Acoustic Noise

Target audience: MRI engineers who specialize in gradient coil design, acoustic noise reduction and hybrid system development. Purpose: To find an engineering solution that can reduce gradient-switching induced acoustic noise in an MRI-Linear Accelerator (LINAC) system. Methods: We propose a novel method to relocate the acoustic field distribution in a split gradient system (see Fig. ). This method can move the loud areas in the split gradient assembly away from the central imaging area, thus effectively reducing the noise level for patients. This noise reduction scheme stems from beam-deflection theory [1]. If applying a force or moment on a beam, deformation will be produced. The deformation patterns are determined by a number of factors, of which, the boundary condition is a major influence. Assuming there is a beam with pin supports, as is shown in Fig. , the deflection of the beam can be calculated by integration

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Switched reluctance motors (SRMs) are gaining popularity in industrial and automotive applications due to their robust design, fault tolerance, and high torque density, particularly in wide-speed-range operations. However, SRM performance is often limited by torque ripple, speed oscillations, and inefficiencies, which can lead to mechanical stress, vibration, and acoustic noise. Addressing these challenges requires the effective optimization of control strategies. This study aims to enhance the performance of SRM drives by employing an ant colony optimization (ACO) algorithm to optimize the torque sharing function (TSF). The proposed method iteratively tunes TSF parameters to minimize torque ripple and improve speed stability under varying operating conditions. Simulation results demonstrate significant improvements: torque ripple is reduced from a range of-20 Nm to 10 Nm without optimization to below 10 Nm with ACO-based optimization. Similarly, current peaks decrease from 60 A to 5.5 A, ensuring smoother motor operation and enhanced efficiency. Comparative analysis confirms that the ACO-based TSF provides superior tracking of speed set points, reduced mechanical stress, and improved reliability, making it well-suited for highperformance applications in both industrial and automotive sectors.

We would like to thank Professor A. B. M. Harun-ur Rashid, our supervisor, for his many suggestions and constant support during this research. We are also thankful to Professor Md. Kamrul Hasan for his guidance in the theoretical aspects of the research when we were in chaos and confusion. Taufique Hasan Al Banna, an Alumni of Buet currently researching in University of Texas, Dallas, shared with us his knowledge of speech enhancement and provided many useful references and friendly encouragement. Of course, we are grateful to our parents for their patience and love. Without them this work would never have come into existence (literally). Finally, we wish to thank the following: Tarek, Partha, Md. Gaffar, Nasif and all the other friends who gave us love and support.

The relative frequency response is an important acoustic feature used to characterise acoustic targets. This response has been defined as the sv, volume backscattering coefficient, for a specific frequency relative to that of a reference frequency (38 kHz). The acoustic data commonly used in these calculations are derived from integrated measurements in a region containing multiple targets. In this study the relative frequency responses at 18, 38, 70, 120, and 200 kHz have additionally been measured using filtered target strength data on all frequencies. The spatial comparability of the sv-data is thus avoided, while the single-target detection becomes a new challenge. Target strength was extracted from in situ measurements, using calibrated and digitised data from a Simrad EK60 with split-beam transducers transmitting simultaneously at all five frequencies. Selected series with nearly pure catches of Atlantic cod (Gadus Morhua L.), saithe (Pollachius virens L.) and Norway pout (Tri...

2004). Recommendations for the collection of multi-frequency acoustic data. ICES CM2004/R:36, 15 pp. Traditionally, collection of acoustic data has been optimised for a single frequency, while requirements for the optimal combination of multifrequency data has been given less attention. Even though data manipulation can enable single-frequency data to be combined to some extent, optimal multifrequency comparisons cannot be made from a system if the input data are not collected properly. Multiple single-frequency [s(f)] data may be collected in various ways onboard research and fishing vessels. For detailed analysis, the physical and spatial characteristics of acoustic data should be as similar as possible. While direct comparability is impossible in all aspects, ideal data is defined as a reference point for the collection and analysis of multiple s(f) data. Acoustic data from several single frequencies are defined as ideal in this context if they can be used to generate combined fr...

