This paper presents an interactive transfer function design tool based on ellipsoidal Gaussian transfer functions (ETFs). Our approach explores volumetric features in the statistical space by modeling the space using ...
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ISBN:
(纸本)9781424466856
This paper presents an interactive transfer function design tool based on ellipsoidal Gaussian transfer functions (ETFs). Our approach explores volumetric features in the statistical space by modeling the space using the Gaussian mixture model (GMM) with a small number of Gaussians to maximize the likelihood of feature separation. Instant visual feedback is possible by mapping these Gaussians to ETFs and analytically integrating these ETFs in the context of the pre-integrated volume rendering process. A suite of intuitive control widgets is designed to offer automatic transfer function generation and flexible manipulations, allowing an inexperienced user to easily explore undiscovered features with several simple interactions. Our GPU implementation demonstrates interactive performance and plausible scalability which compare favorably with existing solutions. The effectiveness of our approach has been verified on several datasets.
Today, almost all the C2C e-commerce community member reputation evaluating algorithms are time sensitive. The reputation of a community member is accumulated after transactions and the increment of reputation after a...
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Diffie-Hellman key exchange algorithm, which is used in regular scenes base on the discrete logarithm problem, demands that typically two communication parties should struck up a lively conversation leading to a long-...
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ISBN:
(纸本)9781424485017
Diffie-Hellman key exchange algorithm, which is used in regular scenes base on the discrete logarithm problem, demands that typically two communication parties should struck up a lively conversation leading to a long-term dependable fellowship. A high efficiency the polymorphic key exchange algorithm is proposed that is based on the polymorphic key exchange protocol. The identity information of two parties can be appended to the agreement. Both communication parties use their PRNGs to finish the polymorphic virtual S-box together. The security of the PRNG was analyzed by the Strict Avalanche Criterion and some experimental results. It was proposed that the polymorphic key exchange algorithm can become a broad agreement in irregular scenes.
With the spread use of the computers, a new crime space and method are presented for criminals. Thus computer evidence plays a key part in criminal cases. Traditional computer evidence searches require that the comput...
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With the spread use of the computers, a new crime space and method are presented for criminals. Thus computer evidence plays a key part in criminal cases. Traditional computer evidence searches require that the computer specialists know what is stored in the given computer. Binary-based information flow tracking which concerns the changes of control flow is an effective way to analyze the behavior of a program. The existing systems ignore the modifications of the data flow, which may be also a malicious behavior. Thus the function recognition is introduced to improve the information flow tracking. Function recognition is a helpful technique recognizing the function body from the software binary to analyze the binary code. And that no false positive and no false negative in our experiments strongly proves that our approach is effective.
In this paper we have developed a discriminative word alignment method using the liner CRF model for Mongolian-English language pair. Discriminative approaches have the ability to use large variety of features flexibl...
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In this paper we have developed a discriminative word alignment method using the liner CRF model for Mongolian-English language pair. Discriminative approaches have the ability to use large variety of features flexibly and to combine information from various sources. According to the differences between Mongolian and English, we discuss and select the different features, and experiments on Mongolian-English task demonstrate our word alignment model's superiority in performance over the popular GIZA++.
The variations in testing requirements often result in the problem of numerous test cases and low efficiency in regression testing. To solve this problem, a reduction method of testing requirements is proposed based o...
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The variations in testing requirements often result in the problem of numerous test cases and low efficiency in regression testing. To solve this problem, a reduction method of testing requirements is proposed based on the relation mode in this paper. This method analyzes the relationship between the modules and testing requirements, then determines the varied regression testing requirements, and gets the final testing requirement set by reduction of the varied regression testing requirement set and the original testing requirement set in three times. If test cases are generated and reduced on the basis of the testing requirement reduction set, the efficiency of the regression testing will be improved.
Combined blind signature with certificateless cryptography, we propose an efficient provable certificateless blind signature scheme, which is proved to be neither easier than the q-strong Diffie-Hellman problem nor ha...
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Combined blind signature with certificateless cryptography, we propose an efficient provable certificateless blind signature scheme, which is proved to be neither easier than the q-strong Diffie-Hellman problem nor harder than the inverse computational Diffie-Hellman problem. It enjoys all the security requirements of blind signature and is existential unforgeable against adaptively chosen message and chosen identity adversary in the random oracle model. The signing algorithm of the proposed scheme does not require any pairing computation, and the verification algorithm only needs one pairing computation. Compared with other known schemes, our scheme is more efficient by reason of requiring the least computational effort.
This paper presents a discriminative model for part of speech tagging of traditional *** use Maximum Entropy Model with Morphological features of Mongolian. First, the context feature templates are defined and extract...
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This paper presents a discriminative model for part of speech tagging of traditional *** use Maximum Entropy Model with Morphological features of Mongolian. First, the context feature templates are defined and extracted from the training corpus. Then, the parameters of maximum entropy probability models are calculated. Experimental results show that integration of morphological features of Maximum Entropy Model for Mongolian part of speech tagging outperform HMM since they are flexible enough to capture many correlated non-independent features.
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