{"title":"Novel Universal Joint Joystick Based on Linear Compensation","authors":"Hao Lu, Hongchul Kim, Jangmyung Lee, Xiaomeng Li","doi":"10.1109/ISDA.2006.253806","DOIUrl":"https://doi.org/10.1109/ISDA.2006.253806","url":null,"abstract":"A novel non-contact electronic joystick using a single hall-sensor is designed, which detects a horizontal vector in the magnetic field. Furthermore, in this paper, the nonlinear character between the output of the hall-sensor and the movement of joystick bar is illustrated. The dynamic horizontal vector of the magnetic flux is detected by the hall-sensor while a permanent magnet is rotated with the joystick bar, which has a two-dimensional detecting area. Using the nonlinear compensation equations, the output signals of the hall-sensor have been linearized to give higher accuracy in two-dimensional movement. Finally, through real experiments, it is shown that the single hall-sensor structure mechanism is superior to the dual sensor structure in sensing two-dimensional motion without offset","PeriodicalId":116729,"journal":{"name":"Sixth International Conference on Intelligent Systems Design and Applications","volume":"57 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2006-10-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115407210","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":"The Engineering of Experience","authors":"Zhaohao Sun, Hongtao Huo","doi":"10.1109/ISDA.2006.253768","DOIUrl":"https://doi.org/10.1109/ISDA.2006.253768","url":null,"abstract":"Experience has been playing an important role in history of human and current social activities. Automating experience is also one of the most important parts for artificial intelligence. This paper will examine experience and experience based reasoning, experience management, experience engineering and their interrelationships. Then it will propose a unified architecture of experience engineering from a viewpoint of systems development methodologies. This architecture ties together philosophies, methodologies, techniques, tools and applications into a unified framework that includes both logical and intelligent embodiments of the aspects of experience engineering. The proposed approach will facilitate the development of experience management, experience engineering and knowledge based systems","PeriodicalId":116729,"journal":{"name":"Sixth International Conference on Intelligent Systems Design and Applications","volume":"16 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2006-10-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115432445","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 and Scalable Algorithm for Multi-Relational Frequent Pattern Discovery","authors":"Wei Zhang, Bingru Yang","doi":"10.1109/ISDA.2006.92","DOIUrl":"https://doi.org/10.1109/ISDA.2006.92","url":null,"abstract":"We propose MRFPDA, an efficient and scalable algorithm for multi-relational frequent pattern discovery. We incorporate in the algorithm an optimal refinement operator to provide an improvement of the efficiency of candidate generation. Furthermore, MRFPDA utilizes a new strategy of sharing computations to avoid redundant computations in the candidate evaluation. In our experiments, it is shown that on small datasets the performance of MRFPDA is comparable with the performance of the state-of-the-art of multi-relational frequent pattern discovery, and on large datasets MRFPDA is more scalable than two existing approaches","PeriodicalId":116729,"journal":{"name":"Sixth International Conference on Intelligent Systems Design and Applications","volume":"18 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2006-10-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124761885","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 Neuro-control System for Superheated Steam Temperature of Power Plant over Wide Range Operation","authors":"Jian-hang Zhang, G. Hou, Jinfang Zhang","doi":"10.1109/ISDA.2006.85","DOIUrl":"https://doi.org/10.1109/ISDA.2006.85","url":null,"abstract":"In this paper, the dynamics of a superheated steam temperature process in a 600MW supercritical once-through boiler is first analyzed. The dynamics is influenced by the operating conditions represented by steam flow and steam pressure mainly. An intelligent cascade control system is then designed for controlling superheated steam temperature over wide range conditions. The parameter of the proportional controller in the inner loop is fixed all the time. The controller in the main loop is a self-tuning PID neuro-controller whose parameters are adjusted by gradient algorithm, where the Jacobian information of the plant is obtained by RBF neural networks. Finally, the designed control system is applied to control the superheated steam temperature in a 600MW supercritical once-through boiler, and the simulation indicates it has satisfactory performances over wide range","PeriodicalId":116729,"journal":{"name":"Sixth International Conference on Intelligent Systems Design and Applications","volume":"41 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2006-10-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124860801","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":"Automatic Entity Relation Extraction Based on Maximum Entropy","authors":"Zhang Suxiang, Wen Juan, Wang Xiaojie, Li Lei","doi":"10.1109/ISDA.2006.115","DOIUrl":"https://doi.org/10.1109/ISDA.2006.115","url":null,"abstract":"Entity relation extraction (RE) is an very important research domain in information extraction, we can regard RE as a classification problem in this paper, RE is still original study field in Chinese language now, maximum entropy (ME)-based machine learning is the first time to be used to extract entity relations between named entities from Chinese texts, Thirteen features have been designed for entity relation extraction, which includes morphology, grammar and semantic feature. The system architecture for RE has been constructed. Experiment shows that the performance is promising. So it is useful for ME-based machine learning to solve RE problem","PeriodicalId":116729,"journal":{"name":"Sixth International Conference on Intelligent