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148263 articles
Proceedings Article

A Framework for Knowledge-based Management Model on Decision-Making

Shao-Shin Hung, Damon Shing-Min Liu
Knowledge management (KM) is suggested as a method to manage and apply knowledge for business management. In this paper, we suggest a framework based on OPF (Open Process Framework) meta model for the knowledge-based decision-making. Based on the modeling method of OPF, we can translate partial and implicit...
Proceedings Article

A novel OoS-aware Routing for ad hoc networks

Tung-Shih Su, Chih-Hung Lin, Wen-Shyong Hsieh
Most routing protocols focus on obtaining a workable route without considering network traffic condition for a mobile ad hoc network (MANET). Therefore, the quality of service (QoS) is not easily achieved by the real time or multimedia applications. To support QoS, this work proposes a QoS-aware routing...
Proceedings Article

A User-centric Intrusion Detection System by Using Ontology Approach

Shao-Shin Hung, Damon Shing-Min Liu
In the security infrastructure, intrusion detection has become an indispensable defense line in face of increasing vulnerabilities exposed in today’s computing systems and Internet. In this paper, our approach uses ontologies as a way of grasping the knowledge of a domain, expressing the intrusion detection...
Proceedings Article

A Study on Imputing Censored Observations for Exponential Distribution Based on Random Censoring

Kuo-Ching Chiou
Censoring models are frequently employed in reliability analysis to reduce experimental time. There are three censoring model: type-I, type-II and random censoring. In this study, we focus on the right-random censoring model. In the previous literature, an imputation of the censored observation is considered...
Proceedings Article

String Filtering of a Large String Collection on Mobile Devices using a Neural Network

Heng Ma, Chia-Cheng Liu
String matching of a large string collection on mobile devices has been a difficult problem because of the memory space and computing speed constraints. We propose a method to efficiently determine whether a query string exists in the large string collection. The proposed method, based on a string encoder...
Proceedings Article

Novel BCD Circuits Design Using And-Or-Inverter Gate and Its Quantum-Dot Cellular Automata Implementation

JiaChun Lin, JenYin Yeh, WeiChih Tsai
Quantum-dot cellular automata (QCA) provide a novel electronics paradigm for information processing and communication. A basic quantum-dot cell consists of several quantum dots with two excess electrons. A binary coded decimal (BCD) and a decimal coded binary (DCB) circuit based on QCA logic gates: the...
Proceedings Article

Applying XCS Model to Spread Trading of Taiwan Stock Index Futures

Jung-Bin Li, Shih-Chuan Fu, An-Pin Chen
This study attempts to find the possibility of making relatively higher profit with lower risk when trading futures commodities. The system applies XCS classifiers to explore the rules of spread trading of these commodities. Our simulation holds a trading strategy that in every transaction, the proposed...
Proceedings Article

An Empirical Study for Dynamic TIPP Policy Using XCS with Knowledge Rules

Mei-Chih Chen, Ming-Chia Huang, An-Pin Chen
The purpose of this empirical study is intended to investigate XCS (Extended Classifier System) based model with knowledge rules for dynamic TIPP (Time Invariant Portfolio Protection) policy. There are two XCS-based agents in the proposed model (MA-TIPP).One agent dynamically optimizes Multiple and Tolerance...
Proceedings Article

New Approach to Financial Time Series Forecasting - Quantum Minimization Regularizing BWGC and NGARCH Composite Model

Bao Rong Chang, Hsiu Fen Tsai
A hybrid BPNN-weighted GREY-C3LSP prediction (BWGC) is used for resolving the overshooting phenomenon significantly; however, it may lose the localization once volatility clustering occurs. Thus, we propose a compensation to deal with the time-varying variance in the residual errors, that is, incorporating...
Proceedings Article

Learning Martingale Measures From High Frequency Financial Data to Help Option Pricing

Hung-Ching (Justin) Chen, Malik Magdon-Ismail
We provide a framework for learning risk-neutral measures (Martingale measures) for pricing options from high frequency financial data. In a simple geometric Brownian motion model, a price volatility, a fixed interest rate and a no-arbitrage condition suffice to determine a unique risk-neutral measure....
Proceedings Article

Analysis of factors which contribute to inter-enterprise competition

Takumi Shimizu, Yusuke Takada, Takashi Iba
In this paper, we replicate Nelson-Winter model in order to analyze the inter-enterprise competition from the perspective of economic change. For this purpose, we build the simulation model as Multi-Agent-Based Simulation in PlatBox Simulator. By replicating the Nelson-Winter model, which clarifies the...
Proceedings Article

Does Money Matter? An Artificial Intelligence Approach

Jane Binner, Barry Jones, Graham Kendall, Jonathan Tepper, Peter Tino
This paper provides the most complete evidence to date on the importance of monetary aggregates as a policy tool in an inflation forecasting experiment. Every possible definition of ‘money’ in the USA is being considered for the full data period (1960 – 2006), using the most sophisticated non-linear...
Proceedings Article

