4,042 research outputs found
Selection of design and operational parameters in spindle-holder-tool assemblies for maximum chatter stability by using a new analytical model
In this paper, using the analytical model developed by the authors, the effects of certain system design and operational parameters on the tool point FRF, thus on the chatter stability are studied. Important conclusions are derived regarding the selection of the system parameters at the stage of machine tool design and during a practical application in order to increase chatter stability. It is demonstrated that the stability diagram for an application can be modified in a predictable manner in order to maximize the chatter-free material removal rate by selecting favorable system parameters using the analytical model developed. The predictions of the model, which are based on the methodology proposed in this study, are also experimentally verified
Low temperature vapor phase catalytic oxidation unit
Low temperature vapor phase catalytic oxidation unit for removing organics in urine distillatio
Studies of hepatic synthesis in vivo of plasma proteins, including orosomucoid, transferrin, α-antitrypsin, C8, and factor B
Serum protein types were determined in eight recipients and donors in cases of hepatic homotransplantation. A change from recipient type to donor type was observed for factor B, C8, orosomucoid, haptoglobin, transferrin, α1-antitrypsin, C3 and C6, but not for Gm and Inv immunoglobulin markers. The results indicate that all the proteins studied (except immunoglobulins) are produced primarily by the liver in vivo. © 1980
Measurement of the neutral pion cross section in proton-proton collisions at sqrt{s}=200GeV with PHENIX
The inclusive cross section for neutral pion production in the range
1<p_T<13GeV/c in |eta|<0.35 has been measured by the PHENIX experiment in
proton-proton collisions at sqrt{s}=200GeV. An NLO pQCD calculation is, within
the experimental and theoretical uncertainties, consistent with the
measurement.Comment: 4 pages, 4 figures. Talk presented at Quark Matter 2002, Nantes,
France, July 18-24, 2002. To appear in the proceedings (Nucl. Phys. A
OGO-E space vehicle response to transient loading at Atlas booster engine cutoff
Computer program for OGO-E vehicle response analysis to transient loading during Atlas booster burnou
An augmented Lagrangian method for autofocused compressed SAR imaging
We present an autofocus algorithm for Compressed SAR Imaging. The technique estimates and corrects for 1-D phase errors in the phase history domain, based on prior knowledge that the reflectivity field is sparse, as in the case of strong scatterers against a weakly-scattering background. The algorithm relies on the Sparsity Driven Autofocus (SDA) method and Augmented Lagrangian Methods (ALM), particularly Alternating Directions Method of Multipliers (ADMM). In particular, we propose an ADMM-based algorithm that we call Autofocusing Iteratively Re-Weighted Augmented Lagrangian Method (AIRWALM) to solve a constrained formulation of the sparsity driven autofocus problem with an ℓp-norm, p ≤ 1 cost function. We then compare the performance of the proposed algorithm's performance to Phase Gradient Autofocus (PGA) and SDA [2] in terms of autofocusing capability, phase error correction, and computation time
Simultaneous use of Individual and Joint Regularization Terms in Compressive Sensing: Joint Reconstruction of Multi-Channel Multi-Contrast MRI Acquisitions
Purpose: A time-efficient strategy to acquire high-quality multi-contrast
images is to reconstruct undersampled data with joint regularization terms that
leverage common information across contrasts. However, these terms can cause
leakage of uncommon features among contrasts, compromising diagnostic utility.
The goal of this study is to develop a compressive sensing method for
multi-channel multi-contrast magnetic resonance imaging (MRI) that optimally
utilizes shared information while preventing feature leakage.
Theory: Joint regularization terms group sparsity and colour total variation
are used to exploit common features across images while individual sparsity and
total variation are also used to prevent leakage of distinct features across
contrasts. The multi-channel multi-contrast reconstruction problem is solved
via a fast algorithm based on Alternating Direction Method of Multipliers.
Methods: The proposed method is compared against using only individual and
only joint regularization terms in reconstruction. Comparisons were performed
on single-channel simulated and multi-channel in-vivo datasets in terms of
reconstruction quality and neuroradiologist reader scores.
Results: The proposed method demonstrates rapid convergence and improved
image quality for both simulated and in-vivo datasets. Furthermore, while
reconstructions that solely use joint regularization terms are prone to
leakage-of-features, the proposed method reliably avoids leakage via
simultaneous use of joint and individual terms.
Conclusion: The proposed compressive sensing method performs fast
reconstruction of multi-channel multi-contrast MRI data with improved image
quality. It offers reliability against feature leakage in joint
reconstructions, thereby holding great promise for clinical use.Comment: 13 pages, 13 figures. Submitted for possible publicatio
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