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2011 International Conference on Machine Learning and Cybernetics最新文献

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Meteorological bulletin automatic generation based on spatio-temporal reasoning 基于时空推理的气象公报自动生成
2011 International Conference on Machine Learning and Cybernetics Pub Date : 2011-07-10 DOI: 10.1109/ICMLC.2011.6016952
Hua-Ping Zhang, Huang Wu, Jian Gao, Yan-ping Zhao, Zhongliang Lv
{"title":"Meteorological bulletin automatic generation based on spatio-temporal reasoning","authors":"Hua-Ping Zhang, Huang Wu, Jian Gao, Yan-ping Zhao, Zhongliang Lv","doi":"10.1109/ICMLC.2011.6016952","DOIUrl":"https://doi.org/10.1109/ICMLC.2011.6016952","url":null,"abstract":"Meteorological bulletin has more and more diversified, large scale, highly integrated requirements and potential demands from whole society. The strong professional efforts involved in transforming the variety of special meteorological data to natural language text are becoming more challenging in providing sophisticated and easily understood weather features. This paper presents a new Meteorological bulletin automatic generation method based on spatio-temporal reasoning. To enhance an exact and non-redundant description for complex meteorological data, and for special future tendency dynamics in emerged interesting areas. We also evaluate this method with real data from National Meteorological Center and prove that it's feasible and effective after implementing.","PeriodicalId":228516,"journal":{"name":"2011 International Conference on Machine Learning and Cybernetics","volume":"11 4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-07-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124280942","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}
引用次数: 0
Improved density-induced support vector data description 改进的密度诱导支持向量数据描述
2011 International Conference on Machine Learning and Cybernetics Pub Date : 2011-07-10 DOI: 10.1109/ICMLC.2011.6016770
F. Yin, Guang-Xin Huang
{"title":"Improved density-induced support vector data description","authors":"F. Yin, Guang-Xin Huang","doi":"10.1109/ICMLC.2011.6016770","DOIUrl":"https://doi.org/10.1109/ICMLC.2011.6016770","url":null,"abstract":"Support vector data description (SVDD) is a data description method which can give the target data set a spherically shaped description. A density-induced SVDD (D-SVDD) has been proposed to improve the SVDD. However, the dual optimization problem of the D-SVDD is not a simple optimization problem which makes the D-SVDD be not an easy data description method. This paper presents an improved density-induced SVDD. The hyper-spherically shaped boundary of our method resorts to a well-known quadratic programming problem, thus the proposed data description method improves the D-SVDD.","PeriodicalId":228516,"journal":{"name":"2011 International Conference on Machine Learning and Cybernetics","volume":"5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-07-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124311563","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}
引用次数: 2
An intelligent location system based on active RFID 一种基于有源RFID的智能定位系统
2011 International Conference on Machine Learning and Cybernetics Pub Date : 2011-07-10 DOI: 10.1109/ICMLC.2011.6016707
Shou-Hsiung Cheng
{"title":"An intelligent location system based on active RFID","authors":"Shou-Hsiung Cheng","doi":"10.1109/ICMLC.2011.6016707","DOIUrl":"https://doi.org/10.1109/ICMLC.2011.6016707","url":null,"abstract":"This study proposes a straightforward, efficient and high accuracy location system. The system can recognize without difficulty different locations of active RFID tags through machine learning and data mining. The system can accurately recognizes the locations of active RFID tags by using neural network classifiers after the active RFID readers has received different intensity of electromagnetic waves transmitted by active RFID tags. The experimental results show that the proposed system is simple, efficient and useful for practical applications.","PeriodicalId":228516,"journal":{"name":"2011 International Conference on Machine Learning and Cybernetics","volume":"54 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-07-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114545217","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}
引用次数: 2
CET4 passing rate analysis based on fuzzy decision tree induction and active learning 基于模糊决策树归纳和主动学习的大学英语四级通过率分析
2011 International Conference on Machine Learning and Cybernetics Pub Date : 2011-07-10 DOI: 10.1109/ICMLC.2011.6016737
Qing-Shui Qiao, Haitao Wang, Zhen-Yu Wang, Jun-Hai Zhai
