Pub Date : 2012-05-29DOI: 10.1109/FSKD.2012.6233910
Enming Dong, Jianping Li, Jinjie Liu
The signal reconstruction problems of Compressed Sensing is equal to a nonsmooth optimization problem. Since the original signal is sparse, a new l 1 -Minimization reconstruction algorithm is proposed based on modified trust region method of nonsmooth optimization. The algorithm can also reconstruct signal in super-linear convergence rate. Simulation results show that the algorithm is robust in reconstructing the original signal.
{"title":"A Compressed Sensing reconstruct algorithm based on trust region method of nonsmooth optimization","authors":"Enming Dong, Jianping Li, Jinjie Liu","doi":"10.1109/FSKD.2012.6233910","DOIUrl":"https://doi.org/10.1109/FSKD.2012.6233910","url":null,"abstract":"The signal reconstruction problems of Compressed Sensing is equal to a nonsmooth optimization problem. Since the original signal is sparse, a new l 1 -Minimization reconstruction algorithm is proposed based on modified trust region method of nonsmooth optimization. The algorithm can also reconstruct signal in super-linear convergence rate. Simulation results show that the algorithm is robust in reconstructing the original signal.","PeriodicalId":337941,"journal":{"name":"International Conference on Fuzzy Systems and Knowledge Discovery","volume":"311 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":"122017040","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.2012.6234343
Huimin Ji, Yangsen Zhang
Word sense disambiguation (WSD) is the hot and difficult issue in natural language processing. Feature selection is the major factor that influences WSD. Different disambiguation methods selected different characteristics. Because the word in the context influences the polysemous disambiguation results, we proposed the concept of scenario word. Scenario words play different roles when we use them to determine the meaning of polysemy. We divide scenario words into co-occurrence words, collocations and demonstratives. Through the experiment, we test the feasibility of the method.
{"title":"Study of chinese word sense disambiguation based on scenario words","authors":"Huimin Ji, Yangsen Zhang","doi":"10.1109/FSKD.2012.6234343","DOIUrl":"https://doi.org/10.1109/FSKD.2012.6234343","url":null,"abstract":"Word sense disambiguation (WSD) is the hot and difficult issue in natural language processing. Feature selection is the major factor that influences WSD. Different disambiguation methods selected different characteristics. Because the word in the context influences the polysemous disambiguation results, we proposed the concept of scenario word. Scenario words play different roles when we use them to determine the meaning of polysemy. We divide scenario words into co-occurrence words, collocations and demonstratives. Through the experiment, we test the feasibility of the method.","PeriodicalId":337941,"journal":{"name":"International Conference on Fuzzy Systems and Knowledge Discovery","volume":"123 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":"125667494","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.2012.6233934
Xuelian Sun, Man Liu, Xuefeng Sun
In this paper, research papers of complex network which published between 2000 and 2011 are indexed based on SCI database. From quotation analysis, content analysis and statistics analysis, the knowledge mapping of major research country and top quality institution are drawn using Pajek software. Through the knowledge mapping, the detecting research frontier, scientific cooperation are discovered. We also discuss the hot topic of complex network research and forecast the future direction in different country. At the same time, some advice was given to Chinese researchers.
{"title":"The analysis of complex networks research based on scientific knowledge mapping","authors":"Xuelian Sun, Man Liu, Xuefeng Sun","doi":"10.1109/FSKD.2012.6233934","DOIUrl":"https://doi.org/10.1109/FSKD.2012.6233934","url":null,"abstract":"In this paper, research papers of complex network which published between 2000 and 2011 are indexed based on SCI database. From quotation analysis, content analysis and statistics analysis, the knowledge mapping of major research country and top quality institution are drawn using Pajek software. Through the knowledge mapping, the detecting research frontier, scientific cooperation are discovered. We also discuss the hot topic of complex network research and forecast the future direction in different country. At the same time, some advice was given to Chinese researchers.","PeriodicalId":337941,"journal":{"name":"International Conference on Fuzzy Systems and Knowledge Discovery","volume":"44 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":"130442600","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.2012.6234153
Yi Sun, Xiang Mi, Liangrui Tang
Congestion of wireless sensor network will increase transmission delay, even cause serious data loss. Not only it has impact on data transmission and the quality of service, but also wastes energy and shortens the network lifetime. To address this challenge, a novel congestion control strategy is proposed for wireless sensor networks called CCBT (Congestion Control Based on Triangle module operator) that comprises three mechanisms: (i) congestion detection based on triangle module fusion operator, (ii) hop-by-hop congestion notification, (iii) distributed rate adjustment. The simulation results show that CCBT significantly improves the performance of data transmission such as queue delay and the number of packet retransmission. Also, CCBT achieves steady increasing throughput.
