Proceedings of the 11th Joint Conference on Information Sciences (JCIS 2008)
Acceptance Double Sampling Plan with Fuzzy Parameter
Ezzatallah Baloui Jamkhaneh, Bahram Sadeghpour-Gildeh, Gholamhossein Yari
In the present paper we have proposed a method for designing acceptance double sampling plans with fuzzy quality characteristic. we have argued the acceptance double sampling plan when the fraction of defective items is a fuzzy number. These plans are well defined since if the fraction of defective items...
Toolbox for Interval Type-2 Fuzzy Logic Systems
Mohsen Zamani, Hossein Nejati, Amin T. Jahromi, AliReza Partovi, Sadegh H. Nobari, Ghasem N. Shirazi
Type-2 systems has been becoming the focus of research in the field of fuzzy logic in recent years. Comparing with type-1 systems, type-2 fuzzy systems are more complex and relatively more difficult to understand and implement. We developed an interactive graphical user interface (GUI) based toolbox,...
Optimism and Pessimism in Decision Making Based on Intuitionistic Fuzzy Sets
Ting-Yu Chen, Che-Wei Tsui
This paper presents a method of relat-ing optimism and pessimism to multiple criteria decision analysis based on intuitionistic fuzzy sets. We develop the concepts of optimistic and pessimistic point operators to measure optimism and pessimism, respectively. Furthermore, we provide an approach to effectively...
A Comparative Study of Intuitionistic Fuzzy Entropy on Attribute Importance
Ting-Yu Chen, Chia-Hang Li, Che-Wei Tsui
We propose a new objective weight method by using intuitionistic fuzzy (IF) entropy measures for multiple attribute decision making (MADM). We utilize the nature of IF entropy to assess the attribute weight based on the credibility of data, and the concept is totally different with the traditional one....
Personalized Advertisement System Based On Computational Intelligence
A software company develops an online socialization platform where users inter-act with others at virtual environments. The company’s income is from the adver-tisements displayed at these virtual envi-ronments. They are willing to develop a personalized advertisement system in or-der to increase their...
Key Risk Factors Assessment for Metropolitan Underground Project
Shih-Tong Lu, Cheng-Wei Lin, Hsin-Lung Liu
Underground construction project in metropolis is more dynamic and risky. A key risk factors analysis will give project contractor a more rational basis on which to make decision. This study applies the fuzzy preference relations to deal with the degree of impact and rank for the main risk factors of...
Clustering Blog Information
Mayank Prakash Jaiswal, H. Chris Tseng
Blogs form an important source of information in today’s internet world. Most of the blog websites have the blogs arranged in chronological order rather than its con-tents. Such arrangement of blogs makes it difficult for the user searching information about a particular topic from the blog. To resolve...
Demonstration of Learned Helplessness with Fuzzy Reinforcement Learning
Vali Derhami, Zahra Youhannaei
This paper demonstrates a kind of learned helplessness in human being that is ap-peared in Fuzzy Reinforcement Learning (FRL) algorithm. At the beginning of learning, when an agent continuously per-forms actions that cause sequential pun-ishments, afterwards it does not usually behave well and...
Similarity Based Fuzzy and Possibilistic c-means Algorithm
Chunhui Zhang, Yiming Zhou, Trevor Martin
A similarity based fuzzy and possibilistic c-means algorithm called SFPCM is presented in this paper. It is derived from original fuzzy and possibilistic c-means algorithm(FPCM) which was proposed by Bezdek. The difference between the two algorithms is that the proposed SFPCM algorithm processes relational...
Toward A Measurement Model of Fuzzy Prioritization Operators
The Fuzzy Prioritization Operators (FPOs) have been studied by various studies. As various FPOs produce different results, the fitness levels of FPOs are necessary to be measured. This research reviews two important FPOs, and proposes a Fuzzy Prioritization Measurement (FPM) model to measure the appropriateness...
Type-2 Fuzzy Classifier Ensembles for Text Entailment
Asli Celikyilmaz, I. Burhan Turksen
This paper presents a new Type-2 Fuzzy Classifier ensemble, which enables to model parameter uncertainties by charac-terizing the fuzzy sets with secondary membership values. We use fuzzy clus-tering method to characterize primary membership values and genetic algorithm to approximate secondary membership...
Application of Sensitivity Analysis, “Worst Case”, and Maximum Possible Risk (MPR) to Adventitious Events
T. Taylor, T. Whalen, M. Cohen
We present here a logical progression of probability and risk analysis for adventi-tious events, events whose probability is not well measurably different from zero (WMDZ). We will show that such analy-ses culminate in maximum possible risk (MPR) and, further, that MPR is equiva-lent to a boundary condition...
