高分辨率卫星影像图在震害快速预估中的应用

随着高分辨率卫星遥感技术的发展,遥感技术在地震灾害预估、评估和地震应急工作中发挥着越来越重要的作用,并成为震害评估和应急工作的重要发展方向之一。通过分析高分辨率遥感影像上建筑物的影像特征,设计了一种自动提取建筑物三维信息的模型;将提取出的建筑物三维信息,结合实验区人工调查的人口、经济数据．利用震害矩阵计算出不同类型建筑物在地震烈度场内的破坏等级和不同破坏等级建筑物的总面积,给出一定地震等级下的人员伤亡和经济损失的实际数据,建立了一套利用高分辨率卫星进行震害预估的技术流程。选取上海市宝山区为试验区．利用该技术进行了震害预估试验研究。预估结果具有较高的精度。     

Lignin in marine environment and its analysis—A review

Lignin is a group of phenolic polymers which is abundant in the woody tissues of vascular plants,and is essentially absent from all other living organisms.It has therefore been accepted as a tracer for terrestrial organic carbon(TOC) in marine environment since the 1970s.Lignin polymers are not amenable to direct chemical analysis without prior isolation.This review focused on the methods of chemical decomposition,extraction,derivatization and detection of lignin in marine environment.We described and compared several chemical decomposition methods,including nitrobenzene oxidation,alkaline cupric oxide(CuO) oxidation and thermochemolysis,and detection methods such as gas chromatography(GC),gas chromatography-mass spectrometry(GC-MS),high performance liquid chromatography(HPLC) and so on.Possible improvement of lignin analysis and the application prospects of this tracer were also discussed.     

基于Gabor变换和支持向量机的手写体字符识别算法

针对在手写字符识别中由于书写习惯和风格的不同造成字符模式不稳定的问题,将支持向量机SVM方法用于手写字符的识别.算法首先采用Gabor变换提取手写字符图像的特征参数,然后采用提取的特征训练SVM分类器.再应用SVM分类器分类和判别手写字符.实验表明这种方法具有良好的车牌识别效果,较强的鲁棒性,较大的应用价值.     

基于深度学习的滑坡灾害易发性分析

滑坡灾害成因机理复杂、影响因素众多,深度学习作为当前人工智能领域的热点,能够更好地模拟滑坡灾害的形成并准确预测潜在的斜坡。为了挖掘深度学习在滑坡易发性的应用潜能,本文构建了一维、二维和三维的滑坡数据表达形式,并提出3种基于卷积神经网络模型（Convolutional Neural Networks, CNN）的滑坡易发性分析处理框架：基于CNN分类器、基于CNN与逻辑回归的融合和基于CNN集成,最后以江西省铅山县为研究对象进行验证,结果表明：所有基于CNN的易发性模型都能够获得准确且可靠的滑坡易发性分析结果。其中,基于二维数据的CNN模型在所有单分类器中预测精度最高,为78.95%。此外,二维CNN特征提取能够显著提升逻辑回归的预测精度,其准确率提升7.9%。最后,异质集成策略能够大幅度提升基于CNN分类器的滑坡预测精度,其准确率提升4.35%~8.78%。     

面向高分遥感影像道路提取的轻量级双注意力和特征补偿残差网络模型

针对高分辨率遥感影像背景复杂,道路提取容易受阴影、建筑物和铁路等背景信息干扰的问题,提出一种带有轻量级双注意力和特征补偿机制的DAFCResUnet模型。该模型在ResUnet的基础上,通过增加轻量级的双注意力和特征补偿模块实现模型在性能和时空复杂度上的平衡。其中,双注意力模块可以增强模型的特征提取能力,特征补偿模块可以融合网络中来自深浅层的道路特征。在DeepGlobe和GF-2道路数据集上的实验结果表明,DAFCResUnet模型的IoU和F1-score可以达到0.6713、0.8033和0.7402、0.8507,模型的整体精度优于U-Net、ResUnet和VNet模型。与U-Net和ResUnet模型相比,DAFCResUnet模型仅增加了少量的计算量和参数量,但IoU和F1-score均有较大幅度的提高;与VNet模型相比,DAFCResUnet模型在计算量和参数量远低于VNet的情况下取得了更高的精度,模型在精度和时空复杂度两方面均有优势。相比其他对比模型,DAFCResUnet模型具有更强的特征提取和抗干扰能力,能更好解决道路上的干扰物、与道路特征相似地物、树荫或阴影...     

