30 resultados para ensemble empirical mode decomposition with canonical correlation analysis (EEMD-CCA)

em Aston University Research Archive


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The thesis presents new methodology and algorithms that can be used to analyse and measure the hand tremor and fatigue of surgeons while performing surgery. This will assist them in deriving useful information about their fatigue levels, and make them aware of the changes in their tool point accuracies. This thesis proposes that muscular changes of surgeons, which occur through a day of operating, can be monitored using Electromyography (EMG) signals. The multi-channel EMG signals are measured at different muscles in the upper arm of surgeons. The dependence of EMG signals has been examined to test the hypothesis that EMG signals are coupled with and dependent on each other. The results demonstrated that EMG signals collected from different channels while mimicking an operating posture are independent. Consequently, single channel fatigue analysis has been performed. In measuring hand tremor, a new method for determining the maximum tremor amplitude using Principal Component Analysis (PCA) and a new technique to detrend acceleration signals using Empirical Mode Decomposition algorithm were introduced. This tremor determination method is more representative for surgeons and it is suggested as an alternative fatigue measure. This was combined with the complexity analysis method, and applied to surgically captured data to determine if operating has an effect on a surgeon’s fatigue and tremor levels. It was found that surgical tremor and fatigue are developed throughout a day of operating and that this could be determined based solely on their initial values. Finally, several Nonlinear AutoRegressive with eXogenous inputs (NARX) neural networks were evaluated. The results suggest that it is possible to monitor surgeon tremor variations during surgery from their EMG fatigue measurements.

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The pattern of correlation between two sets of variables can be tested using canonical variate analysis (CVA). CVA, like principal components analysis (PCA) and factor analysis (FA) (Statnote 27, Hilton & Armstrong, 2011b), is a multivariate analysis Essentially, as in PCA/FA, the objective is to determine whether the correlations between two sets of variables can be explained by a smaller number of ‘axes of correlation’ or ‘canonical roots’.

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This study examines the relationship between student perceptions of different types of educator power and different modes of student complaining behaviour in the case of university education. A large sample of marketing students in the business school responded to the study from a state university in Northeastern United States. Factor analysis and canonical correlation analysis are used to explore the relationships between five bases of power perceptions (referent, expert, reward, legitimate, and punishment) and four modes of complaining behaviour (voice, negative word of mouth, third party, and exit). The results indicate that students engage in different modes of complaining as they perceive different types of educator power. The predominant complaining mode is found to be voice under referent or expert power, third party under legitimate power, and exit under reward or punishment power. Our findings offer important implications for student satisfaction, retention, and completion rates in higher education.

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We analyze a Big Data set of geo-tagged tweets for a year (Oct. 2013–Oct. 2014) to understand the regional linguistic variation in the U.S. Prior work on regional linguistic variations usually took a long time to collect data and focused on either rural or urban areas. Geo-tagged Twitter data offers an unprecedented database with rich linguistic representation of fine spatiotemporal resolution and continuity. From the one-year Twitter corpus, we extract lexical characteristics for twitter users by summarizing the frequencies of a set of lexical alternations that each user has used. We spatially aggregate and smooth each lexical characteristic to derive county-based linguistic variables, from which orthogonal dimensions are extracted using the principal component analysis (PCA). Finally a regionalization method is used to discover hierarchical dialect regions using the PCA components. The regionalization results reveal interesting linguistic regional variations in the U.S. The discovered regions not only confirm past research findings in the literature but also provide new insights and a more detailed understanding of very recent linguistic patterns in the U.S.

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Although event-related potentials (ERPs) are widely used to study sensory, perceptual and cognitive processes, it remains unknown whether they are phase-locked signals superimposed upon the ongoing electroencephalogram (EEG) or result from phase-alignment of the EEG. Previous attempts to discriminate between these hypotheses have been unsuccessful but here a new test is presented based on the prediction that ERPs generated by phase-alignment will be associated with event-related changes in frequency whereas evoked-ERPs will not. Using empirical mode decomposition (EMD), which allows measurement of narrow-band changes in the EEG without predefining frequency bands, evidence was found for transient frequency slowing in recognition memory ERPs but not in simulated data derived from the evoked model. Furthermore, the timing of phase-alignment was frequency dependent with the earliest alignment occurring at high frequencies. Based on these findings, the Firefly model was developed, which proposes that both evoked and induced power changes derive from frequency-dependent phase-alignment of the ongoing EEG. Simulated data derived from the Firefly model provided a close match with empirical data and the model was able to account for i) the shape and timing of ERPs at different scalp sites, ii) the event-related desynchronization in alpha and synchronization in theta, and iii) changes in the power density spectrum from the pre-stimulus baseline to the post-stimulus period. The Firefly Model, therefore, provides not only a unifying account of event-related changes in the EEG but also a possible mechanism for cross-frequency information processing.

