Traffic congestion is a very serious problem in large cities. With the number of vehicles increasing rapidly, especially in cities whose economy is booming, the situation is getting even worse. In this paper, by lever...
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Cybersecurity threats are increasing rapidly as hackers use advanced *** a result,cybersecurity has now a significant factor in protecting organizational *** detection systems(IDSs)are used in networks to flag serious...
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Cybersecurity threats are increasing rapidly as hackers use advanced *** a result,cybersecurity has now a significant factor in protecting organizational *** detection systems(IDSs)are used in networks to flag serious issues during network management,including identifying malicious traffic,which is a *** remains an open contest over how to learn features in IDS since current approaches use deep learning *** learning,which combines swarm intelligence and evolution,is gaining attention for further improvement against cyber *** this study,we employed a PSO-GA(fusion of particle swarm optimization(PSO)and genetic algorithm(GA))for feature selection on the CICIDS-2017 *** achieve better accuracy,we proposed a hybrid model called LSTM-GRU of deep learning that fused the GRU(gated recurrent unit)and LSTM(long short-term memory).The results show considerable improvement,detecting several network attacks with 98.86%accuracy.A comparative study with other current methods confirms the efficacy of our proposed IDS scheme.
Answer selection aims at identifying the correct answer for a given question from a set of potentially correct answers. Contrary to previous works, which typically focus on the semantic similarity between a question a...
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As context-aware systems become more widespread and mobile there is an increasing need for a common distributed event platform for gathering context information and delivering to context-aware applications. The likely...
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As context-aware systems become more widespread and mobile there is an increasing need for a common distributed event platform for gathering context information and delivering to context-aware applications. The likely heterogeneity across the body of context information can be addressed using runtime reasoning over ontology-based context models. However, existing knowledge-based reasoning is not typically optimised for real-time operation so its inclusion in any context delivery platform needs to be carefully evaluated from a performance perspective. In this paper we propose a benchmark for knowledge-based context delivery platforms and in particular examine suitable knowledge benchmarks for assessing the ability of platforms to deal with semantic interoperability
The recent rise of conversational applications such as online customer service systems and intelligent personal assistants has promoted the development of conversational knowledge base question answering (ConvKBQA). D...
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Open Government data (OGD) refers to the provision of data produced by the government to the general public, in a format that is readily readable and can be used by machines with ease. It can also promote transparency...
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knowledge computation tasks are often infeasible for large data sets. This is in particular true when deriving knowledge bases in formal concept analysis (FCA). Hence, it is essential to come up with techniques to cop...
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In most accounts of common-sense reasoning, only the most preferred among models supplied by the evidence are retaiined (and the rest eUminated) in order to enheince the inferential prowess. One problem with this stra...
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