This paper resumes a research project developed in the concession area of AES Eletropaulo, the largest electrical energy distribution company in Brazil. First, the global standards of information exchange within power...This paper resumes a research project developed in the concession area of AES Eletropaulo, the largest electrical energy distribution company in Brazil. First, the global standards of information exchange within power transmission and distribution area were evaluated, allowing the definition of state of the art on the theme, followed by determining its applications considering technologies already applied by the company. The specifications needed for the generation of a data integration model are adapted to radial overhead network at company concession area. The project developed an intermediary connectivity layer, based on the CIM （common information model）, which enables corporative systems to communicate in a standard way, through the use of integrating technologies. It, therefore, enabled modeling all main subjects of an electrical network in an open, extensible and non-proprietary way, in a model that contains classes and attributes of such subjects, as well as their relationships. Calculation and planning products adopted by the company were integrated to the technological layer implemented.展开更多
Regarding the performance of traditional endpoint detection algorithms degrades as the environment noise level increases, a recursive calculating algorithm for higher-order cu- mulants over a sliding window is propose...Regarding the performance of traditional endpoint detection algorithms degrades as the environment noise level increases, a recursive calculating algorithm for higher-order cu- mulants over a sliding window is proposed. Then it is applied to the speech endpoint detection. Furthermore, endpoint detection is carried out with the feature of energy. Experimental results show that both the computational efficiency and the robustness against noise of the proposed algorithm are improved remarkably compared with traditional algorithm. The average prob- ability of correct point detection （Pc-point） of the proposed voice activity detection （VAD） is 6.07% higher than that of G.729b VAD in different noisy at different signal-noise ratios （SNRs） environments.展开更多
文摘This paper resumes a research project developed in the concession area of AES Eletropaulo, the largest electrical energy distribution company in Brazil. First, the global standards of information exchange within power transmission and distribution area were evaluated, allowing the definition of state of the art on the theme, followed by determining its applications considering technologies already applied by the company. The specifications needed for the generation of a data integration model are adapted to radial overhead network at company concession area. The project developed an intermediary connectivity layer, based on the CIM （common information model）, which enables corporative systems to communicate in a standard way, through the use of integrating technologies. It, therefore, enabled modeling all main subjects of an electrical network in an open, extensible and non-proprietary way, in a model that contains classes and attributes of such subjects, as well as their relationships. Calculation and planning products adopted by the company were integrated to the technological layer implemented.
基金supported by the National Natural Science Eoundation of China(61271352)
文摘Regarding the performance of traditional endpoint detection algorithms degrades as the environment noise level increases, a recursive calculating algorithm for higher-order cu- mulants over a sliding window is proposed. Then it is applied to the speech endpoint detection. Furthermore, endpoint detection is carried out with the feature of energy. Experimental results show that both the computational efficiency and the robustness against noise of the proposed algorithm are improved remarkably compared with traditional algorithm. The average prob- ability of correct point detection （Pc-point） of the proposed voice activity detection （VAD） is 6.07% higher than that of G.729b VAD in different noisy at different signal-noise ratios （SNRs） environments.
