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Your search keyword '"Whelan, B. M."' showing total 10 results
Start Over Author "Whelan, B. M." Publication Year Range Last 50 years Language english
10 results on '"Whelan, B. M."'

6. Defining a role for the subthalamic nucleus within operative theoretical models of subcortical participation in language

Author

Whelan, B-M, Murdoch, B.E., Theodoros, D.G., Hall, B., and Silburn, P.

Subjects
Thalamus -- Influence, Language acquisition -- Evaluation, Cognitive learning -- Evaluation, Parkinson's disease -- Complications and side effects, Health, Psychology and mental health, Influence, Evaluation, Complications and side effects
Abstract

J Neurol Neurosurg Psychiatry 2003;74: 1543-1550 Objective: To investigate the effects of bilateral, surgically induced functional inhibition of the subthalamic nucleus (STN) on general language, high level linguistic abilities, and [...]

Published
2003

9. A comparison of bivariate classification and segmentation approaches to delineating and interpreting grain yield-protein management units

Author

Taylor, J. A., Charnomordic, B., Serge Guillaume, Tisseyre, B., Whelan, B. M., CLEREL CORNELL UNIVERSITY PORTLAND USA, Partenaires IRSTEA, Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture (IRSTEA)-Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture (IRSTEA), Institut National de la Recherche Agronomique (INRA), Information – Technologies – Analyse Environnementale – Procédés Agricoles (UMR ITAP), Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture (IRSTEA)-Institut national d’études supérieures agronomiques de Montpellier (Montpellier SupAgro), Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro), Institut national d’études supérieures agronomiques de Montpellier (Montpellier SupAgro), Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro), PRECISION ARICULTURE LABORATORY FAE SYDNEY AUS, CLEREL, Cornell University, Mathématiques, Informatique et STatistique pour l'Environnement et l'Agronomie (MISTEA), Institut national d’études supérieures agronomiques de Montpellier (Montpellier SupAgro)-Institut National de la Recherche Agronomique (INRA), Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture (IRSTEA), Precision Agriculture Laboratory, FAE, University of Sydney, Cornell University [New York], Institut National de la Recherche Agronomique (INRA)-Institut national d’études supérieures agronomiques de Montpellier (Montpellier SupAgro), Irstea Publications, Migration, Institut national d’études supérieures agronomiques de Montpellier (Montpellier SupAgro)-Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture (IRSTEA), and ProdInra, Archive Ouverte

Subjects
[SDV] Life Sciences [q-bio], [SDE] Environmental Sciences, NITROGEN, mathématiques appliquées, FUZZY INFERENCE SYSTEM, algorithm, [SDV]Life Sciences [q-bio], [SDE]Environmental Sciences, applied mathematics, TESSELLATION, algorithme
Abstract

International audience; A univariate segmentation algorithm has recently been developed for precision agricultural applications. This algorithm is adapted to a bivariate analysis to investigate zoning based on both yield and protein responses in an eastern Australian wheat field. The intention is to provide a zone-by-zone interpretation of the agronomic response to N. The segmentation algorithm provided management zone results comparable with the more widely used k-means classification. The algorithm is still under development but allows expert-knowledge to be incorporated into the zone delineation process.

Published
2013

10. Variability and uncertainty in spatial, temporal and spatiotemporal crop-yield and related data.

Author

McBratney AB, Whelan BM, and Shatar TM

Subjects
Crops, Agricultural growth & development, Ecosystem, Models, Biological, Models, Statistical
Abstract

Application of the theories of precision agriculture to the practicalities of broad-acre farming relies on successful handling of the ramifications of uncertainty in information, i.e. information pertaining to the spatial and temporal variation of those factors which determine yield components and/or environmental losses. This paper discusses the uncertainty of yield and related variables as measured by their spatial and temporal variance. The magnitude of these two components gives a suggestion as to the appropriate scale of management. Simultaneous reporting on spatial and temporal variation is rare and the theory of these types of process is still in its infancy. Some brief theory is presented, followed by several examples from the Rothamsted classic experiments, yield-monitoring experiments in Australia, a long-term barley trial in Denmark, and a soil moisture monitoring network. It is clear that annual temporal variation is much larger than the spatial variation within single fields. This leads to the conclusion that if precision agriculture is to have a sound scientific basis and ultimately a practical outcome then the null hypothesis that still remains to be seriously researched is: 'given the large temporal variation in yields relative to the scale of a single field, then the optimal risk aversion strategy is uniform management.'

Published
1997
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