359 Result(s)
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Chapter and Conference Paper
Extension of lower probabilities and coherence of belief measures
Coherence is an important concept which is introduced and discussed in a new mathematics branch, Imprecise Probability Theory. By using the Choquet integral, belief measures can be extended to be coherent lowe...
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Chapter and Conference Paper
Extract Frequent Pattern from Simple Graph Data
Mining the frequent pattern from data set is one of the key success stories of data mining research. Currently, most of the efforts are focused on the independent data such as the items in the marketing basket...
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Chapter and Conference Paper
Theoretical Analysis of Simple Evolution Strategies in Quickly Changing Environments
Evolutionary algorithms applied to dynamic optimization problems has become a promising research area. So far, all papers in the area have assumed that the environment changes only between generations. In this pa...
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Chapter and Conference Paper
An Efficient Algorithm of Frequent Connected Subgraph Extraction
Mining frequent patterns from datasets is one of the key success stories of data mining research. Currently, most of the works focus on independent data, such as the items in the marketing basket. However, the...
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Chapter and Conference Paper
Enhanced Active Shape Models with Global Texture Constraints for Image Analysis
Active Shape Model (ASM) has been widely recognized as one of the best methods for image understanding. In this paper, we propose to enhance ASMs by introducing global texture constraints expressed by its reco...
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Chapter and Conference Paper
Beyond Supervised Learning of Wrappers for Extracting Information from Unseen Web Sites
We investigate the problem of wrapper adaptation which aims at adapting a previously learned wrapper to an unseen target site. To achieve this goal, we make use of extraction rules previously discovered from a...
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Chapter and Conference Paper
Visual Search in Alzheimer’s Disease — fMRI Study
The aim was to investigate the neural basis of visual attention deficits in Alzheimer’s disease (AD) patients using functional MRI. Thirteen AD patients and 13 age-matched controls participated in the experime...
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Chapter and Conference Paper
Efficient Pattern-Growth Methods for Frequent Tree Pattern Mining
Mining frequent tree patterns is an important research problems with broad applications in bioinformatics, digital library, e-commerce, and so on. Previous studies highly suggested that pattern-growth methods ...
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Chapter and Conference Paper
Answering Approximate Range Aggregate Queries on OLAP Data Cubes with Probabilistic Guarantees
Approximate range aggregate queries are one of the most frequent and useful kinds of queries for Decision Support Systems (DSS). Traditionally, sampling- based techniques have been proposed to tackle this prob...
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Chapter and Conference Paper
Modeling Dynamic System by Recurrent Neural Network with State Variables
A study is performed to investigate the state evolution of a kind of recurrent neural network. The state variable in the neural system summarize the information of external excitation and initial state, and de...
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Chapter and Conference Paper
A Novel Individual Blood Glucose Control Model Based on Mixture of Experts Neural Networks
An individual blood glucose control model (IBGCM) based on the Mixture of Experts (MOE) neural networks algorithm was designed to improve the diabetic care. MOE was first time used to integrate multiple indivi...
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Chapter and Conference Paper
A Novel Intrusion Detection Method Based on Principle Component Analysis in Computer Security
Intrusion detection is an important technique in the defense-in-depth network security framework and a hot topic in computer security in recent years. In this paper, a new intrusion detection method based on P...
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Chapter and Conference Paper
GiSA: A Grid System for Genome Sequences Assembly
Sequencing genomes is a fundamental aspect of biological research. Shotgun sequencing, since introduced by Sanger et al [2], has remained the mainstay in the research field of genome sequence assembly. This me...
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Chapter and Conference Paper
A Novel Approach to Ocular Image Enhancement with Diffusion and Parallel AOS Algorithm
This paper suggests a new diffusion method, which based on modified coherence diffusion for the enhancement of ocular fundus images (OFI) and parallel AOS scheme is applied to speed algorithm, which is faster ...
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Chapter and Conference Paper
Subgraph Join: Efficient Processing Subgraph Queries on Graph-Structured XML Document
The information in many applications can be naturally represented as graph-structured XML document. Structural query on graph structured XML document matches the subgraph of graph structured XML document on so...
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Chapter and Conference Paper
Pneumatic Climbing Robots for Glass Wall Cleaning
Recently various robots have been designed for wall cleaning and maintenance. There are three kinds of kinematics for the motion on smooth vertical surfaces: multiple legs, a sliding frame and a wheeled and ch...
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Chapter and Conference Paper
ADenTS: An Adaptive Density-Based Tree Structure for Approximating Aggregate Queries over Real Attributes
In many fields and applications, it is critical for users to make decisions through OLAP queries. How to promote accuracy and efficiency while answering multiple aggregate queries, e.g. COUNT, SUM, AVG, MAX, M...
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Chapter and Conference Paper
Grid-ODF: Detecting Outliers Effectively and Efficiently in Large Multi-dimensional Databases
In this paper, we will propose a novel outlier mining algorithm, called Grid-ODF, that takes into account both the local and global perspectives of outliers for effective detection. The notion ofOutlying Degree F...
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Chapter and Conference Paper
Locating Human Eyes Using Edge and Intensity Information
In this paper, a new eye detection method is presented. The method consists of three steps: (1) extraction of binary edge image (BEI) based on the multi-resolution analysis of wavelet transform; (2) extraction...
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Chapter and Conference Paper
Term Graph Model for Text Classification
Most existing text classification methods (and text mining methods at large) are based on representing the documents using the traditional vector space model. We argue that important information, such as the r...