塔吉克斯坦经济与资源环境协调发展评价研究

如今世界各国都在寻求经济与资源环境的可协调发展,以实现经济的可持续发展。塔吉克斯坦经济发展正处于起步阶段,为了避免走“先污染,后治理”的老路子,文章运用2000—2011年数据,结合变异系数法和协调度模型,得出塔吉克斯坦经济与资源环境协调度很好,但是建立在工业发展滞后的基础上,表现为经济发展综合质量与资源环境综合质量较低,资源环境承载经济增长的负荷较低。针对这种结果,为了实现经济与资源环境达到更好的协调发展度提出建议。     

消应力退火对无取向硅钢组织和磁性能的影响

采用连续退火和井式退火两种消应力退火工艺生产35SW440牌号的爱泼斯坦方圈样,并对不同消应力退火工艺与组织、析出及磁性能之间的关系进行了比较研究。结果表明：一次退火板经消应力退火后铁损明显降低,磁感增加。与井式退火工艺相比,连续退火工艺生产的铁心在高磁密条件下磁性能较差,主要原因是带钢表面出现了明显的表面渗氮现象。表面渗氮源于其保护气氛、退火工艺设计不合理,形成大量细小弥散的AlN析出物。AlN析出物通过影响磁畴壁和磁矩运动,恶化磁性能。井式退火工艺由于有效控制了带钢表面渗氮,显著降低了电工钢片高磁密下铁损值,使成品铁心性能指标得到改善。     

基于波叠加法的非共形近场声全息波函数的构造与选择

在传统波叠加法的近场声全息算法中通常采用单层势或双层势波函数作为积分核函数,这类波函数在全息面与等效源面非共形的情况下极易导致系统矩阵的线性相关性增强和病态加重。以往研究多侧重对病态矩阵的正则化处理,以求获得更好的计算结果。从理论上分析了传统单层势或双层势波函数导致系统产生病态的原因,进而通过对格林函数的各阶求导构造出了系列具有较强指向性的射线波函数。利用该系列射线波函数替换传统波叠加法中的单层势或双层势波函数,可以使所形成的系统矩阵呈现主对角占优且近似对称的良态形式,从而可获得更精确、更稳定的计算结果。对脉动球源、振动球源以及可叠加为任意声源外声场的一般球源进行了数值仿真。研究表明:采用高阶波函数叠加法在传统波叠加法的系统矩阵已病态且不使用Tikhonov正则化就无法获得满意计算结果的情况下,能明显降低系统矩阵的条件数,使系统矩阵良态化。因而从这个意义上说,该方法也是一种可提高重建稳定性的正则化手段。同时发现,无论是传统的单层势和双层势波函数,还是射线波函数都各有其适用范围和优缺点,因此在实际使用中应根据不同的情况选择不同的波函数以提高计算稳定性和计算效率。     

Comparative Analysis of Cloud Boundary Observed by Millimeter Wave Cloud Radar and Radiosonde

The observation data obtained by a Ka-band cloud radar and radiosondes during July to August 2013,in Inner Mongolia were used to detect the cloud boundary.The results show that the Cloud Base Height(CBH) determined by the cloud radar is about 300 m lower than that from the radiosonde,and the CBHs from two equipments are close in most cases;however,the heights of cloud top are largely different.The analysis of the case with larger CBH deviation indicates that the radar detection is more sensitive than the radiosonde because of the presence of an atmosphere "dry layer" under the cloud base;The main causes of the deviation are the horizontal drift of the radiosonde and the humidity sensor error that increases with increasing height.By calculating and comparing the variation rate of cloud reflectivity,a credibility criterion is given for cloud radar detection of the height of cloud base and cloud top.     

An Improved Method for Object Extracting based on Context Information Using Multisouce Data

This paper proposed a new method which combines the airborne LiDAR data with aerial image to extract Rolling Stones on mountainous.Firstly,the aerial image is processed with multi-scale segmentation to get segmentation objects,and the LiDAR data are processed by classification,interpolation,difference for elevation information.Then compute the segmentation object based on visible-band difference vegetation index to remove the interference of vegetation information,and the nonvegetated segmentation objects are obtained.In order to effectively use the shadow,this paper put forward the normalized difference shadow index and use threshold segmentation to get shadow object.And then the automatic extraction algorithm based on the shadow and elevation information is used to preliminary obtain the rolling stones information.Finally,The height threshold filtering is set according to the actual demand to get the final rolling information.This paper took a certain area of Hong Kong aviation image and LiDAR data as experimental data to validate the proposed method.The results show that the method can well extract the Rolling Stones and effectivly distinguish the exposed bedrock,roads and similar spectral information of ground objects as Rolling Stones.The extraction accuracy of Rolling Stones is above 88% which basically satisfies the needs of rockfall in lands department.     

