In this paper, a modeling method of fuzzy membership based on data domain description is proposed for image coding by fuzzy support vector regression. The original image is divided into some non-overlapped rectangular blocks and their transform domain coefficients are treated as training data sets. On each data set, data points are nonlinearly mapped into a high dimensional feature space where the smallest enclosing hypersphere is obtained. Then the corresponding fuzzy membership model is constructed from the distance of each point to the center of the sphere. The established model is eventually embedded into the image coding scheme which adopts adaptively variable penalty factors. Experimental results show that the proposed approach achieves improved quality in both subjective and objective measurement.
{"title":"A Fuzzy Membership Model for FSVR-Based Image Coding","authors":"Qingshan She, Zhizeng Luo, Yaping Zhu","doi":"10.1109/ICNC.2008.58","DOIUrl":"https://doi.org/10.1109/ICNC.2008.58","url":null,"abstract":"In this paper, a modeling method of fuzzy membership based on data domain description is proposed for image coding by fuzzy support vector regression. The original image is divided into some non-overlapped rectangular blocks and their transform domain coefficients are treated as training data sets. On each data set, data points are nonlinearly mapped into a high dimensional feature space where the smallest enclosing hypersphere is obtained. Then the corresponding fuzzy membership model is constructed from the distance of each point to the center of the sphere. The established model is eventually embedded into the image coding scheme which adopts adaptively variable penalty factors. Experimental results show that the proposed approach achieves improved quality in both subjective and objective measurement.","PeriodicalId":6404,"journal":{"name":"2008 Fourth International Conference on Natural Computation","volume":"14 1","pages":"8-12"},"PeriodicalIF":0.0,"publicationDate":"2008-10-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"78369275","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}
The utilization of U-shaped layouts in place of the traditional straight-line configuration has become increasingly popular, with reported benefits of substantial improvements in productivity and quality. In this paper, a new design of ant colony optimization (ACO) is proposed for solving type 1 of the U-shaped line balancing problem (ULBP-1). The proposed algorithm made use of the trail information which is deposited between the task and the task selected position, and pheromone summation rules was adopted. The heuristic information is set to the position weight for tasks of ULBP-1, which synthesis consider processing time of the task and the number of successors/predecessors. The results of the computational experiments indicate that the proposed ACO-based algorithm performs quite effectively.
{"title":"A Novel Ant Colony Optimization Algorithm for U-Shaped Line Balancing Problem","authors":"Zeqiang Zhang, Wenming Cheng, Yue Cheng, Jian Liang","doi":"10.1109/ICNC.2008.18","DOIUrl":"https://doi.org/10.1109/ICNC.2008.18","url":null,"abstract":"The utilization of U-shaped layouts in place of the traditional straight-line configuration has become increasingly popular, with reported benefits of substantial improvements in productivity and quality. In this paper, a new design of ant colony optimization (ACO) is proposed for solving type 1 of the U-shaped line balancing problem (ULBP-1). The proposed algorithm made use of the trail information which is deposited between the task and the task selected position, and pheromone summation rules was adopted. The heuristic information is set to the position weight for tasks of ULBP-1, which synthesis consider processing time of the task and the number of successors/predecessors. The results of the computational experiments indicate that the proposed ACO-based algorithm performs quite effectively.","PeriodicalId":6404,"journal":{"name":"2008 Fourth International Conference on Natural Computation","volume":"5 1","pages":"455-459"},"PeriodicalIF":0.0,"publicationDate":"2008-10-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"78495762","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}
This paper presents the architecture and functional model of cooperative radio resource management (Co-RRM) for the efficient integration of different radio access technologies. The cooperative management mechanism and procedure is designed and the policy-based network resource allocation algorithm is introduced to keep mobile users always best connected. In order to optimize the resource utilization, a scheme namely adaptive vertical handover (AVHO) based on the information of available bandwidth passed from Layer 2.5 trigger is proposed. We have implemented the cooperative management scheme on the simulation platform, and investigated the improvement of transmission control protocol (TCP) performance during vertical handover, and demonstrated the enhancement of resource utilization under the control of Co-RRM.
