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Physical Sciences and Mathematics Commons™
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- Keyword
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- Biomedical literature searching (1)
- Biomedical text mining (1)
- Brain-computer interface (BCI) (1)
- Data mining (1)
- Digital libraries (1)
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- Electroencephalogram (EEG) (1)
- Genescene (1)
- Genetic (1)
- Independent component analysis (ICA) (1)
- Information extraction (1)
- Information retrieval (1)
- Internet (1)
- Medical information systems (1)
- Motion planning (1)
- NP-completeness (1)
- Natural language processing technique (1)
- Natural languages (1)
- Neural networks (1)
- Online interface (1)
- PSPACE-completeness (1)
- Text analysis (1)
Articles 1 - 3 of 3
Full-Text Articles in Physical Sciences and Mathematics
Enabling Computer Decisions Based On Eeg Input, Benjamin J. Culpepper, Robert M. Keller
Enabling Computer Decisions Based On Eeg Input, Benjamin J. Culpepper, Robert M. Keller
All HMC Faculty Publications and Research
Multilayer neural networks were successfully trained to classify segments of 12-channel electroencephalogram (EEG) data into one of five classes corresponding to five cognitive tasks performed by a subject. Independent component analysis (ICA) was used to segregate obvious artifact EEG components from other sources, and a frequency-band representation was used to represent the sources computed by ICA. Examples of results include an 85% accuracy rate on differentiation between two tasks, using a segment of EEG only 0.05 s long and a 95% accuracy rate using a 0.5-s-long segment.
Genescene: Biomedical Text And Data Mining, Gondy Leroy, Hsinchun Chen, Jesse D. Martinez, Shauna Eggers, Ryan R. Falsey, Kerri L. Kislin, Zan Huang, Jiexun Li, Jie Xu, Daniel M. Mcdonald, Gavin Ng
Genescene: Biomedical Text And Data Mining, Gondy Leroy, Hsinchun Chen, Jesse D. Martinez, Shauna Eggers, Ryan R. Falsey, Kerri L. Kislin, Zan Huang, Jiexun Li, Jie Xu, Daniel M. Mcdonald, Gavin Ng
CGU Faculty Publications and Research
To access the content of digital texts efficiently, it is necessary to provide more sophisticated access than keyword based searching. GeneScene provides biomedical researchers with research findings and background relations automatically extracted from text and experimental data. These provide a more detailed overview of the information available. The extracted relations were evaluated by qualified researchers and are precise. A qualitative ongoing evaluation of the current online interface indicates that this method to search the literature is more useful and efficient than keyword based searching.
The Computational Complexity Of Motion Planning, Jeff R.K. Hartline '01, Ran Libeskind-Hadas
The Computational Complexity Of Motion Planning, Jeff R.K. Hartline '01, Ran Libeskind-Hadas
All HMC Faculty Publications and Research
In this paper we show that a generalization of a popular motion planning puzzle called Lunar Lockout is computationally intractable. In particular, we show that the problem is PSPACE-complete. We begin with a review of NP-completeness and polynomial-time reductions, introduce the class PSPACE, and motivate the significance of PSPACE-complete problems. Afterwards, we prove that determining whether a given instance of a generalized Lunar Lockout puzzle is solvable is PSPACE-complete.