The classification and prediction of macroinvertebrate communities in British rivers

This article describes the progress of the River Communities Project which commenced in 1977. This project aimed to develop a sensitive and practical system for river site classification using macroinvertebrates as an objective means of appraising the status of British rivers. The relationship between physical and chemical features of sites and their biological communities were examined. Sampling was undertaken on 41 British rivers. Ordination techniques were used to analyze data and the sites were classified into 16 groups using multiple discrimination analysis. The potential for using the environmental data to predict to which group a site belonged and the fauna likely to be present was investigated.

On the optimal usage of labelled examples in semi-supervised multi-class classification problems

In recent years, the performance of semi-supervised learning has been theoretically investigated. However, most of this theoretical development has focussed on binary classification problems. In this paper, we take it a step further by extending the work of Castelli and Cover [1] [2] to the multi-class paradigm. Particularly, we consider the key problem in semi-supervised learning of classifying an unseen instance x into one of K different classes, using a training dataset sampled from a mixture density distribution and composed of l labelled records and u unlabelled examples. Even under the assumption of identifiability of the mixture and having infinite unlabelled examples, labelled records are needed to determine the K decision regions. Therefore, in this paper, we first investigate the minimum number of labelled examples needed to accomplish that task. Then, we propose an optimal multi-class learning algorithm which is a generalisation of the optimal procedure proposed in the literature for binary problems. Finally, we make use of this generalisation to study the probability of error when the binary class constraint is relaxed.

ICF靶场中光束口径与列阵间隔的研究

从靶场反射镜架模块的机械结构设计布局所需几何空间的角度出发，根据大口径、列阵器件的特殊要求，给出符合“神光Ⅲ”装置总体技术要求的ICF靶场光束口径与列阵间隔之间的关系，得出靶场△纵、△横应满足的公式．

ICF中可调法布里-珀罗滤波器间距稳定度研究

在神光Ⅱ第9路ICF高功率激光装置中，采用可调法布里-珀罗（F-P）滤波器对幅度调制效应进行补偿，根据补偿装置的技术要求，提出-种应用nm量级精度的电容式位移传感器对可调F-P滤波器间距稳定度进行监控的系统，详细论述了监控系统的结构与工作原理。给出了电容式位移传感器的驱动电路及数据处理与控制软件的设计方案，并对电容式位移传感器的精度进行了标定。实验结果表明，该位移监控系统能够使可调F—P滤波器的间距稳定度保持在15nm／h以内，使幅度调制效应的调制深度优于4％。

一种ICF用新型可阵列反射镜架结构

运用并联机构原理设计了一种新型惯性约束聚变（Inetial Confinement Fusion, ICF）用可阵列反射镜架结构,并用坐标变换方法分析了机构的调整正交性与旋转轴正交性之间的关系.装置的实际测试结果表明调整正交性与分析结果一致,并且反射镜架的稳定性以及调节准确度均能符合ICF装置的使用要求.

Contributions on distance-based algorithms, multi-classifier construction and pairwise classification

179 p.

Contributions to learning Bayesian network models from weakly supervised data: Application to Assisted Reproductive Technologies and Software Defect Classification

162 p.

Synopsis de la classification des larves et des nymphes de diptères chironomidae des ecosystèmes dulçaquicoles de l'Afrique de l'Ouest: clés de détermination des sous-familles, des tribus et des genres

Synopsis of this numerically very important Diptera category, which is dominant and consequently of relevance in most aquatic environments.