Extraction and Analysis of Hyperspectral Data and Characteristics from Pedicularis on Bayanbulak Grassland in Xinjiang

Through the field acquisition of three vegetation spectral datas,flowering Pedicularis,non flowering Pedicularis and common vegetation on Bayanbulak grassland,the first derivative,the two derivative and the reciprocal logarithm transformation were used to the smoothed and denoised data to analyze the difference sensitive bands of vegetation.The results showed that in visible light,non flowering Pedicularis and common vegetation showed the overall consistency,but the spectral curve of flowering Pedicularis showed a significant difference.In the red band and near infrared band at 750nm,non flowering Pedicularis reflectance increased significantly,and the three kinds of spectral reflectance showed significant differences.The reciprocal logarithmic transformation in the visible 580~680 nm band could be used to distinguish the Pedicularis as sensitive area.The spectral reflectance difference between the three at 655 nm was the most obvious.That solved the non flowering Pedicularis and common vegetation confusable problems.The improved normalized difference vegetation index by calculation,to further validate and showed the reciprocal logarithmic transformed values NDVI RLR could be distinguished the difference of flowering Pedicularis,non flowering Pedicularis and common vegetation.The extraction and analysis of hyperspectral data and characteristics from Pedicularis provided a theoretical basis for remote sensing monitoring of Pedicularis,and Remote sensing technology has great significance in Pedicularis resource survey and monitoring application.     

Progresson Sustainable City Assessment Index System for SDGs

Urban sustainability has become the world’s most important urban issue.The evaluation index system is an effective tool to objectively diagnosethe current status and problems of sustainable development.The existing urban sustainability evaluation index systems are mostly based on traditional statistical data and they have different emphases.Due to the suitability of index and availability of data,etc,These index systems are hardly used for comparative evaluation amongdifferent cities.With the interpretation of the sustainable city connotation by the Sustainable Development Goals11,and the use of multi-source data such as remote sensing and network big data,it is possible to achieve higher resolution for urban sustainability assessment under a unified standard.Based on this,this work analyzes the evolution of the concept of urban sustainable development and identifies the key areas of the connotation of sustainable city construction.This work also summarizes the research progress of sustainability evaluation indicators and analyzes typical index system.Based on SDG11,this study establish an open city sustainability index system,with combining traditional statistical data and multi-source data,such as remote sensing data and network big data.The framework of the evaluation index system aims to provide reference for the sustainability evaluation of cities in China under the framework of the United Nations.     

改进Smote算法在不平衡数据集上的分类研究

在不平衡数据集中,过抽样算法如Smote(Synthetic Minority Oversampling)算法、R-Smote算法与SD-ISmote算法可能会模糊多数类与少数类的边界以及使用噪声数据合成新样本。本文提出的ImprovedSmote算法使用少数数据集的簇心与其对应类别的少数集数据,在簇心与不大于样本属性数的对应类别少数集数据形成的图形内随机插值来生成新数据。ImprovedSmote算法结合C4.5决策树与神经网络算法在实验数据集上的结果比Smote, R-Smote与SD-ISmote算法更好,可以有效地提高分类器分类性能。     

基于Levenshtein和TFRSF的文本相似度计算方法

在社交网络中查找和收集个人信息可以建立一个包含目标履历、生活、爱好以及朋友等属性的信息体系,但是不同社交网络中存在大量同名用户。为了解决同名歧义问题,采用计算用户信息相似度,可以判断2个用户是否属于同一个人。由于文档中描述信息位置颠倒会导致计算机误判,为此,本文通过对莱文斯坦（Levenshtein）和词频相关字符串频率（TFRSF）方法融合计算词频和编辑距离,判断属性值是否相同。实验结果表明,本文提出的计算文本相似度方法在多种评价指标上准确性都有所提高,准确率（Precision）、召回率（Recall）、F1值（F1 Measure）均大于87%。     

基于堆叠降噪稀疏自动编码器的软件缺陷预测

特征提取是软件缺陷预测中的关键步骤,特征提取的质量决定了缺陷预测模型的性能,但传统的特征提取方法难以提取出软件缺陷数据的深层本质特征。深度学习理论中的自动编码器能够从原始数据中自动学习特征,并获得其特征表示,同时为了增强自动编码器的鲁棒性,本文提出一种基于堆叠降噪稀疏自动编码器的特征提取方法,通过设置不同的隐藏层数、稀疏性约束和加噪方式,可以直接高效地从软件缺陷数据中提取出分类预测所需的各层次特征表示。利用Eclipse缺陷数据集的实验结果表明,该方法较传统特征提取方法具有更好的性能。