Higher indoor carbon dioxide (CO 2 ) levels have been directly associated with impaired work performance and increased health symptoms. Historically, it was believed that these associations exist only because higher indoor CO 2 concentrations, resulting from lower outdoor air ventilation rates, are also correlated with higher levels of other indoor-generated pollutants that directly cause the adverse effects. More recent studies, however, have found that CO 2 itself, even at levels previously considered acceptable, may have adverse effects. Considering the benefits and demonstrated return on investment, building owners and operators should consider proactive methods of improving IAQ. Established strategies and guidelines are readily available to help identify and implement IAQ-related improvements. These include recognizing and addressing potential and real IAQ issues during the design, construction, renovation, and ongoing maintenance of buildings. Research has found that the benefits of IAQ improvement far outweigh the costs, with estimates of 3-6 times returns for increased ventilation, 8 times returns for increased filtration, and up to 60 times returns when all improvements and related benefits are combined. Collectively, the scientific literature demonstrates that improved workplace productivity and reduced absenteeism from improved IAQ have been shown to provide substantial financial benefits, with the benefits often greatly outweighing the associated costs.

A hybrid adaptive algorithm is developed for an active noise control system that leverages the stability of the filtered-input normalized least mean squares (FxNLMS) adaptive algorithm, with the high convergence speed of the filtered-input recursive least squares (FxRLS) adaptive algorithm. This algorithm is motivated by practical issues in implementing a real-time active noise control system. It leads to fast initial convergence with low, stable steady-state error while being limited by the computational capability of hardware. It gives better convergence speed than either the FxNLMS or FxRLS algorithm individually, lower residual error, and a lower overall computational complexity than the FxRLS algorithm, when appropriate filter lengths are chosen. Experimental results are presented for the implementation of the hybrid algorithm to cancel functional magnetic resonance imaging (fMRI) acoustic noise in an fMRI test-bed.

In this paper, the acoustic-phonetic characteristics of American English stop consonants are investigated. Features studied in the literature are evaluated for their information content and new features are proposed. A statistically guided, knowledge-based, acoustic-phonetic system for the automatic classification of stops, in speaker independent continuous speech, is proposed. The system uses a new auditory-based front-end processing and incorporates new algorithms for the extraction and manipulation of the acoustic-phonetic features that proved to be rich in their information content. Recognition experiments are performed using hard decision algorithms on stops extracted from the TIMIT database continuous speech of 60 speakers (not used in the design process) from seven different dialects of American English. An accuracy of 96% is obtained for voicing detection, 90% for place articulation detection and 86% for the overall classification of stops.

The reassignment method for the short-time Fourier transform is proposed as a technique for improving the time and frequency estimates of musical audio data. Based on this representation, four classes of expected objects (sinusoid, unresolved sinusoid, transient and noise) are proposed and explained. Pattern classification methods are then used to extract objects conforming to these classes from individual frames of the reassigned spectrogram, with each frame being examined independently. Results for several simple real-world examples are presented, showing the capability of this method even without the aid of tracking from frame to frame. The main benefits of the proposed reassignment stage are that it yields an improved time-frequency localisation estimate relative to standard methods, and that it produces a measure of the variance of these estimates to be used as an aid in later processing.

Nowadays, the accuracy of speech processing systems is strongly affected by acoustic noise. This is a serious obstacle regarding the demands of modern applications. Therefore, these systems often need a noise reduction algorithm working in combination with a precise voice activity detector (VAD). The computation needed to achieve denoising and speech detection must not exceed the limitations imposed by real time speech processing systems. This paper presents a novel VAD for improving speech detection robustness in noisy environments and the performance of speech recognition systems in real time applications. The algorithm is based on a Multivariate Complex Gaussian (MCG) observation model and defines an optimal likelihood ratio test (LRT) involving multiple and correlated observations (MCO) based on a jointly Gaussian probability distribution (jGpdf) and a symmetric covariance matrix. The complete derivation of the jGpdf-LRT for the general case of a symmetric covariance matrix is shown in terms of the Cholesky decomposition which allows to efficiently compute the VAD decision rule. An extensive analysis of the proposed methodology for a low dimensional observation model demonstrates: (i) the improved robustness of the proposed approach by means of a clear reduction of the classification error as the number of observations is increased, and (ii) the trade-off between the number of observations and the detection performance. The proposed strategy is also compared to different VAD methods including the G.729, AMR and AFE standards, as well as other recently reported algorithms showing a sustained advantage in speech/non-speech detection accuracy and speech recognition performance using the AURORA databases.

