oalib

Publish in OALib Journal

ISSN: 2333-9721

APC: Only $99

Submit

Any time

2019 ( 83 )

2018 ( 2185 )

2017 ( 2311 )

2016 ( 2606 )

Custom range...

Search Results: 1 - 10 of 98829 matches for " 许等平 "
All listed articles are free for downloading (OA Articles)
Page 1 /98829
Display every page Item
气象灾害对天水市蜜桃生产影响的评估
Evaluation on influence of meteorological disasters to peach production in Tianshui city

,姚晓红,刘晓强,
- , 2016,
Abstract: 【目的】评估农业气象灾害对天水市蜜桃生产的影响,为有效防御农业气象灾害,最大限度减轻或减免农业损失提供参考。【方法】在提取了1982-2011年天水市蜜桃生产总产量、主要农业气象灾害影响因子的基础上,利用统计学方法对主要农业气象灾害划分等级;根据综合灾情指数评估天水市蜜桃生产的农业气象灾害类型,并与实际情况进行对比分析。【结果】影响天水市蜜桃正常生长的主要农业气象灾害为:蜜桃花芽萌动至开放的早春3月上中旬干旱、仲春4月上中旬花期高温干旱、低温冻害和蜜桃第2次速生膨大至果实成熟期7月下旬-8月上旬低温连阴雨灾害。1982-2011年间,天水市蜜桃生产综合评估有农业气象灾害19年,实况轻、中、重和特重灾害共18年,评估准确率95%,除轻灾、重灾评估准确率略低外,中灾评估准确率达83%,无灾和特重灾害评估准确率均达100%。【结论】根据本研究提取的灾害因子进行综合灾害评估的效果比较理想,对农业防灾减灾有一定的指导意义。
【Objective】To effectively defend the agricultural meteorological disasters and provide references for minimizing agricultural losses,this study evaluated the influence of agricultural meteorological disasters on peach production in Tianshuicity.【Method】After extracting the peach production data from 1982 to 2011 and the main agricultural meteorological disaster factors,statistical method was used to classify levels of main agricultural meteorological disasters.Then comprehensive disaster index was used to evaluate agricultural meteorological disaster types of peach production and the results were compared with actual situation.【Result】The main meteorological disasters affecting growth of peaches included drought at flower-bud germinating and blooming stages in early and middle March,high temperature,drought and freezing at flowering stage in early and middle April,as well as low temperature and continuous rain at the second fast growing and inflating stage to fruit maturing stage from late July to early August.There were 19 disaster years predicted from 1982 to 2011 while the actual years were 18 for mild,moderate,severe and worst disasters.Thus,the evaluation accuracy was 95%.Specifically,the evaluation accuracy on moderate disasters was 83%,and that on no-disaster and the worst disaster were 100%.【Conclusion】The disaster evaluation result was ideal and could be used in prevention and reduction of agricultural disasters
站点密度对复杂地形PRISM月降雨空间插值精度的影响
蒋育昊,刘鹏举,夏智武,,张英凯
南京林业大学学报(自然科学版) , 2017, DOI: 10.3969/j.issn.1000-2006.201603045
Abstract: 【目的】利用降雨和高程与坡向等地形因子之间关系,分析站点密度对于坡面回归方程模型(PRISM)插值精度的影响,探究该模型的适用范围。【方法】以北京西北山区为例,基于研究区数字高程模型(DEM)、山地自动气象站点数据和降雨数据计算插值结果,采用反距离加权法(IDW)、克里金法(Kriging)和样条函数法(Spline)等插值方法,以及交叉验证和实测数据验证等方法进行数据对比,分析站点密度对插值结果的影响。【结果】当站点密度从0.55×10-2个/km2降低到0.18×10-2个/km2时,各种插值方法的插值精度均随站点密度的减少而降低,PRISM模型的变化程度最大,Spline的变化程度最小; 同时当站点密度逐渐降低至0.18×10-2个/km2时,PRISM模型的插值误差超越Kriging和IDW,但仍在Spline之上。【结论】当站点密度较低时,PRISM模型优势不明显,建议使用IDW和Kriging。
【Objective】Investigate the influence of station density on the accuracy of PRISM interpolation, in order to elucidatethe model's scope of application.【Method】Based on the DEM of the northwest mountains of Beijing and rainfall data from the mountain automatic weather stations to calculate the result of interpolation. These results were then compared with the IDW, Kriging and Spline interpolation models using cross validation and test data validation.【Result】The precision of interpolation was reduced when site density was reduced from 0.55×10-2 to 0.18×10-2 sites/km2 but was reduced most when using the PRISM model and least when using the Spline model. Furthermore, when the site density was reduced to 0.18×10-2 sites/km2, the error of the PRISM model was less than that of the Spline model, but still greater than the Kriging and IDW models. 【Conclusion】The present study suggests that the IDW and Kriging models should be used when stations are sparse
基于CNN的无人机遥感影像质量评价
,任怡,闫哲,业巧林,张冬
- , 2018, DOI: 10.13360/j.issn.2096-1359.2018.05.019
Abstract: 运用无人机的遥感影像来调查林地状态是一种有效的途径,为了进一步提升遥感图像质量的评价精度,笔者提出了一种基于卷积神经网络(convolutional neural network, CNN)的无人机遥感图像质量评价方法,主要包括图像采集与预处理、数据扩增、模型训练和测试4个阶段。首先对无人机采集到的遥感图像进行主观质量打分,分别获取同一区域不同阶段图像的质量分数; 然后运用图像旋转和剪裁等方法对遥感图像进行数据扩增,将扩增后的图片和原始图片融合作为实验数据集; 其次在Caffe深度学习框架中构建基于CNN深层特征的回归模型,并训练; 最后,根据已建立好的深度回归模型和学习到的参数,预测无人机遥感图像的质量分数。结果表明,提出的方法可以取得较准确的评分效果,在保证客观打分的同时,能基本保持和人眼视觉的感受一致。
