2008

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Increasingly, knowledge-based tasks such as new product development and market research are being conducted by geographically dispersed teams. Early evidence from knowledge-based view of the firm and geographically dispersed work literatures suggests that at least four kinds of knowledge gaps---transactive…

Brazil nut is widely recognized as the cornerstone of the Amazonian extractive economy. Tight linkages between Brazil nut production, regional income, and intact mature forests have thrust this species into focus as a key component of Amazonian conservation and income…

Knowledge-based Cascade-correlation is a neural network algorithm that combines inductive learning and knowledge transfer (Shultz & Rivest, 2001). In the present thesis, this algorithm is tested on several real-world and artificial problems, and extended in several ways. The first extension…

In order to close the gap that exists between the research areas of mathematics anxiety and mathematics learning, this study examined cognitive, metacognitive, and affective aspects of mathematics anxiety as well as students' mathematics performance and competence. One hundred and…

Efforts to resolve environmental planning and decision-making conflicts usually focus on participant involvement, mutual understanding of the problem situation, evaluation criteria identification, data availability, and potential alternative solutions. However, as the alternatives become less distinct and participant values more diverse,…

The last decade has seen an increase in empirical research pertaining to coaching science and education. A great deal of research has focused on coaches of elite able-bodied athletes, while coaches of athletes with a disability have generally been overlooked.…

The role of the FEF/FPA and SEF in oculomotor prediction was investigated using psychophysics, functional MRI (fMRI) and TMS. The separate contribution of advance knowledge of target direction and target timing to predictive saccades, and neural activity in frontal oculomotor…

With the increasing demands of transforming raw data into information and knowledge, data mining becomes an important field to the discovery of useful information and hidden patterns in huge datasets. Both machine learning and database research have made major contributions…