Network intrusion detection aims at distinguishing the attacks on the Internet from normal use of the Internet. this is a typical problem of the classfication,so intrusion detection(ID) can be seen as a pattern recogn...
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ISBN:
(纸本)9780769533223
Network intrusion detection aims at distinguishing the attacks on the Internet from normal use of the Internet. this is a typical problem of the classfication,so intrusion detection(ID) can be seen as a patternrecognition problem. In this paper, In this paper, we build the intrusion detection system using Adaboost, a prevailing machine learning algorithm, construction detection classification. In the algorithm, decision RBF neural network are used as weak classifiers. For the training sets is multi-attribute non-linear and massive, we use patternrecognition method of non-linear datadimension reduction algorithm-Isomap algorithm to feature extraction and to improve the speed and training for the handling of classified speed In the feature extraction after the feature of the dimension and Adaboost algorithm training rounds, were studied and experimented. Finally, the experiment proved that Isomap and Adaboost combination of testing the effectiveness of the mothod.
Coronary heart disease (CHD) remains the single leading cause of death of adults worldwide, but the traditional related factors can not explain the whole situations. Unstable angina (UA) is a type of CHD. the aim of t...
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ISBN:
(纸本)9781424447138
Coronary heart disease (CHD) remains the single leading cause of death of adults worldwide, but the traditional related factors can not explain the whole situations. Unstable angina (UA) is a type of CHD. the aim of this study was to establish clinical diagnose pattern for UA with blood stasis syndrome. Twenty-two biological parameters were detected on seven hundreds and seventy-six unstable angina with or without blood stasis syndrome patients. Using decision tree, we gain a pattern made by four biological parameters which could distinguish unstable angina with blood stasis syndrome patients from the none-blood stasis syndrome patients. the diagnosis accuracy could reach 82%. the obtained patterns are validated by 3-fold cross validation. though the diagnosis accuracy is not very high, the pattern may be useful in the syndrome clinical diagnosis in the future.
In this paper, we propose an automatic weak learners selection approach to perform advanced weak learners. In patternrecognition, the weak learners play a critical role in order to explain distinguishable features. O...
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We present a novel approach to crystallographic ligand density interpretation based on Zernike shape descriptors. Electron density for a bound ligand is expanded in an orthogonal polynomial series (3D Zernike polynomi...
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ISBN:
(纸本)9783642040306
We present a novel approach to crystallographic ligand density interpretation based on Zernike shape descriptors. Electron density for a bound ligand is expanded in an orthogonal polynomial series (3D Zernike polynomials) and the coefficients from this expansion are employed to construct rotation-invariant descriptors. these descriptors can be compared highly efficiently against large databases of descriptors computed front other molecules. In this manuscript we describe this process and show initial results from an electron density interpretation study oil a dataset containing over a hundred OMIT maps. We could identify the correct ligand as the first hit in about 30% of the cases, within the top five in a further 30% of the cases, and giving rise to an 80% probability of getting the correct ligand within the top ten matches. In all but a few examples, the top hit was highly similar to the correct ligand in both shape and chemistry. Further extensions and intrinsic limitations of the method are discussed.
On the difficulty for the current patternrecognition to deal with fuzzy uncertain information, in this paper, the author tries to give a definition of intuitionistic fuzzy relative entropy, and meanwhile introduces t...
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ISBN:
(纸本)9780769550169
On the difficulty for the current patternrecognition to deal with fuzzy uncertain information, in this paper, the author tries to give a definition of intuitionistic fuzzy relative entropy, and meanwhile introduces the weighted thought into fuzzy patternrecognition, putting forward the method of patternrecognition based on Weighted Intuitionistic Fuzzy Relative Entropy. the new method accurately describes and shows the uncertainty of historical information, effectively realizes the quantitative analysis of patternrecognition, and improves the reliability, accuracy, and the robust performance of the system. Finally, through the examples, the effectiveness and superiority are proved.
Concerning the actual status of protection in the power grid, a new strategy is proposed in this paper to evaluate the cascade tripping. Based on an operating equation of the backup relay protection, the relationship ...
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ISBN:
(纸本)9781538630136
Concerning the actual status of protection in the power grid, a new strategy is proposed in this paper to evaluate the cascade tripping. Based on an operating equation of the backup relay protection, the relationship between nodal injection power and the cascade tripping is analyzed. the relationship between node injection power and cascade tripping is reconstructed by patternrecognition technology, which is employed to assess the probability of cascading failure in a power network subjected to an initial failure. A certain number of samples are obtained by simulation in IEEE39 system, which are trained and tested based on BP neural network pattern. the validity of the assessment method is verified by the calculation result.
Withthe development of medical treatment, various kinds of medical images become more and more important. the traditional hierarchical structural image representation methods put too much emphasis upon the symmetry o...
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ISBN:
(纸本)9781424447138
Withthe development of medical treatment, various kinds of medical images become more and more important. the traditional hierarchical structural image representation methods put too much emphasis upon the symmetry of segmentation, they are not the optimal image representation methods. DNAM-based multi-valued image presentation method has not only better compression ability but also has better reconstruction quality. On the basis of the DNAM method, a new storage structure is presented in this paper. By describing dNAM, the coding and decoding algorithms of tag-matrix storage mode are given. the complexity of the algorithm is analyzed. According to the theoretical analysis and the result of the experiment, comparing withthe traditional NAM storage mode, the tag-matrix storage structure has obvious advantages. the method is valuable for the medical image representation.
Syntactic methods in patternrecognition have been used extensively in bioinformatics, and in particular, in the analysis of gene and protein expressions, and in the recognition and classification of biosequences, the...
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ISBN:
(纸本)9783642040306
Syntactic methods in patternrecognition have been used extensively in bioinformatics, and in particular, in the analysis of gene and protein expressions, and in the recognition and classification of biosequences, these methods are almost universally distance-based. this paper concerns the use of an Optimal and Information theoretic (OIT) probabilistic model [11] to achieve peptide classification using the information residing in their syntactic representations. the latter has traditionally been achieved using the edit distances required in the respective peptide comparisons. We advocate that, one can model the differences between compared strings as a mutation model consisting of random Substitutions, Insertions and Deletions (SID) obeying the OIT model. thus, in this paper, we show that the probability measure obtained. from the OIT model can be perceived as a sequence similarity metric, using which a Support Vector Machine (SVM)-based peptide classifier, referred to as OIT-SVM, can be devised. the classifier, which we have built has been tested for eight different "substitution" matrices and for two different data sets, namely, the HIV-1 Protease Cleavage sites and the T-cell Epitopes. the results show that the OIT model performs significantly better than the one which uses a Needleman-Wunsch sequence alignment score, and the peptide classification methods that previously experimented withthe same two datasets.
the proceedings contain 65 papers. the topics discussed include: inference and learning for active sensing, experimental design and control;large scale online learning of image similarity through ranking;inpainting id...
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ISBN:
(纸本)3642021719
the proceedings contain 65 papers. the topics discussed include: inference and learning for active sensing, experimental design and control;large scale online learning of image similarity through ranking;inpainting ideas for image compression;smoothed disparity maps for continuous American sign language recognition;human action recognition using optical flow accumulated local histograms;trajectory modeling using mixtures of vector fields;high speed human detection using a multiresolution cascade of histograms of oriented gradients;face-to-face social activity detection using data collected with a wearable device;estimating vehicle velocity using Image profiles on rectified images;kernel based multi-object tracking using gabor functions embedded in a region covariance matrix;and autonomous configuration of parameters in robotic digital cameras.
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