Remote sensing images processing for Unmanned Aerial Vehicle(UAV)is an effective approach in woodland survey, and convolution neural network(CNN)is one of the most representative techniques of deep learning methods. The quality evaluation accuracy of remote sensing images could be improved using these technologies. In this paper, a novel method for quality evaluation of the UAV remote sensing images is presented, which was based on the CNN. The processing phase was divided into following four stages, i.e., image acquisition and preprocessing, data augmentation, CNN model training and performance testing. In particular, firstly quality scores for the collected remote sensing images were created, which were from different stages of the same region. The quality score of these images was divided into following 5 grades, namely, very good, good, general, poor and bad, and their corresponding scores were 5, 4, 3, 2 and 1, respectively. The scoring results established by the 10 experts were further processed, and the Mean Opinion Score(MOS)was taken as the final quality scores of these images by removing the obvious discrete values. Then, remote sensing images were augmented using rotation and clipping, and each remote sensing image was rotated clockwise before the forward shear. Augmented images and the original images were fused together as the experimental data in this work. After that, the fused images were randomly divided into the training set, the validation set, and the testing set with the proportion of 10:1:1. Then the regression model based on the CNN hierarchy features and subjective quality scores was constructed in the Caffe deep learning framework. The training set and the validation set were used to train the established CNN model and calculate the training performance. Finally, according to the trained regression CNN model and parameters, the testing set was used to calculate the testing accuracy by the real quality scores and regression values. Experimental results showed that the proposed method can achieve a high-quality scoring accuracy, meanwhile can maintain the objective scoring and almost achieve the same visual perception as the human. The accuracy and universality of the
L1范数最大间隔分类器设计
寇振宇,杨绪兵,张福全,杨红鑫,
南京师范大学学报(自然科学版) , 2018, DOI: 10.3969/j.issn.1001-4616.2018.04.010
Abstract: 以L1范数为例,设计了一个L1范数的大间隔分类器L1MMC(L1-norm Maximum Margin Classifier),主要特点如下:(1)间隔由L1范数的点到平面距离解析表示;(2)该分类器与SVM一样,通过最大化L1间隔,达到同时最小化经验风险和结构风险的目的;(3)只需要通过线性规划进行求解,避免了SVM的二次规划问题;(4)分类精度达到甚至超过SVM. 最后,在人工数据和国际标准UCI数据集上,验证了该方法的有效性.
L1 norm is taken as an example to design an L1 norm L1MMC(L1-norm Maximum Margin Classifier). The main features are as follows:(1)The interval is represented by the point-to-plane distance analysis of the L1 norm;(2)This classifier,like SVM,maximizes the L1 interval to minimize the risk of both empirical and structural risks;(3)Only need to be solved through linear programming to avoid the quadratic programming problem of SVM;(4)Classification accuracy reaches or even exceeds SVM. Finally,on the artificial data and the international standard UCI data set,verify the effectiveness of the method
马氏度量下局部化广义特征值最接近支持向量机
周健航,杨绪兵,张福全,业巧林,
南京师范大学学报(自然科学版) , 2018, DOI: 10.3969/j.issn.1001-4616.2018.04.011
Abstract: 局部化广义特征值最接近支持向量机(Localized GEPSVM,LGEPSVM)是从广义特征值最接近支持向量机(GEPSVM:Proximal Support Vector Machine via Generalized Eigenvalues)衍生而来,其原理是在GEPSVM通过求解广义特征值获得两个彼此不平行的超平面的基础上,分别求解两个超平面的凸壳,修改GEPSVM的分类判据为将测试样本归为距其最近凸壳所属的那一类. 分析和实验表明,LGEPSVM较之GEPSVM具有更高的分类精度. 然而,由于LGEPSVM在训练和分类过程中都涉及凸壳计算问题,因而费时较多. 为了缓解这一问题,本文提出的基于马氏度量的最小椭圆凸壳算法MLGEPSVM(LGEPSVM based on Mahalanobis Metric),即分类时只需要判断样本与对应椭圆凸壳的距离. 较之LGEPSVM和GEPSVM,MLGEPSVM具有如下几个特点:(1)给出了马氏度量下的椭圆凸壳计算方法,(2)分类速度更快,(3)更低的存储空间,每类样本仅需存储椭圆凸壳(可通过中心和协方差表示),而不是所有的凸壳顶点. 在人工和标准数据集上的实验,验证了MLGEPSVM的上述性能.
GEPSVM(Proximal Support Vector Machine via Generalized Eigenvalues)have been played more attention in machine learning and pattern recognition. It adopts data fitting to construct classifier,and further leading to two Generalized Eigenvalue problems. One of its variants is Localized GEPSVM,shortly LGEPSVM. Instead of the closest nonparallel planes of GEPSVM,LGEPSVM classifies an unknown sample to the closest convex hulls on the projection plane. Experimental results show that LGEPSVM able to achieve comparable or even better test correctness than GEPSVM. However,due to training convex hull,LGEPSVM would cost much time in training stage. To speed training LGEPSVM,in this paper,we propose a new version LGEPSVM,termed as MLGEPSVM,based on Mahalanobis metric. Concretely,MLGEPSVM aims to find two ellipsoidal convex hulls,and then classify the samples to the class corresponding to its closest ellipsoid. Compared to LGEPSVM and GEPSVM,advantages of MLGEPSVM lie in three aspects:(1)calculation method of ellipsoid convex hull,(2)faster classification speed,and(3)less storage requirement,only ellipsoid convex hull of each class will be stored(the sample center and covariance matrix). Finally,analysis and experiments on artificial and UCI benchmark datasets will validate our foresaid superiorities
乳腺癌游离皮瓣乳房重建术后的麻醉管理
Intraoperative anesthetic management in breast cancer patients undergoing free flap breast reconstruction

