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Lyon Freire I.,Brazilian Military Institute of Engineering
Journal of the Acoustical Society of America | Year: 2014

This work investigates the direction-of-arrival problem. A time-delay-estimate (TDE) obtained from a peak of a correlation function is subject to two types of error: type I, approximation errors, and type II, errors due to spurious signals. The iterative least-squares algorithm tentatively selects spatially coherent subsets of TDEs containing no type II errors and minor contributions of type I errors ("matched-lags"). Simulations use a seven-microphone array and a gunshot signal. The evaluation methodology is rigorous, comparing empirical distribution functions of estimation error of algorithms through two-sample, one-sided Kolmogorov-Smirnov tests, and quantifying differences with Cohen's D. The direction-of-arrival estimate is improved, specifically at low signal-to-noise ratios. © 2014 Acoustical Society of America.

Franca T.C.C.,Brazilian Military Institute of Engineering
Journal of Biomolecular Structure and Dynamics | Year: 2015

In the last decades, homology modeling has become a popular tool to access theoretical three-dimensional (3D) structures of molecular targets. So far several 3D models of proteins have been built by this technique and used in a great diversity of structural biology studies. But are those models consistent enough with experimental structures to make this technique an effective and reliable tool for drug discovery? Here we present, briefly, the fundamentals and current state-of-the-art of the homology modeling techniques used to build 3D structures of molecular targets, which experimental structures are not available in databases, and list some of the more important works, using this technique, available in literature today. In many cases those studies have afforded successful models for the drug design of more selective agonists/antagonists to the molecular targets in focus and guided promising experimental works, proving that, when the appropriate templates are available, useful models can be built using some of the several software available today for this purpose. Limitations of the experimental techniques used to solve 3D structures allied to constant improvements in the homology modeling software will maintain the need for theoretical models, establishing the homology modeling as a fundamental tool for the drug discovery. © 2014 Taylor & Francis.

de Oliveira L.F.,Federal University of Rio de Janeiro | Luporini Menegaldo L.,Brazilian Military Institute of Engineering
Journal of Biomechanics | Year: 2010

EMG-driven models can be used to estimate muscle force in biomechanical systems. Collected and processed EMG readings are used as the input of a dynamic system, which is integrated numerically. This approach requires the definition of a reasonably large set of parameters. Some of these vary widely among subjects, and slight inaccuracies in such parameters can lead to large model output errors. One of these parameters is the maximum voluntary contraction force (Fom). This paper proposes an approach to find Fom by estimating muscle physiological cross-sectional area (PCSA) using ultrasound (US), which is multiplied by a realistic value of maximum muscle specific tension. Ultrasound is used to measure muscle thickness, which allows for the determination of muscle volume through regression equations. Soleus, gastrocnemius medialis and gastrocnemius lateralis PCSAs are estimated using published volume proportions among leg muscles, which also requires measurements of muscle fiber length and pennation angle by US. Fom obtained by this approach and from data widely cited in the literature was used to comparatively test a Hill-type EMG-driven model of the ankle joint. The model uses 3 EMGs (Soleus, gastrocnemius medialis and gastrocnemius lateralis) as inputs with joint torque as the output. The EMG signals were obtained in a series of experiments carried out with 8 adult male subjects, who performed an isometric contraction protocol consisting of 10s step contractions at 20% and 60% of the maximum voluntary contraction level. Isometric torque was simultaneously collected using a dynamometer. A statistically significant reduction in the root mean square error was observed when US-obtained Fom was used, as compared to Fom from the literature. © 2010 Elsevier Ltd.

Nicolalde Rodriguez D.P.,Brazilian Military Institute of Engineering | Apolinario Jr. J.A.,Brazilian Military Institute of Engineering | Biscainho L.W.P.,Federal University of Rio de Janeiro
IEEE Transactions on Information Forensics and Security | Year: 2010

This paper addresses a forensic tool used to assess audio authenticity. The proposed method is based on detecting phase discontinuity of the power grid signal; this signal, referred to as electric network frequency (ENF), is sometimes embedded in audio signals when the recording is carried out with the equipment connected to an electrical outlet or when certain microphones are in an ENF magnetic field. After down-sampling and band-filtering the audio around the nominal value of the ENF, the result can be considered a single tone such that a high-precision Fourier analysis can be used to estimate its phase. The estimated phase provides a visual aid to locating editing points (signalled by abrupt phase changes) and inferring the type of audio editing (insertion or removal of audio segments). From the estimated values, a feature is used to quantify the discontinuity of the ENF phase, allowing an automatic decision concerning the authenticity of the audio evidence. The theoretical background is presented along with practical implementation issues related to the proposed technique, whose performance is evaluated on digitally edited audio signals. © 2010 IEEE.

Zao L.,Brazilian Military Institute of Engineering | Coelho R.,Brazilian Military Institute of Engineering
IEEE Signal Processing Letters | Year: 2011

This letter proposes a colored noise based multicondition training technique for robust speaker identification in unknown noisy environments. The colored noise samples generation is based on filtering a white Gaussian sequence that leads to a power spectral density (PSD) proportional to 1/f β, where β ε [0, 2]. Gaussian mixture models (GMM) are applied to obtain the speaker models using the noisy speech signals with a single signal-to-noise ratio (SNR). The colored noise based multicondition training is evaluated for the speaker identification task considering the test utterances corrupted with real acoustic noises and different values of SNR. The results show that the proposed technique outperforms the white noise based multicondition and the clean-speech training approaches. © 2011 IEEE.

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