The Infona portal uses cookies, i.e. strings of text saved by a browser on the user's device. The portal can access those files and use them to remember the user's data, such as their chosen settings (screen view, interface language, etc.), or their login data. By using the Infona portal the user accepts automatic saving and using this information for portal operation purposes. More information on the subject can be found in the Privacy Policy and Terms of Service. By closing this window the user confirms that they have read the information on cookie usage, and they accept the privacy policy and the way cookies are used by the portal. You can change the cookie settings in your browser.
Data stream clustering is an active area of research in big data. It refers to clustering constantly arriving new data records and updating existing cluster patterns and outliers in light of the newly arriving data. Density-based algorithms for solving this problem have the promise for finding arbitrary shape clusters and detecting anomalies without prior knowledge of the number of clusters. In this...
Clustering is a classical unsupervised learning task, which is aimed to divide a data set into several groups with similar objects. Clustering problem has been studied for many years, and many excellent clustering algorithms have been proposed. In this paper, we propose a novel clustering method based on density, which is simple but effective. The primary idea of the proposed method is given as follows...
The density peak based clustering algorithm is a recently proposed clustering approach. It uses the local density of each data and the distance to the nearest neighbor with higher density to isolate and identify the cluster centers. After the cluster centers are identified, the other data are assigned labels equaling to those of their nearest neighbors with higher density. This algorithm is simple...
Data stream is relatively new and emerging domain in the current era of Internet advancement. Clustering data streams is equally important and difficult because of the numerous hurdles attached to it. A number of algorithms have been proposed to offer solutions for efficient clustering. Grid-based clustering approach was adopted few years ago to overcome the limitations of conventional partition-based...
Predictive maintenance task is of crucial role for any plant equipment supervision and scheduling of service activities. For this purpose it should be known what is current aging status of any equipment. Presented approach assumes that we know the nominal (starting) element curve and a damage one as well. It is also assumed that the aging course progresses according to some good practice aging Lorentz...
The traditional affine iterative closest point (ICP) algorithm is fast and accuracy for affine registration of point sets, but it performs worse when the point sets with large outliers. This paper introduces a novel algorithm based on correntropy for affine registration of point sets with outliers. First, a novel objective function is proposed by introducing the maximum correntropy criterion (MCC)...
Despite the wealth of information contained in the Web of Linked Data, the current limitations and entry barriers of the Semantic Web technologies hinder the users from taking advantage of these information resources. Linked Data visualization can alleviate this problem. In this paper, we adopt a proper Linked Data visualization model, design Linked Data visualization algorithms, and develop a lightweight,...
This paper proposes a new affine registration algorithm for 2D point matching. It is a two-step iterative registration algorithm by soft weight assignment based on bidirectional distance. At each iteration, the affine transformation is updated by two optimization steps, in which the model data and the test data are matched from each other respectively. By the optimization of registration at separate...
We explore the problem of characterizing fragments using Par-aView in situ with an explosion simulation. By running in situ we can see a much higher temporal view of the data as well as potentially compress the output to only those statistics about fragments we care about. However, the fragment finding must be able to scale as well as the simulation. In order to achieve the necessary scales, we borrow...
Present an approach which can quickly identity window features according to pre-setting parameters and ICP algorithm, and can rapidly reconstruct their 3D window models. The approach changes the 3D data to 2D by projection, so a high processing efficiency can be reached and can deal with huge quantity of point clouds in semi-automatic style. The experimental results demonstrate that our algorithm...
Nowadays, large bodies of data in different domains are collected and stored. An efficient extraction of useful knowledge from these data becomes a huge challenge. This leads to the need for developing distributed data mining techniques. However, only a few research concerns distributed clustering for analysing large, heterogeneous and distributed datasets. Besides, current distributed clustering...
Adaptive Neuro-Fuzzy Inference System (ANFIS) has become a popular tool in neuro-fuzzy modeling. However, since it includes many parameters needed to be set, its designing process is a complicated and time-intensive task for experimenters. To tackle this problem, in this paper we implement the Design of Experiment (DOE) technique to identify the significant parameters of ANFIS when it applies to the...
Because the current triangle mesh simplification algorithm base on edge collapse have the problem that it always miss the Geometric Features of models,we present a new method of edge collapse triangle mesh simplification.The new method based on the classical algorithm QEM,using Guassian curvature we define the concept of curvature factors of collapsing edge and embed it into the original Garland's...
Iterative Closest Point (ICP) is a classical algorithm for rigid point set registration. However, with the number of points in the set increasing, its computational efficiency usually suffers a reduction, which limits the practical applications of this algorithm. Based on Weber's Law in psychophysics, this paper proposes a fast ICP algorithm based on hierarchical and multi-resolution model for point...
Symbolic execution plays an important role in the area of software testing and program verification. However, there are several difficulties facing symbolic execution, one of which is how to abstract various data types in source codes. This paper addresses this problem by proposing a memory model that is based on the abstract symbol table. The abstract symbol table records names, abstract addresses...
A new spline method has been introduced. It is a generalization of the Ballpsilas cubic spline method and also serves as an affective alternate to the weighted Nu-splines. The generated spline curves have second order geometric continuity similar to those of weighted Nu-splines. In comparison with the existing techniques, the degree of the spline method is ideally three and the domain of the shape...
This paper presents a novel method of contour reconstruction from dexel data solving the shape anomalies for the complex geometry in virtual sculpting. Grouping and traversing processes are developed to find connectivity between dexels along every two adjacent rays. After traveling through all the rays on one slice, sub-boundaries are connected into full boundaries which are desired contours. The...
We have investigated a technique for recognising faces invariant of facial expressions. We apply multi-linear tensor algebra, which subsumes linear algebra, to analyse and recognise 3D face surfaces. This potent framework possesses a remarkable ability to deal with the shortcomings of principle component analysis in less constrained situations. A set of vector spaces can be used to represent the variation...
The virtual product data model in its different stages is an essential prerequisite for the virtual modeling of processes and their virtual simulation. Product design starts with conceptual design including the concepts for the future productpsilas shape and function - the gestalt. In this stage, the designers work on fuzzy product data interpreted in so-called scribbles and applied to perception...
This paper presents a new technique to generate triangular mesh surface parameterization and characterize 3-D surfaces by invariant spherical harmonic shape descriptors of objects with spherical topology. First, the surface is initially parameterized by defining a continuous one-to-one mapping from the surface of the object to the surface of a unit sphere. Then, the initial parameterization is optimized...
Set the date range to filter the displayed results. You can set a starting date, ending date or both. You can enter the dates manually or choose them from the calendar.