via different means. The analysis is driven by the search for a non-degenerate form of a certain generalised eigen-value problem, and effectively leads to a new derivation of the relevant case of the HEIV algorithm. This work may be seen as an extension of previous efforts to rationalise and inter-relate a spectrum of estimators, including the renormalisation method of Kanatani and the normalised eight-point method of Hartley.Wojciech Chojnacki, Michael J. Brooks, Anton van den Hengel, Darren Gawle

A voting scheme for estimating the synchrony of moving-camera videos

Copyright © 2003 IEEERecovery of dynamic scene properties from multiple videos usually requires the manipulation of synchronous (simultaneously captured) frames. This paper is concerned with the automated determination of this synchrony when the temporal alignment of sequences is unknown. A cost function characterising departure from synchrony is first evolved for the case in which two videos are generated by cameras that may be moving. A novel voting method is then presented for minimising the cost function in the case where the ratio of the cameras' frame rates is unknown. Experimental results indicate this relatively general approach holds promise.Pooley, D.W.; Brooks, M.J.; van den Hengel, A.J.; Chojnacki, W