{"title":"Graph transformation with variables for formalizing delegation authorization of workflow","authors":"Yonghe Wei","doi":"10.1109/ICINFA.2009.5205032","DOIUrl":"https://doi.org/10.1109/ICINFA.2009.5205032","url":null,"abstract":"Using graph transformation with variables yields very expressive rules that are still comprehensible. After reviewing the basic notations of graph transformation with variables, this article presents specification formalisms for workflow delegation policies using graph transformation with variables. In this research, authorization states are represented by graphs and state transition by graph transformation with variables. The proposed formalization provides an intuitive description for the manipulation of graph structures as they occur in workflow delegation and a precise specification of consistency conditions on graphs and graph transformations. We specifies a type graph to represents the type information in the graph transformation for workflow delegation, a set of rule schemes to build the system states and sets of positive and negative constraints to specify wanted and unwanted framework. Using formal properties of graph transformation, it can to detect inconsistencies between a rules and a constraint and lay the foundation for their resolutions. We present an algorithm to automatically check and eliminate conflicts between rules and positive and negative constraints.","PeriodicalId":223425,"journal":{"name":"2009 International Conference on Information and Automation","volume":"3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2009-06-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125003748","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":"Research on work mechanism of intelligent CAPP","authors":"Zhongbin Wang, Yuliu Chen, Qing Li","doi":"10.1109/ICINFA.2009.5205128","DOIUrl":"https://doi.org/10.1109/ICINFA.2009.5205128","url":null,"abstract":"Different manufacturing enterprises need the different CAPP systems, which interrupts popularization of CAPP. In order to improve expansibility, reusability and dynamic adaptability of CAPP system, the work mechanism of an intelligent CAPP system based on multi-agent system was investigated, and this paper researched on the architecture and function of the agents in the intelligent CAPP. The reason of conflict generation was analyzed, and conflict resolution mechanism based on knowledge was represented. The conflicts which intelligent CAPP generated were resolved by use of rule-based reasoning and case-based reasoning, the relevant agents were developed, the investigation achievement was applied in the process of producing shearer. It is shown that the intelligent CAPP based on multi-agent system has good expansibility and reusability, it can adapt to the changes of products and production conditions in the enterprise.","PeriodicalId":223425,"journal":{"name":"2009 International Conference on Information and Automation","volume":"230 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2009-06-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116769896","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}
Lingfei Wu, M.Q.-H. Meng, Jian Huang, Huawei Liang, Zijing Lin
{"title":"An improvement of DV-Hop Algorithm Based on Collinearity","authors":"Lingfei Wu, M.Q.-H. Meng, Jian Huang, Huawei Liang, Zijing Lin","doi":"10.1109/ICINFA.2009.5204899","DOIUrl":"https://doi.org/10.1109/ICINFA.2009.5204899","url":null,"abstract":"In order to fully consider the topology relationship among the anchor nodes and the topology relationship between the anchor nodes and unknown nodes, an Improvement of DV-Hop Algorithm Based on Collinearity is proposed. The main principle of the proposed scheme is to introduce the concept of normalized colinearity (NC) into the selection phase of beacon nodes. Based on DV-Hop, best available anchor terns are elected to accomplish more accurate localization by using NC. The experimental results show that the location accuracy of the proposed algorithm outweighs significantly the DV-Hop algorithm, especially in the cases where the connectivity is lower than 10.","PeriodicalId":223425,"journal":{"name":"2009 International Conference on Information and Automation","volume":"7 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2009-06-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125182821","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":"Inversion of eddy current NDE signals using artificial neural network based forward model and particle swarm optimization algorithm","authors":"Siquan Zhang, Hefa Yang","doi":"10.1109/ICINFA.2009.5205120","DOIUrl":"https://doi.org/10.1109/ICINFA.2009.5205120","url":null,"abstract":"An inversion algorithm for the reconstruction of natural crack shape from eddy current testing signals is developed by using an artificial neural network based forward model and particle swarm optimization algorithm. Eddy current inspections are performed to measure signals caused by fatigue cracks introduced into plate specimens. The preprocessed ECT signals and the true crack shapes are used in the training of neural network. The parameters of the particle swarm optimization algorithm are modified and the results are discussed. The reconstruction results of crack shape verified both the efficiency of neural network based forward model and the promising of particle swarm optimization algorithm in crack shape inversion.","PeriodicalId":223425,"journal":{"name":"2009 International Conference on Information and Automation","volume":"34 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2009-06-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125188121","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 background update based on mixture models of Gaussian","authors":"Feng Wang, S. Dai","doi":"10.1109/ICINFA.2009.5204945","DOIUrl":"https://doi.org/10.1109/ICINFA.2009.5204945","url":null,"abstract":"In computer vision system, detection of moving targets has interference in subsequent processes including classification, tracking and recognition. Background subtraction method is commonly used in image segmentation for moving region of video. This paper puts emphasis on background model update based on mixture models of Gaussian in complicated situation, and implements an adaptive learning method to update background models. Each pixel is classified into 4 different types: still background, dynamic background, moving object, temporary still object. And the proposed method reduces