{"title":"CET4 passing rate analysis based on fuzzy decision tree induction and active learning","authors":"Qing-Shui Qiao, Haitao Wang, Zhen-Yu Wang, Jun-Hai Zhai","doi":"10.1109/ICMLC.2011.6016737","DOIUrl":"https://doi.org/10.1109/ICMLC.2011.6016737","url":null,"abstract":"College English Test Band Four (CET4) in China has been a significant impact on evaluating the English preliminary level of a college student or a class. How to improve the college English teaching and go further to raise passing rate of CET4 are a challenge for many colleges and universities. This paper makes an attempt to quantitatively analyze the CET4 and exam-related factors by using fussy decision tree technique and active learning based on uncertainty. Several features are selected to formulate this problem. The weighted margin is proposed as the new uncertainty measure criterion for unlabeled instance, and a density measure is introduced for avoiding selecting isolated instances. Experiments and simulations on different classes of students show the proposed quantitative analysis method is feasible and effective, which can provide teachers with some useful guidelines for how to improve the college English teaching.","PeriodicalId":228516,"journal":{"name":"2011 International Conference on Machine Learning and Cybernetics","volume":"18 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-07-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114714551","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}
引用次数: 2
Rank of Hangzhou Public Free-Bicycle System rent stations by improved k-means clustering 基于改进k均值聚类的杭州公共免费自行车系统租赁站排名
2011 International Conference on Machine Learning and Cybernetics Pub Date : 2011-07-10 DOI: 10.1109/ICMLC.2011.6017021
Yinglong Ge, Liming Tu, Haitao Xu
{"title":"Rank of Hangzhou Public Free-Bicycle System rent stations by improved k-means clustering","authors":"Yinglong Ge, Liming Tu, Haitao Xu","doi":"10.1109/ICMLC.2011.6017021","DOIUrl":"https://doi.org/10.1109/ICMLC.2011.6017021","url":null,"abstract":"In China, Hangzhou is the first city to set up the Public Free-Bicycle System. There are many and many technology problems in the decision of intelligent dispatch. In this paper, we investigate the rank of Hangzhou Public Free-Bicycle System rent station with improved k-means clustering. Actually, ranking rent station is a very challenge work. In this paper, an improved k-means clustering algorithm is proposed for efficient getting the rank of Hangzhou Public Free-Bicycle System rent s-tations. At first, by passing over the cruel one week's database, a rent-return database is initialed. Then, the rank is determined from the borrow-return database.","PeriodicalId":228516,"journal":{"name":"2011 International Conference on Machine Learning and Cybernetics","volume":"12 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-07-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114910429","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}
引用次数: 0
Existence of positive solutions for some boundary value problem with parameter 一类带参数边值问题正解的存在性
2011 International Conference on Machine Learning and Cybernetics Pub Date : 2011-07-10 DOI: 10.1109/ICMLC.2011.6016811
Lifen Li
{"title":"Existence of positive solutions for some boundary value problem with parameter","authors":"Lifen Li","doi":"10.1109/ICMLC.2011.6016811","DOIUrl":"https://doi.org/10.1109/ICMLC.2011.6016811","url":null,"abstract":"In this paper, the existence of positive solutions is studied for some boundary value problem with parameter. In our discussion, the nonlinearity can change sign, while prevenient literatures need the nonlinearity is non-negative. We combine the method of upper and lower solution and the method of topology degree and then obtain the existence of positive solutions for the boundary value problem. In addition, concrete interval of parameter is given.","PeriodicalId":228516,"journal":{"name":"2011 International Conference on Machine Learning and Cybernetics","volume":"14 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-07-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114941720","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}
引用次数: 0
Hiding data in Tetris 在俄罗斯方块中隐藏数据
2011 International Conference on Machine Learning and Cybernetics Pub Date : 2011-07-10 DOI: 10.1109/ICMLC.2011.6016684
Zhan-He Ou, Ling-Hwei Chen
{"title":"Hiding data in Tetris","authors":"Zhan-He Ou, Ling-Hwei Chen","doi":"10.1109/ICMLC.2011.6016684","DOIUrl":"https://doi.org/10.1109/ICMLC.2011.6016684","url":null,"abstract":"Many kinds of data hiding methods using different cover media have been proposed, several papers use games to do steganography recently. Tetris is a famous puzzle game, and this game randomly generates the tetrominoes pieces to the player. In this paper, we proposed a steganography system for the Tetris game through the generated tetromino sequences. A three phases embedding algorithm is provided to make the stegoed tetromino sequence look like those generated by a normal way. The experimental results show that this system is undetectable.","PeriodicalId":228516,"journal":{"name":"2011 International Conference on Machine Learning and Cybernetics","volume":"41 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-07-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115091105","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}
引用次数: 6
Arranging a hybrid-weight for attribute in weighted naïve Bayesian classifier 在加权naïve贝叶斯分类器中设置属性的混合权值
2011 International Conference on Machine Learning and Cybernetics Pub Date : 2011-07-10 DOI: 10.1109/ICMLC.2011.6016776
Chao Geng, Hao-Ying Guan, Hai-tao Liu
