Ziyang Chen

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In this paper, we focus on efficient keyword query processing for XML data based on the SLCA and ELCA semantics. We propose a novel form of inverted lists for keywords which include IDs of nodes that directly or indirectly contain a given keyword. We propose a family of efficient algorithms that are based on the set intersection operation for both(More)
Natural enemies have long been used in biological control programs to mitigate the damage caused by herbivory. Many herbivorous insect species also act as plant virus vectors, enabling virus transmission from plant to plant and hence disease development in a plant population. Whilst an intuitive assumption would be to expect a decrease in vector numbers to(More)
Vehicle trajectories are one of the most important data in location-based services. The quality of trajectories directly affects the services. However, in the real applications, trajectory data are not always sampled densely. In this paper, we study the problem of recovering the entire route between two distant consecutive locations in a trajectory. Most(More)
Efficiently answering XML keyword queries has attracted much research effort in the last decade. One key factors resulting in the inefficiency of existing methods are the common-ancestor-repetition (CAR) and visiting-useless-nodes (VUN) problems. In this paper, we propose a generic top-down processing strategy to answer a given keyword query w.r.t.(More)
Instead of using a single large aperture antenna to implement track and commute with spatial targets, array-based receiving architecture is quickly becoming an attractive approach due to its low cost, flexibility and robustness. In this paper, we consider a scene in which multiple receiving sensors are randomly distributed. Two co-channel signals from(More)
Temozolomide (TMZ) is the main chemotherapeutic drug utilized for the treatment of glioblastoma multiforme (GMB), however, drug resistance often leads to tumor recurrence and poor outcomes. GMB cell lines were treated with TMZ for up to two weeks and then subjected to proteomics analysis to identify the underlying molecular pathology that is associated with(More)