We present a quantitative discussion of the acoustic transmission line theory pertaining to experimental results from a resonant photoacoustic cell excited in its first longitudinal mode. Window absorption is optimally suppressed by buffer volumes and tunable air columns. The acoustic behavior of an ultrasensitive one inch condenser microphone is quantitatively described. A small and sensitive photoacoustic cell has been developed for intracavity use in a CO2 waveguide laser permitting measurements of ethylene down to 6 pptv (long term stability 20 pptv) with a time response of 2 s at a trace gas flow of 6 1/h. To demonstrate the fast time response within a biological application the instant ethylene release of a single tomato is measured.

The study determines the behavior type of the parallel-series amplifier and determines the amplification of the basic amplifier, the input and output resistance, as well as the amplification of the reaction network and the input and output resistance of the reaction network. With the help of the negative reaction, the designer can change the properties of the amplifier. Thus, a dynamic, automatic stability of the amplification system is obtained.

The study determines the behavior type of the parallel-series amplifier and determines the amplification of the basic amplifier, the input and output resistance, as well as the amplification of the reaction network and the input and output resistance of the reaction network. With the help of the negative reaction, the designer can change the properties of the amplifier. Thus, a dynamic, automatic stability of the amplification system is obtained.

In this research paper, various performances of five different rotor pole topologies of the proposed novel modular stator (MS) permanent magnet (PM) flux reversal machine were investigated. The proposed design had concentrated, non-overlapping winding, which offered high average torque capability at a wide speed range. The no-load performances such as coil test analysis, three-phase flux linkage, flux distribution, back-EMF, and cogging torque, and load analysis, such as average torque versus current density, instantaneous torque, and average electromagnetic torque, were compared. The PM modular stator machine had high cogging torque, which created vibration and noise in the machine. Different cogging torque reduction techniques, such as notching, arc, flange and hybrid technique arc flange, arc notch, notch flange, and arc notch flange, were applied to reduce the cogging torque, improve average load torque, and reduce the induced voltage, harmonics, and torque ripples. The maximum ...

We address a problem of speech enhancement: recovering a speech source from a mixture of its delayed versions and additive noise. By using the constrained-optimization technique, the second order statistics based algorithm is developed. The new proposed algorithm requires no strong limitations to the speech signal and the noise. Simulation results show that our algorithm achieves a better performance as compared to other algorithms.

We show that the intriguing observation of noise enhancement in the charge transport through two vertically coupled quantum dots can be explained by the interplay of quantum coherence and strong Coulomb blockade. We demonstrate that this novel mechanism for super-Poissonian charge transfer is very sensitive to decoherence caused by electron-phonon scattering as inferred from the measured temperature dependence.

HAL is a multi-disciplinary open access archive for the deposit and dissemination of scientific research documents, whether they are published or not. The documents may come from teaching and research institutions in France or abroad, or from public or private research centers. L'archive ouverte pluridisciplinaire HAL, est destinée au dépôt et à la diffusion de documents scientifiques de niveau recherche, publiés ou non, émanant des établissements d'enseignement et de recherche français ou étrangers, des laboratoires publics ou privés.

A binaural complex consisting of two dichotically presented tones close in frequency will have a pitch different from that of either component presented monaurally. The object of the present experiment was to study the pitch of the binaural complex as a function of both interaural intensity difference and the bandwidth of one of the dichotic components. The dichotic stimulus consisted of a 100-ms burst of narrow-band noise centered at 1700 Hz and of a simultaneous, 100-ms pure tone having its frequency fixed either at 1650 or 1750 Hz. Using a modified Method-of-Adjustments procedure, the listeners matched the pitch of various dichotic tone-noise complexes to that of a binaural tone of variable frequency. Results indicate that the effective bandwidth of the monaural components contributing to the pitch of such complexes corresponds to that of the Critical Band. Relevance of the data to a central pitch processor theory will be discussed. [Work supported by the Veterans Administration.]

