Pub Date : 2012-05-29DOI: 10.1109/FSKD.2012.6234108
Yi Sun, Ying Wang, Liangrui Tang
As the IEEE 802.11 DCF has the disadvantage of not adjusting itself to the network load and the probability distribution of slot selection is extremely uneven, an improved algorithm based on fuzzy theory is presented. With the use of local history regarding successes or collisions in packets transmission to characterize the current network condition, a proper membership function is established to reflect the relation between network load level and the possibility of packet collision and select an appropriate slot when the node will access the shared channel. The main advantage of the proposed algorithm is that there is no need of additional overheads which means simple design and low complexity. Simulation results confirm the effectiveness of the new algorithm in elevating the network performance on normalized saturation throughput, average delay, and congestion recovery.
{"title":"An improved algorithm based on fuzzy theory for 802.11 DCF","authors":"Yi Sun, Ying Wang, Liangrui Tang","doi":"10.1109/FSKD.2012.6234108","DOIUrl":"https://doi.org/10.1109/FSKD.2012.6234108","url":null,"abstract":"As the IEEE 802.11 DCF has the disadvantage of not adjusting itself to the network load and the probability distribution of slot selection is extremely uneven, an improved algorithm based on fuzzy theory is presented. With the use of local history regarding successes or collisions in packets transmission to characterize the current network condition, a proper membership function is established to reflect the relation between network load level and the possibility of packet collision and select an appropriate slot when the node will access the shared channel. The main advantage of the proposed algorithm is that there is no need of additional overheads which means simple design and low complexity. Simulation results confirm the effectiveness of the new algorithm in elevating the network performance on normalized saturation throughput, average delay, and congestion recovery.","PeriodicalId":337941,"journal":{"name":"International Conference on Fuzzy Systems and Knowledge Discovery","volume":"51 4","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-05-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"120983659","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}
Cognitive diagnostic assessment (CDA) is an effective data mining approach in education. It aims to discover diagnostic information about students' cognitive strengths and weaknesses. A large number of CDA statistical models are developed and based on different assumptions about how attributes or combinations of attributes influence item response. However, the relationship between attributes and item response is unknown in reality. This challenges the researcher to make a conscious thought on the mechanism of item response and model selection before data analysis. This article introduced the reversible jump Markov Chain Monte Carlo (RJMCMC) method for the determination of three conjunctive diagnostic models that based on different assumptions in order to achieve better model-data fit and higher correct classification rate. Firstly, three conjunctive cognitive diagnostic models were described briefly. Secondly, the algorithm of RJMCMC for automatic model selection was established. Finally, a simulation study and an analysis of real data were presented to verify the algorithm. The simulation and the real data analysis results demonstrated that the model selection algorithm of RJMCMC can work well among three models.
{"title":"Using reversible jump MCMC for cognitive diagnostic model selection","authors":"Li-hong Song, Wen-yi Wang, Haiqi Dai, Shu-liang Ding","doi":"10.1109/FSKD.2012.6233829","DOIUrl":"https://doi.org/10.1109/FSKD.2012.6233829","url":null,"abstract":"Cognitive diagnostic assessment (CDA) is an effective data mining approach in education. It aims to discover diagnostic information about students' cognitive strengths and weaknesses. A large number of CDA statistical models are developed and based on different assumptions about how attributes or combinations of attributes influence item response. However, the relationship between attributes and item response is unknown in reality. This challenges the researcher to make a conscious thought on the mechanism of item response and model selection before data analysis. This article introduced the reversible jump Markov Chain Monte Carlo (RJMCMC) method for the determination of three conjunctive diagnostic models that based on different assumptions in order to achieve better model-data fit and higher correct classification rate. Firstly, three conjunctive cognitive diagnostic models were described briefly. Secondly, the algorithm of RJMCMC for automatic model selection was established. Finally, a simulation study and an analysis of real data were presented to verify the algorithm. The simulation and the real data analysis results demonstrated that the model selection algorithm of RJMCMC can work well among three models.","PeriodicalId":337941,"journal":{"name":"International Conference on Fuzzy Systems and Knowledge Discovery","volume":"179 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-05-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125189790","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 : 2012-05-29DOI: 10.1109/FSKD.2012.6234078
Long-ming Gui, Wen-ku Shi, W. Liu
In this paper, a Magneto-Rheological (MR) fluid semi-active suspension system was tested on a off-road vehicle to determine the performance improvements compared to passive suspensions. In the process of suspension design, ride comfort and handing stability are two conflicting considerations. MR fluid dampers are a new class of devices that more suitable for the requirements of automotive applications, including having very low power requirements. According to different driving conditions and body posture, semi-active suspension based on MR damper can coordinate the body posture angle, and reduce the vibration from suspension pass to vehicle body. This paper deals with theoretical analysis and experiments of MR fluid damper in semi-active suspension system. For the purpose of developing semi-active controller, a detailed vehicle Virtual Prototyping model with steering, frame and semi-active suspensions systems was established by vehicle dynamics simulation software SIMPACK. The co-simulation of ride comfort and handing stability showed that the semi-active suspension designed in this paper was suitable for improving the ride and handing performance simultaneously.