Explicit Spatial-Temporal Simulation of a Rare Disease
Ling Bian, T Whalen, M Cohen, Y. Huang, G. Lee, E. Lim, L. Mao, Y. Yan
This paper reports on the use of possibility theory and agent based explicit spatio-temporal simulation to compare the effects on each of three real communities given the assumption that a rare disease is carried out of a hypothetical high containment biological research laboratory sited in that community....
Issues in Microbial Risk Assessment
M. Cohen, T. Taylor, Jr. T. Whalen
Microbial risk assessment is the quantita-tive (or qualitative) characterization of the potential health effects of a particular mi-croorganism on individuals or populations. Practical public health policy/decisions to-day requires rethinking traditional ap-proaches in how microbial risk assessments...
Maximum Possible Risk Modeling
M. Schütz, M. Cohen, T. Whalen, T. Taylor
Counterfactual assumptions enable a maximum possible risk analysis of the possibility of an aerosol release of pathogens such as anthrax spores from a biological research laboratory. Eight counter-factual assumptions in conjunction ensure that any actual laboratory accident would pose a risk of exposure...
Possibilistic Risk and Counterfactual Probabilities
T. Whalen, T. Taylor, M. Cohen
Possibility theory is applied to assessing the relative risk associated with very rare, high-consequence hazards. The probability of rare negative events has to be estimated from a few past occurrences that are spread over long exposure periods, with counter- measures added in response to each event...
Speedup Factor Estimation through Dynamic Behavior Analysis for FPGA
Zhongda Yuan, Jinian Bian, Qiang Wu, Oskar Mencer
In reconfigurable platform, before convert and download program into real hardware, reliable estimation of speedup factor is of great importance for task schedulers. In this paper, a novel technique for speedup factor estimation is proposed. From the event patterns collected by hardware counters built...
Multilevel Based Global Routing Algorithm for Hierarchical FPGA
Limin Zhu, Jinan Bian, Qiang Zhou, Xianlong Hong
This paper presents an efficient global routing algorithm for a hierarchical inter-connection architecture of FPGA. What is different from the traditional FPGA rout-ing algorithm is that the proposed algo-rithm takes advantage of the hierarchical structure of this particular FPGA. We use a hierarchical...
Fast Wirelength-driven Partition-based Placement for Island Style FPGAs
Wentao Sui, Sheqin Dong, Jinian Bian, Xianlong Hong
In this paper, we propose a placement method for island-style FPGAs. This me-thod consists of three steps: recursive bi-partition with terminal propagation con-sideration, minimum-cost flow initial placement and low temperature simulated annealing optimization. Unlike the traditional partitioning-based...
Physical Information Driven Packing Method in FPGA
Wentao Sui, Sheqin Dong, Jinian Bian, Hong Xianlong
Packing-integrating basic logic units into higher level logic unit-is an important step in cluster-based hierarchical FPGA placement. The physical information of logic block acquiring before packing has a real influence over both wirelength-driven and timing-driven packing algo-rithms. A new packing...
Even Distribution Evaluation in Random Stimulus Generation
Zhiqiu Kong, Shujun Deng, Jinian Bian, Yanni Zhao
This paper has two contributions: First is to analyze the entropy evaluation for random stimulus generation in one paper of DATE 2008; second is to present better methods to evaluate the solutions’ even distribution for random stimulus generation. An evaluation strategy called min-distance-sum takes...
RTL Test Generation via Fault Insertion and Hybrid Satisfiability Solving
Test generation at RTL (Register-Transfer Level) is a challenging task be-cause bit and word variables co-existent and the high-level functional units impose more complex constraints. We propose an effective way to the problem. In our method, given the circuit as well as the fault point to be checked,...
Driver Fatigue Detection based on Eye State Analysis
Yong Du, Peijun Ma, Xiaohong Su, Yingjun Zhang
Driver fatigue is one of the important fac-tors in a large number of traffic accidents. Eye states (full open, half open or closed) analysis is an efficient measure to evalu-ate driver’s alertness. In this paper, we present an effective vision-based driver fatigue detection method. Firstly, the in-terframe...
Power aware accuracy-guaranteed fractional bit-widths optimization
Linsheng Zhang, Yan Zhang, Wenbiao Zhou
A novel power aware accuracy-guaranteed fractional bit-widths optimization scheme for floating-point to fixed-point transformation of DSP algorithms is presented in this paper. Quantization-Operation-Error (QOE) model is used to construct the worst case quantization error propagation. Based on QOE, a...
