Successful prediction of protein domain boundaries provides valuable information not only for the computational structure prediction of muhi-domain proteins but also for the experimental structure determination. A nov...Successful prediction of protein domain boundaries provides valuable information not only for the computational structure prediction of muhi-domain proteins but also for the experimental structure determination. A novel method for domain boundary prediction has been presented, which combines the support vector machine with domain guess by size algorithm. Since the evolutional information of multiple domains can be detected by position specific score matrix, the support vector machine method is trained and tested using the values of position specific score matrix generated by PSI-BLAST. The candidate domain boundaries are selected from the output of support vector machine, and are then inputted to domain guess by size algorithm to give the final results of domain boundary, prediction. The experimental results show that the combined method outperforms the individual method of both support vector machine and domain guess by size.展开更多
A number of automated video shot boundary detection methods for indexing a videosequence to facilitate browsing and retrieval have been proposed in recent years.Among these methods,the dissolve shot boundary isn't...A number of automated video shot boundary detection methods for indexing a videosequence to facilitate browsing and retrieval have been proposed in recent years.Among these methods,the dissolve shot boundary isn't accurately detected because it involves the camera operation and objectmovement.In this paper,a method based on support vector machine (SVM) is proposed to detect thedissolve shot boundary in MPEG compressed sequence.The problem of detection between the dissolveshot boundary and other boundaries is considered as two-class classification in our method.Featuresfrom the compressed sequences are directly extracted without decoding them,and the optimal classboundary between two classes are learned from training data by using SVM.Experiments,whichcompare various classification methods,show that using proposed method encourages performance ofvideo shot boundary detection.展开更多
In the image steganalysis,the training samples often determine the performance of the model when the features and classification are in the same condition.However the existing research on steganalysis lacks the in-dep...In the image steganalysis,the training samples often determine the performance of the model when the features and classification are in the same condition.However the existing research on steganalysis lacks the in-depth study of the classifier's training method which may deeply influence the detection performance.This paper provides an optimization of universal steganalysis based on the boundary samples classification concerning about image steganalysis.This paper proposes a strategy of selecting boundary samples in steganalysis and divides the training samples into good samples,poor samples and boundary samples three categories and then chose the optimal threshold to get boundary samples through experiments.The experimental results show the effectiveness of boundary sample,which dramatically improve detection capability especially for the low embedding rate Stego-image.展开更多
为了提高生活污水处理工艺流程设计的效率,建立污水处理工艺数据库,用以保存从现实生活污水处理工艺流程抽象而来的数据样本。使用基于边界点的支持向量机(support vector machine classification algorithm based on boundary points,B...为了提高生活污水处理工艺流程设计的效率,建立污水处理工艺数据库,用以保存从现实生活污水处理工艺流程抽象而来的数据样本。使用基于边界点的支持向量机(support vector machine classification algorithm based on boundary points,BP-SVM)的工艺流程设计算法选择工艺,设置多个BP-SVM解决多分类问题,并使用遗传算法(genetic algorithm,GA)对BP-SVM参数进行参数寻优。结果表明:工艺流程设计算法给出了合适的方案,准确率达到94%,并且与其他算法相比消耗更小。证明了算法的可行性与有效性。展开更多
基金Supported by the National Natural Science Foundation of China （No. 60435020）
文摘Successful prediction of protein domain boundaries provides valuable information not only for the computational structure prediction of muhi-domain proteins but also for the experimental structure determination. A novel method for domain boundary prediction has been presented, which combines the support vector machine with domain guess by size algorithm. Since the evolutional information of multiple domains can be detected by position specific score matrix, the support vector machine method is trained and tested using the values of position specific score matrix generated by PSI-BLAST. The candidate domain boundaries are selected from the output of support vector machine, and are then inputted to domain guess by size algorithm to give the final results of domain boundary, prediction. The experimental results show that the combined method outperforms the individual method of both support vector machine and domain guess by size.
文摘A number of automated video shot boundary detection methods for indexing a videosequence to facilitate browsing and retrieval have been proposed in recent years.Among these methods,the dissolve shot boundary isn't accurately detected because it involves the camera operation and objectmovement.In this paper,a method based on support vector machine (SVM) is proposed to detect thedissolve shot boundary in MPEG compressed sequence.The problem of detection between the dissolveshot boundary and other boundaries is considered as two-class classification in our method.Featuresfrom the compressed sequences are directly extracted without decoding them,and the optimal classboundary between two classes are learned from training data by using SVM.Experiments,whichcompare various classification methods,show that using proposed method encourages performance ofvideo shot boundary detection.
基金Sponsored by the National Natural Science Foundation of China(Grant No.61373169 and 61272453)Doctoral Fund of Ministry of Education of China(Grant No.0110141130006)
文摘In the image steganalysis,the training samples often determine the performance of the model when the features and classification are in the same condition.However the existing research on steganalysis lacks the in-depth study of the classifier's training method which may deeply influence the detection performance.This paper provides an optimization of universal steganalysis based on the boundary samples classification concerning about image steganalysis.This paper proposes a strategy of selecting boundary samples in steganalysis and divides the training samples into good samples,poor samples and boundary samples three categories and then chose the optimal threshold to get boundary samples through experiments.The experimental results show the effectiveness of boundary sample,which dramatically improve detection capability especially for the low embedding rate Stego-image.
文摘为了提高生活污水处理工艺流程设计的效率,建立污水处理工艺数据库,用以保存从现实生活污水处理工艺流程抽象而来的数据样本。使用基于边界点的支持向量机(support vector machine classification algorithm based on boundary points,BP-SVM)的工艺流程设计算法选择工艺,设置多个BP-SVM解决多分类问题,并使用遗传算法(genetic algorithm,GA)对BP-SVM参数进行参数寻优。结果表明:工艺流程设计算法给出了合适的方案,准确率达到94%,并且与其他算法相比消耗更小。证明了算法的可行性与有效性。
