Clonal selection algorithm (CSA) is one of the most representative Immune algorithms (IA) and was applied into the protein structure prediction (PSP) on AB off-lattice model, but it required a long time in the calculation. So in this paper, a parallel clonal selection algorithm (CSA) was proposed, which was implemented using distributed computing model that employed Open MP on four core computer. In the algorithm, several sub-populations replaced the original single population, and each sub-population evolved independently, and the current best individual was distributed into all the sub-populations. The parallel algorithm overcame premature convergence and found global optima efficiently. And the experiment results shown that the performance had beensignificantly improved.
{"title":"Paralleling Clonal Selection Algorithm with OpenMP","authors":"Hongbing Zhu, Sicheng Chen, Jianguo Wu","doi":"10.1109/ICINIS.2010.41","DOIUrl":"https://doi.org/10.1109/ICINIS.2010.41","url":null,"abstract":"Clonal selection algorithm (CSA) is one of the most representative Immune algorithms (IA) and was applied into the protein structure prediction (PSP) on AB off-lattice model, but it required a long time in the calculation. So in this paper, a parallel clonal selection algorithm (CSA) was proposed, which was implemented using distributed computing model that employed Open MP on four core computer. In the algorithm, several sub-populations replaced the original single population, and each sub-population evolved independently, and the current best individual was distributed into all the sub-populations. The parallel algorithm overcame premature convergence and found global optima efficiently. And the experiment results shown that the performance had beensignificantly improved.","PeriodicalId":319379,"journal":{"name":"2010 Third International Conference on Intelligent Networks and Intelligent Systems","volume":"15 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115372135","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 adaptive filter was implemented in this paper, which was based on NLMS algorithm. High performance signals could be gotten by filtering the time-varying and unknown interference in the communication channels. The NLMS algorithm was achieved by discussing the principle of LMS algorithm and its improvements. It was concluded that NLMS algorithm could be implemented on FPGA chips. This paper described the method of the specific implementation. This method introduces bit-shift in terms of subsection instead of division operation, by which the operation speed of FPGA is improved apparently. The spectrogram of the output signals proved that the attenuation reached to 99.21 dB when the normalized frequency was 0.04375π offset from the center frequency. The adaptive filter could filter the interference effectively in the communication channels. Moreover, the implementation of this adaptive filter requires considerably less FPGA resources because of the decreases of its calculating complexity. It could meet the requirements of high-speed signal processing.
{"title":"NLMS Adaptive Algorithm Implement Based on FPGA","authors":"Jing Dai, Yanmei Wang","doi":"10.1109/ICINIS.2010.97","DOIUrl":"https://doi.org/10.1109/ICINIS.2010.97","url":null,"abstract":"A adaptive filter was implemented in this paper, which was based on NLMS algorithm. High performance signals could be gotten by filtering the time-varying and unknown interference in the communication channels. The NLMS algorithm was achieved by discussing the principle of LMS algorithm and its improvements. It was concluded that NLMS algorithm could be implemented on FPGA chips. This paper described the method of the specific implementation. This method introduces bit-shift in terms of subsection instead of division operation, by which the operation speed of FPGA is improved apparently. The spectrogram of the output signals proved that the attenuation reached to 99.21 dB when the normalized frequency was 0.04375π offset from the center frequency. The adaptive filter could filter the interference effectively in the communication channels. Moreover, the implementation of this adaptive filter requires considerably less FPGA resources because of the decreases of its calculating complexity. It could meet the requirements of high-speed signal processing.","PeriodicalId":319379,"journal":{"name":"2010 Third International Conference on Intelligent Networks and Intelligent Systems","volume":"355 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115440602","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}
In order to utilize a best hot rolling process, intelligent database system involving with rolling conditions rolling materials was developed in this research work. The system design is to consider how to optimize manufacturing condition of rolling process and rolling materials. The system was constructed on internet environment, so that all data and information can be obtained conveniently on internet. The way of hot rolling data search is largely broadened and thus the utility of the data and information of hot rolling can be greatly improved. A kind of model based on multi-line regression is established by the database on hot-roll product's performance. Then we can design new products and new techniques by the established model.