Stock Data Mining through Fuzzy Genetic Algorithms

Longbing Cao, Chao Luo, Jiarui Ni, Dan Luo, Chengqi Zhang
Stock data mining such as financial pairs mining is useful for trading supports and market surveillance. Financial pairs mining targets mining pair relationships between financial entities such as stocks and markets. This paper introduces a fuzzy genetic algorithm framework and strategies for discovering...
Proceedings Article

Dimensionality Reduction using GA-PSO

Cheng-Hong Yang, Chung-Jui Tu, Jun-Yang Chang, Hsiou-Hsiang Liu, Po-Chang Ko
The feature selection process can be considered a problem of global combinatorial optimization in machine learning, which reduces the number of features, removes irrelevant, noisy and redundant data, and results in acceptable classification accuracy. In this paper, we propose a combination of genetic...
Proceedings Article

Two Are Better than One?

Ming-Yuan Li
In this paper we adopt the Markov-switching specification to establish the hybrid model with time-varying loading on each of chartist and fundamentalist techniques. The US dollar exchange rates of four Asian tiger countries’ currencies serve as the representative examples in this paper. Our empirical...
Proceedings Article

An Evolutionary Weight Encoding Scheme and Crossover Methodology in Portfolio Assets Allocation

Ping-Chen Lin, Po-Chang Ko, Hsin-Chieh Wang
Most of GA-based portfolio assets allocation uses normalization method to allocate investment asset’s weight. However, the normalization process will cause unease converging and even diverging characteristics, because it changes the gene’s relativity of address in chromosome. In this paper, we propose...
Proceedings Article

Time series data analysis using probabilistic and neural network

Chiu-Che Tseng
Artificial intelligence decision support system is always a popular topic in providing the human user with an optimized decision recommendation when operating under uncertainty in complex environments. The particular focus of our discussion is to compare different methods of artificial intelligence decision...
Proceedings Article

Stock Trend Analysis and Trading Strategy

Hongxing He, Jie Chen, Jin Huidong, Chen Shu-Heng
This paper outlines a data mining approach to analysis and prediction of the trend of stock prices. The approach consists of three steps, namely partitioning, analysis and prediction. A modification of the commonly used k-means clustering algorithm is used to partition stock price time series data. After...
Proceedings Article

Oligopolistic Interdependency in a Mixed Market

Tay-Cheng Ma
This paper uses data from Taiwan’s banking sector to investigate if state-owned banks can serve as an internal regulation mechanism to sustain market competition. In contrast to the traditional second-best literature, the evidence shows that a certain degree of market coordination exists in the industry,...
Proceedings Article

Using Fuzzy Regression and Neural Network to Predict Organizational Performance

Liang-Hung Lin
As everyone knows, multiple regression analysis is an important approach to prediction studies. However, regression model has some limitations and constraints in the real world practices. This study applied fuzzy regression using neural network (FRNN) to predict organizational performance, and the findings...
Proceedings Article

The Development of Neural Network Models by Revised Particle Swarm Optimization

Peitsang Wu, Chin-Shiuh Shieh, Jar-Her Kao
A novel training paradigm for artificial neural networks had been developed and presented in this article. In the proposed approach, a revised version of particle swarm optimization (PSO) had been employed to find out the optimal connection weights of feed-forward artificial neural networks for given...
Proceedings Article

How does Sample Size Affect GARCH Models?

HS Raymond NG, KP LAM
GARCH model has a long history and permeates the modern financial theory. Most researchers use several thousands of financial data and maximum likelihood to estimate the coefficients of model. Statistically, more samples imply better estimation but are hard to obtain. How many samples are sufficient...
Proceedings Article

Decision Support for IC Molding Parameter Settings Using Grey Relational Analysis and Neural Network

Yu-Min Chiang, Chung-Hsien Chou, Yung-Yuan Chuang
In order to be competitive in the semiconductor manufacturing industry, quality improvement and yield enhancement have received increasing attention. The research focuses on the molding process of Integrated Circuit (IC) assembly. The defects often occurred in molding process include hole, vein, crack,...
Proceedings Article

Evolutionary Fuzzy Case-based Reasoning for Financial Performance Ranking

Sheng-Tun Li, Hei-Fong Ho, Yi-Chung Cheng
we propose a hybrid decision model for supporting the ranking financial status of corporations using case-based reasoning augmented with genetic algorithms and the fuzzy nearest neighbor method. An empirical experimentation on 746 cases was conducted that shows that the average accuracy of the ranking...
Proceedings Article

