Double Fourier analysis for Emotion Identification in Voiced Speech

We propose a novel analysis alternative, based on two Fourier Transforms for emotion recognition from speech -- Fourier analysis allows for display and synthesizes different signals, in terms of power spectral density distributions -- A spectrogram of the voice signal is obtained performing a short time Fourier Transform with Gaussian windows, this spectrogram portraits frequency related features, such as vocal tract resonances and quasi-periodic excitations during voiced sounds -- Emotions induce such characteristics in speech, which become apparent in spectrogram time-frequency distributions -- Later, the signal time-frequency representation from spectrogram is considered an image, and processed through a 2-dimensional Fourier Transform in order to perform the spatial Fourier analysis from it -- Finally features related with emotions in voiced speech are extracted and presented

Spectral Frame Analysis and Learning through Graph Structure

This dissertation investigates the connection between spectral analysis and frame theory. When considering the spectral properties of a frame, we present a few novel results relating to the spectral decomposition. We first show that scalable frames have the property that the inner product of the scaling coefficients and the eigenvectors must equal the inverse eigenvalues. From this, we prove a similar result when an approximate scaling is obtained. We then focus on the optimization problems inherent to the scalable frames by first showing that there is an equivalence between scaling a frame and optimization problems with a non-restrictive objective function. Various objective functions are considered, and an analysis of the solution type is presented. For linear objectives, we can encourage sparse scalings, and with barrier objective functions, we force dense solutions. We further consider frames in high dimensions, and derive various solution techniques. From here, we restrict ourselves to various frame classes, to add more specificity to the results. Using frames generated from distributions allows for the placement of probabilistic bounds on scalability. For discrete distributions (Bernoulli and Rademacher), we bound the probability of encountering an ONB, and for continuous symmetric distributions (Uniform and Gaussian), we show that symmetry is retained in the transformed domain. We also prove several hyperplane-separation results. With the theory developed, we discuss graph applications of the scalability framework. We make a connection with graph conditioning, and show the in-feasibility of the problem in the general case. After a modification, we show that any complete graph can be conditioned. We then present a modification of standard PCA (robust PCA) developed by Cand\`es, and give some background into Electron Energy-Loss Spectroscopy (EELS). We design a novel scheme for the processing of EELS through robust PCA and least-squares regression, and test this scheme on biological samples. Finally, we take the idea of robust PCA and apply the technique of kernel PCA to perform robust manifold learning. We derive the problem and present an algorithm for its solution. There is also discussion of the differences with RPCA that make theoretical guarantees difficult.

Wavelet analysis and hierarchical clustering of ofm phenotypic population's variations originated from southern america and europe and attempts of a first relation to molecular divergence.

In this work we compare Grapholita molesta Busck (Lepidoptera: Tortricidae) populations originated from Brazil, Chile, Spain, Italy and Greece using power spectral density and phylogenetic analysis to detect any similarities between the population macro- and the molecular micro-level. Log-transformed population data were normalized and AR(p) models were developed to generate for each case population time series of equal lengths. The time-frequency/scale properties of the population data were further analyzed using wavelet analysis to detect any population dynamics frequency changes and cluster the populations. Based on the power spectral of each population time series and the hierarchical clustering schemes, populations originated from Southern America (Brazil and Chile) exhibit similar rhythmic properties and are both closer related with populations originated from Greece. Populations from Spain and especially Italy, have higher distance by terms of periodic changes on their population dynamics. Moreover, the members within the same cluster share similar spectral information, therefore they are supposed to participate in the same temporally regulated population process. On the contrary, the phylogenetic approach revealed a less structured pattern that bears indications of panmixia, as the two clusters contain individuals from both Europe and South America. This preliminary outcome will be further assessed by incorporating more individuals and likely employed a second molecular marker.

Variabilidade da frequencia cardiaca : estudo das influencias autonomicas sobre suas caracteristicas temporal e espectral em halterofilistas e sedentarios

Universidade Estadual de Campinas. Faculdade de Educação Física

Influence of high- and low-carbohydrate diet following glycogen-depleting exercise on heart rate variability and plasma catecholamines

