11th Joint International Conference on Information Sciences

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123 articles

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

Kemal Kilic
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

Hsin-Lung Liu, Shih-Tong Lu, Cheng-Wei Lin
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

K.K.F. YUEN
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

Weimin Wu
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...