Feedback decoupling-controller design of 3-D systems in state space

This paper solves the input-output decoupling problem of three-dimensional (3-D) systems formulated in state-space representation. The control policy adopted is of the static state feedback type u=Kx+Nw where K, N are appropriate matrices to be determined, x is the system state vector, and w is the new input vector assumed equidimensional to the actual input vector u. The procedure derived determines K and N such that the resulting closed-loop system has a diagonal and nonsingular transfer-function matrix. The case, where only partial input-output decoupling is possible, is also considered, and the corresponding state-feedback matrices K and N are determined. The results are illustrated by simple numerical examples. The required 3-D generalization of the well known Cayley-Hamilton theorem is provided.     

Theories and algorithms for 3-D root canal model construction

This paper presents theories and algorithms for 3-D root canal model construction from 2-D X-ray images in a clinically practical way: (1) the geometrical rectification algorithm for correcting distorted 2-D X-ray images, (2) the transformation algorithms from 2-D X-ray image coordinate system to unified 3-D reference coordinate system, (3) the merging algorithms and theory for obtaining spatial root canal centerline by intersecting two surfaces with assumed parallel projection, and (4) the elliptical theory for exploring the root canal cross-sectional geometry. Using those theories and algorithms, three 3-D computer models constructed from teeth samples are presented to show the feasibility. The internal geometrical structure provided by 3-D computer graphics enables the clinician and the patient to comprehend root canal morphology efficiently, and the destructive access preparation before a clinician's inspection may be avoided during clinic practice.     

Plan-based boundary extraction and 3-D reconstruction for orthogonal 2-D echocardiography

This paper describes an automatic boundary extraction method from 2-D echocardiograms and 3-D reconstruction based on the extracted boundary lines. We use an orthogonal 2-D echocardiography which has two probes with different frequencies and can take two sectional cardiac ultrasound images simultaneously. When we extract the boundary lines, we use plans to reduce the processing time and to interpolate the boundary of no echo area.     

An analytic mapping of 3-D space to facilitate physical analysis

A method is presented for the solution of Laplace's equation in three dimensions through the use of a combination of polynomial and eigenfunction solutions. Results are presented comparing the method with an exact solution. Excellent agreement is obtained for economical solution representations. The aproximate analytic solution is supplemented by a correction term to ensure that the boundary conditions for the problem are satified exactly. In this form, the method is used to present calculations for the mapping of a hexahedral space to the unit cube.     

Perceptual grouping of line features in 3-D space: a model-based framework

In this paper, we propose a novel model-based perceptual grouping algorithm for the line features of 3-D polyhedral objects. Given a 3-D polyhedral model, perceptual grouping is performed to extract a set of 3-D line segments which are geometrically consistent with the 3-D model. Unlike the conventional approaches, grouping is done in 3-D space in a model-based framework. In our unique approach, a decision tree classifier is employed for encoding and retrieving the geometric information of the 3-D model. A Gestalt graph is constructed by classifying input instances into proper Gestalt relations using the decision tree. The Gestalt graph is then decomposed into a few subgraphs, yielding appropriate groups of features. As an application, we suggest a 3-D object recognition system which can be accomplished by selecting a best-matched group. In order to evaluate the performance of the proposed algorithm, experiments are carried out on both synthetic and real scenes.     

On the feature extraction in discrete space

In many pattern recognition applications, feature space expansion is a key step for improving the performance of the classifier. In this paper, we (i) expand the discrete feature space by generating all orderings of values of k discrete attributes exhaustively, (ii) modify the well-known decision tree and rule induction classifiers (ID3, Quilan, 1986 [1] and Ripper, Cohen, 1995 [2]) using these orderings as the new attributes. Our simulation results on 15 datasets from UCI repository [3] show that the novel classifiers perform better than the proper ones in terms of error rate and complexity.     

