Planar shape matching based on binary tree shape representation

In this paper we suggest a new way of representing planar two-dimensional shapes and a shape matching method which utilizes the new representation. Through merging of the neighboring boundary runs, a shape can be partitioned into a set of triangles. These triangles are inherently connected according to a binary tree structure. Here we use the binary tree with the triangles as its nodes to represent the shape. This representation is found to be insensitive to shape translation, rotation, scaling and skewing changes due to viewer's location changes (or the object's pose changes). Furthermore, the representation is of multiresolution.

In shape matching we compare the two trees representing two given shapes node by node according to the breadth-first tree traversing sequence. The comparison is done from top of the tree and moving downward, which means that we first compare the lower resolution approximations of the two shapes. If the two approximations are different, the comparison stops. Otherwise, it goes on and compares the finer details of the two shapes. Only when the two shapes are very similar, will the two corresponding trees be compared entirely. Thus, the matching algorithm utilizes the multiresolution characteristic of the tree representation and appears to be very efficient.     

An analytical representation of conformal mapping for genus-zero implicit surfaces and its application to surface shape similarity assessment

This paper develops an analytical representation of conformal mapping for genus-zero implicit surfaces based on algebraic polynomial functions, and its application to surface shape similarity assessment. Generally, the conformal mapping often works as a tool of planar or spherical parameterization for triangle mesh surfaces. It is further exploited for implicit surface matching in this study. The method begins with discretizing one implicit surface by triangle mesh, where a discrete harmonic energy model related to both the mesh and the other implicit surface is established based on a polynomial-function mapping. Then both the zero-center constraint and the landmark constraints are added to the model to ensure the uniqueness of mapping result with the Möbius transformation. By searching optimal polynomial coefficients with the Lagrange–Newton method, the analytical representation of conformal mapping is obtained, which reveals all global and continuous one-to-one correspondent point pairs between two implicit surfaces. Finally, a shape similarity assessment index for (two) implicit surfaces is proposed through calculating the differences of all the shape index values among those corresponding points. The proposed analytical representation method of conformal mapping and the shape assessment index are both verified by the simulation cases for the closed genus-zero implicit surfaces. Experimental results show that the method is effective for genus-zero implicit surfaces, which will offer a new way for object retrieval and manufactured surface inspection.     

Spectra of shape contexts: An application to symbol recognition

The pixel-level constraint (PLC) histograms are known for robustness and invariance in symbol recognition but limited in O(N³) complexity. This paper proves that matching two PLC histograms can approximately be solved as matching the power spectra of the corresponding shape contexts. As a result, spectra of shape contexts (SSC) inherit robustness and invariance from PLC while the computational cost can be reduced. Moreover, a maximum clique based scheme is proposed for outlier rejection. The theoretical and experimental validation justifies that SSC possesses the desired properties for symbol recognition, that is, robustness, invariance, and efficiency. It outperforms PLC in terms of robustness and time efficiency, and shape context in terms of rotation invariance.     

A genetic algorithm based heuristic to the multi-period fixed charge distribution problem

This paper proposes a genetic algorithm (GA) based heuristic to the multi-period fixed charge distribution problem associated with backorder and inventories. The objective is to determine the size of the shipments, backorder and inventories at each period, so that, the total cost incurred during the entire period towards transportation, backorder and inventories is minimum. The model is formulated as pure integer nonlinear programming and 0-1 mixed integer linear programming problems, and proposes a GA based heuristic to provide solution to the above problem. The proposed GA based heuristic is evaluated by comparing their solutions with lower bound, LINGO solver and approximate solutions. The comparisons reveal that the GA generates better solutions than the approximate solutions, and is capable of providing solutions equal to LINGO solutions and closer to the lower bound value of the problems.     

压电传感器现场监测石英表面电荷分布

理论上解析了石英表面电荷分布情况,利用双液隔电极压电传感器(ESPS)与溶液直接接触的特点,对阴、阳离子表面活性剂的吸附情况进行了现场监测,间接地证明了理论分析,这对传感器本身以及石英表面改性处理有重要参考价值。     

Fuzzy-Pareto-dominance driven possibilistic model based planning of electrical distribution systems using multi-objective particle swarm optimization

