Large-aperture automatic focimeter for the measurement of optical power and other optical characteristics of ophthalmic lenses

We propose an optical apparatus enabling the measurement of spherical power, cylindrical power, and optical center coordinates of ophthalmic lenses. The main advantage of this new focimeter is to provide a full bidimensional mapping of the characteristics of ophthalmic glasses. This is made possible thanks to the use of a large-area and high-resolution position-sensitive detector. We describe the measurement principle and present some typical mappings, particularly for progressive lenses. We then discuss the advantages in terms of speed and versatility of such a focimeter for the measurement of complex lens mappings. (C) 2002 Optical Society of America.

On the classification of lakes and lake-like bodies of the Ukraine [Translation from: Gidrobiologicheskie Zhurnal, Kiev 19(2) 100-101, 1983]

In the Ukraine there are several thousand large, medium and small lakes and lake-like reservoirs, distinguished by origin, salinity, regional position, productivity and by construction a significant number of large and small water bodies, ponds and industrial reservoirs of variable designation. The problem of national systems necessitates the creation of specific schemes and classifications. Classifying into specific types of reservoir by means of suitable specifications is required for planning national measures with the objective of the rational utilisation of natural resources. It is now necessary to consider the present-day characteristics of Ukranian lakes. In the case of the Ukraine it is possible to use two approaches - genetical and ecological. This paper uses the genetical system to classify the lake-like water bodies of the Ukraine.

Automatic identification and enumeration of algae

A good understanding of the population dynamics of algal communities is vital in many ecological and pollution studies of freshwater and oceanic systems. Present methods require manual counting and identification of algae and can take up to 90 min to obtain a statistically reliable count on a complex population. Several alternative techniques to accelerate the process have been tried on marine samples but none have been completely successful because insufficient effort has been put into verifying the technique before field trials. The objective of the present study has been to assess the potential of in vivo fluorescence of algal pigments as a means of automatically identifying algae. For this work total fluorescence spectroscopy was chosen as the observation technique.

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.

Laser beam automatic alignment in multipass amplifier

A laser beam automatic alignment system is applied in a multipass amplifier of the SG-III prototype laser. Considering the requirements of the SG-III prototype facility, by combining the general techniques of the laser beam automatic alignment system, according to the image relayed of the pinholes in the spatial filter, and utilizing the optical position and the spatial distribution of the four pinholes of the main spatial filter in the multipass amplifier of the SG-III prototype, a reasonable and optimized scheme for automatic aligning multipass beam paths is presented. It is demonstrated on the multipass amplifier experimental system. (C) 2004 Society of Photo-Optical Instrumentation Engineers.

Interpretação de imagens multitemporais de sensoriamento remoto.

Estudos multitemporais de dados de sensoriamento remoto dedicam-se ao mapeamento temático de uso da terra em diferentes instâncias de tempo com o objetivo de identificar as mudanças ocorridas em uma região em determinado período. Em sua maioria, os trabalhos de classificação automática supervisionada de imagens de sensoriamento remoto não utilizam um modelo de transformação temporal no processo de classificação. Pesquisas realizadas na última década abriram um importante precedente ao comprovarem que a utilização de um modelo de conhecimento sobre a dinâmica da região (modelo de transformação temporal), baseado em Cadeias de Markov Fuzzy (CMF), possibilita resultados superiores aos produzidos pelos classificadores supervisionados monotemporais. Desta forma, o presente trabalho enfoca um dos aspectos desta abordagem pouco investigados: a combinação de CMF de intervalos de tempo curtos para classificar imagens de períodos longos. A área de estudo utilizada nos experimentos é um remanescente florestal situado no município de Londrina-PR e que abrange todo o limite do Parque Estadual Mata dos Godoy. Como dados de entrada, são utilizadas cinco imagens do satélite Landsat 5 TM com intervalo temporal de cinco anos. De uma forma geral, verificou-se, a partir dos resultados experimentais, que o uso das Cadeias de Markov Fuzzy contribuiu significativamente para a melhoria do desempenho do processo de classificação automática em imagens orbitais multitemporais, quando comparado com uma classificação monotemporal. Ainda, pôde-se observar que as classificações com base em matrizes estimadas para períodos curtos sempre apresentaram resultados superiores aos das classificações com base em matrizes estimadas para períodos longos. Também, que a superioridade da estimação direta frente à extrapolação se reduz com o aumento da distância temporal. Os resultados do presente trabalho poderão servir de motivação para a criação de sistemas automáticos de classificação de imagens multitemporais. O potencial de sua aplicação se justifica pela aceleração do processo de monitoramento do uso e cobertura da terra, considerando a melhoria obtida frente a classificações supervisionadas tradicionais.