The turbid, low-light waters characteristic of aquaculture ponds have made it difficult or impossible for previous video cameras to provide clear imagery of the ponds’ benthic habitat. We developed a highly sensitive, underwater video system (UVS) for this particular application and tested it in shrimp ponds having turbidities typical of those in southern Taiwan. The system’s high-quality video stream and images, together with its camera capacity (up to nine cameras), permit in situ observations of shrimp feeding behavior, shrimp size and internal anatomy, and organic matter residues on pond sediments. The UVS can operate continuously and be focused remotely, a convenience to shrimp farmers. The observations possible with the UVS provide aquaculturists with information critical to provision of feed with minimal waste; determining whether the accumulation of organic-matter residues dictates exchange of pond water; and management decisions concerning shrimp health.

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Compiling documents in extensible markup language (XML) plays an important role in accessing data services. An efficient query service should be based on a skillful representation that can support query diversification and solve ambiguity in order to improve highprecision search capabilities. However, to the best of our knowledge, research on query diversification, target hierarchical level and the problem of ambiguity is insufficient. In this study we aimed to solve these problems so that the results are able not only to satisfy query diversification, but also to offer better precision compared with the existing twig join algorithms. An extended twig join Swift (TJSwift) associated with adjacent linked lists for the provision of efficient XML query services is also proposed, whereby queries can be versatile in terms of predicates. It can completely preserve hierarchical information; in addition, the new index generated from XML is used to save semantic information.

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