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We show transmission of a 3x112-Gb/s DP-QPSK mode-division-multiplexed signal up to 80km, with and without multi-mode EDFA, using blind 6x6 MIMO digital signal processing. We show that the OSNR-penalty induced by mode-mixing in the multi-mode EDFA is negligible.

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In this paper, we investigate the design of few-mode fibers (FMFs) guiding 4 to 12 non-degenerate linearly polarized (LP) modes with low differential mode delay (DMD) over the C-band, suitable for long-haul transmission. The refractive index profile considered is composed by a graded-core with a cladding trench (GCCT). The optimization of the profile parameters aims the lowest possible DMD and macro-bend losses (MBL) lower than the ITU-T standard recommendation. The optimization results show that the optimum DMD and the MBL scale with the number of modes. Additionally, it is shown that the refractive-index relative difference at the core center is one of the most preponderant parameters, allowing to reduce the DMD at the expense of increasing MBL. Finally, the optimum DMD obtained for 12 LP modes is lower than 3 ps/km. © 2014 IEEE.

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In this paper, we investigate the design of few-mode fibers (FMFs) guiding 2 to 12 linearly polarized (LP) modes with low differential mode delay (DMD) over the C-band, suitable for long-haul transmission. Two different types of refractive index profile have been considered: a graded-core with a cladding trench (GCCT) profile and a multi-step-index (MSI) profile. The profiles parameters are optimized in order to achieve: the lowest possible DMD and macro-bend losses (MBL) lower than the ITU-T standard recommendation. The optimization results show that the MSI profiles present lower DMD than the minimum achieved with a GCCT profile. Moreover, it is shown that the optimum DMD and the MBL scale with the number of modes for both profiles. The optimum DMD obtained for 12 LP modes is lower than 3 ps/km using a GCCT profile and lower than 2.5 ps/km using a MSI profile. The optimization results reveal that the most preponderant parameter of the GCCT profile is the refractive index relative difference at the core center, Δnco. Reducing Δn co, the DMD is reduced at the expense of increasing the MBL. Regarding the MSI profiles, it is shown that 64 steps are required to obtain a DMD improvement considering 12 LP modes. Finally, the impact of the fabrication margins on the optimum DMD is analyzed. The probability of having a manufactured FMF with 12 LP modes and DMD lower than 12 ps/km is approximately 68% using a GCCT profile and 16% using a MSI profile. © 2013 IEEE.

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This letter proposes the use of a refractive index profile with a graded core and a cladding trench for the design of few-mode fibers, aiming an arbitrary differential mode delay (DMD) flattened over the C+ L band. By optimizing the core grading exponent and the dimensioning of the trench, a deviation lower than 0.01 ps/km from a target DMD is observed over the investigated wavelength range. Additionally, it is found that the dimensioning of the trench is almost independent of the target DMD, thereby enabling the use of a simple design rule that guarantees a maximum DMD deviation of 1.8 ps/km for a DMD target between-200 and 200 ps/km. © 2012 IEEE.

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We show transmission of a 3x112-Gb/s DP-QPSK mode-division-multiplexed signal up to 80km, with and without multi-mode EDFA, using blind 6x6 MIMO digital signal processing. We show that the OSNR-penalty induced by mode-mixing in the multi-mode EDFA is negligible.

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We show experimentally and numerically new transient lasing regime between stable single-pulse generation and noise-like generation. We characterize qualitatively all three regimes of single pulse generation per round-trip of all-normal-dispersion fiber lasers mode-locked due to effect of nonlinear polarization evolution. We study spectral and temporal features of pulses produced in all three regimes as well as compressibility of such pulses. Simple criteria are proposed to identify lasing regime in experiment. © 2012 Optical Society of America.

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Diabetes patients might suffer from an unhealthy life, long-term treatment and chronic complicated diseases. The decreasing hospitalization rate is a crucial problem for health care centers. This study combines the bagging method with base classifier decision tree and costs-sensitive analysis for diabetes patients' classification purpose. Real patients' data collected from a regional hospital in Thailand were analyzed. The relevance factors were selected and used to construct base classifier decision tree models to classify diabetes and non-diabetes patients. The bagging method was then applied to improve accuracy. Finally, asymmetric classification cost matrices were used to give more alternative models for diabetes data analysis.

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We report an investigation on the statistics of group delay for few-mode fibres operating in the weak and strong linear coupling regimes as well as in the intermediate coupling regime. A single expression linking the standard deviation of the group delay spread to the fibre linear mode coupling is validated for any coupling regime, considering up to six linearly polarized guided modes. Furthermore, the study of the probability density function of the group delays allowed deriving and validating an analytical estimation for the maximum group delay spread as a function of linear mode coupling.