Pub Date : 2010-05-22DOI: 10.1109/IWISA.2010.5473721
Chunliang Jiang, Hanhong Jiang, Chaoliang Zhang, Song Zhao
In order to improve the efficiency and accuracy of warship target detection in sea-sky background,and according to the obvious gray scale contrast between the sky region and the sea region, this paper operate the division of the two regional context by looking for low-water mark of the histogram's Valley, which is one feature of the histogram called "Two Peaks and a Valley". Then the method obtains the statistics and classification of background pixels, and selects the relevant parameters to establish Gaussian model A and parameter model B. Model A is used to complete the perception of invasion target and to transmit the relevant information to model B immediately,then the model B distinguishes the target with labeling. The experimental results show that the algorithm has a good ability to adapt to the environment, easy to implement and accurate at target detection.
{"title":"Dual-Model Detection Method of Warship Target in the Sea-Sky Background","authors":"Chunliang Jiang, Hanhong Jiang, Chaoliang Zhang, Song Zhao","doi":"10.1109/IWISA.2010.5473721","DOIUrl":"https://doi.org/10.1109/IWISA.2010.5473721","url":null,"abstract":"In order to improve the efficiency and accuracy of warship target detection in sea-sky background,and according to the obvious gray scale contrast between the sky region and the sea region, this paper operate the division of the two regional context by looking for low-water mark of the histogram's Valley, which is one feature of the histogram called \"Two Peaks and a Valley\". Then the method obtains the statistics and classification of background pixels, and selects the relevant parameters to establish Gaussian model A and parameter model B. Model A is used to complete the perception of invasion target and to transmit the relevant information to model B immediately,then the model B distinguishes the target with labeling. The experimental results show that the algorithm has a good ability to adapt to the environment, easy to implement and accurate at target detection.","PeriodicalId":298764,"journal":{"name":"2010 2nd International Workshop on Intelligent Systems and Applications","volume":"3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-05-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117033535","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}
Pub Date : 2010-05-22DOI: 10.1109/IWISA.2010.5473529
Yongqi Huang, Gaoyan Deng, Xiaochun Wu, Zhui Zhao
In future, GIS will develop in the direction of popular application. Geography information sharing has become a stringent problem needed to resolve. Because people's cognition of real geographic world is different from each other, semantic discrepancy comes into being. As a result, Realization of geography information sharing has firstly to realize GIS's semantic sharing. Geo-ontology provides generally accepted concepts in geographic information domain and explicit formalized definitions thereof, so as to resolve the problem different geographic cognition gives rise to and inter-translation problem of description logic thereof. Geo-ontology can be applied to integration and sharing of geographic information. Start with the process of abstraction and generalization from real geographic world to computer world, this paper analyzes the source of semantic heterogeneity, and introduces geographic feature and its representing generalized geographic objects. Then this paper analyzes relationships between geo-ontology and geographic feature in detail, finally lay emphasis upon research on how to use geo-ontology to represent geographic features.
{"title":"Research on Representation of Geographic Feature Based on Geo-Ontology","authors":"Yongqi Huang, Gaoyan Deng, Xiaochun Wu, Zhui Zhao","doi":"10.1109/IWISA.2010.5473529","DOIUrl":"https://doi.org/10.1109/IWISA.2010.5473529","url":null,"abstract":"In future, GIS will develop in the direction of popular application. Geography information sharing has become a stringent problem needed to resolve. Because people's cognition of real geographic world is different from each other, semantic discrepancy comes into being. As a result, Realization of geography information sharing has firstly to realize GIS's semantic sharing. Geo-ontology provides generally accepted concepts in geographic information domain and explicit formalized definitions thereof, so as to resolve the problem different geographic cognition gives rise to and inter-translation problem of description logic thereof. Geo-ontology can be applied to integration and sharing of geographic information. Start with the process of abstraction and generalization from real geographic world to computer world, this paper analyzes the source of semantic heterogeneity, and introduces geographic feature and its representing generalized geographic objects. Then this paper analyzes relationships between geo-ontology and geographic feature in detail, finally lay emphasis upon research on how to use geo-ontology to represent geographic features.","PeriodicalId":298764,"journal":{"name":"2010 2nd International Workshop on Intelligent Systems and Applications","volume":"72 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-05-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117211926","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}
Pub Date : 2010-05-22DOI: 10.1109/IWISA.2010.5473684
Qingqiu Chen, Jing Li, Yexin Gao
The paper elaborates on the principle of applying fuzzy inference to single factor prediction method in precipitation irrigation requirement forecasting. Through the introduction of prediction example, the paper showed us how to conduct a prediction process specifically. Finally, it is proved that the precision of prediction of this approach can meet the need of agricultural production.
