基于神经网络的时间域直升机电磁数据电导率深度成像

采用G-S变换以及高斯数值积分法,形成了时间域直升机的航空电磁响应正演样本集,分析了飞机测量过程中吊舱高度变化对电磁响应的影响,并将吊舱高度的变化等效成电导率为零的假层厚度的变化,以去除高度计等的影响.以假层半空间模型为基础,研究了基于人工神经网络的电导率深度成像算法,通过分析两个三层模型的电导率深度成像结果得出,神经网络方法计算时间域航空电磁探测的视电导率精度较高,特别是对高阻层的视电导率计算.     

Fatty acid profiles of benthic environment associated with artificial reefs in subtropical Hong Kong

Artificial reefs can enhance habitat heterogeneity, especially in seabed degraded by bottom-dredging and trawling. However, the trophodynamics of such reef systems are not well understood. This study provided baseline data on trophic relationships in the benthic environment associated with artificial reefs in late spring and mid summer of subtropical Hong Kong, using fatty acid profiles as an indicator. Data from sediments collected at the reef base, materials from sediment traps deployed on top and bottom of the reefs, total particulate matter from the water column and oyster tissues from reef surface were subjected to principal component analysis. Results showed variations of fatty acid profiles in the total particulate matter, upper sediment trap and oyster tissue samples collected in the two samplings, indicating seasonal, trophodynamic changes within the reef system. The wastes produced by fish aggregating at the reefs can also contribute a source of biodeposits to the nearby benthic environment.     

某异型钢管混凝土拱桥地震反应分析

本文以某异型钢管混凝土拱桥为研究对象,通过ANSYS建立了结构的空间有限元模型,计算和分析了该桥的动力特性。同时,通过MATLAB程序生成拟合规范反应谱的人工地震波,并运用时程分析法计算了该桥在一维和多维输入下的地震反应,分析了该桥的地震反应规律,为钢管混凝土拱桥的抗震性能分析提供了一定的依据。     

Constraints to effective adoption of innovative livestock production technologies in the Rift Valley (Kenya)

We surveyed small-scale farmers in the Kenyan Rift Valley province (Narok and Nakuru districts) to describe constraints to, and changes in, livestock production and to assess the extent to which farmers have adopted new technologies promoted by extension services. In the arid areas of southern Narok, farmers' main constraints were drought and disease. Farmers in Nakuru district, situated in the fertile highlands of the Rift Valley, were also affected by disease but also lacked markets and capital. Although 83% of the farmers had regular contact with extension services that provided advice on new technologies and livestock production innovations, only about half of the respondents implemented the proposed changes. Many of those who did change (38%) improved pasture/nutrition/manure management and relatively few (16%) improved their animal breeding practices. Results of a multinomial logit model revealed that, apart from the significant differences between the two districts, the nature of the advice and the expected outcomes had the strongest influence on the probability of successfully implementing changes to livestock production. The results further suggest that adoption of new technologies is limited by lack of knowledge, inadequate support and a failure to target local needs and conditions and empower livestock keepers.     

Positional uncertainty in manually digitized map data

Digital map coordinates represent the locations of real world entities. As such, differences can exist between the ‘tru’ and digital database coordinates of those entities. This paper reports on a statistical characterization of positional error in manually-digitized and map-registered point data, the relative contribution of point type and operator to digitization error, and the effects of map media type on the positional uncertainty associated with registration.

Manually-digitized point data were collected by four operators from mylar and paper maps. Point locations for a number of different feature types were sampled from United States Geological Survey (USGS) 1:24 000 scale maps. Linear models were used to estimate the variance components due to among-operator, map media, point type and registration effects. The statistical distribution of signed distance deviations for manually-digitized data was leptokurtic relative to a random normal variate. Unsigned deviations averaged 0-054 mm. Squared distance deviations were not different from a Chi-square random variate. Variance components indicate that among-operator differences in positional uncertainty were large and statistically significant, while differences among point type were small and non-significant. Signed distance deviations associated with a first-order afhne followed a normal distribution. Unsigned distance deviations associated with a first-order affinc transformation averaged 0068mm, and squared distance deviations were distributed as a Chi-square. Differences in transformation accuracy were not related to type of map media.     

Representing geographical objects with scale‐induced indeterminate boundaries: A neural network‐based data model

The degree of uncertainty of many geographical objects has long been known to be in intimate relation with the scale of its observation and representation. Yet, the explicit consideration of scaling operations when modeling uncertainty is rarely found. In this study, a neural network‐based data model was investigated for representing geographical objects with scale‐induced indeterminate boundaries. Two types of neural units, combined with two types of activation function, comprise the processing core of the model, where the activation function can model either hard or soft transition zones. The construction of complex fuzzy regions, as well as lines and points, is discussed and illustrated with examples. It is shown how the level of detail that is apparent in the boundary at a given scale can be controlled through the degree of smoothness of each activation function. Several issues about the practical implementation of the model are discussed and indications on how to perform complex overlay operations of fuzzy maps provided. The model was illustrated through an example of representing multi‐resolution, sub‐pixel maps that are typically derived from remote sensing techniques.     