A Galerkin Method for the Simulation of the Transient 2-D/2-D and 3-D/3-D Linear Boltzmann Equation

Many production steps used in the manufacturing of integrated circuits involve the deposition of material from the gas phase onto wafers. Models for these processes should account for gaseous transport in a range of flow regimes, from continuum flow to free molecular or Knudsen flow, and for chemical reactions at the wafer surface. We develop a kinetic transport and reaction model whose mathematical representation is a system of transient linear Boltzmann equations. In addition to time, a deterministic numerical solution of this system of kinetic equations requires the discretization of both position and velocity spaces, each two-dimensional for 2-D/2-D or each three-dimensional for 3-D/3-D simulations. Discretizing the velocity space by a spectral Galerkin method approximates each Boltzmann equation by a system of transient linear hyperbolic conservation laws. The classical choice of basis functions based on Hermite polynomials leads to dense coefficient matrices in this system. We use a collocation basis instead that directly yields diagonal coefficient matrices, allowing for more convenient simulations in higher dimensions. The systems of conservation laws are solved using the discontinuous Galerkin finite element method. First, we simulate chemical vapor deposition in both two and three dimensions in typical micron scale features as application example. Second, stability and convergence of the numerical method are demonstrated numerically in two and three dimensions. Third, we present parallel performance results which indicate that the implementation of the method possesses very good scalability on a distributed-memory cluster with a high-performance Myrinet interconnect.     

Computer-based derivation and transformations of spatial motion equations of a large space structure in the course of its assembly

A mechanic system of the form of a large space structure being assembled in orbit is considered. The problem of on-line computer-based derivation of the current mathematical model of the spatial motion of a mechanic system with its structure changing when extra bodies or constraints are either added or removed is studied. The problem is solved using Lagrange equations of second kind. In the problem statement, it is required that the computing system linearize the obtained nonlinear Lagrange mathematical model, transform it by reducing it to the principal (normal) coordinates and then pass to more constructive, in terms of synthesizing control laws, modally physical representation. The mathematical technique for solving the listed problems is given. A number of necessary propositions are proved. The examples are given to illustrate that the proposed methods are constructive and can be implemented sufficiently simply in Maple.     

Real-time rendering of 3-D scenes using subband 3-D warping

Three techniques for increasing the frame rates of three-dimensional warping, namely subsampling, wavelet baseband, and wavelet transform (including high frequencies) are presented. Additionally noninteger and integer splats are applied for the techniques. The Haar baseband and subsampling methods using integer splats both produce excellent frame rates and perceptual quality of warped images.     

基于三维拼接技术的三维测量系统的开发

提出一种利用参考底座对三维数据进行剪裁拼接的新方法并应用于360°三维全场测量.通过对测量算法、控制软件、云台以及计算机串口通信的系列研究,开发出相应的程序和控制硬件,最终建立了采用面结构光照明的、自动化的360°三维形貌测量系统.该系统给工业三维全场测量提供了一个可操作平台,精确度也达到了实用要求.     

Perception of 3-D surfaces from 2-D contours

Inference of 3-D shape from 2-D contours in a single image is an important problem in machine vision. The authors survey classes of techniques proposed in the past and provide a critical analysis. They show that two kinds of symmetries in figures, which are known as parallel and skew symmetries, give significant information about surface shape for a variety of objects. They derive the constraints imposed by these symmetries and show how to use them to infer 3-D shape. They also discuss the zero Gaussian curvature (ZGC) surfaces in depth and show results on the recovery of surface orientation for various ZGC surfaces     

神经功能束边缘提取与三维重建软件整合研究

针对神经切片显微图像的功能束边缘不连续的特征,采用基于阈值的图像分割法,对功能束边缘的获取进行了研究.为更好解决神经修复问题,整合神经显微图像的配准、边缘提取、功能束识别与重建软件等关键技术,设计相应的接口,基于VC++平台开发神经功能束显微图像的三维重建软件.通过系统运行实例,不仅验证了此软件的可行性,而且表明通过整合于此系统,确实实现了神经功能束边缘的自动获取,使得重建流程更加智能,为今后对神经的智能重建以还原其真实模型打下了坚实的基础.     