{"title":"Study on Applying Fuzzy Inference to Single Factor Prediction Method for Precipitation Irrigation Requirement Forecast","authors":"Qingqiu Chen, Jing Li, Yexin Gao","doi":"10.1109/IWISA.2010.5473684","DOIUrl":"https://doi.org/10.1109/IWISA.2010.5473684","url":null,"abstract":"The paper elaborates on the principle of applying fuzzy inference to single factor prediction method in precipitation irrigation requirement forecasting. Through the introduction of prediction example, the paper showed us how to conduct a prediction process specifically. Finally, it is proved that the precision of prediction of this approach can meet the need of agricultural production.","PeriodicalId":298764,"journal":{"name":"2010 2nd International Workshop on Intelligent Systems and Applications","volume":"101 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-05-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116338195","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}
Pub Date : 2010-05-22DOI: 10.1109/IWISA.2010.5473439
Xiaojun Lin, Dan Li, Xihong Wu
In this paper, we propose a novel joint topical n-gram language model that combines the semantic topic information with local constraints in the training procedure. Instead of training the n-gram language model and topic model independently, we estimate the joint probability of latent semantic topic and n-gram directly. In this procedure Latent Dirichlet allocation (LDA) is employed to compute latent topic distributions for sentence instances. Not only does our model capture the long-range dependencies, it also distinguishes the probability distribution of each n-gram in different topics without leading to the problem of data sparseness. Experiments show that our model can lower the perplexity significantly and it is robust on topic numbers and training data scales.
{"title":"A Joint Topical N-Gram Language Model Based on LDA","authors":"Xiaojun Lin, Dan Li, Xihong Wu","doi":"10.1109/IWISA.2010.5473439","DOIUrl":"https://doi.org/10.1109/IWISA.2010.5473439","url":null,"abstract":"In this paper, we propose a novel joint topical n-gram language model that combines the semantic topic information with local constraints in the training procedure. Instead of training the n-gram language model and topic model independently, we estimate the joint probability of latent semantic topic and n-gram directly. In this procedure Latent Dirichlet allocation (LDA) is employed to compute latent topic distributions for sentence instances. Not only does our model capture the long-range dependencies, it also distinguishes the probability distribution of each n-gram in different topics without leading to the problem of data sparseness. Experiments show that our model can lower the perplexity significantly and it is robust on topic numbers and training data scales.","PeriodicalId":298764,"journal":{"name":"2010 2nd International Workshop on Intelligent Systems and Applications","volume":"189 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-05-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116878287","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}
Pub Date : 2010-05-22DOI: 10.1109/IWISA.2010.5473505
Xiangjian Chen, Zhijun Xu, Di Li, Kehui Long
An efficient differential recurrent neural network is developed in this paper, and the trained network can be used in the nonlinear model predictive control, and also predict the future dynamic behavior of the nonlinear process in real time. In the new training network, use Taylor series expansion and automatic differentiation techniques. The effectiveness of the differential recurrent neural network predictive model training and predictive controller demonstrated through the MAV attitude control. The differential recurrent neural network-based NMPC approach results in good control performance.
{"title":"Differential Recurrent Neural Network Based Model Predictive Control for the Control of MAV Attitude","authors":"Xiangjian Chen, Zhijun Xu, Di Li, Kehui Long","doi":"10.1109/IWISA.2010.5473505","DOIUrl":"https://doi.org/10.1109/IWISA.2010.5473505","url":null,"abstract":"An efficient differential recurrent neural network is developed in this paper, and the trained network can be used in the nonlinear model predictive control, and also predict the future dynamic behavior of the nonlinear process in real time. In the new training network, use Taylor series expansion and automatic differentiation techniques. The effectiveness of the differential recurrent neural network predictive model training and predictive controller demonstrated through the MAV attitude control. The differential recurrent neural network-based NMPC approach results in good control performance.","PeriodicalId":298764,"journal":{"name":"2010 2nd International Workshop on Intelligent Systems and Applications","volume":"5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-05-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124676247","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}
Pub Date : 2010-05-22DOI: 10.1109/IWISA.2010.5473715
Chao-bo He, Qimai Chen
According to the problem of attribute subset selection,the paper put forward a method based on evaluation of attribute significance.Based on the rough set theories the method first defined the calculation formula of attribute significance and designed the corresponding solution algorithm,whose running time complexity decreased about |U|2 orders of magnitude comparing with the similar algorithm on the same test dataset with |U| rescords.The result of application example shows that this method can reserve the condition attributes,which are important for decision attributes,and also can perform the data reduction operation effectively.
