Sphericity Evaluation Based on Minimum Circumscribed Sphere Method

The search of sphericity evaluation is a time-consuming work. The minimum circumscribed sphere (MCS) is suitable for the sphere with the maximum material condition. An algorithm of sphericity evaluation based on the MCS is introduced. The MCS of a measured data point set is determined by a small number of critical data points according to geometric criteria. The vertices of the convex hull are the candidates of these critical data points. Two theorems are developed to solve the sphericity evaluation problems. The validated results show that the proposed strategy offers an effective way to identify the critical data points at the early stage of computation and gives an efficient approach to solve the sphericity problems.

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The Research of Data Points Quality Assessment Method in Reverse Engineering

Key Engineering Materials ◽

10.4028/www.scientific.net/kem.419-420.445 ◽

2009 ◽

Vol 419-420 ◽

pp. 445-448 ◽

Cited By ~ 2

Author(s):

Jun Ting Cheng ◽

Wei Ling Zhao ◽

Can Zhao ◽

Xue Dong Xie

Keyword(s):

Reverse Engineering ◽

Data Quality ◽

Quality Assessment ◽

Assessment Method ◽

Measured Data ◽

Quality Data ◽

Data Quality Assessment ◽

Quality Assessment Method ◽

Data Points ◽

Data Point

In the field of reverse engineering, data quality assessment is a very important work in the detection, the result of data quality assessment will directly or indirectly affect the detection and the following manufacturing process quality. Data quality assessment can be used in the camera calibration, the model and model reconstruction comparison, and so on. In this paper, on the basis of the existing method of calculating each point error, and multipurpose use of average and standard error and some other concepts of mathematical statistics, and then improve a novel and simple calculating error method. This method is applicable to many groups of one-to-one ideal data and the measured data comparison, and it can be more intuitive to reflect the error of overall data, as well as the error distribution, and it can be more efficient to determine the measured data is reasonable or not. In this paper, the data point quality which is collected in the reverse engineering is assessed, and it can see that the method which is proposed in this article has some advantages in the data point quality assessment field.

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An Efficient Approach of Convex Hull Triangulation Based on Monotonic Chain

Applied Mechanics and Materials ◽

10.4028/www.scientific.net/amm.263-266.1605 ◽

2012 ◽

Vol 263-266 ◽

pp. 1605-1608

Author(s):

Yu Ping Zhang ◽

Zhao Ri Deng ◽

Rui Qi Zhang

Keyword(s):

Convex Hull ◽

Convex Polygon ◽

Efficient Approach ◽

Point Set ◽

Delaunay Algorithm ◽

Better Than

The triangulation of convex hull has the characteristics of point-set and polygon triangulation. According to some relative definitions, this paper proposed a triangulation of convex hull based on a monotonic chain. This method is better than Delaunay algorithm and is more efficient than other convex polygon algorithms. It is a good algorithm.

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Accelerating Density Peak Clustering Algorithm

Symmetry ◽

10.3390/sym11070859 ◽

2019 ◽

Vol 11 (7) ◽

pp. 859 ◽

Cited By ~ 1

Author(s):

Lin

Keyword(s):

Clustering Algorithm ◽

Local Density ◽

Early Stage ◽

Separation Distance ◽

Density Peak ◽

Density Peaks ◽

Density Based Clustering ◽

Data Points ◽

Data Point ◽

Density Peak Clustering

The Density Peak Clustering (DPC) algorithm is a new density-based clustering method. It spends most of its execution time on calculating the local density and the separation distance for each data point in a dataset. The purpose of this study is to accelerate its computation. On average, the DPC algorithm scans half of the dataset to calculate the separation distance of each data point. We propose an approach to calculate the separation distance of a data point by scanning only the neighbors of the data point. Additionally, the purpose of the separation distance is to assist in choosing the density peaks, which are the data points with both high local density and high separation distance. We propose an approach to identify non-peak data points at an early stage to avoid calculating their separation distances. Our experimental results show that most of the data points in a dataset can benefit from the proposed approaches to accelerate the DPC algorithm.

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An Efficient Convex Hull Algorithm for Planar Point Set Based on Recursive Method

ACTA AUTOMATICA SINICA ◽

10.3724/sp.j.1004.2012.01375 ◽

2012 ◽

Vol 38 (8) ◽

pp. 1375 ◽

Cited By ~ 3

Author(s):

Bin LIU ◽

Tao WANG

Keyword(s):

Convex Hull ◽

Recursive Method ◽

Planar Point ◽

Point Set ◽

Convex Hull Algorithm

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An Efficient Improved Algorithm of Convex Hull

Applied Mechanics and Materials ◽

10.4028/www.scientific.net/amm.602-605.3104 ◽

2014 ◽

Vol 602-605 ◽

pp. 3104-3106

Author(s):

Shao Hua Liu ◽

Jia Hua Zhang

Keyword(s):

Convex Hull ◽

Line Segment ◽

Main Idea ◽

Discrete Point ◽

Directed Line ◽

Generation Algorithm ◽

Simple Program ◽

Point Set ◽

High Computational Efficiency ◽

Improved Algorithm

This paper introduced points and directed line segment relation judgment method, the characteristics of generation and Graham method using the original convex hull generation algorithm of convex hull discrete points of the convex hull, an improved algorithm for planar discrete point set is proposed. The main idea is to use quadrilateral to divide planar discrete point set into five blocks, and then by judgment in addition to the four district quadrilateral internally within the point is in a convex edge. The result shows that the method is relatively simple program, high computational efficiency.

