SINGLE STAGE LED DRIVER TECHNOLOGY WITH LOW FREQUENCY RIPPLE CANCELLATION

Because of high efficacy, long lifespan, and environment-friendly operation, LED lighting devices become more and more popular in every part of our life, such as ornament/interior lighting, outdoor lightings and flood lighting. The LED driver is the most critical part of the LED lighting fixture. It heavily affects the purchasing cost, operation cost as well as the light quality. Design a high efficiency, low component cost and flicker-free LED driver is the goal. The conventional single-stage LED driver can achieve low cost and high efficiency. However, it inevitably produces significant twice-line-frequency lighting flicker, which adversely affects our health. The conventional two-stage LED driver can achieve flicker-free LED driving at the expenses of significantly adding component cost, design complexity and low the efficiency. The basic ripple cancellation LED driving method has been proposed in chapter three. It achieves a high efficiency and a low component cost as the single-stage LED driver while also obtaining flicker-free LED driving performance. The basic ripple cancellation LED driver is the foundation of the entire thesis. As the research evolving, another two ripple cancellation LED drivers has been developed to improve different aspects of the basic ripple cancellation LED driver design. The primary side controlled ripple cancellation LED driver has been proposed in chapter four to further reduce cost on the control circuit. It eliminates secondary side compensation circuit and an opto-coupler in design while at the same time maintaining flicker-free LED driving. A potential integrated primary side controller can be designed based on the proposed LED driving method. The energy channeling ripple cancellation LED driver has been proposed in chapter five to further reduce cost on the power stage circuit. In previous two ripple cancellation LED drivers, an additional DC-DC converter is needed to achieve ripple cancellation. A power transistor has been used in the energy channeling ripple cancellation LED driving design to successfully replace a separate DC-DC converter and therefore achieved lower cost. The detailed analysis supports the theory of the proposed ripple cancellation LED drivers. Simulation and experiment have also been included to verify the proposed ripple cancellation LED drivers.

Digging up the frequency of phrasal verbs in English for the Police: the case of "up"

The present study focuses on the frequency of phrasal verbs with the particle up in the context of crime and police investigative work. This research emerges from the need to enlarge McCarthy and O’Dell’s (2004) scope from purely criminal behavior to police investigative actions. To do so, we relied on a corpus of 504,124 running words made up of spoken dialogues extracted from the script of the American TV series Castle shown on ABC since 2009. Based on Rudzka-Ostyn’s (2003) cognitive motivations for the particle up, we have identified five different meaning extensions for our phrasal verbs. Drawing from these findings, we have designed pedagogical activities for those L2 learners that study English at the Police Academy.

Modeling, Analysis and Performance Comparison of Two Direct Sampling DCSK Receivers under Frequency Nonselective Fading Channels

Two direct sampling correlator-type receivers for differential chaos shift keying (DCSK) communication systems under frequency non-selective fading channels are proposed. These receivers operate based on the same hardware platform with different architectures. In the first scheme, namely sum-delay-sum (SDS) receiver, the sum of all samples in a chip period is correlated with its delayed version. The correlation value obtained in each bit period is then compared with a fixed threshold to decide the binary value of recovered bit at the output. On the other hand, the second scheme, namely delay-sum-sum (DSS) receiver, calculates the correlation value of all samples with its delayed version in a chip period. The sum of correlation values in each bit period is then compared with the threshold to recover the data. The conventional DCSK transmitter, frequency non-selective Rayleigh fading channel, and two proposed receivers are mathematically modelled in discrete-time domain. The authors evaluated the bit error rate performance of the receivers by means of both theoretical analysis and numerical simulation. The performance comparison shows that the two proposed receivers can perform well under the studied channel, where the performances get better when the number of paths increases and the DSS receiver outperforms the SDS one.

Theta-associated high-frequency oscillations (110–160 Hz) in the hippocampus and neocortex

TORT, A. B. L. ; SCHEFFER-TEIXEIRA, R ; Souza, B.C. ; DRAGUHN, A. ; BRANKACK, J. . Theta-associated high-frequency oscillations (110-160 Hz) in the hippocampus and neocortex. Progress in Neurobiology , v. 100, p. 1-14, 2013.

On the effect of word frequency on distributional similarity

The dependency of word similarity in vector space models on the frequency of words has been noted in a few studies, but has received very little attention. We study the influence of word frequency in a set of 10 000 randomly selected word pairs for a number of different combinations of feature weighting schemes and similarity measures. We find that the similarity of word pairs for all methods, except for the one using singular value decomposition to reduce the dimensionality of the feature space, is determined to a large extent by the frequency of the words. In a binary classification task of pairs of synonyms and unrelated words we find that for all similarity measures the results can be improved when we correct for the frequency bias.

