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2014 International Conference on Machine Learning and Cybernetics最新文献

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Solving the maximum satisfiability problem by fuzzy converting it into a continuous optimization problem 将最大可满足性问题模糊转化为连续优化问题，求解最大可满足性问题
2014 International Conference on Machine Learning and Cybernetics Pub Date : 2014-07-13 DOI: 10.1109/ICMLC.2014.7009141
L. Tseng, Chun Chen
{"title":"Solving the maximum satisfiability problem by fuzzy converting it into a continuous optimization problem","authors":"L. Tseng, Chun Chen","doi":"10.1109/ICMLC.2014.7009141","DOIUrl":"https://doi.org/10.1109/ICMLC.2014.7009141","url":null,"abstract":"The satisfiability problem is the first problem proved to be NP-Complete and has been one of the core NP-Complete problems since then. The satisfiability problem is a decision problem. And the maximum satisfiability problem is its optimization version that aims to find an assignment that satisfies most clauses. In this study, a fuzzy conversion method is proposed to convert the maximum satisfiability problem into a continuous optimization problem. Then the continuous optimization problem is solved by the multiple trajectory search that was previously proposed by us. The proposed fuzzy conversion method transforms the discrete search space into the continuous search space. Furthermore, the fitness function defined on this continuous search space is itself continuous. This fact makes the search much easier. An experiment was conducted to evaluate the performance of the proposed method. Comparison with several methods published in the literature reveals that the proposed method is promising.","PeriodicalId":335296,"journal":{"name":"2014 International Conference on Machine Learning and Cybernetics","volume":"37 9 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-07-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114154223","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
An intelligent fall detection system using triaxial accelerometer integrated by active RFID 一种基于有源RFID集成三轴加速度计的智能跌倒检测系统
2014 International Conference on Machine Learning and Cybernetics Pub Date : 2014-07-13 DOI: 10.1109/ICMLC.2014.7009661
Shou-Hsiung Cheng
{"title":"An intelligent fall detection system using triaxial accelerometer integrated by active RFID","authors":"Shou-Hsiung Cheng","doi":"10.1109/ICMLC.2014.7009661","DOIUrl":"https://doi.org/10.1109/ICMLC.2014.7009661","url":null,"abstract":"This study proposes a straightforward, efficient and intelligent fall detection system using triaxial accelerometer integrated by active RFID. The intelligent fall detection system can not only detect walking and falls but also recognize the postural orientation of the wearer. The experimental results show that the proposed system is simple, efficient and useful for practical applications.","PeriodicalId":335296,"journal":{"name":"2014 International Conference on Machine Learning and Cybernetics","volume":"34 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-07-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114200506","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: 15
The design of the secure transmission and authorization management system based on RBAC 基于RBAC的安全传输与授权管理系统的设计
2014 International Conference on Machine Learning and Cybernetics Pub Date : 2014-07-13 DOI: 10.1109/ICMLC.2014.7009100
Gvoqing Lu, Lingling Zhao, Kuihe Yang
{"title":"The design of the secure transmission and authorization management system based on RBAC","authors":"Gvoqing Lu, Lingling Zhao, Kuihe Yang","doi":"10.1109/ICMLC.2014.7009100","DOIUrl":"https://doi.org/10.1109/ICMLC.2014.7009100","url":null,"abstract":"This paper designs a secure transmission and authorization management system which based on the principles of Public Key Infrastructure and Rose-Based Access Control. It can solve the problems of identity authentication, secure transmission and access control on internet. In the first place, according to PKI principles, certificate authority system is implemented. It can issue and revoke the server-side and client-side digital certificate. Data secure transmission is achieved through the combination of digital certificate and SSL protocol. In addition, this paper analyses access control mechanism and RBAC model. The structure of RBAC model has been improved. The principle of group authority is added into the model and the combination of centralized authority and distributed authority management is adopted, so the model becomes more flexible.","PeriodicalId":335296,"journal":{"name":"2014 International Conference on Machine Learning and Cybernetics","volume":"71 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-07-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132367780","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
A fuzzy integral-based intuitionistic decision system for evaluation and improvement of suppliers in supply chain management 基于模糊积分的供应链供应商评价与改进直觉决策系统
2014 International Conference on Machine Learning and Cybernetics Pub Date : 2014-07-13 DOI: 10.1109/ICMLC.2014.7009709
Li-Hui He, Guo-Fang Zhang, L. Song