A Fixed-outline Floorplanning Method Based on 2.5D
Sheqin Dong, Qi Xie
In this paper, a fixed-outline floorplan-ning algorithm based on 2.5D is proposed. By using constraints of area and number of pins to divide the modules into 4 layers, it confines the variations of the widths of the floorplans to a small region through common subsequence of sequence pair representation....
Recommender System based on Higher-order Logic Data Representation
Linna Li, Bingru Yang, Zhuo Chen
Collaborative Filtering help users to deal with information overload and guide them in a personalized way to interesting or useful objects in a large space of possible options. In this paper, we present a novel and elegant hybrid recommender system called HOLCF, which use higher-order logic as data representation...
A Petri-Net Based Approach to Verifying Compositional Correctness of System Components
King Sing Cheung
In component-based system design, one need to obtain from a given set of com-ponents an integrated system which is correct in the sense that the system is live, bounded and reversible. In this paper, based on the composition of augmented marked graphs, we propose a method for verifying correctness of...
Technical Research on Describing Reconfigurable Systems by Object Oriented Petri net
Jun Guo, Sheqin Dong, Kegang Hao, Satoshi Goto
An object oriented Petri net was proposed in order to describe reconfigurable systems. The formal definitions of this kind of Petri net were presented carefully. The methods of subnet partition were discussed in details. And techniques of mapping objects to reconfigurable platform were discussed as well....
Application of Linear Model Fitting in Image Edge Fast Detection
Peng Wang, Zhao Wei
A linear model parameter estimation method is proposed based on Bayesian treatment in addition to the linear least squares ,The detail algorithm of one order linear model parameter estimation was introduced in the paper , it can also be used to the parameter estimation of multi-order linear model .we...
A Software Dependability Growth Model based on Self-Reconfiguration
Qian Zhao, HuiQiang Wang, HongWu Lv, Guangsheng Feng
With wide application of computers, software quality attracts people`s atten-tion. Traditional software dependability theory can’t satisfy people`s requirement, which need induct new idea to resolve the serious software quality crisis. This paper uses self-reconfiguration mechanism of Autonomic Computing...
The Features Vector Research on Target Recognition of Airplane
Shuangzi Sun, Lihong Yuan, Yong Yang, Xiaochao Chen
The selection of the features vector is crucial, taking direct effect on the accuracy of target recognition. Considering that the airplane has smooth surface and regular geometric shape, this paper chooses the geometric shape feature to describe the target of airplane. These geometric features vector...
Ultrasound Image Segmentation Based On Probability Distance and Maximum Likelihood
Bo Liu, H. D. Cheng, Jianghua Huang, Jiafeng Liu, Tang Xianglong
In this paper, a novel geometric active contour model for segmenting ultrasound image is presented. A partial differential equation is designed to minimize the dif-ference between the actual and the esti-mated intensity probability distributions of the image regions. The Rayleigh dis-tribution and maximum...
Fully automatic and segmentation-robust classification of breast tumors based on local texture analysis
Bo Liu, H. D. Cheng, Jianghua Huang, Jiafeng Liu, Tang XIanglong
In this paper, a novel fully automatic classification method of breast tumors using ultrasound (US) image is proposed. The proposed method can be divided into two steps: “ROI generation step” and “ROI classification step”. In the ROI generation step, the proposed method fo-cuses on finding a credible...
A Rain Removal Method Using Chromatic Property for Image Sequence
Peng Liu, Jing Xu, Jiafeng Liu, Xianglong Tang, Wei Zhao
Raindrops degrade the performance of outdoor vision system, and bring difficulties for objects detection and analysis in image sequence. In this paper, we propose an algorithm for raindrop removal using chromatic based properties in order to improve the data quality and vision effect of image sequence....
Adaptive attacking algorithm against DCT-based watermarking
Tao Zhang, Daoshun Wang, Shundong Li, Xunxue Cui, Yiqi Dai
In this paper we present a new water-marking attacking algorithm based on the periodic transformation of matrix. By analyzing of the principles of adaptive watermarking embedding in DCT domain, we chose some blocks of the stegoimage to embed the watermarking based on the characteristics of human visual...
Road Boundary Detection in Complex Urban Environment based on Low-Resolution Vision
Qinghua Wen, Zehong Yang, Yixu Song, Peifa Jia
In this paper, we proposed a real-time road boundary detection method in com-plex urban road environment. The detec-tion difficulty lies in road wear, both exis-tence of marked and unmarked boundary and low-resolution vision. The idea of the algorithm is to extract the road surface firstly using improved...
