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An urgent need for energy management has emerged all over the world because ever growing consumption demands will eventually surpass the supply of critical resources. Energy management should be more effective and efficient in smart cities. In this study, we propose a method for the energy management with a battery system of a smart city. An energy supply is optimized using the newsboy model. Energy...
Lack of human prior knowledge is one of the main reasons that semantic gap still remains when it comes to automatic multimedia understanding. In this work, we exploit the ontological structure of target concepts and propose an universal ontological inference framework for image understanding. The framework explicitly utilizes subclass and co-occurrence relation to effectively refine the coarse concept...
For the influence from the randomness of wind power output to the system operation, a model, which achieves the spinning reserve in wind power integrated system, is studied. With the modeling idea about combining power generation plan and reserve plan, minimizing the total cost of power production and spinning reserve as an objective, conditional value-at-risk is presented in this paper. Under regarding...
The aerodynamic properties of the Twin Swirl Combustor (TSC) are studied and discussed in different locations of air inlet and different flow ratio by numerical simulation. The calculation results reveal that the location of air inlet plays a more important role in the aerodynamic properties, compared with the flow rate, and in C3 (R1=0.055m), the recirculation zone and the swirling flow field can...
This paper presents the first work known publicly on spoken term detection from bilingual spontaneous speech using code-switched lattice-based structures for word and subword units. The corpus used is the lectures with Chinese as the host language and English as the guest language recorded for a real course offered in National Taiwan University. The techniques reported here have been successfully...
This paper proposes a generative model-based speaker clustering algorithm in the maximum a posteriori adapted Gaussian mixture model (GMM) mean supervector space. The algorithm can be viewed as an extension of the standard expectation maximization algorithm for fitting a mixture model to the data, which iterates between two steps - a sample re-assignment step (E-step) and a model re-estimation step...
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