{"title":"A fuzzy integral-based intuitionistic decision system for evaluation and improvement of suppliers in supply chain management","authors":"Li-Hui He, Guo-Fang Zhang, L. Song","doi":"10.1109/ICMLC.2014.7009709","DOIUrl":"https://doi.org/10.1109/ICMLC.2014.7009709","url":null,"abstract":"In this paper, an intuitionistic fuzzy rule decision support system based on the fuzzy measure and the fuzzy integral is proposed to handle the various attributes associated with supplier evaluation problem in the supply chain management In this proposed decision support system, because of the importance of continuous evaluation of a particular supplier, the antecedent variable and the consequence variable in the fuzzy if-then rule are considered as the intuitionistic fuzzy variables based on the theory of intuitionistic fuzzy sets which is a generalized fuzzy set whose elements are characterized by both a membership and a non-membership to that set At the same time, given that decision with respect to the improvement and selection of suppliers is intrinsically multiple criteria decision making problem and is strategically important to enterprises, as well as the criteria are not actually independent where the interdependence of the criteria exists in supply chain network system. Evenly in the fact, there is the interdependence in the fuzzy if-then rules of the decision system in the actual supply chain case. Therefore the fuzzy measure and the fuzzy integral are applied to treat the above interdependence in presented system. Finally, the number experiment in a supply chain example shows that the reasoning process of the proposed decision support system provides a more reasonable representation of the real world.","PeriodicalId":335296,"journal":{"name":"2014 International Conference on Machine Learning and Cybernetics","volume":"45 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-07-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133570077","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
A real-time algorithm for aluminum surface defect extraction on non-uniform image from CCD camera 一种基于CCD相机非均匀图像的铝表面缺陷实时提取算法
2014 International Conference on Machine Learning and Cybernetics Pub Date : 2014-07-13 DOI: 10.1109/ICMLC.2014.7009668
Xiu-Qin Huang, Xinbin Luo
{"title":"A real-time algorithm for aluminum surface defect extraction on non-uniform image from CCD camera","authors":"Xiu-Qin Huang, Xinbin Luo","doi":"10.1109/ICMLC.2014.7009668","DOIUrl":"https://doi.org/10.1109/ICMLC.2014.7009668","url":null,"abstract":"A novel real-time defect extraction framework is proposed for handling non-uniform images in high-speed aluminum strip surface inspection. The image is first preprocessed by Gaussian smoothing operator and Prewitt edge detection, which is robust to image non-uniformity. Afterwards, a fast adaptive segmentation algorithm is applied to further remove the effect of non-uniformity and enhance the edge detection. The final defect extraction image is achieved through morphological operations. The resultant method is computationally efficient and robust to non-uniformity. The proposed framework is evaluated on a large dataset of aluminum strip surface images obtained from the product line. The experimental results show that the proposed method achieves real-time defects extraction, and it outperforms the previous methods in accuracy.","PeriodicalId":335296,"journal":{"name":"2014 International Conference on Machine Learning and Cybernetics","volume":"94 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-07-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127008975","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: 8
Application of Genetic Algorithm and Fuzzy Vector Quantization on EEG-based automatic sleep staging by using Hidden Markov Model 遗传算法和模糊矢量量化在隐马尔可夫模型脑电自动睡眠分期中的应用
2014 International Conference on Machine Learning and Cybernetics Pub Date : 2014-07-13 DOI: 10.1109/ICMLC.2014.7009670
Sheng-Fu Liang, Ching-Fa Chen, Jian-Hong Zeng, Shing‐Tai Pan
{"title":"Application of Genetic Algorithm and Fuzzy Vector Quantization on EEG-based automatic sleep staging by using Hidden Markov Model","authors":"Sheng-Fu Liang, Ching-Fa Chen, Jian-Hong Zeng, Shing‐Tai Pan","doi":"10.1109/ICMLC.2014.7009670","DOIUrl":"https://doi.org/10.1109/ICMLC.2014.7009670","url":null,"abstract":"The Genetic Algorithm (GA) and Fuzzy Vector Quantization (FVQ) are combined in this paper to improve the performance of sleep staging. We use GA to train a codebook for Hidden Markov Model (HMM) and use FVQ to model HMM to improve the performance of the HMM. This paper adopts the sleep features of EEG based on 1968's R&K rules as well as the features used in other research for sleep staging. All the selected features are used to train HMM model and then are fed into the HMM model for recognition. In the previous researches, the modeling of HMM is independent of the special properties of the sleep stage transition. In this study, the HMM modeling is designed to meet the special properties of sleep stage transition. The experimental results in this paper show that the proposed method greatly enhances the recognition rate compared with those in other existing researches.","PeriodicalId":335296,"journal":{"name":"2014 International Conference on Machine Learning and Cybernetics","volume":"16 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-07-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133214363","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: 4
A new image fusion strategy based on target segmentaion 一种新的基于目标分割的图像融合策略
2014 International Conference on Machine Learning and Cybernetics Pub Date : 2014-07-13 DOI: 10.1109/ICMLC.2014.7009110
Jian-wei Liu