Experienced observers were asked to identify, in a four-level 2AFC situation, the longer of two unfilled time intervals, each of which was marked by a pair of 20-msec acoustic pulses. When all the markers were identical, high-level (86-dB SPL) bursts of coherently gated sinusoids or bursts of band-limited Gaussian noise, a change in the spectrum of the markers generally did not affect performance. On the other hand, for I-kHz tone-burst markers, intensity decreases below 25 dB SL were accompanied by sizable deterioration of the discrimination performance, especially at short (25-msec) base intervals. Similarly large changes in performance were observed also when the two tonal markers of each interval were made very dissimilar from each other, either in frequency (frequency difference larger than 1 octave) or in intensity (level of the first marker at least 45 dB below the level of the second marker). Time-difference thresholds in these two latter cases were found to be nonmonotonically related to the base interval, the minima occurring between 40-and 80-msec onset separations.

This paper presents an optimal method for rotordynamic simulation of induction motors, including the effects of unbalanced magnetic pull (UMP). The developed simulation method containing the UMP model is simple but still accurate for the actual design process of induction motors. The UMP model is simplified by using the magnetizing current without calculation of the rotor current. The effects of the slot opening and saturation are initially incorporated into the model by using the Carter factor. To improve the accuracy of the model, the magnetizing current is calculated by the finite element analysis (FEA), and the proposed correction factor is also built into the model. Moreover, mixed eccentricity is modeled and applied to the time step rotordynamic simulation for considering the actual rotor eccentricity condition. Based on the developed UMP and eccentricity models, rotordynamic simulation methods within the induction motor design process are proposed and tested in a standard four-pole induction motor. The simulation results show that inclusion of the UMP force reduces the critical speeds and generates electromagnetic excitation. The study further shows that the effects of UMP vary with a change in static eccentricity, dynamic eccentricity, slip, and bearing stiffness. Finally, based on the results, a utilization plan of the developed methods is proposed. Induction motor, mixed eccentricity, rotordynamics, unbalanced magnetic pull. NOMENCLATURE B δ Air-gap magnetic flux density. C Damping matrix. c Correction factor. e dy Amplitude of dynamic eccentricity. e mix Amplitude of mixed eccentricity. e st Amplitude of static eccentricity. F Magnetomotive force. F g Gravity force matrix. F ub Unbalance force matrix. F ump UMP force matrix. F x Net UMP force in horizontal direction. F y Net UMP force in vertical direction. Gyroscopic matrix. The associate editor coordinating the review of this manuscript and approving it for publication was Xiaodong Sun . x 1 -y 1 Stator reference coordinate system. x 2 -y 2 Reference coordinate system with the bearing center as origin. y st y coordinate of static eccentricity. α Circumferential location of the air gap on the rotor surface. δ Air-gap length. δ 0 Mean air-gap length. δ 0 Equivalent mean air-gap length. δ 0 Equivalent mean air-gap length multiplied by correction factor. ε mix Relative mixed eccentricity. θ dy Direction angle of dynamic eccentricity. θ mix Direction angle of mixed eccentricity. θ st Direction angle of static eccentricity. Air-gap permeance. µ 0 Air permeance. v Harmonic order. Rotor angular velocity. n First critical speed of the rotor. ω Electric angular velocity.

Ambient noise suppression in a reverberant room is usually performed by the microphone array. The adaptive beamforming, whose typical representative is minimum variance distortionless (MVDR) beamformer, is an effective method for noise suppression. However, MVDR beamformer gives poor results in the real room because of its sensitivity to the steering error and the multipath wave propagation. In this paper we propose a noise suppression method based on assumption that the positions of the speakers in the reverberant room are roughly known. Noise reduction is realized by two MVDR beamformers directed toward each of the speakers. Adaptation of the MVDR beamformers are controlled by a speaker activity detector which decision is based on power transfer model of the multiple superdirective beamformers in combined diffuse and coherent noise field. The proposed voice activity detector also provides residual noise reduction. The proposed method and its robustness to steering error were tested on the model of simulated room as well as in real room environment. The improvement of the restored speech signal was evaluated by Signal to Noise Ratio Enhancement (SNRE) and by Perceptual evaluation of speech quality (PESQ) measure.

