A comparison of three approaches for predicting C4 species cover of northern mixed grass prairie

The C4 composition of Canadian mixed-grass communities is more sensitive to environmental change than other grasslands. Reliable methods of detecting such changes are necessary if these landscapes are to be properly managed. One approach is to use satellite remote sensing systems. Various studies have shown that the asynchronous seasonality of C3 and C4 species allows the relative abundance of each photosynthetic type to be estimated using temporal trajectory indices (TTIs) of sensor-derived normalized difference vegetation index (NDVI). In this study, we compared three approaches for predicting C4 species cover at Grasslands National Park (GNP) (Saskatchewan, Canada). TTIs related to Approach I were calculated from plots of NDVI vs. day-of-year (DOY). TTIs related to Approach II were calculated from plots of normalized cumulative NDVI vs. growing degree day (GDD). TTIs related to Approach III were calculated as ratios of early-season NDVI to late-season NDVI. Our analyses were conducted at two separate ecological scales. A within-community analysis used field-sampled data from upland grassland to compare techniques at sampling resolutions of 0.5, 2.5, 10, and 50 m. An across-community analysis compared techniques using a vegetation survey of the GNP region and TTIs calculated from Advanced Very High Resolution Radiometer (AVHRR) data (1 km). At both scales, TTIs related to the timing of specific phenological events were the best predictors of C4 species cover. While all techniques performed well in the within-community study, Approach III performed best. Here, the predictive ability of each approach was weak at a resolution of 0.5 m but stronger at 2.5, 10, and 50 m resolutions. We also found that the optimal sampling dates for Approach III fell within a certain GDD range. This is encouraging for the a priori selection of sample dates, which would make the need for full seasonal time series redundant. In the across-community analysis, the AVHRR-derived Approach II TTIs were better able to discriminate among grasslands of different C4 composition than any other technique (overall accuracy=74%). However, for some C4 cover classes, the predictive accuracy of this approach was low. While these results are encouraging for the use of spectral data in monitoring the C4 cover of northern prairie, various research issues remain. At the within-community level, these include (a) further attempts to define objective criteria for the a priori identification of sampling dates for Approach III, and (b) and the extension of such studies to other growing seasons and community types/grassland regions. At the across-community level, these include the expansion of such techniques to a larger geographical region that contains a wider range in C4 cover values and land use types (e.g. ungrazed vs. grazed grasslands).     

Pesticide monitoring programme of the Ministry of Health of Brazil

The structure of the recently introduced Brazilian government programme for monitoring pesticide residues in six major agricultural products is described. Residues found from the analysis of samples of tomatoes and strawberries are discussed in detail. The much greater frequency of detection of pesticide residues, many of which are not approved for use in Brazil, in produce being sold on the domestic market, as opposed to that produced for export, is of major concern. It is perceived that this new monitoring programme will become permanent and be used to underpin enforcement actions that will need to be taken to reduce the numbers of incidents of illegal residues occurring, particularly in fresh fruits and vegetables.     

Characteristics of origin-destination pair traffic in Funet

In this paper we analyze measurements gathered from a 2.5~Gbps link in the Finnish university network (Funet) in 2004. The traffic is broken down into origin-destination (OD) pair components based on source and destination IP address. We study the traffic characteristics of these components, and identify four typical representative OD pairs. For these pairs we investigate the validity of a moving IID Gaussian model. We find that the statistical properties of these OD pairs differ significantly from each other, with only some of them close to Gaussian. The OD pairs are also found to have some cross-correlation between each other, contradicting an often made assumption about OD pair independence. Furthermore, the existence of a mean-variance relation between the OD pairs is studied. We find that there is a relation between mean and variance, but for some periods of time it is rather weak.     

赴日无线电监测技术考察报告

首先介绍了日本总务省关东综合通信局电波监理部的情况，然后对日本安立公司生产的RR510A型无线电监测接收机和技术参数以及MS8609A型数字移动无线发射机测试仪的功能进行了分析和介绍。     

基于回归方法的移动通信话务量预测

针对移动通信话务量与市场用户和相应资费政策相关的特点，采用回归预测方法，建立了基于市场用户数及每用户收入的话务量预测模型，并对模型进行了经济学意义上的检验。根据此模型，对话务量进行了初步的预测分析。     

Modeling of Temperature–Frequency Correlation Using Combined Principal Component Analysis and Support Vector Regression Technique

A good understanding of environmental effects on structural modal properties is essential for reliable performance of vibration-based damage diagnosis methods. In this paper, a method of combining principal component analysis (PCA) and support vector regression (SVR) technique is proposed for modeling temperature-caused variability of modal frequencies for structures instrumented with long-term monitoring systems. PCA is first applied to extract principal components from the measured temperatures for dimensionality reduction. The predominant feature vectors in conjunction with the measured modal frequencies are then fed into a support vector algorithm to formulate regression models that may take into account thermal inertia effect. The research is focused on proper selection of the hyperparameters to obtain SVR models with good generalization performance. A grid search method with cross validation and a heuristic method are utilized for determining the optimal values of SVR hyperparameters. The proposed method is compared with the method directly using measurement data to train SVR models and the multivariate linear regression (MLR) method through the use of long-term measurement data from a cable-stayed bridge. It is shown that PCA-compressed features make the training and validation of SVR models more efficient in both model accuracy and computational costs, and the formulated SVR model performs much better than the MLR model in generalization performance. When continuously measured data is available, the SVR model formulated taking into account thermal inertia effect can achieve more accurate prediction than that without considering thermal inertia effect.     

Use of process signals for tool wear progression sensing in drilling small deep holes

Detailed knowledge about the relation between wear progression of a cutting tool and the cutting forces generated is of paramount importance for the development of a tool condition monitoring strategy. This paper discusses the changes in the different process signals with progressing tool wear of small diameter twist drills (D=1.5 mm), when drilling boreholes having a depth of 10 times the diameter in plain carbon steel using MQL. The effect of different wear patterns on the process signals is presented. Furthermore, several features, which evolve over the life of the drills, are identified and extracted from the process signals. Knowledge about the evolution of these features can support the user to determine the final tool life stage, so that the drill can be replaced before the final fracture occurs.     

基于Java RMI技术的大型机群监控系统的设计与实现

机群监控系统可有效的提高大型机群的可管理性和可用性。本文提出了一种基于JAVA RMI技术的机群监控系统模型，并给出其实现方法。该系统具有开发快速、可跨平台、易于扩展等特性。     

浆砌石坝爆破拆除及监测技术

在陕西宝鸡峡引水枢纽浆砌石大坝改建过程中 ,Ⅱ坝段的全部以及Ⅵ坝段的部分须用爆破方法拆除。为了避免爆破震动对相邻的和保留的浆砌石坝体的不利影响 ,利用伸缩缝和预先开挖的沟槽隔震 ,采用了浅孔爆破分层拆除的方法 ,实施微差爆破 ,严格控制最大一段药量。爆破震动监测和声波测试的结果表明 ,保留的浆砌石坝体没有受到损伤     

动力能源调度监控技术在冶金企业的应用

总结了动力能源调度监控技术在冶金企业的应用情况，介绍了这项技术的发展历程及企业在应用时需要注意的几个重要事项，分析了目前存在的问题，提出了相应对策。