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Support slimming for single material based additive manufacturing

COMPUTER-AIDED DESIGN 2015年 65卷 1-10页

作者： Hu, Kailun Jin, Shuo Wang, Charlie C. L. Chinese Univ Hong Kong Dept Mech & Automat Engn Hong Kong Hong Kong Peoples R China

In layer-based additive manufacturing (AM), supporting structures need to be inserted to support the overhanging regions. The adding of supporting structures slows down the speed of fabrication and introduces artifacts onto the finished surface. We present an orientation-driven shape optimizer to slim down the supporting structures used in single material-based AM. The optimizer can be employed as a tool to help designers to optimize the original model to achieve a more self-supported shape, which can be used as a reference for their further design. The model to be optimized is first enclosed in a volumetric mesh, which is employed as the domain of computation. The optimizer is driven by the operations of reorientation taken on tetrahedra with 'facing-down' surface facets. We formulate the demand on minimizing shape variation as global rigidity energy. The local optimization problem for determining a minimal rotation is analyzed on the Gauss sphere, which leads to a closed-form solution. Moreover, we also extend our approach to create the functions of controlling the deformation and searching for optimal printing directions. (C) 2015 Elsevier Ltd. All rights reserved.

关键词： geometric algorithm Shape optimization Design tool Additive manufacturing

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geometric algorithms for parametric-margin ν-support vector machine

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NEUROCOMPUTING 2013年 99卷 197-205页

作者： Peng, Xinjun Xu, Dong Shanghai Normal Univ Dept Math Shanghai 200234 Peoples R China

The parametric-margin nu-support vector machine (par-nu-SVM) is a useful classifier in many cases, especially when the noise is heteroscedastic. In this paper, the geometric interpretation for the par-nu-SVM is described, which is equivalent to finding a couple of points in two disjoint mu-reduced convex hulls (mu-RCHs) by simultaneously minimizing the square distance and maximizing the square norm of their sum with a weight factor 1/(c nu) given by users. Motivated by the Gilbert-Schlesinger-Kozinec (GSK) and Mitchell-Dem'yanov-Malozemov (MDM) algorithms, two geometric algorithms, called the parametric mu-GSK (par-mu-GSK) and parametric mu-MDM (par-mu-MDM) algorithms, are introduced to solve the par-nu-SVM. Computational results on several synthetic as well as benchmark datasets demonstrate the significant performance of the proposed algorithms in terms of both kernel operations and classification accuracy. Crown Copyright (C) 2012 Published by Elsevier B.V. All rights reserved.

关键词： Support vector machine Parametric-margin Nearest point problem Reduced convex hull geometric algorithm

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Research on the faulty treatment of cascaded Hbridge inverter under neutral shift

Research on the faulty treatment of cascaded Hbridge inverte...

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2012 International Conference on Power Electronics Engineering and Computer Technology(PEECT 2012)

作者： Ren Lei Shouzhi Li Hao Wang Department of Electrical Engineering Xi'an University of Technology The Professor of Department of Electrical Engineering Xi'an University of Technology Xi'an jiaotong University

Neutral shift can effectively use the remaining normal unit to increase the output voltage value,but the calculation method of offset angle is complicated,and this method will bring more harmonic. This article proposed a kind of simple geometric algorithm and designed a user interface to calculate results more efficienttly and made optimization for harmonic cancellation to ensure that the output line voltage balance. The results of simulation validate the correctness of theoretical analysis.

关键词： multilevel of cascaded H-bridge inverter neutral offset geometric algorithm user interface Harmonic frequency

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A complete and improved mathematical framework of the geometric approach based on the Scaled convex hull (SCH) and its application to large medical data sets

A complete and improved mathematical framework of the geomet...

