Design, implementation, and testing of advanced virtual coordinate-measuring machines

Copyright @ 2011 IEEE. This article has been made available through the Brunel Open Access Publishing Fund.Advanced virtual coordinate-measuring machines (CMMs) (AVCMMs) have recently been developed at Brunel University, which provide vivid graphical representation and powerful simulation of CMM operations, together with Monte-Carlo-based uncertainty evaluation. In an integrated virtual environment, the user can plan an inspection strategy for a given task, carry out virtual measurements, and evaluate the uncertainty associated with the measurement results, all without the need of using a physical machine. The obtained estimate of uncertainty can serve as a rapid feedback for the user to optimize the inspection plan in the AVCMM before actual measurements or as an evaluation of the measurement results performed. This paper details the methodology, design, and implementation of the AVCMM system, including CMM modeling, probe contact and collision detection, error modeling and simulation, and uncertainty evaluation. This paper further reports experimental results for the testing of the AVCMM

Task Specific Uncertainty in Coordinate Measurement

Task specific uncertainty is the measurement uncertainty associated with the measurement of a specific feature using a specific measurement plan. This paper surveys techniques developed to model and estimate task specific uncertainty for coordinate measuring systems, primarily coordinate measuring machines using contacting probes. Sources of uncertainty are also reviewed

Cohort Efficacy Study of Natural Family Planning among Perimenopause Age Women

Objective: To determine the efficacy of using natural family planning (NFP) methods to avoid unintended pregnancy among women of perimenopause age (i.e., age 40-55 years). Design: A secondary analysis of subset data from two prospective observational cohort studies. Setting: A university based in-person and online NFP service program. Participants: One hundred and sixty couples who used either a website or an in-person NFP service to learn how to avoid pregnancy from January 2001 to November 2012. Methods: A prospective 12-month effectiveness study among 160 women (between ages 40-55) who used NFP to avoid pregnancy. The women used either a hormonal fertility monitor, cervical mucus monitoring, or both to estimate the fertile phase of their menstrual cycles. Survival analysis was used to determine the pregnancy rate over 12 months of use. Results: There were a total of five unintended pregnancies among the participants. The typical use pregnancy rate was six per 100 women over 12 months. The monitor alone participants (n = 35) had a 12-month pregnancy rate of three, the participants (n = 73) who used mucus alone had a pregnancy rate of four, and the participants (n = 42) who used the fertility monitor plus mucus had a pregnancy rate of six. Conclusion: Natural family planning methods can be effective for older women to avoid an unintended pregnancy with correct use and adequate instructions. The pregnancy rate most likely was affected by diminished fertility and motivation to limit family size

Covariant and Heavy Quark Symmetric Quark Models

There exist relativistic quark models (potential or MIT-bag) which satisfy the heavy quark symmetry (HQS) relations among meson decay constants and form factors. Covariant construction of the momentum eigenstates, developed here, can correct for spurious center-of-mass motion contributions.Proton form factor and M1 transitions in quarkonia are calculated. Explicit expression for the Isgur-Wise function is found and model determined deviations from HQS are studied. All results depend on the model parameters only. No additional ad hoc assumptions are needed.Comment: 34 pages (2 figures not included but avaliable upon request), LATEX, (to be published in Phys.Rev.D

Every Smile is Unique: Landmark-Guided Diverse Smile Generation

Each smile is unique: one person surely smiles in different ways (e.g., closing/opening the eyes or mouth). Given one input image of a neutral face, can we generate multiple smile videos with distinctive characteristics? To tackle this one-to-many video generation problem, we propose a novel deep learning architecture named Conditional Multi-Mode Network (CMM-Net). To better encode the dynamics of facial expressions, CMM-Net explicitly exploits facial landmarks for generating smile sequences. Specifically, a variational auto-encoder is used to learn a facial landmark embedding. This single embedding is then exploited by a conditional recurrent network which generates a landmark embedding sequence conditioned on a specific expression (e.g., spontaneous smile). Next, the generated landmark embeddings are fed into a multi-mode recurrent landmark generator, producing a set of landmark sequences still associated to the given smile class but clearly distinct from each other. Finally, these landmark sequences are translated into face videos. Our experimental results demonstrate the effectiveness of our CMM-Net in generating realistic videos of multiple smile expressions.Comment: Accepted as a poster in Conference on Computer Vision and Pattern Recognition (CVPR), 201

Review of the mathematical foundations of data fusion techniques in surface metrology

The recent proliferation of engineered surfaces, including freeform and structured surfaces, is challenging current metrology techniques. Measurement using multiple sensors has been proposed to achieve enhanced benefits, mainly in terms of spatial frequency bandwidth, which a single sensor cannot provide. When using data from different sensors, a process of data fusion is required and there is much active research in this area. In this paper, current data fusion methods and applications are reviewed, with a focus on the mathematical foundations of the subject. Common research questions in the fusion of surface metrology data are raised and potential fusion algorithms are discussed

Performance characterisation of a new photo-microsensor based sensing head for displacement measurement

This paper presents a robust displacement sensor with nanometre-scale resolution over a micrometre range. It is composed of low cost commercially available slotted photo-microsensors (SPMs). The displacement sensor is designed with a particular arrangement of a compact array of SPMs with specially designed shutter assembly and signal processing to significantly reduce sensitivity to ambient light, input voltage variation, circuit electronics drift, etc. The sensor principle and the characterisation results are described in this paper. The proposed prototype sensor has a linear measurement range of 20 μm and resolution of 21 nm. This kind of sensor has several potential applications, including mechanical structural deformation monitoring system