Sample records for noise robust automatic

  1. Noise robust automatic speech recognition with adaptive quantile based noise estimation and speech band emphasizing filter bank

    DEFF Research Database (Denmark)

    Bonde, Casper Stork; Graversen, Carina; Gregersen, Andreas Gregers


    An important topic in Automatic Speech Recognition (ASR) is to reduce the effect of noise, in particular when mismatch exists between the training and application conditions. Many noise robutness schemes within the feature processing domain use as a prerequisite a noise estimate prior to the appe......An important topic in Automatic Speech Recognition (ASR) is to reduce the effect of noise, in particular when mismatch exists between the training and application conditions. Many noise robutness schemes within the feature processing domain use as a prerequisite a noise estimate prior....... Furthermore the paper investigates an alternative to the standard mel frequency cepstral coefficient filter bank (MFCC), an empirically chosen Speech Band Emphasizing filter bank (SBE), which improves the resolution in the speech band. The combinations of AQBNE and SBE are tested on the Danish SpeechDat-Car...

  2. Noise robust automatic speech recognition with adaptive quantile based noise estimation and speech band emphasizing filter bank

    DEFF Research Database (Denmark)

    Bonde, Casper Stork; Graversen, Carina; Gregersen, Andreas Gregers


    to the appearance of the speech signal which require noise robust voice activity detection and assumptions of stationary noise. However, both of these requirements are often not met and it is therefore of particular interest to investigate methods like the Quantile Based Noise Estimation (QBNE) mehtod which...... estimates the noise during speech and non-speech sections without the use of a voice activity detector. While the standard QBNE-method uses a fixed pre-defined quantile accross all frequency bands, this paper suggests adaptive QBNE (AQBNE) which adapts the quantile individually to each frequency band...

  3. Robust automatic camera pointing for airborne surveillance (United States)

    Dwyer, David; Wren, Lee; Thornton, John; Bonsor, Nigel


    Airborne electro-optic surveillance from a moving platform currently requires regular interaction from a trained operator. Even simple tasks such as fixating on a static point on the ground can demand constant adjustment of the camera orientation to compensate for platform motion. In order to free up operator time for other tasks such as navigation and communication with ground assets, an automatic gaze control system is needed. This paper describes such a system, based purely on tracking points within the video image. A number of scene points are automatically selected and their inter-frame motion tracked. The scene motion is then estimated using a model of a planar projective transform. For reliable and accurate camera pointing, the modeling of the scene motion must be robust to common problems such as scene point obscuration, objects moving independently within the scene and image noise. This paper details a COTS based system for automatic camera fixation and describes ways of preventing objects moving in the scene or poor motion estimates from corrupting the scene motion model.

  4. Automatic Synthesis of Robust and Optimal Controllers

    DEFF Research Database (Denmark)

    Cassez, Franck; Jessen, Jan Jacob; Larsen, Kim Guldstrand


    In this paper, we show how to apply recent tools for the automatic synthesis of robust and near-optimal controllers for a real industrial case study. We show how to use three different classes of models and their supporting existing tools, Uppaal-TiGA for synthesis, phaver for verification...

  5. Automatic Mode Transition Enabled Robust Triboelectric Nanogenerators. (United States)

    Chen, Jun; Yang, Jin; Guo, Hengyu; Li, Zhaoling; Zheng, Li; Su, Yuanjie; Wen, Zhen; Fan, Xing; Wang, Zhong Lin


    Although the triboelectric nanogenerator (TENG) has been proven to be a renewable and effective route for ambient energy harvesting, its robustness remains a great challenge due to the requirement of surface friction for a decent output, especially for the in-plane sliding mode TENG. Here, we present a rationally designed TENG for achieving a high output performance without compromising the device robustness by, first, converting the in-plane sliding electrification into a contact separation working mode and, second, creating an automatic transition between a contact working state and a noncontact working state. The magnet-assisted automatic transition triboelectric nanogenerator (AT-TENG) was demonstrated to effectively harness various ambient rotational motions to generate electricity with greatly improved device robustness. At a wind speed of 6.5 m/s or a water flow rate of 5.5 L/min, the harvested energy was capable of lighting up 24 spot lights (0.6 W each) simultaneously and charging a capacitor to greater than 120 V in 60 s. Furthermore, due to the rational structural design and unique output characteristics, the AT-TENG was not only capable of harvesting energy from natural bicycling and car motion but also acting as a self-powered speedometer with ultrahigh accuracy. Given such features as structural simplicity, easy fabrication, low cost, wide applicability even in a harsh environment, and high output performance with superior device robustness, the AT-TENG renders an effective and practical approach for ambient mechanical energy harvesting as well as self-powered active sensing.

  6. Unsupervised modulation filter learning for noise-robust speech recognition. (United States)

    Agrawal, Purvi; Ganapathy, Sriram


    The modulation filtering approach to robust automatic speech recognition (ASR) is based on enhancing perceptually relevant regions of the modulation spectrum while suppressing the regions susceptible to noise. In this paper, a data-driven unsupervised modulation filter learning scheme is proposed using convolutional restricted Boltzmann machine. The initial filter is learned using the speech spectrogram while subsequent filters are learned using residual spectrograms. The modulation filtered spectrograms are used for ASR experiments on noisy and reverberant speech where these features provide significant improvements over other robust features. Furthermore, the application of the proposed method for semi-supervised learning is investigated.

  7. Robust Subspace Clustering With Complex Noise. (United States)

    He, Ran; Zhang, Yingya; Sun, Zhenan; Yin, Qiyue


    Subspace clustering has important and wide applications in computer vision and pattern recognition. It is a challenging task to learn low-dimensional subspace structures due to complex noise existing in high-dimensional data. Complex noise has much more complex statistical structures, and is neither Gaussian nor Laplacian noise. Recent subspace clustering methods usually assume a sparse representation of the errors incurred by noise and correct these errors iteratively. However, large corruptions incurred by complex noise cannot be well addressed by these methods. A novel optimization model for robust subspace clustering is proposed in this paper. Its objective function mainly includes two parts. The first part aims to achieve a sparse representation of each high-dimensional data point with other data points. The second part aims to maximize the correntropy between a given data point and its low-dimensional representation with other points. Correntropy is a robust measure so that the influence of large corruptions on subspace clustering can be greatly suppressed. An extension of pairwise link constraints is also proposed as prior information to deal with complex noise. Half-quadratic minimization is provided as an efficient solution to the proposed robust subspace clustering formulations. Experimental results on three commonly used data sets show that our method outperforms state-of-the-art subspace clustering methods.

  8. Robust, accurate and fast automatic segmentation of the spinal cord. (United States)

    De Leener, Benjamin; Kadoury, Samuel; Cohen-Adad, Julien


    Spinal cord segmentation provides measures of atrophy and facilitates group analysis via inter-subject correspondence. Automatizing this procedure enables studies with large throughput and minimizes user bias. Although several automatic segmentation methods exist, they are often restricted in terms of image contrast and field-of-view. This paper presents a new automatic segmentation method (PropSeg) optimized for robustness, accuracy and speed. The algorithm is based on the propagation of a deformable model and is divided into three parts: firstly, an initialization step detects the spinal cord position and orientation using a circular Hough transform on multiple axial slices rostral and caudal to the starting plane and builds an initial elliptical tubular mesh. Secondly, a low-resolution deformable model is propagated along the spinal cord. To deal with highly variable contrast levels between the spinal cord and the cerebrospinal fluid, the deformation is coupled with a local contrast-to-noise adaptation at each iteration. Thirdly, a refinement process and a global deformation are applied on the propagated mesh to provide an accurate segmentation of the spinal cord. Validation was performed in 15 healthy subjects and two patients with spinal cord injury, using T1- and T2-weighted images of the entire spinal cord and on multiecho T2*-weighted images. Our method was compared against manual segmentation and against an active surface method. Results show high precision for all the MR sequences. Dice coefficients were 0.9 for the T1- and T2-weighted cohorts and 0.86 for the T2*-weighted images. The proposed method runs in less than 1min on a normal computer and can be used to quantify morphological features such as cross-sectional area along the whole spinal cord. Copyright © 2014 Elsevier Inc. All rights reserved.

  9. Robust parameter design for automatically controlled systems and nanostructure synthesis (United States)

    Dasgupta, Tirthankar


    This research focuses on developing comprehensive frameworks for developing robust parameter design methodology for dynamic systems with automatic control and for synthesis of nanostructures. In many automatically controlled dynamic processes, the optimal feedback control law depends on the parameter design solution and vice versa and therefore an integrated approach is necessary. A parameter design methodology in the presence of feedback control is developed for processes of long duration under the assumption that experimental noise factors are uncorrelated over time. Systems that follow a pure-gain dynamic model are considered and the best proportional-integral and minimum mean squared error control strategies are developed by using robust parameter design. The proposed method is illustrated using a simulated example and a case study in a urea packing plant. This idea is also extended to cases with on-line noise factors. The possibility of integrating feedforward control with a minimum mean squared error feedback control scheme is explored. To meet the needs of large scale synthesis of nanostructures, it is critical to systematically find experimental conditions under which the desired nanostructures are synthesized reproducibly, at large quantity and with controlled morphology. The first part of the research in this area focuses on modeling and optimization of existing experimental data. Through a rigorous statistical analysis of experimental data, models linking the probabilities of obtaining specific morphologies to the process variables are developed. A new iterative algorithm for fitting a Multinomial GLM is proposed and used. The optimum process conditions, which maximize the above probabilities and make the synthesis process less sensitive to variations of process variables around set values, are derived from the fitted models using Monte-Carlo simulations. The second part of the research deals with development of an experimental design methodology, tailor

  10. Noise robustness of interferometric surface topography evaluation methods. Correlogram correlation (United States)

    Kiselev, Ilia; Kiselev, Egor I.; Drexel, Michael; Hauptmannl, Michael


    Different surface height estimation methods are differently affected by interferometric noise. From a theoretical analysis we obtain height variance estimators for the methods. The estimations allow us to rigorously compare the noise robustness of popular evaluation algorithms. The envelope methods have the highest variances and hence the lowest noise resistances. The noise robustness improves from the envelope to the phase methods, but a technique involving the correlation of correlograms is superior even to the latter. We dwell on some details of this correlogram correlation method and the range of its application.

  11. A Noise Robust Statistical Texture Model

    DEFF Research Database (Denmark)

    Hilger, Klaus Baggesen; Stegmann, Mikkel Bille; Larsen, Rasmus


    This paper presents a novel approach to the problem of obtaining a low dimensional representation of texture (pixel intensity) variation present in a training set after alignment using a Generalised Procrustes analysis.We extend the conventional analysis of training textures in the Active...... Appearance Models segmentation framework. This is accomplished by augmenting the model with an estimate of the covariance of the noise present in the training data. This results in a more compact model maximising the signal-to-noise ratio, thus favouring subspaces rich on signal, but low on noise....... Differences in the methods are illustrated on a set of left cardiac ventricles obtained using magnetic resonance imaging....

  12. Robust Automatic Speech Recognition Features using Complex Wavelet Packet Transform Coefficients

    Directory of Open Access Journals (Sweden)

    Tjong Wan Sen


    Full Text Available To improve the performance of phoneme based Automatic Speech Recognition (ASR in noisy environment; we developed a new technique that could add robustness to clean phonemes features. These robust features are obtained from Complex Wavelet Packet Transform (CWPT coefficients. Since the CWPT coefficients represent all different frequency bands of the input signal, decomposing the input signal into complete CWPT tree would also cover all frequencies involved in recognition process. For time overlapping signals with different frequency contents, e. g. phoneme signal with noises, its CWPT coefficients are the combination of CWPT coefficients of phoneme signal and CWPT coefficients of noises. The CWPT coefficients of phonemes signal would be changed according to frequency components contained in noises. Since the numbers of phonemes in every language are relatively small (limited and already well known, one could easily derive principal component vectors from clean training dataset using Principal Component Analysis (PCA. These principal component vectors could be used then to add robustness and minimize noises effects in testing phase. Simulation results, using Alpha Numeric 4 (AN4 from Carnegie Mellon University and NOISEX-92 examples from Rice University, showed that this new technique could be used as features extractor that improves the robustness of phoneme based ASR systems in various adverse noisy conditions and still preserves the performance in clean environments.

  13. Robust Automatic Speech Recognition Features using Complex Wavelet Packet Transform Coefficients

    Directory of Open Access Journals (Sweden)

    TjongWan Sen


    Full Text Available To improve the performance of phoneme based Automatic Speech Recognition (ASR in noisy environment; we developed a new technique that could add robustness to clean phonemes features. These robust features are obtained from Complex Wavelet Packet Transform (CWPT coefficients. Since the CWPT coefficients represent all different frequency bands of the input signal, decomposing the input signal into complete CWPT tree would also cover all frequencies involved in recognition process. For time overlapping signals with different frequency contents, e. g. phoneme signal with noises, its CWPT coefficients are the combination of CWPT coefficients of phoneme signal and CWPT coefficients of noises. The CWPT coefficients of phonemes signal would be changed according to frequency components contained in noises. Since the numbers of phonemes in every language are relatively small (limited and already well known, one could easily derive principal component vectors from clean training dataset using Principal Component Analysis (PCA. These principal component vectors could be used then to add robustness and minimize noises effects in testing phase. Simulation results, using Alpha Numeric 4 (AN4 from Carnegie Mellon University and NOISEX-92 examples from Rice University, showed that this new technique could be used as features extractor that improves the robustness of phoneme based ASR systems in various adverse noisy conditions and still preserves the performance in clean environments.

  14. Light field reconstruction robust to signal dependent noise (United States)

    Ren, Kun; Bian, Liheng; Suo, Jinli; Dai, Qionghai


    Capturing four dimensional light field data sequentially using a coded aperture camera is an effective approach but suffers from low signal noise ratio. Although multiplexing can help raise the acquisition quality, noise is still a big issue especially for fast acquisition. To address this problem, this paper proposes a noise robust light field reconstruction method. Firstly, scene dependent noise model is studied and incorporated into the light field reconstruction framework. Then, we derive an optimization algorithm for the final reconstruction. We build a prototype by hacking an off-the-shelf camera for data capturing and prove the concept. The effectiveness of this method is validated with experiments on the real captured data.

  15. ADSL Transceivers Applying DSM and Their Nonstationary Noise Robustness

    Directory of Open Access Journals (Sweden)

    Bostoen Tom


    Full Text Available Dynamic spectrum management (DSM comprises a new set of techniques for multiuser power allocation and/or detection in digital subscriber line (DSL networks. At the Alcatel Research and Innovation Labs, we have recently developed a DSM test bed, which allows the performance of DSM algorithms to be evaluated in practice. With this test bed, we have evaluated the performance of a DSM level-1 algorithm known as iterative water-filling in an ADSL scenario. This paper describes the results of, on the one hand, the performance gains achieved with iterative water-filling, and, on the other hand, the nonstationary noise robustness of DSM-enabled ADSL modems. It will be shown that DSM trades off nonstationary noise robustness for performance improvements. A new bit swap procedure is then introduced to increase the noise robustness when applying DSM.

  16. ADSL Transceivers Applying DSM and Their Nonstationary Noise Robustness (United States)

    den Bogaert, Etienne Van; Bostoen, Tom; Verlinden, Jan; Cendrillon, Raphael; Moonen, Marc


    Dynamic spectrum management (DSM) comprises a new set of techniques for multiuser power allocation and/or detection in digital subscriber line (DSL) networks. At the Alcatel Research and Innovation Labs, we have recently developed a DSM test bed, which allows the performance of DSM algorithms to be evaluated in practice. With this test bed, we have evaluated the performance of a DSM level-1 algorithm known as iterative water-filling in an ADSL scenario. This paper describes the results of, on the one hand, the performance gains achieved with iterative water-filling, and, on the other hand, the nonstationary noise robustness of DSM-enabled ADSL modems. It will be shown that DSM trades off nonstationary noise robustness for performance improvements. A new bit swap procedure is then introduced to increase the noise robustness when applying DSM.

  17. Robust image authentication in the presence of noise

    CERN Document Server


    This book addresses the problems that hinder image authentication in the presence of noise. It considers the advantages and disadvantages of existing algorithms for image authentication and shows new approaches and solutions for robust image authentication. The state of the art algorithms are compared and, furthermore, innovative approaches and algorithms are introduced. The introduced algorithms are applied to improve image authentication, watermarking and biometry.    Aside from presenting new directions and algorithms for robust image authentication in the presence of noise, as well as image correction, this book also:   Provides an overview of the state of the art algorithms for image authentication in the presence of noise and modifications, as well as a comparison of these algorithms, Presents novel algorithms for robust image authentication, whereby the image is tried to be corrected and authenticated, Examines different views for the solution of problems connected to image authentication in the pre...

  18. A Review of Signal Subspace Speech Enhancement and Its Application to Noise Robust Speech Recognition

    Directory of Open Access Journals (Sweden)

    Hermus Kris


    Full Text Available The objective of this paper is threefold: (1 to provide an extensive review of signal subspace speech enhancement, (2 to derive an upper bound for the performance of these techniques, and (3 to present a comprehensive study of the potential of subspace filtering to increase the robustness of automatic speech recognisers against stationary additive noise distortions. Subspace filtering methods are based on the orthogonal decomposition of the noisy speech observation space into a signal subspace and a noise subspace. This decomposition is possible under the assumption of a low-rank model for speech, and on the availability of an estimate of the noise correlation matrix. We present an extensive overview of the available estimators, and derive a theoretical estimator to experimentally assess an upper bound to the performance that can be achieved by any subspace-based method. Automatic speech recognition experiments with noisy data demonstrate that subspace-based speech enhancement can significantly increase the robustness of these systems in additive coloured noise environments. Optimal performance is obtained only if no explicit rank reduction of the noisy Hankel matrix is performed. Although this strategy might increase the level of the residual noise, it reduces the risk of removing essential signal information for the recogniser's back end. Finally, it is also shown that subspace filtering compares favourably to the well-known spectral subtraction technique.

  19. An Automatic Learning-Based Framework for Robust Nucleus Segmentation. (United States)

    Xing, Fuyong; Xie, Yuanpu; Yang, Lin


    Computer-aided image analysis of histopathology specimens could potentially provide support for early detection and improved characterization of diseases such as brain tumor, pancreatic neuroendocrine tumor (NET), and breast cancer. Automated nucleus segmentation is a prerequisite for various quantitative analyses including automatic morphological feature computation. However, it remains to be a challenging problem due to the complex nature of histopathology images. In this paper, we propose a learning-based framework for robust and automatic nucleus segmentation with shape preservation. Given a nucleus image, it begins with a deep convolutional neural network (CNN) model to generate a probability map, on which an iterative region merging approach is performed for shape initializations. Next, a novel segmentation algorithm is exploited to separate individual nuclei combining a robust selection-based sparse shape model and a local repulsive deformable model. One of the significant benefits of the proposed framework is that it is applicable to different staining histopathology images. Due to the feature learning characteristic of the deep CNN and the high level shape prior modeling, the proposed method is general enough to perform well across multiple scenarios. We have tested the proposed algorithm on three large-scale pathology image datasets using a range of different tissue and stain preparations, and the comparative experiments with recent state of the arts demonstrate the superior performance of the proposed approach.

  20. Next Generation Robust Low Noise Seismometer for Nuclear Monitoring

    Energy Technology Data Exchange (ETDEWEB)

    Abramovich, Igor A.


    Implementation of the proposed seismometers turned out to be much more challenging than anticipated. The noise levels achieved are indeed well below those ever featured by any electrochemical sensor and just very nearly miss reaching the original objectives. However, while noise-wise the instruments could still prove their usefulness, especially considering their robustness and no-maintenance operation, the implementation of the proposed noise-reduction concept resulted in much larger and heavier devices than originally expected. Moreover, these large dimensions relate only to single-component vertical sensors. While building similar horizontal component is possible, the resulting three-component instrument would be way too large and heavy to be of any practical use. The prototype instruments developed and built retained the inherent advantages of the electrochemical seismometers: no maintenance operation; ability to perform with large installation tilts; and, unfortunately, to a much lesser extent in terms of robustness.

  1. Robustness analysis of superpixel algorithms to image blur, additive Gaussian noise, and impulse noise (United States)

    Brekhna, Brekhna; Mahmood, Arif; Zhou, Yuanfeng; Zhang, Caiming


    Superpixels have gradually become popular in computer vision and image processing applications. However, no comprehensive study has been performed to evaluate the robustness of superpixel algorithms in regard to common forms of noise in natural images. We evaluated the robustness of 11 recently proposed algorithms to different types of noise. The images were corrupted with various degrees of Gaussian blur, additive white Gaussian noise, and impulse noise that either made the object boundaries weak or added extra information to it. We performed a robustness analysis of simple linear iterative clustering (SLIC), Voronoi Cells (VCells), flooding-based superpixel generation (FCCS), bilateral geodesic distance (Bilateral-G), superpixel via geodesic distance (SSS-G), manifold SLIC (M-SLIC), Turbopixels, superpixels extracted via energy-driven sampling (SEEDS), lazy random walk (LRW), real-time superpixel segmentation by DBSCAN clustering, and video supervoxels using partially absorbing random walks (PARW) algorithms. The evaluation process was carried out both qualitatively and quantitatively. For quantitative performance comparison, we used achievable segmentation accuracy (ASA), compactness, under-segmentation error (USE), and boundary recall (BR) on the Berkeley image database. The results demonstrated that all algorithms suffered performance degradation due to noise. For Gaussian blur, Bilateral-G exhibited optimal results for ASA and USE measures, SLIC yielded optimal compactness, whereas FCCS and DBSCAN remained optimal for BR. For the case of additive Gaussian and impulse noises, FCCS exhibited optimal results for ASA, USE, and BR, whereas Bilateral-G remained a close competitor in ASA and USE for Gaussian noise only. Additionally, Turbopixel demonstrated optimal performance for compactness for both types of noise. Thus, no single algorithm was able to yield optimal results for all three types of noise across all performance measures. Conclusively, to solve real

  2. Robustness of digitally modulated signal features against variation in HF noise model

    Directory of Open Access Journals (Sweden)

    Shoaib Mobien


    Full Text Available Abstract High frequency (HF band has both military and civilian uses. It can be used either as a primary or backup communication link. Automatic modulation classification (AMC is of an utmost importance in this band for the purpose of communications monitoring; e.g., signal intelligence and spectrum management. A widely used method for AMC is based on pattern recognition (PR. Such a method has two main steps: feature extraction and classification. The first step is generally performed in the presence of channel noise. Recent studies show that HF noise could be modeled by Gaussian or bi-kappa distributions, depending on day-time. Therefore, it is anticipated that change in noise model will have impact on features extraction stage. In this article, we investigate the robustness of well known digitally modulated signal features against variation in HF noise. Specifically, we consider temporal time domain (TTD features, higher order cumulants (HOC, and wavelet based features. In addition, we propose new features extracted from the constellation diagram and evaluate their robustness against the change in noise model. This study is targeting 2PSK, 4PSK, 8PSK, 16QAM, 32QAM, and 64QAM modulations, as they are commonly used in HF communications.

  3. Arduino-based noise robust online heart-rate detection. (United States)

    Das, Sangita; Pal, Saurabh; Mitra, Madhuchhanda


    This paper introduces a noise robust real time heart rate detection system from electrocardiogram (ECG) data. An online data acquisition system is developed to collect ECG signals from human subjects. Heart rate is detected using window-based autocorrelation peak localisation technique. A low-cost Arduino UNO board is used to implement the complete automated process. The performance of the system is compared with PC-based heart rate detection technique. Accuracy of the system is validated through simulated noisy ECG data with various levels of signal to noise ratio (SNR). The mean percentage error of detected heart rate is found to be 0.72% for the noisy database with five different noise levels.

  4. ASR Systems in Noisy Environment: Analysis and Solutions for Increasing Noise Robustness

    Directory of Open Access Journals (Sweden)

    J. Rajnoha


    Full Text Available This paper deals with the analysis of Automatic Speech Recognition (ASR suitable for usage within noisy environment and suggests optimum configuration under various noisy conditions. The behavior of standard parameterization techniques was analyzed from the viewpoint of robustness against background noise. It was done for Melfrequency cepstral coefficients (MFCC, Perceptual linear predictive (PLP coefficients, and their modified forms combining main blocks of PLP and MFCC. The second part is devoted to the analysis and contribution of modified techniques containing frequency-domain noise suppression and voice activity detection. The above-mentioned techniques were tested with signals in real noisy environment within Czech digit recognition task and AURORA databases. Finally, the contribution of special VAD selective training and MLLR adaptation of acoustic models were studied for various signal features.

  5. Robust semi-automatic segmentation of single- and multichannel MRI volumes through adaptable class-specific representation (United States)

    Nielsen, Casper F.; Passmore, Peter J.


    Segmentation of MRI volumes is complicated by noise, inhomogeneity and partial volume artefacts. Fully or semi-automatic methods often require time consuming or unintuitive initialization. Adaptable Class-Specific Representation (ACSR) is a semi-automatic segmentation framework implemented by the Path Growing Algorithm (PGA), which reduces artefacts near segment boundaries. The user visually defines the desired segment classes through the selection of class templates and the following segmentation process is fully automatic. Good results have previously been achieved with color cryo section segmentation and ACSR has been developed further for the MRI modality. In this paper we present two optimizations for robust ACSR segmentation of MRI volumes. Automatic template creation based on an initial segmentation step using Learning Vector Quantization is applied for higher robustness to noise. Inhomogeneity correction is added as a pre-processing step, comparing the EQ and N3 algorithms. Results based on simulated T1-weighed and multispectral (T1 and T2) MRI data from the BrainWeb database and real data from the Internet Brain Segmentation Repository are presented. We show that ACSR segmentation compares favorably to previously published results on the same volumes and discuss the pros and cons of using quantitative ground truth evaluation compared to qualitative visual assessment.