Measuring, Modeling, and Forecasting Volatility and Correlations from High-Frequency Data

This dissertation contains four essays that all share a common purpose: developing new methodologies to exploit the potential of high-frequency data for the measurement, modeling and forecasting of financial assets volatility and correlations. The first two chapters provide useful tools for univariate applications while the last two chapters develop multivariate methodologies. In chapter 1, we introduce a new class of univariate volatility models named FloGARCH models. FloGARCH models provide a parsimonious joint model for low frequency returns and realized measures, and are sufficiently flexible to capture long memory as well as asymmetries related to leverage effects. We analyze the performances of the models in a realistic numerical study and on the basis of a data set composed of 65 equities. Using more than 10 years of high-frequency transactions, we document significant statistical gains related to the FloGARCH models in terms of in-sample fit, out-of-sample fit and forecasting accuracy compared to classical and Realized GARCH models. In chapter 2, using 12 years of high-frequency transactions for 55 U.S. stocks, we argue that combining low-frequency exogenous economic indicators with high-frequency financial data improves the ability of conditionally heteroskedastic models to forecast the volatility of returns, their full multi-step ahead conditional distribution and the multi-period Value-at-Risk. Using a refined version of the Realized LGARCH model allowing for time-varying intercept and implemented with realized kernels, we document that nominal corporate profits and term spreads have strong long-run predictive ability and generate accurate risk measures forecasts over long-horizon. The results are based on several loss functions and tests, including the Model Confidence Set. Chapter 3 is a joint work with David Veredas. We study the class of disentangled realized estimators for the integrated covariance matrix of Brownian semimartingales with finite activity jumps. These estimators separate correlations and volatilities. We analyze different combinations of quantile- and median-based realized volatilities, and four estimators of realized correlations with three synchronization schemes. Their finite sample properties are studied under four data generating processes, in presence, or not, of microstructure noise, and under synchronous and asynchronous trading. The main finding is that the pre-averaged version of disentangled estimators based on Gaussian ranks (for the correlations) and median deviations (for the volatilities) provide a precise, computationally efficient, and easy alternative to measure integrated covariances on the basis of noisy and asynchronous prices. Along these lines, a minimum variance portfolio application shows the superiority of this disentangled realized estimator in terms of numerous performance metrics. Chapter 4 is co-authored with Niels S. Hansen, Asger Lunde and Kasper V. Olesen, all affiliated with CREATES at Aarhus University. We propose to use the Realized Beta GARCH model to exploit the potential of high-frequency data in commodity markets. The model produces high quality forecasts of pairwise correlations between commodities which can be used to construct a composite covariance matrix. We evaluate the quality of this matrix in a portfolio context and compare it to models used in the industry. We demonstrate significant economic gains in a realistic setting including short selling constraints and transaction costs.

Rational Function Interpolation of Electromagnetic Transfer Functions of High-Speed Interconnect Systems from Discrete Time-Domain and Frequency-Domain Data

We present new methodologies to generate rational function approximations of broadband electromagnetic responses of linear and passive networks of high-speed interconnects, and to construct SPICE-compatible, equivalent circuit representations of the generated rational functions. These new methodologies are driven by the desire to improve the computational efficiency of the rational function fitting process, and to ensure enhanced accuracy of the generated rational function interpolation and its equivalent circuit representation. Toward this goal, we propose two new methodologies for rational function approximation of high-speed interconnect network responses. The first one relies on the use of both time-domain and frequency-domain data, obtained either through measurement or numerical simulation, to generate a rational function representation that extrapolates the input, early-time transient response data to late-time response while at the same time providing a means to both interpolate and extrapolate the used frequency-domain data. The aforementioned hybrid methodology can be considered as a generalization of the frequency-domain rational function fitting utilizing frequency-domain response data only, and the time-domain rational function fitting utilizing transient response data only. In this context, a guideline is proposed for estimating the order of the rational function approximation from transient data. The availability of such an estimate expedites the time-domain rational function fitting process. The second approach relies on the extraction of the delay associated with causal electromagnetic responses of interconnect systems to provide for a more stable rational function process utilizing a lower-order rational function interpolation. A distinctive feature of the proposed methodology is its utilization of scattering parameters. For both methodologies, the approach of fitting the electromagnetic network matrix one element at a time is applied. It is shown that, with regard to the computational cost of the rational function fitting process, such an element-by-element rational function fitting is more advantageous than full matrix fitting for systems with a large number of ports. Despite the disadvantage that different sets of poles are used in the rational function of different elements in the network matrix, such an approach provides for improved accuracy in the fitting of network matrices of systems characterized by both strongly coupled and weakly coupled ports. Finally, in order to provide a means for enforcing passivity in the adopted element-by-element rational function fitting approach, the methodology for passivity enforcement via quadratic programming is modified appropriately for this purpose and demonstrated in the context of element-by-element rational function fitting of the admittance matrix of an electromagnetic multiport.