{"title":"A new image fusion strategy based on target segmentaion","authors":"Jian-wei Liu","doi":"10.1109/ICMLC.2014.7009110","DOIUrl":"https://doi.org/10.1109/ICMLC.2014.7009110","url":null,"abstract":"By analyzing the characteristics of target in multi spectral image and panchromatic image, a new fusion strategy based on target segmentation is proposed to fuse multi spectral image and panchromatic image. Firstly, Hue-Saturation-Intensity (HSI) transform is performed on the multi spectral image. Secondly, the intensity component by HSI transform is segmented by the expectation maximization (EM) algorithm and the panchromatic image is segmented by fuzzy C means (FCM) clustering algorithm, and obtains the better target area, followed by effective filling of the target area to get the new intensity component. Finally, the new fusion image is obtained by inverse HSI transform. Compared with the traditional HSI method, experiment results shows that the proposed strategy not only increases information entropy and average gradient of fusion image, but also decreases spectral bias index. Therefore, the proposed strategy is better than traditional HSI method. It not only enhances spatial resolution of fusion image and obtains detailed and feature information, but also preserves spectral information of the original multi-spectral image well.","PeriodicalId":335296,"journal":{"name":"2014 International Conference on Machine Learning and Cybernetics","volume":"11 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-07-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133434269","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
A new efficient density-based data clustering technique using cross expansion for data mining 一种新的基于密度的交叉扩展数据聚类技术
2014 International Conference on Machine Learning and Cybernetics Pub Date : 2014-07-13 DOI: 10.1109/ICMLC.2014.7009662
Cheng-Fa Tsai, Po-Yi She
{"title":"A new efficient density-based data clustering technique using cross expansion for data mining","authors":"Cheng-Fa Tsai, Po-Yi She","doi":"10.1109/ICMLC.2014.7009662","DOIUrl":"https://doi.org/10.1109/ICMLC.2014.7009662","url":null,"abstract":"This investigation develops a new data clustering technique. It is a new density-based clustering scheme by diagonal sampling and a new method of fold and rotation for enhancing data clustering performance. The proposed algorithm's expansion without selecting data points to increase computation cost and it may considerably lower time cost The experimental results confirm that the presented approach has fairly high clustering accuracy and noise filtering rate, and is faster than numerous well-known existing density-based data clustering algorithms such as DBSCAN, IDBSCAN, KIDBSCAN and FDBSCAN approaches.","PeriodicalId":335296,"journal":{"name":"2014 International Conference on Machine Learning and Cybernetics","volume":"11 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-07-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134045997","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: 3
Microblog hot topic detection based on topic model using term correlation matrix 基于词相关矩阵的话题模型的微博热点话题检测
2014 International Conference on Machine Learning and Cybernetics Pub Date : 2014-07-13 DOI: 10.1109/ICMLC.2014.7009104
Huifang Ma, Yuexin Sun, Meihuizi Jia, Zhichang Zhang
{"title":"Microblog hot topic detection based on topic model using term correlation matrix","authors":"Huifang Ma, Yuexin Sun, Meihuizi Jia, Zhichang Zhang","doi":"10.1109/ICMLC.2014.7009104","DOIUrl":"https://doi.org/10.1109/ICMLC.2014.7009104","url":null,"abstract":"In order to face the challenges of feature sparsity of short text messages for microblog hot topic detection, in this paper, we first explore the relation between terms, and then build term correlation matrix which is much denser than term-document matrix. Symmetric non-negative matrix factorization (SNMF) on term correlation matrix is applied to obtain term-topic matrix. Finally, we formulated the topic learning problem as probabilistic Latent semantic analysis (pLSA) on term-topic matrix. Besides, this paper also presents the definition of heat and mechanism of sorting the topics. Experiments show that our method can effectively cluster topics and be applied to microblog hot topic detection.","PeriodicalId":335296,"journal":{"name":"2014 International Conference on Machine Learning and Cybernetics","volume":"267 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-07-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134292514","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
Modeling of wind turbine power curve based on Gaussian process 基于高斯过程的风力机功率曲线建模
2014 International Conference on Machine Learning and Cybernetics Pub Date : 2014-07-13 DOI: 10.1109/ICMLC.2014.7009094
Jin Zhou, Peng Guo, Xue-Ru Wang
{"title":"Modeling of wind turbine power curve based on Gaussian process","authors":"Jin Zhou, Peng Guo, Xue-Ru Wang","doi":"10.1109/ICMLC.2014.7009094","DOIUrl":"https://doi.org/10.1109/ICMLC.2014.7009094","url":null,"abstract":"For wind farms, the relationship between wind speed and output can be described by power curve of wind turbines, and it is an important embodiment of power performance of wind turbines. Based on the mathematical model of the power curve of wind turbine, monitoring performance of the wind turbine can be designed. Power curve model of wind turbines can be established by using Gaussian process. Within the Bayesian context, the paper aims to train the Gaussian process by using the maximum likelihood optimized approach to find the optimal hyperparameters. The model was validated by the data. Finally, based on the wind turbine power curve mathematical model, the states of the wind turbine can be monitored by using the technology of control charts.","PeriodicalId":335296,"journal":{"name":"2014 International Conference on Machine Learning and Cybernetics","volume":"18 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-07-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115435089","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: 13
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