  6. Robust Angle Estimation for MIMO Radar with the Coexistence of Mutual Coupling and Colored Noise

    Directory of Open Access Journals (Sweden)

    Junxiang Wang


    Full Text Available This paper deals with joint estimation of direction-of-departure (DOD and direction-of- arrival (DOA in bistatic multiple-input multiple-output (MIMO radar with the coexistence of unknown mutual coupling and spatial colored noise by developing a novel robust covariance tensor-based angle estimation method. In the proposed method, a third-order tensor is firstly formulated for capturing the multidimensional nature of the received data. Then taking advantage of the temporal uncorrelated characteristic of colored noise and the banded complex symmetric Toeplitz structure of the mutual coupling matrices, a novel fourth-order covariance tensor is constructed for eliminating the influence of both spatial colored noise and mutual coupling. After a robust signal subspace estimation is obtained by using the higher-order singular value decomposition (HOSVD technique, the rotational invariance technique is applied to achieve the DODs and DOAs. Compared with the existing HOSVD-based subspace methods, the proposed method can provide superior angle estimation performance and automatically jointly perform the DODs and DOAs. Results from numerical experiments are presented to verify the effectiveness of the proposed method.

  7. A blood pressure monitor with robust noise reduction system under linear cuff inflation and deflation. (United States)

    Usuda, Takashi; Kobayashi, Naoki; Takeda, Sunao; Kotake, Yoshifumi


    We have developed the non-invasive blood pressure monitor which can measure the blood pressure quickly and robustly. This monitor combines two measurement mode: the linear inflation and the linear deflation. On the inflation mode, we realized a faster measurement with rapid inflation rate. On the deflation mode, we realized a robust noise reduction. When there is neither noise nor arrhythmia, the inflation mode incorporated on this monitor provides precise, quick and comfortable measurement. Once the inflation mode fails to calculate appropriate blood pressure due to body movement or arrhythmia, then the monitor switches automatically to the deflation mode and measure blood pressure by using digital signal processing as wavelet analysis, filter bank, filter combined with FFT and Inverse FFT. The inflation mode succeeded 2440 measurements out of 3099 measurements (79%) in an operating room and a rehabilitation room. The new designed blood pressure monitor provides the fastest measurement for patient with normal circulation and robust measurement for patients with body movement or severe arrhythmia. Also this fast measurement method provides comfortableness for patients.

  8. Noise-robust unsupervised spike sorting based on discriminative subspace learning with outlier handling (United States)

    Keshtkaran, Mohammad Reza; Yang, Zhi


    Objective. Spike sorting is a fundamental preprocessing step for many neuroscience studies which rely on the analysis of spike trains. Most of the feature extraction and dimensionality reduction techniques that have been used for spike sorting give a projection subspace which is not necessarily the most discriminative one. Therefore, the clusters which appear inherently separable in some discriminative subspace may overlap if projected using conventional feature extraction approaches leading to a poor sorting accuracy especially when the noise level is high. In this paper, we propose a noise-robust and unsupervised spike sorting algorithm based on learning discriminative spike features for clustering. Approach. The proposed algorithm uses discriminative subspace learning to extract low dimensional and most discriminative features from the spike waveforms and perform clustering with automatic detection of the number of the clusters. The core part of the algorithm involves iterative subspace selection using linear discriminant analysis and clustering using Gaussian mixture model with outlier detection. A statistical test in the discriminative subspace is proposed to automatically detect the number of the clusters. Main results. Comparative results on publicly available simulated and real in vivo datasets demonstrate that our algorithm achieves substantially improved cluster distinction leading to higher sorting accuracy and more reliable detection of clusters which are highly overlapping and not detectable using conventional feature extraction techniques such as principal component analysis or wavelets. Significance. By providing more accurate information about the activity of more number of individual neurons with high robustness to neural noise and outliers, the proposed unsupervised spike sorting algorithm facilitates more detailed and accurate analysis of single- and multi-unit activities in neuroscience and brain machine interface studies.

  9. Noise-robust acoustic signature recognition using nonlinear Hebbian learning. (United States)

    Lu, Bing; Dibazar, Alireza; Berger, Theodore W


     dB, the proposed system dramatically decreases the error rate over normally used acoustic feature extraction method, mel-frequency cepstral computation (MFCC), by 26%, 36.3%, and 60.3%, respectively; and, over LHL by 20%, 2.3%, and 15.3%, respectively. Another applicable project is vehicle type identification. The proposed system achieves better performance than LHL, e.g., 40% improvement when gasoline heavy wheeled car is contaminated by AWGN at SNR=5 dB. More importantly, the proposed system is implemented in real-time field testing for months. The purpose is to detect vehicle with any make or model moving on the street with speed 10-35 mph. The missing rate is 1-2%, when vehicle is contaminated by any surrounding noises (human conversation, animal sound, airplane, wind, etc.) at SNR=0-20 dB. The false alarm rate is around 1%. To summarize, this study not only provides an efficient approach to extract representative independent features from high-dimensional data, but also offers robustness against severe noises. Published by Elsevier Ltd.

  10. Robust Fallback Scheme for the Danish Automatic Voltage Control System

    DEFF Research Database (Denmark)

    Qin, Nan; Dmitrova, Evgenia; Lund, Torsten


    This paper proposes a fallback scheme for the Danish automatic voltage control system. It will be activated in case of the local station loses telecommunication to the control center and/or the local station voltage violates the acceptable operational limits. It cuts in/out switchable and tap...

  11. Robust output tracking control of a laboratory helicopter for automatic landing (United States)

    Liu, Hao; Lu, Geng; Zhong, Yisheng


    In this paper, robust output tracking control problem of a laboratory helicopter for automatic landing in high seas is investigated. The motion of the helicopter is required to synchronise with that of an oscillating platform, e.g. the deck of a vessel subject to wave-induced motions. A robust linear time-invariant output feedback controller consisting of a nominal controller and a robust compensator is designed. The robust compensator is introduced to restrain the influences of parametric uncertainties, nonlinearities and external disturbances. It is shown that robust stability and robust tracking property can be achieved simultaneously. Experimental results on the laboratory helicopter for automatic landing demonstrate the effectiveness of the designed control approach.

  12. Modification of computational auditory scene analysis (CASA) for noise-robust acoustic feature (United States)

    Kwon, Minseok

    While there have been many attempts to mitigate interferences of background noise, the performance of automatic speech recognition (ASR) still can be deteriorated by various factors with ease. However, normal hearing listeners can accurately perceive sounds of their interests, which is believed to be a result of Auditory Scene Analysis (ASA). As a first attempt, the simulation of the human auditory processing, called computational auditory scene analysis (CASA), was fulfilled through physiological and psychological investigations of ASA. CASA comprised of Zilany-Bruce auditory model, followed by tracking fundamental frequency for voice segmentation and detecting pairs of onset/offset at each characteristic frequency (CF) for unvoiced segmentation. The resulting Time-Frequency (T-F) representation of acoustic stimulation was converted into acoustic feature, gammachirp-tone frequency cepstral coefficients (GFCC). 11 keywords with various environmental conditions are used and the robustness of GFCC was evaluated by spectral distance (SD) and dynamic time warping distance (DTW). In "clean" and "noisy" conditions, the application of CASA generally improved noise robustness of the acoustic feature compared to a conventional method with or without noise suppression using MMSE estimator. The intial study, however, not only showed the noise-type dependency at low SNR, but also called the evaluation methods in question. Some modifications were made to capture better spectral continuity from an acoustic feature matrix, to obtain faster processing speed, and to describe the human auditory system more precisely. The proposed framework includes: 1) multi-scale integration to capture more accurate continuity in feature extraction, 2) contrast enhancement (CE) of each CF by competition with neighboring frequency bands, and 3) auditory model modifications. The model modifications contain the introduction of higher Q factor, middle ear filter more analogous to human auditory system

  13. Robust blind identification of room acoustic channels in symmetric alpha-stable distributed noise environments. (United States)

    He, Hongsen; Lu, Jing; Chen, Jingdong; Qiu, Xiaojun; Benesty, Jacob


    Blind multichannel identification is generally sensitive to background noise. Although there have been some efforts in the literature devoted to improving the robustness of blind multichannel identification with respect to noise, most of those works assume that the noise is Gaussian distributed, which is often not valid in real room acoustic environments. This paper deals with the more practical scenario where the noise is not Gaussian. To improve the robustness of blind multichannel identification to non-Gaussian noise, a robust normalized multichannel frequency-domain least-mean M-estimate algorithm is developed. Unlike the traditional approaches that use the squared error as the cost function, the proposed algorithm uses an M-estimator to form the cost function, which is shown to be immune to non-Gaussian noise with a symmetric α-stable distribution. Experiments based on the identification of a single-input/multiple-output acoustic system demonstrate the robustness of the proposed algorithm.

  14. From bounded-noise data to robust PI-controller design

    NARCIS (Netherlands)

    Steinbuch, Luc; Keesman, K.J.


    An approach is presented to design a robust PI-controller from bounded noise measurement data of a first order process with and without time delay. This controller guarantees a known robust performance. It is shown that in the case without time delay, the conservatism of the robust approach can

  15. Computationally Efficient and Noise Robust DOA and Pitch Estimation

    DEFF Research Database (Denmark)

    Karimian-Azari, Sam; Jensen, Jesper Rindom; Christensen, Mads Græsbøll


    signals are often contaminated by different types of noise, which challenges the assumption of white Gaussian noise in most state-of-the-art methods. We establish filtering methods based on noise statistics to apply to nonparametric spectral and spatial parameter estimates of the harmonics. We design...... a joint DOA and pitch estimator. In white Gaussian noise, we derive even more computationally efficient solutions which are designed using the narrowband power spectrum of the harmonics. Numerical results reveal the performance of the estimators in colored noise compared with the Cram\\'{e}r-Rao lower...... bound. Experiments on real-life signals indicate the applicability of the methods in practical low local signal-to-noise ratios....

  16. Radiation Noise Separation of Internal Combustion Engine Based on Gammatone-RobustICA Method

    Directory of Open Access Journals (Sweden)

    Jiachi Yao


    Full Text Available In the internal combustion engine noise source separation process, the combustion noise and the piston slap noise are found to be seriously aliased in time-frequency domain. It is difficult to accurately separate them. Therefore, the noise source separation method which is based on Gammatone filter bank and robust independent component analysis (RobustICA is proposed. The 6-cylinder internal combustion engine vibration and noise test are carried out in a semianechoic chamber. The lead covering method is adopted to isolate the interference noise from numbers 1 to 5 cylinder parts, with only the number 6 cylinder parts left bare. Firstly, many mode components of the measured near-field radiated noise signals are extracted through the designed Gammatone filter bank. Then, the RobustICA algorithm is utilised to extract the independent components. Finally, the spectrum analysis, the continuous wavelet time-frequency analysis, the correlation function method, and the drag test are employed to further identify the separation results. The research results show that the frequency of the combustion noise and the piston slap noise are, respectively, concentrated at 4025 Hz and 1725 Hz. Compared with the EWT-RobustICA method, the separation results obtained by the Gammatone-RobustICA method have very fewer interference components.

  17. Robust thresholdlike effect of internal noise on stochastic resonance in an organic field-effect transistor (United States)

    Suzuki, Yoshiharu; Asakawa, Naoki


    The application of noise to a nonlinear system can have the effect of increasing the signal transmission of the system through the phenomenon of stochastic resonance (SR). This paper presents an analytical characterization of the dependence of the signal transmission performance of an organic field-effect transistor (OFET) on external noise. Similarly to the threshold of a nonlinear system, the additive internal noise of the system can be used to control the emergence of SR. Internal noise or the addition of random numbers to the system enables one to observe the SR phenomenon in an OFET under an intrinsically nonresonant condition. Internal noise plays a thresholdlike role, but it functions in a different manner. The fluctuations in performance due to external noise become smaller when the effect of internal noise becomes dominant compared with that of the threshold. In conclusion, it is found that internal noise plays a robust thresholdlike role with respect to variations in external noise intensity.

  18. A Robust Classifier to Distinguish Noise from fMRI Independent Components (United States)

    Sochat, Vanessa; Supekar, Kaustubh; Bustillo, Juan; Calhoun, Vince; Turner, Jessica A.; Rubin, Daniel L.


    Analyzing Functional Magnetic Resonance Imaging (fMRI) of resting brains to determine the spatial location and activity of intrinsic brain networks–a novel and burgeoning research field–is limited by the lack of ground truth and the tendency of analyses to overfit the data. Independent Component Analysis (ICA) is commonly used to separate the data into signal and Gaussian noise components, and then map these components on to spatial networks. Identifying noise from this data, however, is a tedious process that has proven hard to automate, particularly when data from different institutions, subjects, and scanners is used. Here we present an automated method to delineate noisy independent components in ICA using a data-driven infrastructure that queries a database of 246 spatial and temporal features to discover a computational signature of different types of noise. We evaluated the performance of our method to detect noisy components from healthy control fMRI (sensitivity = 0.91, specificity = 0.82, cross validation accuracy (CVA) = 0.87, area under the curve (AUC) = 0.93), and demonstrate its generalizability by showing equivalent performance on (1) an age- and scanner-matched cohort of schizophrenia patients from the same institution (sensitivity = 0.89, specificity = 0.83, CVA = 0.86), (2) an age-matched cohort on an equivalent scanner from a different institution (sensitivity = 0.88, specificity = 0.88, CVA = 0.88), and (3) an age-matched cohort on a different scanner from a different institution (sensitivity = 0.72, specificity = 0.92, CVA = 0.79). We additionally compare our approach with a recently published method [1]. Our results suggest that our method is robust to noise variations due to population as well as scanner differences, thereby making it well suited to the goal of automatically distinguishing noise from functional networks to enable investigation of human brain function. PMID:24748378

  19. Diffusion Maximum Correntropy Criterion Based Robust Spectrum Sensing in Non-Gaussian Noise Environments

    Directory of Open Access Journals (Sweden)

    Xiguang Xu


    Full Text Available Spectrum sensing is the most important task in cognitive radio (CR. In this paper, a new robust distributed spectrum sensing approach, called diffusion maximum correntropy criterion (DMCC-based robust spectrum sensing, is proposed for CR in the presence of non-Gaussian noise or impulsive noise. The proposed distributed scheme, which does not need any central processing unit, is characterized by an adaptive diffusion model. The maximum correntropy criterion, which is insensitive to impulsive interference, is introduced to deal with the effect of non-Gaussian noise. Simulation results show that the DMCC-based spectrum sensing algorithm has an excellent robust property with respect to non-Gaussian noise. It is also observed that the new method displays a considerably better detection performance than its predecessor (i.e., diffusion least mean square (DLMS in impulsive noise. Moreover, the mean and variance convergence analysis of the proposed algorithm are also carried out.

  20. Cortical activity patterns predict robust speech discrimination ability in noise (United States)

    Shetake, Jai A.; Wolf, Jordan T.; Cheung, Ryan J.; Engineer, Crystal T.; Ram, Satyananda K.; Kilgard, Michael P.


    The neural mechanisms that support speech discrimination in noisy conditions are poorly understood. In quiet conditions, spike timing information appears to be used in the discrimination of speech sounds. In this study, we evaluated the hypothesis that spike timing is also used to distinguish between speech sounds in noisy conditions that significantly degrade neural responses to speech sounds. We tested speech sound discrimination in rats and recorded primary auditory cortex (A1) responses to speech sounds in background noise of different intensities and spectral compositions. Our behavioral results indicate that rats, like humans, are able to accurately discriminate consonant sounds even in the presence of background noise that is as loud as the speech signal. Our neural recordings confirm that speech sounds evoke degraded but detectable responses in noise. Finally, we developed a novel neural classifier that mimics behavioral discrimination. The classifier discriminates between speech sounds by comparing the A1 spatiotemporal activity patterns evoked on single trials with the average spatiotemporal patterns evoked by known sounds. Unlike classifiers in most previous studies, this classifier is not provided with the stimulus onset time. Neural activity analyzed with the use of relative spike timing was well correlated with behavioral speech discrimination in quiet and in noise. Spike timing information integrated over longer intervals was required to accurately predict rat behavioral speech discrimination in noisy conditions. The similarity of neural and behavioral discrimination of speech in noise suggests that humans and rats may employ similar brain mechanisms to solve this problem. PMID:22098331

  1. Automatic Design of Robust Optimal Controller for Interval Plants Using Genetic Programming and Kharitonov Theorem

    Directory of Open Access Journals (Sweden)

    Peng Chen


    Full Text Available This paper presents a novel approach to automatic design of a robust optimal controller for interval plants with Genetic Programming based on Kharitonov Theorem (KT, which provides a theoretical foundation in the design of robust controller for interval plants. The structure and parameters of the robust optimal controller for interval plants are optimized by Genetic Programming and the Generalized KT related stability criteria are integrated into the solution to guarantee the stability of the closed-loop system. Consequently, the evolved controller not only minimizes time-weighted absolute error (ITAE of the closed-loop system, but also stabilizes the whole interval plant family robustly. Finally, the simulations on a benchmark problem show that the proposed method can effectively generate a robust optimal controller for interval plants.

  2. Robust and fast schemes in broadband active noise and vibration control

    NARCIS (Netherlands)

    Fraanje, P.R.


    This thesis presents robust and fast active control algorithms for the suppression of broadband noise and vibration disturbances. Noise disturbances, e.g., generated by engines in airplanes and cars or by air ow, can be reduced by means of passive or active methods.

  3. A Robust Adaptive Unscented Kalman Filter for Nonlinear Estimation with Uncertain Noise Covariance. (United States)

    Zheng, Binqi; Fu, Pengcheng; Li, Baoqing; Yuan, Xiaobing


    The Unscented Kalman filter (UKF) may suffer from performance degradation and even divergence while mismatch between the noise distribution assumed as a priori by users and the actual ones in a real nonlinear system. To resolve this problem, this paper proposes a robust adaptive UKF (RAUKF) to improve the accuracy and robustness of state estimation with uncertain noise covariance. More specifically, at each timestep, a standard UKF will be implemented first to obtain the state estimations using the new acquired measurement data. Then an online fault-detection mechanism is adopted to judge if it is necessary to update current noise covariance. If necessary, innovation-based method and residual-based method are used to calculate the estimations of current noise covariance of process and measurement, respectively. By utilizing a weighting factor, the filter will combine the last noise covariance matrices with the estimations as the new noise covariance matrices. Finally, the state estimations will be corrected according to the new noise covariance matrices and previous state estimations. Compared with the standard UKF and other adaptive UKF algorithms, RAUKF converges faster to the actual noise covariance and thus achieves a better performance in terms of robustness, accuracy, and computation for nonlinear estimation with uncertain noise covariance, which is demonstrated by the simulation results.

  4. Automatic physiological waveform processing for FMRI noise correction and analysis.

    Directory of Open Access Journals (Sweden)

    Daniel J Kelley


    Full Text Available Functional MRI resting state and connectivity studies of brain focus on neural fluctuations at low frequencies which share power with physiological fluctuations originating from lung and heart. Due to the lack of automated software to process physiological signals collected at high magnetic fields, a gap exists in the processing pathway between the acquisition of physiological data and its use in fMRI software for both physiological noise correction and functional analyses of brain activation and connectivity. To fill this gap, we developed an open source, physiological signal processing program, called PhysioNoise, in the python language. We tested its automated processing algorithms and dynamic signal visualization on resting monkey cardiac and respiratory waveforms. PhysioNoise consistently identifies physiological fluctuations for fMRI noise correction and also generates covariates for subsequent analyses of brain activation and connectivity.

  5. White noise theory of robust nonlinear filtering with correlated state and observation noises

    NARCIS (Netherlands)

    Bagchi, Arunabha; Karandikar, Rajeeva


    In the direct white noise theory of nonlinear filtering, the state process is still modeled as a Markov process satisfying an Ito stochastic differential equation, while a finitely additive white noise is used to model the observation noise. In the present work, this asymmetry is removed by modeling

  6. White noise theory of robust nonlinear filtering with correlated state and observation noises

    NARCIS (Netherlands)

    Bagchi, Arunabha; Karandikar, Rajeeva


    In the existing `direct¿ white noise theory of nonlinear filtering, the state process is still modelled as a Markov process satisfying an Itô stochastic differential equation, while a `finitely additive¿ white noise is used to model the observation noise. We remove this asymmetry by modelling the

  7. Making tensor factorizations robust to non-gaussian noise.

    Energy Technology Data Exchange (ETDEWEB)

    Chi, Eric C. (Rice University, Houston, TX); Kolda, Tamara Gibson


    Tensors are multi-way arrays, and the CANDECOMP/PARAFAC (CP) tensor factorization has found application in many different domains. The CP model is typically fit using a least squares objective function, which is a maximum likelihood estimate under the assumption of independent and identically distributed (i.i.d.) Gaussian noise. We demonstrate that this loss function can be highly sensitive to non-Gaussian noise. Therefore, we propose a loss function based on the 1-norm because it can accommodate both Gaussian and grossly non-Gaussian perturbations. We also present an alternating majorization-minimization (MM) algorithm for fitting a CP model using our proposed loss function (CPAL1) and compare its performance to the workhorse algorithm for fitting CP models, CP alternating least squares (CPALS).

  8. Noise Robust Voice Activity Detection Based on Switching Kalman Filter (United States)

    Fujimoto, Masakiyo; Ishizuka, Kentaro

    This paper addresses the problem of voice activity detection (VAD) in noisy environments. The VAD method proposed in this paper is based on a statistical model approach, and estimates statistical models sequentially without a priori knowledge of noise. Namely, the proposed method constructs a clean speech/silence state transition model beforehand, and sequentially adapts the model to the noisy environment by using a switching Kalman filter when a signal is observed. In this paper, we carried out two evaluations. In the first, we observed that the proposed method significantly outperforms conventional methods as regards voice activity detection accuracy in simulated noise environments. Second, we evaluated the proposed method on a VAD evaluation framework, CENSREC-1-C. The evaluation results revealed that the proposed method significantly outperforms the baseline results of CENSREC-1-C as regards VAD accuracy in real environments. In addition, we confirmed that the proposed method helps to improve the accuracy of concatenated speech recognition in real environments.

  9. Robust relationship between reading span and speech recognition in noise. (United States)

    Souza, Pamela; Arehart, Kathryn


    Working memory refers to a cognitive system that manages information processing and temporary storage. Recent work has demonstrated that individual differences in working memory capacity measured using a reading span task are related to ability to recognize speech in noise. In this project, we investigated whether the specific implementation of the reading span task influenced the strength of the relationship between working memory capacity and speech recognition. The relationship between speech recognition and working memory capacity was examined for two different working memory tests that varied in approach, using a within-subject design. Data consisted of audiometric results along with the two different working memory tests; one speech-in-noise test; and a reading comprehension test. The test group included 94 older adults with varying hearing loss and 30 younger adults with normal hearing. Listeners with poorer working memory capacity had more difficulty understanding speech in noise after accounting for age and degree of hearing loss. That relationship did not differ significantly between the two different implementations of reading span. Our findings suggest that different implementations of a verbal reading span task do not affect the strength of the relationship between working memory capacity and speech recognition.

  10. Noise in Load Cell Signal in an Automatic Weighing System Based on a Belt Conveyor

    Directory of Open Access Journals (Sweden)

    Kyoo Nam Choi


    Full Text Available Noise in load cell signal in an automatic weighing system based on a belt conveyor has been examined experimentally in time and frequency domains to enhance signal quality. The noise frequency spectrum showed nonlinearly increasing multiple resonance peaks as speed increased. The noise reduction process using noise reduction algorithm, by sharply rejecting peak noise frequency component and afterward forming optimum pulse width ratio through filter slope control using selective switching of 6 LPF stages, was used for enhanced accuracy. The effectiveness of proposed method, controlling both cutoff frequency and slope of LPF, was evaluated by feeding 50 g test mass, and this noise reduction process showed better noise filtering with enhanced accuracy than fixed cutoff frequency control method. The ratio of top to bottom pulse width showed that LPF cutoff frequency above 5 Hz had the ratio above 50% up to 80 m/min speed range.

  11. Speech Waveform Compression Using Robust Adaptive Voice Activity Detection for Nonstationary Noise

    Directory of Open Access Journals (Sweden)

    Hsiao-Chun Wu


    Full Text Available The voice activity detection (VAD is crucial in all kinds of speech applications. However, almost all existing VAD algorithms suffer from the nonstationarity of both speech and noise. To combat this difficulty, we propose a new voice activity detector, which is based on the Mel-energy features and an adaptive threshold related to the signal-to-noise ratio (SNR estimates. In this paper, we first justify the robustness of the Bayes classifier using the Mel-energy features over that using the Fourier spectral features in various noise environments. Then, we design an algorithm using the dynamic Mel-energy estimator and the adaptive threshold, which depends on the SNR estimates. In addition, a realignment scheme is incorporated to correct the sparse-and-spurious noise estimates. Numerous simulations are carried out to evaluate the performance of our proposed VAD method and the comparisons are made with a couple of existing representative schemes, namely, the VAD using the likelihood ratio test with Fourier spectral energy features and that based on the enhanced time-frequency parameters. Three types of noises, namely, white noise (stationary, babble noise (nonstationary, and vehicular noise (nonstationary were artificially added by the computer for our experiments. As a result, our proposed VAD algorithm significantly outperforms other existing methods as illustrated by the corresponding receiver operating characteristics (ROC curves. Finally, we demonstrate one of the major applications, namely, speech waveform compression associated with our new robust VAD scheme and quantify the effectiveness in terms of compression efficiency.

  12. Speech Waveform Compression Using Robust Adaptive Voice Activity Detection for Nonstationary Noise

    Directory of Open Access Journals (Sweden)

    Syed WaheeduddinQ


    Full Text Available The voice activity detection (VAD is crucial in all kinds of speech applications. However, almost all existing VAD algorithms suffer from the nonstationarity of both speech and noise. To combat this difficulty, we propose a new voice activity detector, which is based on the Mel-energy features and an adaptive threshold related to the signal-to-noise ratio (SNR estimates. In this paper, we first justify the robustness of the Bayes classifier using the Mel-energy features over that using the Fourier spectral features in various noise environments. Then, we design an algorithm using the dynamic Mel-energy estimator and the adaptive threshold, which depends on the SNR estimates. In addition, a realignment scheme is incorporated to correct the sparse-and-spurious noise estimates. Numerous simulations are carried out to evaluate the performance of our proposed VAD method and the comparisons are made with a couple of existing representative schemes, namely, the VAD using the likelihood ratio test with Fourier spectral energy features and that based on the enhanced time-frequency parameters. Three types of noises, namely, white noise (stationary, babble noise (nonstationary, and vehicular noise (nonstationary were artificially added by the computer for our experiments. As a result, our proposed VAD algorithm significantly outperforms other existing methods as illustrated by the corresponding receiver operating characteristics (ROC curves. Finally, we demonstrate one of the major applications, namely, speech waveform compression associated with our new robust VAD scheme and quantify the effectiveness in terms of compression efficiency.

