{"title":"Continuity of the fractional integral operator on Morrey-Herz spaces","authors":"Meng Zhou, Jian-Guo Shi, Yan-Fang Shi","doi":"10.1109/ICMLC.2014.7009711","DOIUrl":"https://doi.org/10.1109/ICMLC.2014.7009711","url":null,"abstract":"The purpose of this paper is to show the continuity of the fractional integral operator in Morrey-Herz spaces on homogeneous spaces. The method of the proof is the Minkowski's inequality and Hölde's inequality. Besides the decomposition of function spaces established is widely applied in machine learning and cybernetics.","PeriodicalId":335296,"journal":{"name":"2014 International Conference on Machine Learning and Cybernetics","volume":"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":"125908741","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}
{"title":"Finger-knuckle-print recognition based on image sets and convex optimization","authors":"Ying Xu, Yikui Zhai, Junying Gan, Junying Zeng, Yu Huang","doi":"10.1109/ICMLC.2014.7009092","DOIUrl":"https://doi.org/10.1109/ICMLC.2014.7009092","url":null,"abstract":"In order to enhance the stability and security of biometric features recognition, the finger-knuckle-print (FKP) is used in this paper to study high performance recognition problem based on image set. After extracting the image feature by the method of local phase quantization, an image set can transform to a closely related set of points in the affine space. Then the models of the convex hulls are constructed by these point sets. Finally, the FKP recognition was processed in the optimized convex model. Experiments on the publish FKP database show that the proposed algorithm achieves a reliable performance and is suitable for the image data sets.","PeriodicalId":335296,"journal":{"name":"2014 International Conference on Machine Learning and Cybernetics","volume":"22 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":"125145179","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}
{"title":"Salient object detection based on global contrast on texture and color","authors":"Yan-Fei Ren, Zhichun Mu","doi":"10.1109/ICMLC.2014.7009083","DOIUrl":"https://doi.org/10.1109/ICMLC.2014.7009083","url":null,"abstract":"Computationally detecting salient image object based on human attention is of great significance for image understanding. In this paper, we introduce a method for saliency map generation with a novel way of extracting texture feature and a strategy for feature fusion. Our method combines texture and color region contrasts to make the salient object stand out from images. We compare our algorithm to five salient region detection methods with ground truth and salient object segmentation. Our method outperforms the five algorithms on both the ground-truth evaluation and salient object segmentation.","PeriodicalId":335296,"journal":{"name":"2014 International Conference on Machine Learning and Cybernetics","volume":"176 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":"130896340","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}
Hen-Kung Wang, Po-Lun Chang, Fei-Hu Hsieh, H. Hsieh
{"title":"Nonlinear phenomenon in a current-mode controlled buck-boost converter with solar cell input via varying reference current","authors":"Hen-Kung Wang, Po-Lun Chang, Fei-Hu Hsieh, H. Hsieh","doi":"10.1109/ICMLC.2014.7009682","DOIUrl":"https://doi.org/10.1109/ICMLC.2014.7009682","url":null,"abstract":"This paper investigates the nonlinear phenomena in a current-mode controlled buck-boost DC-DC converter with solar cells. The converter is operated in continuous conduction mode (CCM) with inductor current. It is also controlled by varying reference current to study the occurrence of nonlinear phenomena from the initial periodic steady-state to period-doubling bifurcation into the last chaos condition. Firstly, this paper introduces the basic principles of solar cells and current-mode controlled buck-boost converter. Secondly, the equivalent circuit model of solar cells and converter is constructed and the mathematical model is derived. Then, this study adopts MATLAB / SIMULINK for modeling and simulation. The converter nonlinear phenomena are verified through time-domain waveforms, phase portraits and bifurcation diagrams.","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":"134086138","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}
{"title":"Adaptive genetic algorithm based on a new entropy measurement","authors":"Q. Ma, Jiang-Chuan Chen, Xiao-Yan Xu, Yabin Shao","doi":"10.1109/ICMLC.2014.7009112","DOIUrl":"https://doi.org/10.1109/ICMLC.2014.7009112","url":null,"abstract":"In this paper, we propose an adaptive genetic algorithm based on a new entropy measurement, and deduce the limit of the selection probabilities of individuals under the entropy measurement. The theoretical analysis and a comparative experiment show that the new selection strategy based on the new entropy measurement can adjust dynamically the selection intensity according to the population state. The proposed method shifts dynamically the balance between the exploitation and exploration performance of genetic algorithms to enhance global optimal performance of algorithm.","PeriodicalId":335296,"journal":{"name":"2014 International Conference on Machine Learning and Cybernetics","volume":"6 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":"133130993","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}
Xiangwen Liao, Hu Chen, Jingjing Wei, Zhiyong Yu, Guolong Chen
{"title":"A weighted lexicon-based generative model for opinion retrieval","authors":"Xiangwen Liao, Hu Chen, Jingjing Wei, Zhiyong Yu, Guolong Chen","doi":"10.1109/ICMLC.2014.7009715","DOIUrl":"https://doi.org/10.1109/ICMLC.2014.7009715","url":null,"abstract":"In recent years, opinion retrieval attracted a growing research interest as online users' opinions become more and more valuable for market survey, political polls, etc. The goal of opinion retrieval is to find relevant and opinionate documents according to a user's query. Compared with previous lexicon-based generative model for opinion retrieval considering that the sentiment words are equal for a query, which cannot reflect different sentiment words' relevant opinion strength, we propose a graph-based approach by using HITS model to capture the sentiment words' relevant opinion strength. Then the weights are incorporated into the weighted lexicon-based generative model for opinion retrieval. Experimental results on two datasets show the effectiveness of the proposed generative model. Compared with the baseline approach, improvements of 4% and 11% have been obtained on two real datasets.","PeriodicalId":335296,"journal":{"name":"2014 International Conference on Machine Learning and Cybernetics","volume":"58 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":"115044696","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}
