Dynamic model error and observation model error was the main factor to badly pollute the precision of orbit determination, especially in space based observation. Model error compensation technology was researched by designing semi-parametric orbit determination regression model. Stahel-Donoho Kernel estimator was applied to solve the semi-parametric model, which can effectively estimate the model error and restrain the gross error. Simulation Experiments was processed under space based surveillance system, and results proved that the Stahel-Donoho Kernel estimator can improve the precision of orbit determination largely.
{"title":"Satellite Orbit Determination Based on Stahel–Donoho Kernel Estimator","authors":"Xiaogang Pan, Haiyin Zhou","doi":"10.1109/WKDD.2009.225","DOIUrl":"https://doi.org/10.1109/WKDD.2009.225","url":null,"abstract":"Dynamic model error and observation model error was the main factor to badly pollute the precision of orbit determination, especially in space based observation. Model error compensation technology was researched by designing semi-parametric orbit determination regression model. Stahel-Donoho Kernel estimator was applied to solve the semi-parametric model, which can effectively estimate the model error and restrain the gross error. Simulation Experiments was processed under space based surveillance system, and results proved that the Stahel-Donoho Kernel estimator can improve the precision of orbit determination largely.","PeriodicalId":143250,"journal":{"name":"2009 Second International Workshop on Knowledge Discovery and Data Mining","volume":"45 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2009-01-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128971254","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
A novel blind robust 3D mesh object watermarking method is proposed. Firstly, we choose the prongs of the mesh; secondly, to suppose that the prongs are the centers of the circle and the length we choose is the radius, we can get the areas which could be watermarked; and then, with the sphere coordinate, we will get the distance from the object center to the vertices, and perform DFT on the sphere radiuses; the watermark will be embedded by changing the DFT frequency coefficients. Experimental results show that this watermarking scheme is robust against the attacks such as rotation, translation, uniform scaling and even cropping and the embedded watermark is invisible.
{"title":"Blind Mesh Watermarking Based on the Featured Points in the Frequency Domain","authors":"Guangfu Ren, Cai-ming Zhang, Xingqiang Yang","doi":"10.1109/WKDD.2009.188","DOIUrl":"https://doi.org/10.1109/WKDD.2009.188","url":null,"abstract":"A novel blind robust 3D mesh object watermarking method is proposed. Firstly, we choose the prongs of the mesh; secondly, to suppose that the prongs are the centers of the circle and the length we choose is the radius, we can get the areas which could be watermarked; and then, with the sphere coordinate, we will get the distance from the object center to the vertices, and perform DFT on the sphere radiuses; the watermark will be embedded by changing the DFT frequency coefficients. Experimental results show that this watermarking scheme is robust against the attacks such as rotation, translation, uniform scaling and even cropping and the embedded watermark is invisible.","PeriodicalId":143250,"journal":{"name":"2009 Second International Workshop on Knowledge Discovery and Data Mining","volume":"33 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2009-01-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129101769","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Facial symmetry can be regarded as a not absolute but useful and natural feature. In this paper, this symmetrical feature is applied to two-dimensional linear discriminant analysis (2DLDA) for face image feature extraction, furthermore, the distance measure (DM) and Frobenius-norm measure(FM) are also developed to classify faces. Symmetrical 2DLDA (S2DLDA) used pure statistical mathematical technique (just like 2DLDA), as well as the characters of face image (just like SLDA), to improve the recognition performance. The typical similarity measure used in 2DLDA is applied to S2DLDA, which is the sum of the Euclidean distance between two feature vectors in feature matrix, called DM. The similarity measure based on Frobenius-norm is also developed to classify face images for S2DLDA. To test their performance, experiments are performed on YALE and ORL face databases. The experimental results show that when DM is used, S2DLDA has the potential to outperform 2DLDA.