  13. Auto Regressive Moving Average (ARMA) Modeling Method for Gyro Random Noise Using a Robust Kalman Filter (United States)

    Huang, Lei


    To solve the problem in which the conventional ARMA modeling methods for gyro random noise require a large number of samples and converge slowly, an ARMA modeling method using a robust Kalman filtering is developed. The ARMA model parameters are employed as state arguments. Unknown time-varying estimators of observation noise are used to achieve the estimated mean and variance of the observation noise. Using the robust Kalman filtering, the ARMA model parameters are estimated accurately. The developed ARMA modeling method has the advantages of a rapid convergence and high accuracy. Thus, the required sample size is reduced. It can be applied to modeling applications for gyro random noise in which a fast and accurate ARMA modeling method is required. PMID:26437409

  14. An automatic classifier of emotions built from entropy of noise. (United States)

    Ferreira, Jacqueline; Brás, Susana; Silva, Carlos F; Soares, Sandra C


    The electrocardiogram (ECG) signal has been widely used to study the physiological substrates of emotion. However, searching for better filtering techniques in order to obtain a signal with better quality and with the maximum relevant information remains an important issue for researchers in this field. Signal processing is largely performed for ECG analysis and interpretation, but this process can be susceptible to error in the delineation phase. In addition, it can lead to the loss of important information that is usually considered as noise and, consequently, discarded from the analysis. The goal of this study was to evaluate if the ECG noise allows for the classification of emotions, while using its entropy as an input in a decision tree classifier. We collected the ECG signal from 25 healthy participants while they were presented with videos eliciting negative (fear and disgust) and neutral emotions. The results indicated that the neutral condition showed a perfect identification (100%), whereas the classification of negative emotions indicated good identification performances (60% of sensitivity and 80% of specificity). These results suggest that the entropy of noise contains relevant information that can be useful to improve the analysis of the physiological correlates of emotion. © 2016 Society for Psychophysiological Research.

  15. Robust terahertz self-heterodyne system using a phase noise compensation technique. (United States)

    Song, Hajun; Song, Jong-In


    We propose and demonstrate a robust terahertz self-heterodyne system using a phase noise compensation technique. Conventional terahertz self-heterodyne systems suffer from degraded phase noise performance due to phase noise of the laser sources. The proposed phase noise compensation technique uses an additional photodiode and a simple electric circuit to produce phase noise identical to that observed in the terahertz signal produced by the self-heterodyne system. The phase noise is subsequently subtracted from the terahertz signal produced by the self-heterodyne system using a lock-in amplifier. While the terahertz self-heterodyne system using a phase noise compensation technique offers improved phase noise performance, it also provides a reduced phase drift against ambient temperature variations. The terahertz self-heterodyne system using a phase noise compensation technique shows a phase noise of 0.67 degree in terms of a standard deviation value even without using overall delay balance control. It also shows a phase drift of as small as approximately 10 degrees in an open-to-air measurement condition without any strict temperature control.

  16. Robust Cyclic MUSIC Algorithm for Finding Directions in Impulsive Noise Environment

    Directory of Open Access Journals (Sweden)

    Sen Li


    Full Text Available This paper addresses the issue of direction finding of a cyclostationary signal under impulsive noise environments modeled by α-stable distribution. Since α-stable distribution does not have finite second-order statistics, the conventional cyclic correlation-based signal-selective direction finding algorithms do not work effectively. To resolve this problem, we define two robust cyclic correlation functions which are derived from robust statistics property of the correntropy and the nonlinear transformation, respectively. The MUSIC algorithm with the robust cyclic correlation matrix of the received signals of arrays is then used to estimate the direction of cyclostationary signal in the presence of impulsive noise. The computer simulation results demonstrate that the two proposed robust cyclic correlation-based algorithms outperform the conventional cyclic correlation and the fractional lower order cyclic correlation based methods.

  17. Aerodynamic design applying automatic differentiation and using robust variable fidelity optimization (United States)

    Takemiya, Tetsushi

    , and that (2) the AMF terminates optimization erroneously when the optimization problems have constraints. The first problem is due to inaccuracy in computing derivatives in the AMF, and the second problem is due to erroneous treatment of the trust region ratio, which sets the size of the domain for an optimization in the AMF. In order to solve the first problem of the AMF, automatic differentiation (AD) technique, which reads the codes of analysis models and automatically generates new derivative codes based on some mathematical rules, is applied. If derivatives are computed with the generated derivative code, they are analytical, and the required computational time is independent of the number of design variables, which is very advantageous for realistic aerospace engineering problems. However, if analysis models implement iterative computations such as computational fluid dynamics (CFD), which solves system partial differential equations iteratively, computing derivatives through the AD requires a massive memory size. The author solved this deficiency by modifying the AD approach and developing a more efficient implementation with CFD, and successfully applied the AD to general CFD software. In order to solve the second problem of the AMF, the governing equation of the trust region ratio, which is very strict against the violation of constraints, is modified so that it can accept the violation of constraints within some tolerance. By accepting violations of constraints during the optimization process, the AMF can continue optimization without terminating immaturely and eventually find the true optimum design point. With these modifications, the AMF is referred to as "Robust AMF," and it is applied to airfoil and wing aerodynamic design problems using Euler CFD software. The former problem has 21 design variables, and the latter 64. In both problems, derivatives computed with the proposed AD method are first compared with those computed with the finite

  18. Environmental noise, genetic diversity and the evolution of evolvability and robustness in model gene networks.

    Directory of Open Access Journals (Sweden)

    Christopher F Steiner

    Full Text Available The ability of organisms to adapt and persist in the face of environmental change is accepted as a fundamental feature of natural systems. More contentious is whether the capacity of organisms to adapt (or "evolvability" can itself evolve and the mechanisms underlying such responses. Using model gene networks, I provide evidence that evolvability emerges more readily when populations experience positively autocorrelated environmental noise (red noise compared to populations in stable or randomly varying (white noise environments. Evolvability was correlated with increasing genetic robustness to effects on network viability and decreasing robustness to effects on phenotypic expression; populations whose networks displayed greater viability robustness and lower phenotypic robustness produced more additive genetic variation and adapted more rapidly in novel environments. Patterns of selection for robustness varied antagonistically with epistatic effects of mutations on viability and phenotypic expression, suggesting that trade-offs between these properties may constrain their evolutionary responses. Evolution of evolvability and robustness was stronger in sexual populations compared to asexual populations indicating that enhanced genetic variation under fluctuating selection combined with recombination load is a primary driver of the emergence of evolvability. These results provide insight into the mechanisms potentially underlying rapid adaptation as well as the environmental conditions that drive the evolution of genetic interactions.

  19. The Effects of Background Noise on the Performance of an Automatic Speech Recogniser (United States)

    Littlefield, Jason; HashemiSakhtsari, Ahmad


    Ambient or environmental noise is a major factor that affects the performance of an automatic speech recognizer. Large vocabulary, speaker-dependent, continuous speech recognizers are commercially available. Speech recognizers, perform well in a quiet environment, but poorly in a noisy environment. Speaker-dependent speech recognizers require training prior to them being tested, where the level of background noise in both phases affects the performance of the recognizer. This study aims to determine whether the best performance of a speech recognizer occurs when the levels of background noise during the training and test phases are the same, and how the performance is affected when the levels of background noise during the training and test phases are different. The relationship between the performance of the speech recognizer and upgrading the computer speed and amount of memory as well as software version was also investigated.

  20. Automatic switching between noise classification and speech enhancement for hearing aid devices. (United States)

    Saki, Fatemeh; Kehtarnavaz, Nasser


    This paper presents a voice activity detector (VAD) for automatic switching between a noise classifier and a speech enhancer as part of the signal processing pipeline of hearing aid devices. The developed VAD consists of a computationally efficient feature extractor and a random forest classifier. Previously used signal features as well as two newly introduced signal features are extracted and fed into the classifier to perform automatic switching. This switching approach is compared to two popular VADs. The results obtained indicate the introduced approach outperforms these existing approaches in terms of both detection rate and processing time.

  1. Automatic Ki-67 counting using robust cell detection and online dictionary learning. (United States)

    Xing, Fuyong; Su, Hai; Neltner, Janna; Yang, Lin


    Ki-67 proliferation index is a valid and important biomarker to gauge neuroendocrine tumor (NET) cell progression within the gastrointestinal tract and pancreas. Automatic Ki-67 assessment is very challenging due to complex variations of cell characteristics. In this paper, we propose an integrated learning-based framework for accurate automatic Ki-67 counting for NET. The main contributions of our method are: 1) A robust cell counting and boundary delineation algorithm that is designed to localize both tumor and nontumor cells. 2) A novel online sparse dictionary learning method to select a set of representative training samples. 3) An automated framework that is used to differentiate tumor from nontumor cells (such as lymphocytes) and immunopositive from immunonegative tumor cells for the assessment of Ki-67 proliferation index. The proposed method has been extensively tested using 46 NET cases. The performance is compared with pathologists' manual annotations. The automatic Ki-67 counting is quite accurate compared with pathologists' manual annotations. This is much more accurate than existing methods.

  2. Robust Machine Learning-Based Correction on Automatic Segmentation of the Cerebellum and Brainstem. (United States)

    Wang, Jun Yi; Ngo, Michael M; Hessl, David; Hagerman, Randi J; Rivera, Susan M


    Automated segmentation is a useful method for studying large brain structures such as the cerebellum and brainstem. However, automated segmentation may lead to inaccuracy and/or undesirable boundary. The goal of the present study was to investigate whether SegAdapter, a machine learning-based method, is useful for automatically correcting large segmentation errors and disagreement in anatomical definition. We further assessed the robustness of the method in handling size of training set, differences in head coil usage, and amount of brain atrophy. High resolution T1-weighted images were acquired from 30 healthy controls scanned with either an 8-channel or 32-channel head coil. Ten patients, who suffered from brain atrophy because of fragile X-associated tremor/ataxia syndrome, were scanned using the 32-channel head coil. The initial segmentations of the cerebellum and brainstem were generated automatically using Freesurfer. Subsequently, Freesurfer's segmentations were both manually corrected to serve as the gold standard and automatically corrected by SegAdapter. Using only 5 scans in the training set, spatial overlap with manual segmentation in Dice coefficient improved significantly from 0.956 (for Freesurfer segmentation) to 0.978 (for SegAdapter-corrected segmentation) for the cerebellum and from 0.821 to 0.954 for the brainstem. Reducing the training set size to 2 scans only decreased the Dice coefficient ≤0.002 for the cerebellum and ≤ 0.005 for the brainstem compared to the use of training set size of 5 scans in corrective learning. The method was also robust in handling differences between the training set and the test set in head coil usage and the amount of brain atrophy, which reduced spatial overlap only by learning provides a valuable method for accurate and efficient segmentation of the cerebellum and brainstem, particularly in large-scale neuroimaging studies, and potentially for segmenting other neural regions as well.

  3. Comparison of PAM and CAP modulations robustness against mode partition noise in optical links (United States)

    Stepniak, Grzegorz


    Mode partition noise (MPN) of the laser employed at the transmitter can significantly degrade the transmission performance. In the paper, we introduce a simulation model of MPN in vertical cavity surface emitting laser (VCSEL) and simulate transmission of pulse amplitude modulation (PAM) and carrierless amplitude phase (CAP) signals in multimode fiber (MMF) link. By turning off other effects, like relative intensity noise (RIN), we focus solely on the influence of MPN on transmission performance degradation. Robustness of modulation and equalization type against MPN is studied.

  4. Transform Domain Robust Variable Step Size Griffiths' Adaptive Algorithm for Noise Cancellation in ECG (United States)

    Hegde, Veena; Deekshit, Ravishankar; Satyanarayana, P. S.


    The electrocardiogram (ECG) is widely used for diagnosis of heart diseases. Good quality of ECG is utilized by physicians for interpretation and identification of physiological and pathological phenomena. However, in real situations, ECG recordings are often corrupted by artifacts or noise. Noise severely limits the utility of the recorded ECG and thus needs to be removed, for better clinical evaluation. In the present paper a new noise cancellation technique is proposed for removal of random noise like muscle artifact from ECG signal. A transform domain robust variable step size Griffiths' LMS algorithm (TVGLMS) is proposed for noise cancellation. For the TVGLMS, the robust variable step size has been achieved by using the Griffiths' gradient which uses cross-correlation between the desired signal contaminated with observation or random noise and the input. The algorithm is discrete cosine transform (DCT) based and uses symmetric property of the signal to represent the signal in frequency domain with lesser number of frequency coefficients when compared to that of discrete Fourier transform (DFT). The algorithm is implemented for adaptive line enhancer (ALE) filter which extracts the ECG signal in a noisy environment using LMS filter adaptation. The proposed algorithm is found to have better convergence error/misadjustment when compared to that of ordinary transform domain LMS (TLMS) algorithm, both in the presence of white/colored observation noise. The reduction in convergence error achieved by the new algorithm with desired signal decomposition is found to be lower than that obtained without decomposition. The experimental results indicate that the proposed method is better than traditional adaptive filter using LMS algorithm in the aspects of retaining geometrical characteristics of ECG signal.

  5. Concurrent Codes: A Holographic-Type Encoding Robust against Noise and Loss.

    Directory of Open Access Journals (Sweden)

    David M Benton

    Full Text Available Concurrent coding is an encoding scheme with 'holographic' type properties that are shown here to be robust against a significant amount of noise and signal loss. This single encoding scheme is able to correct for random errors and burst errors simultaneously, but does not rely on cyclic codes. A simple and practical scheme has been tested that displays perfect decoding when the signal to noise ratio is of order -18dB. The same scheme also displays perfect reconstruction when a contiguous block of 40% of the transmission is missing. In addition this scheme is 50% more efficient in terms of transmitted power requirements than equivalent cyclic codes. A simple model is presented that describes the process of decoding and can determine the computational load that would be expected, as well as describing the critical levels of noise and missing data at which false messages begin to be generated.

  6. Comparison of the Noise Robustness of FVC Retrieval Algorithms Based on Linear Mixture Models

    Directory of Open Access Journals (Sweden)

    Hiroki Yoshioka


    Full Text Available The fraction of vegetation cover (FVC is often estimated by unmixing a linear mixture model (LMM to assess the horizontal spread of vegetation within a pixel based on a remotely sensed reflectance spectrum. The LMM-based algorithm produces results that can vary to a certain degree, depending on the model assumptions. For example, the robustness of the results depends on the presence of errors in the measured reflectance spectra. The objective of this study was to derive a factor that could be used to assess the robustness of LMM-based algorithms under a two-endmember assumption. The factor was derived from the analytical relationship between FVC values determined according to several previously described algorithms. The factor depended on the target spectra, endmember spectra, and choice of the spectral vegetation index. Numerical simulations were conducted to demonstrate the dependence and usefulness of the technique in terms of robustness against the measurement noise.

  7. Robust Machine Learning-Based Correction on Automatic Segmentation of the Cerebellum and Brainstem.

    Directory of Open Access Journals (Sweden)

    Jun Yi Wang

    Full Text Available Automated segmentation is a useful method for studying large brain structures such as the cerebellum and brainstem. However, automated segmentation may lead to inaccuracy and/or undesirable boundary. The goal of the present study was to investigate whether SegAdapter, a machine learning-based method, is useful for automatically correcting large segmentation errors and disagreement in anatomical definition. We further assessed the robustness of the method in handling size of training set, differences in head coil usage, and amount of brain atrophy. High resolution T1-weighted images were acquired from 30 healthy controls scanned with either an 8-channel or 32-channel head coil. Ten patients, who suffered from brain atrophy because of fragile X-associated tremor/ataxia syndrome, were scanned using the 32-channel head coil. The initial segmentations of the cerebellum and brainstem were generated automatically using Freesurfer. Subsequently, Freesurfer's segmentations were both manually corrected to serve as the gold standard and automatically corrected by SegAdapter. Using only 5 scans in the training set, spatial overlap with manual segmentation in Dice coefficient improved significantly from 0.956 (for Freesurfer segmentation to 0.978 (for SegAdapter-corrected segmentation for the cerebellum and from 0.821 to 0.954 for the brainstem. Reducing the training set size to 2 scans only decreased the Dice coefficient ≤0.002 for the cerebellum and ≤ 0.005 for the brainstem compared to the use of training set size of 5 scans in corrective learning. The method was also robust in handling differences between the training set and the test set in head coil usage and the amount of brain atrophy, which reduced spatial overlap only by <0.01. These results suggest that the combination of automated segmentation and corrective learning provides a valuable method for accurate and efficient segmentation of the cerebellum and brainstem, particularly in large

  8. Robust noise attenuation based on nuclear norm minimization and a trace prediction strategy (United States)

    Zhou, Yatong; Zhang, Shili


    Rejecting noise in seismic data while not affecting the amplitude of useful signals is a long standing problem in seismic data processing. Seismic noise attenuation can be formulated as a nuclear norm minimization (NNM) problem. To meet the assumption that seismic data should have low nuclear norm, we first map the seismic data into a low-rank matrix based on a trace prediction strategy. We provide detailed algorithm workflow and mathematical analysis of the trace prediction method. The seismic data after trace rearrangement is demonstrated to be locally low-rank. The NNM problem is then solved via the singular value thresholding (SVT) algorithm. The effectiveness of the proposed method is validated via both synthetic and field data examples. We also test the robustness of the proposed method with respect to random noise, spiky noise, and blending interference. Compared with the state-of-the-art predictive filtering method, median filtering method, singular spectrum analysis method, and curvelet thresholding method, the proposed method obtains an obviously better performance in compromising signal preservation and noise removal.

  9. Robust active noise control in the loadmaster area of a military transport aircraft. (United States)

    Kochan, Kay; Sachau, Delf; Breitbach, Harald


    The active noise control (ANC) method is based on the superposition of a disturbance noise field with a second anti-noise field using loudspeakers and error microphones. This method can be used to reduce the noise level inside the cabin of a propeller aircraft. However, during the design process of the ANC system, extensive measurements of transfer functions are necessary to optimize the loudspeaker and microphone positions. Sometimes, the transducer positions have to be tailored according to the optimization results to achieve a sufficient noise reduction. The purpose of this paper is to introduce a controller design method for such narrow band ANC systems. The method can be seen as an extension of common transducer placement optimization procedures. In the presented method, individual weighting parameters for the loudspeakers and microphones are used. With this procedure, the tailoring of the transducer positions is replaced by adjustment of controller parameters. Moreover, the ANC system will be robust because of the fact that the uncertainties are considered during the optimization of the controller parameters. The paper describes the necessary theoretic background for the method and demonstrates the efficiency in an acoustical mock-up of a military transport aircraft.

  10. A Robust Vision-based Runway Detection and Tracking Algorithm for Automatic UAV Landing

    KAUST Repository

    Abu Jbara, Khaled F.


    This work presents a novel real-time algorithm for runway detection and tracking applied to the automatic takeoff and landing of Unmanned Aerial Vehicles (UAVs). The algorithm is based on a combination of segmentation based region competition and the minimization of a specific energy function to detect and identify the runway edges from streaming video data. The resulting video-based runway position estimates are updated using a Kalman Filter, which can integrate other sensory information such as position and attitude angle estimates to allow a more robust tracking of the runway under turbulence. We illustrate the performance of the proposed lane detection and tracking scheme on various experimental UAV flights conducted by the Saudi Aerospace Research Center. Results show an accurate tracking of the runway edges during the landing phase under various lighting conditions. Also, it suggests that such positional estimates would greatly improve the positional accuracy of the UAV during takeoff and landing phases. The robustness of the proposed algorithm is further validated using Hardware in the Loop simulations with diverse takeoff and landing videos generated using a commercial flight simulator.

  11. Robust cubature Kalman filter for GNSS/INS with missing observations and colored measurement noise. (United States)

    Cui, Bingbo; Chen, Xiyuan; Tang, Xihua; Huang, Haoqian; Liu, Xiao


    In order to improve the accuracy of GNSS/INS working in GNSS-denied environment, a robust cubature Kalman filter (RCKF) is developed by considering colored measurement noise and missing observations. First, an improved cubature Kalman filter (CKF) is derived by considering colored measurement noise, where the time-differencing approach is applied to yield new observations. Then, after analyzing the disadvantages of existing methods, the measurement augment in processing colored noise is translated into processing the uncertainties of CKF, and new sigma point update framework is utilized to account for the bounded model uncertainties. By reusing the diffused sigma points and approximation residual in the prediction stage of CKF, the RCKF is developed and its error performance is analyzed theoretically. Results of numerical experiment and field test reveal that RCKF is more robust than CKF and extended Kalman filter (EKF), and compared with EKF, the heading error of land vehicle is reduced by about 72.4%. Copyright © 2017 ISA. Published by Elsevier Ltd. All rights reserved.

  12. Automatic spinal cord localization, robust to MRI contrasts using global curve optimization. (United States)

    Gros, Charley; De Leener, Benjamin; Dupont, Sara M; Martin, Allan R; Fehlings, Michael G; Bakshi, Rohit; Tummala, Subhash; Auclair, Vincent; McLaren, Donald G; Callot, Virginie; Cohen-Adad, Julien; Sdika, Michaël


    During the last two decades, MRI has been increasingly used for providing valuable quantitative information about spinal cord morphometry, such as quantification of the spinal cord atrophy in various diseases. However, despite the significant improvement of MR sequences adapted to the spinal cord, automatic image processing tools for spinal cord MRI data are not yet as developed as for the brain. There is nonetheless great interest in fully automatic and fast processing methods to be able to propose quantitative analysis pipelines on large datasets without user bias. The first step of most of these analysis pipelines is to detect the spinal cord, which is challenging to achieve automatically across the broad range of MRI contrasts, field of view, resolutions and pathologies. In this paper, a fully automated, robust and fast method for detecting the spinal cord centerline on MRI volumes is introduced. The algorithm uses a global optimization scheme that attempts to strike a balance between a probabilistic localization map of the spinal cord center point and the overall spatial consistency of the spinal cord centerline (i.e. the rostro-caudal continuity of the spinal cord). Additionally, a new post-processing feature, which aims to automatically split brain and spine regions is introduced, to be able to detect a consistent spinal cord centerline, independently from the field of view. We present data on the validation of the proposed algorithm, known as "OptiC", from a large dataset involving 20 centers, 4 contrasts (T 2 -weighted n = 287, T 1 -weighted n = 120, T 2 ∗ -weighted n = 307, diffusion-weighted n = 90), 501 subjects including 173 patients with a variety of neurologic diseases. Validation involved the gold-standard centerline coverage, the mean square error between the true and predicted centerlines and the ability to accurately separate brain and spine regions. Overall, OptiC was able to cover 98.77% of the gold-standard centerline, with a

  13. Taking NIRS-BCIs outside the lab: towards achieving robustness against environment noise. (United States)

    Falk, Tiago H; Guirgis, Mirna; Power, Sarah; Chau, Tom T


    This paper reported initial findings on the effects of environmental noise and auditory distractions on the performance of mental state classification based on near-infrared spectroscopy (NIRS) signals recorded from the prefrontal cortex. Characterization of the performance losses due to environmental factors could provide useful information for the future development of NIRS-based brain-computer interfaces that can be taken beyond controlled laboratory settings and into everyday environments. Experiments with a hidden Markov model-based classifier showed that while significant performance could be attained in silent conditions, only chance levels of sensitivity and specificity were obtained in noisy environments. In order to achieve robustness against environment noise, two strategies were proposed and evaluated. First, physiological responses harnessed from the autonomic nervous system were used as complementary information to NIRS signals. More specifically, four physiological signals (electrodermal activity, skin temperature, blood volume pulse, and respiration effort) were collected in synchrony with the NIRS signals as the user sat at rest and/or performed music imagery tasks. Second, an acoustic monitoring technique was proposed and used to detect startle noise events, as both the prefrontal cortex and ANS are known to involuntarily respond to auditory startle stimuli. Experiments with eight participants showed that with a startle noise compensation strategy in place, performance comparable to that observed in silent conditions could be recovered with the hybrid ANS-NIRS system.

  14. Adaptive cerebellar spiking model embedded in the control loop: context switching and robustness against noise. (United States)

    Luque, N R; Garrido, J A; Carrillo, R R; Tolu, S; Ros, E


    This work evaluates the capability of a spiking cerebellar model embedded in different loop architectures (recurrent, forward, and forward&recurrent) to control a robotic arm (three degrees of freedom) using a biologically-inspired approach. The implemented spiking network relies on synaptic plasticity (long-term potentiation and long-term depression) to adapt and cope with perturbations in the manipulation scenario: changes in dynamics and kinematics of the simulated robot. Furthermore, the effect of several degrees of noise in the cerebellar input pathway (mossy fibers) was assessed depending on the employed control architecture. The implemented cerebellar model managed to adapt in the three control architectures to different dynamics and kinematics providing corrective actions for more accurate movements. According to the obtained results, coupling both control architectures (forward&recurrent) provides benefits of the two of them and leads to a higher robustness against noise.

  15. Noise-robust cortical tracking of attended speech in real-world acoustic scenes

    DEFF Research Database (Denmark)

    Fuglsang, Søren; Dau, Torsten; Hjortkjær, Jens


    Selectively attending to one speaker in a multi-speaker scenario is thought to synchronize low-frequency cortical activity to the attended speech signal. In recent studies, reconstruction of speech from single-trial electroencephalogram (EEG) data has been used to decode which talker a listener...... is attending to in a two-talker situation. It is currently unclear how this generalizes to more complex sound environments. Behaviorally, speech perception is robust to the acoustic distortions that listeners typically encounter in everyday life, but it is unknown whether this is mirrored by a noise......-robust neural tracking of attended speech. Here we used advanced acoustic simulations to recreate real-world acoustic scenes in the laboratory. In virtual acoustic realities with varying amounts of reverberation and number of interfering talkers, listeners selectively attended to the speech stream...