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Upward continuation of scattered potential field data

Geophysics ◽

10.1190/1.1444549 ◽

1999 ◽

Vol 64 (2) ◽

pp. 443-451 ◽

Cited By ~ 10

Author(s):

Maurizio Fedi ◽

Antonio Rapolla ◽

Guido Russo

Keyword(s):

Linear Combination ◽

Computation Time ◽

Measured Data ◽

Potential Field Data ◽

Zero Level ◽

Local Character ◽

Upward Continuation ◽

Data Points ◽

The Stability ◽

Variable Topography

Numerous methods have been used for upward continuation, but most of them require data on a regular grid. Gridding can introduce errors that affect the continued data in an unpredictable way. To avoid this problem, we design a continuation operator used for the direct continuation of scattered data on a 3-D basis. In this approach a harmonic function, satisfying the constraints imposed by the measured data, is developed. The continuation is written in the form of a linear combination of the measured data, but it depends on the arbitrary choice of the topographic zero level. However, the coefficients of the linear combination depend only on the position of the data points. This allows the zero level to be estimated on the basis of the continuation of synthetic anomalies calculated between the starting and ending surface. An important feature of the method is its local character, which allows the reduction of computation time. Also, the stability of the method for noisy data is reasonably good. The method is applied to both synthetic and real cases. Synthetic examples show how gridding‐related errors may affect the continuation when an irregular distribution of data points and a variable topography are considered.

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QOS ANALYSIS OF WIRELESS NETWORKS BASED ON LOW MOBILITY PROTOCOL

March 2019 - IRO Journal on Sustainable Wireless Systems ◽

10.36548/jsws.2019.2.005 ◽

2019 ◽

Vol 01 (02) ◽

pp. 126-138

Author(s):

Bindhu V

Keyword(s):

Quality Of Service ◽

Performance Measure ◽

Point Problem ◽

Delivery Ratio ◽

Mobile Wireless ◽

Data Points ◽

Data Point ◽

Hidden Data ◽

Existing Structure

The decision on the possible trails to be taken by an information that is to be transmitted from a data point to its destined point enact to have more significance on the performance measure of the transmission. The mobile wireless network is also one such network whose quality of service are determined from the ways the trails are entrenched. This wireless adhoc network that is independent of the previously existing structure forms a topology that undergoes spontaneous changes with the closely existing data points or devices. This type of networks are well suited for many adverse situation and environment, but certain attributes of the wireless adhoc such as insubstantial bandwidth, more over head in paths , hidden data point problem, energy restraints, motility interfered routing make them visage difficulties in having a proper routing, empowering MANET to achieve lesser quality in the service provided. So this paper quality of service analysis for the MANET using high power low mobility protocol ensures a routing path entrenchment between highly energetic with diminished motility data points to improvise the quality of service. The QoS analysis is done based on the delay, throughput and the packet delivery ratio to measure its performance.

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Parameterization Method on B-Spline Curve

Mathematical Problems in Engineering ◽

10.1155/2012/640472 ◽

2012 ◽

Vol 2012 ◽

pp. 1-22 ◽

Cited By ~ 22

Author(s):

H. Haron ◽

A. Rehman ◽

D. I. S. Adi ◽

S. P. Lim ◽

T. Saba

Keyword(s):

Computer Model ◽

Basis Function ◽

Real Object ◽

Reconstruction Process ◽

B Spline ◽

Parameterization Method ◽

Spline Basis ◽

Data Points ◽

Data Point ◽

2D And 3D

The use of computer graphics in many areas allows a real object to be transformed into a three-dimensional computer model (3D) by developing tools to improve the visualization of two-dimensional (2D) and 3D data from series of data point. The tools involved the representation of 2D and 3D primitive entities and parameterization method using B-spline interpolation. However, there is no parameterization method which can handle all types of data points such as collinear data points and large distance of two consecutive data points. Therefore, this paper presents a new parameterization method that is able to solve those drawbacks by visualizing the 2D primitive entity of scanned data point of a real object and construct 3D computer model. The new method has improved a hybrid method by introducing exponential parameterization method in the beginning of the reconstruction process, followed by computing B-spline basis function to find maximum value of the function. The improvement includes solving a linear system of the B-spline basis function using numerical method. Improper selection of the parameterization method may lead to the singularity matrix of the system linear equations. The experimental result on different datasets show that the proposed method performs better in constructing the collinear and two consecutive data points compared to few parameterization methods.

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