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International Conference on Mechatronics Engineering and Computing Technology (ICMECT)

作者： Guo, Haoyan Cheng, Yuanzhi Wang, Dazheng Xu, Jiacheng Harbin Inst Technol Sch Mech Elect Harbin 150001 Peoples R China Harbin Inst Technol Sch Comp Harbin 150001 Peoples R China Harbin Inst Technol Sch Mech Elect Harbin 150001 Peoples R China Harbin Inst Technol Sch Math Harbin 150001 Peoples R China

ISBN: (纸本)9783038351153

In this paper a complete and improved mathematical framework of the geometric approach based on the Scaled convex hull (SCH), which includes two parts, SCH-based geometric algorithms for SVM and a fast and novel geometric method for model selection in SCH-based SVM, is developed to solve SCH-based SVM classification of large data sets. On the basis of this framework, these geometric algorithms are more suitable for classification task of large data sets. Results of numerical experiments show that the proposed geometric algorithms can reduce kernel calculations and display nice performances on large medical data sets, such as computer assisted screening for lung cancer.

关键词： Kernel methods scaled convex hull (SCH) support vector machines (SVMs) geometric algorithm

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A geometric algorithm based on tetrahedral meshes to generate a dense polydisperse sphere packing

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GRANULAR MATTER 2009年第1期11卷 43-52页

作者： Jerier, Jean-Francois Imbault, Didier Donze, Frederic-Victor Doremus, Pierre Univ Grenoble 1 Lab Sols Solides Struct & Risques Inst Natl Polytech Grenoble Grenoble France

In the discrete element method, the packing generation of polydisperse spheres with a high packing density value is a major concern. Among the methods already developed, few algorithms can generate sphere packing with a high density value. The aim of this paper is to present a new geometric algorithm based on tetrahedral meshes to generate dense isotropic arrangements of non-overlapping spheres. The method consists of first filling in every tetrahedron with spheres in contact (i.e., hard-sphere clusters). Then, the algorithm increases the packing density value by detecting the large empty spaces and filling them with new spheres. This new geometric algorithm can also generate a complex shape structure.

关键词： Discrete element method Sphere packing geometric algorithm Polydisperse spheres

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Efficient Hausdorff Distance computation for freeform geometric models in close proximity

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COMPUTER-AIDED DESIGN 2013年第2期45卷 270-276页

作者： Kim, Yong-Joon Oh, Young-Taek Yoon, Seung-Hyun Kim, Myung-Soo Elber, Gershon Seoul Natl Univ Sch Comp Sci & Engn Seoul 151744 South Korea Samsung Adv Inst Technol Yongin 446712 Gyeonggi South Korea Dongguk Univ Dept Multimedia Engn Seoul 100715 South Korea Technion Israel Inst Technol Dept Comp Sci IL-32000 Haifa Israel

We present an interactive-speed algorithm for computing the Hausdorff Distance (HD) between two freeform geometric models represented with NURBS surfaces. The algorithm is based on an effective technique for matching a surface patch from one model to the corresponding nearby surface patch on the other model. To facilitate the matching procedure, we employ a bounding volume hierarchy (BVH) for freeform NURBS surfaces, which provides a hierarchy of Coons patches and bilinear surfaces approximating the NURBS surfaces (Kim et al., 2011 [1]). Comparing the local HD upper bound against a global HD lower bound, we can eliminate the majority of redundant surface patches from further consideration. The resulting algorithm and the associated data structures are considerably simpler than the previous BVH-based HD algorithms. As a result, we can compute the HD of two freeform geometric models efficiently and robustly even when the two models are in close proximity. We demonstrate the effectiveness of our approach using several experimental results. (C) 2012 Published by Elsevier Ltd

关键词： Hausdorff Distance NURBS surface Coons patch Bounding volume hierarchy (BVH) Hierarchical data structure geometric algorithm

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Gathering identical autonomous systems on a circle using stigmergy

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DISTRIBUTED COMPUTING 2012年第6期25卷 461-472页

作者： Kozlov, Dmitry N. Univ Bremen Dept Math D-28334 Bremen Germany

In this paper we provide a protocol solving the problem of gathering of identical autonomous systems (aka ants) on a circle. In our biologically inspired model the autonomous systems are unable to communicate directly, instead they employ the mechanism of pheromone marking. The gathering on a circle is not always solvable, however our protocol will terminate in finite time if ants are in a general initial position. Since the gathering problem on a line is unsolvable for obvious reasons for any non-degenerate initial position, this implies that if the ants are in generic initial position they will be able to decide in finite time whether they are on a line or on a circle. We give asymptotic bounds for the time our protocol needs to terminate, and show that for fixed number of ants, the termination time of any protocol can be arbitrarily long. Finally, our protocol may be adopted to the case of asynchronous drop-downs and starting times of the autonomous systems.