  16. Feasibility of online IMPT adaptation using fast, automatic and robust dose restoration (United States)

    Bernatowicz, Kinga; Geets, Xavier; Barragan, Ana; Janssens, Guillaume; Souris, Kevin; Sterpin, Edmond


    Intensity-modulated proton therapy (IMPT) offers excellent dose conformity and healthy tissue sparing, but it can be substantially compromised in the presence of anatomical changes. A major dosimetric effect is caused by density changes, which alter the planned proton range in the patient. Three different methods, which automatically restore an IMPT plan dose on a daily CT image were implemented and compared: (1) simple dose restoration (DR) using optimization objectives of the initial plan, (2) voxel-wise dose restoration (vDR), and (3) isodose volume dose restoration (iDR). Dose restorations were calculated for three different clinical cases, selected to test different capabilities of the restoration methods: large range adaptation, complex dose distributions and robust re-optimization. All dose restorations were obtained in less than 5 min, without manual adjustments of the optimization settings. The evaluation of initial plans on repeated CTs showed large dose distortions, which were substantially reduced after restoration. In general, all dose restoration methods improved DVH-based scores in propagated target volumes and OARs. Analysis of local dose differences showed that, although all dose restorations performed similarly in high dose regions, iDR restored the initial dose with higher precision and accuracy in the whole patient anatomy. Median dose errors decreased from 13.55 Gy in distorted plan to 9.75 Gy (vDR), 6.2 Gy (DR) and 4.3 Gy (iDR). High quality dose restoration is essential to minimize or eventually by-pass the physician approval of the restored plan, as long as dose stability can be assumed. Motion (as well as setup and range uncertainties) can be taken into account by including robust optimization in the dose restoration. Restoring clinically-approved dose distribution on repeated CTs does not require new ROI segmentation and is compatible with an online adaptive workflow.

  17. Evidence of "hidden hearing loss" following noise exposures that produce robust TTS and ABR wave-I amplitude reductions. (United States)

    Lobarinas, Edward; Spankovich, Christopher; Le Prell, Colleen G


    In animals, noise exposures that produce robust temporary threshold shifts (TTS) can produce immediate damage to afferent synapses and long-term degeneration of low spontaneous rate auditory nerve fibers. This synaptopathic damage has been shown to correlate with reduced auditory brainstem response (ABR) wave-I amplitudes at suprathreshold levels. The perceptual consequences of this "synaptopathy" remain unknown but have been suggested to include compromised hearing performance in competing background noise. Here, we used a modified startle inhibition paradigm to evaluate whether noise exposures that produce robust TTS and ABR wave-I reduction but not permanent threshold shift (PTS) reduced hearing-in-noise performance. Animals exposed to 109 dB SPL octave band noise showed TTS >30 dB 24-h post noise and modest but persistent ABR wave-I reduction 2 weeks post noise despite full recovery of ABR thresholds. Hearing-in-noise performance was negatively affected by the noise exposure. However, the effect was observed only at the poorest signal to noise ratio and was frequency specific. Although TTS >30 dB 24-h post noise was a predictor of functional deficits, there was no relationship between the degree of ABR wave-I reduction and degree of functional impairment. Copyright © 2016 Elsevier B.V. All rights reserved.

  18. Nonlatching positive feedback enables robust bimodality by decoupling expression noise from the mean (United States)

    Razooky, Brandon S.; Cao, Youfang; Hansen, Maike M. K.; Perelson, Alan S.; Simpson, Michael L.


    Fundamental to biological decision-making is the ability to generate bimodal expression patterns where 2 alternate expression states simultaneously exist. Here, we use a combination of single-cell analysis and mathematical modeling to examine the sources of bimodality in the transcriptional program controlling HIV’s fate decision between active replication and viral latency. We find that the HIV transactivator of transcription (Tat) protein manipulates the intrinsic toggling of HIV’s promoter, the long terminal repeat (LTR), to generate bimodal ON-OFF expression and that transcriptional positive feedback from Tat shifts and expands the regime of LTR bimodality. This result holds for both minimal synthetic viral circuits and full-length virus. Strikingly, computational analysis indicates that the Tat circuit’s noncooperative “nonlatching” feedback architecture is optimized to slow the promoter’s toggling and generate bimodality by stochastic extinction of Tat. In contrast to the standard Poisson model, theory and experiment show that nonlatching positive feedback substantially dampens the inverse noise-mean relationship to maintain stochastic bimodality despite increasing mean expression levels. Given the rapid evolution of HIV, the presence of a circuit optimized to robustly generate bimodal expression appears consistent with the hypothesis that HIV’s decision between active replication and latency provides a viral fitness advantage. More broadly, the results suggest that positive-feedback circuits may have evolved not only for signal amplification but also for robustly generating bimodality by decoupling expression fluctuations (noise) from mean expression levels. PMID:29045398

  19. Nonlatching positive feedback enables robust bimodality by decoupling expression noise from the mean

    Energy Technology Data Exchange (ETDEWEB)

    Razooky, Brandon S. [Rockefeller Univ., New York, NY (United States). Lab. of Virology and Infectious Disease; Gladstone Institutes (Virology and Immunology), San Francisco, CA (United States); Univ. of California, San Francisco, CA (United States); Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States). Center for Nanophase Materials Science (CNMS); Univ. of Tennessee, Knoxville, TN (United States). Bredesen Center for Interdisciplinary; Cao, Youfang [Los Alamos National Lab. (LANL), Los Alamos, NM (United States); Hansen, Maike M. K. [Gladstone Institutes (Virology and Immunology), San Francisco, CA (United States); Perelson, Alan S. [Los Alamos National Lab. (LANL), Los Alamos, NM (United States); Simpson, Michael L. [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States). Center for Nanophase Materials Science (CNMS); Univ. of Tennessee, Knoxville, TN (United States). Bredesen Center for Interdisciplinary; Weinberger, Leor S. [Gladstone Institutes (Virology and Immunology), San Francisco, CA (United States); Univ. of California, San Francisco, CA (United States). Dept. of Biochemistry and Biophysics; Univ. of California, San Francisco, CA (United States). QB3: California Inst. of Quantitative Biosciences; Univ. of California, San Francisco, CA (United States). Dept. of Pharmaceutical Chemistry


    Fundamental to biological decision-making is the ability to generate bimodal expression patterns where two alternate expression states simultaneously exist. Here in this study, we use a combination of single-cell analysis and mathematical modeling to examine the sources of bimodality in the transcriptional program controlling HIV’s fate decision between active replication and viral latency. We find that the HIV Tat protein manipulates the intrinsic toggling of HIV’s promoter, the LTR, to generate bimodal ON-OFF expression, and that transcriptional positive feedback from Tat shifts and expands the regime of LTR bimodality. This result holds for both minimal synthetic viral circuits and full-length virus. Strikingly, computational analysis indicates that the Tat circuit’s non-cooperative ‘non-latching’ feedback architecture is optimized to slow the promoter’s toggling and generate bimodality by stochastic extinction of Tat. In contrast to the standard Poisson model, theory and experiment show that non-latching positive feedback substantially dampens the inverse noise-mean relationship to maintain stochastic bimodality despite increasing mean-expression levels. Given the rapid evolution of HIV, the presence of a circuit optimized to robustly generate bimodal expression appears consistent with the hypothesis that HIV’s decision between active replication and latency provides a viral fitness advantage. More broadly, the results suggest that positive-feedback circuits may have evolved not only for signal amplification but also for robustly generating bimodality by decoupling expression fluctuations (noise) from mean expression levels.

  20. Fully integrated low-noise readout circuit with automatic offset cancellation loop for capacitive microsensors. (United States)

    Song, Haryong; Park, Yunjong; Kim, Hyungseup; Cho, Dong-Il Dan; Ko, Hyoungho


    Capacitive sensing schemes are widely used for various microsensors; however, such microsensors suffer from severe parasitic capacitance problems. This paper presents a fully integrated low-noise readout circuit with automatic offset cancellation loop (AOCL) for capacitive microsensors. The output offsets of the capacitive sensing chain due to the parasitic capacitances and process variations are automatically removed using AOCL. The AOCL generates electrically equivalent offset capacitance and enables charge-domain fine calibration using a 10-bit R-2R digital-to-analog converter, charge-transfer switches, and a charge-storing capacitor. The AOCL cancels the unwanted offset by binary-search algorithm based on 10-bit successive approximation register (SAR) logic. The chip is implemented using 0.18 μm complementary metal-oxide-semiconductor (CMOS) process with an active area of 1.76 mm². The power consumption is 220 μW with 3.3 V supply. The input parasitic capacitances within the range of -250 fF to 250 fF can be cancelled out automatically, and the required calibration time is lower than 10 ms.

  1. Robust Wavelet Estimation to Eliminate Simultaneously the Effects of Boundary Problems, Outliers, and Correlated Noise

    Directory of Open Access Journals (Sweden)

    Alsaidi M. Altaher


    Full Text Available Classical wavelet thresholding methods suffer from boundary problems caused by the application of the wavelet transformations to a finite signal. As a result, large bias at the edges and artificial wiggles occur when the classical boundary assumptions are not satisfied. Although polynomial wavelet regression and local polynomial wavelet regression effectively reduce the risk of this problem, the estimates from these two methods can be easily affected by the presence of correlated noise and outliers, giving inaccurate estimates. This paper introduces two robust methods in which the effects of boundary problems, outliers, and correlated noise are simultaneously taken into account. The proposed methods combine thresholding estimator with either a local polynomial model or a polynomial model using the generalized least squares method instead of the ordinary one. A primary step that involves removing the outlying observations through a statistical function is considered as well. The practical performance of the proposed methods has been evaluated through simulation experiments and real data examples. The results are strong evidence that the proposed method is extremely effective in terms of correcting the boundary bias and eliminating the effects of outliers and correlated noise.

  2. Inversion of seismic arrival times with erratic noise using robust Tikhonov-TV regularization (United States)

    Alrajawi, M.; Siahkoohi, H. R.; Gholami, A.


    A variety of methods have been presented to invert arrival times of seismic waves for velocity distribution. In real world, the velocity distribution models are piecewise smooth and consist of blocky structures as well as smooth varying parts. In such cases, implementation of Tikhonov regularization alone will recover the smooth varying parts of the velocity model, while the total variation (TV) regularization only is capable of recovering the blocky varying parts of the velocity model. In previous studies, combination of Tikhonov and TV regularizations (hereafter called classic Tikhonov-TV regularization) was used as a remedy for solving such inverse problems. In this study, we propose a method to minimize a cost function which of both Tikhonov and TV regularizations. The method is capable of suppressing undesired effects of the erratic noises and recovering both blocky and smooth varying parts of the model. An iteratively reweighted least-squares technique is used as a fast and efficient algorithm for minimization of the cost function. To demonstrate the effectiveness of the method, it is tested on both synthetic and real vertical seismic profiling arrival times as well as on a synthetic and real cross well arrival times. The proposed robust Tikhonov-TV method estimates better velocity model as compared to the robust Tikhonov and robust TV regularization methods. According to the results, the proposed hybrid method efficiently eliminates the individual weaknesses of constituent regularization methods.

  3. Multi-stream LSTM-HMM decoding and histogram equalization for noise robust keyword spotting. (United States)

    Wöllmer, Martin; Marchi, Erik; Squartini, Stefano; Schuller, Björn


    Highly spontaneous, conversational, and potentially emotional and noisy speech is known to be a challenge for today's automatic speech recognition (ASR) systems, which highlights the need for advanced algorithms that improve speech features and models. Histogram Equalization is an efficient method to reduce the mismatch between clean and noisy conditions by normalizing all moments of the probability distribution of the feature vector components. In this article, we propose to combine histogram equalization and multi-condition training for robust keyword detection in noisy speech. To better cope with conversational speaking styles, we show how contextual information can be effectively exploited in a multi-stream ASR framework that dynamically models context-sensitive phoneme estimates generated by a long short-term memory neural network. The proposed techniques are evaluated on the SEMAINE database-a corpus containing emotionally colored conversations with a cognitive system for "Sensitive Artificial Listening".

  4. Advanced Quantitative Robust Control Engineering: New Solutions for Automatic Loop-Shaping for SISO and MIMO Systems. Part 1: SISO Systems (United States)


    Report 3. DATES COVERED (From – To) 17 September 2008 - 17-Sep-09 4. TITLE AND SUBTITLE Advanced Quantitative Robust Control Engineering : New...083027 Date: 1.September.2009 Page 1 Advanced Quantitative Robust Control Engineering : New Solutions for Automatic Loop-shaping for SISO...and MIMO Systems.Part 1: SISO Systems. Advanced Quantitative Robust Control Engineering : New Solutions for Automatic Loop-Shaping for SISO and

  5. Enhancement of Motion Estimation Robustness Against Noise and Brightness Variations in Digital Image Sequences

    Directory of Open Access Journals (Sweden)

    Homayoun Mahdavi-Nasab


    Full Text Available Motion estimation and compensation are main stages in hybrid video coding standards. Due to structural simplicity the block-matching motion estimation is the most used method in digital video technology. In recent years the mesh-based motion estimation is considered by the researchers because of its more complex motion models and lack of blocking artifacts. However, mesh-based motion estimation suffers from error propagation and weak performance in noisy and brightness varying conditions. In this paper motion adaptive interpolation functions are proposed for the mesh-based motion estimation to overcome these problems. The simulation results show the better robustness of the proposed scheme against noise and brightness variations, not only regarding to mesh-based but also block-matching motion estimation techniques.

  6. Towards social touch intelligence: developing a robust system for automatic touch recognition

    NARCIS (Netherlands)

    Jung, Merel Madeleine


    Touch behavior is of great importance during social interaction. Automatic recognition of social touch is necessary to transfer the touch modality from interpersonal interaction to other areas such as Human-Robot Interaction (HRI). This paper describes a PhD research program on the automatic

  7. Robust automatic intelligibility assessment techniques evaluated on speakers treated for head and neck cancer

    NARCIS (Netherlands)

    Middag, C.; Clapham, R.; van Son, R.; Martens, J-P.


    It is generally acknowledged that an unbiased and objective assessment of the communication deficiency caused by a speech disorder calls for automatic speech processing tools. In this paper, a new automatic intelligibility assessment method is presented. The method can predict running speech

  8. Automatic bearing fault diagnosis of permanent magnet synchronous generators in wind turbines subjected to noise interference (United States)

    Guo, Jun; Lu, Siliang; Zhai, Chao; He, Qingbo


    An automatic bearing fault diagnosis method is proposed for permanent magnet synchronous generators (PMSGs), which are widely installed in wind turbines subjected to low rotating speeds, speed fluctuations, and electrical device noise interferences. The mechanical rotating angle curve is first extracted from the phase current of a PMSG by sequentially applying a series of algorithms. The synchronous sampled vibration signal of the fault bearing is then resampled in the angular domain according to the obtained rotating phase information. Considering that the resampled vibration signal is still overwhelmed by heavy background noise, an adaptive stochastic resonance filter is applied to the resampled signal to enhance the fault indicator and facilitate bearing fault identification. Two types of fault bearings with different fault sizes in a PMSG test rig are subjected to experiments to test the effectiveness of the proposed method. The proposed method is fully automated and thus shows potential for convenient, highly efficient and in situ bearing fault diagnosis for wind turbines subjected to harsh environments.

  9. The role of binary mask patterns in automatic speech recognition in background noise. (United States)

    Narayanan, Arun; Wang, DeLiang


    Processing noisy signals using the ideal binary mask improves automatic speech recognition (ASR) performance. This paper presents the first study that investigates the role of binary mask patterns in ASR under various noises, signal-to-noise ratios (SNRs), and vocabulary sizes. Binary masks are computed either by comparing the SNR within a time-frequency unit of a mixture signal with a local criterion (LC), or by comparing the local target energy with the long-term average spectral energy of speech. ASR results show that (1) akin to human speech recognition, binary masking significantly improves ASR performance even when the SNR is as low as -60 dB; (2) the ASR performance profiles are qualitatively similar to those obtained in human intelligibility experiments; (3) the difference between the LC and mixture SNR is more correlated to the recognition accuracy than LC; (4) LC at which the performance peaks is lower than 0 dB, which is the threshold that maximizes the SNR gain of processed signals. This broad agreement with human performance is rather surprising. The results also indicate that maximizing the SNR gain is probably not an appropriate goal for improving either human or machine recognition of noisy speech.

  10. A Low-Power Wireless Image Sensor Node with Noise-Robust Moving Object Detection and a Region-of-Interest Based Rate Controller (United States)


    A Low-Power Wireless Image Sensor Node with Noise-Robust Moving Object Detection and a Region-of-Interest Based Rate Controller Jong Hwan Ko...military surveillance, with a noise-robust moving object detection and region-of-interest based rate controller . The improved robustness to noise...from both environment and hardware further reduces the transmission energy with negligible computation and memory overhead. The rate controller

  11. The benefit obtained from visually displayed text from an automatic speech recognizer during listening to speech presented in noise

    NARCIS (Netherlands)

    Zekveld, A.A.; Kramer, S.E.; Kessens, J.M.; Vlaming, M.S.M.G.; Houtgast, T.


    OBJECTIVES: The aim of this study was to evaluate the benefit that listeners obtain from visually presented output from an automatic speech recognition (ASR) system during listening to speech in noise. DESIGN: Auditory-alone and audiovisual speech reception thresholds (SRTs) were measured. The SRT

  12. A new robust markerless method for automatic image-to-patient registration in image-guided neurosurgery system. (United States)

    Liu, Yinlong; Song, Zhijian; Wang, Manning


    Compared with the traditional point-based registration in the image-guided neurosurgery system, surface-based registration is preferable because it does not use fiducial markers before image scanning and does not require image acquisition dedicated for navigation purposes. However, most existing surface-based registration methods must include a manual step for coarse registration, which increases the registration time and elicits some inconvenience and uncertainty. A new automatic surface-based registration method is proposed, which applies 3D surface feature description and matching algorithm to obtain point correspondences for coarse registration and uses the iterative closest point (ICP) algorithm in the last step to obtain an image-to-patient registration. Both phantom and clinical data were used to execute automatic registrations and target registration error (TRE) calculated to verify the practicality and robustness of the proposed method. In phantom experiments, the registration accuracy was stable across different downsampling resolutions (18-26 mm) and different support radii (2-6 mm). In clinical experiments, the mean TREs of two patients by registering full head surfaces were 1.30 mm and 1.85 mm. This study introduced a new robust automatic surface-based registration method based on 3D feature matching. The method achieved sufficient registration accuracy with different real-world surface regions in phantom and clinical experiments.

  13. Robustness of SOC Estimation Algorithms for EV Lithium-Ion Batteries against Modeling Errors and Measurement Noise

    Directory of Open Access Journals (Sweden)

    Xue Li


    Full Text Available State of charge (SOC is one of the most important parameters in battery management system (BMS. There are numerous algorithms for SOC estimation, mostly of model-based observer/filter types such as Kalman filters, closed-loop observers, and robust observers. Modeling errors and measurement noises have critical impact on accuracy of SOC estimation in these algorithms. This paper is a comparative study of robustness of SOC estimation algorithms against modeling errors and measurement noises. By using a typical battery platform for vehicle applications with sensor noise and battery aging characterization, three popular and representative SOC estimation methods (extended Kalman filter, PI-controlled observer, and H∞ observer are compared on such robustness. The simulation and experimental results demonstrate that deterioration of SOC estimation accuracy under modeling errors resulted from aging and larger measurement noise, which is quantitatively characterized. The findings of this paper provide useful information on the following aspects: (1 how SOC estimation accuracy depends on modeling reliability and voltage measurement accuracy; (2 pros and cons of typical SOC estimators in their robustness and reliability; (3 guidelines for requirements on battery system identification and sensor selections.

  14. Robust AlGaN/GaN Low Noise Amplifier MMICs for C-, Ku- and Ka-Band Space Applications

    NARCIS (Netherlands)

    Suijker, E.M.; Rodenburg, M.; Hoogland, J.A.; van Heijningen, M; Seelmann-Eggebert, M.; Quay, R.; Bruckner, P.; van Vliet, Frank Edward


    Abstract The high power capabilities in combination with the low noise performance of gallium nitride (GaN) makes this technology an excellent choice for robust receivers. This paper presents the design and measured results of three different LNAs, which operate in C-, Ku-, and Ka-band. The designs

  15. Resolution and robustness to noise of the sensitivity-based method for microwave imaging with data acquired on cylindrical surfaces

    International Nuclear Information System (INIS)

    Zhang, Yifan; Tu, Sheng; Amineh, Reza K; Nikolova, Natalia K


    The spatial resolution limit of a Jacobian-based microwave imaging algorithm and its robustness to noise are evaluated. The focus here is on tomographic systems where the wideband data are acquired with a vertically scanned circular sensor array and at each scanning step a 2D image is reconstructed in the plane of the sensor array. The theoretical resolution is obtained as one-half of the maximum-frequency wavelength with far-zone data and about two-thirds of the array radius with near-zone data. Validation examples are given using analytical electromagnetic models. The algorithm is shown to be robust to noise when the response data are corrupted by Gaussian white noise. (paper)

  16. Iterative reconstruction and automatic tube voltage selection reduce clinical CT radiation doses and image noise. (United States)

    O'Hora, L; Foley, S J


    Computed Tomography (CT) use has increased in recent years with trends indicating increasing population doses as a result. Optimization of clinical radiation doses through technological developments has demonstrated potential to reduce patient dose from CT. This study aimed to quantify these dose reductions across a large clinical cohort. Patient cohort was divided into three groups, assigned by CT optimisation technique. Group one underwent scanning with automated tube current modulation only. Group two underwent scanning with automated tube current modulation and iterative reconstruction and group three underwent scanning with automated tube current modulation, iterative reconstruction and automatic tube voltage modulation. Patient dose length product doses were retrospectively collected for the three groups. Clinical radiation doses between the groups were compared for four common CT examinations (Brain, pulmonary angiography, abdomen and thorax abdomen pelvis scans). Of 4011 patients, group one comprised of 1643 patients (40.96%), group two 1077 patients (26.85%) and group three 1291 patients (32.19%). No differences were found when comparing AP diameter between groups (p ≥ 0.05). Statistically significant dose reductions of 16-31% were achieved using iterative reconstruction alone (p = 0.001) and 24-42% with both iterative reconstruction and automatic tube voltage selection (p = 0.001). Objective noise improved when iterative reconstruction was used (p staff and procedural protocols remaining consistent throughout. Dose reductions are likely to reflect the clinical dose reducing potential of the optimization software investigated. Copyright © 2017 The College of Radiographers. Published by Elsevier Ltd. All rights reserved.

  17. Advancing Noise Robust Automatic Speech Recognition for Command and Control Applications

    National Research Council Canada - National Science Library

    Bass, James D


    .... The reliable elimination of the keyboard and mouse in mounted and un-mounted C2 systems has been a desire of systems developers and requirements writers since the development of PC-based ASR systems in the early 1990...

  18. Robust fuzzy control subject to state variance and passivity constraints for perturbed nonlinear systems with multiplicative noises. (United States)

    Chang, Wen-Jer; Huang, Bo-Jyun


    The multi-constrained robust fuzzy control problem is investigated in this paper for perturbed continuous-time nonlinear stochastic systems. The nonlinear system considered in this paper is represented by a Takagi-Sugeno fuzzy model with perturbations and state multiplicative noises. The multiple performance constraints considered in this paper include stability, passivity and individual state variance constraints. The Lyapunov stability theory is employed to derive sufficient conditions to achieve the above performance constraints. By solving these sufficient conditions, the contribution of this paper is to develop a parallel distributed compensation based robust fuzzy control approach to satisfy multiple performance constraints for perturbed nonlinear systems with multiplicative noises. At last, a numerical example for the control of perturbed inverted pendulum system is provided to illustrate the applicability and effectiveness of the proposed multi-constrained robust fuzzy control method. Copyright © 2014 ISA. Published by Elsevier Ltd. All rights reserved.

  19. Research on an Automatic Measurement of Impulse Electromagnetic Noise (IV) : Relation of Electromagnetic Induction Noise and Malfunction of Print Circuits


    佐野, 博也; 松本, 史生; サノ, ヒロヤ; マツモト, フミオ; Hiroya, SANO; Fumio, MATUMOTO


    Experimental studies were made on electromagnetic susceptibility and malfunction of high speed CMOS digital printed circuit boards (PCB). We measured the induced noise voltage on a printed loop circuit caused by electromagnetic emission from an adjacent digital PCB. Electromagnetic susceptibility of a bus circuit was measured with a TEM cell in frequency range of 10 to 250 MHz. The induced noise increased near the resonance frequency of the circuit. We also measured the amplitude of noise vol...

  20. Robust automatic high resolution segmentation of SOFC anode porosity in 3D

    DEFF Research Database (Denmark)

    Jørgensen, Peter Stanley; Bowen, Jacob R.


    Routine use of 3D characterization of SOFCs by focused ion beam (FIB) serial sectioning is generally restricted by the time consuming task of manually delineating structures within each image slice. We apply advanced image analysis algorithms to automatically segment the porosity phase of an SOFC...

  1. A Noise-Assisted Data Analysis Method for Automatic EOG-Based Sleep Stage Classification Using Ensemble Learning. (United States)

    Olesen, Alexander Neergaard; Christensen, Julie A E; Sorensen, Helge B D; Jennum, Poul J


    Reducing the number of recording modalities for sleep staging research can benefit both researchers and patients, under the condition that they provide as accurate results as conventional systems. This paper investigates the possibility of exploiting the multisource nature of the electrooculography (EOG) signals by presenting a method for automatic sleep staging using the complete ensemble empirical mode decomposition with adaptive noise algorithm, and a random forest classifier. It achieves a high overall accuracy of 82% and a Cohen's kappa of 0.74 indicating substantial agreement between automatic and manual scoring.

  2. Robust shot-noise measurement for continuous-variable quantum key distribution (United States)

    Kunz-Jacques, Sébastien; Jouguet, Paul


    We study a practical method to measure the shot noise in real time in continuous-variable quantum key distribution systems. The amount of secret key that can be extracted from the raw statistics depends strongly on this quantity since it affects in particular the computation of the excess noise (i.e., noise in excess of the shot noise) added by an eavesdropper on the quantum channel. Some powerful quantum hacking attacks relying on faking the estimated value of the shot noise to hide an intercept and resend strategy were proposed. Here, we provide experimental evidence that our method can defeat the saturation attack and the wavelength attack.

  3. Automatic Generation of Machine Emulators: Efficient Synthesis of Robust Virtual Machines for Legacy Software Migration

    DEFF Research Database (Denmark)

    Franz, Michael; Gal, Andreas; Probst, Christian


    As older mainframe architectures become obsolete, the corresponding le- gacy software is increasingly executed via platform emulators running on top of more modern commodity hardware. These emulators are virtual machines that often include a combination of interpreters and just-in-time compilers....... Implementing interpreters and compilers for each combination of emulated and target platform independently of each other is a redundant and error-prone task. We describe an alternative approach that automatically synthesizes specialized virtual-machine interpreters and just-in-time compilers, which...