This paper presents a fuzzy-Pareto dominance driven possibilistic model based planning of electrical distribution systems using multi-objective particle swarm optimization (MOPSO). This multi-objective planning model captures the possibilistic variations of the system loads using a fuzzy triangular number. The MOPSO based on the Pareto-optimality principle is used to obtain a set of non-dominated solutions representing different network structures under uncertainties in load demands and these non-dominated solutions are stored in an elite archive of limited size. Normally, choosing the candidate non-dominated solutions to be retained in the elite archive while maintaining the quality of the Pareto-approximation front as well as maintaining the diversity of solutions on this front is very much computationally demanding. In this paper, the principles of fuzzy Pareto-dominance are used to find out and rank the non-dominated solutions on the Pareto-approximation front. This ranking in turn is used to maintain the elite archive of limited size by discarding the lower ranked solutions. The two planning objectives are: (i) minimization of total installation and operational cost and (ii) minimization of risk factor. The risk factor is defined as a function of an index called contingency-load-loss index (CLLI), which captures the effect of load loss under contingencies, and the degree of network constraint violations. The minimization of the CLLI improves network reliability. The network variables that are optimized are: (i) number of feeders and their routes, and (ii) number and locations of sectionalizing switches. An MOPSO (developed by the authors), based on a novel technique for the selection and assignment of leaders/guides for efficient search of non-dominated solutions, is used as the optimization tool. The proposed planning approach is validated on a typical 100-node distribution system. Performance comparisons between the planning approaches with the possibilistic and deterministic load models are provided highlighting the relative merits and demerits. It is also verified that the proposed solution ranking scheme based on the fuzzy-Pareto dominance is very much better from both quality and computational burden point of view in comparison with the other well-known archive truncation techniques based on clustering and solution density measurement etc.     

GFREG: a computer program for maximum likelihood regression using the Generalized F distribution

A FORTRAN program is described for maximum likelihood estimation within the Generalized F family of distributions. It can be used to estimate regression parameters in a log-linear model for censored survival times with covariates, for which the error distribution may have a great variety of shapes, including most distributions of current use in biostatistics. The optimization is performed by an algorithm based on the generalized reduced gradient method. A stepwise variable search algorithm for covariate selection is included in the program. Output features include: model selection criteria, standard errors of parameter estimates, quantile and survival rates with their standard errors, residuals and several plots. An example based on data from Princess Margaret Hospital, Toronto, is discussed to illustrate the program's capabilities.     

Near net shape technology: An innovative opportunity for the automotive industry

Near net shape is an innovative concept in industrial manufacturing. The main focus of this technology is to produce parts, as near as possible close to their final shape and contour, implementing non-chipping techniques. In this way the manufacturing gives the possibility of a finished product with minimal cutting. Near net shape technology also generates the opportunity to reduce the productive steps for a given process chain. Both the above-mentioned characteristics have the same main goal: achieving cost reduction. This fundamental target incorporates several other advantages, such as: reduction of process variability, quality improvement in the finished product and the possibility to focus the design of mechanical devices on functional features, eliminating technical constraints imposed by the process. Based on these factors and in cooperation with the IWU Fraunhofer Institut of Chemnitz, the authors conducted a research regarding the manufacturing of an innovative automotive gear shaft, produced by applying near net shape processes. The goal of this study is to evaluate whether it is more convenient to produce the part implementing a traditional production chain or an innovative one, based on near net shape techniques. The first step was to locate the available technologies in order to produce the selected part. There are two alternatives: a traditional cutting manufacture, performed with a numerical control turning machine and a near-net-shape technique, characterized only by deformation processes. The next step was to detect the main differential costs between the two opportunities. Comparing technical data and information available in literature, the authors detected the main differential voices of cost: raw material, amortization, manpower and direct setup. In order to make the study more reliable, the authors assumed an actual industrial environment, featured by an annual demand of 400,000 pieces and a product lifetime cycle of 10 yr. The evaluation led to the conclusion that the innovative manufacturing chain is more convenient.     

基于构件形状分布和配准位置的BIM 模型对比方法

建筑全生命周期的各个阶段中会出现各种不同版本的BIM 模型,其间的差异可以 对建筑的施工和运维阶段提供决策支持。大部分BIM 模型对比都是基于目视检查、手动计数和 选择性属性检查。尽管目前有学者和相关机构研究了一些自动比较BIM 模型的方法,但大多依 赖于模型中构件的ID,而且比较的结果无法直观地体现到具体构件、具体属性上。针对以上问 题,提出了一种基于形状分布和位置配准的BIM 模型对比方法,即提取构件特征进行构件匹配, 从构件级进行BIM 模型对比。首先根据构件的几何信息构造构件的形状分布,计算类型相近构 件的形状分布之间的相似度;再配准构件的位置,计算位置之间的相似度;然后结合2 个相似 度进行构件匹配,比较匹配构件之间的差异;最后得出模型间的差异,并利用WebGL 进行可 视化展示。该方法忽略了构件ID 变化对模型对比的影响,并且能得出模型构件级别的差异。     

人脸特征潜在分布规律的人脸注释算法

提出了一种简单有效的人脸注释改进算法。该算法将二值边缘图像的梯度映射和人的面部特征的潜在分布规律相结合。首先应用二值边缘图像的按水平方向以及按垂直方向的梯度的映射,快速确定人脸位置以及人眼的粗略位置;然后对人眼的位置使用逐步逼近法进行进一步的精确定位,再利用图像垂直方向的梯度映射确定嘴的位置;结合人眼和嘴的位置,以及人脸面部特征的潜在分布规律,确定鼻子的位置。     

An effective estimation of distribution algorithm for the multi-mode resource-constrained project scheduling problem