The purpose of this study was to investigate the effects of a short-term low-or high-carbohydrate (CHO) diet consumed after exercise on sympathetic nervous system activity. Twelve healthy males underwent a progressive incremental test; a control measurement of plasma catecholamines and heart rate variability (HRV); an exercise protocol to reduce endogenous CHO stores; a low-or high-CHO diet (counterbalanced order) consumed for 2 days, beginning immediately after the exercise protocol; and a second resting plasma catecholamine and HRV measurement. The exercise and diet protocols and the second round of measurements were performed again after a 1-week washout period. The mean (+/- SD) values of the standard deviation of R-R intervals were similar between conditions (control, 899.0 +/- 146.1 ms; low-CHO diet, 876.8 +/- 115.8 ms; and high-CHO diet, 878.7 +/- 127.7 ms). The absolute high-and low-frequency (HF and LF, respectively) densities of the HRV power spectrum were also not different between conditions. However, normalized HF and LF (i.e., relative to the total power spectrum) were lower and higher, respectively, in the low-CHO diet than in the control diet (mean +/- SD, 17 +/- 9 normalized units (NU) and 83 +/- 9 NU vs. 27 +/- 11 NU and 73 +/- 17 NU, respectively; p < 0.05). The LF/HF ratio was higher with the low-CHO diet than with the control diet (mean +/- SD, 7.2 +/- 6.2 and 4.2 +/- 3.2, respectively; p < 0.05). The mean values of plasma catecholamines were not different between diets. These results suggest that the autonomic control of the heart rate was modified after a short-term low-CHO diet, but plasma catecholamine levels were not altered.

A low carbohydrate diet affects autonomic modulation during heavy but not moderate exercise

The aim of this study was to examine the effects of low carbohydrate (CHO) availability on heart rate variability (HRV) responses during moderate and severe exercise intensities until exhaustion. Six healthy males (age, 26.5 +/- 6.7 years; body mass, 78.4 +/- 7.7 kg; body fat %, 11.3 +/- 4.5%; (V) over dotO(2max), 39.5 +/- 6.6 mL kg(-1) min(-1)) volunteered for this study. All tests were performed in the morning, after 8-12 h overnight fasting, at a moderate intensity corresponding to 50% of the difference between the first (LT(1)) and second (LT(2)) lactate breakpoints and at a severe intensity corresponding to 25% of the difference between the maximal power output and LT(2). Forty-eight hours before each experimental session, the subjects performed a 90-min cycling exercise followed by 5-min rest periods and subsequent 1-min cycling bouts at 125% (V) over dotO(2max) (with 1-min rest periods) until exhaustion, in order to deplete muscle glycogen. A diet providing 10% (CHO(low)) or 65% (CHO(control)) of energy as carbohydrates was consumed for the following 2 days until the experimental test. The Poicare plots (standard deviations 1 and 2: SD1 and SD2, respectively) and spectral autoregressive model (low frequency LF, and high frequency HF) were applied to obtain HRV parameters. The CHO availability had no effect on the HRV parameters or ventilation during moderate-intensity exercise. However, the SD1 and SD2 parameters were significantly higher in CHO(low) than in CHO(control), as taken at exhaustion during the severe-intensity exercise (P < 0.05). The HF and LF frequencies (ms(2)) were also significantly higher in CHO(low) than in CHO(control) (P < 0.05). In addition, ventilation measured at the 5 and 10-min was higher in CHO(low) (62.5 +/- 4.4 and 74.8 +/- 6.5 L min(-1), respectively, P < 0.05) than in CHO(control) (70.0 +/- 3.6 and 79.6 +/- 5.1 L min(-1), respectively; P < 0.05) during the severe-intensity exercise. These results suggest that the CHO availability alters the HRV parameters during severe-, but not moderate-, intensity exercise, and this was associated with an increase in ventilation volume.

Postural control during kneeling

Postural control was studied when the subject was kneeling with erect trunk in a quiet posture and compared to that obtained during quiet standing. The analysis was based on the center of pressure motion in the sagittal plane (CPx), both in the time and in the frequency domains. One could assume that postural control during kneeling would be poorer than in standing because it is a less natural posture. This could cause a higher CPx variability. The power spectral density (PSD) of the CPx obtained from the experimental data in the kneeling position (KN) showed a significant decrease at frequencies below 0.3 Hz compared to upright (UP) (P < 0.01), which indicates less sway in KN. Conversely, there was an increase in fast postural oscillations (above 0.7 Hz) during KN compared to UP (P < 0.05). The root mean square (RMS) of the CPx was higher for UP (P < 0.01) while the mean velocity (MV) was higher during KN (P < 0.05). Lack of vision had a significant effect on the PSD and the parameters estimated from the CPx in both positions. We also sought to verify whether the changes in the PSD of the CPx found between the UP and KN positions were exclusively due to biomechanical factors (e.g., lowered center of gravity), or also reflected changes in the neural processes involved in the control of balance. To reach this goal, besides the experimental approach, a simple feedback model (a PID neural system, with added neural noise and controlling an inverted pendulum) was used to simulate postural sway in both conditions (in KN the pendulum was shortened, the mass and the moment of inertia were decreased). A parameter optimization method was used to fit the CPx power spectrum given by the model to that obtained experimentally. The results indicated that the changed anthropometric parameters in KN would indeed cause a large decrease in the power spectrum at low frequencies. However, the model fitting also showed that there were considerable changes also in the neural subsystem when the subject went from standing to kneeling. There was a lowering of the proportional and derivative gains and an increase in the neural noise power. Additional increases in the neural noise power were found also when the subject closed his eyes.