Building a Concept Hierarchy by Hierarchical Clustering with Join/Merge Decision

Huang-Cheng Kuo, Tsung-Han Tsai, Huang Jen-Peng
Concept hierarchies are important for generalization in many data mining applications. We propose a method to automatically build a concept hierarchy from a provided distance matrix. The method is a modification of traditional agglomerative hierarchical clustering algorithm. When two closest clusters...
Proceedings Article

Two-dimentional Encoding Schema and Genetic Operators

Tzung-Pei Hong, Ming-Wen Tsai, Tung-Kuan Liu
In this paper, we propose a new genetic algorithm based on the two-dimensional encoding method. Appropriate two-dimensional crossover and mutation operations are designed based on the two-dimensional representation to generate the next generations. A two-dimensional repairing mechanism is also proposed...
Proceedings Article

A quantum model of dynamic interdependent uncertainties for industrial organizations

William Lawless, Laurent Chaudron
A major failure of rational models (cognitive science, game theory) of organizations is the use of static concepts of interdependence to predict dynamic behavior. A quantum model of organizations transforms the traditional model with its dynamic interdependence of uncertainty. We consider field and laboratory...
Proceedings Article

Return Distribution under Behavioral Biases: A Numerical Simulation Study

Xiaoguang Yang, Fenghua Wen, Delong Huang, Qiujun Lan
Investors’ overconfidence and regret aversion lead to behavioral biases, such as over-reaction、under-reaction and disposition effect. By constructing a numerical simulation model, this paper shows that, return distributions under the behavioral biases have higher peaks and fatter tails, and they are...
Proceedings Article

A Knowledge Discovery Approach to Supporting Crime Prevention

Sheng-Tun Li, Fu-Ching Tsai, Shu-Ching Kuo, Yi-Chung Cheng
The main objective of this study is developing a linguistic cluster model in order to meet the public security index requirement and extract crime rule in time series. In contrast to the current studies in crime theory which mostly rely on traditional behavior science, we turned to a hybrid approach...
Proceedings Article

Does Information Technology Always Help? Theory and Evidence from Taiwan's Banking Industry

Hsieh Meng-Fen, Shirley J. Ho
Information technology (IT) has been extensively adopted in banking industries. The reasons for this massive adoption of IT are mainly twofold: for individual banks, IT can reduce banks’ operational costs (the cost advantage), and facilitate transactions among customers within the same network (the network...
Proceedings Article

Applying Grey Relation Analysis to Establish the Financial Distress Prediction Model for Electronic Companies in Taiwan

Meng-Fen Hsieh, Rong-Tsu Wang, I-Chuan Lu
Most researches have focused on the use of document feedback or factor analysis as metrics for financial distress prediction. The theoretical basis for the former is relatively weak, while the latter is severely limited by data requirements. As such, this paper will instead use grey relation analysis...
Proceedings Article

Super-fair Platforms Widely Hidden in Multinational Securities Business

Ruan Jishou, Jun He, Qi Dai
A general phenomenon puzzles all investors is that on one hand, most individual investors believe they need to construct the portfolio consisting of 15 or more stocks to prevent risk because that large investment companies frequently get high returns is due to they obey the existing investment theory...
Proceedings Article

An Application of Intellectual Capital on Financial Distress Models by Using Neural Network

Kuang-Hua Hsu, Jian-Fa Li, Hon-Jenq Fan
As the era of knowledge economy is prevalent in U.S. during 1992, knowledge economy plays an important role around the world. The value and competition of the traditional companies accounted on tangible assets. However, in the era of knowledge economy, the value and continuing operation of the companies...
Proceedings Article

Recognition of profitable customers for dental services marketing--a case of dental clinics in Taiwan

Bih-Yaw Shih, Wan-I Lee, Yi-Shun Chung, Ai-Wei Chen, Yichaio Sui
The medical care industry has been dramatically developed in the last two decades in Taiwan and it has resulted in an extremely risky position. The purpose of the research was the development of a neural network model to recognize profitable customers for dental services marketing. Data set was built...
Proceedings Article

3D model retrieval based on Grid Sphere and Dodecahedral Silhouette Descriptors

Jau-Ling Shih
With the development of computer graphics and virtual realities, the demand for a content-based 3D model retrieval system becomes urgent. In this study, two features, grid sphere and dodecahedral silhouettes, are proposed and combined for 3D model retrieval. The experiments are conducted on a 3D model...
Proceedings Article

Apriori Data Mining on Rotationally Invariant Multiresolutional Moments for Pattern Recognition

Annupan Rodtook, Stanislav Makhanov
We propose a new feature selection procedure based on a combination of a pruning algorithm, Apriori mining techniques and fuzzy C-mean clustering. The feature selection algorithm is designed to mine on a multiresolution filter bank composed of rotationally invariant moments. The numerical experiments,...
Proceedings Article

