Theorem proving based on the extension rule is a new reasoning method. It is, in a sense, potentially a complementary method to resolution based method. HRIER is a very fast extension rule algorithm with reduction rul...
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Theorem proving based on the extension rule is a new reasoning method. It is, in a sense, potentially a complementary method to resolution based method. HRIER is a very fast extension rule algorithm with reduction rules and heuristic function. DR is a fast ordering-based restricted resolution method in proposition logic. In order to make best use of the respective characteristic of the extension rule method and resolution method, this paper proposes a combined algorithm CDE based on HRIER and DR. And then the soundness and completeness of it are proved. The experiment results show CDE is a fast SAT solver.
One of the most prevalent security problems in network is the rampant propagation of email worms. Unlike active worms, the email worm has to be activated by user action in order to spread further. This paper deals wit...
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One of the most prevalent security problems in network is the rampant propagation of email worms. Unlike active worms, the email worm has to be activated by user action in order to spread further. This paper deals with modeling email worm propagation by analyzing and combining human factors. Impact of human factors on email worm propagation is investigated and discussed. Results of email worm propagation under a practical simulation environment show that the presented model well describes the email worm behavior. Conclusions are also drawn that infection probability decreases during evolution of worm infection due to the security consciousness rising, and highly connected nodes are more susceptible.
Classification of hyperspectral data with high spatial resolution from urban areas is investigated. The approach is an extension of existing approaches, using both spectral and spatial information for classification. ...
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Classification of hyperspectral data with high spatial resolution from urban areas is investigated. The approach is an extension of existing approaches, using both spectral and spatial information for classification. The spatial information is derived by mathematical morphology and principal components of the hyperspectral data set, generating a set of different morphological profiles. The whole data set is classified by the Random Forest algorithm. However, the computational complexity as well as the increased dimensionality and redundancy of data sets based on morphological profiles are potential drawbacks. Thus, in the presented study, feature selection is applied, using nonparametric weighted feature extraction and the variable importance of the random forests. The proposed approach is applied to ROSIS data from an urban area. The experimental results demonstrate that a feature reduction is useful in terms of accuracy. Moreover, the proposed approach also shows excellent results with a limited training set.
Theorem proving based on the extension rule is a new reasoning method. Based on the extension rule algorithm RIER, this paper presents a more efficient algorithm HRIER, which uses the heuristic strategy to guide the c...
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Theorem proving based on the extension rule is a new reasoning method. Based on the extension rule algorithm RIER, this paper presents a more efficient algorithm HRIER, which uses the heuristic strategy to guide the choosing of restricted searching space. The experiment results show HRIER improves the efficiency a lot, meanwhile it keeps the essence characteristic of extension rule method, namely it is still potentially a complementary method to resolution based methods.
Constraint Satisfaction Problem is an important branch of Artificial Intelligence, one typical algorithm to solve Constraint Satisfaction Problem is the searching algorithm based on backtracking. The Dynamic Backtrack...
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Constraint Satisfaction Problem is an important branch of Artificial Intelligence, one typical algorithm to solve Constraint Satisfaction Problem is the searching algorithm based on backtracking. The Dynamic Backtracking algorithm proposed by Ginsberg in 1993 is an efficient algorithm which uses backtracking integrates with constraint propagation. Now, according to the basic idea of dynamic backtracking, we put forward four implementary strategies and demonstrate that the efficiency and backtracking times of these four strategies are different The most efficient strategy of these four strategies is the Strategy2.1,it can significantly improve the efficiency and reduce the backtracking times. Anatomizing the results of experiments, we find the differences between these four strategies, then we propose an heuristic rules to improve dynamic backtracking algorithm on selecting a variable that has not been instantiated - Successful Assignment Principle. According to the Failure First Principle, we propose an optimization strategy that combine the Successful Assignment Principle with the Failure First Principle - Strategy 2.4. What is more ,the final test results show that efficiency of Strategy 2.4 is 1.595 ～2.227 times more than the that of Strategy 2.1.