  4. Stochastic models of cellular circadian rhythms in plants help to understand the impact of noise on robustness and clock structure

    Directory of Open Access Journals (Sweden)

    Maria Luisa eGuerriero


    Full Text Available Rhythmic behavior is essential for plants; for example, daily (circadian rhythms control photosynthesis and seasonal rhythms regulate their life cycle. The core of the circadian clock is a genetic network that coordinates the expression of specific clock genes in a circadian rhythm reflecting the 24-hour day/night cycle.Circadian clocks exhibit stochastic noise due to the low copy numbers of clock genes and the consequent cell-to-cell variation: this intrinsic noise plays a major role in circadian clocks by inducing more robust oscillatory behavior. Another source of noise is the environment, which causes variation in temperature and light intensity: this extrinsic noise is part of the requirement for the structural complexity of clock networks.Advances in experimental techniques now permit single-cell measurements and the development of single-cell models. Here we present some modeling studies showing the importance of considering both types of noise in understanding how plants adapt to regular and irregular light variations. Stochastic models have proven useful for understanding the effect of regular variations. By contrast, the impact of irregular variations and the interaction of different noise sources are less studied.

  5. Stochastic models of cellular circadian rhythms in plants help to understand the impact of noise on robustness and clock structure (United States)

    Guerriero, Maria L.; Akman, Ozgur E.; van Ooijen, Gerben


    Rhythmic behavior is essential for plants; for example, daily (circadian) rhythms control photosynthesis and seasonal rhythms regulate their life cycle. The core of the circadian clock is a genetic network that coordinates the expression of specific clock genes in a circadian rhythm reflecting the 24-h day/night cycle. Circadian clocks exhibit stochastic noise due to the low copy numbers of clock genes and the consequent cell-to-cell variation: this intrinsic noise plays a major role in circadian clocks by inducing more robust oscillatory behavior. Another source of noise is the environment, which causes variation in temperature and light intensity: this extrinsic noise is part of the requirement for the structural complexity of clock networks. Advances in experimental techniques now permit single-cell measurements and the development of single-cell models. Here we present some modeling studies showing the importance of considering both types of noise in understanding how plants adapt to regular and irregular light variations. Stochastic models have proven useful for understanding the effect of regular variations. By contrast, the impact of irregular variations and the interaction of different noise sources are less well studied. PMID:25374576

  6. Robust driver heartbeat estimation: A q-Hurst exponent based automatic sensor change with interactive multi-model EKF. (United States)

    Vrazic, Sacha


    Preventing car accidents by monitoring the driver's physiological parameters is of high importance. However, existing measurement methods are not robust to driver's body movements. In this paper, a system that estimates the heartbeat from the seat embedded piezoelectric sensors, and that is robust to strong body movements is presented. Multifractal q-Hurst exponents are used within a classifier to predict the most probable best sensor signal to be used in an Interactive Multi-Model Extended Kalman Filter pulsation estimation procedure. The car vibration noise is reduced using an autoregressive exogenous model to predict the noise on sensors. The performance of the proposed system was evaluated on real driving data up to 100 km/h and with slaloms at high speed. It is shown that this method improves by 36.7% the pulsation estimation under strong body movement compared to static sensor pulsation estimation and appears to provide reliable pulsation variability information for top-level analysis of drowsiness or other conditions.

  7. A method for blind automatic evaluation of noise variance in images based on bootstrap and myriad operations (United States)

    Lukin, Vladimir V.; Abramov, Sergey K.; Vozel, Benoit; Chehdi, Kacem


    Multichannel (multispectral) remote sensing (MRS) is widely used for various applications nowadays. However, original images are commonly corrupted by noise and other distortions. This prevents reliable retrieval of useful information from remote sensing data. Because of this, image pre-filtering and/or reconstruction are typical stages of multichannel image processing. And majority of modern efficient methods for image pre-processing requires availability of a priori information concerning noise type and its statistical characteristics. Thus, there is a great need in automatic blind methods for determination of noise type and its characteristics. However, almost all such methods fail to perform appropriately well if an image under consideration contains a large percentage of texture regions, details and edges. In this paper we demonstrate that by applying bootstrap it is possible to obtain rather accurate estimates of noise variance that can be used either as the final or preliminary ones. Different quantiles (order statistics) are used as initial estimates of mode location for distribution of noise variance local estimations and then bootstrap is applied for their joint analysis. To further improve accuracy of noise variance estimations, it is proposed under certain condition to apply myriad operation with tunable parameter k set in accordance with preliminary estimate obtained by bootstrap. Numerical simulation results confirm applicability of the proposed approach and produce data allowing to evaluate method accuracy.

  8. A Robust Automatic Ionospheric O/X Mode Separation Technique for Vertical Incidence Sounders (United States)

    Harris, T. J.; Pederick, L. H.


    The sounding of the ionosphere by a vertical incidence sounder (VIS) is the oldest and most common technique for determining the state of the ionosphere. The automatic extraction of relevant ionospheric parameters from the ionogram image, referred to as scaling, is important for the effective utilization of data from large ionospheric sounder networks. Due to the Earth's magnetic field, the ionosphere is birefringent at radio frequencies, so a VIS will typically see two distinct returns for each frequency. For the automatic scaling of ionograms, it is highly desirable to be able to separate the two modes. Defence Science and Technology Group has developed a new VIS solution which is based on direct digital receiver technology and includes an algorithm to separate the O and X modes. This algorithm can provide high-quality separation even in difficult ionospheric conditions. In this paper we describe the algorithm and demonstrate its consistency and reliability in successfully separating 99.4% of the ionograms during a 27 day experimental campaign under sometimes demanding ionospheric conditions.

  9. QFT Based Robust Positioning Control of the PMSM Using Automatic Loop Shaping with Teaching Learning Optimization

    Directory of Open Access Journals (Sweden)

    Nitish Katal


    Full Text Available Automation of the robust control system synthesis for uncertain systems is of great practical interest. In this paper, the loop shaping step for synthesizing quantitative feedback theory (QFT based controller for a two-phase permanent magnet stepper motor (PMSM has been automated using teaching learning-based optimization (TLBO algorithm. The QFT controller design problem has been posed as an optimization problem and TLBO algorithm has been used to minimize the proposed cost function. This facilitates designing low-order fixed-structure controller, eliminates the need of manual loop shaping step on the Nichols charts, and prevents the overdesign of the controller. A performance comparison of the designed controller has been made with the classical PID tuning method of Ziegler-Nichols and QFT controller tuned using other optimization algorithms. The simulation results show that the designed QFT controller using TLBO offers robust stability, disturbance rejection, and proper reference tracking over a range of PMSM’s parametric uncertainties as compared to the classical design techniques.

  10. An Automatic K-Means Clustering Algorithm of GPS Data Combining a Novel Niche Genetic Algorithm with Noise and Density

    Directory of Open Access Journals (Sweden)

    Xiangbing Zhou


    Full Text Available Rapidly growing Global Positioning System (GPS data plays an important role in trajectory and their applications (e.g., GPS-enabled smart devices. In order to employ K-means to mine the better origins and destinations (OD behind the GPS data and overcome its shortcomings including slowness of convergence, sensitivity to initial seeds selection, and getting stuck in a local optimum, this paper proposes and focuses on a novel niche genetic algorithm (NGA with density and noise for K-means clustering (NoiseClust. In NoiseClust, an improved noise method and K-means++ are proposed to produce the initial population and capture higher quality seeds that can automatically determine the proper number of clusters, and also handle the different sizes and shapes of genes. A density-based method is presented to divide the number of niches, with its aim to maintain population diversity. Adaptive probabilities of crossover and mutation are also employed to prevent the convergence to a local optimum. Finally, the centers (the best chromosome are obtained and then fed into the K-means as initial seeds to generate even higher quality clustering results by allowing the initial seeds to readjust as needed. Experimental results based on taxi GPS data sets demonstrate that NoiseClust has high performance and effectiveness, and easily mine the city’s situations in four taxi GPS data sets.

  11. Robust spinal cord resting-state fMRI using independent component analysis-based nuisance regression noise reduction. (United States)

    Hu, Yong; Jin, Richu; Li, Guangsheng; Luk, Keith Dk; Wu, Ed X


    Physiological noise reduction plays a critical role in spinal cord (SC) resting-state fMRI (rsfMRI). To reduce physiological noise and increase the robustness of SC rsfMRI by using an independent component analysis (ICA)-based nuisance regression (ICANR) method. Retrospective. Ten healthy subjects (female/male = 4/6, age = 27 ± 3 years, range 24-34 years). 3T/gradient-echo echo planar imaging (EPI). We used three alternative methods (no regression [Nil], conventional region of interest [ROI]-based noise reduction method without ICA [ROI-based], and correction of structured noise using spatial independent component analysis [CORSICA]) to compare with the performance of ICANR. Reduction of the influence of physiological noise on the SC and the reproducibility of rsfMRI analysis after noise reduction were examined. The correlation coefficient (CC) was calculated to assess the influence of physiological noise. Reproducibility was calculated by intraclass correlation (ICC). Results from different methods were compared by one-way analysis of variance (ANOVA) with post-hoc analysis. No significant difference in cerebrospinal fluid (CSF) pulsation influence or tissue motion influence were found (P = 0.223 in CSF, P = 0.2461 in tissue motion) in the ROI-based (CSF: 0.122 ± 0.020; tissue motion: 0.112 ± 0.015), and Nil (CSF: 0.134 ± 0.026; tissue motion: 0.124 ± 0.019). CORSICA showed a significantly stronger influence of CSF pulsation and tissue motion (CSF: 0.166 ± 0.045, P = 0.048; tissue motion: 0.160 ± 0.032, P = 0.048) than Nil. ICANR showed a significantly weaker influence of CSF pulsation and tissue motion (CSF: 0.076 ± 0.007, P = 0.0003; tissue motion: 0.081 ± 0.014, P = 0.0182) than Nil. The ICC values in the Nil, ROI-based, CORSICA, and ICANR were 0.669, 0.645, 0.561, and 0.766, respectively. ICANR more effectively reduced physiological noise from both tissue motion and CSF pulsation than three alternative methods. ICANR increases the robustness of SC rsf

  12. Automatic post-implant needle reconstruction algorithm to characterize and improve implant robustness analyses

    International Nuclear Information System (INIS)

    Archambault, Louis; Beaulieu, Luc; Tubic, Dragan


    Post-implant analysis in permanent implant brachytherapy is an important process that provides a feedback on treatment quality. Random seed movements, edema, and needle related factors contribute to deteriorate dose coverage. For a complete study of these movements, it is important to reconstruct the post-implant seeds clusters but, up to now, this task was only possible via a long and difficult manual process. To facilitate post-implant analysis a simulated annealing algorithm was developed to perform automatic reconstructions. This process is fast (30-60 s on a 1.3 GHz pentium) and has a high level of success, even with up to 5% of seed loss. Tests on 21 clinical cases show that the algorithm yields exactly the same results as manual reconstructions. A realistic simulation tool was used to generate 58 synthetic post-implant data, in which cases the exact configuration was known. Even if some errors were found, pertinent information was extracted. For medium seed density [corresponding to seeds of 0.6 mCi (0.762 U)], 97% of seeds are matched with their correct needle and 89% are matched with their correct planned position. This method provides pertinent information that can be used to understand inhomogenous dose coverage in specific prostate quadrants; to make realistic post-implant simulations or to identify seeds belonging to a needle loaded with different seed types or activity

  13. Weighted Robust Adaptive Filtering in Krein Space and Its Application in Active Noise Control

    NARCIS (Netherlands)

    Jayawardhana, Bayu; Yuan, Shuqing; Xie, Lihua


    Robust adaptive filtering ensures the minimization of the transfer function from the disturbance to the estimation error and thus, guarantees the robustness against the worst-case disturbance in the system. However, a more general approach will be given in this paper hy employing frequency

  14. A Robust Approach For Acoustic Noise Suppression In Speech Using ANFIS (United States)

    Martinek, Radek; Kelnar, Michal; Vanus, Jan; Bilik, Petr; Zidek, Jan


    The authors of this article deals with the implementation of a combination of techniques of the fuzzy system and artificial intelligence in the application area of non-linear noise and interference suppression. This structure used is called an Adaptive Neuro Fuzzy Inference System (ANFIS). This system finds practical use mainly in audio telephone (mobile) communication in a noisy environment (transport, production halls, sports matches, etc). Experimental methods based on the two-input adaptive noise cancellation concept was clearly outlined. Within the experiments carried out, the authors created, based on the ANFIS structure, a comprehensive system for adaptive suppression of unwanted background interference that occurs in audio communication and degrades the audio signal. The system designed has been tested on real voice signals. This article presents the investigation and comparison amongst three distinct approaches to noise cancellation in speech; they are LMS (least mean squares) and RLS (recursive least squares) adaptive filtering and ANFIS. A careful review of literatures indicated the importance of non-linear adaptive algorithms over linear ones in noise cancellation. It was concluded that the ANFIS approach had the overall best performance as it efficiently cancelled noise even in highly noise-degraded speech. Results were drawn from the successful experimentation, subjective-based tests were used to analyse their comparative performance while objective tests were used to validate them. Implementation of algorithms was experimentally carried out in Matlab to justify the claims and determine their relative performances.

  15. A robust and semi-automatic procedure for Silicon Photomultipliers characterisation (United States)

    Arosio, V.; Beretta, M.; Caccia, M.; Santoro, R.


    Silicon Photomultipliers are state-of-the-art solid state sensors of light with single photon sensitivity, unprecedented photon number resolving capability and high photon detection efficiency. SiPM are cost effective, compact, magnetic field insensitive and with an extreme flexibility in the design to cope with different applications in fundamental and applied science and industry. As a rapidly evolving technology, new generation of sensors are being continuously proposed by different producers, requiring the development of reliable and efficient SiPM characterisation methods to perform a quick assessment and comparison. The procedure presented here is based on post-processing of digitised SiPM waveforms recording the response of the sensor to an ultra-fast light pulse. For every pulse, the signal is synchronously sampled, digitised and recorded on the timescale of a few microseconds with the objective of extracting from a single set of waveforms a full picture of the sensor characteristics in terms of Gain, Breakdown Voltage, Dark Count Rate , Optical Cross-Talk and After Pulse probability. The need of a unique and consistent data-set guarantees a fast and robust characterisation, stable against environmental condition changes, notably temperature.

  16. A robust automatic leukocyte recognition method based on island-clustering texture

    Directory of Open Access Journals (Sweden)

    Xiaoshun Li


    Full Text Available A leukocyte recognition method for human peripheral blood smear based on island-clustering texture (ICT is proposed. By analyzing the features of the five typical classes of leukocyte images, a new ICT model is established. Firstly, some feature points are extracted in a gray leukocyte image by mean-shift clustering to be the centers of islands. Secondly, the growing region is employed to create regions of the islands in which the seeds are just these feature points. These islands distribution can describe a new texture. Finally, a distinguished parameter vector of these islands is created as the ICT features by combining the ICT features with the geometric features of the leukocyte. Then the five typical classes of leukocytes can be recognized successfully at the correct recognition rate of more than 92.3% with a total sample of 1310 leukocytes. Experimental results show the feasibility of the proposed method. Further analysis reveals that the method is robust and results can provide important information for disease diagnosis.

  17. Experimental investigation of the robustness against noise for different Bell-type inequalities in three-qubit Greenberger-Horne-Zeilinger states

    International Nuclear Information System (INIS)

    Lu Huaixin; Zhao Jiaqiang; Cao Lianzhen; Wang Xiaoqin


    There are different families of inequalities that can be used to characterize the entanglement of multiqubit entangled states by the violation of quantum mechanics prediction versus local realism prediction. In a noisy environment, the violation of different inequalities distinguishes a direct from a noise-free environment. That is, each inequality has a different robustness against noise. We investigate theoretically and experimentally this proposition with the Mermin inequality, Bell inequality, and Svetlichny inequality using three-qubit GHZ states for different levels of noise. Our purpose is to determine which one of the inequalities is more robust against noise and thus more suitable to characterize entanglement of states. Our results show that the Mermin inequality is the most robust against stronger noise and is, thus, more suitable for characterizing the entanglement of three-qubit GHZ states in a noisy environment.

  18. The area-of-interest problem in eyetracking research: A noise-robust solution for face and sparse stimuli. (United States)

    Hessels, Roy S; Kemner, Chantal; van den Boomen, Carlijn; Hooge, Ignace T C


    A problem in eyetracking research is choosing areas of interest (AOIs): Researchers in the same field often use widely varying AOIs for similar stimuli, making cross-study comparisons difficult or even impossible. Subjective choices while choosing AOIs cause differences in AOI shape, size, and location. On the other hand, not many guidelines for constructing AOIs, or comparisons between AOI-production methods, are available. In the present study, we addressed this gap by comparing AOI-production methods in face stimuli, using data collected with infants and adults (with autism spectrum disorder [ASD] and matched controls). Specifically, we report that the attention-attracting and attention-maintaining capacities of AOIs differ between AOI-production methods, and that this matters for statistical comparisons in one of three groups investigated (the ASD group). In addition, we investigated the relation between AOI size and an AOI's attention-attracting and attention-maintaining capacities, as well as the consequences for statistical analyses, and report that adopting large AOIs solves the problem of statistical differences between the AOI methods. Finally, we tested AOI-production methods for their robustness to noise, and report that large AOIs-using the Voronoi tessellation method or the limited-radius Voronoi tessellation method with large radii-are most robust to noise. We conclude that large AOIs are a noise-robust solution in face stimuli and, when implemented using the Voronoi method, are the most objective of the researcher-defined AOIs. Adopting Voronoi AOIs in face-scanning research should allow better between-group and cross-study comparisons.

  19. Noise Robust Face Image Super-Resolution Through Smooth Sparse Representation. (United States)

    Jiang, Junjun; Ma, Jiayi; Chen, Chen; Jiang, Xinwei; Wang, Zheng


    Face image super-resolution has attracted much attention in recent years. Many algorithms have been proposed. Among them, sparse representation (SR)-based face image super-resolution approaches are able to achieve competitive performance. However, these SR-based approaches only perform well under the condition that the input is noiseless or has small noise. When the input is corrupted by large noise, the reconstruction weights (or coefficients) of the input low-resolution (LR) patches using SR-based approaches will be seriously unstable, thus leading to poor reconstruction results. To this end, in this paper, we propose a novel SR-based face image super-resolution approach that incorporates smooth priors to enforce similar training patches having similar sparse coding coefficients. Specifically, we introduce the fused least absolute shrinkage and selection operator-based smooth constraint and locality-based smooth constraint to the least squares representation-based patch representation in order to obtain stable reconstruction weights, especially when the noise level of the input LR image is high. Experiments are carried out on the benchmark FEI face database and CMU+MIT face database. Visual and quantitative comparisons show that the proposed face image super-resolution method yields superior reconstruction results when the input LR face image is contaminated by strong noise.

  20. Noise Robust Monitoring of Lombard Speech Using a Wireless Necksurface Accelerometer and Microphone (United States)


    Observations of the relationship between noise exposure and preschool teacher voice usage in day -care center environments,” J. Voice, 25(2):166-172...Jensen, Z. R., Rolins, M. K., and Whiting, J. K., “ Teachers and teaching: Speech production accommodations due to changes in the acoustic environment

  1. Virtual sensors for active noise control in acoustic-structural coupled enclosures using structural sensing: robust virtual sensor design. (United States)

    Halim, Dunant; Cheng, Li; Su, Zhongqing


    The work was aimed to develop a robust virtual sensing design methodology for sensing and active control applications of vibro-acoustic systems. The proposed virtual sensor was designed to estimate a broadband acoustic interior sound pressure using structural sensors, with robustness against certain dynamic uncertainties occurring in an acoustic-structural coupled enclosure. A convex combination of Kalman sub-filters was used during the design, accommodating different sets of perturbed dynamic model of the vibro-acoustic enclosure. A minimax optimization problem was set up to determine an optimal convex combination of Kalman sub-filters, ensuring an optimal worst-case virtual sensing performance. The virtual sensing and active noise control performance was numerically investigated on a rectangular panel-cavity system. It was demonstrated that the proposed virtual sensor could accurately estimate the interior sound pressure, particularly the one dominated by cavity-controlled modes, by using a structural sensor. With such a virtual sensing technique, effective active noise control performance was also obtained even for the worst-case dynamics. © 2011 Acoustical Society of America

  2. Fast and robust automatic calibration for single-shot dual-wavelength digital holography based on speckle displacements. (United States)

    Khodadad, Davood; Bergström, Per; Hällstig, Emil; Sjödahl, Mikael


    The objective of this paper is to describe a fast and robust automatic single-shot dual-wavelength holographic calibration method that can be used for online shape measurement applications. We present a model of the correction in two terms for each lobe, one to compensate the systematic errors caused by off-axis angles and the other for the curvature of the reference waves, respectively. Each hologram is calibrated independently without a need for an iterative procedure or information of the experimental set-up. The calibration parameters are extracted directly from speckle displacements between different reconstruction planes. The parameters can be defined as any fraction of a pixel to avoid the effect of quantization. Using the speckle displacements, problems associated with phase wrapping is avoided. The procedure is shown to give a shape accuracy of 34 μm using a synthetic wavelength of 1.1 mm for a measurement on a cylindrical test object with a trace over a field of view of 18  mm×18  mm.

  3. Robust Sequential Circuits Design Technique for Low Voltage and High Noise Scenarios

    Directory of Open Access Journals (Sweden)

    Garcia-Leyva Lancelot


    In this paper we introduce an innovative input and output data redundancy principle for sequential block circuits, the responsible to keep the state of the system, showing its efficiency in front of other robust technique approaches. The methodology is totally different from the Von Neumann approaches, because element are not replicated N times, but instead, they check the coherence of redundant input data no allowing data propagation in case of discrepancy. This mechanism does not require voting devices.

  4. Noise (United States)

    Noise is all around you, from televisions and radios to lawn mowers and washing machines. Normally, you ... sensitive structures of the inner ear and cause noise-induced hearing loss. More than 30 million Americans ...

  5. Automatic IMU sensor characterization using Allan variance plots (United States)

    Skurowski, Przemysław; Paszkuta, Marcin


    We present an automatic method for the evaluation of the noise parameters of IMU devices. The method is a the two-stage optimization problem for polyline regression of the Allan variance in log-log domain. We address the initialization issue and segmentation to identify the existing noises which results in the robustness of the results obtained with the numerical solver.

  6. Investigation of neural network paradigms for the development of automatic noise diagnostic/reactor surveillance systems

    International Nuclear Information System (INIS)

    Korsah, K.; Uhrig, R.E.


    The use of artificial intelligence (AI) techniques as an aid in the maintenance and operation of nuclear power plant systems has been recognized for the past several years, and several applications using expert systems technology currently exist. The authors investigated the backpropagation paradigm for the recognition of neutron noise power spectral density (PSD) signatures as a possible alternative to current methods based on statistical techniques. The goal is to advance the state of the art in the application of noise analysis techniques to monitor nuclear reactor internals. Continuous surveillance of reactor systems for structural degradation can be quite cost-effective because (1) the loss of mechanical integrity of the reactor internal components can be detected at an early stage before severe damage occurs, (2) unnecessary periodic maintenance can be avoided, (3) plant downtime can be reduced to a minimum, (4) a high level of plant safety can be maintained, and (5) it can be used to help justify the extension of a plant's operating license. The initial objectives were to use neutron noise PSD data from a pressurized water reactor, acquired over a period of ∼2 years by the Oak Ridge National Laboratory (ORNL) Power Spectral Density RECognition (PSDREC) system to develop networks that can (1) differentiate between normal neutron spectral data and anomalous spectral data (e.g., malfunctioning instrumentation); and (2) detect significant shifts in the positions of spectral resonances while reducing the effect of small, random shifts (in neutron noise analysis, shifts in the resonance(s) present in a neutron PSD spectrum are the primary means for diagnosing degradation of reactor internals). 11 refs, 8 figs

  7. Robust Frame Synchronization for Low Signal-to-Noise Ratio Channels Using Energy-Corrected Differential Correlation

    Directory of Open Access Journals (Sweden)

    Kim Pansoo


    Full Text Available Recent standards for wireless transmission require reliable synchronization for channels with low signal-to-noise ratio (SNR as well as with a large amount of frequency offset, which necessitates a robust correlator structure for the initial frame synchronization process. In this paper, a new correlation strategy especially targeted for low SNR regions is proposed and its performance is analyzed. By utilizing a modified energy correction term, the proposed method effectively reduces the variance of the decision variable to enhance the detection performance. Most importantly, the method is demonstrated to outperform all previously reported schemes by a significant margin, for SNRs below 5 dB regardless of the existence of the frequency offsets. A variation of the proposed method is also presented for further enhancement over the channels with small frequency errors. The particular application considered for the performance verification is the second generation digital video broadcasting system for satellites (DVB-S2.

  8. Denoising of B1+ field maps for noise-robust image reconstruction in electrical properties tomography

    International Nuclear Information System (INIS)

    Michel, Eric; Hernandez, Daniel; Cho, Min Hyoung; Lee, Soo Yeol


    Purpose: To validate the use of adaptive nonlinear filters in reconstructing conductivity and permittivity images from the noisy B 1 + maps in electrical properties tomography (EPT). Methods: In EPT, electrical property images are computed by taking Laplacian of the B 1 + maps. To mitigate the noise amplification in computing the Laplacian, the authors applied adaptive nonlinear denoising filters to the measured complex B 1 + maps. After the denoising process, they computed the Laplacian by central differences. They performed EPT experiments on phantoms and a human brain at 3 T along with corresponding EPT simulations on finite-difference time-domain models. They evaluated the EPT images comparing them with the ones obtained by previous EPT reconstruction methods. Results: In both the EPT simulations and experiments, the nonlinear filtering greatly improved the EPT image quality when evaluated in terms of the mean and standard deviation of the electrical property values at the regions of interest. The proposed method also improved the overall similarity between the reconstructed conductivity images and the true shapes of the conductivity distribution. Conclusions: The nonlinear denoising enabled us to obtain better-quality EPT images of the phantoms and the human brain at 3 T

  9. Charisma: an integrated approach to automatic H&E-stained skeletal muscle cell segmentation using supervised learning and novel robust clump splitting. (United States)

    Janssens, Thomas; Antanas, Laura; Derde, Sarah; Vanhorebeek, Ilse; Van den Berghe, Greet; Güiza Grandas, Fabian


    Histological image analysis plays a key role in understanding the effects of disease and treatment responses at the cellular level. However, evaluating histology images by hand is time-consuming and subjective. While semi-automatic and automatic approaches for image segmentation give acceptable results in some branches of histological image analysis, until now this has not been the case when applied to skeletal muscle histology images. We introduce Charisma, a new top-down cell segmentation framework for histology images which combines image processing techniques, a supervised trained classifier and a novel robust clump splitting algorithm. We evaluate our framework on real-world data from intensive care unit patients. Considering both segmentation and cell property distributions, the results obtained by our method correspond well to the ground truth, outperforming other examined methods. Copyright © 2013 Elsevier B.V. All rights reserved.