A power system control scheme based on security visualisation in parameter space

Power system real time security assessment is one of the fundamental modules of the electricity markets. Typically, when a contingency occurs, it is required that security assessment and enhancement module shall be ready for action within about 20 minutes’ time to meet the real time requirement. The recent California black out again highlighted the importance of system security. This paper proposed an approach for power system security assessment and enhancement based on the information provided from the pre-defined system parameter space. The proposed scheme opens up an efficient way for real time security assessment and enhancement in a competitive electricity market for single contingency case

A framework for electricity price spike analysis with advanced data mining methods

There are many techniques for electricity market price forecasting. However, most of them are designed for expected price analysis rather than price spike forecasting. An effective method of predicting the occurrence of spikes has not yet been observed in the literature so far. In this paper, a data mining based approach is presented to give a reliable forecast of the occurrence of price spikes. Combined with the spike value prediction techniques developed by the same authors, the proposed approach aims at providing a comprehensive tool for price spike forecasting. In this paper, feature selection techniques are firstly described to identify the attributes relevant to the occurrence of spikes. A simple introduction to the classification techniques is given for completeness. Two algorithms: support vector machine and probability classifier are chosen to be the spike occurrence predictors and are discussed in details. Realistic market data are used to test the proposed model with promising results.

Complete assignments of (1)H and (13)C NMR spectral data for 7,7 `-dihydroarylnaphthalene lignan lactones

In this article we present a complete (1)H and (13)C NMR spectral analysis of three 7,7`-dihydroarylnaphthalene lignan lactones using modern NMR techniques such as COSY, HSQC, HMBC and NOE experiments. Complete assignment and homonuclear hydrogen coupling constant measurements were performed. Copyright (C) 2009 John Wiley & Sons, Ltd.

Effect of the duration of daily aerobic physical training on cardiac autonomic adaptations

The present study has investigated in conscious rats the influence of the duration of physical training sessions on cardiac autonomic adaptations by using different approaches; 1) double blockade with methylatropine and propranolol; 2) the baroreflex sensitivity evaluated by alternating bolus injections of phenylephrine and sodium nitroprusside; and 3) the autonomic modulation of HRV in the frequency domain by means of spectral analysis. The animals were divided into four groups: one sedentary group and three training groups submitted to physical exercise (swimming) for 15, 30, and 60 min a day during 10 weeks. All training groups showed similar reduction in intrinsic heart rate (IHR) after double blockade with methylatropine and propranolol. However, only 30-min and 60-min physical training presented an increase in the vagal autonomic component for determination of basal heart rate (HR) in relation to group sedentary. Spectral analysis of HR showed that the 30-min and 60-min physical training presented the reduction in low-frequency oscillations (LF = 0.20-0.75 Hz) and the increase in high-frequency oscillations (HF = 0.75-2.5 Hz) in normalized units. These both groups only showed an increased baroreflex sensitivity to tachycardiac responses in relation to group sedentary, however when compared, the physical training of 30-min exhibited a greater gain. In conclusion, cardiac autonomic adaptations, characterised by the increased predominance of the vagal autonomic component, were not proportional to the duration of daily physical training sessions. In fact, 30-minute training sessions provided similar cardiac autonomic adaptations, or even more enhanced ones, as in the case of baroreflex sensitivity compared to 60-minute training sessions. (C) 2010 Elsevier B.V. All rights reserved.

Sympathetic-mediated hypertension of awake juvenile rats submitted to chronic intermittent hypoxia is not linked to baroreflex dysfunction