{"title":"A Database System of Hot Rolling Process and Materials Constructed on Internet","authors":"Zhang Yujun, Ju Dongying","doi":"10.1109/ICINIS.2010.117","DOIUrl":"https://doi.org/10.1109/ICINIS.2010.117","url":null,"abstract":"In order to utilize a best hot rolling process, intelligent database system involving with rolling conditions rolling materials was developed in this research work. The system design is to consider how to optimize manufacturing condition of rolling process and rolling materials. The system was constructed on internet environment, so that all data and information can be obtained conveniently on internet. The way of hot rolling data search is largely broadened and thus the utility of the data and information of hot rolling can be greatly improved. A kind of model based on multi-line regression is established by the database on hot-roll product's performance. Then we can design new products and new techniques by the established model.","PeriodicalId":319379,"journal":{"name":"2010 Third International Conference on Intelligent Networks and Intelligent Systems","volume":"56 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117056151","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}
An improve method of the block wise non-local means (BNL - means) is proposed for removing noise in the digital image. This method consists of the spectral decomposition of the Gaussian weighted matrix, the pseudo filter constructions, computations of the pseudo weighted coefficients and image denoising using the weighted sum of Gaussian. Experimental results show that this method is simpler, more efficient than the traditional NL-means algorithm and the denoising results are promising for the natural and textural image over the additive Gaussian white noise.
{"title":"Novel Non-local Means Method for Image Denoising","authors":"Zheng Haozhe, Jin Yunan, Lu Xiaomei","doi":"10.1109/ICINIS.2010.24","DOIUrl":"https://doi.org/10.1109/ICINIS.2010.24","url":null,"abstract":"An improve method of the block wise non-local means (BNL - means) is proposed for removing noise in the digital image. This method consists of the spectral decomposition of the Gaussian weighted matrix, the pseudo filter constructions, computations of the pseudo weighted coefficients and image denoising using the weighted sum of Gaussian. Experimental results show that this method is simpler, more efficient than the traditional NL-means algorithm and the denoising results are promising for the natural and textural image over the additive Gaussian white noise.","PeriodicalId":319379,"journal":{"name":"2010 Third International Conference on Intelligent Networks and Intelligent Systems","volume":"50 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124833794","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}
Feature extraction is among the most important problems in face recognition systems. In this paper, Kernel Principal Component Analysis (KPCA) has been used in feature extraction and face recognition. By the use of integral kernel function, one can efficiently compute principal components in high dimensional feature spaces, related to input space by some nonlinear map. Polynomial kernel was used. The experimental results demonstrate that the KPCA is not only good at dimensional reduction, but also available to get better performance than conventional PCA. The highest rate is 90%.
{"title":"Facial Recognition Based on Kernel PCA","authors":"Yanmei Wang, Yanzhu Zhang","doi":"10.1109/ICINIS.2010.88","DOIUrl":"https://doi.org/10.1109/ICINIS.2010.88","url":null,"abstract":"Feature extraction is among the most important problems in face recognition systems. In this paper, Kernel Principal Component Analysis (KPCA) has been used in feature extraction and face recognition. By the use of integral kernel function, one can efficiently compute principal components in high dimensional feature spaces, related to input space by some nonlinear map. Polynomial kernel was used. The experimental results demonstrate that the KPCA is not only good at dimensional reduction, but also available to get better performance than conventional PCA. The highest rate is 90%.","PeriodicalId":319379,"journal":{"name":"2010 Third International Conference on Intelligent Networks and Intelligent Systems","volume":"124 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123763920","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}
Engineering education has become increasingly reliant on more powerful software tools to assist in solving more complex problems. This paper presents examples of the application of Matlab and Simulink software to theoretical analysis and experiments in the course of Computer Control System. These examples include the dynamic behavior investigation of the experiment of computer control two-tank system when the value of the controller gain and the length of the sample time are changed. The great potential of Matlab and Simulink software in the engineering education is shown through these examples.
{"title":"The Application of Matlab and Simulink to Computer Control System Course Education","authors":"Liang Zhang, Xuemei Zhu, Y. Guo","doi":"10.1109/ICINIS.2010.140","DOIUrl":"https://doi.org/10.1109/ICINIS.2010.140","url":null,"abstract":"Engineering education has become increasingly reliant on more powerful software tools to assist in solving more complex problems. This paper presents examples of the application of Matlab and Simulink software to theoretical analysis and experiments in the course of Computer Control System. These examples include the dynamic behavior investigation of the experiment of computer control two-tank system when the value of the controller gain and the length of the sample time are changed. The great potential of Matlab and Simulink software in the engineering education is shown through these examples.","PeriodicalId":319379,"journal":{"name":"2010 Third International Conference on Intelligent Networks and Intelligent Systems","volume":"53 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115081468","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 main peak extraction method was proposed, considering the main peak uncertainty of multi-peak signal and the inadequateness of existing methods. The purpose of main peak extraction was achieved by relevant processing, and the ambiguity of sub-peak triggered was removed, the characteristic of single peak was restituted. In the same time the method was simulated, the conclusion proved that the main peak extraction method was effective.