Adaptive Algorithm in Image Denoising Based on Data Mining
Yan-hua Ma, Chuan-jun Liu
An adaptive filtering algorithm based on data mining is proposed for image de-noising when an image is merged by pep-per-and-salt noise. It can adjust the rotat-ing mask size based on the noisy density in the input image so that it raises greatly the computing speed; On the other hand, the algorithm...
A Novel Approach to Speckle Reduction to Ultrasound Image
Yanhui Guo, H.D. Cheng, Jiawei Tian, Yingtao Zhang
Speckle noise is inherent in ultrasound images, and it generally tends to reduce the resolution and contrast, thereby，to degrade the diagnostic accuracy of this modality. Speckle reduction is very im-portant and critical for ultrasound imag-ing. In this paper, we propose a novel ap-proach for speckle...
A Novel Approach to Breast Ultrasound Image Segmentation Based on the Characteristics of Breast Tissue and Particle Swarm Optimization
Yanhui Guo, H.D. Cheng, Jiawei Tian, Yingtao Zhang
Breast cancer occurs to over 8% women during their lifetime, and is a leading cause of death among women. Sonography is superior to mammography in its ability to detect focal abnormalities in the dense breasts and has no side-effect. In this paper, we proposed a novel automatic segmentation algorithm...
A NOVEL HOUGH TRANSFORM BASED ON ELIMINATING PARTICLE SWARM OPTIMIZATION AND ITS APPLICATIONS
Yanhui Guo, H.D. Cheng, Wei Zhao, Yingtao Zhang
Hough transform (HT) is a well estab-lished method for curve detection and recognition due to its robustness and in-sensitiveness to noise, and its parallel processing capability. However, HT is quite time-consuming. In this paper, an eliminating particle swarm optimization (EPSO) algorithm is studied...
A NEW NEUTROSOPHICAPPRAOCH TO IMAGE THRESHOLDING
Yanhui Guo, H.D. Cheng, Yingtao Zhang, Wei Zhao
A neutrosophic set (Ns), a part of neutro-sophy theory, studies the origin, nature, and scope of neutralities, as well as their interactions with different ideational spectra. The neutrosophic set is a power-ful general formal framework that has been recently proposed. However, the neutrosophic set needs...
A New Neutrosophic Approach to Image Denoising
Yanhui Guo, H.D. Cheng, Yingtao Zhang, Wei Zhao
A neutrosophic set (NS), a part of neu-trosphy theory, studies the origin, na-ture, and scope of neutralities, as well as their interactions with different idea-tional spectra. The neutrosophic set is a general formal framework that has been recently proposed. However, the neutrosophic set needs to be...
Study on Algorithms of Keyword Confusion Network Generation
Lei Zhang, Meimei Jia, Lili Guo
Keyword spotting based on large vocabulary continuous speech recognition (LVCSR) is the main researching direction of keyword spotting field. Lattice as the middle result of LVCSR, is often used in this system. But because of its big size, the performance is not efficient as we expect to be. In this...
A Novel Image Segmentation Algorithm Based on Fuzzy C-means Algorithm and Neutrosophic Set
Yanhui Guo, H.D. Cheng, Wei Zhao, Yingtao Zhang
Image segment is an important step in image processing, pattern recognition and computer vision. Numerous algorithms have been proposed to in this field for last twenty years. However, a generalized segmentation method, especial for noisy image, are not studied greatly. A neutrosophic set (NS), a part...
Nonlinear Diffusion Combined with Brownian Motions for Image Denoising
Mingliang Guo, Peng Liu
We introduce Brownian motion into the nonlinear diffusion process for image denoising in this paper. Brownian motion in our work stands for the variation of gray value of a pixel in the form of “random walking” which analogs the irregular and unceasing movement of a small particle. A reflection wall...
Invariant Features Extraction for Banknote Classification
Peng Wang, Peng Liu
An invariant feature extraction method is proposed for banknote classification. The movement of banknote is complex in the channel of financial instruments. The scale is various. The rotation and translation are also to occur. The method of feature extraction is insensitive to the variety of scale, rotation...
Multi-Class Object Classification and Lo-cation of Thermal Imagery in Electric Substation
Yubo Li, Hengda Cheng, Xianglong Tang, Jiafeng Liu
We present an algorithm based on chamfer matching for classification and location of thermal imagery in electric substation. We first refine the chamfer algorithm, then we present a new object class classification and location algorithm based on chamfer distance, also we analyze the object class recognition...