A near optimal isosurface extraction algorithm using the span space

Presents the “Near Optimal IsoSurface Extraction” (NOISE) algorithm for rapidly extracting isosurfaces from structured and unstructured grids. Using the span space, a new representation of the underlying domain, we develop an isosurface extraction algorithm with a worst case complexity of o(√n+k) for the search phase, where n is the size of the data set and k is the number of cells intersected by the isosurface. The memory requirement is kept at O(n) while the preprocessing step is O(n log n). We utilize the span space representation as a tool for comparing isosurface extraction methods on structured and unstructured grids. We also present a fast triangulation scheme for generating and displaying unstructured tetrahedral grids     

Self-assembly of 3-D structures using 2-D folding tiles

Natural Computing - Self-assembly is a process which is ubiquitous in natural, especially biological systems. It occurs when groups of relatively simple components spontaneously combine to form...     

On the location error of curved edges in low-pass filtered 2-D and3-D images

The authors study the location error of curved edges in two- and three-dimensional images after analog and digital low-pass filtering. The zero crossing of a second derivative filter is a well-known edge localization criterion. The second derivative in gradient direction (SDGD) produces a predictable bias in edge location towards the centers of curvature while the linear Laplace filter produces a shift in the opposite direction. Their sum called PLUS (PLUS=Laplace+SDGD) leads to an edge detector that finds curved edges one order more accurately than its constituents. This argument holds irrespective of the dimension. The influence of commonly used low-pass filters (such as the PSF originating from diffraction limited optics using incoherent light (2-D), the Gaussian filter with variable cutoff point (D-D), and the isotropic uniform filter (D-D)) is studied     

Minimal Simple Pairs in the 3-D Cubic Grid

Preserving topological properties of objects during thinning procedures is an important issue in the field of image analysis. This paper constitutes an introduction to the study of non-trivial simple sets in the framework of cubical 3-D complexes. A simple set has the property that the homotopy type of the object in which it lies is not changed when the set is removed. The main contribution of this paper is a characterisation of the non-trivial simple sets composed of exactly two voxels, such sets being called minimal simple pairs.

Bifurcation phenomenon in the wake of a 3-D cylinder

Numerical simulations are carried out for a long slender rigid circular cylinder in a cross flow to investigate the effect of end-plates on the bifurcation phenomenon in the near wake. A multiple relaxation time lattice Boltzmann method (MRT-LBM) is used for the solution of three-dimensional unsteady flow. At the Reynolds number of 200, there exists shedding frequency bifurcation along the span which is resulted from the shedding phase oscillation.     

Computer-based data entry for nurses in the ICU

Efforts are being made to improve the efficiency and quality of care in intensive care units (ICUs) at Latter Day Saints Hospital. The ICUs have been computerized, and the collection, storage, and presentation of patients' data have been improved. Nurses use computers for entering clinical data and plans for nursing care, and the effects of these changes on the work patterns of nurses in the ICU have been evaluated. Contrary to our expectation, our studies showed a decrease in the proportion of time that nurses spent in direct patient care (from 49.1% to 43.2%) and an increase in the proportion they spent entering clinical data (from 18.2% to 24.2%) after computerization. These changes, however, were attributed to a decrease in the severity of patients' illnesses, rather than the availability of the computer. There was no measurable difference in the proportion of time spent at other nursing activities.     

Evidence-based recognition of 3-D objects

An evidence-based recognition technique is defined that identifies 3-D objects by looking for their notable features. This technique makes use of an evidence rule base, which is a set of salient or evidence conditions with corresponding evidence weights for various objects in the database. A measure of similarity between the set of observed features and the set of evidence conditions for a given object in the database is used to determine the identity of an object in the scene or reject the object(s) in the scene as unknown. This procedure has polynomial time complexity and correctly identifies a variety of objects in both synthetic and real range images. A technique for automatically deriving the evidence rule base from training views of objects is shown to generate evidence conditions that successfully identify new views of those objects