{"title":"Congestion control based on triangle module fusion operator in wireless sensor networks","authors":"Yi Sun, Xiang Mi, Liangrui Tang","doi":"10.1109/FSKD.2012.6234153","DOIUrl":"https://doi.org/10.1109/FSKD.2012.6234153","url":null,"abstract":"Congestion of wireless sensor network will increase transmission delay, even cause serious data loss. Not only it has impact on data transmission and the quality of service, but also wastes energy and shortens the network lifetime. To address this challenge, a novel congestion control strategy is proposed for wireless sensor networks called CCBT (Congestion Control Based on Triangle module operator) that comprises three mechanisms: (i) congestion detection based on triangle module fusion operator, (ii) hop-by-hop congestion notification, (iii) distributed rate adjustment. The simulation results show that CCBT significantly improves the performance of data transmission such as queue delay and the number of packet retransmission. Also, CCBT achieves steady increasing throughput.","PeriodicalId":337941,"journal":{"name":"International Conference on Fuzzy Systems and Knowledge Discovery","volume":"46 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":"134430616","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.2012.6233847
Xu Zhang, YU Peng, Xiao Chen, R. Tang, Yang Xiang
This paper presents two improved techniques to determine boundaries and depth from observed gravity or magnetic anomalies. The first technique is based on analysis of the largest curvature of the total horizontal gradient of the total magnetic field to determine boundaries. The second technique is based on analysis signal of the total gradient of the total magnetic field to estimate depth. The technique is just only to calculate the total gradient magnitude of gravity or magnetic anomalies, rather than two derivatives of the total gradient magnitude. It is a particularly useful transformation for reducing the effects of noise and increasing the coherency of solutions from model-independent functions. The techniques is shown to work successfully in models and yield excellent results in delineating magnetic contact edges and reasonable performance in producing depth estimates. A practical surveyed data of the South China Sea show good correlation with known structural features.
{"title":"The use of curvature in gravity and magnetic anomalies analysis","authors":"Xu Zhang, YU Peng, Xiao Chen, R. Tang, Yang Xiang","doi":"10.1109/FSKD.2012.6233847","DOIUrl":"https://doi.org/10.1109/FSKD.2012.6233847","url":null,"abstract":"This paper presents two improved techniques to determine boundaries and depth from observed gravity or magnetic anomalies. The first technique is based on analysis of the largest curvature of the total horizontal gradient of the total magnetic field to determine boundaries. The second technique is based on analysis signal of the total gradient of the total magnetic field to estimate depth. The technique is just only to calculate the total gradient magnitude of gravity or magnetic anomalies, rather than two derivatives of the total gradient magnitude. It is a particularly useful transformation for reducing the effects of noise and increasing the coherency of solutions from model-independent functions. The techniques is shown to work successfully in models and yield excellent results in delineating magnetic contact edges and reasonable performance in producing depth estimates. A practical surveyed data of the South China Sea show good correlation with known structural features.","PeriodicalId":337941,"journal":{"name":"International Conference on Fuzzy Systems and Knowledge Discovery","volume":"3 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":"130999839","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.2012.6233752
Li-xiang Duan, Nan Liu, Yu Tang, Yafeng Liu, Qinchun Zhang
Vibration signal measured from machinery is often heavily interfered with by various noises. This paper puts forward a joint method to reduce noises, acquire the enhanced signals from the decomposed subbands and extract the incipient fault features. First, the signals are denoised by the method of singular value decomposition (SVD). Then, the denoised signal is decomposed into four layers by undecimated lifting scheme packet (ULSP). Finally, all 16 subbands of the fourth layer are plotted and the rich-fault-information subbands are used to extract incipient features. The effectiveness of the proposed method is validated with simulated data. Furthermore, in the processing of engineering signal, the weak feature caused by the fault of a valve in reciprocating compressor is bulged and the early failure of spring is detected.
