0000000000441630
AUTHOR
Martti Juhola
Classification and retrieval on macroinvertebrate image databases
Aquatic ecosystems are continuously threatened by a growing number of human induced changes. Macroinvertebrate biomonitoring is particularly efficient in pinpointing the cause-effect structure between slow and subtle changes and their detrimental consequences in aquatic ecosystems. The greatest obstacle to implementing efficient biomonitoring is currently the cost-intensive human expert taxonomic identification of samples. While there is evidence that automated recognition techniques can match human taxa identification accuracy at greatly reduced costs, so far the development of automated identification techniques for aquatic organisms has been minimal. In this paper, we focus on advancing …
Evaluation of the postural stability of elderly persons using time domain signal analysis
A force platform is widely used in the evaluation of postural stability in man. Although an abundance of parameters are typically retrieved from force platform data, no uniform analysis of the data has been carried out. In general, the signal analysis does not analyze the underlying postural event, i.e., whether the signal consists of several small corrections or large excursions. In the present work, we studied the postural stability of 4589 elderly persons from Iceland on a force platform under visual and non-visual conditions during stance on a solid surface. We analyzed the internal relationship between frequently used time domain variables. In addition, we conducted a factor analysis u…
Evaluating the performance of artificial neural networks for the classification of freshwater benthic macroinvertebrates
Abstract Macroinvertebrates form an important functional component of aquatic ecosystems. Their ability to indicate various types of anthropogenic stressors is widely recognized which has made them an integral component of freshwater biomonitoring. The use of macroinvertebrates in biomonitoring is dependent on manual taxa identification which is currently a time-consuming and cost-intensive process conducted by highly trained taxonomical experts. Automated taxa identification of macroinvertebrates is a relatively recent research development. Previous studies have displayed great potential for solutions to this demanding data mining application. In this research we have a collection of 1350 …