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This paper presents two methods for determining the noise power (mainly caused by crosstalk) in Digital Subscriber Line (DSL) networks. A fuzzy system approach is compared to a linear regression approach. Both are applied to a real world DSL network where a variable noise power is injected. Knowledge Discovery in Database (KDD) is used to organize the data selection, while linear regression and Fuzzy...
In this study, a spotlight filter for capturing the local structure information in tracing object's contour is proposed for object contour extraction. By searching the possible contour path between the initial source and destination contour points, the spotlight filter is able to capture the local structure information along the path, filter out the edge candidate pixels with weak evidence of being...
Segmentation of brain tissue in magnetic resonance imaging (MRI) can identify anatomical areas of interest. It has been widely used in medical imaging applications. In this paper, we propose a new brain MRI segmentation method, which takes advantage of spatial prior and neighboring pixels affinities. In addition, the underlying model can naturally describe the partial volume effects. Firstly, the...
In this paper, we present a novel framework, called learning by propagability, for two essential data mining tasks, i.e., classification and regression. The whole learning process is driven by the philosophy that the data labels and the optimal feature representation jointly constitute a harmonic system, where the data labels are invariant with respect to the propagation on the similarity graph constructed...
There has been a lot of interest in mining the time series data. Stock data mining plays an important role to visualize the behavior of financial market. In financial data mining the data is normally represented in the numeric format, however, the symbolic representation is also used to evaluate the overall impact. Time series data are difficult to manipulate, but when they are treated as symbols...
Most existing process mining methods were designed for ignoring time variability from real business process data, thus it could be hard to implement adaptive process mining. To deal with this problem, a new method of adaptive process mining was proposed in order to mine unremittingly process models of gradual change which represents the improvement stages of business processes and improve accuracy...
Nowadays, commercial activities on the internet and media need to be protected by increasing of security, using the 2D Barcode with a digital watermark in security field. This paper proposes that QR Code (Quick Response Code) is embedded with an invisible watermark by using Discrete-Cosine-Transform, or DCT for an information hiding (secret information) within the group through the QR Code image with...
An application which operates on an imbalanced dataset loses its classification performance on a minority class, which is rare and important. There are a number of over-sampling techniques, which insert minority instances into a dataset, to adjust the class distribution. Unfortunately, these instances highly affect the computation of generating a classifier. In this paper, a new simple and effective...
The capture of data provenance is a fundamentally important task in eScience. While provenance can be captured using techniques such as scientific workflows, typically these techniques do not trace internal data manipulations that occur within off-the-shelf analysis tools. Yet it is still essential to capture data provenance within such environments. This paper discusses an in situ provenance approach...
A general task in data mining consists in finding all rectangles of 1 in a boolean matrix in which the order of the rows and columns is not important. However, most algorithms which have been developed to solve this task are unable to be adapted to real data that may contain noise. The effect of the noise is to shatter relevant item sets into a set of small irrelevant item sets, yielding an explosion...
With the advantages of some current web text extraction algorithms, this paper puts forward a new method based on the combination of the regular expressions and density of page text, the method firstly uses the regular expressions to clear the html tags by the characteristics of the web page source code, and then extracts the main text of page with the distribution density of text. The algorithm is...
Internet technologies and web based social networking have seen wide adopted in the recent years and the user is exposed to lots of data from his friends and acquaintances. The data presented to the user needs to be filtered based on his current state and prioritized. In this paper we propose a method for identifying change points related to busy and free periods based on mobile phone call detail...
The real-time data stream clustering and the detection of clustering boundary is an interesting research work. This paper proposes a clustering algorithm named DDBound with boundary detection ability for grid clustering based on distance and density. DDBound firstly calculates the densities of all grids, and divides them into high-density grids and low-density grids. From all grids, the algorithm...
This paper describes a fast plane extraction algorithm for 3D range data. Taking advantage of the point neighborhood structure in data acquired from 3D sensors like range cameras, laser range finders and Microsoft Kinect, it divides the plane-segment extraction task into three steps. The first step is a 2D line segment extraction from raw sensor data, interpreted as 2D data, followed by a line segment...
This paper proposes a novel approach that allows region-based active contour energy to be re-expressed combining local and global information. The basic idea of this technique consists in extracting image statistics locally from the heterogeneous region (foreground or background) and globally from the other region at each point along the curve. By exploiting benefits of both local-based and global-based...
Interpretation of seismic data is a time-consuming and arduous task. Clustering analysis as an intelligent analysis method can be applied to the petroleum industry. While most clustering algorithms have good performance on transactional data, they are not suitable for seismic data. Unlike traditional data, seismic data have some characteristics of its own: spatially position, fuzzy nature and arbitrary...
This paper proposed LSB Information Hiding algorithm which can Lift wavelet transform image. Furthermore, made the objective evaluation of image quality by the peak signal to noise ratio and normalized cross correlation coefficient. Achieving the purpose of information hiding with the secret bits of information to replace the random noise, using the lowest plane embedding secret information to avoid...
From the fact that human behavior is determined by both miners' intrinsic characteristics and external environment, the factors that may affect human behavior safety in metal underground mining are analyzed. Based on the analysis, countermeasures such as choose eligible miners and optimize environment are proposed, consequently to minimize the adverse effect and maximize the efficiency of miners matching...
The information measure is the important parameter reflecting edge characteristic of image. Three basic features of edge point have been represented using information measure technology to distill edge information. This paper has proposed a computing method of information measure and a basic method of distilling edge information using image information measure with nearby area consistency measure...
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