{"title":"Cooperation Radio Resource Management and Adaptive Vertical Handover in Heterogeneous Wireless Networks","authors":"Yifei Wei, Xiaowei Li, Mei Song, Junde Song","doi":"10.1109/ICNC.2008.504","DOIUrl":"https://doi.org/10.1109/ICNC.2008.504","url":null,"abstract":"This paper presents the architecture and functional model of cooperative radio resource management (Co-RRM) for the efficient integration of different radio access technologies. The cooperative management mechanism and procedure is designed and the policy-based network resource allocation algorithm is introduced to keep mobile users always best connected. In order to optimize the resource utilization, a scheme namely adaptive vertical handover (AVHO) based on the information of available bandwidth passed from Layer 2.5 trigger is proposed. We have implemented the cooperative management scheme on the simulation platform, and investigated the improvement of transmission control protocol (TCP) performance during vertical handover, and demonstrated the enhancement of resource utilization under the control of Co-RRM.","PeriodicalId":6404,"journal":{"name":"2008 Fourth International Conference on Natural Computation","volume":"196 1","pages":"197-201"},"PeriodicalIF":0.0,"publicationDate":"2008-10-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"79905110","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}
Mona Noori Hosseini, S. Gharibzadeh, P. Gifani, S. Babaei, B. Makki
In the last decades, considerable attention has been focused on development of bio-inspired systems. This paper employs the principals of information processing in the Basal Ganglia (BG) to develop a new method for selectively extracting dynamic principal components (DPCs) of multidimensional datasets. The DPCs are extracted by are current structure of auto-associative neural network and selectivity is achieved by means of a reinforcement-like signal which modifies the desired outputs and the learning coefficient of the network. Performance of the model is evaluated through two experiments; at first, the DPCs of a stock price database are extracted and then, speech compression capability of the method is checked which illustrates the efficiency of the proposed approach.
{"title":"Selective Dynamic Principal Component Analysis Using Recurrent Neural Networks","authors":"Mona Noori Hosseini, S. Gharibzadeh, P. Gifani, S. Babaei, B. Makki","doi":"10.1109/ICNC.2008.810","DOIUrl":"https://doi.org/10.1109/ICNC.2008.810","url":null,"abstract":"In the last decades, considerable attention has been focused on development of bio-inspired systems. This paper employs the principals of information processing in the Basal Ganglia (BG) to develop a new method for selectively extracting dynamic principal components (DPCs) of multidimensional datasets. The DPCs are extracted by are current structure of auto-associative neural network and selectivity is achieved by means of a reinforcement-like signal which modifies the desired outputs and the learning coefficient of the network. Performance of the model is evaluated through two experiments; at first, the DPCs of a stock price database are extracted and then, speech compression capability of the method is checked which illustrates the efficiency of the proposed approach.","PeriodicalId":6404,"journal":{"name":"2008 Fourth International Conference on Natural Computation","volume":"130 1","pages":"306-310"},"PeriodicalIF":0.0,"publicationDate":"2008-10-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"77202500","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}
Using the wavelet neural networks, an adaptive control system, with two wavelet neural networks as controller and dynamics model identifier respectively, is developed for lower extreme carrying exoskeleton robot. Because the wavelet neural networks have the ability to approximate nonlinear functions and good advantage of time-frequency localization properties, this system can identify nonlinear system dynamic characters more precisely, and can map more complex control strategies. Results show that this control system is more effective than those based on normal controller, where the exoskeleton tracking precision is high and the operator feels very little torque.
{"title":"Lower Extreme Carrying Exoskeleton Robot Adative Control Using Wavelet Neural Networks","authors":"Xiuxia Yang, Lihua Gui, Zhiyong Yang, W. Gu","doi":"10.1109/ICNC.2008.754","DOIUrl":"https://doi.org/10.1109/ICNC.2008.754","url":null,"abstract":"Using the wavelet neural networks, an adaptive control system, with two wavelet neural networks as controller and dynamics model identifier respectively, is developed for lower extreme carrying exoskeleton robot. Because the wavelet neural networks have the ability to approximate nonlinear functions and good advantage of time-frequency localization properties, this system can identify nonlinear system dynamic characters more precisely, and can map more complex control strategies. Results show that this control system is more effective than those based on normal controller, where the exoskeleton tracking precision is high and the operator feels very little torque.","PeriodicalId":6404,"journal":{"name":"2008 Fourth International Conference on Natural Computation","volume":"16 1","pages":"399-403"},"PeriodicalIF":0.0,"publicationDate":"2008-10-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"82444638","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}
Many current P2P trust models are not suitable for P2P e-commerce because the characteristics of P2P e-commerce are not taken into account. In addition, the simple representation of trust cannot be used to accurately gain assess to other peers in the e-commerce community because of the diversity and subjectivity of trust. In order to evaluate the peers for each other, this paper developed a vector-based trust model named VBTMod. There are two main features of the model. First, the specialty and complexity of e-commerce are considered and it reflects the characteristics of P2P e-commerce. Second, the trust is expressed with vector, which includes various factors of trust in e-commerce. With this model it is easier to extract useful information from the trust and accurately gain assess to other peers. Accordingly, the paper proposed a few assessment approaches for vector trust and strategies to defend attack. Simulation results show that VBTMod enables peers to have more accurate assessment to other peers according to their own needs and effectively defends a variety of attacks. Consequently the model can effectively reduce the risk in transactions.