Trusted network connect (TNC), whose goal is to improve network security from source, now has become hot topic in security domain. We proposed a new access model for the terminals without meeting the requirements in T...
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Trusted network connect (TNC), whose goal is to improve network security from source, now has become hot topic in security domain. We proposed a new access model for the terminals without meeting the requirements in TNC specifications. Also we discussed the work flow and communication process of presented model. Simulations show that the feasibility of the presented model used in the scenario where terminals fall short of network demand can pass the access authentication of network with TNC specifications.
One of the most prevalent security problems in network is the rampant propagation of email worms. In this paper game theory is suggested as a method for modeling and computing the probabilities of expected behaviors o...
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One of the most prevalent security problems in network is the rampant propagation of email worms. In this paper game theory is suggested as a method for modeling and computing the probabilities of expected behaviors of email users in the email worm propagation process. The game situation models the actions of the email users under the condition that at the time they open an attachment, the system may be infected. Results of email worm propagation simulation under a practical simulation environment show that well camouflaged worms spread more quickly and survive longer than naive worms, moreover, user's security consciousness and the update frequency of anti-virus software make great impact on email worm propagation.
Information fusion is an interdisciplinary research field aiming to combine and merge the information or data from different information sources. The output of information fusion system is a global schema through whic...
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Information fusion is an interdisciplinary research field aiming to combine and merge the information or data from different information sources. The output of information fusion system is a global schema through which users can get information or data from different dispersed sources. To generate a deep Web information fusion system is facing many challenges, because the nature of Web is different from those of traditional databases and multi-databases. The major challenge in a deep Web information fusion system is the data source modeling problem, which determine the technical method of the whole system. The query interfaces provided by the deep Web are the clues to disclose the hidden schemas. But the complicated semantic relationships in the query interfaces lead to the lower generality and ability of local as view (LAV) method in the traditional information fusion system. We present an approach that the semantic relationships between semantic related attributes can be evaluated by the WordNet, a kind of ontology instrument. The experiment is carried out on the famous dataset, and the result shows the efficiency of ontology extended LAV of building mappings between local views and mediator schema.
The Web has been dramatically deepened by the deep Web, which the traditional information fusion system shows disability to integrate. The myriad information hidden behind the deep Web attracts the considerable attent...
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The Web has been dramatically deepened by the deep Web, which the traditional information fusion system shows disability to integrate. The myriad information hidden behind the deep Web attracts the considerable attention from the researchers. The key element in a deep Web information fusion system is the data source modeling problem, which determine the whole technical method of the whole system. The query interfaces provided by the deep Web are the clues to disclose the hidden schemas. But the complicated semantic relationships in the query interfaces lead to the low generality and ability of local as view (LAV) method in the traditional information fusion system. An approach of evaluating the semantic relationships between the attributes in the query interfaces by utilizing WordNet, a typical ontology technique, is presented in this paper. The semantic relationships between semantic related attributes are evaluated by the semantic calculating method of WordNet. The meaningless attributes is instantiated by instance information embedded in the interfaces in order to attach correlated semantic information. The experiment is carried out in the real life domains, and the result shows the efficiency of ontology based semantic evaluating method in LAV.
This paper studies the technique of preprocessing in constraint satisfaction problem (CSP). Firstly, we propose a notion of entirety singleton consistency (ESC) and the algorithm, and then analyze the time and space c...
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This paper studies the technique of preprocessing in constraint satisfaction problem (CSP). Firstly, we propose a notion of entirety singleton consistency (ESC) and the algorithm, and then analyze the time and space complexity and correctness. Based on this, we present a new preprocessing algorithm SAC-ESC based on ESC, and prove its correctness. Furthermore, we use the divide-conquer strategy for the algorithm to automatically adapt to domain partition of various problems. In our experiments on random CSPs, pigeon problems, N-queens problems and benchmarks, the efficiency of our algorithm SAC-ESC is 3-20 times those of the existing SAC-SDS and SAC-3.
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