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Analyzing large textual collections has become increasingly challenging given the size of the data available and the rate that more data is being generated. Topic-based text summarization methods coupled with interactive visualizations have presented promising approaches to address the challenge of analyzing large text corpora. As the text corpora and vocabulary grow larger, more topics need to be...
This paper addresses the problem of failure diagnosis in component-based discrete event systems. In this paper we propose a method to obtain the set of components when dealing with diagnosis in large complex discrete event systems. In the new method, before disassembling the system into components, we need to identify whether insert communication events into the system or not. When analyzing the diagnosability,...
When diagnosing dynamic system represented as discrete-event systems, it needs to find what happened to the systems from observations. The behavior of system could be represented by automaton model. The diagnostic task consists in determining the models compatible with the observations, but the global computation which is needed in synchronization costs exponential time. In this paper we propose a...
In this paper, a novel statistics-driven spectrum sensing algorithm is developed for improving spectrum sensing efficiency in the media access control (MAC) layer of cognitive radio (CR) systems. The proposed algorithm aims to achieve higher spectrum sensing efficiency and spectrum access opportunity by prioritizing channels for fine sensing based on the statistical likelihood of channel availability...
In this paper, a novel cooperative stochastic channel prioritization algorithm is presented for the purpose of improving spectrum sensing efficiency in cooperative cognitive radio systems. The proposed algorithm achieves the goal by prioritizing the channels for fine sensing based on both local statistics obtained by the cognitive radio as well as long-term spatiotemporal statistics obtained from...
As in traditional relational database, there also exists redundant data dependency in temporal database. Effective elimination of redundant data dependency is the foundation of further normalization for temporal databases. In order to eliminate redundant dependencies, cover of data dependency sets should be investigated. Coexist of multiple time granularities, temporal functional dependencies(TFDs)...
In this paper, an efficient approach to Medium Access Control layer spectrum sensing algorithm is introduced for the purpose of peer-to-peer communications with cognitive radio. The proposed algorithm is designed specifically for the application scenario of information gathering in a full-loaded legacy voice and data band, where the cognitive radio tries to utilize other available licensed bands through...
This paper presents a unified kinematic model of a family of four different topologies of translational parallel manipulators of general geometry. With this unified model, it becomes possible to implement kinematic synthesis algorithms that can take both geometrical and topological parameters as design variables. Using this model, we derive a single set of algebraic equations representing the necessary...
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