GJY灌浆自动记录仪后处理软件的研制及工程应用

GJY灌浆自动记录仪后处理软件主要配合G JY系列灌浆自动记录仪使用,用于采集、分析和管理各类灌浆施工数据。主要介绍了该软件的研制背景、功能设计、开发平台、体系结构、数据结构、运行平台、主要功能、当前在工程实践中的应用效果及改进措施。     

GPS/PWV时间序列特征提取方法的研究

针对GAMIT/GLOBK软件解算得到的4 a GPS/PWV时间序列的特征提取问题,提出基于滤波辅助的部分集成经验模态分解（PEEMD）与Hilbert谱分析相结合的特征提取方法。首先,在PEEMD方法的基础上,结合滤波辅助的PEEMD方法与Hilbert谱分析,建立GPS/PWV时间序列特征提取模型;然后,将所提出的方法应用于TNML测站4 a的GPS/PWV长时间序列和7 d的GPS/PWV短时间序列分析中,并将滤波辅助的PEEMD结果与传统的小波分解结果进行对比。结果表明,该特征提取方法能准确有效地提取出 GPS/PWV时间序列中的周年周期和日周期特征分量,滤波辅助的PEEMD分解结果与小波分解结果一致,且提取的特征分量与原始信号更加吻合。     

Characterization of Turbot(Scophthalmus maximus) Skin and the Extracted Acid-Soluble Collagen

The biochemical composition of the turbot skin was investigated. The moisture level of the skin was found to be 51.4%. Based on dry matter content, there were relatively high protein(82.1%) and lipid(13.1%) concentrations in the turbot skin. Mineral element analysis revealed that the turbot skin had high Ca content(2069.0 mg kg^-1), and the concentrations of toxic heavy metals Hg and Pb were less than 0.005 mg kg^-1, which indicates that the turbot skin is a safe resource for collagen production. The sodium dodecyl sulfate-polyacrylamide gel electrophoresis(SDS-PAGE) analysis showed that acid-soluble collagen(ASC) extracted from the turbot skin was type-I collagen. The imino acid content of the ASC was 241.6 per 1000 amino acids, which suggests a relatively high denaturation temperature. The Fourier transform infrared(FTIR) spectra of ASC reflected a highly stable structure, and the measured denaturation temperature of ASC was 29.5℃, which is higher than those from many temperate fishes. ASC was the most soluble at pH 4.0, and when the pH values were below or above 4.0, the solubility decreased rapidly. The ASC exhibited a relatively high solubility when NaCl concentration was lower than 2%. These results show that turbo skin can be employed as a source for producing collagen with high quality.     

A high precision comprehensive evaluation method for flood disaster loss based on improved genetic programming

Precise comprehensive evaluation of flood disaster loss is significant for the prevention and mitigation of flood disasters. Here, one of the difficulties involved is how to establish a model capable of describing the complex relation between the input and output data of the system of flood disaster loss. Genetic programming （GP） solves problems by using ideas from genetic algorithm and generates computer programs automatically. In this study a new method named the evaluation of the grade of flood disaster loss （EGFD） on the basis of improved genetic programming （IGP） is presented （IGP-EGFD）. The flood disaster area and the direct economic loss are taken as the evaluation indexes of flood disaster loss. Obviously that the larger the evaluation index value, the larger the corresponding value of the grade of flood disaster loss is. Consequently the IGP code is designed to make the value of the grade of flood disaster be an increasing function of the index value. The result of the application of the IGP-EGFD model to Henan Province shows that a good function expression can be obtained within a bigger searched function space; and the model is of high precision and considerable practical significance. Thus, IGP-EGFD can be widely used in automatic modeling and other evaluation systems.     

3种贝类糖胺聚糖的粗提及含量比较

以企鹅珍珠贝、菲律宾蛤仔和锯齿巴非蛤全脏器为原料,经酶解、离心去蛋白、醇沉、分离、洗涤、干燥,得糖胺聚糖(GAG)粗制品,分别测定并比较3种贝类的GAG的含量和得率。结果表明,企鹅珍珠贝的GAG质量分数为22.35%,菲律宾蛤仔为18.69%,锯齿巴非蛤为20.36%,由此得出企鹅珍珠贝的GAG的含量比其他两种贝类高,是较好的GAG来源。