Search results for "Termination"
showing 10 items of 780 documents
Fallzahlplanung bei ophthalmologischen Studien*
2000
An essential aspect in the cooperation of clinic and biometry consists in designing of studies, e.g. during the preparation of grant applications or for review by official drug surveillance institutions. A central aspect in study planning is the design-adequate and well-documented prediction of sample size, which should be recommended for any intended study. Based on several examples for sample size planning in study designs, which are of common relevance for ophthalmology, guidelines are derived to enable clinical researchers to perform sample size planning on their own. The latter can be based on the various available software packages for sample size prediction.
Comparison of Metrics for the Classification of Soils Under Variable Geometrical Conditions Using Hyperspectral Data
2008
International audience; The objective of this letter is to find a distance metric between reflectance spectra that is not sensitive to the variations on the soil reflectance induced by the geometry of solar-view angles. This is motivated by the fact that differences between spectra measured for the same soil under different observation and illumination configurations can lead to misclassifications. Using 26 soils of different compositions simulated with Hapke’s model and 92 soils of different compositions measured under 28 solarview angle geometries in laboratory conditions, we tested three metrics, namely, root-mean-square error, spectral angle mapper, and R2 (the coefficient of determinat…
Using Aerial Platforms in Predicting Water Quality Parameters from Hyperspectral Imaging Data with Deep Neural Networks
2020
In near future it is assumable that automated unmanned aerial platforms are coming more common. There are visions that transportation of different goods would be done with large planes, which can handle over 1000 kg payloads. While these planes are used for transportation they could similarly be used for remote sensing applications by adding sensors to the planes. Hyperspectral imagers are one this kind of sensor types. There is need for the efficient methods to interpret hyperspectral data to the wanted water quality parameters. In this work we survey the performance of neural networks in the prediction of water quality parameters from remotely sensed hyperspectral data in freshwater basin…
Comparison of metrics to remove the influence of geometrical conditions on soil reflectance
2007
The objective of this work is to find the best metric to ignore the variations of soil reflectance induced by the solar-view angles geometry. Differences between spectra measured for the same soil under different observation and illumination configurations can leads to misclassifications. Using ninety two soils of different composition measured under twenty eight solar- view angles geometries, we tested 3 metrics : RMSE, SAM, R2 (the coefficient of determination) and we compared their performances. The best metric seems to be the coefficient of determination with 93 % of good classifications.
A modified applicative criterion of the physical model concept for evaluating plot soil erosion predictions
2015
Abstract In this paper, the physical model concept by Nearing (1998. Catena 32: 15–22) was assessed. Soil loss data collected on plots of different widths (2–8 m), lengths (11–44 m) and steepnesses (14.9–26.0%), equipped in south and central Italy, were used. Differences in width between plots of given length and steepness determined a lower data correlation and more deviation of the fitted regression line from the identity one. A coefficient of determination between measured, M , and predicted, P , soil losses of 0.77 was representative of the best-case prediction scenario, according to Nearing (1998). The relative differences, Rdiff = ( P − M ) / ( P + M ), decreased in absolute value a…
Prediction of soil texture distributions using VNIR-SWIR reflectance spectroscopy
2013
Abstract Reflectance spectroscopy provides an alternate method to non-destructively characterize key soil properties. Different approaches, including chemometrics techniques or specific absorption features, have been proposed to estimate soil properties from visible and near-infrared (VNIR, 400-1200 nm) and shortwave infrared (SWIR, 1200-2500 nm) reflectance domains. The main goal of this study was to test the performance of two distinct methods for soil texture estimation by VNIR-SWIR reflectance measurements: i) the Continuum Removal (CR) technique that was used to correlate specific spectral absorption features with clay, silt and sand content, and ii) the Partial Least-Squares Regressio…
Learning Motivation and Activity Contexts
1994
Abstract Learning motivation has a special explanatory status in educational psychology and educational practice. Motivation and learning often are studied separately. In the achievement motivation tradition, achievement situation is the connecting link between learning process and achievement need. The explanatory power of this link has limitations. The activity concept is proposed as a unit which is able to offer a broader basis for a unified concept of learning motivation.
Challenges in the determination of engineered nanomaterials in foods
2016
Detection, characterization, and quantification of engineering nanomaterials (ENMs) in foods is still a pending issue that needs to be tackle to protect consumers and to fix some related aspects (e.g. labelling or control). The global challenge for the analytical sciences is that ENMs are a new sort of analytes, involving both chemical (composition, mass and number concentration) and physical information (e.g. size, shape, aggregation). In this critical review, we evaluate and compare the procedures involved in the analytical methods and studies developed thus far for the identification and quantification of ENMs in food. We discuss advantages and limitation as well as prospects. We pointed…
The impact of sample reduction on PCA-based feature extraction for supervised learning
2006
"The curse of dimensionality" is pertinent to many learning algorithms, and it denotes the drastic raise of computational complexity and classification error in high dimensions. In this paper, different feature extraction (FE) techniques are analyzed as means of dimensionality reduction, and constructive induction with respect to the performance of Naive Bayes classifier. When a data set contains a large number of instances, some sampling approach is applied to address the computational complexity of FE and classification processes. The main goal of this paper is to show the impact of sample reduction on the process of FE for supervised learning. In our study we analyzed the conventional PC…
Editing prototypes in the finite sample size case using alternative neighborhoods
1998
The recently introduced concept of Nearest Centroid Neighborhood is applied to discard outliers and prototypes 111 class overlapping regions in order to improve the performance of the Nearest Neighbor rule through an editing procedure, This approach is related to graph based editing algorithms which also define alternative neighborhoods in terms of geornetric relations, Classical editing algorithms are compared to these alternative editing schemes using several synthetic and real data problems. The empirical results show that, the proposed editing algorithm constitutes a good trade-off among performance and computational burden.