Noise is one of the major challenges in the development of robust automatic speech recognition (ASR) System. There are several speech enhancement techniques available to reduce the effect of noise from speech signals. In this paper, a statistical analysis is presented on the impact of speech enhancement techniques on the feature vectors of noisy speech signals by estimating Bhattacharya distances (BD) from the feature vectors of approximately noise free training speech signals to the feature vectors of noisy testing speech signals. Here Sub-band Spectral Subtraction (SSS) and Frame Selection (FS) have been used as speech enhancement techniques at signal level and Cepstral Mean Normalization (CMN) has been used as feature normalization technique at feature level. In this research work, combination of Mel-Frequency Cepstral Coefficients (MFCC), Log energies, first time derivatives and second time derivatives of MFCCs and Log energies has been used as speech feature vectors. Speech rec...

The Active Noise Controller (ANC) system described here implements a practical design that significantly decreases background noise of signals common to most portable audio devices. This is achieved by a mixture of conventional ANC blocks with less traditional implementations, including a combined FIR/IIR structure using switched-capacitor blocks such as summers, integrators, multipliers, and delays. The proposed design also works as a stand-alone system and it has been successfully implemented on a 1.2-m CMOS technology.

A major problem associated with the use of functional magnetic resonance imaging (fMRI) is the attendant gradient noise, which causes undesirable auditory system stimulation. A method is presented here that delays data acquisition to a period immediately after task completion, utilizing the physiological delay and dispersion between neuronal activity and its resulting hemodynamic lag. Subjects performed finger movements with the gradients off, followed by a rest period with the gradients on. This resulted in task-related signals comparable to those obtained with concurrent task performance and image data acquisition. This behavior interleaved gradients technique may be particularly useful for the studies involving auditory stimulation or overt verbal responses. Magn Reson Med 41:13

This paper proposes a technique for reducing torque ripples and speed control of switched reluctance motor (SRM) using artificial intelligence. The controller of SRM is developed based on a fuzzy logic controller using MATLAB/Simulink software. Fuzzy logic controller overcomes the nonlinearity and uncertainty of the SRM. The proposed controller is used for predicting torque ripples and speed control profiles. The machine performance using the proposed controller is compared with using a traditional PI controller. In addition, comparison of motor performance with and without the use of proposed controllers is highlighted. The motor performance is evaluated using the suggested different controllers. The simulation results show that the proposed method indicates a 65% to 75% reduction in torque ripples compared to the traditional PI method.

This paper describes a series of related research and software projects in the analysis and synthesis of stochastic sounds in general, and more specifically, applications in the synthesis of environmental sounds. Analysis and synthesis of sounds as varied as a maraca (many beans bouncing around in a gourd), to groups of noise-making animals and insects, to human applause will be covered. Specific open-source project software will be described, such as the "Shakers" and "Flox" classes in the Synthesis ToolKit in C++ (STK), GaitLab (analysis and synthesis of walking sounds), ClapLab and ClaPD (synthesis of applause), TAPESTREA (Techniques and Paradigms for Expressive Synthesis and Transformation of Environmental Audio), and the new audio programming language ChucK.

Cavitationlike bubble collapses and the bursting of floating bubbles have been proposed in the literature as sources of oceanic ambient noise at kilohertz frequencies. The first process is shown to be physically impossible in the oceanic environment. The noise produced by the second mechanism is estimated and shown to be too weak to be of any significance.

A simulation study is conducted to demonstrate in principle that time reversal processing can be used to locate sound sources in an outdoor urban area with many buildings. Acoustic pulse propagation in this environment is simulated using a two-dimensional finite difference time domain (FDTD) computation. Using the simulated time traces from only a few sensors and back propagating them with the FDTD model, the sound energy refocuses in the vicinity of the true source location. This time reversal numerical experiment confirms that using information acquired only at non-line-of-sight locations is sufficient to obtain accurate source locations in a complex urban terrain.