{"title":"The Method of Main Peak Extraction Based on Multi-peak Signal","authors":"Fang Liu, Ming-hao Tian, Yongxin Feng","doi":"10.1109/ICINIS.2010.185","DOIUrl":"https://doi.org/10.1109/ICINIS.2010.185","url":null,"abstract":"The main peak extraction method was proposed, considering the main peak uncertainty of multi-peak signal and the inadequateness of existing methods. The purpose of main peak extraction was achieved by relevant processing, and the ambiguity of sub-peak triggered was removed, the characteristic of single peak was restituted. In the same time the method was simulated, the conclusion proved that the main peak extraction method was effective.","PeriodicalId":319379,"journal":{"name":"2010 Third International Conference on Intelligent Networks and Intelligent Systems","volume":"5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122330344","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 non-embedded type area was analyzed by using the projection method according to its characteristics.
根据非嵌入型区域的特点，采用投影法对其进行了分析。
{"title":"The Application of the Projection Method in the Analysis of Non-embedded Type Area","authors":"L. Shanshan","doi":"10.1109/ICINIS.2010.108","DOIUrl":"https://doi.org/10.1109/ICINIS.2010.108","url":null,"abstract":"The non-embedded type area was analyzed by using the projection method according to its characteristics.","PeriodicalId":319379,"journal":{"name":"2010 Third International Conference on Intelligent Networks and Intelligent Systems","volume":"150 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122762087","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}
In the on-line fault diagnosis of auto engineer before factory in FAW, we adopt Bayesian network inference to get diagnosis result. To reduce inference complexity, an improved Bayesian network inference algorithm is presented based on graph search strategy under Martelli standard. Through proof, the complexity of the improved algorithm can reduce from exponential level to polynomial level. In experiment, the algorithm has been realized and been compared with expert system method, the experiment shows that the improved algorithm can improve the diagnosis efficiency. The algorithm has been applied in the on-line fault diagnosis of auto engineer before factory in FAW successfully.
{"title":"An Improved Bayesian Network Inference Algorithm","authors":"Xiaodan Zhang","doi":"10.1109/ICINIS.2010.183","DOIUrl":"https://doi.org/10.1109/ICINIS.2010.183","url":null,"abstract":"In the on-line fault diagnosis of auto engineer before factory in FAW, we adopt Bayesian network inference to get diagnosis result. To reduce inference complexity, an improved Bayesian network inference algorithm is presented based on graph search strategy under Martelli standard. Through proof, the complexity of the improved algorithm can reduce from exponential level to polynomial level. In experiment, the algorithm has been realized and been compared with expert system method, the experiment shows that the improved algorithm can improve the diagnosis efficiency. The algorithm has been applied in the on-line fault diagnosis of auto engineer before factory in FAW successfully.","PeriodicalId":319379,"journal":{"name":"2010 Third International Conference on Intelligent Networks and Intelligent Systems","volume":"79 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122148664","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}
Virtual proving ground (VPG) technology is applied to simulate vehicle ride comfort. The multi-body dynamics model for vehicle virtual simulation and random road surface are established under VPG. The body acceleration time-domain curves and frequency-domain power spectrums are obtained by LS-DYNA. Total weighted acceleration of vehicle ride comfort is evaluated by root-mean-square method. The effects of suspension system on the vehicle ride comfort are analyzed by changing stiffness and damper parameters of suspension. Simulation results show that simulation of vehicle ride comfort based on VPG can truly reflect real test condition , and results achieved are accurate and reliable.
{"title":"Simulation of Vehicle Ride Comfort Based on VPG","authors":"K. Chen, Jie Ying Gao","doi":"10.1109/ICINIS.2010.14","DOIUrl":"https://doi.org/10.1109/ICINIS.2010.14","url":null,"abstract":"Virtual proving ground (VPG) technology is applied to simulate vehicle ride comfort. The multi-body dynamics model for vehicle virtual simulation and random road surface are established under VPG. The body acceleration time-domain curves and frequency-domain power spectrums are obtained by LS-DYNA. Total weighted acceleration of vehicle ride comfort is evaluated by root-mean-square method. The effects of suspension system on the vehicle ride comfort are analyzed by changing stiffness and damper parameters of suspension. Simulation results show that simulation of vehicle ride comfort based on VPG can truly reflect real test condition , and results achieved are accurate and reliable.","PeriodicalId":319379,"journal":{"name":"2010 Third International Conference on Intelligent Networks and Intelligent Systems","volume":"102 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116675195","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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