楼菲菲,,黄乃思,
LOU Feifei
, XU Pingbo, HUANG Naisi, et al

- , 2016, DOI: 10.3969/j.issn.1007-3969.2016.05.005
Abstract: 背景与目的:围术期的麻醉管理对游离皮瓣乳房重建术成功与否至关重要。该研究拟探讨游离腹壁下深血管穿支皮瓣(deep inferior epigastric perforator flap,DIEP)乳房重建术中的补液、血流动力学以及体温管理。方法:收集自2011年6月—2015年12月共126例接受DIEP乳房重建术的患者资料。回顾性分析患者术后并发症、术中补液速度、以下时点的平均动脉血压(mean arterial blood pressure,MAP)和中心体温:麻醉诱导前(T0)、皮瓣切取完毕移植前(T1)、皮瓣血管吻合完毕后15 min(T2),手术结束(T3)。结果:9例患者发生皮瓣危象,其中7例解救成功,2例失败。术中平均补液速度为(5.44±1.66) (mL·kg-1)/h。T0、T1、T2和T3的MAP分别为(87.45±8.90)、(74.19±8.63)、(74.60±8.71)和(79.62±7.88) mmHg。T0、T1、T2和T3的中心体温分别为(36.69±0.14)、(36.36±0.18)、(36.27±0.14)和(36.21±0.15) ℃。结论:研究者应该针对游离皮瓣乳房重建术中的补液、血流动力学以及体温管理建立规范化标准,以优化皮瓣转归。
99mTc标记PSMA小分子抑制剂靶向前列腺癌分子影像初步临床研究
Preliminary clinical study of 99mTc-labelled small molecules against PSMA for prostate cancer imaging