  10. Synthesis of multi-wavelength temporal phase-shifting algorithms optimized for high signal-to-noise ratio and high detuning robustness using the frequency transfer function. (United States)

    Servin, Manuel; Padilla, Moises; Garnica, Guillermo


    Synthesis of single-wavelength temporal phase-shifting algorithms (PSA) for interferometry is well-known and firmly based on the frequency transfer function (FTF) paradigm. Here we extend the single-wavelength FTF-theory to dual and multi-wavelength PSA-synthesis when several simultaneous laser-colors are present. The FTF-based synthesis for dual-wavelength (DW) PSA is optimized for high signal-to-noise ratio and minimum number of temporal phase-shifted interferograms. The DW-PSA synthesis herein presented may be used for interferometric contouring of discontinuous industrial objects. Also DW-PSA may be useful for DW shop-testing of deep free-form aspheres. As shown here, using the FTF-based synthesis one may easily find explicit DW-PSA formulae optimized for high signal-to-noise and high detuning robustness. To this date, no general synthesis and analysis for temporal DW-PSAs has been given; only ad hoc DW-PSAs formulas have been reported. Consequently, no explicit formulae for their spectra, their signal-to-noise, their detuning and harmonic robustness has been given. Here for the first time a fully general procedure for designing DW-PSAs (or triple-wavelengths PSAs) with desire spectrum, signal-to-noise ratio and detuning robustness is given. We finally generalize DW-PSA to higher number of wavelength temporal PSAs.

  11. A turbo engine with automatic transmission? How to many chemicomotion to the subtleties and robustness of life

    DEFF Research Database (Denmark)

    Koefoed, S.; Otten, M.F.; Købmann, Brian Jensen


    benefits of the turbo-charging of catabolic pathways, of loose coupling, low-gear catabolism, automatic transmission in energy coupling, and of homeostasis. Mechanisms for such phenomena may reside at the level of individual proton pumps, or consist of rerouting of electrons over parallel pathways...

  12. Robust random telegraph conductivity noise in single crystals of the ferromagnetic insulating manganite La0.86Ca0.14MnO3 (United States)

    Przybytek, J.; Fink-Finowicki, J.; Puźniak, R.; Shames, A.; Markovich, V.; Mogilyansky, D.; Jung, G.


    Robust random telegraph conductivity fluctuations have been observed in La0.86Ca0.14MnO3 manganite single crystals. At room temperatures, the spectra of conductivity fluctuations are featureless and follow a 1 /f shape in the entire experimental frequency and bias range. Upon lowering the temperature, clear Lorentzian bias-dependent excess noise appears on the 1 /f background and eventually dominates the spectral behavior. In the time domain, fully developed Lorentzian noise appears as pronounced two-level random telegraph noise with a thermally activated switching rate, which does not depend on bias current and applied magnetic field. The telegraph noise is very robust and persists in the exceptionally wide temperature range of more than 50 K. The amplitude of the telegraph noise decreases exponentially with increasing bias current in exactly the same manner as the sample resistance increases with the current, pointing out the dynamic current redistribution between percolation paths dominated by phase-separated clusters with different conductivity as a possible origin of two-level conductivity fluctuations.

  13. Automatic Subspace Learning via Principal Coefficients Embedding. (United States)

    Peng, Xi; Lu, Jiwen; Yi, Zhang; Yan, Rui


    In this paper, we address two challenging problems in unsupervised subspace learning: 1) how to automatically identify the feature dimension of the learned subspace (i.e., automatic subspace learning) and 2) how to learn the underlying subspace in the presence of Gaussian noise (i.e., robust subspace learning). We show that these two problems can be simultaneously solved by proposing a new method [(called principal coefficients embedding (PCE)]. For a given data set , PCE recovers a clean data set from and simultaneously learns a global reconstruction relation of . By preserving into an -dimensional space, the proposed method obtains a projection matrix that can capture the latent manifold structure of , where is automatically determined by the rank of with theoretical guarantees. PCE has three advantages: 1) it can automatically determine the feature dimension even though data are sampled from a union of multiple linear subspaces in presence of the Gaussian noise; 2) although the objective function of PCE only considers the Gaussian noise, experimental results show that it is robust to the non-Gaussian noise (e.g., random pixel corruption) and real disguises; and 3) our method has a closed-form solution and can be calculated very fast. Extensive experimental results show the superiority of PCE on a range of databases with respect to the classification accuracy, robustness, and efficiency.

  14. A robust and accurate two-stage approach for automatic recovery of distal locking holes in computer-assisted intramedullary nailing of femoral shaft fractures. (United States)

    Zheng, Guoyan; Zhang, Xuan; Haschtmann, Daniel; Gedet, Philippe; Dong, Xiao; Nolte, Lutz-Peter


    It has been recognized that one of the most difficult steps in intramedullary nailing of femoral shaft fractures is the distal locking - the insertion of distal transverse interlocking screws, for which it is necessary to know the positions and orientations of the distal locking holes (DLHs) of the intramedullary nail (IMN). This paper presents a robust and accurate approach for solving this problem based on two calibrated and registered fluoroscopic images. The problem is formulated as a two-stage model-based optimal fitting process. The first stage, nail detection, automatically estimates the axis of the distal part of the IMN (DP-IMN) by iteratively fitting a cylindrical model to the images. The second stage, pose recovery, resolves the translations and the rotations of the DLHs around the estimated axis by iteratively fitting the geometrical models of the DLHs to the images. An iterative best matched projection point (IBMPP) algorithm is combined with random sample strategies to effectively and robustly solve the fitting problems in both stages. We designed and conducted comprehensive experiments to validate the robustness and the accuracy of the present approach. Our in vitro experiments show on average less than 14 s execution time on a Linux machine, a mean angular error of 0.48 degrees (std = 0.21 degrees ), and a mean translational error of 0.09 mm (std = 0.041 mm). We conclude that the present approach is fast, robust, and accurate for distal locking applications.

  15. Robustness and precision of an automatic marker detection algorithm for online prostate daily targeting using a standard V-EPID. (United States)

    Aubin, S; Beaulieu, L; Pouliot, S; Pouliot, J; Roy, R; Girouard, L M; Martel-Brisson, N; Vigneault, E; Laverdière, J


    An algorithm for the daily localization of the prostate using implanted markers and a standard video-based electronic portal imaging device (V-EPID) has been tested. Prior to planning, three gold markers were implanted in the prostate of seven patients. The clinical images were acquired with a BeamViewPlus 2.1 V-EPID for each field during the normal course radiotherapy treatment and are used off-line to determine the ability of the automatic marker detection algorithm to adequately and consistently detect the markers. Clinical images were obtained with various dose levels from ranging 2.5 to 75 MU. The algorithm is based on marker attenuation characterization in the portal image and spatial distribution. A total of 1182 clinical images were taken. The results show an average efficiency of 93% for the markers detected individually and 85% for the group of markers. This algorithm accomplishes the detection and validation in 0.20-0.40 s. When the center of mass of the group of implanted markers is used, then all displacements can be corrected to within 1.0 mm in 84% of the cases and within 1.5 mm in 97% of cases. The standard video-based EPID tested provides excellent marker detection capability even with low dose levels. The V-EPID can be used successfully with radiopaque markers and the automatic detection algorithm to track and correct the daily setup deviations due to organ motions.

  16. Talker- and language-specific effects on speech intelligibility in noise assessed with bilingual talkers: Which language is more robust against noise and reverberation? (United States)

    Hochmuth, Sabine; Jürgens, Tim; Brand, Thomas; Kollmeier, Birger


    Investigate talker- and language-specific aspects of speech intelligibility in noise and reverberation using highly comparable matrix sentence tests across languages. Matrix sentences spoken by German/Russian and German/Spanish bilingual talkers were recorded. These sentences were used to measure speech reception thresholds (SRTs) with native listeners in the respective languages in different listening conditions (stationary and fluctuating noise, multi-talker babble, reverberated speech-in-noise condition). Four German/Russian and four German/Spanish bilingual talkers; 20 native German-speaking, 10 native Russian-speaking, and 10 native Spanish-speaking listeners. Across-talker SRT differences of up to 6 dB were found for both groups of bilinguals. SRTs of German/Russian bilingual talkers were the same in both languages. SRTs of German/Spanish bilingual talkers were higher when they talked in Spanish than when they talked in German. The benefit from listening in the gaps was similar across all languages. The detrimental effect of reverberation was larger for Spanish than for German and Russian. Within the limitations set by the number and slight accentedness of talkers and other possible confounding factors, talker- and test-condition-dependent differences were isolated from the language effect: Russian and German exhibited similar intelligibility in noise and reverberation, whereas Spanish was more impaired in these situations.

  17. Fast, accurate, and robust automatic marker detection for motion correction based on oblique kV or MV projection image pairs

    International Nuclear Information System (INIS)

    Slagmolen, Pieter; Hermans, Jeroen; Maes, Frederik; Budiharto, Tom; Haustermans, Karin; Heuvel, Frank van den


    Purpose: A robust and accurate method that allows the automatic detection of fiducial markers in MV and kV projection image pairs is proposed. The method allows to automatically correct for inter or intrafraction motion. Methods: Intratreatment MV projection images are acquired during each of five treatment beams of prostate cancer patients with four implanted fiducial markers. The projection images are first preprocessed using a series of marker enhancing filters. 2D candidate marker locations are generated for each of the filtered projection images and 3D candidate marker locations are reconstructed by pairing candidates in subsequent projection images. The correct marker positions are retrieved in 3D by the minimization of a cost function that combines 2D image intensity and 3D geometric or shape information for the entire marker configuration simultaneously. This optimization problem is solved using dynamic programming such that the globally optimal configuration for all markers is always found. Translational interfraction and intrafraction prostate motion and the required patient repositioning is assessed from the position of the centroid of the detected markers in different MV image pairs. The method was validated on a phantom using CT as ground-truth and on clinical data sets of 16 patients using manual marker annotations as ground-truth. Results: The entire setup was confirmed to be accurate to around 1 mm by the phantom measurements. The reproducibility of the manual marker selection was less than 3.5 pixels in the MV images. In patient images, markers were correctly identified in at least 99% of the cases for anterior projection images and 96% of the cases for oblique projection images. The average marker detection accuracy was 1.4±1.8 pixels in the projection images. The centroid of all four reconstructed marker positions in 3D was positioned within 2 mm of the ground-truth position in 99.73% of all cases. Detecting four markers in a pair of MV images

  18. Automatic minimization of ocular artifacts fromelectroencephalogram: A novel approach by combining CompleteEEMD with Adaptive Noise and Renyi’s Entropy

    DEFF Research Database (Denmark)

    Guarascio, Mario; Puthusserypady, Sadasivan


    evaluated on simulated OAs (one, two, and several blinks as well as saccadic eye movements)corrupted EEG signals and then extended to real EEG signals. The signal-to-noise ratio improvement(SNRimp) along with time and power spectral density (PSD) plots are used for evaluating the performanceof the scheme....... The method is compared to the one based on the CEEMDAN and manual choice of IMFsfor OAs minimization from EEG. Results from extensive simulation studies clearly indicate the efficacyof the proposed scheme in automatically minimizing the OAs from the corrupted EEG signals....

  19. A robust, high-throughput method for computing maize ear, cob, and kernel attributes automatically from images. (United States)

    Miller, Nathan D; Haase, Nicholas J; Lee, Jonghyun; Kaeppler, Shawn M; de Leon, Natalia; Spalding, Edgar P


    Grain yield of the maize plant depends on the sizes, shapes, and numbers of ears and the kernels they bear. An automated pipeline that can measure these components of yield from easily-obtained digital images is needed to advance our understanding of this globally important crop. Here we present three custom algorithms designed to compute such yield components automatically from digital images acquired by a low-cost platform. One algorithm determines the average space each kernel occupies along the cob axis using a sliding-window Fourier transform analysis of image intensity features. A second counts individual kernels removed from ears, including those in clusters. A third measures each kernel's major and minor axis after a Bayesian analysis of contour points identifies the kernel tip. Dimensionless ear and kernel shape traits that may interrelate yield components are measured by principal components analysis of contour point sets. Increased objectivity and speed compared to typical manual methods are achieved without loss of accuracy as evidenced by high correlations with ground truth measurements and simulated data. Millimeter-scale differences among ear, cob, and kernel traits that ranged more than 2.5-fold across a diverse group of inbred maize lines were resolved. This system for measuring maize ear, cob, and kernel attributes is being used by multiple research groups as an automated Web service running on community high-throughput computing and distributed data storage infrastructure. Users may create their own workflow using the source code that is staged for download on a public repository. © 2016 The Authors. The Plant Journal published by Society for Experimental Biology and John Wiley & Sons Ltd.

  20. Accuracy Maximization Analysis for Sensory-Perceptual Tasks: Computational Improvements, Filter Robustness, and Coding Advantages for Scaled Additive Noise.

    Directory of Open Access Journals (Sweden)

    Johannes Burge


    Full Text Available Accuracy Maximization Analysis (AMA is a recently developed Bayesian ideal observer method for task-specific dimensionality reduction. Given a training set of proximal stimuli (e.g. retinal images, a response noise model, and a cost function, AMA returns the filters (i.e. receptive fields that extract the most useful stimulus features for estimating a user-specified latent variable from those stimuli. Here, we first contribute two technical advances that significantly reduce AMA's compute time: we derive gradients of cost functions for which two popular estimators are appropriate, and we implement a stochastic gradient descent (AMA-SGD routine for filter learning. Next, we show how the method can be used to simultaneously probe the impact on neural encoding of natural stimulus variability, the prior over the latent variable, noise power, and the choice of cost function. Then, we examine the geometry of AMA's unique combination of properties that distinguish it from better-known statistical methods. Using binocular disparity estimation as a concrete test case, we develop insights that have general implications for understanding neural encoding and decoding in a broad class of fundamental sensory-perceptual tasks connected to the energy model. Specifically, we find that non-orthogonal (partially redundant filters with scaled additive noise tend to outperform orthogonal filters with constant additive noise; non-orthogonal filters and scaled additive noise can interact to sculpt noise-induced stimulus encoding uncertainty to match task-irrelevant stimulus variability. Thus, we show that some properties of neural response thought to be biophysical nuisances can confer coding advantages to neural systems. Finally, we speculate that, if repurposed for the problem of neural systems identification, AMA may be able to overcome a fundamental limitation of standard subunit model estimation. As natural stimuli become more widely used in the study of

  1. Accuracy Maximization Analysis for Sensory-Perceptual Tasks: Computational Improvements, Filter Robustness, and Coding Advantages for Scaled Additive Noise. (United States)

    Burge, Johannes; Jaini, Priyank


    Accuracy Maximization Analysis (AMA) is a recently developed Bayesian ideal observer method for task-specific dimensionality reduction. Given a training set of proximal stimuli (e.g. retinal images), a response noise model, and a cost function, AMA returns the filters (i.e. receptive fields) that extract the most useful stimulus features for estimating a user-specified latent variable from those stimuli. Here, we first contribute two technical advances that significantly reduce AMA's compute time: we derive gradients of cost functions for which two popular estimators are appropriate, and we implement a stochastic gradient descent (AMA-SGD) routine for filter learning. Next, we show how the method can be used to simultaneously probe the impact on neural encoding of natural stimulus variability, the prior over the latent variable, noise power, and the choice of cost function. Then, we examine the geometry of AMA's unique combination of properties that distinguish it from better-known statistical methods. Using binocular disparity estimation as a concrete test case, we develop insights that have general implications for understanding neural encoding and decoding in a broad class of fundamental sensory-perceptual tasks connected to the energy model. Specifically, we find that non-orthogonal (partially redundant) filters with scaled additive noise tend to outperform orthogonal filters with constant additive noise; non-orthogonal filters and scaled additive noise can interact to sculpt noise-induced stimulus encoding uncertainty to match task-irrelevant stimulus variability. Thus, we show that some properties of neural response thought to be biophysical nuisances can confer coding advantages to neural systems. Finally, we speculate that, if repurposed for the problem of neural systems identification, AMA may be able to overcome a fundamental limitation of standard subunit model estimation. As natural stimuli become more widely used in the study of psychophysical and

  2. Structural noise from automatic exposure control device and its relationship to X-ray tube voltage used for calibration of a flat-panel detector system. (United States)

    Mizuta, Masayoshi; Akazawa, Hiroyuki; Kasai, Toshifumi; Sanada, Shigeru; Abe, Shuji; Mitou, Shigeki


    In flat-panel detector (FPD) systems, the ion-chamber dosimeters used for automatic exposure control (AEC), which are placed between the detector and the source, should not affect clinical images because of FPD gain correction, but can sometimes still introduce fixed-pattern noise. In this study, we investigated whether such artifacts were caused by structural noise from the AEC detector on the basis of the noise power spectrum (NPS) and the mean square error (MSE) of FPD images taken at various tube voltages either with or without the AEC detector. When the NPS was measured without the AEC detector, the NPS did not increase in the low special-frequency band at all radiation qualities tested, irrespective of X-ray calibration tube voltages. However, when the NPS was measured while the AEC detector was used, the NPS increased in the low special-frequency band at all radiation qualities when the X-ray calibration tube voltages were at low levels. Similarly, the MSE increased when the X-ray calibration tube voltages were at low levels. From these results, artifacts in the AEC detector appear to be suppressed when a radiation quality of approximately 90 kV is used at four different standardized radiations quality (RQA3, RQA5, RQA7, and RQA9).

  3. Robust, fully automatic delineation of the head contour by stereotactical normalization for attenuation correction according to Chang in dopamine transporter scintigraphy

    Energy Technology Data Exchange (ETDEWEB)

    Lange, Catharina; Brenner, Winfried; Buchert, Ralph [Charite - Universitaetsmedizin Berlin, Department of Nuclear Medicine, Berlin (Germany); Kurth, Jens; Schwarzenboeck, Sarah; Krause, Bernd J. [Universitaetsmedizin Rostock, Department of Nuclear Medicine, Rostock (Germany); Seese, Anita; Steinhoff, Karen; Sabri, Osama; Hesse, Swen [Universitaetsklinikum Leipzig, Department of Nuclear Medicine, Leipzig (Germany); Umland-Seidler, Bert [GE Healthcare Buchler GmbH and Co. KG, Munich (Germany)


    Chang's method, the most widely used attenuation correction (AC) in brain single-photon emission computed tomography (SPECT), requires delineation of the outer contour of the head. Manual and automatic threshold-based methods are prone to errors due to variability of tracer uptake in the scalp. The present study proposes a new method for fully automated delineation of the head based on stereotactical normalization. The method was validated for SPECT with I-123-ioflupane. The new method was compared to threshold-based delineation in 62 unselected patients who had received I-123-ioflupane SPECT at one of 3 centres. The impact on diagnostic power was tested for semi-quantitative analysis and visual reading of the SPECT images (six independent readers). The two delineation methods produced highly consistent semi-quantitative results. This was confirmed by receiver operating characteristic analyses in which the putamen specific-to-background ratio achieved highest area under the curve with negligible effect of the delineation method: 0.935 versus 0.938 for stereotactical normalization and threshold-based delineation, respectively. Visual interpretation of DVR images was also not affected by the delineation method. Delineation of the head contour by stereotactical normalization appears useful for Chang AC in I-123-ioflupane SPECT. It is robust and does not require user interaction. (orig.)

  4. Liquid chromatography-mass spectrometry platform for both small neurotransmitters and neuropeptides in blood, with automatic and robust solid phase extraction (United States)

    Johnsen, Elin; Leknes, Siri; Wilson, Steven Ray; Lundanes, Elsa


    Neurons communicate via chemical signals called neurotransmitters (NTs). The numerous identified NTs can have very different physiochemical properties (solubility, charge, size etc.), so quantification of the various NT classes traditionally requires several analytical platforms/methodologies. We here report that a diverse range of NTs, e.g. peptides oxytocin and vasopressin, monoamines adrenaline and serotonin, and amino acid GABA, can be simultaneously identified/measured in small samples, using an analytical platform based on liquid chromatography and high-resolution mass spectrometry (LC-MS). The automated platform is cost-efficient as manual sample preparation steps and one-time-use equipment are kept to a minimum. Zwitter-ionic HILIC stationary phases were used for both on-line solid phase extraction (SPE) and liquid chromatography (capillary format, cLC). This approach enabled compounds from all NT classes to elute in small volumes producing sharp and symmetric signals, and allowing precise quantifications of small samples, demonstrated with whole blood (100 microliters per sample). An additional robustness-enhancing feature is automatic filtration/filter back-flushing (AFFL), allowing hundreds of samples to be analyzed without any parts needing replacement. The platform can be installed by simple modification of a conventional LC-MS system.

  5. Robustness of spiking Deep Belief Networks to noise and reduced bit precision of neuro-inspired hardware platforms (United States)

    Stromatias, Evangelos; Neil, Daniel; Pfeiffer, Michael; Galluppi, Francesco; Furber, Steve B.; Liu, Shih-Chii


    Increasingly large deep learning architectures, such as Deep Belief Networks (DBNs) are the focus of current machine learning research and achieve state-of-the-art results in different domains. However, both training and execution of large-scale Deep Networks require vast computing resources, leading to high power requirements and communication overheads. The on-going work on design and construction of spike-based hardware platforms offers an alternative for running deep neural networks with significantly lower power consumption, but has to overcome hardware limitations in terms of noise and limited weight precision, as well as noise inherent in the sensor signal. This article investigates how such hardware constraints impact the performance of spiking neural network implementations of DBNs. In particular, the influence of limited bit precision during execution and training, and the impact of silicon mismatch in the synaptic weight parameters of custom hybrid VLSI implementations is studied. Furthermore, the network performance of spiking DBNs is characterized with regard to noise in the spiking input signal. Our results demonstrate that spiking DBNs can tolerate very low levels of hardware bit precision down to almost two bits, and show that their performance can be improved by at least 30% through an adapted training mechanism that takes the bit precision of the target platform into account. Spiking DBNs thus present an important use-case for large-scale hybrid analog-digital or digital neuromorphic platforms such as SpiNNaker, which can execute large but precision-constrained deep networks in real time. PMID:26217169

  6. Noise effects on robust synchronization of a small pacemaker neuronal ensemble via nonlinear controller: electronic circuit design. (United States)

    Megam Ngouonkadi, Elie Bertrand; Fotsin, Hilaire Bertrand; Kabong Nono, Martial; Louodop Fotso, Patrick Herve


    In this paper, we report on the synchronization of a pacemaker neuronal ensemble constituted of an AB neuron electrically coupled to two PD neurons. By the virtue of this electrical coupling, they can fire synchronous bursts of action potential. An external master neuron is used to induce to the whole system the desired dynamics, via a nonlinear controller. Such controller is obtained by a combination of sliding mode and feedback control. The proposed controller is able to offset uncertainties in the synchronized systems. We show how noise affects the synchronization of the pacemaker neuronal ensemble, and briefly discuss its potential benefits in our synchronization scheme. An extended Hindmarsh-Rose neuronal model is used to represent a single cell dynamic of the network. Numerical simulations and Pspice implementation of the synchronization scheme are presented. We found that, the proposed controller reduces the stochastic resonance of the network when its gain increases.

  7. Robust, low-noise, polarization-maintaining mode-locked Er-fiber laser with a planar lightwave circuit (PLC) device as a multi-functional element. (United States)

    Kim, Chur; Kwon, Dohyeon; Kim, Dohyun; Choi, Sun Young; Cha, Sang Jun; Choi, Ki Sun; Yeom, Dong-Il; Rotermund, Fabian; Kim, Jungwon


    We demonstrate a new planar lightwave circuit (PLC)-based device, integrated with a 980/1550 wavelength division multiplexer, an evanescent-field-interaction-based saturable absorber, and an output tap coupler, which can be employed as a multi-functional element in mode-locked fiber lasers. Using this multi-functional PLC device, we demonstrate a simple, robust, low-noise, and polarization-maintaining mode-locked Er-fiber laser. The measured full-width at half-maximum bandwidth is 6 nm centered at 1555 nm, corresponding to 217 fs transform-limited pulse duration. The measured RIN and timing jitter are 0.22% [10 Hz-10 MHz] and 6.6 fs [10 kHz-1 MHz], respectively. Our results show that the non-gain section of mode-locked fiber lasers can be easily implemented as a single PLC chip that can be manufactured by a wafer-scale fabrication process. The use of PLC processes in mode-locked lasers has the potential for higher manufacturability of low-cost and robust fiber and waveguide lasers.

  8. Pan-Antarctic analysis aggregating spatial estimates of Adélie penguin abundance reveals robust dynamics despite stochastic noise. (United States)

    Che-Castaldo, Christian; Jenouvrier, Stephanie; Youngflesh, Casey; Shoemaker, Kevin T; Humphries, Grant; McDowall, Philip; Landrum, Laura; Holland, Marika M; Li, Yun; Ji, Rubao; Lynch, Heather J


    Colonially-breeding seabirds have long served as indicator species for the health of the oceans on which they depend. Abundance and breeding data are repeatedly collected at fixed study sites in the hopes that changes in abundance and productivity may be useful for adaptive management of marine resources, but their suitability for this purpose is often unknown. To address this, we fit a Bayesian population dynamics model that includes process and observation error to all known Adélie penguin abundance data (1982-2015) in the Antarctic, covering >95% of their population globally. We find that process error exceeds observation error in this system, and that continent-wide "year effects" strongly influence population growth rates. Our findings have important implications for the use of Adélie penguins in Southern Ocean feedback management, and suggest that aggregating abundance across space provides the fastest reliable signal of true population change for species whose dynamics are driven by stochastic processes.Adélie penguins are a key Antarctic indicator species, but data patchiness has challenged efforts to link population dynamics to key drivers. Che-Castaldo et al. resolve this issue using a pan-Antarctic Bayesian model to infer missing data, and show that spatial aggregation leads to more robust inference regarding dynamics.

