130 Result(s)
within
Conference Paper
Hong**g Cheng
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Chapter and Conference Paper
Dielectric Properties and Applications of Strontium Titanate Thin Films for Tunable Electronics
The dielectric constant (ε) of ferroelectric materials, such as (Ba,Sr)TiO3 (BST) and SrTiO3 (STO), depends strongly on the applied electric field [1, 2]. This phenomenon has been referred to as the dielectric no...
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Chapter and Conference Paper
Case Mining from Large Databases
This paper presents an approach of case mining to automatically discover case bases from large datasets in order to improve both the speed and the quality of case based reasoning. Case mining constructs a case...
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Chapter and Conference Paper
Principal Component Analysis Neural Network Based Probabilistic Tracking of Unpaved Road
Based on principal component analysis neural network, within a probabilistic framework, we introduce a new Monte Carlo tracking technique for autonomous navigation of land vehicle on unpaved road. The use of s...
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Chapter and Conference Paper
Neural Network Based Online Feature Selection for Vehicle Tracking
Aiming at vehicle tracking with a single moving camera for autonomous driving, this paper presents a strategy of online feature selection combined with related process framework. Detected vehicle can provide m...
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Chapter and Conference Paper
TextCC: New Feed Forward Neural Network for Classifying Documents Instantly
Corner classification (CC) network is a kind of feed forward neural network for instantly document classification. To classify text object instantly, new training algorithm, named as TextCC, for feed forward n...
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Chapter and Conference Paper
Principle for Outputs of Hidden Neurons in CC4 Network
Corner classification (CC) is a kind of algorithms for instantly classification. The feed forward neural network trained by CC algorithm can be used validly by information retrieval, especially online informat...
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Chapter and Conference Paper
Research on Stereographic Projection and It’s Application on Feed Forward Neural Network
Feed forward neural network for classification instantly requires that the modular length of input vector is 1. On the other hand, Stereographic projection can map a point in n dimensional real space into the ...
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Chapter and Conference Paper
Vanishing Point and Gabor Feature Based Multi-resolution On-Road Vehicle Detection
Robust and reliable vehicle detection is a challenging task under the conditions of variable size and distance, various weather and illumination, cluttered background, the relative motion between the host vehi...
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Chapter and Conference Paper
Bandwidth Guaranteed Routing in Wireless Mesh Networks
Interference can make significant impact on the performance of wireless networks. Wireless mesh networks (WMNs) allow multiple orthogonal channels to be used simultaneously in the system and the throughput can...
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Chapter and Conference Paper
Access Scheduling on the Control Channels in TDMA Wireless Mesh Networks
The access scheduling on the control channels in TDMA wireless mesh networks is studied in this paper. The problem is to assign time-slots for each node in the network to access the control channels so that it...
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Chapter and Conference Paper
Access Scheduling on the Control Channels in TDMA Wireless Mesh Networks
The access scheduling on the control channels in TDMA wireless mesh networks is studied in this paper. The problem is to assign time-slots for each node in the network to access the control channels so that it...
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Chapter and Conference Paper
Forward Semi-supervised Feature Selection
Traditionally, feature selection methods work directly on labeled examples. However, the availability of labeled examples cannot be taken for granted for many real world applications, such as medical diagnosis...
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Chapter and Conference Paper
DSM based Multi-view Process Modelling Method for Concurrent Product Development
Process management system for concurrent product development is one of the key technologies and its main functional modules include product development process modeling, process analysis, process optimization,...
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Chapter and Conference Paper
Mining Closed Episodes from Event Sequences Efficiently
Recent studies have proposed different methods for mining frequent episodes. In this work, we study the problem of mining closed episodes based on minimal occurrences. We study the properties of minimal occurr...
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Chapter and Conference Paper
Five-Axis Milling Simulation Based on B-rep Model
Formulating the swept volume by a cutter along its path plays an important role in volumetric simulation of five-axis machining. In some cases, the swept volume may experience self-intersection, which is a cru...
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Chapter and Conference Paper
Graph-Based Semi-supervised Feature Selection with Application to Automatic Spam Image Identification
In this paper, we propose a new spectral semi-supervised feature selection criterion called s-Laplacian score. It identifies discriminate features by measuring their capability of preserving both local and glo...
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Chapter and Conference Paper
A Study on the Model of Work-Embedded E-learning
Work-embedded e-learning is a new learning model which not only replaces the age-old model of “learn-then-do” but also is the development of e-learning. The paper concluded two modes of work-embedded learning ...
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Chapter and Conference Paper
An Efficient Intrusion Detection Scheme for Wireless Sensor Networks
As a hot issue, wireless sensor network have gained widely attention. WSNs in general and in nature are unattended and physically reachable from the outside world, they could be vulnerable to physical attacks ...
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Chapter and Conference Paper
Querying Shortest Path Distance with Bounded Errors in Large Graphs
Shortest paths and shortest path distances are important primary queries for users to query in a large graph. In this paper, we propose a new approach to answer shortest path and shortest path distance queries...
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Chapter and Conference Paper
Bayesian Network Structure Learning from Attribute Uncertain Data
In recent years there has been a growing interest in Bayesian Network learning from uncertain data. While many researchers focus on Bayesian Network learning from data with tuple uncertainty, Bayesian Network ...