{"title":"The Method for Data Reduction Based on Evaluation of Attribute Significance","authors":"Chao-bo He, Qimai Chen","doi":"10.1109/IWISA.2010.5473715","DOIUrl":"https://doi.org/10.1109/IWISA.2010.5473715","url":null,"abstract":"According to the problem of attribute subset selection,the paper put forward a method based on evaluation of attribute significance.Based on the rough set theories the method first defined the calculation formula of attribute significance and designed the corresponding solution algorithm,whose running time complexity decreased about |U|2 orders of magnitude comparing with the similar algorithm on the same test dataset with |U| rescords.The result of application example shows that this method can reserve the condition attributes,which are important for decision attributes,and also can perform the data reduction operation effectively.","PeriodicalId":298764,"journal":{"name":"2010 2nd International Workshop on Intelligent Systems and Applications","volume":"39 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-05-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124866440","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}
Pub Date : 2010-05-22DOI: 10.1109/IWISA.2010.5473241
Anuj Mehra, Mahender Kumawat, R. Ranjan, B. Pandey, Sushil Ranjan, A. Shukla, R. Tiwari
Biometric authentication techniques such as lips, face, and eyes are more reliable and efficient than conventional authentication techniques such as password authentication, token, cards, personal identification number, etc. In this research paper, the emphasis has been laid on the speaker identification based on lip features. In this study, we have presented a detailed comparative analysis for speaker identification by using lip features, Principal Component Analysis (PCA), and neural network classifiers. PCA has been used for feature extraction from the six geometric lip features which are height of the outer corners of the mouth, width of the outer corners of the mouth, height of the inner corners of the mouth, width of the inner corners of the mouth, height of the upper lip, and height of the lower lip. These features are then used for training of the network by using different neural network classifiers such as Back Propagation (BP), Radial Basis Function (RBF) and Learning Vector Quantization (LVQ). These approaches are incorporated on "TULIPS1 database, (Movellan, 1995)" which is a small audiovisual database of 12 subjects saying the first 4 digits in English. After the detailed analysis and evaluation a maximum of 91.07% accuracy in speaker recognition is obtained using PCA and RBF. Speaker identification has a wide range of applications such as Audio Processing, Medical data, Finance, Array processing, etc.
{"title":"Expert System for Speaker Identification Using Lip Features with PCA","authors":"Anuj Mehra, Mahender Kumawat, R. Ranjan, B. Pandey, Sushil Ranjan, A. Shukla, R. Tiwari","doi":"10.1109/IWISA.2010.5473241","DOIUrl":"https://doi.org/10.1109/IWISA.2010.5473241","url":null,"abstract":"Biometric authentication techniques such as lips, face, and eyes are more reliable and efficient than conventional authentication techniques such as password authentication, token, cards, personal identification number, etc. In this research paper, the emphasis has been laid on the speaker identification based on lip features. In this study, we have presented a detailed comparative analysis for speaker identification by using lip features, Principal Component Analysis (PCA), and neural network classifiers. PCA has been used for feature extraction from the six geometric lip features which are height of the outer corners of the mouth, width of the outer corners of the mouth, height of the inner corners of the mouth, width of the inner corners of the mouth, height of the upper lip, and height of the lower lip. These features are then used for training of the network by using different neural network classifiers such as Back Propagation (BP), Radial Basis Function (RBF) and Learning Vector Quantization (LVQ). These approaches are incorporated on \"TULIPS1 database, (Movellan, 1995)\" which is a small audiovisual database of 12 subjects saying the first 4 digits in English. After the detailed analysis and evaluation a maximum of 91.07% accuracy in speaker recognition is obtained using PCA and RBF. Speaker identification has a wide range of applications such as Audio Processing, Medical data, Finance, Array processing, etc.","PeriodicalId":298764,"journal":{"name":"2010 2nd International Workshop on Intelligent Systems and Applications","volume":"31 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-05-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128549748","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}
Pub Date : 2010-05-22DOI: 10.1109/IWISA.2010.5473708
Tangjian Deng, Ling Feng, Yue Suo, Yu Chen
A smart meeting room usually refers to a working environment, which can provide meeting attendees with a highly effective information acquisition and exchange space, with an aim to improve the working and decision-making efficiency. Concerning on the needs of attendees in a smart meeting room, this paper explores the issue of how to make computing devices interoperate spontaneously based on context-awareness so as to provide users with adaptable and suitable services. We abstract devices spontaneous interoperations into three categories and present our design and implementation of a context-aware spontaneous interoperation of information devices in building a smart meeting room.