Theta-associated high-frequency oscillations (110–160 Hz) in the hippocampus and neocortex

TORT, A. B. L. ; SCHEFFER-TEIXEIRA, R ; Souza, B.C. ; DRAGUHN, A. ; BRANKACK, J. . Theta-associated high-frequency oscillations (110-160 Hz) in the hippocampus and neocortex. Progress in Neurobiology , v. 100, p. 1-14, 2013.

A Multidimensional Approach to Social Support: the Questionnaire on the Frequency of and Satisfaction with Social Support (QFSSS)

The Questionnaire on the Frequency of and Satisfaction with Social Support (QFSSS) was designed to assess the frequency of and the degree of satisfaction with perceived social support received from different sources in relation to three types of support: emotional, informational, and instrumental. This study tested the reliability of the questionnaire scores and its criterion and structural validity. The data were drawn from survey interviews of 2042 Spanish people. The results show high internal consistency (values of Cronbach's alpha ranged from .763 to .952). The correlational analysis showed significant positive associations between QFSSS scores and measures of subjective well-being and perceived social support, as well as significant negative associations with measures of loneliness (values of Pearson's r correlation ranged from .11 to .97). Confirmatory factor analysis using structural equation modelling verified an internal 4-factor structure that corresponds to the sources of support analysed: partner, family, friends, and community (values ranged from .93 to .95 for the Goodness of Fit Index (GFI); from .95 to .98 for the Comparative Fit Index (CFI); and from .10 to .07 for the Root Mean Square Error of Approximation (RMSEA)). These results confirm the validity of the QFSSS as a versatile tool which is suitable for the multidimensional assessment of social support.

Low-frequency and common genetic variation in ischemic stroke: The METASTROKE collaboration

Erratum in: Low-frequency and common genetic variation in ischemic stroke: The METASTROKE collaboration. [Neurology. 2016]

Comparison of two field methods for estimating body fat in different Spanish Dance disciplines

The purpose of the present study was to investigate percentage body fat (%BF) differences in three Spanish dance disciplines and to compare skinfold and bioelectrical impedance predictions of body fat percentage in the same sample. Seventy-six female dancers, divided into three groups, Classical (n=23), Spanish (n=29) and Flamenco (n=24), were measured using skinfold measurements at four sites: triceps, subscapular, biceps and iliac crest, and whole body multi-frequency bioelectrical impedance (BIA). The skin-fold measures were used to predict body fat percentage via Durnin and Womersley's and Segal, Sun and Yannakoulia equations by BIA. Differences in percent fat mass between groups (Classical, Spanish and Flamenco) were tested by using repeated measures analysis (ANOVA). Also, Pearson's product-moment correlations were performed on the body fat percentage values obtained using both methods. In addition, Bland-Altman plots were used to assess agreement, between anthropometric and BIA methods. Repeated measures analysis of variance did not found differences in %BF between modalities (p<0.05). Fat percentage correlations ranged from r= 0.57 to r=0.97 (all, p<0.001). Bland-Altman analysis revealed differences between BIA Yannakoulia as a reference method with BIA Segal (-0.35 ± 2.32%, 95%CI: -0.89to 0.18, p=0.38), with BIA Sun (-0.73 ± 2.3%, 95%CI: -1.27 to -0.20, p=0.014) and Durnin-Womersley (-2.65 ± 2,48%, 95%CI: -3.22 to -2.07, p<0.0001). It was concluded that body fat percentage estimates by BIA compared with skinfold method were systematically different in young adult female ballet dancers, having a tendency to produce underestimations as %BF increased with Segal and Durnin-Womersley equations compared to Yannakoulia, concluding that these methods are not interchangeable.

