Instructional strategy plays a prominent role in traditional classrooms, but it is not widely noticed in e-learning environments. This study adopts the widespread pedagogical method of mastery learning and proposes an e-learning system architecture that considers the concept of process management and applications of mobile device. This study also offers several scenarios to explain how to use this kind of system. The proposed system could assist teachers to manage their students more easily and it can streamline the teaching processes. It could also make personalised teaching more popular and easier.
In the electricity market, the real-time balance of electricity generation and consumption is a main task. In view of this, power providers usually sign contracts with their critical consumers (i.e., usually large-scale industrial companies) for managing their capacity demands. On the other hand, aggregators group commercial and residential consumers, and integrate their demands to negotiate with power providers. With a proper grouping of numerous electricity consumers, aggregators help to ensure stable electric supply, and reduce the burden of managing many consumers. In this work, we thus propose a novel data clustering approach to group complementary consumers based on their usage patterns (i.e., daily electricity consumption curves.) Furthermore, we incorporate the technique of discrete wavelet transform to speed up the clustering process. Specifically, approximations reconstructed from only a few wavelet coefficients may precisely capture the shape of original usage patterns. Experimental results based on a real dataset show that our approach is promising in practical applications.
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