基于PGNAA技术在线分析系统的应用

近年来,随着核探测与分析技术的日趋成熟,使复杂γ谱的获取、解析达到了在线测量的要求,从而使在线PGNAA(中子活化瞬发γ射线分析)技术获得了飞速的发展。它可对一些工业生产过程中的全物料进行在线测量,其分析精度、可靠性等皆能满足在线元素含量分析的需要,因而显示出巨大的发展潜力和广阔的市场前景。这里介绍了基于PGNAA技术的在线分析系统的基本原理、组成和发展,并概述了它在水泥、煤炭等行业的应用情况。     

Outlier detection algorithms and their performance in GOCE gravity field processing

The satellite missions CHAMP, GRACE, and GOCE mark the beginning of a new era in gravity field determination and modeling. They provide unique models of the global stationary gravity field and its variation in time. Due to inevitable measurement errors, sophisticated pre-processing steps have to be applied before further use of the satellite measurements. In the framework of the GOCE mission, this includes outlier detection, absolute calibration and validation of the SGG (satellite gravity gradiometry) measurements, and removal of temporal effects. In general, outliers are defined as observations that appear to be inconsistent with the remainder of the data set. One goal is to evaluate the effect of additive, innovative and bulk outliers on the estimates of the spherical harmonic coefficients. It can be shown that even a small number of undetected outliers (<0.2 of all data points) can have an adverse effect on the coefficient estimates. Consequently, concepts for the identification and removal of outliers have to be developed. Novel outlier detection algorithms are derived and statistical methods are presented that may be used for this purpose. The methods aim at high outlier identification rates as well as small failure rates. A combined algorithm, based on wavelets and a statistical method, shows best performance with an identification rate of about 99%. To further reduce the influence of undetected outliers, an outlier detection algorithm is implemented inside the gravity field solver (the Quick-Look Gravity Field Analysis tool was used). This results in spherical harmonic coefficient estimates that are of similar quality to those obtained without outliers in the input data.     

Physical properties of ultrahigh-pressure metamorphic rocks from the Sulu terrain, eastern central China: implications for the seismic structure at the Donghai (CCSD) drilling site

About 30 samples representing major lithologies of Sulu ultrahigh-pressure (UHP) metamorphic rocks were collected from surface exposures and exploration wells, and compressional (Vp) and shear wave (Vs) velocities and their directional dependence (anisotropy) were determined over a range of constant confining pressures up to 600 MPa and temperatures ranging from 20 to 600 °C. Samples range in composition from acidic to ultramafic. P- and S-wave velocities measured at 600 MPa vary from 5.08 to 8.64 km/s and 2.34 to 4.93 km/s, respectively. Densities are in the range from 2.60 to 3.68 g/cm³. To make a direct tie between seismic measurements (refraction and reflection) and subsurface lithologies, the experimental velocity data (corresponding to shallow depths) were used to calculate velocity profiles for the different lithologies and profiles of reflection coefficients at possible lithologic interfaces across the projected 5000-m Chinese Continental Scientific Drilling Program (CCSD) crustal segment. Comparison of calculated in situ velocities with respective intrinsic velocities suggests that the in situ velocities at shallow depths are lowered by an increased abundance of open microcracks. The strongly reflective zone beneath the Donghai drill site can be explained by the impedance contrasts between the different lithologies. Contacts between eclogite/peridotite and felsic rocks (gt-gneiss, granitic gneiss), in particular, may give rise to strong seismic reflections. In addition, shear-induced (lattice preferred orientation (LPO)-related) seismic anisotropy can increase reflectivity. For the explanation of the high velocity bodies (>6.4 km/s) around 1000 m and below 3200-m depth, large proportions of eclogite/peridotite (about 40 and 30 vol.%, respectively) are needed.     

ARTIFICIAL NEURAL NETWORK CORRECTION OF ROUGH ERRORS OF OBSERVATIONS*

In the context of tower measured radiation datasets.following the correction principle meeting a diagnostic equation in data quality control and in terms of a technique for model construction on data and ANN (artificial neural network) retrieval for BP correction of radiation measurements with rough errors available,a BP model is presented.Evidence suggests that the developed model works well and is superior to a convenient multivariate linear regression model,indicating its wide applications.     

