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.
Due to the complex species, the changing dimensions and 2D nesting structure of mathematical formula symbols, the accuracy of symbol segmentation still cannot meet the actual needs. Projection is only suitable for simple mathematical formula without subscript and hierarchy. This paper presents a kind of improved algorithm based on the connected domain for symbol segmentation of mathematical formula...
With the rapid development of database and web technology, the way data organized and presented is becoming increasingly complicated while data sources are also intermingled with inaccurate information. Therefore, studies in truth discovery becomes overwhelmingly significant for it is critical for netizens to identify sources of high quality as well as to select the most accurate information from...
A visibility-culling-based geometric rendering algorithm is proposed in this paper so as to visualize large-scale particle data efficiently. In the algorithm, the particles are culled based on their visibility at two granularities. All data patches beyond the OpenGL view frustum are firstly thrown away as a coarse culling. And then, the remaining particles will be judged their visibility based on...
In today's world, there are number of transactions can be performed on social media. In such distributed environment where timely accessing of data is important, it becomes difficult to generate strong association rules. So it is necessary to reduce these rules for increasing rule reduction rate. This paper uses w-Tabular algorithm which combines weight assignment method and Quine-Mccluskey method...
Clustering is among the most common data mining techniques and Fuzzy clustering can model the world even more realistically and more precisely. One of the most favorable fuzzy clustering methods is the Fuzzy C-Means (FCM) algorithm, which is actually identical to the (original) K-Means clustering algorithm fueled with a fuzzy flavor. However, there are some issues with the fuzzy clustering methods;...
An improved cloud resource revenue optimization models are proposed, which include the benefits of service providers and users negotiate SLA agreement. And the models define the constraint mechanism for describing service quality problems such as service response time and customer satisfaction. We design the comprehensive response indicator and use this indicator to quantify the rationality of the...
Now a day's many of crimes are related to financial domain so forensic analysis of such documents is required. Due to digitization many of documents for investigation is faster. If analyzer analyzes the document manually it will time consuming and tedious task so, we follow the approach which will specify the clustering algorithm to document for forensic analysis of seize system which will help the...
As technology has advanced nowadays, it is common for a system to be optimized under more than one objective function, which leads to inconclusive results if two contradictory objectives exist. Traditional approaches suggest a simple aggregation of multiple objectives into one via a linear combination, but it is hard to justify the weights quantitatively. This paper proposes a systematic therapy to...
Community structure is a common feature in real-world network. Overlap community detection is an important method to analyze topology structure and function of the network. Most algorithms are based on the network structure, without considering the node attributes. In this paper, we propose an overlapping community detection algorithm based on node convergence degree which combines the network topology...
Syntax matching is a challenging basic issue, and related algorithms can be widely used in natural language processing. This paper addresses the problem of how to efficiently match a sentence with the most similar syntactic structure to a given Japanese sentence from a big set of Japanese sentences, designs a novel lexical index data structure of hiratoken-sentence index (HSI) according to our Japanese...
The optimal Latin hypercube designs have been applied in many computer experiments as a basic method of experiment design. In this paper, we propose a novel criterion for constructing optimal Latin hypercube designs. The corresponding foundation of the novel criterion ideas is that the each point of the uniform design should have approximately equal distance with adjacent points. It means if we count...
As the size of data table grows, the concepts generated become larger in number. Making sure the set of extent remaining unchanged, the purpose of attribute reduction of concept lattice is to find out minimum subsets of attributes and make knowledge presented by concept lattice simpler, decision problem simplified as well. This paper introduced the definition of introducer which was minimum closure...
For solving numerical integral problems, a composite Simpson method based on Differential Evolution algorithm (S-DE) is proposed. The proposed method can be viewed as a piecewise integration method. It firstly uses the differential evolution algorithm (DE) to find the optimal segmentation points on the integral interval of an integrand. The approximate integral value of the integrand is then calculated...
In this paper, we present a hierarchical butterfly communication model, which is applied to an asynchronous distributed ADMM algorithm. The goal is to minimize the communication overhead of the distributed ADMM algorithm in the fully connected network. We give a theoretical analysis of the convergence of the algorithm with hierarchical butterfly communication model. Experiments show that hierarchical...
Detectors and descriptors refer to the key points of the images where informative features can be detected or extracted to use in machine learning for classification or clustering problems. Four algorithms as two descriptor (SURF, MRES) and two detectors (Harris, Shi Tomasi) are utilized for semen cell detection problem in this paper. Results emphasize the best algorithm for future studies to use...
As the Tibetan traditional game with unique connotation and characteristics of national culture, Tibetan chess plays an important role in Tibetan culture heritage and protection. Tibetan chess includes different types of chess board and regulations. Chess board is with huge branching factor, the complexity of the search space is very high. Besides, chess play record collection is important issue facing...
This paper is a part of work on the attempt to implement the continuous control system which dynamically derives the control law during its operation, on basis of a model-based control algorithm. The measurements obtained from the sensors are dynamically included or excluded depending on the availability of individual sensors. The prototype application was developed in the JADE environment, and its...
A new HSS (Hierarchically Semiseparable) direct matrix solution algorithm, including both factorization and inversion, is developed for solving the volume integral equation (VIE) for large-scale electrodynamic analysis. This direct solution algorithm is exact in the sense that the matrix factorization, inversion, and solution do not involve any approximation. The HSS-representation of the VIE dense...
In order to reduce decision rule effectively, a decision rule reduction method based on core value and a decision rule prioritizing method were provided. The results show that effective decision rule reduction can be gotten through above methods and all of these help to improve decision ability.
Many biclustering algorithms have been proposed in analyzing the gene expression data and ensemble biclustering methods can improve performance of the biclustering algorithm. We propose a new method of obtaining a variety of constituent biclusters which use different quality measures of bicluster. To demonstrate the efficiency of our methods, experiment on six real gene expression data shows the diversity...
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.