Prior research has shown that articulatory information, if extracted properly from the speech signal, can improve the performance of automatic speech recognition systems. However, such information is not readily available in the signal. The challenge posed by the estimation of articulatory information from speech acoustics has led to a new line of research known as "acoustic-to-articulatory inversion" or "speech-inversion." While most of the research in this area has focused on estimating articulatory information more accurately, few have explored ways to apply this information in speech recognition tasks. In this paper, we first estimated articulatory information in the form of vocal tract constriction variables (abbreviated as TVs) from the Aurora-2 speech corpus using a neural network based speech-inversion model. Word recognition tasks were then performed for both noisy and clean speech using articulatory information in conjunction with traditional acoustic features. Our results indicate that incorporating TVs can significantly improve word recognition rates when used in conjunction with traditional acoustic features.

In this paper the algorithm of signal detection by means passive acoustics and digital data processing is proposed. This algorithm is original and contains the processing of signals, which are received by several acoustic aerials. For signal detection the calculation of wide-band ambiguity function together with its projection on time axis are used. All the calculations are executed with the real signals. As the result the location of the aircraft on Cartesian coordinate plane is observed. The suggested algorithm is also proposed to use for measuring of aircraft noise with the aim of environmental protection.

Ocean noise is characterized by both temporal and specpg 134tral properties. Time-domain statistics are often non-Gaussian, and spectra are typically non-white. Both attributes can be simulated at the same time by applying a spectral shaping filter to random numbers having a specified kurtosis. A method for generating random numbers with arbitrary kurtosis is presented.

Conventional blood oxygenation level-dependent (BOLD) based functional magnetic resonance imaging (fMRI) is accompanied by substantial acoustic gradient noise. This noise can influence the performance as well as neuronal activations. Conventional fMRI typically has a pulsed noise component, which is a particularly efficient auditory stimulus. We investigated whether the elimination of this pulsed noise component in a recent modification of continuous-sound fMRI modifies neuronal activations in a cognitively demanding non-auditory working memory task. Sixteen normal subjects performed a letter variant n-back task. Brain activity and psychomotor performance was examined during fMRI with continuous-sound fMRI and conventional fMRI. We found greater BOLD responses in bilateral medial frontal gyrus, left middle frontal gyrus, left middle temporal gyrus, left hippocampus, right superior frontal gyrus, right precuneus and right cingulate gyrus with continuous-sound compared to conventional fMRI. Conversely, BOLD responses were greater in bilateral cingulate gyrus, left middle and superior frontal gyrus and right lingual gyrus with conventional compared to continuous-sound fMRI. There were no differences in psychomotor performance between both scanning protocols. Although behavioral performance was not affected, acoustic gradient noise interferes with neuronal activations in non-auditory cognitive tasks and represents a putative systematic confound.

Conventional blood oxygenation level-dependent (BOLD) based functional magnetic resonance imaging (fMRI) is accompanied by substantial acoustic gradient noise. This noise can influence the performance as well as neuronal activations. Conventional fMRI typically has a pulsed noise component, which is a particularly efficient auditory stimulus. We investigated whether the elimination of this pulsed noise component in a recent modification of continuous-sound fMRI modifies neuronal activations in a cognitively demanding non-auditory working memory task. Sixteen normal subjects performed a letter variant n-back task. Brain activity and psychomotor performance was examined during fMRI with continuous-sound fMRI and conventional fMRI. We found greater BOLD responses in bilateral medial frontal gyrus, left middle frontal gyrus, left middle temporal gyrus, left hippocampus, right superior frontal gyrus, right precuneus and right cingulate gyrus with continuous-sound compared to conventional fMRI. Conversely, BOLD responses were greater in bilateral cingulate gyrus, left middle and superior frontal gyrus and right lingual gyrus with conventional compared to continuous-sound fMRI. There were no differences in psychomotor performance between both scanning protocols. Although behavioral performance was not affected, acoustic gradient noise interferes with neuronal activations in non-auditory cognitive tasks and represents a putative systematic confound.