战略环境评价若干问题研究

分析了传统环境影响评价制度的不足，回顾了战略环境评价的研究与实践进展，阐述了战略环境评价与环境可持续发展的关系，并对以实现环境可持续发展为目标的战略环境评价体系所存在的问题进行了分析。     

Water use, growth and yield of green gram under rainfed upland crop sequences in Gangetic Plains of Indian sub-tropics

A field experiment was conducted to study the effect of different crop sequences on water use, growth and yield of green gram (Vigna radiata (L) Wilezek) during 1992-93 and 1993-94 under rainfed upland condition in Indo-Gangetic plains of West Bengal. Green gram sown in the month of March as pre-rainy (summer) season crop, as and when the winter crops vacated the land, produced highest dry matter of 372 gm-2 which was significantly highest in black gram-yellow sarson sequence.The results of the field experimentation revealed that green gram gave highest grain yield to the extent of 10.80 q/ha when sown after black gram (rainy season) followed by yellow sarson (winter season) while the crop produced 10.63 q/ha under sesame-yellow sarson sequence. Highest water use of 267mm was achieved in green gram under black gram-yellow sarson sequence and the crop gave water use efficiency of 4.07 kg ha-1mm-1 under black gram-yellow sarson sequences.     

Use of Noise to Augment Training Data: A Neural Network Method of Mineral–Potential Mapping in Regions of Limited Known Deposit Examples

One of the main factors that affects the performance of MLP neural networks trained using the backpropagation algorithm in mineral-potential mapping isthe paucity of deposit relative to barren training patterns. To overcome this problem, random noise is added to the original training patterns in order to create additional synthetic deposit training data. Experiments on the effect of the number of deposits available for training in the Kalgoorlie Terrane orogenic gold province show that both the classification performance of a trained network and the quality of the resultant prospectivity map increasesignificantly with increased numbers of deposit patterns. Experiments are conducted to determine the optimum amount of noise using both uniform and normally distributed random noise. Through the addition of noise to the original deposit training data, the number of deposit training patterns is increased from approximately 50 to 1000. The percentage of correct classifications significantly improves for the independent test set as well as for deposit patterns in the test set. For example, using ±40% uniform random noise, the test-set classification performance increases from 67.9% and 68.0% to 72.8% and 77.1% (for test-set overall and test-set deposit patterns, respectively). Indices for the quality of the resultant prospectivity map, (i.e. D/A, D × (D/A), where D is the percentage of deposits and A is the percentage of the total area for the highest prospectivity map-class, and area under an ROC curve) also increase from 8.2, 105, 0.79 to 17.9, 226, 0.87, respectively. Increasing the size of the training-stop data set results in a further increase in classification performance to 73.5%, 77.4%, 14.7, 296, 0.87 for test-set overall and test-set deposit patterns, D/A, D × (D/A), and area under the ROC curve, respectively.     

智能交通系统中的公交车辆指挥调度体系结构

该文阐述公交智能指挥调度系统总体框架，结合智能交通系统ITS(Intelligent Transport Systems)对公交智能化调度的逻辑结构和物理结构要求，分析公交车辆智能化调度系统结构体系及其模型化，探讨智能调度策略和调度机理。根据该系统总体设计框架构思，了解系统各功能间的相互关系，优化公交车辆运营管理模式，以改善现有公交系统的管理水平以及运营效率，为公交指挥调度系统的完善、提高提供可靠技术基础。     

用废聚苯乙烯泡沫制备胶粘剂

本文研究了回收废旧聚苯乙烯(PS)泡沫塑料制备PS胶粘剂的方法。以废旧聚苯乙烯泡沫塑料为主要原料,选择低毒性、相溶性好的有机溶剂,使其溶解,再与聚乙烯醇(PVA)水溶液共混,制得水包油乳液。加入不同改性材料,制得改性胶粘剂。