Sparse time-frequency data analysis : a multi-scale approach

In this work, we further extend the recently developed adaptive data analysis method, the Sparse Time-Frequency Representation (STFR) method. This method is based on the assumption that many physical signals inherently contain AM-FM representations. We propose a sparse optimization method to extract the AM-FM representations of such signals. We prove the convergence of the method for periodic signals under certain assumptions and provide practical algorithms specifically for the non-periodic STFR, which extends the method to tackle problems that former STFR methods could not handle, including stability to noise and non-periodic data analysis. This is a significant improvement since many adaptive and non-adaptive signal processing methods are not fully capable of handling non-periodic signals. Moreover, we propose a new STFR algorithm to study intrawave signals with strong frequency modulation and analyze the convergence of this new algorithm for periodic signals. Such signals have previously remained a bottleneck for all signal processing methods. Furthermore, we propose a modified version of STFR that facilitates the extraction of intrawaves that have overlaping frequency content. We show that the STFR methods can be applied to the realm of dynamical systems and cardiovascular signals. In particular, we present a simplified and modified version of the STFR algorithm that is potentially useful for the diagnosis of some cardiovascular diseases. We further explain some preliminary work on the nature of Intrinsic Mode Functions (IMFs) and how they can have different representations in different phase coordinates. This analysis shows that the uncertainty principle is fundamental to all oscillating signals.

Antimicrobial resistance of heterotrophic marine bacteria isolated from seawater and sands of recreational beaches with different organic pollution levels in southeastern Brazil: evidences of resistance dissemination

Antimicrobial resistance of marine heterotrophic bacteria to different antimicrobials agents were evaluated in seawater, dry and wet sands from three marine recreational beaches with different pollution levels. In all studied beaches, the greatest frequencies of resistance were found in relation to penicillin. on Gonzaguinha, the most polluted beach, 72.3% of all isolated strains showed simple resistance, whilst 8.33% had multiple resistance. The values found on Ilha Porchat beach, were 70.8% and 6.9% for simple and multiple resistances, respectively. on GuaraA(0), the less polluted beach, only 35.3% of isolated strains had simple resistance. Multiple resistance was not observed. While samples from Gonzaguinha and Ilha Porchat beach showed isolated strains resistant to seven and six different antimicrobial agents, respectively, samples from GuaraA(0) beach were resistant only to penicillin and erytromicin. The positive correlations obtained between the degree of seawater contamination and frequency and variability of bacterial resistance indicate that polluted marine recreational waters and sands are sources of resistant bacteria contributing thus, to the dissemination of bacterial resistance.

Radio Frequency Superconducting Quantum Interference Device Meta-atoms and Metamaterials: Experiment, Theory, and Analysis

Metamamterials are 1D, 2D or 3D arrays of articial atoms. The articial atoms, called "meta-atoms", can be any component with tailorable electromagnetic properties, such as resonators, LC circuits, nano particles, and so on. By designing the properties of individual meta-atoms and the interaction created by putting them in a lattice, one can create a metamaterial with intriguing properties not found in nature. My Ph. D. work examines the meta-atoms based on radio frequency superconducting quantum interference devices (rf-SQUIDs); their tunability with dc magnetic field, rf magnetic field, and temperature are studied. The rf-SQUIDs are superconducting split ring resonators in which the usual capacitance is supplemented with a Josephson junction, which introduces strong nonlinearity in the rf properties. At relatively low rf magnetic field, a magnetic field tunability of the resonant frequency of up to 80 THz/Gauss by dc magnetic field is observed, and a total frequency tunability of 100% is achieved. The macroscopic quantum superconducting metamaterial also shows manipulative self-induced broadband transparency due to a qualitatively novel nonlinear mechanism that is different from conventional electromagnetically induced transparency (EIT) or its classical analogs. A near complete disappearance of resonant absorption under a range of applied rf flux is observed experimentally and explained theoretically. The transparency comes from the intrinsic bi-stability and can be tuned on/ off easily by altering rf and dc magnetic fields, temperature and history. Hysteretic in situ 100% tunability of transparency paves the way for auto-cloaking metamaterials, intensity dependent filters, and fast-tunable power limiters. An rf-SQUID metamaterial is shown to have qualitatively the same behavior as a single rf-SQUID with regards to dc flux, rf flux and temperature tuning. The two-tone response of self-resonant rf-SQUID meta-atoms and metamaterials is then studied here via intermodulation (IM) measurement over a broad range of tone frequencies and tone powers. A sharp onset followed by a surprising strongly suppressed IM region near the resonance is observed. This behavior can be understood employing methods in nonlinear dynamics; the sharp onset, and the gap of IM, are due to sudden state jumps during a beat of the two-tone sum input signal. The theory predicts that the IM can be manipulated with tone power, center frequency, frequency difference between the two tones, and temperature. This quantitative understanding potentially allows for the design of rf-SQUID metamaterials with either very low or very high IM response.

Essays on mixed-frequency data : forecasting and unit root testing

Doutoramento em Economia