112 research outputs found
On the segmentation and classification of hand radiographs
This research is part of a wider project to build predictive models of bone age using hand radiograph images. We examine ways of finding the outline of a hand from an X-ray as the first stage in segmenting the image into constituent bones. We assess a variety of algorithms including contouring, which has not previously been used in this context. We introduce a novel ensemble algorithm for combining outlines using two voting schemes, a likelihood ratio test and dynamic time warping (DTW). Our goal is to minimize the human intervention required, hence we investigate alternative ways of training a classifier to determine whether an outline is in fact correct or not. We evaluate outlining and classification on a set of 1370 images. We conclude that ensembling with DTW improves performance of all outlining algorithms, that the contouring algorithm used with the DTW ensemble performs the best of those assessed, and that the most effective classifier of hand outlines assessed is a random forest applied to outlines transformed into principal components
Design of a Planting Module for an Automatic Device for Forest Regeneration
Forest regeneration by means of seedlings grown in container nurseries is usually performed
manually with the use of the standard dibble bar or the tube dibble. Manual placement of a
large number of seedlings in the soil requires a lot of work. Manual removal of the soil cover
and digging the soil in spots with a diameter of 0.4 m requires, under average conditions, about
38 man-hours/ha, while planting with a dibble bar requires about 34 man-hours/ha. Additional
work time is needed to carry seedlings over an area that is being afforested. At present,
forestry does not have automatic planters that would enable the establishment of forest cultures.
The aim of the paper is to present the concept of an autonomous robot and an innovative
technology of performing forest regeneration and afforestation of former agricultural and reclaimed
areas. The paper also presents the design solutions of the key working unit, which is
a universal, openable dibble, cooperating with a three-toothed shaft to prepare a planting spot.
The solution proposed enables continuous operation of the machine, i.e. without the need to
stop the base vehicle
The effects of meteorological factors on the occurrence of Ganoderma sp. spores in the air
Ganoderma sp. is an airborne fungal spore type known to trigger respiratory allergy symptoms in sensitive patients. Aiming to reduce the risk for allergic individuals, we analysed fungal spore circulation in Szczecin, Poland, and its dependence on meteorological conditions. Statistical models for the airborne spore concentrations of Ganoderma sp.—one of the most abundant fungal taxa in the area—were developed. Aerobiological sampling was conducted over 2004–2008 using a volumetric Lanzoni trap. Simultaneously, the following meteorological parameters were recorded: daily level of precipitation, maximum and average wind speed, relative humidity and maximum, minimum, average and dew point temperatures. These data were used as the explaining variables. Due to the non-linearity and non-normality of the data set, the applied modelling techniques were artificial neural networks (ANN) and mutlivariate regression trees (MRT). The obtained classification and MRT models predicted threshold conditions above which Ganoderma sp. appeared in the air. It turned out that dew point temperature was the main factor influencing the presence or absence of Ganoderma sp. spores. Further analysis of spore seasons revealed that the airborne fungal spore concentration depended only slightly on meteorological factors
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