{"title":"A semi-active suspension design for off-road vehicle base on Magneto-rheological technology","authors":"Long-ming Gui, Wen-ku Shi, W. Liu","doi":"10.1109/FSKD.2012.6234078","DOIUrl":"https://doi.org/10.1109/FSKD.2012.6234078","url":null,"abstract":"In this paper, a Magneto-Rheological (MR) fluid semi-active suspension system was tested on a off-road vehicle to determine the performance improvements compared to passive suspensions. In the process of suspension design, ride comfort and handing stability are two conflicting considerations. MR fluid dampers are a new class of devices that more suitable for the requirements of automotive applications, including having very low power requirements. According to different driving conditions and body posture, semi-active suspension based on MR damper can coordinate the body posture angle, and reduce the vibration from suspension pass to vehicle body. This paper deals with theoretical analysis and experiments of MR fluid damper in semi-active suspension system. For the purpose of developing semi-active controller, a detailed vehicle Virtual Prototyping model with steering, frame and semi-active suspensions systems was established by vehicle dynamics simulation software SIMPACK. The co-simulation of ride comfort and handing stability showed that the semi-active suspension designed in this paper was suitable for improving the ride and handing performance simultaneously.","PeriodicalId":337941,"journal":{"name":"International Conference on Fuzzy Systems and Knowledge Discovery","volume":"25 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-05-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132224542","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 : 2012-05-29DOI: 10.1109/FSKD.2012.6234045
Peng Li, Yi Zheng, Chao Han, Lili Song, B. Cao
The Birge-Massart threshold wavelet methods were used to denoise lightning transient electrical signals, compared with the traditional de-noising methods such as Smoothing filter and FIR digital low-pass filter. The Means square error (MSE) and Magnitude error (ME) of simulation signals were calculated to compare the de-noising effect. The double exponential-decay pulse signals and Gaussian white-noise were composed as the simulating signals. The measured signals were also used to de-nosing with traditional and wavelet threshold methods. The results of simulation data and measured ones proved that the Birge-Massart threshold wavelet method was better than the traditional ones.
{"title":"Wavelet threshold methods used in lightning transient electrical signals denoising","authors":"Peng Li, Yi Zheng, Chao Han, Lili Song, B. Cao","doi":"10.1109/FSKD.2012.6234045","DOIUrl":"https://doi.org/10.1109/FSKD.2012.6234045","url":null,"abstract":"The Birge-Massart threshold wavelet methods were used to denoise lightning transient electrical signals, compared with the traditional de-noising methods such as Smoothing filter and FIR digital low-pass filter. The Means square error (MSE) and Magnitude error (ME) of simulation signals were calculated to compare the de-noising effect. The double exponential-decay pulse signals and Gaussian white-noise were composed as the simulating signals. The measured signals were also used to de-nosing with traditional and wavelet threshold methods. The results of simulation data and measured ones proved that the Birge-Massart threshold wavelet method was better than the traditional ones.","PeriodicalId":337941,"journal":{"name":"International Conference on Fuzzy Systems and Knowledge Discovery","volume":"666 ","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-05-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114098190","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 : 2012-05-29DOI: 10.1109/FSKD.2012.6234175
Zhiying Lu, Yuanxun Zhu, Hongmin Ma
With the rapid development of radar technology, the radar data people can access is growing exponentially. For a mass of high-dimensional data, it is necessary to reduce the data dimension while maintaining the data information in order to minimize the impact of the dimension disasters. The detection method of the strong convective weather (hailstone and rainstorm) is based on manifold learning algorithm in this paper. Firstly the dimension of 22-dimensional features of the strong convective weather is reduced by manifold learning algorithm-Local Tangent Space Alignment, then in low-dimensional (8-dimensional) data space the useful and hidden rules for the detection of strong convective weather is dig out, finally the effective rules are obtained to detect the strong convective weather. Compared with the non-dimensionality reduction method, the proposed method improves the detection accuracy and reduces the time complexity through experimental test.