{"title":"Symmetrical 2DLDA Using Different Measures in Face Recognition","authors":"Jicheng Meng, Li Feng","doi":"10.1109/WKDD.2009.195","DOIUrl":"https://doi.org/10.1109/WKDD.2009.195","url":null,"abstract":"Facial symmetry can be regarded as a not absolute but useful and natural feature. In this paper, this symmetrical feature is applied to two-dimensional linear discriminant analysis (2DLDA) for face image feature extraction, furthermore, the distance measure (DM) and Frobenius-norm measure(FM) are also developed to classify faces. Symmetrical 2DLDA (S2DLDA) used pure statistical mathematical technique (just like 2DLDA), as well as the characters of face image (just like SLDA), to improve the recognition performance. The typical similarity measure used in 2DLDA is applied to S2DLDA, which is the sum of the Euclidean distance between two feature vectors in feature matrix, called DM. The similarity measure based on Frobenius-norm is also developed to classify face images for S2DLDA. To test their performance, experiments are performed on YALE and ORL face databases. The experimental results show that when DM is used, S2DLDA has the potential to outperform 2DLDA.","PeriodicalId":143250,"journal":{"name":"2009 Second International Workshop on Knowledge Discovery and Data Mining","volume":"7 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2009-01-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124345544","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
This paper proposes a three-party quantum secret sharing scheme based on entanglement without local unitary operations. The message sender prepares the entangled states and sends them to the agents, who can obtain the secret message by only performing measurement on their photons if all of the agents collaborate. In contrast to the use of local unitary operations in most of other schemes, our scheme is more convenient for the information receivers.
{"title":"Quantum Secret Sharing Based on Entanglement without Local Unitary Operations","authors":"Yunyan Yang, Guisheng Yin, Ting-quan Deng","doi":"10.1109/WKDD.2009.106","DOIUrl":"https://doi.org/10.1109/WKDD.2009.106","url":null,"abstract":"This paper proposes a three-party quantum secret sharing scheme based on entanglement without local unitary operations. The message sender prepares the entangled states and sends them to the agents, who can obtain the secret message by only performing measurement on their photons if all of the agents collaborate. In contrast to the use of local unitary operations in most of other schemes, our scheme is more convenient for the information receivers.","PeriodicalId":143250,"journal":{"name":"2009 Second International Workshop on Knowledge Discovery and Data Mining","volume":"237 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2009-01-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121984252","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Aimed at the intrusion behaviors are characterized with uncertainty, complexity, diversity and dynamic tendency and the advantages of wavelet neural network (WNN), an intrusion detection method based on WNN is presented in this paper. Moreover, we adopt a algorithm of reduce the number of the wavelet basic function by analysis the sparseness property of sample data which can optimize the wavelet network in a large extent, and the learning algorithm based on the gradient descent was used to train network. We discussed and analyzed the impact factor of intrusion behaviors. With the ability of strong nonlinear function approach and fast convergence rate of WNN, the intrusion detection method based on WNN can detect various intrusion behaviors rapidly and effectively by learning the typical intrusion characteristic information. The experimental result shows that this intrusion detection method is feasible and effective.
{"title":"Intrusion Detection Method Based on Wavelet Neural Network","authors":"Jianjing Sun, Han Yang, Jingwen Tian, Fan Wu","doi":"10.1109/WKDD.2009.214","DOIUrl":"https://doi.org/10.1109/WKDD.2009.214","url":null,"abstract":"Aimed at the intrusion behaviors are characterized with uncertainty, complexity, diversity and dynamic tendency and the advantages of wavelet neural network (WNN), an intrusion detection method based on WNN is presented in this paper. Moreover, we adopt a algorithm of reduce the number of the wavelet basic function by analysis the sparseness property of sample data which can optimize the wavelet network in a large extent, and the learning algorithm based on the gradient descent was used to train network. We discussed and analyzed the impact factor of intrusion behaviors. With the ability of strong nonlinear function approach and fast convergence rate of WNN, the intrusion detection method based on WNN can detect various intrusion behaviors rapidly and effectively by learning the typical intrusion characteristic information. The experimental result shows that this intrusion detection method is feasible and effective.","PeriodicalId":143250,"journal":{"name":"2009 Second International Workshop on Knowledge Discovery and Data Mining","volume":"12 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2009-01-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121599810","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Based on summing-up the theory of knowledge management of venture enterprise, this paper does a research on growing-up mechanism of venture enterprise based on knowledge management, and argues that the growing-up process of venture enterprise is aiming at encouraging the growth of venture enterprise in the end through gaining market competitive advantage by means of acquisition and transformation of knowledge and resource. Moreover, it analyses the fostering means of venture enterprise based on knowledge management and sets up value adding mechanism of venture capitalist, in which arranging follow-up financing and assisting enterprise to win over potential customers and suppliers is in favor of improving enterprise competence in acquiring resource and knowledge; enterprise’s transforming capability will be enhanced by making development strategy and monitoring its operating and financial performance; and recruiting core member for management team is crucial for both enterprise’s acquiring and transforming competence.