笼养条件下秃鹫繁殖期的行为日节律及时间分配的观察研究

2012年3～5月,采用直接瞬时扫描法和间接监控器摄像相结合的方式,对北京市野生动物救护中心顺义饲养繁育基地的一对秃鹫的繁殖行为的时间分配和活动规律进行了研究,结果显示:秃鹫在警戒、理羽、吃食、交配、孵化等行为存在着明显的节律性,警戒、理羽行为在行为比例中较高,警戒行为占绝对优势。取食行为多发生在上午的中间阶段,孵化行为不间断、并且轮流孵化幼鸟。孵化期内雌、雄个体的行为差异不大,秃鹫发情期各种行为所占的比例存在着一定的性别差异。     

新丰江库区上地壳三维细结构层析成像

在新丰江库区布设一个范围约50 km×40 km、由50个地震临时台站组成的观测台阵,接收来自不同方位的人工震源产生的莫霍界面反射波;台阵中的20个台站和5个区域固定台还对2009年3月至2010年5月发生在库区的地方震进行了观测.本文联合利用人工地震莫霍面反射波走时和天然地震直达波走时,采用连续模型反演技术重建了库区上地壳P波、S波慢度扰动和V_p/V_s扰动分布图像.研究结果表明:新丰江库区东、西部地区上地壳结构存在明显的差异.库区东部地区构造复杂,多条断裂在该区呈交叉状分布.北西向的石角-新港-白田断裂带在库区段内具有复杂的岩性和构造特征,该断裂带在新港至双塘一线可能延伸至地下8 km左右;近北东向的断裂带切割地壳较深.峡谷区及大坝以东附近地区存在上、下贯通的波速比高值区,尤其是大坝以西的深水峡谷区,存在一条顺河走向的陡倾角断层裂隙带,为库水渗透提供了良好通道.库区西部地区为相对稳定构造区,完整坚硬的花岗岩体透水性能较差,受库水渗透影响很小.新丰江水库诱发地震的形成与深部构造环境密切相关.峡谷区及大坝以东附近地区上地壳介质性质呈现明显的横向不均匀性,微震分布在介质物性结构的特定部位,"软"、"硬"交错的介质环境是倾滑正断层型微小震产生的可能原因.     

Artificial neural networks and nonlinear regression techniques to assess the influence of slake durability cycles on the prediction of uniaxial compressive strength and modulus of elasticity for carbonate rocks

Understanding rock material characterizations and solving relevant problems are quite difficult tasks because of their complex behavior, which sometimes cannot be identified without intelligent, numerical, and analytical approaches. Because of that, some prediction techniques, like artificial neural networks (ANN) and nonlinear regression techniques, can be utilized to solve those problems. The purpose of this study is to examine the effects of the cycling integer of slake durability index test on intact rock behavior and estimate some rock properties, such as uniaxial compressive strength (UCS) and modulus of elasticity (E) from known rock index parameters using ANN and various regression techniques. Further, new performance index (PI) and degree of consistency (Cd) are introduced to examine the accuracy of generated models. For these purposes, intact rock dataset is established by performing rock tests including uniaxial compressive strength, modulus of elasticity, Schmidt hammer, effective porosity, dry unit weight, p‐wave velocity, and slake durability index tests on selected carbonate rocks. Afterward, the models are developed using ANN and nonlinear regression techniques. The concluding remark given is that four‐cycle slake durability index (I_d4) provides more accurate results to evaluate material characterization of carbonate rocks, and it is one of the reliable input variables to estimate UCS and E of carbonate rocks; introduced performance indices, both PI and Cd, may be accepted as good indicators to assess the accuracy of the complex models, and further, the ANN models have more prediction capability than the regression techniques to estimate relevant rock properties. Copyright © 2011 John Wiley & Sons, Ltd.     

Evaluation of classifiers for processing Hyperion (EO-1) data of tropical vegetation

There is an urgent necessity to monitor changes in the natural surface features of earth. Compared to broadband multispectral data, hyperspectral data provides a better option with high spectral resolution. Classification of vegetation with the use of hyperspectral remote sensing generates a classical problem of high dimensional inputs. Complexity gets compounded as we move from airborne hyperspectral to Spaceborne technology. It is unclear how different classification algorithms will perform on a complex scene of tropical forests collected by spaceborne hyperspectral sensor. The present study was carried out to evaluate the performance of three different classifiers (Artificial Neural Network, Spectral Angle Mapper, Support Vector Machine) over highly diverse tropical forest vegetation utilizing hyperspectral (EO-1) data. Appropriate band selection was done by Stepwise Discriminant Analysis. The Stepwise Discriminant Analysis resulted in identifying 22 best bands to discriminate the eight identified tropical vegetation classes. Maximum numbers of bands came from SWIR region. ANN classifier gave highest OAA values of 81% with the help of 22 selected bands from SDA. The image classified with the help SVM showed OAA of 71%, whereas the SAM showed the lowest OAA of 66%. All the three classifiers were also tested to check their efficiency in classifying spectra coming from 165 processed bands. SVM showed highest OAA of 80%. Classified subset images coming from ANN (from 22 bands) and SVM (from 165 bands) are quite similar in showing the distribution of eight vegetation classes. Both the images appeared close to the actual distribution of vegetation seen in the study area. OAA levels obtained in this study by ANN and SVM classifiers identify the suitability of these classifiers for tropical vegetation discrimination.