"符号学方阵"是巴黎学派的符号学家格雷马斯在学术上除"行动元模型"之外的又一重要贡献。该方阵旨在解决意义的构成方式这一重大问题,故而在学术上有着极广泛的适用性(例如,叙事分析、文化批评等)。格雷马斯本人也..."符号学方阵"是巴黎学派的符号学家格雷马斯在学术上除"行动元模型"之外的又一重要贡献。该方阵旨在解决意义的构成方式这一重大问题,故而在学术上有着极广泛的适用性(例如,叙事分析、文化批评等)。格雷马斯本人也曾在《受符号学制约的游戏》(Les jeux des contraintes sémiotiques)一文中提到,由本方阵在赋值研究中延伸得到的三个模型可作分析小说作品人物关系之用。然而格雷马斯在这个方向上并没有给出更多更详细的分析。故而本文即从此处着眼,试图通过对法国文学史上一干小说人物关系的例证分析以及对格雷马斯关于符号学方阵的相关理论的梳理,以期得到关于小说人物关系分析的具体模型。展开更多
The integration of the Lab model with the extended histogram of oriented gradients （EHOG） is proposed to improve the accuracy of human appearance matching across disjoint camera views under perturbations such as ill...The integration of the Lab model with the extended histogram of oriented gradients （EHOG） is proposed to improve the accuracy of human appearance matching across disjoint camera views under perturbations such as illumination changes and different viewing angles. For the Lab model that describes the global information of observations, a sorted nearest neighbor clustering method is proposed for color clustering and then a partitioned color matching method is used to calculate the color similarity between observations. The Bhattacharya distance is employed for the textural similarity calculation of the EHOG which describes the local information. The global information, which is robust to different viewing angles and scale changes, describes the observations well. Meanwhile, the use of local information, which is robust to illumination changes, can strengthen the discriminative ability of the method. The integration of global and local information improves the accuracy and robustness of the proposed matching approach. Experiments are carried out indoors, and the results show a high matching accuracy of the proposed method.展开更多
Based on potted plant experiment, BP-artifieial neural network was used to simulate crop evapotranspiration and 3 kinds of artificial neural network models were constructed as ET1 （meteorological factors）, ET2（ met...Based on potted plant experiment, BP-artifieial neural network was used to simulate crop evapotranspiration and 3 kinds of artificial neural network models were constructed as ET1 （meteorological factors）, ET2（ meteorological factors and sowing days） and ET3 （meteorological factors, sowing days and water content）. And the predicted result was compared with actual value ET that was obtained by weighing method. The results showed that the ET3 model had higher calculation precision and an optimum BP-artificial neural network model for calculating crop evapotranspiration.展开更多
文摘"符号学方阵"是巴黎学派的符号学家格雷马斯在学术上除"行动元模型"之外的又一重要贡献。该方阵旨在解决意义的构成方式这一重大问题,故而在学术上有着极广泛的适用性(例如,叙事分析、文化批评等)。格雷马斯本人也曾在《受符号学制约的游戏》(Les jeux des contraintes sémiotiques)一文中提到,由本方阵在赋值研究中延伸得到的三个模型可作分析小说作品人物关系之用。然而格雷马斯在这个方向上并没有给出更多更详细的分析。故而本文即从此处着眼,试图通过对法国文学史上一干小说人物关系的例证分析以及对格雷马斯关于符号学方阵的相关理论的梳理,以期得到关于小说人物关系分析的具体模型。
基金The National Natural Science Foundation of China(No.60972001)the Science and Technology Plan of Suzhou City(No.SG201076)
文摘The integration of the Lab model with the extended histogram of oriented gradients （EHOG） is proposed to improve the accuracy of human appearance matching across disjoint camera views under perturbations such as illumination changes and different viewing angles. For the Lab model that describes the global information of observations, a sorted nearest neighbor clustering method is proposed for color clustering and then a partitioned color matching method is used to calculate the color similarity between observations. The Bhattacharya distance is employed for the textural similarity calculation of the EHOG which describes the local information. The global information, which is robust to different viewing angles and scale changes, describes the observations well. Meanwhile, the use of local information, which is robust to illumination changes, can strengthen the discriminative ability of the method. The integration of global and local information improves the accuracy and robustness of the proposed matching approach. Experiments are carried out indoors, and the results show a high matching accuracy of the proposed method.
基金Supported by the National Natural Science Foundation of China(50609022)~~
文摘Based on potted plant experiment, BP-artifieial neural network was used to simulate crop evapotranspiration and 3 kinds of artificial neural network models were constructed as ET1 （meteorological factors）, ET2（ meteorological factors and sowing days） and ET3 （meteorological factors, sowing days and water content）. And the predicted result was compared with actual value ET that was obtained by weighing method. The results showed that the ET3 model had higher calculation precision and an optimum BP-artificial neural network model for calculating crop evapotranspiration.