{"title":"A Vector-Based Trust Model for P2P E-commerce","authors":"Qian Wang, Lifang Wang","doi":"10.1109/ICNC.2008.616","DOIUrl":"https://doi.org/10.1109/ICNC.2008.616","url":null,"abstract":"Many current P2P trust models are not suitable for P2P e-commerce because the characteristics of P2P e-commerce are not taken into account. In addition, the simple representation of trust cannot be used to accurately gain assess to other peers in the e-commerce community because of the diversity and subjectivity of trust. In order to evaluate the peers for each other, this paper developed a vector-based trust model named VBTMod. There are two main features of the model. First, the specialty and complexity of e-commerce are considered and it reflects the characteristics of P2P e-commerce. Second, the trust is expressed with vector, which includes various factors of trust in e-commerce. With this model it is easier to extract useful information from the trust and accurately gain assess to other peers. Accordingly, the paper proposed a few assessment approaches for vector trust and strategies to defend attack. Simulation results show that VBTMod enables peers to have more accurate assessment to other peers according to their own needs and effectively defends a variety of attacks. Consequently the model can effectively reduce the risk in transactions.","PeriodicalId":6404,"journal":{"name":"2008 Fourth International Conference on Natural Computation","volume":"88 1","pages":"117-123"},"PeriodicalIF":0.0,"publicationDate":"2008-10-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"81330036","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}
A new matching crossover real-code adaptive genetic algorithm base on the population maturity is presented to optimize the parameters of a PID controller. The individual is coded in real number, and its crossover probability varies according to the individual fitness and the population maturity in course of evolution. New individuals generated by the crossover between individuals with the best fitness and the second best fitness are added into the population to decrease the search size of the real-coded genetic algorithm. To a certain extent, this algorithm can improve the crossover efficiency of the real-coded adaptive genetic algorithm, solve the premature problem and generate new preponderant individuals much more efficiently. The experiments on the PID parameter optimization of a 6 R series arc welding manipulators demonstrate that this algorithm can enhance the performance of searching global optimum and keep the population diversity at a high level at the same time. The optimization result of this algorithm is better than the one of the others.
{"title":"Real-Coded Adaptive Genetic Algorithm Applied to PID Parameter Optimization on a 6R Manipulators","authors":"Yuan-Ming Ding, Xuan-yin Wang","doi":"10.1109/ICNC.2008.82","DOIUrl":"https://doi.org/10.1109/ICNC.2008.82","url":null,"abstract":"A new matching crossover real-code adaptive genetic algorithm base on the population maturity is presented to optimize the parameters of a PID controller. The individual is coded in real number, and its crossover probability varies according to the individual fitness and the population maturity in course of evolution. New individuals generated by the crossover between individuals with the best fitness and the second best fitness are added into the population to decrease the search size of the real-coded genetic algorithm. To a certain extent, this algorithm can improve the crossover efficiency of the real-coded adaptive genetic algorithm, solve the premature problem and generate new preponderant individuals much more efficiently. The experiments on the PID parameter optimization of a 6 R series arc welding manipulators demonstrate that this algorithm can enhance the performance of searching global optimum and keep the population diversity at a high level at the same time. The optimization result of this algorithm is better than the one of the others.","PeriodicalId":6404,"journal":{"name":"2008 Fourth International Conference on Natural Computation","volume":"23 1","pages":"635-639"},"PeriodicalIF":0.0,"publicationDate":"2008-10-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"81488286","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}
A neural network-based model predictive control scheme is proposed for nonlinear systems. In this scheme an adaptive diagonal recurrent neural network (DRNN) is used for modeling of nonlinear processes. A recursive estimation algorithm using the extended Kalman filter (EKF) is proposed to calculate Jacobian matrix in the model adaptation so that the algorithm is simple and converges fast. Particle swarm optimization (PSO) is adopted to obtain optimal future control inputs over a prediction horizon, which overcomes effectively the shortcoming of descent-based nonlinear programming method on the initial condition sensitivity. A case study of biochemical fermentation process shows that the performance of the proposed control scheme is better than that of PI controller.