{"title":"Detection of strong convective weather based on manifold learning","authors":"Zhiying Lu, Yuanxun Zhu, Hongmin Ma","doi":"10.1109/FSKD.2012.6234175","DOIUrl":"https://doi.org/10.1109/FSKD.2012.6234175","url":null,"abstract":"With the rapid development of radar technology, the radar data people can access is growing exponentially. For a mass of high-dimensional data, it is necessary to reduce the data dimension while maintaining the data information in order to minimize the impact of the dimension disasters. The detection method of the strong convective weather (hailstone and rainstorm) is based on manifold learning algorithm in this paper. Firstly the dimension of 22-dimensional features of the strong convective weather is reduced by manifold learning algorithm-Local Tangent Space Alignment, then in low-dimensional (8-dimensional) data space the useful and hidden rules for the detection of strong convective weather is dig out, finally the effective rules are obtained to detect the strong convective weather. Compared with the non-dimensionality reduction method, the proposed method improves the detection accuracy and reduces the time complexity through experimental test.","PeriodicalId":337941,"journal":{"name":"International Conference on Fuzzy Systems and Knowledge Discovery","volume":"56 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-05-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114355390","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 : 2012-05-29DOI: 10.1109/FSKD.2012.6234040
Linlin Wang, Yunfang Chen
In order to improve the automatic control of water and electricity resource, an intelligent resource management system for community based on a sensor network is presented for the reason that sensor network has the advantage of low-power transmission. It is provided by a number of experiments that this system has successfully achieved the automatic control goal by rotational solar-energy heater, mechanical control techniques and the intelligent management of the entire system. The overall architecture for electrical control and mechanical control of the system is introduced in order to describe the intelligent management of the system. Finally, the theoretical and experimental analyses are presented to support the validity and advances of this system.
{"title":"An intelligent management of community water and electricity based on wireless sensor network","authors":"Linlin Wang, Yunfang Chen","doi":"10.1109/FSKD.2012.6234040","DOIUrl":"https://doi.org/10.1109/FSKD.2012.6234040","url":null,"abstract":"In order to improve the automatic control of water and electricity resource, an intelligent resource management system for community based on a sensor network is presented for the reason that sensor network has the advantage of low-power transmission. It is provided by a number of experiments that this system has successfully achieved the automatic control goal by rotational solar-energy heater, mechanical control techniques and the intelligent management of the entire system. The overall architecture for electrical control and mechanical control of the system is introduced in order to describe the intelligent management of the system. Finally, the theoretical and experimental analyses are presented to support the validity and advances of this system.","PeriodicalId":337941,"journal":{"name":"International Conference on Fuzzy Systems and Knowledge Discovery","volume":"27 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-05-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134561059","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 : 2012-05-29DOI: 10.1109/FSKD.2012.6234349
F. Kong
This paper presents a method for the establishment of mapping between low-level visual features and high-level semantic features based on Gaussian mixture model (GMM). We combine color features and texture features based on Gabor filter, an image annotation algorithm based on GMM clustering is put forward through the research in image processing. In an image database that contains 1000 images, the experimental results show that the proposed method has better performance.
{"title":"Image Annotation Based on Color and Texture features","authors":"F. Kong","doi":"10.1109/FSKD.2012.6234349","DOIUrl":"https://doi.org/10.1109/FSKD.2012.6234349","url":null,"abstract":"This paper presents a method for the establishment of mapping between low-level visual features and high-level semantic features based on Gaussian mixture model (GMM). We combine color features and texture features based on Gabor filter, an image annotation algorithm based on GMM clustering is put forward through the research in image processing. In an image database that contains 1000 images, the experimental results show that the proposed method has better performance.","PeriodicalId":337941,"journal":{"name":"International Conference on Fuzzy Systems and Knowledge Discovery","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-05-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129872617","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 : 2012-05-29DOI: 10.1109/FSKD.2012.6234059
Hongcan Yan, Chen Liu, Baoxiang Liu
The knowledge base of description logics are composed of two parts TBox and ABox. Tableau Algorithm is for the uniformity testing in the knowledge reasoning of DLs, which is based on two-value logics, it can not realize the uniformity testing for multiple-valued concepts. This paper take the fundamental ideal to the system of DLs, improving Tableau Algorithm through the definition of rough concept implication degree, and by using rough concept express related concepts and relationships in the TBbox, The rough description logics can be completed on the reasoning of rough concept, laying the foundation for knowledge base inference engine design.
