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Full-Text Articles in Physical Sciences and Mathematics
Comparison Of Apple's Ios 5 And Android For Mobile Applications Development: A Developer's Perspective, Estela Pochintesta
Comparison Of Apple's Ios 5 And Android For Mobile Applications Development: A Developer's Perspective, Estela Pochintesta
Electronic Theses and Dissertations
Body composition, or the proportion of fat, muscle, and bone of an individual's body, is an important indication of health status. Numerous techniques can be used to assess body composition, producing varied results and measurements. For individuals with insufficient or excessive amounts of body fat, accurate assessment of body composition is crucial. Two commonly used techniques for measuring body composition are air displacement plethysmography (adp) and dual-energy x-ray absorptiometry (dxa). Past research has been conducted, comparing adp and dxa, but the results are inconsistent. The majority of past studies found that, when compared to dxa, adp underestimated body fat percentage, …
Restricting Supervised Learning: Feature Selection And Feature Space Partition, Xiaofei Nan
Restricting Supervised Learning: Feature Selection And Feature Space Partition, Xiaofei Nan
Electronic Theses and Dissertations
Many supervised learning problems are considered difficult to solve either because of the redundant features or because of the structural complexity of the generative function. Redundant features increase the learning noise and therefore decrease the prediction performance. Additionally, a number of problems in various applications such as bioinformatics or image processing, whose data are sampled in a high dimensional space, suffer the curse of dimensionality, and there are not enough observations to obtain good estimates. Therefore, it is necessary to reduce such features under consideration. Another issue of supervised learning is caused by the complexity of an unknown generative model. …
An Ssvep Brain-Computer Interface: A Machine Learning Approach, Fei Teng
An Ssvep Brain-Computer Interface: A Machine Learning Approach, Fei Teng
Electronic Theses and Dissertations
A Brain-Computer Interface (BCI) provides a bidirectional communication path for a human to control an external device using brain signals. Among neurophysiological features in BCI systems, steady state visually evoked potentials (SSVEP), natural responses to visual stimulation at specific frequencies, has increasingly drawn attentions because of its high temporal resolution and minimal user training, which are two important parameters in evaluating a BCI system. The performance of a BCI can be improved by a properly selected neurophysiological signal, or by the introduction of machine learning techniques. With the help of machine learning methods, a BCI system can adapt to the …