{"title":"Incipient Feature extraction based on singular value decomposition and undecimated lifting scheme packet","authors":"Li-xiang Duan, Nan Liu, Yu Tang, Yafeng Liu, Qinchun Zhang","doi":"10.1109/FSKD.2012.6233752","DOIUrl":"https://doi.org/10.1109/FSKD.2012.6233752","url":null,"abstract":"Vibration signal measured from machinery is often heavily interfered with by various noises. This paper puts forward a joint method to reduce noises, acquire the enhanced signals from the decomposed subbands and extract the incipient fault features. First, the signals are denoised by the method of singular value decomposition (SVD). Then, the denoised signal is decomposed into four layers by undecimated lifting scheme packet (ULSP). Finally, all 16 subbands of the fourth layer are plotted and the rich-fault-information subbands are used to extract incipient features. The effectiveness of the proposed method is validated with simulated data. Furthermore, in the processing of engineering signal, the weak feature caused by the fault of a valve in reciprocating compressor is bulged and the early failure of spring is detected.","PeriodicalId":337941,"journal":{"name":"International Conference on Fuzzy Systems and Knowledge Discovery","volume":"35 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":"115805864","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.2012.6234096
Kai Chen, Wenbo Wei, M. Deng, Jiang-jie Huang, Tian Cheng, Zhen-Dong Wang, Meng Wang
As an effective method to improve the successful rate of marine oil and gas drilling, marine controlled-source electromagnetic method requires acquisition of many marine controlled-source electromagnetic receivers which record electromagnetic data on the same time axis. However, receiver works on the seabed where GPS signal is shielded and relatively constant temperatures, this will bring about a consequence that the land synchronization method could not be implemented. To get the marine receivers which are time synchronization, we combine the GPS and OCXO (Oven Controlled Crystal Oscillator), and then calculate time drift. This method makes time drift down minimum by time drift compensation between different receivers.
{"title":"Time synchronization for marine controlled source electromagnetic recorder","authors":"Kai Chen, Wenbo Wei, M. Deng, Jiang-jie Huang, Tian Cheng, Zhen-Dong Wang, Meng Wang","doi":"10.1109/FSKD.2012.6234096","DOIUrl":"https://doi.org/10.1109/FSKD.2012.6234096","url":null,"abstract":"As an effective method to improve the successful rate of marine oil and gas drilling, marine controlled-source electromagnetic method requires acquisition of many marine controlled-source electromagnetic receivers which record electromagnetic data on the same time axis. However, receiver works on the seabed where GPS signal is shielded and relatively constant temperatures, this will bring about a consequence that the land synchronization method could not be implemented. To get the marine receivers which are time synchronization, we combine the GPS and OCXO (Oven Controlled Crystal Oscillator), and then calculate time drift. This method makes time drift down minimum by time drift compensation between different receivers.","PeriodicalId":337941,"journal":{"name":"International Conference on Fuzzy Systems and Knowledge Discovery","volume":"19 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":"115554453","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.2012.6233758
Xiupeng Jia, Peng Huang, Wenyi Zhang
In order to extract cloud cover feature from ISCCP D2 dataset, a method of feature extraction using wavelet and statistics was used. This method concerned the characteristic of the cloud cover and the applications requirement, and combined the autocorrelation function, partial autocorrelation function with the wavelet method. We can get the conclusion from the features: (1) the features from wavelet analysis are more evident than the features from original series; (2) most of the cloud amount series in ISCCP D2 dataset are stationary series, and the autocorrelation functions (AF) and partial autocorrelation functions (PAF) shows there are diurnal cycle in these series. As a result, it is possible to establish ARIMA model to estimate the cloud amount for a small region in the world.