  9. Signal-to-noise ratio and dose to the lens of the eye for computed tomography examination of the brain using an automatic tube current modulation system. (United States)

    Sookpeng, Supawitoo; Butdee, Chitsanupong


    The study aimed to evaluate the image quality in terms of signal-to-noise ratio (SNR) and dose to the lens of the eye and the other nearby organs from the CT brain scan using an automatic tube current modulation (ATCM) system with or without CT gantry tilt is needed. An anthropomorphic phantom was scanned with different settings including use of different ATCM, fixed tube current time product (mAs) settings and degree angles of gantry tilt. Gafchromic film XR-QA2 was used to measure absorbed dose of the organs. Relative doses and SNR for the various scan settings were compared with the reference setting of the fixed 330 mAs. Average absorbed dose for the lens of the eyes varied from 8.7 to 21.7 mGy. The use of the ATCM system with the gantry tilt resulted in up to 60% decrease in the dose to the lens of the eye. SNR significantly decreased while tilting the gantry using the fixed mAs techniques, compared to that of the reference setting. However, there were no statistical significant differences for SNRs between the reference setting and all ATCM settings. Compared to the reference setting of the fixed effective mAs, using the ATCM system and appropriate tilting, the gantry resulted in a substantial decrease in the dose to the lens of the eye while preserving signal-to-noise ratio. CT brain examination should be carefully controlled to optimize dose for lens of the eye and image quality of the examination.

  10. Robust Microarray Image Processing


    Novikov, Eugene; Barillot, Emmanuel


    In this work we have presented a complete solution for robust, high-throughput, two-color microarray image processing comprising procedures for automatic spot localization, spot quantification and spot quality control. The spot localization algorithm is fully automatic and robust with respect to deviations from perfect spot alignment and contamination. As an input, it requires only the common array design parameters: number of blocks and number of spots in the x and y directions of the array....

  11. TU-F-17A-01: BEST IN PHYSICS (JOINT IMAGING-THERAPY) - An Automatic Toolkit for Efficient and Robust Analysis of 4D Respiratory Motion

    International Nuclear Information System (INIS)

    Wei, J; Yuan, A; Li, G


    Purpose: To provide an automatic image analysis toolkit to process thoracic 4-dimensional computed tomography (4DCT) and extract patient-specific motion information to facilitate investigational or clinical use of 4DCT. Methods: We developed an automatic toolkit in MATLAB to overcome the extra workload from the time dimension in 4DCT. This toolkit employs image/signal processing, computer vision, and machine learning methods to visualize, segment, register, and characterize lung 4DCT automatically or interactively. A fully-automated 3D lung segmentation algorithm was designed and 4D lung segmentation was achieved in batch mode. Voxel counting was used to calculate volume variations of the torso, lung and its air component, and local volume changes at the diaphragm and chest wall to characterize breathing pattern. Segmented lung volumes in 12 patients are compared with those from a treatment planning system (TPS). Voxel conversion was introduced from CT# to other physical parameters, such as gravity-induced pressure, to create a secondary 4D image. A demon algorithm was applied in deformable image registration and motion trajectories were extracted automatically. Calculated motion parameters were plotted with various templates. Machine learning algorithms, such as Naive Bayes and random forests, were implemented to study respiratory motion. This toolkit is complementary to and will be integrated with the Computational Environment for Radiotherapy Research (CERR). Results: The automatic 4D image/data processing toolkit provides a platform for analysis of 4D images and datasets. It processes 4D data automatically in batch mode and provides interactive visual verification for manual adjustments. The discrepancy in lung volume calculation between this and the TPS is <±2% and the time saving is by 1–2 orders of magnitude. Conclusion: A framework of 4D toolkit has been developed to analyze thoracic 4DCT automatically or interactively, facilitating both investigational

  12. Multi-Phase Sub-Sampling Fractional-N PLL with soft loop switching for fast robust locking

    NARCIS (Netherlands)

    Liao, Dongyi; Dai, FA Foster; Nauta, Bram; Klumperink, Eric A.M.


    This paper presents a low phase noise sub-sampling PLL (SSPLL) with multi-phase outputs. Automatic soft switching between the sub-sampling phase loop and frequency loop is proposed to improve robustness against perturbations and interferences that may cause a traditional SSPLL to lose lock. A

  13. Robust Spacecraft Component Detection in Point Clouds. (United States)

    Wei, Quanmao; Jiang, Zhiguo; Zhang, Haopeng


    Automatic component detection of spacecraft can assist in on-orbit operation and space situational awareness. Spacecraft are generally composed of solar panels and cuboidal or cylindrical modules. These components can be simply represented by geometric primitives like plane, cuboid and cylinder. Based on this prior, we propose a robust automatic detection scheme to automatically detect such basic components of spacecraft in three-dimensional (3D) point clouds. In the proposed scheme, cylinders are first detected in the iteration of the energy-based geometric model fitting and cylinder parameter estimation. Then, planes are detected by Hough transform and further described as bounded patches with their minimum bounding rectangles. Finally, the cuboids are detected with pair-wise geometry relations from the detected patches. After successive detection of cylinders, planar patches and cuboids, a mid-level geometry representation of the spacecraft can be delivered. We tested the proposed component detection scheme on spacecraft 3D point clouds synthesized by computer-aided design (CAD) models and those recovered by image-based reconstruction, respectively. Experimental results illustrate that the proposed scheme can detect the basic geometric components effectively and has fine robustness against noise and point distribution density.

  14. A study on the feasibility of active contours on automatic CT bone segmentation. (United States)

    Truc, Phan T H; Kim, Tae-Seong; Lee, Sungyoung; Lee, Young-Koo


    Automatic bone segmentation of computed tomography (CT) images is an important step in image-guided surgery that requires both high accuracy and minimal user interaction. Previous attempts include global thresholding, region growing, region competition, watershed segmentation, and parametric active contour (AC) approaches, but none claim fully satisfactory performance. Recently, geometric or level-set-based AC models have been developed and appear to have characteristics suitable for automatic bone segmentation such as initialization insensitivity and topology adaptability. In this study, we have tested the feasibility of five level-set-based AC approaches for automatic CT bone segmentation with both synthetic and real CT images: namely, the geometric AC, geodesic AC, gradient vector flow fast geometric AC, Chan-Vese (CV) AC, and our proposed density distance augmented CV AC (Aug. CV AC). Qualitative and quantitative evaluations have been made in comparison with the segmentation results from standard commercial software and a medical expert. The first three models showed their robustness to various image contrasts, but their performances decreased much when noise level increased. On the contrary, the CV AC's performance was more robust to noise, yet dependent on image contrast. On the other hand, the Aug. CV AC demonstrated its robustness to both noise and contrast levels and yielded improved performances on a set of real CT data compared with the commercial software, proving its suitability for automatic bone segmentation from CT images.

  15. Effect of contrast material on image noise and radiation dose in adult chest computed tomography using automatic exposure control: A comparative study between 16-, 64- and 128-slice CT

    Energy Technology Data Exchange (ETDEWEB)

    Paul, Jijo, E-mail: [Clinic of the Goethe University, Department of Diagnostic and Interventional Radiology, Haus 23C UG, Theodor-Stern-Kai 7, 60590 Frankfurt am Main (Germany); Goethe University, Department of Biophysics, Max von Laue-Strasse 1, 60438 Frankfurt am Main (Germany); Schell, Boris, E-mail: [Clinic of the Goethe University, Department of Diagnostic and Interventional Radiology, Haus 23C UG, Theodor-Stern-Kai 7, 60590 Frankfurt am Main (Germany); Kerl, J. Matthias, E-mail: [Clinic of the Goethe University, Department of Diagnostic and Interventional Radiology, Haus 23C UG, Theodor-Stern-Kai 7, 60590 Frankfurt am Main (Germany); Maentele, Werner, E-mail: [Goethe University, Department of Biophysics, Max von Laue-Strasse 1, 60438 Frankfurt am Main (Germany); Vogl, Thomas J., E-mail: [Clinic of the Goethe University, Department of Diagnostic and Interventional Radiology, Haus 23C UG, Theodor-Stern-Kai 7, 60590 Frankfurt am Main (Germany); Bauer, Ralf W., E-mail: [Clinic of the Goethe University, Department of Diagnostic and Interventional Radiology, Haus 23C UG, Theodor-Stern-Kai 7, 60590 Frankfurt am Main (Germany)


    Purpose: To determine the difference in radiation dose between non-enhanced (NECT) and contrast-enhanced (CECT) chest CT examinations contributed by contrast material with different scanner generations with automatic exposure control (AEC). Methods and materials: Each 42 adult patients received a NECT and CECT of the chest in one session on a 16-, 64- or 128-slice CT scanner with the same scan protocol settings. However, AEC technology (Care Dose 4D, Siemens) underwent upgrades in each of the three scanner generations. DLP, CTDIvol and image noise were compared. Results: Although absolute differences in image noise were very small and ranged between 10 and 13 HU for NECT and CECT in median, the differences in image noise and dose (DLP: 16-slice:+2.8%; 64-slice:+3.9%; 128-slice:+5.6%) between NECT and CECT were statistically significant in all groups. Image noise and dose parameters were significantly lower in the most recent 128-slice CT generation for both NECT and CECT (DLP: 16-slice:+35.5-39.2%; 64-slice:+6.8-8.5%). Conclusion: The presence of contrast material lead to an increase in dose for chest examinations in three CT generations with AEC. Although image noise values were significantly higher for CECT, the absolute differences were in a range of 3 HU. This can be regarded as negligible, thus indicating that AEC is able to fulfill its purpose of maintaining image quality. However, technological developments lead to a significant reduction of dose and image noise with the latest CT generation.

  16. Radiometric Normalization of Temporal Images Combining Automatic Detection of Pseudo-Invariant Features from the Distance and Similarity Spectral Measures, Density Scatterplot Analysis, and Robust Regression

    Directory of Open Access Journals (Sweden)

    Ana Paula Ferreira de Carvalho


    Full Text Available Radiometric precision is difficult to maintain in orbital images due to several factors (atmospheric conditions, Earth-sun distance, detector calibration, illumination, and viewing angles. These unwanted effects must be removed for radiometric consistency among temporal images, leaving only land-leaving radiances, for optimum change detection. A variety of relative radiometric correction techniques were developed for the correction or rectification of images, of the same area, through use of reference targets whose reflectance do not change significantly with time, i.e., pseudo-invariant features (PIFs. This paper proposes a new technique for radiometric normalization, which uses three sequential methods for an accurate PIFs selection: spectral measures of temporal data (spectral distance and similarity, density scatter plot analysis (ridge method, and robust regression. The spectral measures used are the spectral angle (Spectral Angle Mapper, SAM, spectral correlation (Spectral Correlation Mapper, SCM, and Euclidean distance. The spectral measures between the spectra at times t1 and t2 and are calculated for each pixel. After classification using threshold values, it is possible to define points with the same spectral behavior, including PIFs. The distance and similarity measures are complementary and can be calculated together. The ridge method uses a density plot generated from images acquired on different dates for the selection of PIFs. In a density plot, the invariant pixels, together, form a high-density ridge, while variant pixels (clouds and land cover changes are spread, having low density, facilitating its exclusion. Finally, the selected PIFs are subjected to a robust regression (M-estimate between pairs of temporal bands for the detection and elimination of outliers, and to obtain the optimal linear equation for a given set of target points. The robust regression is insensitive to outliers, i.e., observation that appears to deviate

  17. Synthesis of multi-wavelength temporal phase-shifting algorithms optimized for high signal-to-noise ratio and high detuning robustness using the frequency transfer function


    Servin, Manuel; Padilla, Moises; Garnica, Guillermo


    Synthesis of single-wavelength temporal phase-shifting algorithms (PSA) for interferometry is well-known and firmly based on the frequency transfer function (FTF) paradigm. Here we extend the single-wavelength FTF-theory to dual and multi-wavelength PSA-synthesis when several simultaneous laser-colors are present. The FTF-based synthesis for dual-wavelength PSA (DW-PSA) is optimized for high signal-to-noise ratio and minimum number of temporal phase-shifted interferograms. The DW-PSA synthesi...

  18. Acoustic ambient noise recorder

    Digital Repository Service at National Institute of Oceanography (India)

    Saran, A.K.; Navelkar, G.S.; Almeida, A.M.; More, S.R.; Chodankar, P.V.; Murty, C.S.

    with a robust outfit that can withstand high pressures and chemically corrosion resistant materials. Keeping these considerations in view, a CMOS micro-controller-based marine acoustic ambient noise recorder has been developed with a real time clock...

  19. Robust Circle Detection Using Harmony Search

    Directory of Open Access Journals (Sweden)

    Jaco Fourie


    Full Text Available Automatic circle detection is an important element of many image processing algorithms. Traditionally the Hough transform has been used to find circular objects in images but more modern approaches that make use of heuristic optimisation techniques have been developed. These are often used in large complex images where the presence of noise or limited computational resources make the Hough transform impractical. Previous research on the use of the Harmony Search (HS in circle detection showed that HS is an attractive alternative to many of the modern circle detectors based on heuristic optimisers like genetic algorithms and simulated annealing. We propose improvements to this work that enables our algorithm to robustly find multiple circles in larger data sets and still work on realistic images that are heavily corrupted by noisy edges.

  20. Robust smile detection using convolutional neural networks (United States)

    Bianco, Simone; Celona, Luigi; Schettini, Raimondo


    We present a fully automated approach for smile detection. Faces are detected using a multiview face detector and aligned and scaled using automatically detected eye locations. Then, we use a convolutional neural network (CNN) to determine whether it is a smiling face or not. To this end, we investigate different shallow CNN architectures that can be trained even when the amount of learning data is limited. We evaluate our complete processing pipeline on the largest publicly available image database for smile detection in an uncontrolled scenario. We investigate the robustness of the method to different kinds of geometric transformations (rotation, translation, and scaling) due to imprecise face localization, and to several kinds of distortions (compression, noise, and blur). To the best of our knowledge, this is the first time that this type of investigation has been performed for smile detection. Experimental results show that our proposal outperforms state-of-the-art methods on both high- and low-quality images.

  1. Noise suppression by noise


    Vilar, J. M. G. (José M. G.), 1972-; Rubí Capaceti, José Miguel


    We have analyzed the interplay between an externally added noise and the intrinsic noise of systems that relax fast towards a stationary state, and found that increasing the intensity of the external noise can reduce the total noise of the system. We have established a general criterion for the appearance of this phenomenon and discussed two examples in detail.

  2. Active Noise Control for Dishwasher noise (United States)

    Lee, Nokhaeng; Park, Youngjin


    The dishwasher is a useful home appliance and continually used for automatically washing dishes. It's commonly placed in the kitchen with built-in style for practicality and better use of space. In this environment, people are easily exposed to dishwasher noise, so it is an important issue for the consumers, especially for the people living in open and narrow space. Recently, the sound power levels of the noise are about 40 - 50 dBA. It could be achieved by removal of noise sources and passive means of insulating acoustical path. For more reduction, such a quiet mode with the lower speed of cycle has been introduced, but this deteriorates the washing capacity. Under this background, we propose active noise control for dishwasher noise. It is observed that the noise is propagating mainly from the lower part of the front side. Control speakers are placed in the part for the collocation. Observation part of estimating sound field distribution and control part of generating the anti-noise are designed for active noise control. Simulation result shows proposed active noise control scheme could have a potential application for dishwasher noise reduction.

  3. A variational Bayesian method to inverse problems with impulsive noise

    KAUST Repository

    Jin, Bangti


    We propose a novel numerical method for solving inverse problems subject to impulsive noises which possibly contain a large number of outliers. The approach is of Bayesian type, and it exploits a heavy-tailed t distribution for data noise to achieve robustness with respect to outliers. A hierarchical model with all hyper-parameters automatically determined from the given data is described. An algorithm of variational type by minimizing the Kullback-Leibler divergence between the true posteriori distribution and a separable approximation is developed. The numerical method is illustrated on several one- and two-dimensional linear and nonlinear inverse problems arising from heat conduction, including estimating boundary temperature, heat flux and heat transfer coefficient. The results show its robustness to outliers and the fast and steady convergence of the algorithm. © 2011 Elsevier Inc.

  4. Automatic sequences

    CERN Document Server

    Haeseler, Friedrich


    Automatic sequences are sequences which are produced by a finite automaton. Although they are not random they may look as being random. They are complicated, in the sense of not being not ultimately periodic, they may look rather complicated, in the sense that it may not be easy to name the rule by which the sequence is generated, however there exists a rule which generates the sequence. The concept automatic sequences has special applications in algebra, number theory, finite automata and formal languages, combinatorics on words. The text deals with different aspects of automatic sequences, in particular:· a general introduction to automatic sequences· the basic (combinatorial) properties of automatic sequences· the algebraic approach to automatic sequences· geometric objects related to automatic sequences.

  5. Robust Affine Invariant Descriptors

    Directory of Open Access Journals (Sweden)

    Jianwei Yang


    Full Text Available An approach is developed for the extraction of affine invariant descriptors by cutting object into slices. Gray values associated with every pixel in each slice are summed up to construct affine invariant descriptors. As a result, these descriptors are very robust to additive noise. In order to establish slices of correspondence between an object and its affine transformed version, general contour (GC of the object is constructed by performing projection along lines with different polar angles. Consequently, affine in-variant division curves are derived. A slice is formed by points fall in the region enclosed by two adjacent division curves. To test and evaluate the proposed method, several experiments have been conducted. Experimental results show that the proposed method is very robust to noise.

  6. The PhysIO Toolbox for Modeling Physiological Noise in fMRI Data. (United States)

    Kasper, Lars; Bollmann, Steffen; Diaconescu, Andreea O; Hutton, Chloe; Heinzle, Jakob; Iglesias, Sandra; Hauser, Tobias U; Sebold, Miriam; Manjaly, Zina-Mary; Pruessmann, Klaas P; Stephan, Klaas E


    Physiological noise is one of the major confounds for fMRI. A common class of correction methods model noise from peripheral measures, such as ECGs or pneumatic belts. However, physiological noise correction has not emerged as a standard preprocessing step for fMRI data yet due to: (1) the varying data quality of physiological recordings, (2) non-standardized peripheral data formats and (3) the lack of full automatization of processing and modeling physiology, required for large-cohort studies. We introduce the PhysIO Toolbox for preprocessing of physiological recordings and model-based noise correction. It implements a variety of noise models, such as RETROICOR, respiratory volume per time and heart rate variability responses (RVT/HRV). The toolbox covers all intermediate steps - from flexible read-in of data formats to GLM regressor/contrast creation - without any manual intervention. We demonstrate the workflow of the toolbox and its functionality for datasets from different vendors, recording devices, field strengths and subject populations. Automatization of physiological noise correction and performance evaluation are reported in a group study (N=35). The PhysIO Toolbox reproduces physiological noise patterns and correction efficacy of previously implemented noise models. It increases modeling robustness by outperforming vendor-provided peak detection methods for physiological cycles. Finally, the toolbox offers an integrated framework with full automatization, including performance monitoring, and flexibility with respect to the input data. Through its platform-independent Matlab implementation, open-source distribution, and modular structure, the PhysIO Toolbox renders physiological noise correction an accessible preprocessing step for fMRI data. Copyright © 2016 The Authors. Published by Elsevier B.V. All rights reserved.

  7. L∞ fitting for inverse problems with uniform noise (United States)

    Clason, Christian


    For inverse problems where the data are corrupted by uniform noise such as arising from quantization errors, the L∞ norm is a more robust data-fitting term than the standard L2 norm. Well-posedness and regularization properties for linear inverse problems with L∞ data fitting are shown, and the automatic choice of the regularization parameter is discussed. After introducing an equivalent reformulation of the problem and a Moreau-Yosida approximation, a superlinearly convergent semi-smooth Newton method becomes applicable for the numerical solution of L∞ fitting problems. Numerical examples illustrate the performance of the proposed approach as well as the qualitative behavior of L∞ fitting.

  8. Comparison of models of automatic classification of textural patterns of mineral presents in Colombian coals

    International Nuclear Information System (INIS)

    Lopez Carvajal, Jaime; Branch Bedoya, John Willian


    The automatic classification of objects is a very interesting approach under several problem domains. This paper outlines some results obtained under different classification models to categorize textural patterns of minerals using real digital images. The data set used was characterized by a small size and noise presence. The implemented models were the Bayesian classifier, Neural Network (2-5-1), support vector machine, decision tree and 3-nearest neighbors. The results after applying crossed validation show that the Bayesian model (84%) proved better predictive capacity than the others, mainly due to its noise robustness behavior. The neuronal network (68%) and the SVM (67%) gave promising results, because they could be improved increasing the data amount used, while the decision tree (55%) and K-NN (54%) did not seem to be adequate for this problem, because of their sensibility to noise

  9. Robust adaptive subspace detection in impulsive noise

    KAUST Repository

    Ben Atitallah, Ismail


    This paper addresses the design of the Adaptive Subspace Matched Filter (ASMF) detector in the presence of compound Gaussian clutters and a mismatch in the steering vector. In particular, we consider the case wherein the ASMF uses the regularized Tyler estimator (RTE) to estimate the clutter covariance matrix. Under this setting, a major question that needs to be addressed concerns the setting of the threshold and the regularization parameter. To answer this question, we consider the regime in which the number of observations used to estimate the RTE and their dimensions grow large together. Recent results from random matrix theory are then used in order to approximate the false alarm and detection probabilities by deterministic quantities. The latter are optimized in order to maximize an upper bound on the asymptotic detection probability while keeping the asymptotic false alarm probability at a fixed rate. © 2016 IEEE.

  10. Active noise cancellation algorithms for impulsive noise. (United States)

    Li, Peng; Yu, Xun


    Impulsive noise is an important challenge for the practical implementation of active noise control (ANC) systems. The advantages and disadvantages of popular filtered- X least mean square (FXLMS) ANC algorithm and nonlinear filtered-X least mean M-estimate (FXLMM) algorithm are discussed in this paper. A new modified FXLMM algorithm is also proposed to achieve better performance in controlling impulsive noise. Computer simulations and experiments are carried out for all three algorithms and the results are presented and analyzed. The results show that the FXLMM and modified FXLMM algorithms are more robust in suppressing the adverse effect of sudden large amplitude impulses than FXLMS algorithm, and in particular, the proposed modified FXLMM algorithm can achieve better stability without sacrificing the performance of residual noise when encountering impulses.

  11. Noise Analysis of MAIA System and Possible Noise Suppression

    Directory of Open Access Journals (Sweden)

    J. Svihlik


    Full Text Available This paper is devoted to the noise analysis and noise suppression in a system for double station observation of the meteors now known as MAIA (Meteor Automatic Imager and Analyzer. The noise analysis is based on acquisition of testing video sequences in different light conditions and their further statistical evaluation. The main goal is to find a suitable noise model and subsequently determine if the noise is signal dependent or not. Noise and image model in the wavelet domain should be based on Gaussian mixture model (GMM or Generalized Laplacian Model (GLM and the model parameters should be estimated by moment method. Furthermore, noise should be modeled by GMM or GLM also in the space domain. GMM and GLM allow to model various types of probability density functions. Finally the advanced denoising algorithm using Bayesian estimator is applied and its performance is verified.

  12. Automatic quantitative renal scintigraphy

    International Nuclear Information System (INIS)

    Valeyre, J.; Deltour, G.; Delisle, M.J.; Bouchard, A.


    Renal scintigraphy data may be analyzed automatically by the use of a processing system coupled to an Anger camera (TRIDAC-MULTI 8 or CINE 200). The computing sequence is as follows: normalization of the images; background noise subtraction on both images; evaluation of mercury 197 uptake by the liver and spleen; calculation of the activity fractions on each kidney with respect to the injected dose, taking into account the kidney depth and the results referred to normal values; edition of the results. Automation minimizes the scattering parameters and by its simplification is a great asset in routine work [fr

  13. Robust Scientists

    DEFF Research Database (Denmark)

    Gorm Hansen, Birgitte

    their core i nterests, 2) developing a selfsupply of industry interests by becoming entrepreneurs and thus creating their own compliant industry partner and 3) balancing resources within a larger collective of researchers, thus countering changes in the influx of funding caused by shifts in political...... knowledge", Danish research policy seems to have helped develop politically and economically "robust scientists". Scientific robustness is acquired by way of three strategies: 1) tasting and discriminating between resources so as to avoid funding that erodes academic profiles and push scientists away from...

  14. Robust surface registration using N-points approximate congruent sets

    Directory of Open Access Journals (Sweden)

    Yao Jian


    Full Text Available Abstract Scans acquired by 3D sensors are typically represented in a local coordinate system. When multiple scans, taken from different locations, represent the same scene these must be registered to a common reference frame. We propose a fast and robust registration approach to automatically align two scans by finding two sets of N-points, that are approximately congruent under rigid transformation and leading to a good estimate of the transformation between their corresponding point clouds. Given two scans, our algorithm randomly searches for the best sets of congruent groups of points using a RANSAC-based approach. To successfully and reliably align two scans when there is only a small overlap, we improve the basic RANSAC random selection step by employing a weight function that approximates the probability of each pair of points in one scan to match one pair in the other. The search time to find pairs of congruent sets of N-points is greatly reduced by employing a fast search codebook based on both binary and multi-dimensional lookup tables. Moreover, we introduce a novel indicator of the overlapping region quality which is used to verify the estimated rigid transformation and to improve the alignment robustness. Our framework is general enough to incorporate and efficiently combine different point descriptors derived from geometric and texture-based feature points or scene geometrical characteristics. We also present a method to improve the matching effectiveness of texture feature descriptors by extracting them from an atlas of rectified images recovered from the scan reflectance image. Our algorithm is robust with respect to different sampling densities and also resilient to noise and outliers. We demonstrate its robustness and efficiency on several challenging scan datasets with varying degree of noise, outliers, extent of overlap, acquired from indoor and outdoor scenarios.

