Remote sensing of snow – a review of available methods

The use of satellite remote sensing for the mapping of snow-cover characteristics has a long-lasting history reaching back until the 1960s. Because snow cover plays an important role in the Earth's climate system, it is necessary to map snow-cover extent and snow mass in both high temporal and high spatial resolutions. This task can only be achieved by the use of remotely sensed data. Many different sensors have been used in the past decades with various algorithms and respective accuracies. This article provides an overview of the most common methods. The limitations, advantages and drawbacks will be illustrated while error sources and strategies on how to ease their impact will be reviewed. Beginning with a short summary of the physical and spectral properties of snow, methods to map snow extent from the reflective part of the spectrum, algorithms to estimate snow water equivalent (SWE) from passive microwave (PM) data and the combination of both spectra will be delineated. At the end, the reader should have an overarching overview of what is currently possible and the difficulties that can occur in the context of snow-cover mapping from the reflective and microwave parts of the spectrum.     

新浪微博snow ball采样算法偏差研究(英文)

随着在线社交网络的广泛应用,多种多样的采样算法应用于在线社交网络结构和特性的建模和分析。本文首先对这些常用的在线社交网络采样算法做分类对比,然后对应用相对广泛的snow ball采样算法进行深入研究。本文通过对国内最早、应用最广泛的在线社交网络新浪微博的数据进行采样分析,研究新浪微博网络结构的特点,验证得出数据量不足会导致在线社交网络的网络半径和度分布产生较大偏差。     

Pronouncibility index (Π): a distance-based and confusion-based speech quality measure for dysarthric speakers

Recently, there have been many modern speech technologies, including those of speech synthesis and recognition, developed to help people with disabilities. While most of such technologies have successfully been applied to process speech of normal speakers, they may not be effective for speakers with speech disorder, depending on their severity. This paper proposes an automated method to preliminarily assess the ability of a speaker in pronouncing a word. Based on signal features, an indicator called pronouncibility index (Π) is introduced to express speech quality with two complementary measures, called distance-based and confusion-based factors. In the distance-based factor, the 1-norm, 2-norm and 3-norm distance are investigated while boundary-based and Gaussian-based approaches are introduced for confusion-based factors. The Π is used to estimate performance of speech recognition when it is applied to recognize speech of a dysarthric speaker. Three measures are applied to evaluate the effectiveness of Π, rank-order inconsistency, correlation coefficient, and root-mean-square of difference. The evaluations had been done by comparing its predicted recognition rates with ones predicted by the standard methods called the articulatory and intelligibility tests based on the two recognition systems (HMM and ANN). For the phoneme-test set (the training set), Π outperforms the articulatory and intelligibility tests in all three evaluations. The performance of Π decreases for the device-control set (the test set), and the intelligibility test becomes the best method followed by Π and the articulatory test. In general, Π is a promising indicator for predicting recognition rate with comparison to the standard assessments.     

Accessible network of performance index tables

In each of the information processing apparatuses connected to each other via a network, there is arranged a quality of service (QOS) table to which functions and performance thereof are registered. When an information processing apparatus is additionally linked with the network, a QOS table thereof is automatically registered to a local directory of the network such that an agent converts the contents of the QOS table into service information to be supplied via a user interface to the user. Thanks to the operation, information of functions and performance of each information processing apparatus connected to the network is converted into service information for the user. Consequently, the user can much more directly receive necessary services.     

index.dat文件结构解析

在Windows操作系统中,index．dat文件是一个由IE浏览器和资源管理器创建的文件。通过对文件结构的分析研究．从二进制流数据中提取出用户个人信息．并编写程序进行验证。结果表明对文件结构理解的正确性,以及该解析过程在计算机取证中的应用。     

The determination of snow specific surface area,albedo and effective grain size using AATSR space‐borne measurements

New techniques to retrieve snow specific surface area (SSA), albedo and grain size from satellite data are described. The described methods are applied to the determination of the snow properties at the coast of Greenland. It was found that the effective grain diameters were about 0.5 mm and the specific surface area was about 150 cm²g^?1 for the region studied. The snow albedo was close to 0.93. The results were obtained using AATSR data. SSA spatial distribution was for the first time derived using satellite measurements.     

Cobol: a historic past, a vital future?

One of the strangest stories in the software world centers around the programming language Cobol. Academics have reviled it for decades; its demise has been predicted since the 1960s; industry gurus have suggested that programmers who know only Cobol are committing career suicide. You would think, based on all this bad press, that Cobol was not long for this software world. Yet the giant lumbers on. In poll after poll, it is either the most-used or the second-most-used programming language in industry. In fact, in one industry poll, each year those contacted predict that Cobol's use will diminish by the next poll, and each year the findings are that Cobol is the only language whose use has actually increased. The devil refuses to die. What's with Cobol? I give my Loyal Opposition answer to that question and then give some input on the subject from a Cobol expert who is tracking Cobol's future directions     

Analysis of remotely-sensed ecological indexes' influence on urban thermal environment dynamic using an integrated ecological index: a case study of Xi’an,China

The spatio-temporal pattern of surface ecological status affects urban thermal environment distribution significantly. Urban thermal pattern, however, is a complicated physical phenomenon involving a series of terrestrial environmental parameters. Thus, it is insufficient to employ only one ecological parameter for depicting the variation of land surface temperature (LST). This paper begins with the analysis of four ecological parameters' influence on LST using regression analysis, based on 24 Landsat images which cover Xi’an of China from 1992 to 2014. These four parameters include greenness degree (i.e. the soil adjusted vegetation index, SAVI), soil moisture degree (i.e. the normalized difference moisture index, NDMI), dryness degree (i.e. the normalized difference soil index, NDSI) and resident aggregation degree (i.e. the normalized difference build-up index, NDBI). Besides, contribution intensity index was introduced to investigate the contribution effect of four ecological parameters on LST, and a new ecological index, integrated ecological index (IEI), was founded using the principal component analysis technique to integratedly represent its spatial and mathematical correlations with LST. Results indicate that four ecological parameters all possessed pronounced performance in impacting LST pattern in all dates: SAVI and NDMI were found to be correlated negatively with LST, whereas NDBI and NDSI correlated positively with LST. Additionally, SAVI had a profound impact on LST distribution compared with the other three parameters, and there was the biggest heating contribution in the lowest SAVI category. Further finding suggests that IEI as a new ecological index can be used to integratedly estimate the spatio-temporal change of LST, manifesting a negative correlation with LST. Our study thinks that the comprehensive characterization of surface ecological status is conducive to benefit us to better understand the spatio-temporal mechanism of thermal environment and ecosystem and to help urban decision-makers to execute effective conservation policies for the ecosystem.