中国对虾幼体期视觉器官的发育

于１９９４年３－５月，以中国对虾无节幼体６个亚期，蚤状幼体３个亚期，糖虾幼体３个亚期及仔虾各时期的幼体为材料，用日产Ｏｌｙｍｐｕｓ万能研究显微镜观察研究各期幼体单眼及复眼的发育。结果表明：在中国对虾无节幼体Ｎ１－Ｎ６６个亚期，单眼的两侧均有复眼的原基组织。     

预警地震在地震预测中的意义

对新疆1970-2002年地震资料以不同范围、不同震级进行全时空扫描。结果表明，新疆台网监测能力较好地区绝大多数6级以上地震前地震活动关联图较为清晰。提出了预警地震的概念，认为预警地震在短临预报方面有一定的作用。     

Research relevance, 'knowledge transfer' and the geographies of CASE studentship collaboration

The Co-operative Awards in Science and Engineering (CASE) studentship programme of the UK Research Councils provide one example of wider efforts internationally to encourage so-called 'knowledge transfer' and thereby harness publicly supported university research more closely to the goals of national competitiveness, regional economic development and local regeneration. In this paper we describe the implications of how the various UK research councils have interpreted the objectives and beneficiaries of 'knowledge transfer', both for the relative opportunities available to human and physical geographers for collaboration through CASE and for the sorts of values that their research must serve. Then, we draw on unpublished data from the Economic and Social Research Council (ESRC) to explore the geographies of CASE studentship allocation and participation. The broad regional and institutional patterns of participation we describe have important implications for ongoing debates in the UK about research selectivity and the role of the university as an engine of local development, while the striking disciplinary patterns of CASE participation, and in particular the overwhelming success of geographers in this competitive programme, provide an opportunity to reassess claims about whether and for whom geographical research is relevant.     

Site characterization model using least‐square support vector machine and relevance vector machine based on corrected SPT data (Nc)

Statistical learning algorithms provide a viable framework for geotechnical engineering modeling. This paper describes two statistical learning algorithms applied for site characterization modeling based on standard penetration test (SPT) data. More than 2700 field SPT values (N) have been collected from 766 boreholes spread over an area of 220 sqkm area in Bangalore. To get N corrected value (N_c), N values have been corrected (N_c) for different parameters such as overburden stress, size of borehole, type of sampler, length of connecting rod, etc. In three‐dimensional site characterization model, the function N_c=N_c (X, Y, Z), where X, Y and Z are the coordinates of a point corresponding to N_c value, is to be approximated in which N_c value at any half‐space point in Bangalore can be determined. The first algorithm uses least‐square support vector machine (LSSVM), which is related to a ridge regression type of support vector machine. The second algorithm uses relevance vector machine (RVM), which combines the strengths of kernel‐based methods and Bayesian theory to establish the relationships between a set of input vectors and a desired output. The paper also presents the comparative study between the developed LSSVM and RVM model for site characterization. Copyright © 2009 John Wiley & Sons, Ltd.     

高光谱影像概率分类向量机分类方法研究

从分析基于支持向量机和相关向量机的高光谱影像分类方法的优势和不足出发,将基于概率分类向量机的方法用于高光谱影像分类试验。在贝叶斯理论框架下,概率分类向量机为基函数权值引入截断Gauss先验概率分布,使得不同类别的基函数权值具有不同符号的先验分布,并利用EM算法进行参数推断,得到足够稀疏的概率模型,弥补了相关向量机选取错误类别的样本作为相关向量的不足,从而有效地提高了模型的分类精度和稳定性。OMIS和PHI影像分类试验表明,概率分类向量机能够很好地应用在高光谱影像分类。     

应用数字航道航标信息提高航标测绘效率

通过研究"数字航道"动态监测平台中航标的各项信息与航标测绘数据的关联性,实现航标数据共享,优化现阶段航道维护性中航标测绘的工作方式和流程,从而实现利用数字航道航标信息提升航道测绘工作效率和质量,降低航道维护测量成本。     

GNSS形变监测中系统误差的时空相关性研究

通过大量实测数据分析了系统误差的时空变化规律,论证了具有时空相关性的双差观测值系统误差残差的存在,实现了观测值的滤波及求差,提高了分离微小形变量的精度。     

西施舌器官的发生和形成

本文叙述采用“直接法”、连续又系统地观察西族舌幼虫至幼贝器官的发生和形成的细微，变的全过程，有全套显微绘图和摄影并详细文字说明，特别是对雅贝与幼贝的晶杆囊、平衡囊和三对神经节的形成之描述，是国内，外的首例。     

关于Eofletcheria minima Lin et Chow的讨论

本文对 Eofletcheria minima Lin et Chow 分类位置重新修订,把该生物以动物界珊瑚动物门类中转移到植物界红藻门类里,并定名为 pseudoeofletcheria minima(Lin et Chow)Comb.nov.;同时认为生物化石分类的鉴定质量,对古生态的研究程度所做出的质量有重要的影响,同样古生态学的研究亦有助于重新去思索和确定一些生物化石的分类归属位置。     

红外卫星云图和相关向量机的有眼热带气旋客观定强模型

热带气旋TC(Tropical Cyclone)是全球影响最严重的自然灾害之一。TC强度和路径的准确预报,对于减轻其带来的灾害影响至关重要。本文基于静止红外卫星云图和相关向量机RVM(Relevance Vector Machine)构建有眼TC客观定强模型。首先,利用高斯平滑对红外卫星云图进行去噪;然后,利用基于测地活动轮廓GAC(Geodesic Active Contour)模型的偏微分方程PDE(Partial Differential Equation)法对有眼TC的眼壁进行分割,提取眼壁的亮温梯度信息,计算眼壁亮温梯度的最大值及梯度数据不同概率时的均值,从而构造与TC强度密切相关的特征因子;最后,利用RVM构建单特征因子、多特征因子与近地面最大中心风速的客观定强模型,研究不同特征维度对TC客观定强误差的影响。实验结果表明,在单特征因子的模型定强中,95%概率眼壁亮温梯度均值的定强误差最小,相比利用单特征因子所构建的定强模型,多特征因子的模型定强误差更小,即多特征因子中包含更多与TC强度相关的特征信息。在多特征因子的模型定强中,二特征因子优于三特征因子模型,说明应当合理选择特征因子维数,并非越多越好。本文所用RVM模型具有良好的高维非线性处理能力,能对TC强度进行有效估计。