Computational aeroacoustics (CAA) has emerged as a tool to complement theoretical and experimental approaches for robust and accurate prediction of sound levels from aircraft airframes and engines. CAA, unlike computational fluid dynamics (CFD), involves the accurate prediction of smallamplitude acoustic fluctuations and their correct propagation to the far field. In that respect, CAA poses significant challenges for researchers because the computational scheme should have high accuracy, good spectral resolution, and low dispersion and diffusion errors. A high-order compact finite difference scheme, which is implicit in space, can be used for such simulations because it fulfills the requirements for CAA. Usually, this method is parallelized using a transposition scheme; however, that approach has a high communication overhead. In this paper, we discuss the use of a parallel tridiagonal linear system solver based on the truncated SPIKE algorithm for reducing the communication overhead in our large eddy simulations. We report experimental results collected on two parallel computing platforms.

This paper discusses the performance improvement that a neural network can provide to a contactless distance sensor based on the measurement of the time of flight (TOF) of an ultrasonic (US) pulse. The sensor, which embeds a correction system for the temperature effect, achieves a distance uncertainty (rms) of less than 0.5 mm over 0.5 m by using a two-level neural network to process the US echo and determine the TOF in the presence of environmental acoustic noise. The network embeds a "guard" neuron that guards against gross measurement errors, which would be possible in the presence of high environmental noise.

This paper discusses the performance improvement that a neural network can provide to a contactless distance sensor based on the measurement of the time of flight (TOF) of an ultrasonic (US) pulse. The sensor, which embeds a correction system for the temperature effect, achieves a distance uncertainty (rms) of less than 0.5 mm over 0.5 m by using a two-level neural network to process the US echo and determine the TOF in the presence of environmental acoustic noise. The network embeds a "guard" neuron that guards against gross measurement errors, which would be possible in the presence of high environmental noise.

This paper presents a maximum likelihood (ML) approach, concerned to the background model estimation, in noisy acoustic non-stationary environments. The external noise source is characterised by a time constant convolutional and a time varying additive components. The HMM composition technique, provides a mechanism for integrating parametric models of acoustic background with the signal model, so that noise compensation is tightly coupled with the background model estimation. However, the existing continuous adaptation algorithms usually do not take advantage of this approach, being essentially based on the MLLR algorithm. Consequently, a model for environmental mismatch is not available and, even under constrained conditions a significant number of model parameters have to be updated. From a theoretical point of view only the noise model parameters need to be updated, being the clean speech ones unchanged by the environment. So, it can be advantageous to have a model for environmental mismatch. Additionally separating the additive and convolutional components means a separation between the environmental mismatch and speaker mismatch when the channel does not change for long periods. This approach was followed in the development of the algorithm proposed in this paper. One drawback sometimes attributed to the continuous adaptation approach is that recognition failures originate poor background estimates. This paper also proposes a MAP-like method to deal with this situation.

An automated approach to degradation analysis is proposed that uses a rotating machine's acoustic signal to determine Remaining Useful Life (RUL). High resolution spectral features are extracted from the acoustic data collected over the entire lifetime of the machine. A novel approach to the computation of Mutual Information based Feature Subset Selection is applied, to remove redundant and irrelevant features, that does not require class label boundaries of the dataset or spectral locations of developing defect to be known or pre-estimated. Using subsets of the feature space, multi-class linear and Radial Basis Function (RBF) Support Vector Machine (SVM) classifiers are developed and a comparison of their performance is provided. Performance of all classifiers is found to be very high, 85 to 98%, with RBF SVMs outperforming linear SVMs when a smaller number of features are used. As larger numbers of features are used for classification, the problem space becomes more linearly separable and the linear SVMs are shown to have comparable performance. A detailed analysis of the misclassifications is provided and an approach to better understand and interpret costly misclassifications is discussed. While defining class label boundaries using an automated k-means clustering algorithm improves performance with an accuracy of approximately 99%, further analysis shows that in 88% of all misclassifications the actual class of failure had the next highest probability of occurring. Thus, a system that incorporates probability distributions as a measure of confidence for the predicted RUL would provide additional valuable information for scheduling preventative maintenance.