Grid Particle Filter for Human Head Tracking Using 3D Model
Chenguang Liu, Jiafeng Liu, Jianhua Huang, Xianglong Tang
A new 3D head-shoulder model based particle filter is presented for finding human head in static images. Edge cues are used as the likelihood function of the proposed particle filter. The positions of head as well as its direction are evaluated simultaneously. At each time step, the proposed algorithm...
Improving shape correspondences using salient points
Xin Li, XingWei Yang, Chengen Lu
Quality of a shape matching technique is correlated to the quality of contour point correspondences obtained. Improving correspondences hence can be useful for better shape matching. In this paper we present a framework that can find salient points correspondences along the contour.The results demonstrate...
Fast Tracking 3D Arm Motion with Joint-Chain Motion Model
X.S. Yu, W Zhao, J.F. Liu, X.L. Tang, J.H. Huang
Focusing on the problem of low computa-tion efficiency in the process of tracking human 3D motion, the fast tracking algo-rithm for 3D arm motion based on Joint-Chain Motion Model (JCMM) is pro-posed based on the Particle Filter. In our algorithm, via the Joint-Chain Motion Model (JCMM) is defined, the...
A Fast Method for Monitoring Driver Fatigue Using Monocular Camera
Hongbiao Ma, Zehong Yang, Yixu Song, Peifa Jia
This paper proposes a real time driver fatigue monitoring method. Haar algorithm is used to locate the face and detect the eye, histogram-based automatic threshold algorithm is used to extract the eye contour,finally we use the moving average of eyelid distance to decide whether driver is fatigue or...
Corner Detection Using Color Density Gradient
Da Sun, Jianhua Huang, Xianglong Tang
Locating theWood Defects with Typical Features and SVM
Zhao Zhang, Ning Ye, Dongyang Wu, Qiaolin Ye
The main purpose of this paper is to present a new wood defect recognition method. Moreover, the results of our proposed method presented here were good or considerably better than the results obtained by the other two methods. The experimental results show our proposed method has better robust to the...
Distances Tree as SVM Ensemble in Digits Recognition Task
Marcin Jerzy Luckner
This paper presents several algorithms that create a classification system based on SVM classifiers grouped in a tree structure. Analysis of similarity between classes allows to reduce of number of used SVM in comparison to DAGSVM method without major reduction of an accuracy. Practical tests of map...
Image Segmentation Based on Pulse Coupled Neural Network
Dansong Cheng, Wei Zhao, Xianglong Tang, Jiafeng Liu
A completely automatic segmentation method for breast ultrasound images using region growing
Juan Shan, H.D. Cheng, Yuxuan Wang
In this paper, we propose a fully automatic segmentation algorithm of masses on breast ultrasound images by using region growing technique. First, a seed point is selected automatically from the mass region based on both textural features and spatial features. Then, from the selected seed point, a region...
Ultrasound Speckle Reduction Based on Image Segmentation and Diffused Region Growing
Xiaoying Li, Dong C. Liu
This paper presents an adaptive speckle reduction method through diffused growing region filtering based on image segmentation. The main idea is to smooth the speckle regions adaptively and preserve the edge and tissue structure. The criterion of speckle region is defined from a similarity value obtained...
Texture and Motion Pattern Fusion for Background Subtraction
Bineng Zhong, Xiaopeng Hong, Hongxun Yao, Shiguang Shan, Xilin Chen, Wen Gao
In this paper, we propose a novel background subtraction algorithm, which takes both texture and motion information into account. Texture information is represented by local binary pattern (LBP), which is tolerant of illumination changes and is computational simplicity. Assuming that there is significant...
A Face Detection Method Based on Skin Color Model
Dazhi Zhang, Boying Wu, Jiebao Sun, Qinglei Liao
Face detection plays a very important role in pattern recognition and the precision of face detection directly affects the following results. This paper proposes a fast and precise method of face detection in complex background based on skin color model. Firstly, we extract skin color regions of the...
HIT-AVDB-II: A New Multi-view and Extreme Feature Cases Contained Audio-Visual Database for Biometrics
Xiaoxin Lin, Hongxun Yao, Xiaopeng Hong, Qian Wang
For research on the proper law of audio-visual speech and biometrics technology, and evaluation of algorithms and sys-tems, we construct a multi-language and multi-view database HIT-AVDB-II with a corpus of various common and special sentences include Chinese and English poems, tongue twister, digits,...
