Radiometric correction of multi-temporal Landsat data for characterization of early successional forest patterns in western Oregon

Detecting and characterizing continuous changes in early forest succession using multi-temporal satellite imagery requires atmospheric correction procedures that are both operationally reliable, and that result in comparable units (e.g., surface reflectance). This paper presents a comparison of five atmospheric correction methods (2 relative, 3 absolute) used to correct a nearly continuous 20-year Landsat TM/ETM+ image data set (19-images) covering western Oregon (path/row 46/29). In theory, full absolute correction of individual images in a time-series should effectively minimize atmospheric effects resulting in a series of images that appears more similar in spectral response than the same set of uncorrected images. Contradicting this theory, evidence is presented that demonstrates how absolute correction methods such as Second Simulation of the Satellite Signal in the Solar Spectrum (6 s), Modified Dense Dark Vegetation (MDDV), and Dark Object Subtraction (DOS) actually make images in a time-series somewhat less spectrally similar to one another. Since the development of meaningful spectral reflectance trajectories is more dependant on consistent measurement of surface reflectance rather than on accurate estimation of true surface reflectance, correction using image pairs is also tested. The relative methods tested are variants of an approach referred to as “absolute-normalization”, which matches images in a time-series to an atmospherically corrected reference image using pseudo-invariant features and reduced major axis (RMA) regression. An advantage of “absolute-normalization” is that all images in the time-series are converted to units of surface reflectance while simultaneously being corrected for atmospheric effects. Of the two relative correction methods used for “absolute-normalization”, the first employed an automated ordination algorithm called multivariate alteration detection (MAD) to statistically locate pseudo-invariant pixels between each subject and reference image, while the second used analyst selected pseudo-invariant features (PIF) common to the entire image set. Overall, relative correction employed in the “absolute-normalization” context produced the most consistent temporal reflectance response, with the automated MAD algorithm performing equally as well as the handpicked PIFs. Although both relative methods performed nearly equally in terms of observed errors, several reasons emerged for preferring the MAD algorithm. The paper concludes by demonstrating how “absolute-normalization” improves (i.e., reduces scatter in) spectral reflectance trajectory models used for characterizing patterns of early forest succession.     

非汉字词语的性质和规范原则--非汉字词语问题讨论会纪要

本文记录了对非汉字词语的不同看法，指出在目前所存在的各种问题。这一现状不利于我国语文建设，建议尽快制定出非汉字词语的规范、标准，并提出了规范原则和方法。     

红土化学成分的变化特征

红土是母岩经历不同程度的红土化作用形成的，不同地区、不同母岩、不同气候条件形成的不同类型红土，其主要化学成分之间存在统计规律，研究结果表明：红土的化学成分都是以SiO2,Fe2O3和Al2O3为主,随着SiO2含量的减小，Fe2O3,Al2O3和R2O3的含量增大；而红土的pH值、烧失量随着R2O3含量的增大而增大；归一化的SiO2与倍半氧化物R2O3关系不论是以含量计算或分子量计算，都存在二项式的分布规律，红土的化学成分实质上是红土化作用结果的反映。     

一种用于识别用户解释冲突的算法

对于面向对象数据库的规范化理论 ,用户解释与模式的冲突是一个关键问题 .本文引入一种统一的面向对象模式和用户解释的 (0 - 1)矩阵表示方法 ,并在此基础上给出了用户解释与模式的冲突的多项式时间的识别算法 ,为面向对象数据库的规范化理论的研究开辟出一个新途径     

用δ函数求解三个量子力学问题

δ函数首先由狄拉克（Ｄｉｒａｃ）根据物理学的需要而引入的，为物理学反映客观世界中某些物理量的关系提供了方便．本文从广义函数着手，引入函数，进而阐明了其运算性质并提出了用函数解决三个量子力学问题的解决方法     

表达式元性理论的性质

本文给出了Ｍａｒｔｉｎ－Ｌｏｆ表达式元性理论的形式系统，并证明了它的弱标准化定理。     

Optimization of memory access for the convolutional neural network training

Batch Normalization (BN) can effectively speed up deep neural network training, while its complex data dependence leads to the serious "memory wall" bottleneck. Aiming at the "memory wall" bottleneck for the training of the convolutional neural network(CNN) with BN layers, an effective memory access optimization method is proposed through BN reconstruction and fused-layers computation. First, through detailed analysis of BN’s data dependence and memory access features during training, some key factors for large amounts of memory access are identified. Second, the “Convolution + BN + ReLU (Rectified Linear Unit)” block is fused as a computational block to reduce memory access with re-computing strategy in training. Besides, the BN layer is split into two sub-layers which are respectively fused with its adjacent layers, and this approach further reduces memory access during training and effectively improves the accelerator’s computational efficiency. Experimental results show that the amount of memory access is decreased by 33%, 22% and 31% respectively, and the actual computing efficiency of the V100 is improved by 20.5%, 18.5% and 18.1% respectively when the ResNet-50, Inception V3 and DenseNet are trained on the NVIDIA TELSA V100 GPU with the optimization method. The proposed method exploits the characteristics of memory access during training, and can be used in conjunction with other optimization methods to further reduce the amount of memory access during training.     

A Subsequence Matching Algorithm that Supports Normalization Transform in Time-Series Databases

In this paper, an algorithm is proposed for subsequence matching that supports normalization transform in time-series databases. Normalization transform enables finding sequences with similar fluctuation patterns even though they are not close to each other before the normalization transform. Simple application of existing subsequence matching algorithms to support normalization transform is not feasible since the algorithms do not have information for normalization transform of subsequences of arbitrary lengths. Application of the existing whole matching algorithm supporting normalization transform to the subsequence matching is feasible, but requires an index for every possible length of the query sequence causing serious overhead on both storage space and update time. The proposed algorithm generates indexes only for a small number of different lengths of query sequences. For subsequence matching it selects the most appropriate index among them. Better search performance can be obtained by using more indexes. In this paper, the approach is called index interpolation. It is formally proved that the proposed algorithm does not cause false dismissal. The search performance can be traded off with storage space by adjusting the number of indexes. For performance evaluation, a series of experiments is conducted using the indexes for only five different lengths out of lengths 256512 of the query sequence. The results show that the proposed algorithm outperforms the sequential scan by up to 2.4 times on the average when the selectivity of the query is 10^–2 and up to 14.6 times when it is 10^–5. Since the proposed algorithm performs better with smaller selectivities, it is suitable for practical situations, where the queries with smaller selectivities are much more frequent.     

非规范化在关系数据库设计中的应用

介绍了在关系数据库设计中的非规范化的概念和方法,即在数据库设计中适当地降低数据库的范式,以数据的冗余和不规则性来换取连接的减少以提高访问速度。并结合城市公共交通“一卡通”系统的数据库设计,分析了非规范化方法在实际问题中的应用,最后给出了非规范化处理的策略。