A vector hydrophone is composed of two or three spatially collocated but orthogonally oriented velocity hydrophones plus an optional collocated pressure hydrophone. A vector hydrophone may form azimuth-elevation beams that are invariant with respect to the sources' frequencies, bandwidths and radial location (in near field as opposed to the far field). This paper characterizes the spatial matched filter beam patterns (a.k.a. fixed or conventional or maximum signal-to-noise ratio beam patterns) and the minimum variance distortionless response (MVDR) beam patterns associated with a single underwater acoustic vector hydrophone distant from any reflecting boundary.

The present paper described the onset cavitation conditions, acoustic noise characteristics and void behaviors of flowing liquid sodium in the venturi made of 316 SS with an inner diameter of 6.5 mm and a length of 20 mm. An experiment was conducted in the range of sodium stagnant pressure in the expansion tank of 0.061-0.181 MPa-a and in the temperature range of 200°-400°C. As a result, it was found that the noise intensity increased greatly when the cavitation coefficient approached unity (onset of cavitation), and it became saturated in lower cavitation coefficient (developed cavitation). The cavitation coefficient at the onset of cavitation was nearly equal to unity. However, an increase in temperature shifted the cavitation coefficient to a value a little higher than unity. The results also showed that velocity in the venturi at the onset of cavitation also increased by increasing the stagnant pressure. Cavitation occurrence produced a noise in the range of 600-20,480 Hz. In developed cavitation condition, the noise intensity was nearly constant at around -50 dB which might be caused by the choking of the fluid. At 400°C, instabilities or fluctuations of the noise spectrums were observed. Simulated results by using CFD showed that voids were formed at the throat of the venturi and the void fraction increased as the static pressure decreased by the flow. The voids were conveyed and collapsed in the downstream of the venturi outlet because of an increase in the static pressure. These voids could cause choking and noise as well as erosion.

This paper addresses the problem of enhancing video service quality for Mobile Ad Hoc Networks (MANET) scenarios. We offer Multipath Optimized Link State (MP-OLSR) routing protocol for H.264/SVC bitstream forwarding in the MANET network. Besides the usage of a suitable routing protocol, the video quality can be further enhanced by using the scalable encoding feature of Scalable Video Coding (SVC) combined with Unequal Error Protection (UEP). SVC is an extension of the H.264/AVC video compression standard used for high-quality video bitstreams encoding, providing spatial, temporal and quality scalability. To evaluate video quality, the Video Quality Metric (VQM) is used. We chose 5 different video contents for our simulations characterized by various temporal and spatial complexities. These video references are taken from the Video Quality Expert Group (VQEG). The results show that multipath routing combined with UEP can effectively improve the quality of video communication over MANET in terms of VQM and successful video decoding.

Laser doppler velocity measurements of gaseous mixing induced by Richtmyer-Meshkov instability JEAN-FRANCOIS HAAS, Commissariat à l'Energie Atomique, DENIS COUNILH -The turbulent mixing of air and SF6 arising from the Richtmyer-Meskov instability is investigated in a shock tube using Schlieren or laser sheet visualization and laser-doppler velocimetry. The shock tube driver, driven and observation sections are 100, 306 and 25 or 30 cm long respectively. The shock tube cross section is 13 by 13 cm square throughout. Initially, the driven and observation sections are filled with air and SF6 at 1 bar and the driver with air at 3.2 bars in order to generate a Mach 1.2 shock wave. Air and SF6 are initially separated with a thin (1 µm) microcellulose membrane maintained in a plane parallel to the shock by two thin metallic grids, of square mesh spacing 1.8 mm (downstream) and 1.0 mm (upstream). After interaction leading to a Mach 1.3 shock transmitted in SF6, an RMI-induced mixing zone moving at 70 m/s develops to an asymptotic thickness of 1 cm. When the Mach 1.3 reflected shock slows down the flow to -20 m/s, the mixing zone rapidly thickens up to 4 cm when the second reflected (expansion) wave reverses the flow again to 10 m/s. The growth rate is faster for the 30 cm observation section. A two-component laser-doppler velocimeter is used to probe the turbulent velocity field for the 25 cm section. The time evolution of the turbulent kinetic energy at several locations is obtained from many superimposed measurements of the axial and transversal velocities.