{"title":"World cloud cover feature extraction base on wavelet and statistics from ISCCP D2 dataset","authors":"Xiupeng Jia, Peng Huang, Wenyi Zhang","doi":"10.1109/FSKD.2012.6233758","DOIUrl":"https://doi.org/10.1109/FSKD.2012.6233758","url":null,"abstract":"In order to extract cloud cover feature from ISCCP D2 dataset, a method of feature extraction using wavelet and statistics was used. This method concerned the characteristic of the cloud cover and the applications requirement, and combined the autocorrelation function, partial autocorrelation function with the wavelet method. We can get the conclusion from the features: (1) the features from wavelet analysis are more evident than the features from original series; (2) most of the cloud amount series in ISCCP D2 dataset are stationary series, and the autocorrelation functions (AF) and partial autocorrelation functions (PAF) shows there are diurnal cycle in these series. As a result, it is possible to establish ARIMA model to estimate the cloud amount for a small region in the world.","PeriodicalId":337941,"journal":{"name":"International Conference on Fuzzy Systems and Knowledge Discovery","volume":"12 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":"126064195","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.2012.6233866
Yujuan Xing, Hengjie Li, Ping Tan
Unclassifiable audio data exists when the conventional SVM was utilized to make classification in the speaker identification. To overcome this problem, this paper proposes a novel hierarchical fuzzy speaker identification method based on fuzzy c-means (FCM) clustering and fuzzy support vector machine (FSVM). Two phases are employed to construct the proposed system. Firstly, the FCM clustering technique is utilized to partition the whole training dataset into several clusters which has its own cluster center. And then, FSVM is trained by the cluster centers to make final decision and process the unclassifiable data. Experiment results show that the proposed method heightens identification accuracy of system remarkablely compared with the baseline SVM speaker identification system.
{"title":"Hierarchical fuzzy speaker identification based on FCM and FSVM","authors":"Yujuan Xing, Hengjie Li, Ping Tan","doi":"10.1109/FSKD.2012.6233866","DOIUrl":"https://doi.org/10.1109/FSKD.2012.6233866","url":null,"abstract":"Unclassifiable audio data exists when the conventional SVM was utilized to make classification in the speaker identification. To overcome this problem, this paper proposes a novel hierarchical fuzzy speaker identification method based on fuzzy c-means (FCM) clustering and fuzzy support vector machine (FSVM). Two phases are employed to construct the proposed system. Firstly, the FCM clustering technique is utilized to partition the whole training dataset into several clusters which has its own cluster center. And then, FSVM is trained by the cluster centers to make final decision and process the unclassifiable data. Experiment results show that the proposed method heightens identification accuracy of system remarkablely compared with the baseline SVM speaker identification system.","PeriodicalId":337941,"journal":{"name":"International Conference on Fuzzy Systems and Knowledge Discovery","volume":" 516","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-05-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"113946746","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.2012.6234280
Lei Li, Yan-hui Hang
The Multidisciplinary Design Optimization (MDO) problem with multiple, conflicting objectives was hardly resolved by tradition individual disciplinary optimization design method. It is combined the MDO method with multi-objective optimization method to formulate the integration of multi-objective MDO method. This integration method could handle hierarchically optimization problems meanwhile trade off multiple objectives in the problems, based on optimization concurrently to attain consistence design. Through a mathematical example, it is verified that this method is acceptably and efficiently.
{"title":"Study on multi-objective optimization based on the integration of linear physical programming within collaborative optimization","authors":"Lei Li, Yan-hui Hang","doi":"10.1109/FSKD.2012.6234280","DOIUrl":"https://doi.org/10.1109/FSKD.2012.6234280","url":null,"abstract":"The Multidisciplinary Design Optimization (MDO) problem with multiple, conflicting objectives was hardly resolved by tradition individual disciplinary optimization design method. It is combined the MDO method with multi-objective optimization method to formulate the integration of multi-objective MDO method. This integration method could handle hierarchically optimization problems meanwhile trade off multiple objectives in the problems, based on optimization concurrently to attain consistence design. Through a mathematical example, it is verified that this method is acceptably and efficiently.","PeriodicalId":337941,"journal":{"name":"International Conference on Fuzzy Systems and Knowledge Discovery","volume":"26 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":"126739620","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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