An Extended Fuzzy Logic Method for Watershed
Ling Zhang, Ming Zhang, H.D. Cheng
Fuzzy Logic was intruded by Lotfi A. Zadeh in 1965. It is for solving uncertainty and ambiguity problems. Fuzzy logic is a multivalued logic defined in . However, there are a lot of paradoxes, as proposition, can not be described in Fuzzy Logic. In this paper, we will define an extended fuzzy logic and...
Fast Synthesis and Rendering of BTF on Arbitrary Surfaces
Zhan Zhang, Yue Qi, Yong Hu
Probability Estimation in Arithmetic Coding and Its Application
Feifei Zhou, Rui Yang, Bo Li
Arithmetic coding is an indispensable part of high performance data compression, which theoretically could encode data close to Shannon entropy. In arithmetic coding, probability estimation is an important step, because it determines coding efficiency directly. The paper discusses the probability estimation...
The Application of Histogram on Rain Detection in Video
Xudong Zhao, Peng Liu, Jiafeng Liu, Tang Xianglong
Rain, which is randomly distributed and falls at high speed, behaves complex in video and makes the work of rain detection hard. The improved histogram model is proposed for detection and removal of rain in video. The properties of this model, which are suitable for both stationary and dynamic scenes,...
Photo Traveler: A System for Exploring Photos in 3D
Shuang He, Yue Qi, Fei Hou
This paper presents a system - Photo Traveler - for exploring large photo col-lections of a scene with a visceral 3D sense. Based on 3d-reconstruction, Photo Traveler managed to rearrange those pho-tos in 3D scene, enabling the user to ex-plore photos as if looking through the real cameras, and move...
A novel particle filter based people tracking method through occlusion
Yuru Wang, Wei Zhao, Jiafeng Liu, Xianglong Tang, Peng Liu
A novel multi-regions based particle filters that effectively deals with occlusion problem in people tracking has been proposed in this paper. After locating multiple key regions, the algorithm uses several nearly independent particle filters (NIPF) to track each region which will be influenced by the...
Evaluation of Risk Area by Myocardial Contrast Echocardiography with a New Computer-aided Method
Jia-Wei Tian, Guo-Qing Du, Ying Liu, Min Ren, Ying Wang, Meng Zhang, Xiang-Long Tang, H.D. Cheng, Yan-Hui Guo
Evaluation of Risk Area by Myocardial Contrast Echocardiography with a New Computer-aided Method
Adaptive frequency domain filtering of legacy cosmic ray recordings
This paper describes an adaptive frequency domain filtering method to enhance the scale and hour lines as well as the data trace prior to their segmentation and extraction.
The Digital Database for Breast Ultrasound Image
Jia-wei Tian, Ying Wang, Jian-hua Huang, Chun-ping Ning, Han-mei Wang, Yan Liu, Xiang-long Tang
The Digital Database for Breast Ultrasound Image (DDBUI) is a database of digitized screen sonography with associated ground truth and some other information. The DDBUI project is a collaborative effort involving the Harbin Institute of Technology and the Second Affiliated Hospital of Harbin Medical...
Effect of a Novel Segment Algorithm on Radiologist’s Diagnosis of Masses Using Breast Ultrasound Imaging
Jia-Wei Tian, Chun-Ping Ning, Yan-Hui Guo, Xiang-Long Tang, Ying Wang, H.D. Cheng
To investigate the effect of using a novel segment algorithm on radiologists’ sensitivity and specificity for discriminating malignant masses from benign masses using breast ultrasound (BUS) imaging. 510 conventional BUS images acquired from 109 masses were processed by the novel segment algorithm. Five...
Classification of Breast Masses Using Color Doppler Flow Imaging
Yingtao Zhang, H. D. Cheng, Yan-Hui Guo, Jiawei Tian, Jianhua Huang, Bo Liu, Yanxin Su
A New Image Binarization Method Using Histogram and Spectral Clustering
Rui Wu, Fang Yin, Jianhua Huang, Xianglong Tang
A novel approach of binarization for gray images is presented in this paper. The proposed algorithm uses the normalized graph cut(Ncut) as the measure for spectral clustering, and the weighted matrix used in evaluating the graph cuts is based on the gray levels of an image, rather than the image pixels...
A novel feature-level multiple HMMs classifier for Lipreading based on Ada-Boost Gabor kernels selection
Shengping Zhang, Hongxun Yao
In this paper, a novel feature-level Multiple HMMs classifier for lipreading is presented. Firstly, it subdivides mouth images into four non-overlapping subblocks. Then AdaBoost is used to adaptively select optimal Gabor kernels from four subblocks convolved with different Gabor kernel functions and...