{"title":"Spontaneous Interoperation of Information Appliances in a Smart Meeting Room","authors":"Tangjian Deng, Ling Feng, Yue Suo, Yu Chen","doi":"10.1109/IWISA.2010.5473708","DOIUrl":"https://doi.org/10.1109/IWISA.2010.5473708","url":null,"abstract":"A smart meeting room usually refers to a working environment, which can provide meeting attendees with a highly effective information acquisition and exchange space, with an aim to improve the working and decision-making efficiency. Concerning on the needs of attendees in a smart meeting room, this paper explores the issue of how to make computing devices interoperate spontaneously based on context-awareness so as to provide users with adaptable and suitable services. We abstract devices spontaneous interoperations into three categories and present our design and implementation of a context-aware spontaneous interoperation of information devices in building a smart meeting room.","PeriodicalId":298764,"journal":{"name":"2010 2nd International Workshop on Intelligent Systems and Applications","volume":"53 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-05-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129586675","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}
Pub Date : 2010-05-22DOI: 10.1109/IWISA.2010.5473572
F. Yi, M. Xie, C. Wei
Through the establishment of dynamic model of tractor-semi-trailer, Laplacing transform them, finding the system transfer function; Changing in the use of tractor-semi- trailer and structural parameters, using of MATLAB programming for digital simulation, finding the root locus; Then according to the root locus changes in trends, to determine whether the system is stable and the size of the stability margin. The results showed that: Speed, tire cornering stiffness, the quality of tractor and trailer, trailer Centro -symmetric hinged points, the distance between the quality parameters such as vehicle handling and stability of the semi-trailer in different degree of influence of, selection of rational parameters can be manipulated to improve the stability of tractor-semi-trailer.
{"title":"Stability Simulation of Operation for Tractor-Semitrailer Based on Root-Locus Method","authors":"F. Yi, M. Xie, C. Wei","doi":"10.1109/IWISA.2010.5473572","DOIUrl":"https://doi.org/10.1109/IWISA.2010.5473572","url":null,"abstract":"Through the establishment of dynamic model of tractor-semi-trailer, Laplacing transform them, finding the system transfer function; Changing in the use of tractor-semi- trailer and structural parameters, using of MATLAB programming for digital simulation, finding the root locus; Then according to the root locus changes in trends, to determine whether the system is stable and the size of the stability margin. The results showed that: Speed, tire cornering stiffness, the quality of tractor and trailer, trailer Centro -symmetric hinged points, the distance between the quality parameters such as vehicle handling and stability of the semi-trailer in different degree of influence of, selection of rational parameters can be manipulated to improve the stability of tractor-semi-trailer.","PeriodicalId":298764,"journal":{"name":"2010 2nd International Workshop on Intelligent Systems and Applications","volume":"75 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-05-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127399261","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}
Pub Date : 2010-05-22DOI: 10.1109/IWISA.2010.5473610
Liang Sun, Jiafei Gan
Two-wheeled self-balancing robot is a non-stable, non-linear, strong coupling system.On the basis of building up the system structure model,kinetic equation is built up by using the Lagrange' s method,then obtaining the linearizing model in the vicinity of the balance.The control method of combining LQR and PID can effectively overcome the impact of the constraints on the system in the linearization process,and whit the controller core of DSP TMS320LF2812,the two-wheeled self-balancing robot can achieve dynamic balance whitin a larger angle range. The physical experiments results demonstrate that it can control the two-wheeled robot system in a very short period of time to get a stable dynamic equilibrium,validity and rationality of the designed controller are verified through the performance experiments of the prototype.
{"title":"Researching of Two-Wheeled Self-Balancing Robot Base on LQR Combined with PID","authors":"Liang Sun, Jiafei Gan","doi":"10.1109/IWISA.2010.5473610","DOIUrl":"https://doi.org/10.1109/IWISA.2010.5473610","url":null,"abstract":"Two-wheeled self-balancing robot is a non-stable, non-linear, strong coupling system.On the basis of building up the system structure model,kinetic equation is built up by using the Lagrange' s method,then obtaining the linearizing model in the vicinity of the balance.The control method of combining LQR and PID can effectively overcome the impact of the constraints on the system in the linearization process,and whit the controller core of DSP TMS320LF2812,the two-wheeled self-balancing robot can achieve dynamic balance whitin a larger angle range. The physical experiments results demonstrate that it can control the two-wheeled robot system in a very short period of time to get a stable dynamic equilibrium,validity and rationality of the designed controller are verified through the performance experiments of the prototype.","PeriodicalId":298764,"journal":{"name":"2010 2nd International Workshop on Intelligent Systems and Applications","volume":"18 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-05-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127303658","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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