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Many researchers in database and machine learning fields are primarily interested in data mining because it offers opportunities to discover useful information and important relevant patterns in large databases. Most previous studies have shown how binary valued transaction data may be handled. Transaction data in real-world applications usually consist of quantitative values, so designing a sophisticated data-mining algorithm able to deal with various types of data presents a challenge to workers in this research field. In the past, we proposed a fuzzy data-mining algorithm to find association rules. Since sequential patterns are also very important for real-world applications, this paper thus focuses on finding fuzzy sequential patterns from quantitative data. A new mining algorithm is proposed, which integrates the fuzzy-set concepts and the AprioriAll algorithm. It first transforms quantitative values in transactions into linguistic terms, then filters them to find sequential patterns by modifying the AprioriAll mining algorithm. Each quantitative item uses only the linguistic term with the maximum cardinality in later mining processes, thus making the number of fuzzy regions to be processed the same as the number of the original items. The patterns mined out thus exhibit the sequential quantitative regularity in databases and can be used to provide some suggestions to appropriate supervisors.

Energy efficiency is an important issue for wireless sensor networks (WSNs). A MAC protocol for WSNs may tolerate higher packet latency in order for minimizing energy consumption, but such a MAC protocol may not accommodate real-time applications. In this paper, we present a hybrid MAC protocol that minimizes both energy consumption and packet latency simultaneously. The protocol utilizes a cross-layer approach that dynamically switches the MAC behavior between TDMA and CSMA based on the routing information of AODV. The nodes which are not involved in data transmission are kept in TDMA mode to minimize their energy consumption. When a node receives a routing request message, it switches to CSMA mode for receiving subsequent data packets promptly. We evaluate the performance of our protocol with various network density. The simulation results show that our protocol can improve both energy efficiency and packet latency of WSNs.

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