In this paper, an estimation of distribution algorithm (EDA) is proposed to solve the multi-mode resource-constrained project scheduling problem (MRCPSP). In the EDA, the individuals are encoded based on the activity-mode list (AML) and decoded by the multi-mode serial schedule generation scheme (MSSGS), and a novel probability model and an updating mechanism are proposed for well sampling the promising searching region. To further improve the searching quality, a multi-mode forward backward iteration (MFBI) and a multi-mode permutation based local search method (MPBLS) are proposed and incorporated into the EDA based search framework to enhance the exploitation ability. Based on the design-of-experiment (DOE) test, suitable parameter combinations are determined and some guidelines are provided to set the parameters. Simulation results based on a set of benchmarks and comparisons with some existing algorithms demonstrate the effectiveness of the proposed EDA.     

Image thresholding based on the EM algorithm and the generalized Gaussian distribution

In this paper, a novel parametric and global image histogram thresholding method is presented. It is based on the estimation of the statistical parameters of “object” and “background” classes by the expectation-maximization (EM) algorithm, under the assumption that these two classes follow a generalized Gaussian (GG) distribution. The adoption of such a statistical model as an alternative to the more common Gaussian model is motivated by its attractive capability to approximate a broad variety of statistical behaviors with a small number of parameters. Since the quality of the solution provided by the iterative EM algorithm is strongly affected by initial conditions (which, if inappropriately set, may lead to unreliable estimation), a robust initialization strategy based on genetic algorithms (GAs) is proposed. Experimental results obtained on simulated and real images confirm the effectiveness of the proposed method.     

Fitting the generalized Pareto distribution to data using maximum goodness-of-fit estimators

Some of the most powerful techniques currently available to test the goodness of fit of a hypothesized continuous cumulative distribution function (CDF) use statistics based on the empirical distribution function (EDF), such as those of Kolmogorov, Cramer-von Mises and Anderson-Darling, among others. The use of EDF statistics was analyzed for estimation purposes. In this approach, maximum goodness-of-fit estimators (also called minimum distance estimators) of the parameters of the CDF can be obtained by minimizing any of the EDF statistics with respect to the unknown parameters. The results showed that there is no unique EDF statistic that can be considered most efficient for all situations. Consequently, the possibility of defining new EDF statistics is entertained; in particular, an Anderson-Darling statistic of degree two and one-sided Anderson-Darling statistics of degree one and two appear to be notable in some situations. The procedure is shown to be able to deal successfully with the estimation of the parameters of homogeneous and heterogeneous generalized Pareto distributions, even when maximum likelihood and other estimation methods fail.     

Vision implants:An electrical device will bring light to the blind

Cochlear implant has been successfully applied in clinic. Recent research indicates vision implants may be the potential way to restore sight for the blind. Here, principle and common structure of vision implants are introduced. Main vision approaches of retinal, optic nerve, and cortical prosthesis are reviewed. In our progress, electrical response at visual cortex is recorded, when penetrating electrodes stimulate rabbit optic nerve, vision implants based on optic nerve stimulator chip （ONSC） and Chipcon radio frequency （RF） chip are under developing. Despite several obstacles to overcome, promising results in animal and human experiments give scientists confidence that artificial vision implants will bring light to the blind in the near future.     

Modified non-Gaussian multivariate statistical process monitoring based on the Gaussian distribution transformation

Independent component analysis (ICA) has been applied for non-Gaussian multivariate statistical process monitoring (MSPM) for several years. As the independent components do not satisfy the multivariate Gaussian distribution, a missed alarm occurs when monitoring with traditional statistics. In this paper, we propose a Gaussian distribution transformation (GDT)-based monitoring method. Independent components are first transformed into approximate Gaussian distributions through the proposed nonlinear mapping. Then, we propose new statistics and their control limits to reduce missed alarms. The proposed method is particularly suitable for slight magnitude fault and early-stage fault detection. The ratio part of the area above the curve (RPAAC) is developed to evaluate the performance in fault detection. The experimental results from a synthetic example show the effectiveness of our proposed method. We also apply our method to monitor an electrical fused magnesia furnace (EFMF), and eruption and furnace wall melt faults can be detected in time.     

A comparative study on the identification of the dynamical model of multi-mass electrical drives using wavelet transforms

This paper deals with dynamical modelling and modal identification of a special class of electromechanical systems: the multi-mass electrical drives. The aim of the work is to investigate the usefulness and the performance of the continuous wavelet transform (CWT) for the estimation of modal parameters, such as damping ratios and natural frequencies of these electromechanical systems. For this investigation, two models of elastic drive systems are considered: the two-mass and the three-mass models. The modal analysis identification using CWT is compared to the Hilbert–Huang transform technique and evaluated in terms of accuracy and ability to estimate modal parameters with different inputs, aptitude to distinguish several modes especially in the case of closely spaced modes and resistance to noisy conditions. In view of the results of the study, the advantages and shortcomings of each technique are presented and discussed.