In this paper, we present a novel method to incorporate metadata into data mining. The method has many advantages. It can be completed automatically and is independent of a specific database. Firstly, we convert metadata into ontology. Then input a rule set to a reasoner, which supports rule-based inference over the ontology model. The outputs of the reasoner describe the prior knowledge in metadata. Finally, incorporate the prior knowledge into data mining.

This letter proposes a new weighted fair queueing algorithm, which adjusts dynamically each flow's service probability according to its weight and average packet length and then uses the service probability parameters to implement fair queueing. This solves the main drawback of traditional weighted fair queueing algorithms--the packet-based tracing of weight parameters. In addition, this letter proposes a novel service probability calculation method which solves the unfairness problem induced by the variable packet length.

Recently, Au et al. proposed a practical hierarchical identity-based encryption (HIBE) scheme and a hierarchical identity-based signature (HIBS) scheme. In this paper, we point out that there exists security weakness both for their HIBE and HIBS scheme. Furthermore, based on q-ABDHE, we present a new HIBE scheme which is proved secure in the standard model and it is also efficient. Compared with all previous HIBE schemes, ciphertext size as well as decryption cost are independent of the hierarchy depth. Ciphertexts in our HIBE scheme are always just four group elements and decryption requires only two bilinear map computations.

Traditional load shedding algorithms for data stream systems calculate current operator selectivity over several run periods and use them to determine where to shed load during the next run period. In this paper, we show that the current selectivity may change due to the implementation of load shedding. Our algorithm, called RLS, determines the optimum drop location by these changed selectivity rather than those pre-calculated values. Simulation results demonstrate that RLS achieves higher accuracy than traditional algorithms.

A multi-user space-time block coding (STBCa) system is a multi-access system where co-channel users employ space-time block codes (STBC). In this paper, we aimed at the design of efficient zero-forcing (ZF) receivers, especially ZF iterative interference cancellation (IC) receivers, for multi-user {G2, G3, G4} STBC systems with an arbitrary number of users, based on the identification of algebraic properties existing in the systems. First, we identify some algebraic properties for {G2, G3, G4} STBC systems. Then, utilizing these algebraic properties, we further expose two significative properties, called "ZF output uncorrelated property" and "ZF output equal Post-detection SNR property" respectively, for least-squares (LS) ZF receivers in multi-user {G2, G3, G4} STBC systems by detailed proofs. Based on the two properties, a novel LS ZF user-ordered successive interference cancellation (ZF UOSIC) detection algorithm is proposed subsequently. Finally, simulation results show that ZF UOSIC is superior to the conventional ZF IC and maximum-likelihood (ML) algorithms and the non-ordered ZF user-based SIC (ZF USIC) algorithm due to adopting iterative IC and optimal ordering among users, and has very close performance to the ZF symbol-ordered SIC but with lower complexity due to the fewer iterative times.

Iterative receivers, which perform MMSE detection and decoding iteratively, can provide significant performance improvement compared with noniterative method. However, due to the high computational cost and numerical instability, conventional MMSE detection using a priori information can not be implemented in hardware. In this letter, we propose a newly-built iterative receiver which is division-free and numerically stable, and then we analyze the results of a fixed-point simulation and present the hardware implementation architecture.