The Study of Regional Structures Identification by Using Remote Sensing Images in Metallogenic Deposit Prognosis
Dongdai Zhou, Wei Zhao, Shaochun Zhong, Sunsun Li
This paper presents a regional structures identification model by using remote sensing images, and the method of automatic extracting feature information from remotesensing images, and recognizing regional structures through spatial correlative analysis with gravitation, magnetic information.
Regional Gravity Structure Interpretation for Mineral Resource Prognosis Using Neural Network
Dongdai Zhou, Shaochun Zhong, Yangling Li, Xiaochun Cheng
In this paper, a correlative structure model based on regional gravity information is generated using back-propagation neural network. The gravity bouguer anomalies of samples are analyzed. The result has been used to process the 1:1,000,000 gravity horizontal derivation maps of the mining areas in the...
Discrimination of Outer Membrane Proteins using Reformulated Support Vector Machine based on Neutrosophic Set
Wen Ju, H. D. Cheng
Neutrosophic logic is introduced in 1995 as a generalization of fuzzy logic. It includes a new component as neutralities. In this paper, we propose a novel neutronsophic set for SVM inputs and combine it with the reformulated SVM which treats samples differently according to the weighting function. The...
Land Covers Classification for Remote Sensing Images Based on Spectral and Textural Information
Wei Zhao, Shumei Cui
In this paper, the classifiers for land/water and natural land/artificial land combined the texture measures with spectral analysis for remote sensing images have been built. The specific recognition has been designed in order to take advantages of both analyses. Moreover, coastal line development analysis,...
Application of Decision Trees in Mining High-Value Credit Card Customers
Jian Wang, Bo Yuan, Wenhuang Liu
Along with the rapid growth of credit card market in China, each bank has al-ready accumulated a large number of cus-tomers. Since it is well known that the majority of the profit usually comes from a small portion of the customers, how to identify high-value customers is an im-portant issue to be addressed...
Predicting Credit Card Customer Loyalty Using Artificial Neural Networks
Tao Zhang, Bo Yuan, Wenhuang Liu
Customer loyalty is one of the key factors in customer retention and segmentation. However, quantitative research in this area based on non-subjective data has been rare in the literature. This paper shows how back propagation neural networks can be used to predict the loyalty level of credit card customers...
A Multi-theory Based Definition of Key Stuff in Enterprise
Zhen Wang, Baiqing Sun
Under the environment of hypercompeti-tion, key stuff in one enterprise has al-ready become a key factor of competition between enterprises. But there are so many issues on the definition of key stuff that the enterprise can’t effectively ad-ministrate them and have them work in full potentiality. As...
Discovering Intraday Price Patterns by Using Hierarchical Self-Organizing Maps
Chueh-Yung Tsao, Chih-Hao Chou
Motivated from the financial literature about the intraday trading behavior, we use the hierarchical self-organizing maps to detect the price patterns during three trading periods, namely, the opening, the middle, and the close of the market. It is found from the empirical study that the three trading...
A Study on the Analysis System of the Harmony Integration in Privacy Enter-prise Senior Team
Zhen Wang, Wenming Li, Bo Pang
In order to control the development of the private enterprise senior team integration, the leaders of private enterprise must build the analytical system of the harmo-nious integration. The author try to deeply research the structure, levels, es-timating index of the system based on the harmonious theory,...
Study on the Influencing Factors of Online Shopping
Na Wang, Dongchang Liu, Jun Cheng
With the rapid development of network technology, electronic commerce and e-marketing had been formed and developed gradually. The number of Internet users was increasing and wound soon overtake the United States as the world's second-largest national Internet users. however the Chinese Internet users...
Evaluating the Independent Intellectual Property base on Multiple Goals Decision-Making Method Model for Mechanical and Electrical Enterprises in Jilin Province
Jing Kang, Na Wang, Fuxia Wei
This article introduced Multiple Goals Decision- Making Method applying in the analysis of intellectual property of Jilin Province. First it was established evaluation index system of intellectual property, made the appropriate assignment to the influencing goals of the intellectual property by using...
The panel data analysis of the regional in-surance differences on the basis of de-mand point
Baiqing Sun, Yange Li, Lin Zhang
A Comparative Study on the IPO Pricing Efficiency between China and Hong Kong Stock Market
Xiaosheng Zhang, Tong Li
This paper carries on a comparative study between China and HK stock market, aiming at finding out the structural discrepancy between the two. The empirical study results as follows: the IPO price in China focuses on the internal factor of firm, little information in the issue factor and market factor....
