Open Access. Powered by Scholars. Published by Universities.®
Articles 1 - 2 of 2
Full-Text Articles in Computer Sciences
Simplification Of Eeg Signal Extraction, Processing, And Classification Using A Consumer-Grade Headset To Facilitate Student Engagement In Bci Research, Jesus D. Rodriguez
Simplification Of Eeg Signal Extraction, Processing, And Classification Using A Consumer-Grade Headset To Facilitate Student Engagement In Bci Research, Jesus D. Rodriguez
Theses and Dissertations
Brain-computer interfaces (BCIs) are an emerging technology that leverage neurophysiological signals as input to computing systems. By circumventing the reliance on traditional input methods (e.g., mouse and keyboard), BCIs show a promising alternative interaction modality for people with disabilities. Advances in BCI research have further inspired a range of novel applications, such as the use of neurophysiological signals as passive input (e.g., to detect and reduce operator workload when managing multiple machines). BCIs have also emerged as a tool for student engagement due to the intrinsic interdisciplinarity of the technology, which spans the fields of computer science, electrical engineering, neuroscience, …
Approximate Set Union Via Approximate Randomization, Pengfei Gu
Approximate Set Union Via Approximate Randomization, Pengfei Gu
Theses and Dissertations
We develop an randomized approximation algorithm for the size of set union problem |A1 U A2 U...UAm|, which given a list of sets A1,...,Am with approximate set size m i for Ai with mi ∈ ((1–βL)|A i|,(1+βR)|Ai|), and biased random generators with Prob(x = RandomElement(Ai)) ∈ [1–a L/Ai, 1 +aR/Ai] for each input set Ai and element x ∈ Ai, where i = 1,2,...,m. The approximation |Ai | |Ai | ratio for |A1 U A2 U...UAm| is in the range [(1–ϵ)(1–aL)(1–βL),(1+ϵ)(1+β R)(1+βR)] for any ϵ ∈ (0,1), where α L,αR,βL,βR ∈ (0,1). The complexity of the algorithm …