Poster Abstract: Automatic Discovery for Common Application Protocol MimicryWith the development of Intrusion Detection Systems (IDS), some malicious applications begin to mimic common application protocol to get rid of detection. In the paper, we propose that we can automatic discover these protocol ...
Power to identify genome-wide significant signals was calculated using Quanto.47,48 This study is adequately powered to detect low-frequency alleles with large effect sizes and common alleles with substantial effect sizes (80% power to detect common alleles with odds ratio (OR)41.5; low-frequency...
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Next, we examined whether self/other differences became stronger in successive ROI sites. We therefore compared mean onset latencies (Fig.4a) with single-site random effect sizes (bfrom analyses in previous paragraph) for peak latency (Fig.5c) and peak power (e.g., self/other selectivity; Fi...
In addition, it has shown potential to achieve similar or improved performance levels with significantly smaller network sizes in a number of tested cases. A study on data augmentation of reverberant speech for robust speech recognition; Tom Ko, Vijayaditya Peddinti, Daniel Povey, Michael L. ...
Trivedi, Albert Montillo ; The application of deep learning to build accurate predictive models from functional neuroimaging data is often hindered by limited dataset sizes. Though data augmentation can help mitigate such training obstacles, most data augmentation methods have been developed for natural ...
to create gene scores. The European panel of the 1000 Genomes project was used as a reference set to estimate LD between SNPs. The analysis also requires the sample size of the study to be specified; because of the unbalanced nature of the study, the effective sample sizes were given here...
Trivedi, Albert Montillo ; The application of deep learning to build accurate predictive models from functional neuroimaging data is often hindered by limited dataset sizes. Though data augmentation can help mitigate such training obstacles, most data augmentation methods have been developed for natural ...
Trivedi, Albert Montillo ; The application of deep learning to build accurate predictive models from functional neuroimaging data is often hindered by limited dataset sizes. Though data augmentation can help mitigate such training obstacles, most data augmentation methods have been developed for natural ...