Feature Extraction and Discovery of microRNAs Using Nonnegative Matrix Factorization
Weixiang Liu, Tianfu Wang, Siping Chen, Aifa Tang
Novel and Significant Spermatogenesis-related Gene Selection and Confirmation with Microarrays
Weixiang Liu, Aifa Tang, Kehong Yuan, Datian Ye
Distance matrix analysis of mutual secondary structure pairs for multiple structure alignment
Chiang-Man Sun, Tun-Wen Pai, Jen-Chun Hung, Ying-Tsang Lo, Po-Hung Chen
The main goal of the proposed system is to enhance the mutual correlation of sec-ondary structure element (SSE) pairs for multiple structure alignment. The algo-rithm utilizes the local matching advan-tages through distance matrix approach to extract suitable candidates of SSE pairs. The similarity scores...
Predicting Protein Subcellular Localization using PsePSSM and Support Vector Machines
Eric Y.T. Juan, J.H. Jhang, W.J. Li
CMAP and FCMAP Comparisons Using Monte-Carlo Simulations
Functional Residue Prediction by Multiple Sequence Alignment for Carbohydrate Binding Modules
WI Chou, WY Chou, SC Lin, TY Jiang, CY Tang, Margaret DT Chang
Multiple sequence alignment is often used to locate consensus sequence stretches with evolutionary and functional conservation. However, when sequence similarity among the queries becomes low, sequence alignment tools generate extremely diverse results. The aim of this study is to incorporate relevant...
Research on SVM Algorithm with Particle Swarm Optimization
Yongjie Zhai, Hai-li Li, Qian Zhou
Support Vector Machines (SVM) is a practical algorithm that has been widely used in many areas. To guarantee its satisfying performance, it is important to set appropriate parameters of SVM algorithm. Sequential Minimal Optimization (SMO) is an effective training algorithm belonging to SVM, so is LS_SVM....
Deadlock Avoidance of a Kind of JSP with Multi-resources Sharing
Jing Li, Hejiao Huang, Farooq Ahmad
This paper presents the scheduling problem with multi-resource sharing, which each operation may need more than one kinds of resource. Timed Petri net is used to formulate this problem to analyze deadlock and minimize the makespan. A deadlock avoidance policy addressed here consists of three stages:...
Soft Instrument for the Flue Gas Oxygen of Power Plant Based On Improved SMO Algorithm
Yongjie Zhai, Hong Qiao, Haili Li, Guorui Ji, Pu Han
As to the problem that normal SVM algorithm has a high computational complexity with large scale data and the method of selecting parameters of the study machine is complexity,we improved the SMO algorithm in two aspects of structure and parametric selection to increase operational speed and efficiency...
Convergence Analysis for Generalized Ant Colony Optimization Algorithm
A new algorithm is proposed, which is called Generalized Ant Colony Optimization (GACO) algorithm. Two new functions are presented to model the behavior for describing the pheromone evaporation and pheromone added to the edges that belong to the best-so-far solution. A class of strictly increasing function...
A Link Structure Based Website Topic Hierarchy Extracting Approach
Zhao Xu, Qingcai Chen, Hongzhi Guo
Visualizing hierarchy of a website is very helpful for both users’ navigating and search engine efficiently presenting results. In this paper, treating webpages as nodes and hyperlinks as directed edges, the link structure is firstly modeled as weighted directed graph. Considering multiple website features,...
A Phrase Combination Approach to Patent SMT
Junguo Zhu, Muyun Yang, Tiejun Zhao, Sheng Li, Qi Haoliang
This paper presents a phrase combination approach to patent SMT (Statistical Ma-chine Translation) for Japanese to English. To minimize the segmentation problems caused by the rich OOV (out-of-vocabulary) words in the patent texts, the character based translation phrases are first introduced to avoid...
Chinese Chunking Algorithm Based on Cascaded Conditional Random Fields
Guanglu Sun, Yuanchao Liu, Peili Qiao, Fei Lang
This paper presents a new Chinese chunking algorithm based on cascaded conditional random fields. Conditional random fields solve the tagging problems well, while the cascaded models restrain the affection of part-of-speech errors. The experimental results show that this approach achieves impressive...
Chinese Part-of-speech Tagging Based on Fusion Model
Guanglu Sun, Fei Lang, Peili Qiao, Zhiming Xu
This paper proposes a new part-of-speech tagging algorithm based on the fusion model which combines Maximum Entro-py model and Error Correction model. According to the analysis of the two models, the fusion tagging model is uti-lized with the profits of conditional prob-ability model and rule based model....