102 research outputs found

    Adaptive two-pass rank order filter to remove impulse noise in highly corrupted images

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    This material is posted here with permission of the IEEE. Such permission of the IEEE does not in any way imply IEEE endorsement of any of Brunel University's products or services. Internal or 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 must be obtained from the IEEE by writing to [email protected]. © 2004 IEEE.In this paper, we present an adaptive two-pass rank order filter to remove impulse noise in highly corrupted images. When the noise ratio is high, rank order filters, such as the median filter for example, can produce unsatisfactory results. Better results can be obtained by applying the filter twice, which we call two-pass filtering. To further improve the performance, we develop an adaptive two-pass rank order filter. Between the passes of filtering, an adaptive process is used to detect irregularities in the spatial distribution of the estimated impulse noise. The adaptive process then selectively replaces some pixels changed by the first pass of filtering with their original observed pixel values. These pixels are then kept unchanged during the second filtering. In combination, the adaptive process and the sec ond filter eliminate more impulse noise and restore some pixels that are mistakenly altered by the first filtering. As a final result, the reconstructed image maintains a higher degree of fidelity and has a smaller amount of noise. The idea of adaptive two-pass processing can be applied to many rank order filters, such as a center-weighted median filter (CWMF), adaptive CWMF, lower-upper-middle filter, and soft-decision rank-order-mean filter. Results from computer simulations are used to demonstrate the performance of this type of adaptation using a number of basic rank order filters.This work was supported in part by CenSSIS, the Center for Subsurface Sensing and Imaging Systems, under the Engineering Research Centers Program of the National Science Foundation (NSF) under Award EEC-9986821, by an ARO MURI on Demining under Grant DAAG55-97-1-0013, and by the NSF under Award 0208548

    INVESTIGATIONS OF DOPED L10 FEPT FILMS FOR HEAT ASSISTED MAGNETIC RECORDING (HAMR)

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    Ph.DDOCTOR OF PHILOSOPH

    Study on surface asperity flattening in cold quasi-static uniaxial planar compression by crystal plasticity finite element method

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    In order to study the surface asperity flattening in a quasi-static cold uniaxial planar compression, the experimental results of atomic force microscope and electron backscattered diffraction have been employed in a ratedependent crystal plasticity model to analyze this process. The simulation results show a good agreement with the experimental results: in this quasi-static deformation process, lubrication can hinder the surface asperity flattening process even under very low deformation rate. However, due to the limitation of the model and some parameters, the simulation results cannot predict all the properties in detail such as S orientation {123}and the maximum stress in sample compressed without lubrication. In addition, the experimental results show, with an increase in gauged reduction, the development of Taylor factor, and CSL boundaries show certain tendencies. Under the same gauged reduction, friction can increase the Taylor factor and Σ = 7

    Automobile components procurement using a DEA-TOPSIS-FMIP approach with all-unit quantity discount and fuzzy factors

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    Components procurement is a crucial process in supply chain management of the automobile industry. The problem is further complicated by imprecise information and discount policies provided by suppliers. This paper aims to develop a computational approach for assisting automobile components procurement with all-unit quantity discount policy and fuzzy factors, from potential suppliers offering different product portfolios. We propose a two-stage approach consisting of a DEA-TOPSIS (data envelopment analysis procedures followed with a technique for order preference by similarity to an ideal solution) approach for screening suppliers, and subsequentially a fuzzy mixed integer programming (FMIP) model with multiple objectives for optimizing order allocations. The DEA-TOPSIS approach integrates suppliers’ comparative performance and diversity performance into an overall index that improves the ranking of potential suppliers, while the FMIP model features a soft time-window in delivery punctuality and an all-unit quantity discount function in cost. By applying it in a case of automobile components procurement, we show that this two-stage approach effectively supports decision makers in yielding procurement plans for various components offered by many potential suppliers. This paper contributes to integrating multi-attribute decision analysis approach in the form of DEA crossevaluation with TOPSIS and FMIP model for supporting components procurement decisions. First published online 19 November 202

    New advances in clinical application of neostigmine: no longer focusing solely on increasing skeletal muscle strength

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    Neostigmine is a clinical cholinesterase inhibitor, that is, commonly used to enhance the function of the cholinergic neuromuscular junction. Recent studies have shown that neostigmine regulates the immune-inflammatory response through the cholinergic anti-inflammatory pathway, affecting perioperative neurocognitive function. This article reviews the relevant research evidence over the past 20 years, intending to provide new perspectives and strategies for the clinical application of neostigmine

    Picturing Electron Capture to the Continuum in the Transfer Ionization of Intermediate-Energy He²⁺ Collisions with Argon

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    Electron emission occurring in transfer ionization for He2+ collisions with argon has been investigated using cold target recoil ion momentum spectroscopy. The double differential cross sections for electron capture to the continuum of the projectile (cusp-shaped electrons) are presented for collision energies from 17.5 to 75 keV/u. For an energy of 30 keV/u, we find a maximum in the experimental ratio of the cusp-shaped electron yield to the total electron yield. This result is explained in terms of the velocity matching between the projectile ion and the electron initially bound to the target. One of the important issues for double electron transitions is the role of electron-electron correlation. If this correlation is weak, then the transfer-ionization process can be viewed as two separate sequential processes. If this correlation is strong, then the transfer-ionization process would happen simultaneously and not sequentially. Our experimental and theoretical results indicate that correlation is weak and that the first step is target ionization followed by charge capture
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