Systems Design and Applications","volume":"72 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2006-10-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122138243","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":"Support Vector Regression Based on Scaling Reproducing Kernel for Black-Box System Identification","authors":"Hong Peng, Jun Wang","doi":"10.1109/ISDA.2006.260","DOIUrl":"https://doi.org/10.1109/ISDA.2006.260","url":null,"abstract":"A new least squares support vector regression model based on scaling reproducing kernel for black-box system identification is presented in this paper. The scaling reproducing kernel, which is a reproducing kernel in reproducing kernel Hilbert space (RKHS), is generated from the set of scaling basis function of some subspace of L 2(R). The support vector regression model incorporated the advantage of the support vector machines and the multi-resolution property of wavelet is discussed in detail. Experiments show that this method has better performance than other approaches","PeriodicalId":116729,"journal":{"name":"Sixth International Conference on Intelligent Systems Design and Applications","volume":"81 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2006-10-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114949543","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}
Fengjian Yang, Chaolong Zhang, Dongqing Wu, Xiaojian Hu
{"title":"Uniformly Stability of Impulsive BAM Neural Networks with Delays","authors":"Fengjian Yang, Chaolong Zhang, Dongqing Wu, Xiaojian Hu","doi":"10.1109/ISDA.2006.275","DOIUrl":"https://doi.org/10.1109/ISDA.2006.275","url":null,"abstract":"This paper is concerned with the stability of the impulsive bidirectional associative memory (BAM) neural networks with time delays. By means of Lyapunov function and analysis technique, sufficient conditions are obtained for the existence and uniformly stability of a unique equilibrium solution without assuming the activation function to be bounded, monotonic or differentiable. This stability property is independent of the stability behavior of continuous-time BAM model since the impulses do contribution to system's uniformly stability","PeriodicalId":116729,"journal":{"name":"Sixth International Conference on Intelligent Systems Design and Applications","volume":"129 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2006-10-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122700288","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":"Robust Stability of Linear Neutral Systems with Time-varying Delay and Nonlinear Perturbations","authors":"Yanhong Jiang, Bin Yang, Shubo Liu, Jincheng Wang","doi":"10.1109/ISDA.2006.253816","DOIUrl":"https://doi.org/10.1109/ISDA.2006.253816","url":null,"abstract":"This paper investigates the robust stability of linear neutral systems with time-varying delay and nonlinear perturbations. Using new Lyapunov-Krasovskii functionals, less conservative delay-dependent sufficient robust stability conditions for such systems in terms of linear matrix inequalities (LMIs) are derived. Numerical examples show that the results obtained in this paper significantly improve the estimate of stability limit over some existing results in the literature","PeriodicalId":116729,"journal":{"name":"Sixth International Conference on Intelligent Systems Design and Applications","volume":"7 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2006-10-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122701358","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":"Study of a Cluster Algorithm Based on Rough Sets Theory","authors":"Licai Yang, Lancang Yang","doi":"10.1109/ISDA.2006.253","DOIUrl":"https://doi.org/10.1109/ISDA.2006.253","url":null,"abstract":"Clustering in data mining is a discovery process that groups a set of data so that the intra-cluster similarity is maximized and the inter-cluster similarity is minimized. Existing clustering algorithms, such as k-medoids, are designed to find clusters, but these algorithms will break down if the choice of parameters in the static model is incorrect with respect to the data set being clustered. Furthermore, these algorithms may break down when the data consists of clusters that are of diverse shapes or densities. Combined the method of calculating equivalence class in rough sets, an improved clustering algorithm based on k-medoids algorithm was presented in this paper. In this algorithm, the number of clusters was firstly specified and the resulting clusters were returned via the k-medoids algorithm, and then the clusters were merged using rough sets theory. The illustrations show that this algorithm is effective to discover the clusters with arbitrary shape and to set the number of clusters, which is difficult for traditional clustering algorithms","PeriodicalId":116729,"journal":{"name":"Sixth International Conference on Intelligent Systems Design and Applications","volume":"42 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2006-10-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122871872","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 Self-coordination Multimode Control System Based on on-line Genetic Optimization","authors":"Qingwu Fan, Pu Wang, Huiqing Zhang, Junqian Liu","doi":"10.1109/ISDA.2006.6","DOIUrl":"https://doi.org/10.1109/ISDA.2006.6","url":null,"abstract":"In order to satisfy the requirements of higher accuracy and faster response of complex system, a control strategy with self-coordination multimode based on P control, fuzzy control, PI control and online genetic optimization is presented in this paper. The results of simulations show that this method improves not only the disturbance resistance, shortens the transition time, accelerates the dynamic response, but also has good anti-interference and disturbance. So this method has better use value","PeriodicalId":116729,"journal":{"name":"Sixth International Conference on Intelligent Systems Design and Applications","volume":"100 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2006-10-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124197743","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}