4 resultados para hollow section joint

em Aston University Research Archive


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Background The somatosensory cortex has been inconsistently activated in pain studies and the functional properties of subregions within this cortical area are poorly understood. To address this we used magnetoencephalography (MEG), a brain imaging technique capable of recording changes in cortical neural activity in real-time, to investigate the functional properties of the somatosensory cortex during different phases of the visceral pain experience. Methods In eight participants (4 male), 151-channel whole cortex MEG was used to detect cortical neural activity during 25 trials lasting 20 seconds each. Each trial comprised four separate periods of 5 seconds in duration. During each of the periods, different visual cues were presented, indicating that period 1=rest, period 2=anticipation, period 3=pain and period 4=post pain. During period 3, participants received painful oesophageal balloon distensions (four at 1 Hz). Regions of cortical activity were identified using Synthetic Aperture Magnetometry (SAM) and by the placement of virtual electrodes in regions of interest within the somatosensory cortex, time-frequency wavelet plots were generated. Results SAM analysis revealed significant activation with the primary (S1) and secondary (S2) somatosensory cortices. The time-frequency wavelet spectrograms showed that activation in S1 increased during the anticipation phase and continued during the presentation of the stimulus. In S2, activation was tightly time and phase-locked to the stimulus within the pain period. Activations in both regions predominantly occurred within the 10–15 Hz and 20–30 Hz frequency bandwidths. Discussion These data are consistent with the role of S1 and S2 in the sensory discriminatory aspects of pain processing. Activation of S1 during anticipation and then pain may be linked to its proposed role in attentional as well as sensory processing. The stimulus-related phasic activity seen in S2 demonstrates that this region predominantly encodes information pertaining to the nature and intensity of the stimulus.

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We have recently proposed the framework of independent blind source separation as an advantageous approach to steganography. Amongst the several characteristics noted was a sensitivity to message reconstruction due to small perturbations in the sources. This characteristic is not common in most other approaches to steganography. In this paper we discuss how this sensitivity relates the joint diagonalisation inside the independent component approach, and reliance on exact knowledge of secret information, and how it can be used as an additional and inherent security mechanism against malicious attack to discovery of the hidden messages. The paper therefore provides an enhanced mechanism that can be used for e-document forensic analysis and can be applied to different dimensionality digital data media. In this paper we use a low dimensional example of biomedical time series as might occur in the electronic patient health record, where protection of the private patient information is paramount.

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Sentiment analysis or opinion mining aims to use automated tools to detect subjective information such as opinions, attitudes, and feelings expressed in text. This paper proposes a novel probabilistic modeling framework based on Latent Dirichlet Allocation (LDA), called joint sentiment/topic model (JST), which detects sentiment and topic simultaneously from text. Unlike other machine learning approaches to sentiment classification which often require labeled corpora for classifier training, the proposed JST model is fully unsupervised. The model has been evaluated on the movie review dataset to classify the review sentiment polarity and minimum prior information have also been explored to further improve the sentiment classification accuracy. Preliminary experiments have shown promising results achieved by JST.

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World's first demonstration of WDM transmission in a HC-PBGF at the predicted low loss region of 2m is presented. A total capacity of 16 Gbit/s is achieved using 1×8.5 Gbit/s and 3×2.5 Gbit/s channels modulated using NRZ OOK over 290 meters of hollow core fiber. © 2013 OSA.