The present authors recorded electroencephalograms (EEGs) from subjects viewing four types of line drawings of body part, tetrapod, home appliance, that were presented on a CRT. The authors investigated a single trial...
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The present authors recorded electroencephalograms (EEGs) from subjects viewing four types of line drawings of body part, tetrapod, home appliance, that were presented on a CRT. The authors investigated a single trial EEGs of the subject precisely after the latency at 400 ms, and determined effective sampling latencies for the discriminant analysis to some types of images. They sampled EEG data at latencies from 400 ms to 900 ms at 25 ms intervals by the four channels such as Fp2, F4, C4 and F8. Data were resampled -1 ms and -2 ms backward. Results of the discriminant analysis with jack knife method for four type objective varieties, the discriminant rates for two subjects were more than 95 %.
The bag of visual words model (BoW) and its variants have demonstrate their effectiveness for visual applications and have been widely used by researchers. The BoW model first extracts local features and generates the...
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In this paper, we present a Monte-Carlo policy rollout technique (called MOCART-CGA) for path planning in dynamic and partially observable real-time environments such as Real-time Strategy games. The emphasis is put o...
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Microbial interaction, such as species competition and symbiotic relationships, plays important role to enable microorganisms to survive by establishing a homeostasis between microbial neighbors and local environments...
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Microbial interaction, such as species competition and symbiotic relationships, plays important role to enable microorganisms to survive by establishing a homeostasis between microbial neighbors and local environments. Thanks to the recent accumulation of large-scale high-throughput sequencing data of complex microbial communities, there are increasing interests in identifying microbial interactions. Computational methods for microbial interactions inference are currently focused on the similarity among microbial individuals (i.e. cooccurrence and correlation patterns), however, less methods considered the dynamics of a single complex community over time. In this paper, we propose to use a multivariate statistical method - Multivariate Vector Autoregression (MVAR) to infer dynamic microbial interactions from the time series of human gut microbiomes. Specifically, we apply MVAR model on a time series data of human gut microbiomes which were treated with repeated antibiotics. The referred microbial interactions identify novel interactions which may provide a novel complementary to similarity or correlation-based methods.
Social media are media contributed by common users and distributed in social networks. There may exist thousands of answers to a single question provided by different users. However, it is difficult to evaluate the au...
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As dynamic kernel runtime objects are a significant source of security and reliability problems in Operating Systems (OSes), having a complete and accurate understanding of kernel dynamic data layout in memory becomes...
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Cloud computing arise as an efficient way to allocate resources for execution of task and services within a set of geographically dispersed providers from different organizations. In cloud computing, an IaaS computing...
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MicroRNAs (miRNAs) are noncoding RNAs of ∼22 nucleotides that play versatile regulatory roles in multicelluler organisms. Since the cloning methods for miRNAs identification are biased towards abundant miRNAs, the co...
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software systems are subject to change. To embrace change, the systems should be equipped with automated mechanisms. Business process and software architecture models are two artifacts that are subject to change in an...
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