关键词： Distributed algorithm Protocol Gathering problem Swarm intelligence Pheromone communication geometric algorithm Ant algorithm

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geometric algorithm for efficient coincident detection of gravitational waves

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Physical Review D 2008年第6期78卷 062002-062002页

作者： C. A. K. Robinson B. S. Sathyaprakash Anand S. Sengupta School of Physics and Astronomy Cardiff University 5 The Parade Cardiff United Kingdom CF24 3AA LIGO Laboratory California Institute of Technology Pasadena California 91125 USA

Data from a network of gravitational-wave detectors can be analyzed in coincidence to increase detection confidence and reduce nonstationarity of the background. We propose and explore a geometric algorithm to combine the data from a network of detectors. The algorithm makes optimal use of the variances and covariances that exist among the different parameters of a signal in a coincident detection of events. The new algorithm essentially associates with each trigger ellipsoidal regions in parameter space defined by the covariance matrix. Triggers from different detectors are deemed to be in coincidence if their ellipsoids have a nonzero overlap. Compared to an algorithm that uses uncorrelated windows separately for each of the signal parameters, the new algorithm greatly reduces the background rate thereby increasing detection efficiency at a given false alarm rate.

关键词： .false New algorithm overlap parameter space ellipsoids covariances detection of gravitational Gravitational-Wave Coherent Analysis Coincidence Analysis geometric algorithm efficient coincident background rate

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The robust and efficient adaptive normal direction support vector regression

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EXPERT SYSTEMS WITH APPLICATIONS 2011年第4期38卷 2998-3008页

作者： Peng, Xinjun Wang, Yifei Shanghai Normal Univ Dept Math Shanghai 200234 Peoples R China Shanghai Univ Sci Comp Key Lab Shanghai 200234 Peoples R China Shanghai Univ Dept Math Shanghai 200444 Peoples R China

The recently proposed reduced convex hull support vector regression (RH-SVR) treats support vector regression (SVR) as a classification problem in the dual feature space by introducing an epsilon-tube. In this paper, an efficient and robust adaptive normal direction support vector regression (AND-SVR) is developed by combining the geometric algorithm for support vector machine (SVM) classification. AND-SVR finds a better shift direction for training samples based on the normal direction of output function in the feature space compared with RH-SVR. Numerical examples on several artificial and UCI benchmark datasets with comparisons show that the proposed AND-SVR derives good generalization performance. Crown Copyright (C) 2010 Published by Elsevier Ltd. All rights reserved.

关键词： Support vector regression geometric algorithm Normal direction Epsilon-tube Sample shift

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A v-twin support vector machine (v-TSVM) classifier and its geometric algorithms

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INFORMATION SCIENCES 2010年第20期180卷 3863-3875页

作者： Peng Xinjun Shanghai Normal Univ Dept Math Shanghai 200234 Peoples R China Sci Comp Key Lab Shanghai Univ Shanghai 200234 Peoples R China

In this paper, a v-twin support vector machine (v-TSVM) is presented, improving upon the recently proposed twin support vector machine (TSVM). This v-TSVM introduces a pair of parameters (v) to control the bounds of the fractions of the support vectors and the error margins. The theoretical analysis shows that this v-TSVM can be interpreted as a pair of minimum generalized Mahalanobis-norm problems on two reduced convex hulls (RCHs). Based on the well-known Gilbert's algorithm, a geometric algorithm for TSVM (GA-TSVM) and its probabilistic speed-up version, named PGA-TSVM, are presented. Computational results on several synthetic as well as benchmark datasets demonstrate the significant advantages of the proposed algorithms in terms of both computation complexity and classification accuracy. Crown Copyright (C) 2010 Published by Elsevier Inc. All rights reserved.

关键词： Pattern recognition Twin support vector machine geometric interpretation geometric algorithm Probabilistic speed-up strategy

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