{"title":"Research on Growing-up Mechanism and Fostering of Venture Enterprise Based on Knowledge Management","authors":"Qing Yang, Yanling Yu, Wenjun Chen","doi":"10.1109/WKDD.2009.21","DOIUrl":"https://doi.org/10.1109/WKDD.2009.21","url":null,"abstract":"Based on summing-up the theory of knowledge management of venture enterprise, this paper does a research on growing-up mechanism of venture enterprise based on knowledge management, and argues that the growing-up process of venture enterprise is aiming at encouraging the growth of venture enterprise in the end through gaining market competitive advantage by means of acquisition and transformation of knowledge and resource. Moreover, it analyses the fostering means of venture enterprise based on knowledge management and sets up value adding mechanism of venture capitalist, in which arranging follow-up financing and assisting enterprise to win over potential customers and suppliers is in favor of improving enterprise competence in acquiring resource and knowledge; enterprise’s transforming capability will be enhanced by making development strategy and monitoring its operating and financial performance; and recruiting core member for management team is crucial for both enterprise’s acquiring and transforming competence.","PeriodicalId":143250,"journal":{"name":"2009 Second International Workshop on Knowledge Discovery and Data Mining","volume":"4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2009-01-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130289284","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
According to the absolute income hypotheses of J. M. Keynes, it constructed the consumption model of Chinese urban households by using the statistical data from 1990 to 2007, and studied the long-term equilibrium as well as short-term fluctuations between per capita annual living expenditure and annual per capita disposable income of urban households in China. The result of Granger causality test showed that the disposable income Granger caused the living expenditure. The result of cointegration test showed that there was a long-term stable equilibrium relationship between the living expenditure and disposable income. Marginal preference of consumption was 0.69. Spontaneous consumption was RMB 271.93 yuan. Error correction model showed that the short-term fluctuations of income levels had a significant positive effect on living expenditure. If the current consumption level has deviation from the long-term equilibrium value by RMB 1 yuan, it will be corrected by RMB 0.52 yuan next year.
{"title":"Research on Consumption Model about Urban Households Based on Keynes' Absolute Income Hypotheses in China","authors":"Junping Zhao","doi":"10.1109/WKDD.2009.119","DOIUrl":"https://doi.org/10.1109/WKDD.2009.119","url":null,"abstract":"According to the absolute income hypotheses of J. M. Keynes, it constructed the consumption model of Chinese urban households by using the statistical data from 1990 to 2007, and studied the long-term equilibrium as well as short-term fluctuations between per capita annual living expenditure and annual per capita disposable income of urban households in China. The result of Granger causality test showed that the disposable income Granger caused the living expenditure. The result of cointegration test showed that there was a long-term stable equilibrium relationship between the living expenditure and disposable income. Marginal preference of consumption was 0.69. Spontaneous consumption was RMB 271.93 yuan. Error correction model showed that the short-term fluctuations of income levels had a significant positive effect on living expenditure. If the current consumption level has deviation from the long-term equilibrium value by RMB 1 yuan, it will be corrected by RMB 0.52 yuan next year.","PeriodicalId":143250,"journal":{"name":"2009 Second International Workshop on Knowledge Discovery and Data Mining","volume":"8 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2009-01-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132779250","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
In this paper, the feasibility of using probabilistic causal-effect model is studied and we apply it in particle swarm optimization algorithm (PSO) to classify the faults of mine hoist. In order to enhance the PSO performance, we propose the probability function to nonlinearly map the data into a feature space in probabilistic causal-effect model, and with it, fault diagnosis is simplified into optimization problem from the original complex feature set. The proposed approach is applied to fault diagnosis, and our implementation has the advantages of being general, robust, and scalable. The raw datasets obtained from mine hoist system are preprocessed and used to generate networks fault diagnosis for the system. We studied the performance of the improved PSO algorithm and generated a Probabilistic Causal-effect network that can detect faults in the test data successfully. It can get ≫90% minimal diagnosis with cardinal number of fault symptom sets greater than 25.