{"title":"Knowledge reasoning and Tableau Algorithm improving based on rough description logics","authors":"Hongcan Yan, Chen Liu, Baoxiang Liu","doi":"10.1109/FSKD.2012.6234059","DOIUrl":"https://doi.org/10.1109/FSKD.2012.6234059","url":null,"abstract":"The knowledge base of description logics are composed of two parts TBox and ABox. Tableau Algorithm is for the uniformity testing in the knowledge reasoning of DLs, which is based on two-value logics, it can not realize the uniformity testing for multiple-valued concepts. This paper take the fundamental ideal to the system of DLs, improving Tableau Algorithm through the definition of rough concept implication degree, and by using rough concept express related concepts and relationships in the TBbox, The rough description logics can be completed on the reasoning of rough concept, laying the foundation for knowledge base inference engine design.","PeriodicalId":337941,"journal":{"name":"International Conference on Fuzzy Systems and Knowledge Discovery","volume":"8 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-05-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124130216","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 : 2012-05-29DOI: 10.1109/FSKD.2012.6233746
Yun Zou, Zheng Li, Xunshen Zhu, Jian Yu, Zheng Gu
Considering the fact that syndrome differentiation of Traditional Chinese Medicine (TCM) is multi-level, multi-angle, holistic and integrated, the concept of fuzzy information granulation is introduced to the intelligent TCM diagnosis system in this paper. The model of TCM knowledge representation and syndrome differentiation is proposed, and then is used to intelligent diagnosis for children with sexual precocity disease. Combining with the database technology, the prototype of computer-assisted intelligent diagnostic system of TCM is developed. Testing result using practical cases shows that the diagnostic accuracy for precocious puberty classification reaches 96%. Knowledge of the intelligent diagnostic system can either be derived from the know-how of Chinese medicine experts or be learnt from cases, and can be modified through self-learning. It is useful to TCM syndrome, objectification of clinical evaluation and scientific research of TCM.
{"title":"Research on the computer-assisted intelligent diagnosis system of Traditional Chinese Medicine","authors":"Yun Zou, Zheng Li, Xunshen Zhu, Jian Yu, Zheng Gu","doi":"10.1109/FSKD.2012.6233746","DOIUrl":"https://doi.org/10.1109/FSKD.2012.6233746","url":null,"abstract":"Considering the fact that syndrome differentiation of Traditional Chinese Medicine (TCM) is multi-level, multi-angle, holistic and integrated, the concept of fuzzy information granulation is introduced to the intelligent TCM diagnosis system in this paper. The model of TCM knowledge representation and syndrome differentiation is proposed, and then is used to intelligent diagnosis for children with sexual precocity disease. Combining with the database technology, the prototype of computer-assisted intelligent diagnostic system of TCM is developed. Testing result using practical cases shows that the diagnostic accuracy for precocious puberty classification reaches 96%. Knowledge of the intelligent diagnostic system can either be derived from the know-how of Chinese medicine experts or be learnt from cases, and can be modified through self-learning. It is useful to TCM syndrome, objectification of clinical evaluation and scientific research of TCM.","PeriodicalId":337941,"journal":{"name":"International Conference on Fuzzy Systems and Knowledge Discovery","volume":"182 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-05-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123007233","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 : 2012-05-29DOI: 10.1109/FSKD.2012.6234030
Na Feng, Jinmin Wang, Qingguo Meng
Reconfigurable multi-station machine tool is new generation manufacturing system of personalized production. A new method for multi-station machine tool reconfiguration through case based reasoning is studied. Specially, the machining parts description and similarity analysis using fuzzy sets theory is proposed for reconfiguration solution retrieval.
{"title":"Research on case based multi-station machine tool reconfiguration","authors":"Na Feng, Jinmin Wang, Qingguo Meng","doi":"10.1109/FSKD.2012.6234030","DOIUrl":"https://doi.org/10.1109/FSKD.2012.6234030","url":null,"abstract":"Reconfigurable multi-station machine tool is new generation manufacturing system of personalized production. A new method for multi-station machine tool reconfiguration through case based reasoning is studied. Specially, the machining parts description and similarity analysis using fuzzy sets theory is proposed for reconfiguration solution retrieval.","PeriodicalId":337941,"journal":{"name":"International Conference on Fuzzy Systems and Knowledge Discovery","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-05-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115964522","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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