Finding The Finger By The Boundary Vector Product

Yuan-Fei Cheng
A finger finding procedure has been presented to recognize the finger number of the hand gesture. The hand gesture is extracted from the stationary background and transformed into a binary image. The hue attribute, that is, the I value in the YIQ color space is used to extract the hand gesture shape....
Proceedings Article

Object-Based Accumulated Motion Feature for the Compressed Domain Human Action Analysis

Cheng-Chang Lien, Chen-Yu Hong, Yu-Ting Fu
This paper proposed an effective and robust method to detect the rare behavior events within the compressed video directly. New motion feature called object-based accumulative motion vector (OAMV) is generated to extract a prominent motion feature and then polar histograms are used to describe the distribution...
Proceedings Article

Natural Scene Segmentation Based on Information Fusion and Homogeneity Property

Heng-Da Cheng, Manasi Datar, Wen Ju
This paper presents a novel approach to natural scene segmentation. It uses both color and texture features in cooperation to provide comprehensive knowledge about every pixel in the image. A novel scheme for the collection of training samples, based on homogeneity, is proposed. Natural scene segmentation...
Proceedings Article

An Improved Vector Quantizer Design Method: the Codebook Reorganization Algorithm

Ting-Wei Hou, Houng-Kuo Ku, Yuan-Tsung Chen
Generalized Lloyd Algorithm(GLA) is important in vector quantizer design. It runs fast, but it is sensitive to initial conditions and it may find a local optimum. We propose an improved approach based on GLA, named vector quantized codebook reorganization algorithm (VQCRA). VQCRA finds better codebooks...
Proceedings Article

Data Fusion and Multi-fault Classification Based On Support Vector Machines

Guohua Gao, Yongzhong ZHANG, Yu ZHU, Guanghuang DUAN
As a new general machine-learning tool based on structural risk minimization principle, Support Vector Machines (SVM) has the advantageous characteristic of good generalization. For this reason, the application of SVM in fault diagnosis field has becomes one growing reach focus. In this paper, data fusion...
Proceedings Article

Head-Shoulder Moving Object Contour Tracking using Shape Model

Yong-Ren Huang, Chung-Ming Kuo, Chaur-Heh Hsieh
This paper proposes a new approach for tracking the contour of moving object for head-shoulder video sequence using initial shape model. First, we can utilize manual process or some segmentation approach to obtain the initial shape model. Then, we detect the changing ratio of intensity outside the bounding...
Proceedings Article

An Effective Drilling Wear Measurement based on Visual Inspection Technique

Yu-Teng Liang, Yih-Chih Chiou
The purpose of this research is to use the visual inspection technique for the automatic tool wear measurement of different coated drills. The tool wear images with the different coated drilling are captured using a machine vision system incorporating with an effective vertex detection algorithm based...
Proceedings Article

A Pornographic Web Patrol System Based-on Hierarchical Image Filtering Techniques

Chumsak Sibunruang, Jantima Polpinij, Rapeeporn Chamchong, Anirut Chotthanom, Somnuk Puangpronpitag
Due to the flood of pornographic web sites on the internet, content-based web filtering has become an important technique to detect and filter inappropriate information on the web. This is because pornographic web sites contain many sexually oriented texts, images, and other information that can be helpful...
Proceedings Article

Efficient Surface Interpolation with Occlusion Detection

Boubakeur Boufama, Houman Rastgar, Saida Bouakaz
In this paper we present a novel dense matching algorithm that relies on sparse stereo data in order to build a dense disparity map. The algorithm uses a recursive updating scheme to estimate the dense stereo data using various interpolation techniques. The major problem of classical template matching...
Proceedings Article

Scene Classification for Baseball Videos Using Spatial and Temporal Features

Mao-hsiung Hung, Chaur-Heh Hsieh, Ying-Chung Zhu
Correct classification of various kinds of scenes in sport videos is essential for higher-level content analysis such as event detection. The paper presents a novel technique for the classification of the typical scenes of baseball videos. The spatial color features are employed to detect pitch scene...
Proceedings Article

Signature recognition using conjugate gradient neural networks

Jamal Abu Hasna
SIGNATURE RECOGNITION USING CONJUGATE GRADIENT NEURAL NETWORKS Transforming the input before training yields much lower error, but is more sensitive. Most importantly, we have presented system can vary in security depending on the situation. Uses for such a system range from securing a credit card transaction...
Proceedings Article

Analysis and Assessment of Knowledge Sharing Risk in the Virtual Enterprise

Tian-hui You, Zhu Zhu, Zhu-chao Yu
A method to analyze and assess knowledge sharing risks in the virtual enterprise is proposed. Firstly, based on risks analysis, an index system is set up to assess such risks as the core competence losing risk, the enterprise culture risk, the knowledge spillover effect risk and the moral risk, etc.....