Classification Methods Based on Pattern Discrimination Models for Web-Based Diagnosis of Rice Diseases

Two classification and identification methods based on pattern discrimination models and the majority-vote technique were investigated for implementing a World Wide Web-based system for the identification of rice diseases. The experiment was carried out using color and shape patterns in 425 images of three rice diseases, which were classified into four classes： two classes of leaf blast, and one class each of sheath blight and brown spot. A method consisting of two discrimination steps involving application of multiple discrimination models of a support vector machine gave the best result because of its capacity to evaluate the similarity of disease types. This accuracy of the method was 88% for leaf blast （A-type）, 94% for sheath blight, and 80% for leaf blast （B-type） and brown spot; on average, the accuracy of this method was 5% greater than that of the other method when three classes were used in the model. Although the accuracy of both methods was inadequate, the results of this study show that it is possible to estimate the least number of possible or similar diseases from a large number of diseases. Therefore, we conclude that there is merit in grouping classes into subgroups rather than attempting to discriminate between all classes simultaneously and that these methods are effective in identifying diseases for web-based diagnosis.

南海海槽西部俯冲带日向滩地区俯冲九州—帕劳洋脊的成像

为了研究九州—帕劳洋脊(KPR)俯冲部分与同震破裂扩展、地震活动性和浅部甚低频地震的关系,对南海海槽西部俯冲带日向滩地区进行了三维地震层析成像。结合岸上和近海记录的主动源和被动源地震数据,成像了从该海槽轴附近到海岸地区的深部板块。我们的结果表明,俯冲的九州—帕劳洋脊为西北—东南向的低速带,向下扩展到约30km的深度。在这个深度,我们认为俯冲的九州—帕劳洋脊与板块分离,成为上覆大陆板块的底座。由于过去大地震的同震滑动地区没有延伸到俯冲的九州—帕劳洋脊,我们认为九州—帕劳洋脊可能阻碍了破裂的扩展。俯冲的九州—帕劳洋脊的内部在很宽的深度上分布有活跃的板内地震活动。浅部甚低频地震在俯冲的九州—帕劳洋脊上部连续发生,而在俯冲的九州—帕劳洋脊的东北部却是间歇地出现。因此,俯冲的九州—帕劳洋脊看来是这个地区同震破裂扩展和地震现象的一个重要因素。