In the present study, we evaluated the mechanisms underpinning the hypertension observed in freely moving juvenile rats submitted to chronic intermittent hypoxia (CIH). Male juvenile Wistar rats (20-21 days old) were submitted to CIH (6% O(2) for 40 s every 9 min, 8 h day(-1)) for 10 days while control rats were maintained in normoxia. Prior to CIH, baseline systolic arterial pressure (SAP), measured indirectly, was similar between groups (86 +/- 1 versus 87 +/- 1 mmHg). After exposure to CIH, SAP recorded directly was higher in the CIH (n = 28) than in the control group (n = 29; 131 +/- 3 versus 115 +/- 2 mmHg, P < 0.05). This higher SAP of CIH rats presented an augmented power of oscillatory components at low (10.05 +/- 0.91 versus 5.02 +/- 0.63 mmHg(2), P < 0.05) and high (respiratory-related) frequencies (12.42 +/- 2.46 versus 3.28 +/- 0.61 mmHg(2), P < 0.05) in comparison with control animals. In addition, rats exposed to CIH also exhibited an increased cardiac baroreflex gain (-3.11 +/- 0.08 versus -2.1 +/- 0.10 beats min(-1) mmHg(-1), P < 0.0001), associated with a shift to the right of the operating point, in comparison with control rats. Administration of hexamethonium (ganglionic blocker, i.v.), injected after losartan (angiotensin II type 1 receptor antagonist) and [beta-mercapto-beta,beta-cyclopenta-methylenepropionyl(1), O-Me-Tyr(2), Arg(8)]-vasopressin (vasopressin type 1a receptor antagonist), produced a larger depressor response in the CIH (n = 8) than in the control group (n = 9; -49 +/- 2 versus -39 +/- 2 mmHg, P < 0.05). Fifteen days after the cessation of exposure to CIH, the mean arterial pressure of CIH rats returned to normal levels. The data indicate that the sympathetic-mediated hypertension observed in conscious juvenile rats exposed to CIH is not secondary to a reduction in cardiac baroreflex gain and exhibits a higher respiratory modulation, indicating that an enhanced respiratory-sympathetic coupling seems to be the major factor contributing to hypertension in rats exposed to CIH.

Reliability of electromyographic and torque measures during isometric axial rotation exertions of the trunk

Objective: The aim of the present study was to investigate the between-days reliability of electromyographic (EMG) measurement of 6 bilateral trunk muscles and also the torque output in 3 planes during isometric right and left axial rotation at different exertion levels. Methods: Ten healthy subjects performed isometric right and left axial rotation at 100, 70, 50 and 30% maximum voluntary contractions in two testing sessions at least 7 days apart. EMG amplitude and frequency analyses of the recorded surface EMG signals were performed for rectus abdominis, external oblique, internal oblique, latissimus dorsi, iliocostalis lumborum and multifidus bilaterally. The primary torque in the transverse plane and the coupling torques in sagittal and coronal planes were measured. Results: For both EMG amplitude and frequency values, good (intraclass correlation coefficient, ICC = 0.75-0.89) to excellent (ICC greater than or equal to 0.90) reliability was found in the 6 trunk muscles at different exertion levels during axial rotation. The reliability of both maximal isometric axial rotation torque and coupling torques in sagittal and coronal planes were found to be excellent (ICC greater than or equal to 0.93). Conclusions: Good to excellent reliability of EMG measures of trunk muscles and torque measurements during isometric axial rotation was demonstrated. This provides further confidence of using EMG and triaxial torque assessment as outcome measures in rehabilitation and in the evaluation of the human performance in the work place. (C) 2003 International Federation of Clinical Neurophysiology. Published by Elsevier Ireland Ltd. All rights reserved.

Analysis of the Van der Pol oscillator containing derivatives of fractional order

In this paper a modified version of the classical Van der Pol oscillator is proposed, introducing fractional-order time derivatives into the state-space model. The resulting fractional-order Van der Pol oscillator is analyzed in the time and frequency domains, using phase portraits, spectral analysis and bifurcation diagrams. The fractional-order dynamics is illustrated through numerical simulations of the proposed schemes using approximations to fractional-order operators. Finally, the analysis is extended to the forced Van der Pol oscillator.

Parallel GPU architecture for hyperspectral unmixing based on augmented Lagrangian method

Hyperspectral imaging has become one of the main topics in remote sensing applications, which comprise hundreds of spectral bands at different (almost contiguous) wavelength channels over the same area generating large data volumes comprising several GBs per flight. This high spectral resolution can be used for object detection and for discriminate between different objects based on their spectral characteristics. One of the main problems involved in hyperspectral analysis is the presence of mixed pixels, which arise when the spacial resolution of the sensor is not able to separate spectrally distinct materials. Spectral unmixing is one of the most important task for hyperspectral data exploitation. However, the unmixing algorithms can be computationally very expensive, and even high power consuming, which compromises the use in applications under on-board constraints. In recent years, graphics processing units (GPUs) have evolved into highly parallel and programmable systems. Specifically, several hyperspectral imaging algorithms have shown to be able to benefit from this hardware taking advantage of the extremely high floating-point processing performance, compact size, huge memory bandwidth, and relatively low cost of these units, which make them appealing for onboard data processing. In this paper, we propose a parallel implementation of an augmented Lagragian based method for unsupervised hyperspectral linear unmixing on GPUs using CUDA. The method called simplex identification via split augmented Lagrangian (SISAL) aims to identify the endmembers of a scene, i.e., is able to unmix hyperspectral data sets in which the pure pixel assumption is violated. The efficient implementation of SISAL method presented in this work exploits the GPU architecture at low level, using shared memory and coalesced accesses to memory.