Ontologies undergo changes for reasons such as changes in knowledge, meeting varying application requirements. Thus, for different versions of a considered ontology, it is important to clarify the difference between t...
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Ontologies undergo changes for reasons such as changes in knowledge, meeting varying application requirements. Thus, for different versions of a considered ontology, it is important to clarify the difference between them. The difference above refers to the logical difference, not syntactic one. Examples of the logical difference include the difference in taxonomy, concept subsumption difference and query difference. These has been well investigated for the lightweight description logic EL because of its tractability and successful application in bio-medical ontologies. Fuzzy EL+ has been put forward and applied in view-based searching in Semantic portals. Thus comes the problem of comparing fuzzy ontologies of different versions and clarifying the difference. In this paper, we define the logical difference of two fuzzy EL+ ontologies. For fuzzy EL+ ontologies of different versions we investigate how to compute the difference in taxonomy and concept subsumption difference. We also explore how to compute approximation of the logical difference of two EL terminologies. Our work can be applied in the scenario of EL+ ontologies with access control if the set of all access rights is a linear order.
Soil fertility grading is an important issue in the agriculture domain, AI based approach has been applied recently. But in most circumstance data obtaining is a expensive and time consuming procedure, sometimes even ...
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In order to solve the security issues of mobile vehicles in the Internet of vehicles, such as identity authentication and integrality verification, we apply the trusted cryptography module (TCM) into the on-vehicle el...
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In order to solve the security issues of mobile vehicles in the Internet of vehicles, such as identity authentication and integrality verification, we apply the trusted cryptography module (TCM) into the on-vehicle electronic systems. TCM has many security features, such as integrality measurement, integrality report and protected storage, by which the on-vehicle electronic systems achieve a trusted boot process. Data and information of vehicles are encrypted before storage and transmission. The experiments show that with the authorization on the vehicular platform, the TCM will improve the credibility and security of the Internet of Vehicles.
With the rapid development of vehicle electronic systems, the vehicle software failure rate has also been rising over time. Providing the convenient and effective maintenance on the vehicle software has become a funda...
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ISBN:
(纸本)9787894631046
With the rapid development of vehicle electronic systems, the vehicle software failure rate has also been rising over time. Providing the convenient and effective maintenance on the vehicle software has become a fundamental block constraining the progress of vehicle electronic industry. A trusted remote remediation framework for vehicle software is presented and realized to enable drivers to online upgrade version or fix bug without needing for driving the vehicles back to the factories or using the specific devices. In this framework, the trusted remediation server takes responsibility for managing and providing the patch programs and the trusted remediation client can download directly from the remediation server to upgrade programs or fix software errors, achieving the self-repair in complex vehicular networks.
The rigorous theoretical analyses of algorithms for #SAT have been proposed in the literature. As we know, previous algorithms for solving #SAT have been analyzed only regarding the number of variables as the paramete...
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The satisfiability problem is the core problem in artificial intellgence. The algorithm directional resolution(DR) is a well known method based on resolution for satisfiability problem. But the number of clauses has g...
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The satisfiability problem is the core problem in artificial intellgence. The algorithm directional resolution(DR) is a well known method based on resolution for satisfiability problem. But the number of clauses has great impact on the efficiency of the method. In this paper, an algorithm SRDR is proposed to solve the problem. SRDR is based on algorithm DR and splitting rule. By using splitting rule, the number of clauses can be reduced obviously. Furthermore, the strategy MO is designed for SRDR. With the strategy, we can get a better order of variables and the efficiency of SRDR is improved. The experimental data shows that SRDR is more efficient that DR.
In recent years, with the development of the wireless sensor networks, the localization method receives the attention of many researchers. However, due to the network cost and characteristics of sensor nodes, most of ...
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In recent years, with the development of the wireless sensor networks, the localization method receives the attention of many researchers. However, due to the network cost and characteristics of sensor nodes, most of the localization algorithms are not well suitable for the wireless sensor network, positioning error is relatively large. Based on the regular moving anchor node and RSSI ranging technique assisting positioning, in this paper, we proposed the RMADV-Hop (Regular Moving Anchor DV-Hop) localization algorithm to improve the DV-Hop algorithm. In the same network condition, we simulated these two localization algorithms using the omnet++ simulation software. Simulation results show that RMADV-Hop algorithm uses less anchor nodes than the DV-Hop algorithm, reduces the cost of network hardware, approximately achieves the evenly distribution of anchor nodes, and can get higher positioning accuracy than the DV-Hop algorithm in the randomly distributed network.
Model counting is an important problem in artificial intelligence and is applied in several areas of information science. Extension rule is a method which could be used to count models. But it's not appropriate wh...
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Model counting is an important problem in artificial intelligence and is applied in several areas of information science. Extension rule is a method which could be used to count models. But it's not appropriate when clause length is short or clause number is huge. After studying extension rule, we found that the satisfiability problem could be solved by hitting set algorithms. And the models could be counted with extension rule after calculating hitting sets of a clause set. Therefore, we proposed an algorithm MCBE in this paper. With Boolean algebra, MCBE could easily calculate hitting sets of a clause set. Then, it gives the number of models with extension rule. The test results show that when clause length is short and clause number is big enough, the algorithm is more efficiency than the algorithm CDP and CER.
Mobile node localization is one of the challenging and crucial issues in wireless sensor networks. The paper proposed a new approach to mobile localization, called LLA (Lee Localization Algorithm), to mitigate TOA mea...
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The satisfiability (SAT) problem is an important problem of automated reasoning. In the past decades, many methods of SAT are proposed, such as method based on resolution, method based on tableau and method based on e...
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The satisfiability (SAT) problem is an important problem of automated reasoning. In the past decades, many methods of SAT are proposed, such as method based on resolution, method based on tableau and method based on extension rule. Based on the study of extension rule, we find that the SAT problem can be solved with hitting set algorithms. If we can find a hitting set of a clause set, and if there is not any pair of complementary literals in the hitting set, the clause set is satisfiable. Algorithm BHS based on Boolean algebra proposed by Jiang is an efficient hitting set algorithm. SSBF proposed in this paper is a revised algorithm of BHS that can be used to judge the satisfiability of a clause set. The test result shows that SSBF is an efficient algorithm.
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