{"title":"Application of an Improved Particle Swarm Optimization for Fault Diagnosis","authors":"Chu-jiao Wang, Shi-Xiong Xia","doi":"10.1109/WKDD.2009.15","DOIUrl":"https://doi.org/10.1109/WKDD.2009.15","url":null,"abstract":"In this paper, the feasibility of using probabilistic causal-effect model is studied and we apply it in particle swarm optimization algorithm (PSO) to classify the faults of mine hoist. In order to enhance the PSO performance, we propose the probability function to nonlinearly map the data into a feature space in probabilistic causal-effect model, and with it, fault diagnosis is simplified into optimization problem from the original complex feature set. The proposed approach is applied to fault diagnosis, and our implementation has the advantages of being general, robust, and scalable. The raw datasets obtained from mine hoist system are preprocessed and used to generate networks fault diagnosis for the system. We studied the performance of the improved PSO algorithm and generated a Probabilistic Causal-effect network that can detect faults in the test data successfully. It can get ≫90% minimal diagnosis with cardinal number of fault symptom sets greater than 25.","PeriodicalId":143250,"journal":{"name":"2009 Second International Workshop on Knowledge Discovery and Data Mining","volume":"84 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2009-01-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131098766","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
In order to improve the precision of model test of the water conservancy project, accelerate the speed of experiment, through bringing in the theory of Multi-Agent, this paper has proposed a kind of new-type Automatic Control System of Water Project Model based on Multi-Agent. This automatic System is made up of Monitoring Agent Federation, namely System control Agent, Flow control Agent, Water Level control Agent and Velocity of flow control Agent. System controls Agent is responsible for automatic control of the whole water project model test, other three control Agent mainly finish the task of testing and regulating the flow, water level and velocity of flow, and sending the final result to System control Agent, making the normal running of model test of the water project. This system has many communication advantages such as being swift, with convenient coordination, is of greater practical value to reach real automation of water project model test.
{"title":"Automatic Control System of Water Conservancy Project Model Based on Multi Agent","authors":"Junhu Yang, Lizhi Yang, T. Zhao, Zhiqiang Jia","doi":"10.1109/WKDD.2009.204","DOIUrl":"https://doi.org/10.1109/WKDD.2009.204","url":null,"abstract":"In order to improve the precision of model test of the water conservancy project, accelerate the speed of experiment, through bringing in the theory of Multi-Agent, this paper has proposed a kind of new-type Automatic Control System of Water Project Model based on Multi-Agent. This automatic System is made up of Monitoring Agent Federation, namely System control Agent, Flow control Agent, Water Level control Agent and Velocity of flow control Agent. System controls Agent is responsible for automatic control of the whole water project model test, other three control Agent mainly finish the task of testing and regulating the flow, water level and velocity of flow, and sending the final result to System control Agent, making the normal running of model test of the water project. This system has many communication advantages such as being swift, with convenient coordination, is of greater practical value to reach real automation of water project model test.","PeriodicalId":143250,"journal":{"name":"2009 Second International Workshop on Knowledge Discovery and Data Mining","volume":"55 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2009-01-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133282366","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Markowitz proposed the theory of asset portfolio via a mean-variance model for security investment combination in 1952. The issue of security investment is still challenging till now. Intelligence algorithms were flourishing in resent years. Particle Swarm Optimization (PSO) is inspired by social behavior of bird flocking or fish schooling. It is co-operative, population-based global search swarm intelligence meta-heuristics and is applied to solve the model. Based on the theory PSO algorithm mentioned above, a multi-factor and optimal model for portfolio investment in the condition of considering friction factors in China’s security market is established. Additionally, the model is implemented on the demonstrated research of the index stock of index 30, the result could provide scientific foundation for security investment.
{"title":"Research on Optimizing Security Investment Combination Based on PSO","authors":"Zehong Li, Weice Ni","doi":"10.1109/WKDD.2009.109","DOIUrl":"https://doi.org/10.1109/WKDD.2009.109","url":null,"abstract":"Markowitz proposed the theory of asset portfolio via a mean-variance model for security investment combination in 1952. The issue of security investment is still challenging till now. Intelligence algorithms were flourishing in resent years. Particle Swarm Optimization (PSO) is inspired by social behavior of bird flocking or fish schooling. It is co-operative, population-based global search swarm intelligence meta-heuristics and is applied to solve the model. Based on the theory PSO algorithm mentioned above, a multi-factor and optimal model for portfolio investment in the condition of considering friction factors in China’s security market is established. Additionally, the model is implemented on the demonstrated research of the index stock of index 30, the result could provide scientific foundation for security investment.","PeriodicalId":143250,"journal":{"name":"2009 Second International Workshop on Knowledge Discovery and Data Mining","volume":"28 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2009-01-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114760679","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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