{"title":"Adaptive Model Predictive Control Using Diagonal Recurrent Neural Network","authors":"Yingyi Jin, Chengli Su","doi":"10.1109/ICNC.2008.575","DOIUrl":"https://doi.org/10.1109/ICNC.2008.575","url":null,"abstract":"A neural network-based model predictive control scheme is proposed for nonlinear systems. In this scheme an adaptive diagonal recurrent neural network (DRNN) is used for modeling of nonlinear processes. A recursive estimation algorithm using the extended Kalman filter (EKF) is proposed to calculate Jacobian matrix in the model adaptation so that the algorithm is simple and converges fast. Particle swarm optimization (PSO) is adopted to obtain optimal future control inputs over a prediction horizon, which overcomes effectively the shortcoming of descent-based nonlinear programming method on the initial condition sensitivity. A case study of biochemical fermentation process shows that the performance of the proposed control scheme is better than that of PI controller.","PeriodicalId":6404,"journal":{"name":"2008 Fourth International Conference on Natural Computation","volume":"21 1","pages":"276-280"},"PeriodicalIF":0.0,"publicationDate":"2008-10-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"82217651","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}
Spatial cognition is a cognitive process of spatial environment. As an important tool of recording and presenting geographic information, map is the main medium for spatial cognition result. This paper evaluates the existing measurement approaches for map information, and the measurement of metric information proposed by Li and Huang is especially emphasized, for it considers the spatial distribution and relationships of map features. Because the map is a complex cognitive system, human cognition should be considered here. However these measures have neglected the cognitive concepts 'type' and 'level' of map features, which are valuable for human's spatial cognition. As a result, the authors employed the weighted Voronoi diagram to propose a new quantitative measure for metric information. An experimental evaluation is also conducted. Results show that metric information considering cognitive multi-type and multi-level is closer to the spatial environment and human's spatial cognition.
{"title":"A Quantitative Measurement Approach for Metric Information of Maps Based on Spatial Cognition","authors":"Shaoyi Wang, Qingyun Du, Zhao Wang","doi":"10.1109/ICNC.2008.379","DOIUrl":"https://doi.org/10.1109/ICNC.2008.379","url":null,"abstract":"Spatial cognition is a cognitive process of spatial environment. As an important tool of recording and presenting geographic information, map is the main medium for spatial cognition result. This paper evaluates the existing measurement approaches for map information, and the measurement of metric information proposed by Li and Huang is especially emphasized, for it considers the spatial distribution and relationships of map features. Because the map is a complex cognitive system, human cognition should be considered here. However these measures have neglected the cognitive concepts 'type' and 'level' of map features, which are valuable for human's spatial cognition. As a result, the authors employed the weighted Voronoi diagram to propose a new quantitative measure for metric information. An experimental evaluation is also conducted. Results show that metric information considering cognitive multi-type and multi-level is closer to the spatial environment and human's spatial cognition.","PeriodicalId":6404,"journal":{"name":"2008 Fourth International Conference on Natural Computation","volume":"31 1","pages":"235-239"},"PeriodicalIF":0.0,"publicationDate":"2008-10-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"78949530","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}
The development of speech recognition technology has made it possible for some intelligent query systems to use a voice interface. In this paper, we developed a pop-song music retrieval system for telecom carriers to facilitate the interactions between the end users and the music database. When trying to improve the system performance, however, it was found that some typical recognizing optimization techniques for large vocabulary continuous speech recognition (LVCSR) is not practicable for such a real-time application, in which accuracy and speed are both highly stressed. Thus, model optimization techniques are considered. Feature discriminative analysis and minimum phone error discriminative training techniques proposed in recent years have obtained great success in LVCSR, however, there are few reports about their practical applications on online grammar-constrained recognition tasks. In this paper, these techniques are employed and evaluated on such a real-time recognition task. The experimental result shows that these techniques can be effectively implemented in our practical application system with a remarkable error rate reduction of 13.3%.
{"title":"Using Discriminative Training Techniques in Practical Intelligent Music Retrieval System","authors":"Ran Xu, Jielin Pan, Yonghong Yan","doi":"10.1109/ICNC.2008.985","DOIUrl":"https://doi.org/10.1109/ICNC.2008.985","url":null,"abstract":"The development of speech recognition technology has made it possible for some intelligent query systems to use a voice interface. In this paper, we developed a pop-song music retrieval system for telecom carriers to facilitate the interactions between the end users and the music database. When trying to improve the system performance, however, it was found that some typical recognizing optimization techniques for large vocabulary continuous speech recognition (LVCSR) is not practicable for such a real-time application, in which accuracy and speed are both highly stressed. Thus, model optimization techniques are considered. Feature discriminative analysis and minimum phone error discriminative training techniques proposed in recent years have obtained great success in LVCSR, however, there are few reports about their practical applications on online grammar-constrained recognition tasks. In this paper, these techniques are employed and evaluated on such a real-time recognition task. The experimental result shows that these techniques can be effectively implemented in our practical application system with a remarkable error rate reduction of 13.3%.","PeriodicalId":6404,"journal":{"name":"2008 Fourth International Conference on Natural Computation","volume":"49 1","pages":"286-290"},"PeriodicalIF":0.0,"publicationDate":"2008-10-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"76402108","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}
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