the computational complexity.","PeriodicalId":223425,"journal":{"name":"2009 International Conference on Information and Automation","volume":"92 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2009-06-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125204549","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":"Adjacent grids algorithm and dynamics programming realization for minimum time-to-climb trajectories","authors":"Chen Yali, Dong Xinmin, Zu Enlin, Liao Kaijun","doi":"10.1109/ICINFA.2009.5205012","DOIUrl":"https://doi.org/10.1109/ICINFA.2009.5205012","url":null,"abstract":"This paper deals with the minimum time-to-climb problem, as a basic function of an aircraft during executing the flight mission. After discussing the longitudinal equation of motion, the relationship between consumption time and other state variables is obtained by disposing the aircraft equations of dynamics and motion. Based on the relationship, the time interval between any adjacent grids in the vertical plane is figured out. Finally, the minimum time cost for climbing from one flight point to the target point is calculated by dynamic programming (DP) method. The numerical simulation shows that, the algorithm presented in this paper which based on adjacent grids and DP can find the optimal flight trajectory series which is realizable in designated flight envelope, and the time cost of obtained trajectory serried satisfies with the requirement.","PeriodicalId":223425,"journal":{"name":"2009 International Conference on Information and Automation","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2009-06-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125217046","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":"Development of ANN inverse compensator for two-dimensional force sensor","authors":"Yuhan Ding, X. Dai, Chunmiao Ma","doi":"10.1109/ICINFA.2009.5204913","DOIUrl":"https://doi.org/10.1109/ICINFA.2009.5204913","url":null,"abstract":"In order to improve the dynamic performance as well as eliminate the coupling between the two dimensions of the oblate ring two-dimensional force sensor, this paper presents an ANN (artificial neural network) inverse compensating method, based on which we construct an ANN inverse compensator. The compensator is composed of several differentiators and a static ANN. By cascading the ANN inverse compensator with the original sensor, a compounded measurement system is then established. The experiment results show that the coupling phenomenon of the compounded system almost disappears and the dynamic performance is ameliorated remarkably compared with those of the original sensor.","PeriodicalId":223425,"journal":{"name":"2009 International Conference on Information and Automation","volume":"22 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2009-06-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121637176","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":"Multi-ultrasonic-sensor grid map building based on D-S evidence theory","authors":"Cao Hongyu, Sun Hanxu, Jia Qingxuan, Zheng Yili","doi":"10.1109/ICINFA.2009.5205048","DOIUrl":"https://doi.org/10.1109/ICINFA.2009.5205048","url":null,"abstract":"A method of constructing and maintaining a grid map using ultrasonic sensors based on Dempster-Shafer evidence theory (D-S evidence theory) is proposed with respect to the problem of unstructured unknown environment exploration and mapping. Mobile robot moving in an environment explores with ultrasonic sensors; D-S evidence theory is used to fuse information; The problem that D-S evidence theory can't be applied to information fusion under certain circumstances and the matter that D-S evidence theory have counter-intuitive behaviors in some cases are discussed; An approximate process algorithm is advanced to avoid above problems; Finally, a two-dimensional grid map is built. Application result shows that this method is appropriate for unstructured unknown environment mapping.","PeriodicalId":223425,"journal":{"name":"2009 International Conference on Information and Automation","volume":"34 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2009-06-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128125613","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":"Skew detection of track images based on wavelet transform and linear least square fitting","authors":"Changyou Li, Q. Yang","doi":"10.1109/ICINFA.2009.5204964","DOIUrl":"https://doi.org/10.1109/ICINFA.2009.5204964","url":null,"abstract":"A novel algorithm to detect the skew angle of a scanned track image is proposed. The proposed algorithm is based on wavelet transform and linear least square fitting method. First, a skew feature image of the original track image, which preserves the track's horizontal feature, is extracted by the wavelet transform. Given a threshold, the skew feature image is then transformed a binary image, in which most of the object points correspond to the top or bottom ends of tracks. Those object points are fitted by using linear least square method to get a line for each top or bottom end row of tracks. The average value of the skew angle of the several lines is regarded as the skew angles of the track images. Experimental results show that this algorithm performs well on track images. The effects of various wavelet basis are investigated too.","PeriodicalId":223425,"journal":{"name":"2009 International Conference on Information and Automation","volume":"115 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2009-06-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133555849","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":"Data mining based on fuzzy rough set theory and its application in the glass identification","authors":"Ruying Sun, Rongcang Han","doi":"10.1109/ICINFA.2009.5204911","DOIUrl":"https://doi.org/10.1109/ICINFA.2009.5204911","url":null,"abstract":"To overcome the disadvantage of determining artificially the class number, fuzzy C means clustering is introduced to fuzzify the continual attribute, and the best minute class number is obtained by cluster validity analysis. The relationship of glass composition and its application is excavated using data mining method in this paper.","PeriodicalId":223425,"journal":{"name":"2009 International Conference on Information and Automation","volume":"30 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2009-06-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131873855","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}