{"title":"Method for improving the Generalized Interpolated Fourier Transform","authors":"Mengmeng He, Liying Zheng","doi":"10.1109/ICMLC.2014.7009677","DOIUrl":"https://doi.org/10.1109/ICMLC.2014.7009677","url":null,"abstract":"Straight line detection is fairly common in computer vision community. Compared with Hough transform, Radon transform has been widely used for detecting Straight lines due to its superior capability .In this paper, we proposed a method for improving the performance of the Generalized Interpolated Fourier Transform(GIFT). The proposed method not only provides a principle to choose the parameters of the GIFT, but also establishes a position mapping file from the Cartesian to polar coordinates transformation. Comparing to the original multiplication and cosine operation, looking up mapping files will save a lot of computing time. Simulation results in Section 4 show that our method has a considerable reduction in computational complexity.","PeriodicalId":335296,"journal":{"name":"2014 International Conference on Machine Learning and Cybernetics","volume":"142 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":"115306385","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}
{"title":"Abnormal crowd event detection based on outlier in time series","authors":"Wei-Lieh Hsu, Yu-Cheng Wang, Chih-Lung Lin","doi":"10.1109/ICMLC.2014.7009142","DOIUrl":"https://doi.org/10.1109/ICMLC.2014.7009142","url":null,"abstract":"Crowd management research shows a lack of depth in the literature insofar as most major incidents can be prevented or minimized by a proper management strategy. Specifically, if abnormal crowd events can be detected early and the relevant governing agency can take appropriate actions towards mitigating the dangers, accidental injury can be prevented or the incident can be contained. This paper presents a technical approach to gather the required crowd data using fixed cameras to collect visual data while using a grid model to describe the crowd distribution. The measured area will be divided into several unit areas and each unit area is considered to be a simple cell in a grid model. The state value of each unit area is determined by changes in the total number of active pixels within the unit area. Under the circumstances, the motion status of the measured area is represented by a dynamic state matrix, which will save computing time. Should abnormal crowd events develop, a crowd tends to attempt to quickly leave the area and the resultant crowd distribution changes accordingly. Thus, we expect the crowd distribution to have a sudden and significant change as the abnormal crowd event unfolds. According to the Uniqueness Theorem, crowd distribution in the grid model can be described by a series of different order moments. To consider the normalization, the Chebyshev moment is used to describe the status distribution in the grid model of each image and a time series is used to describe the varying features of the two adjacent images in the video data. When unusual events occur, the status distribution in the grid model between images will show more obvious changes within a short period of time. We can use an outlier detection method to detect the extreme values and also identify the type of outlier: additive outliers or innovational outliers are used to determine the cause of abnormal feature variation.","PeriodicalId":335296,"journal":{"name":"2014 International Conference on Machine Learning and Cybernetics","volume":"340 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":"116530673","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}
{"title":"An efficient clustering analysis method for image segmentation with noise","authors":"P. Lin, P. Huang, A. S. Lai, Lipin Hsu, Ping Chen","doi":"10.1109/ICMLC.2014.7009657","DOIUrl":"https://doi.org/10.1109/ICMLC.2014.7009657","url":null,"abstract":"One approach to image segmentation is to apply a data clustering method such as fuzzy c-means (FCM) to the pixels of the image. FCM and its variations all require an appropriately predefined number of clusters for a given set of data in order to obtain a correct clustering result However, an optimal number of clusters is usually unknown. Mok et al. proposed a robust adaptive clustering analysis method to identify the desired number of clusters and produce a reliable clustering solution at the same time based on a judgment matrix which represents the clustering relationship between any two data points. When applying the Mok's method to image segmentation, the method becomes very impractical because the judgment matrix is too huge to be handled efficiently. In this paper, a more efficient clustering analysis method is proposed for segmenting images with noise. The efficiency comes from the size of the judgment matrix which is only 256 by 256. Experimental results show that our method is better than Mok's method for segmenting both synthetic and real images with noise.","PeriodicalId":335296,"journal":{"name":"2014 International Conference on Machine Learning and Cybernetics","volume":"39 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":"123288230","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}
{"title":"A transmission-type pinhole detection system for high-speed aluminum foil","authors":"Xinbin Luo, Shan Fu, Xiu-Qin Huang, Qing-Qing Xing","doi":"10.1109/ICMLC.2014.7009119","DOIUrl":"https://doi.org/10.1109/ICMLC.2014.7009119","url":null,"abstract":"A transmission-type pinhole detection system is proposed for high-speed aluminum foil, which could automatically detect and identify pinhole defects on the aluminum foil strip. The transmitting light passes through the pinholes in the foil strip and forms a bright spot area in the camera image to detect the pinholes. However, the pseudo-defects generated by the external factors will affect the identification of pinhole defects; thus, a unique mechanical device is used to shield the external interference. On this basis, a simple, fast, and effective detection and classification algorithm is adopted to meet the requirements of real-time detection and identification. Subsequently, based on the demand of production application, a novel algorithm to merge pinhole defects is designed. This system has been evaluated and applied in an aluminum plant and the field application results show that it is a stable and reliable system for real-time pinhole detection.","PeriodicalId":335296,"journal":{"name":"2014 International Conference on Machine Learning and Cybernetics","volume":"17 2","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-07-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121005769","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}