胡四龙,,朱 耀,
HU Silong
, XU Xiaoping, ZHU Yao, et al

- , 2016, DOI: 10.19401/j.cnki.1007-3639.2016.07.008
Abstract: 背景与目的:前列腺特异性膜抗原(prostate-specific membrane antigen,PSMA)在前列腺癌细胞表面特异性高表达,是前列腺癌诊断和治疗的极具有吸引力的靶点。放射性核素标记的PSMA小分子抑制剂能够高效、特异性探测前列腺癌病灶并进行分期。本研究初步探讨99mTc标记PSMA小分子抑制剂(HYNIC-Glu-Urea-A,简称99mTc-PSMA)SPECT/CT显像诊断前列腺原发灶和转移灶的价值。方法:24例前列腺癌和1例前列腺增生患者静脉注射99mTc-PSMA 2 h后行全身平面扫描和腹盆部SPECT/CT断层显像,采用感兴趣区技术计算肿瘤和肌肉摄取99mTc-PSMA比值(T/N)进行半定量分析,评价全身平面显像结合断层显像检测前列腺癌原发灶和(或)转移灶的灵敏度和特异度,分析99mTc-PSMA阳性率与前列腺癌特异性抗原(prostate-specific antigen,PSA)水平和Gleason评分的关系。结果:以患者为单位,99mTc-PSMA SPECT/CT对前列腺癌原发灶或转移灶检测的灵敏度为72.7%(16/22)、特异度为100%(3/3)。99mTc-PSMA阳性患者,(中位数17.31 ng/mL,范围2.26~3 239.00 ng/mL)水平明显高于99mTc-PSMA阴性患者PSA(中位数0.49 ng/mL,范围0.07~9.28 ng/mL)(Z=-3.51,P<0.001);在初诊和PSA大于2 ng/mL的复发患者中,99mTc-PSMA阳性率明显提高,灵敏度达94.1%(16/17);99mTc-PSMA的阳性率与Gleason评分高低无关(Z=-0.69,P=0.52)。结论:99mTc-PSMA全身平面显像结合局部SPECT/CT断层显像对前列腺癌原发灶和转移灶的探测有较高应用价值,灵敏度及特异度均较高。
西藏弄如日金矿床侵入岩锆石SHRIMPU-Pb年龄与地球化学特征
刘云飞,杨志明,谢玉玲,,,李应栩,李秋耘,曲焕春,
矿床地质 , 2012,
Abstract: 弄如日金矿床位于青藏高原南部冈底斯-喜马拉雅构造区的冈底斯构造-岩浆带东段的中部,是该成矿带内首次发现并评价的浅成低温热液型金锑矿床。文章对该矿区出露的钾长花岗岩和二长花岗斑岩进行了锆石SHRIMPU-Pb测年,并对岩石的主量元素、微量元素进行了分析。测试结果显示,钾长花岗岩的加权平均年龄为(66.6±0.7)Ma,属晚白垩世;岩石富硅〔ω(SiO2)平均为76.74%〕、富碱(ALK平均为8.21%),A/CNK均大于1.0,属过铝质高钾钙碱性岩石;稀土元素球粒陨石配分模式图表现为右倾型,LREE富集、HREE亏损,ΣREE平均为66.31×10-6,并且具有明显的Eu负异常(δEu平均为0.40);微量元素原始地幔蛛网图表现出LILE富集、HFSE相对亏损的特征,暗示其可能为弧岩浆作用的产物。二长花岗斑岩的加权平均年龄为(18.8±0.3)Ma,属中新世;岩石富硅〔ω(SiO2)平均为72.69%〕、富碱(ALK平均为6.73%),A/CNK大于1.0,属过铝质高钾钙碱性岩石;稀土元素球粒陨石配分模式图表现为右倾型,LREE富集、HREE亏损,ΣREE平均为77.33×10-6,Eu异常不明显(δEu平均为1.03);在微量元素原始地幔蛛网图上,具有LILE富集、HFSE相对亏损的特征;同时,该岩石还具有较高的La/Yb比值〔(La/Yb)N平均为18.53〕,显示出一定的埃达克岩亲和性。结合区域地质背景表明:弄如日金矿床形成于陆-陆碰撞后伸展环境,与区域上近SN向正断层系统及裂谷裂陷带有关的冈底斯含矿斑岩的侵位时代相一致,是区域内中新世岩浆活动所形成的斑岩系统外围的浅成低温热液系统的产物。
我国生物技术产业发展的战略思考
雄奇,余瑛
科技进步与对策 , 2001,
Abstract: 生物技术产业被誉为永远的朝阳产业。分析了国际生物技术产业的发展现状和特征,根据我国生物技术产业发展中存在的问题,研究探讨了发展我国生物技术产业的对策思路。生物技术产业现状问题发展战略中国
wap网善cache的实现研究
小刚 夏勤
计算机科学 , 2001,
Abstract:
Page 1 /98829
Display every page Item


Home
Copyright © 2008-2017 Open Access Library. All rights reserved.