AUTOMATIC SURFACE GENERATION WITH A VOXEL-BASED SKELETON DEFINING TOPOLOGICAL CONSTRAINTS

In this paper, an investigation of cutting strategy is presented for the optimization of machining parameters in the ultra-precision machining of polar microstructures, which are used for optical precision measurement. The critical machining parameters affecting the surface generation and surface quality in the machining of polar microstructures are studied. Hence, the critical ranges of machining parameters have been determined through a series of cutting simulations, as well as cutting experiments. First of all, the influence of field of view (FOV) is investigated. After that, theoretical modeling of polar microstructures is built to generate the simulated surface topography of polar microstructures. A feature point detection algorithm is built for image processing of polar microstructures. Hence, an experimental investigation of the influence of cutting tool geometry, depth of cut, and groove spacing of polar microstructures was conducted. There are transition points from which the patterns of surface generation of polar microstructures vary with the machining parameters. The optimization of machining parameters and determination of the optimized cutting strategy are undertaken in the ultra-precision machining of polar microstructures.

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ModularBoost: an efficient network inference algorithm based on module decomposition

BMC Bioinformatics ◽

10.1186/s12859-021-04074-y ◽

2021 ◽

Vol 22 (1) ◽

Author(s):

Xinyu Li ◽

Wei Zhang ◽

Jianming Zhang ◽

Guang Li

Keyword(s):

Network Inference ◽

Detection Methods ◽

Inference Problem ◽

Topological Constraints ◽

Inference Algorithms ◽

Module Detection ◽

Series Expression ◽

Gene Modules ◽

Inference Methods ◽

Complicated Task

Abstract Background Given expression data, gene regulatory network(GRN) inference approaches try to determine regulatory relations. However, current inference methods ignore the inherent topological characters of GRN to some extent, leading to structures that lack clear biological explanation. To increase the biophysical meanings of inferred networks, this study performed data-driven module detection before network inference. Gene modules were identified by decomposition-based methods. Results ICA-decomposition based module detection methods have been used to detect functional modules directly from transcriptomic data. Experiments about time-series expression, curated and scRNA-seq datasets suggested that the advantages of the proposed ModularBoost method over established methods, especially in the efficiency and accuracy. For scRNA-seq datasets, the ModularBoost method outperformed other candidate inference algorithms. Conclusions As a complicated task, GRN inference can be decomposed into several tasks of reduced complexity. Using identified gene modules as topological constraints, the initial inference problem can be accomplished by inferring intra-modular and inter-modular interactions respectively. Experimental outcomes suggest that the proposed ModularBoost method can improve the accuracy and efficiency of inference algorithms by introducing topological constraints.

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Modelling and analysis of micro-grinding surface generation of hard brittle material machined by micro abrasive tools with helical chip pocket

Journal of Materials Processing Technology ◽

10.1016/j.jmatprotec.2021.117242 ◽

2021 ◽

pp. 117242

Author(s):

Yao Sun ◽

Zhipeng Su ◽

Liya Jin ◽

Yadong Gong ◽

Dechun Ba ◽

...

Keyword(s):

Brittle Material ◽

Surface Generation ◽

Abrasive Tools

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Topological constraints in the reconnection of vortex braids

Physics of Fluids ◽

10.1063/5.0047033 ◽

2021 ◽

Vol 33 (5) ◽

pp. 056101

Author(s):

S. Candelaresi ◽

G. Hornig ◽

B. Podger ◽

D. I. Pontin

Keyword(s):

Topological Constraints

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Influence of Supporting Characteristics on Sphericity of Ceramic Balls in Rotated Dual-Plates Lapping Process

Advanced Materials Research ◽

10.4028/www.scientific.net/amr.69-70.69 ◽

2009 ◽

Vol 69-70 ◽

pp. 69-73 ◽

Cited By ~ 2

Author(s):

Bing Hai Lv ◽

Ju Long Yuan ◽

F. Cheng ◽

Fan Yang

Keyword(s):

Numerical Calculation ◽

Fourier Analysis ◽

Support System ◽

Spherical Surface ◽

Surface Generation ◽

Shape Error ◽

Lower Natural Frequency ◽

Sinusoidal Waveform ◽

Higher Spin ◽

Ball Surface

Ceramic balls have become an important component in advanced bearings, and the sphericity of balls is a key qualification focused in lapping process. An investigation on the effect of dynamic behavior of ball support system on the performance of ball lapping in rotated dual-plates lapping method is carried out. Sinusoidal waveform in terms of Fourier analysis is employed to express the shape error of the ball surface, and a dynamic model for support is setup. It is found with numerical calculation that the variation of lapping load lags behind the variation of the shape error for the damping of support. A lower natural frequency of the support system, higher spin speed of balls and a larger value of spin angle in RDP lapping are better to rectify the shape error of balls and reduce the lagged effect. It is concluded that dynamics of lapping system must be taken into consideration in order to understand comprehensively the spherical surface generation mechanism.

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