{"title":"Arranging a hybrid-weight for attribute in weighted naïve Bayesian classifier","authors":"Chao Geng, Hao-Ying Guan, Hai-tao Liu","doi":"10.1109/ICMLC.2011.6016776","DOIUrl":"https://doi.org/10.1109/ICMLC.2011.6016776","url":null,"abstract":"In this paper, a modified naïve Bayesian classifier with hybrid-weight (NBCH) is proposed. NBCH arranges a weight for each condition attribute by considering the gain ratio and correlation coefficient. The gain ration is used to measure the effectiveness of a condition attribute in the classification task. And, the correlation coefficient is designed to depict the linear dependence between condition attribute and decision attribute. Our strategy calculates the hybrid of gain ration and correlation coefficient and uses this hybrid as the weight of given condition attribute. In order to validate the feasibility and effectiveness of NBCH, we experimentally compare our method with standard naïve Bayesian classifier (NBC), NBC with gain ratio weight (NBCGR), and NBC with correlation coefficient weight (NBCCC) on 10 UCI datasets. And, a statistical analysis is also given. The final results show that NBCH can obtain the statistically best classification accuracy.","PeriodicalId":228516,"journal":{"name":"2011 International Conference on Machine Learning and Cybernetics","volume":"38 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-07-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117167255","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}
引用次数: 1
Medical image retrieval: Multiple regression models for user's search target 医学图像检索:用户搜索目标的多元回归模型
2011 International Conference on Machine Learning and Cybernetics Pub Date : 2011-07-10 DOI: 10.1109/ICMLC.2011.6016984
Yue Li, Chia-Hung Wei
{"title":"Medical image retrieval: Multiple regression models for user's search target","authors":"Yue Li, Chia-Hung Wei","doi":"10.1109/ICMLC.2011.6016984","DOIUrl":"https://doi.org/10.1109/ICMLC.2011.6016984","url":null,"abstract":"Breast cancer has been one of leading cancers in women around the world. A great number of digital mammograms are generated in hospitals and screening centers. Those digital mammograms can further be used for study and research by medical professionals. Content-based image retrieval refers to the retrieval of images whose contents are similar to a query example, using information derived from the images themselves. Relevance feedback, expressing the user's search target, can be used to bridge the semantic gap and improve the performance of CBIR systems. This study proposes a learning method for relevance feedback learning, which develops multiple logistic regression models to generalize the classification problem and provide an estimate of probability of class membership. To build the model, relevance feedback is utilized as the training data and the IRLS method is applied to estimate the parameters of the regression model and compute the maximum likelihood. Logistic regression models are created individually. After logistic regression models are fitted, discriminating features are selected by the measure of goodness of fit statistics. The weights of those discriminating features can be assigned according to their individual contributions to the maximum likelihood. The probability of the membership of the relevant class can therefore be obtained for each image of the database. Experimental results show that the proposed learning method can effectively improve the average precision from 30% to 65% through five iterations of relevance feedback rounds.","PeriodicalId":228516,"journal":{"name":"2011 International Conference on Machine Learning and Cybernetics","volume":"13 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-07-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129581736","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}
引用次数: 2
Intelligence thresholding for degraded text-photo document images 退化文本-照片文档图像的智能阈值
2011 International Conference on Machine Learning and Cybernetics Pub Date : 2011-07-10 DOI: 10.1109/ICMLC.2011.6016992
Chun-Ming Tsai
{"title":"Intelligence thresholding for degraded text-photo document images","authors":"Chun-Ming Tsai","doi":"10.1109/ICMLC.2011.6016992","DOIUrl":"https://doi.org/10.1109/ICMLC.2011.6016992","url":null,"abstract":"The conversion of the content from paper books into digital form is captured by digital cameras or scanners. However, after the conversion, the illumination of the captured document images is often unevenly distributed. Conventional thresholding methods cannot threshold these kind documents, usually full text images, properly. If the degraded document image includes both text and photo, these methods produce unsatisfactory binarizaion results. This paper presents an efficient and effective intelligent thresholding method for degraded text-photo document images, including: gray-level region cutting is proposed to segment the gray-level document image into several regions intelligently; each region is thresholded by using region thresholding; the gray-level document image is converted into a binary image. Experimental results show that the performance of the proposed method is better than other available thresholding methods in visual measurement.","PeriodicalId":228516,"journal":{"name":"2011 International Conference on Machine Learning and Cybernetics","volume":"60 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-07-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127317579","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}
引用次数: 1
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