  15. Noise Pollution (United States)

    ... Us Share Clean Air Act Title IV - Noise Pollution The 1990 Clean Air Act Amendments added a ... abatement 7642 Authorization of appropriations What is Noise Pollution? The traditional definition of noise is “unwanted or ...

  16. Influence of binary mask estimation errors on robust speaker identification

    DEFF Research Database (Denmark)

    May, Tobias


    Missing-data strategies have been developed to improve the noise-robustness of automatic speech recognition systems in adverse acoustic conditions. This is achieved by classifying time-frequency (T-F) units into reliable and unreliable components, as indicated by a so-called binary mask. Different...... approaches have been proposed to handle unreliable feature components, each with distinct advantages. The direct masking (DM) approach attenuates unreliable T-F units in the spectral domain, which allows the extraction of conventionally used mel-frequency cepstral coefficients (MFCCs). Instead of attenuating....... Since each of these approaches utilizes the knowledge about reliable and unreliable feature components in a different way, they will respond differently to estimation errors in the binary mask. The goal of this study was to identify the most effective strategy to exploit knowledge about reliable...

  17. Automatic physical inference with information maximizing neural networks (United States)

    Charnock, Tom; Lavaux, Guilhem; Wandelt, Benjamin D.


    Compressing large data sets to a manageable number of summaries that are informative about the underlying parameters vastly simplifies both frequentist and Bayesian inference. When only simulations are available, these summaries are typically chosen heuristically, so they may inadvertently miss important information. We introduce a simulation-based machine learning technique that trains artificial neural networks to find nonlinear functionals of data that maximize Fisher information: information maximizing neural networks (IMNNs). In test cases where the posterior can be derived exactly, likelihood-free inference based on automatically derived IMNN summaries produces nearly exact posteriors, showing that these summaries are good approximations to sufficient statistics. In a series of numerical examples of increasing complexity and astrophysical relevance we show that IMNNs are robustly capable of automatically finding optimal, nonlinear summaries of the data even in cases where linear compression fails: inferring the variance of Gaussian signal in the presence of noise, inferring cosmological parameters from mock simulations of the Lyman-α forest in quasar spectra, and inferring frequency-domain parameters from LISA-like detections of gravitational waveforms. In this final case, the IMNN summary outperforms linear data compression by avoiding the introduction of spurious likelihood maxima. We anticipate that the automatic physical inference method described in this paper will be essential to obtain both accurate and precise cosmological parameter estimates from complex and large astronomical data sets, including those from LSST and Euclid.

  18. SU-E-J-16: Automatic Image Contrast Enhancement Based On Automatic Parameter Optimization for Radiation Therapy Setup Verification

    International Nuclear Information System (INIS)

    Qiu, J; Li, H. Harlod; Zhang, T; Yang, D; Ma, F


    Purpose: In RT patient setup 2D images, tissues often cannot be seen well due to the lack of image contrast. Contrast enhancement features provided by image reviewing software, e.g. Mosaiq and ARIA, require manual selection of the image processing filters and parameters thus inefficient and cannot be automated. In this work, we developed a novel method to automatically enhance the 2D RT image contrast to allow automatic verification of patient daily setups as a prerequisite step of automatic patient safety assurance. Methods: The new method is based on contrast limited adaptive histogram equalization (CLAHE) and high-pass filtering algorithms. The most important innovation is to automatically select the optimal parameters by optimizing the image contrast. The image processing procedure includes the following steps: 1) background and noise removal, 2) hi-pass filtering by subtracting the Gaussian smoothed Result, and 3) histogram equalization using CLAHE algorithm. Three parameters were determined through an iterative optimization which was based on the interior-point constrained optimization algorithm: the Gaussian smoothing weighting factor, the CLAHE algorithm block size and clip limiting parameters. The goal of the optimization is to maximize the entropy of the processed Result. Results: A total 42 RT images were processed. The results were visually evaluated by RT physicians and physicists. About 48% of the images processed by the new method were ranked as excellent. In comparison, only 29% and 18% of the images processed by the basic CLAHE algorithm and by the basic window level adjustment process, were ranked as excellent. Conclusion: This new image contrast enhancement method is robust and automatic, and is able to significantly outperform the basic CLAHE algorithm and the manual window-level adjustment process that are currently used in clinical 2D image review software tools

  19. Robust Toponym Resolution Based on Surface Statistics (United States)

    Sano, Tomohisa; Nobesawa, Shiho Hoshi; Okamoto, Hiroyuki; Susuki, Hiroya; Matsubara, Masaki; Saito, Hiroaki

    Toponyms and other named entities are main issues in unknown word processing problem. Our purpose is to salvage unknown toponyms, not only for avoiding noises but also providing them information of area candidates to where they may belong. Most of previous toponym resolution methods were targeting disambiguation among area candidates, which is caused by the multiple existence of a toponym. These approaches were mostly based on gazetteers and contexts. When it comes to the documents which may contain toponyms worldwide, like newspaper articles, toponym resolution is not just an ambiguity resolution, but an area candidate selection from all the areas on Earth. Thus we propose an automatic toponym resolution method which enables to identify its area candidates based only on their surface statistics, in place of dictionary-lookup approaches. Our method combines two modules, area candidate reduction and area candidate examination which uses block-unit data, to obtain high accuracy without reducing recall rate. Our empirical result showed 85.54% precision rate, 91.92% recall rate and .89 F-measure value on average. This method is a flexible and robust approach for toponym resolution targeting unrestricted number of areas.

  20. Combustion noise (United States)

    Strahle, W. C.


    A review of the subject of combustion generated noise is presented. Combustion noise is an important noise source in industrial furnaces and process heaters, turbopropulsion and gas turbine systems, flaring operations, Diesel engines, and rocket engines. The state-of-the-art in combustion noise importance, understanding, prediction and scaling is presented for these systems. The fundamentals and available theories of combustion noise are given. Controversies in the field are discussed and recommendations for future research are made.

  1. Novel methodologies for automatically and simultaneously determining BTEX components using FTIR spectra. (United States)

    Wang, Liang; Liu, Erming; Cheng, Ying; Bekele, Dawit N; Lamb, Dane; Chen, Zuliang; Megharaj, Mallavarapu; Naidu, Ravendra


    This study introduced a patented novel methodological system for automatically analysis of Fourier Transform Infrared Spectrometer (FTIR) spectrum data located at 'fingerprint' region (wavenumber 670-800 cm(-1)), to simultaneously determinate multiple petroleum hydrocarbons (PHs) in real mixture samples. This system includes: an object oriented baseline correction; Band decomposition (curve fitting) method with mathematical optimization; and Artificial Neural Network (ANN) for determination, which is suitable for the characteristics of this IR regions, where the spectra are normally with low signal to noise ratio and high density of peaks. BTEX components are potentially lethal carcinogens and contained in many petroleum products. As a case study, six BTEX components were determinate automatically and simultaneously in mixture vapor samples. The robustness of the BTEX determination was validated using real petroleum samples, and the prediction results were compared with gas chromatography-mass spectrometry (GC-MS). Copyright © 2015 Elsevier B.V. All rights reserved.

  2. Robust and Real-Time Traffic Lights Recognition in Complex Urban Environments

    Directory of Open Access Journals (Sweden)

    Chunxiang Wang


    Full Text Available The traffic lights play an indispensable role in urban road safety and researches on intelligent vehicles become more popular recently. In this paper an automatic system for robust and real-time detection and recognition of traffic lights for intelligent vehicles based on vehicle-mounted camera is proposed. The method applying image processing and pattern recognition theory mainly works in three stages. First, the candidate regions of traffic lights are extracted using the color threshold segmentation method. Secondly, noise removal and two types of filtering which take account of shape information are applied to the candidate regions. Thirdly, template matching using normalized cross correlation techniques is adopted to validate the traffic lights candidate. Experimental results show that the proposed algorithm works effectively and robustly for traffic lights recognition in complex urban environments.

  3. Robust CPD Algorithm for Non-Rigid Point Set Registration Based on Structure Information.

    Directory of Open Access Journals (Sweden)

    Lei Peng

    Full Text Available Recently, the Coherent Point Drift (CPD algorithm has become a very popular and efficient method for point set registration. However, this method does not take into consideration the neighborhood structure information of points to find the correspondence and requires a manual assignment of the outlier ratio. Therefore, CPD is not robust for large degrees of degradation. In this paper, an improved method is proposed to overcome the two limitations of CPD. A structure descriptor, such as shape context, is used to perform the auxiliary calculation of the correspondence, and the proportion of each GMM component is adjusted by the similarity. The outlier ratio is formulated in the EM framework so that it can be automatically calculated and optimized iteratively. The experimental results on both synthetic data and real data demonstrate that the proposed method described here is more robust to deformation, noise, occlusion, and outliers than CPD and other state-of-the-art algorithms.

  4. Automatic Detection of P and S Phases by Support Vector Machine (United States)

    Jiang, Y.; Ning, J.; Bao, T.


    Many methods in seismology rely on accurately picked phases. A well performed program on automatically phase picking will assure the application of these methods. Related researches before mostly focus on finding different characteristics between noise and phases, which are all not enough successful. We have developed a new method which mainly based on support vector machine to detect P and S phases. In it, we first input some waveform pieces into the support vector machine, then employ it to work out a hyper plane which can divide the space into two parts: respectively noise and phase. We further use the same method to find a hyper plane which can separate the phase space into P and S parts based on the three components' cross-correlation matrix. In order to further improve the ability of phase detection, we also employ array data. At last, we show that the overall effect of our method is robust by employing both synthetic and real data.

  5. Robustness of Linear Systems towards Multi-Dissipative Pertubations

    DEFF Research Database (Denmark)

    Thygesen, Uffe Høgsbro; Poulsen, Niels Kjølstad


    We consider the question of robust stability of a linear time invariant plant subject to dynamic perturbations, which are dissipative in the sense of Willems with respect to several quadratic supply rates. For instance, parasitic dynamics are often both small gain and passive. We reduce several...... robustness analysis questions to linear matrix inequalities: robust stability, robust H2 performance and robust performance in presence of disturbances with finite signal-to-noise ratios...

  6. Health Effects of Noise Exposure in Children. (United States)

    Stansfeld, Stephen; Clark, Charlotte


    Environmental noise exposure, such as road traffic noise and aircraft noise, is associated with a range of health outcomes in children. Children demonstrate annoyance responses to noise, and noise is also related to lower well-being and stress responses, such as increased levels of adrenaline and noradrenaline. Noise does not cause more serious mental health problems, but there is growing evidence for an association with increased hyperactivity symptoms. Studies also suggest that noise might cause changes in cardiovascular functioning, and there is some limited evidence for an effect on low birth weight. There is robust evidence for an effect of school noise exposure on children's cognitive skills such as reading and memory, as well as on standardised academic test scores. Environmental noise does not usually reach levels that are likely to affect children's hearing; however, increasing use of personal electronic devices may leave some children exposed to harmful levels of noise.

  7. Automatic Lumen Detection on Longitudinal Ultrasound B-Mode Images of the Carotid Using Phase Symmetry

    Directory of Open Access Journals (Sweden)

    José Rouco


    Full Text Available This article describes a method that improves the performance of previous approaches for the automatic detection of the common carotid artery (CCA lumen centerline on longitudinal B-mode ultrasound images. We propose to detect several lumen centerline candidates using local symmetry analysis based on local phase information of dark structures at an appropriate scale. These candidates are analyzed with selection mechanisms that use symmetry, contrast or intensity features in combination with position-based heuristics. Several experimental results are provided to evaluate the robustness and performance of the proposed method in comparison with previous approaches. These results lead to the conclusion that our proposal is robust to noise, lumen artifacts, contrast variations and that is able to deal with the presence of CCA-like structures, significantly improving the performance of our previous approach, from 87.5% ± 0.7% of correct detections to 98.3% ± 0.3% in a set of 200 images.

  8. Robust Sonar ATR Through Bayesian Pose-Corrected Sparse Classification (United States)

    McKay, John; Monga, Vishal; Raj, Raghu G.


    Sonar imaging has seen vast improvements over the last few decades due in part to advances in synthetic aperture Sonar (SAS). Sophisticated classification techniques can now be used in Sonar automatic target recognition (ATR) to locate mines and other threatening objects. Among the most promising of these methods is sparse reconstruction-based classification (SRC) which has shown an impressive resiliency to noise, blur, and occlusion. We present a coherent strategy for expanding upon SRC for Sonar ATR that retains SRC's robustness while also being able to handle targets with diverse geometric arrangements, bothersome Rayleigh noise, and unavoidable background clutter. Our method, pose corrected sparsity (PCS), incorporates a novel interpretation of a spike and slab probability distribution towards use as a Bayesian prior for class-specific discrimination in combination with a dictionary learning scheme for localized patch extractions. Additionally, PCS offers the potential for anomaly detection in order to avoid false identifications of tested objects from outside the training set with no additional training required. Compelling results are shown using a database provided by the United States Naval Surface Warfare Center.

  9. Robust Tomato Recognition for Robotic Harvesting Using Feature Images Fusion (United States)

    Zhao, Yuanshen; Gong, Liang; Huang, Yixiang; Liu, Chengliang


    Automatic recognition of mature fruits in a complex agricultural environment is still a challenge for an autonomous harvesting robot due to various disturbances existing in the background of the image. The bottleneck to robust fruit recognition is reducing influence from two main disturbances: illumination and overlapping. In order to recognize the tomato in the tree canopy using a low-cost camera, a robust tomato recognition algorithm based on multiple feature images and image fusion was studied in this paper. Firstly, two novel feature images, the  a*-component image and the I-component image, were extracted from the L*a*b* color space and luminance, in-phase, quadrature-phase (YIQ) color space, respectively. Secondly, wavelet transformation was adopted to fuse the two feature images at the pixel level, which combined the feature information of the two source images. Thirdly, in order to segment the target tomato from the background, an adaptive threshold algorithm was used to get the optimal threshold. The final segmentation result was processed by morphology operation to reduce a small amount of noise. In the detection tests, 93% target tomatoes were recognized out of 200 overall samples. It indicates that the proposed tomato recognition method is available for robotic tomato harvesting in the uncontrolled environment with low cost. PMID:26840313

  10. Data-Driven Neural Network Model for Robust Reconstruction of Automobile Casting (United States)

    Lin, Jinhua; Wang, Yanjie; Li, Xin; Wang, Lu


    In computer vision system, it is a challenging task to robustly reconstruct complex 3D geometries of automobile castings. However, 3D scanning data is usually interfered by noises, the scanning resolution is low, these effects normally lead to incomplete matching and drift phenomenon. In order to solve these problems, a data-driven local geometric learning model is proposed to achieve robust reconstruction of automobile casting. In order to relieve the interference of sensor noise and to be compatible with incomplete scanning data, a 3D convolution neural network is established to match the local geometric features of automobile casting. The proposed neural network combines the geometric feature representation with the correlation metric function to robustly match the local correspondence. We use the truncated distance field(TDF) around the key point to represent the 3D surface of casting geometry, so that the model can be directly embedded into the 3D space to learn the geometric feature representation; Finally, the training labels is automatically generated for depth learning based on the existing RGB-D reconstruction algorithm, which accesses to the same global key matching descriptor. The experimental results show that the matching accuracy of our network is 92.2% for automobile castings, the closed loop rate is about 74.0% when the matching tolerance threshold τ is 0.2. The matching descriptors performed well and retained 81.6% matching accuracy at 95% closed loop. For the sparse geometric castings with initial matching failure, the 3D matching object can be reconstructed robustly by training the key descriptors. Our method performs 3D reconstruction robustly for complex automobile castings.

  11. Noise Protection (United States)


    Environmental Health Systems puts forth an increasing effort in the U.S. to develop ways of controlling noise, particularly in industrial environments due to Federal and State laws, labor union insistence and new findings relative to noise pollution impact on human health. NASA's Apollo guidance control system aided in the development of a noise protection product, SMART. The basis of all SMART products is SMART compound a liquid plastic mixture with exceptional energy/sound absorbing qualities. The basic compound was later refined for noise protection use.

  12. Quantitative Robust Control Engineering: Theory and Applications (United States)


    the twentieth century, there has been a tremendous advance in the state-of-the- art of robust frequency domain methods. One of the main techniques...Templates [28]. Bartlett, A.C., Tesi , A., Vicino, A. (1993). Frequency response of uncertain systems with interval plants. IEEE Trans. On Automatic

  13. Robust facial landmark detection for three-dimensional face segmentation and alignment (United States)

    Wu, Hai Shan; Chen, Yan Qiu


    Three-dimensional human faces have been applied in many fields, such as face animation, identity recognition, and facial plastic surgery. Segmenting and aligning 3-D faces from raw scanned data is the first vital step toward making these applications successful. However, the existence of artifacts, facial expressions, and noises poses many challenges to this problem. We propose an automatic and robust method to segment and align 3-D face surfaces by locating the nose tip and nose ridge. Taking a raw scanned surface as input, a novel feature-based moment analysis on scale spaces is presented to locate the nose tip accurately and robustly, which is then used to crop the face region. A technique called the geodesic Euclidean ratio is then developed to find the nose ridge. Each face is aligned based on the locations of nose tip and nose ridge. The proposed method is not only invariant to translations and rotations, but also robust in the presence of facial expressions and artifacts such as hair, clothing, other body parts, etc. Experimental results on two large 3-D face databases demonstrate the accuracy and robustness of the proposed method.

  14. Robust and Effective Component-based Banknote Recognition by SURF Features. (United States)

    Hasanuzzaman, Faiz M; Yang, Xiaodong; Tian, YingLi


    Camera-based computer vision technology is able to assist visually impaired people to automatically recognize banknotes. A good banknote recognition algorithm for blind or visually impaired people should have the following features: 1) 100% accuracy, and 2) robustness to various conditions in different environments and occlusions. Most existing algorithms of banknote recognition are limited to work for restricted conditions. In this paper we propose a component-based framework for banknote recognition by using Speeded Up Robust Features (SURF). The component-based framework is effective in collecting more class-specific information and robust in dealing with partial occlusion and viewpoint changes. Furthermore, the evaluation of SURF demonstrates its effectiveness in handling background noise, image rotation, scale, and illumination changes. To authenticate the robustness and generalizability of the proposed approach, we have collected a large dataset of banknotes from a variety of conditions including occlusion, cluttered background, rotation, and changes of illumination, scaling, and viewpoints. The proposed algorithm achieves 100% recognition rate on our challenging dataset.

  15. Robust group compressive sensing for DOA estimation with partially distorted observations (United States)

    Wang, Ben; Zhang, Yimin D.; Wang, Wei


    In this paper, we propose a robust direction-of-arrival (DOA) estimation algorithm based on group sparse reconstruction algorithm utilizing signals observed at multiple frequencies. The group sparse reconstruction scheme for DOA estimation is solved through the complex multitask Bayesian compressive sensing algorithm by exploiting the group sparse property of the received multi-frequency signals. Then, we propose a robust reconstruction algorithm in the presence of distorted signals. In particular, we consider a problem where the observed data in some frequencies are distorted due to, e.g., interference contamination. In this case, the residual error will follow the impulsive Gaussian mixture distribution instead of the Gaussian distribution due to the fact that some of the estimation errors significantly depart from the mean value of the estimation error distribution. Thus, the minimum least square restriction used in the conventional sparse reconstruction algorithm may lead to a failed reconstruction result. By exploiting the maximum correntropy criterion which is inherently insensitive to the impulsive noise, a weighting vector is derived to automatically mitigate the effect of the distorted narrowband signals, and a robust group compressive sensing approach is developed to achieve reliable DOA estimation. The robustness and effectiveness of the proposed algorithm are verified using simulation results.

  16. Environmental Noise (United States)

    Rumberg, Martin

    Environmental noise may be defined as unwanted sound that is caused by emissions from traffic (roads, air traffic corridors, and railways), industrial sites and recreational infrastructures, which may cause both annoyance and damage to health. Noise in the environment or community seriously affects people, interfering with daily activities at school, work and home and during leisure time.

  17. Non-Stationary Rician Noise Estimation in Parallel MRI Using a Single Image: A Variance-Stabilizing Approach. (United States)

    Pieciak, Tomasz; Aja-Fernandez, Santiago; Vegas-Sanchez-Ferrero, Gonzalo


    Parallel magnetic resonance imaging (pMRI) techniques have gained a great importance both in research and clinical communities recently since they considerably accelerate the image acquisition process. However, the image reconstruction algorithms needed to correct the subsampling artifacts affect the nature of noise, i.e., it becomes non-stationary. Some methods have been proposed in the literature dealing with the non-stationary noise in pMRI. However, their performance depends on information not usually available such as multiple acquisitions, receiver noise matrices, sensitivity coil profiles, reconstruction coefficients, or even biophysical models of the data. Besides, some methods show an undesirable granular pattern on the estimates as a side effect of local estimation. Finally, some methods make strong assumptions that just hold in the case of high signal-to-noise ratio (SNR), which limits their usability in real scenarios. We propose a new automatic noise estimation technique for non-stationary Rician noise that overcomes the aforementioned drawbacks. Its effectiveness is due to the derivation of a variance-stabilizing transformation designed to deal with any SNR. The method was compared to the main state-of-the-art methods in synthetic and real scenarios. Numerical results confirm the robustness of the method and its better performance for the whole range of SNRs.

  18. Design Robust Controller for Rotary Kiln

    Directory of Open Access Journals (Sweden)

    Omar D. Hernández-Arboleda


    Full Text Available This paper presents the design of a robust controller for a rotary kiln. The designed controller is a combination of a fractional PID and linear quadratic regulator (LQR, these are not used to control the kiln until now, in addition robustness criteria are evaluated (gain margin, phase margin, strength gain, rejecting high frequency noise and sensitivity applied to the entire model (controller-plant, obtaining good results with a frequency range of 0.020 to 90 rad/s, which contributes to the robustness of the system.

  19. Automatic Estimation of Movement Statistics of People

    DEFF Research Database (Denmark)

    Ægidiussen Jensen, Thomas; Rasmussen, Henrik Anker; Moeslund, Thomas B.


    Automatic analysis of how people move about in a particular environment has a number of potential applications. However, no system has so far been able to do detection and tracking robustly. Instead, trajectories are often broken into tracklets. The key idea behind this paper is based around...

  20. Robust tensor estimation in diffusion tensor imaging (United States)

    Maximov, Ivan I.; Grinberg, Farida; Jon Shah, N.


    The signal response measured in diffusion tensor imaging is subject to detrimental influences caused by noise. Noise fields arise due to various contributions such as thermal and physiological noise and sources related to the hardware imperfection. As a result, diffusion tensors estimated by different linear and non-linear least squares methods in absence of a proper noise correction tend to be substantially corrupted. In this work, we propose an advanced tensor estimation approach based on the least median squares method of the robust statistics. Both constrained and non-constrained versions of the method are considered. The performance of the developed algorithm is compared to that of the conventional least squares method and of the alternative robust methods proposed in the literature. Two examples of simulated diffusion attenuations and experimental in vivo diffusion data sets were used as a basis for comparison. The robust algorithms were shown to be advantageous compared to the least squares method in the cases where elimination of the outliers is desirable. Additionally, the constraints were applied in order to prevent generation of the non-positive definite tensors and reduce related artefacts in the maps of fractional anisotropy. The developed method can potentially be exploited also by other MR techniques where a robust regression or outlier localisation is required.

  1. Robust statistics for image deconvolution (United States)

    Lee, M. A.; Budavári, T.; White, R. L.; Gulian, C.


    We present a blind multiframe image-deconvolution method based on robust statistics. The usual shortcomings of iterative optimization of the likelihood function are alleviated by minimizing the M-scale of the residuals, which achieves more uniform convergence across the image. We focus on the deconvolution of astronomical images, which are among the most challenging due to their huge dynamic ranges and the frequent presence of large noise-dominated regions in the images. We show that high-quality image reconstruction is possible even in super-resolution and without the use of traditional regularization terms. Using a robust ρ-function is straightforward to implement in a streaming setting and, hence our method is applicable to the large volumes of astronomy images. The power of our method is demonstrated on observations from the Sloan Digital Sky Survey (Stripe 82) and we briefly discuss the feasibility of a pipeline based on Graphical Processing Units for the next generation of telescope surveys.

  2. Automatic fault extraction using a modified ant-colony algorithm

    International Nuclear Information System (INIS)

    Zhao, Junsheng; Sun, Sam Zandong


    The basis of automatic fault extraction is seismic attributes, such as the coherence cube which is always used to identify a fault by the minimum value. The biggest challenge in automatic fault extraction is noise, including that of seismic data. However, a fault has a better spatial continuity in certain direction, which makes it quite different from noise. Considering this characteristic, a modified ant-colony algorithm is introduced into automatic fault identification and tracking, where the gradient direction and direction consistency are used as constraints. Numerical model test results show that this method is feasible and effective in automatic fault extraction and noise suppression. The application of field data further illustrates its validity and superiority. (paper)

  3. Efficient and robust ventricular tachycardia and fibrillation detection method for wearable cardiac health monitoring devices. (United States)

    Prabhakararao, Eedara; Manikandan, M Sabarimalai


    In this Letter, the authors propose an efficient and robust method for automatically determining the VT and VF events in the electrocardiogram (ECG) signal. The proposed method consists of: (i) discrete cosine transform (DCT)-based noise suppression; (ii) addition of bipolar sequence of amplitudes with alternating polarity; (iii) zero-crossing rate (ZCR) estimation-based VTVF detection; and (iv) peak-to-peak interval (PPI) feature based VT/VF discrimination. The proposed method is evaluated using 18,000 episodes of different ECG arrhythmias taken from 6 PhysioNet databases. The method achieves an average sensitivity (Se) of 99.61%, specificity (Sp) of 99.96%, and overall accuracy (OA) of 99.92% in detecting VTVF and non-VTVF episodes by using a ZCR feature. Results show that the method achieves a Se of 100%, Sp of 99.70% and OA of 99.85% for discriminating VT from VF episodes using PPI features extracted from the processed signal. The robustness of the method is tested using different kinds of ECG beats and various types of noises including the baseline wanders, powerline interference and muscle artefacts. Results demonstrate that the proposed method with the ZCR, PPI features can achieve significantly better detection rates as compared with the existing methods.

  4. Boolean networks with robust and reliable trajectories

    International Nuclear Information System (INIS)

    Schmal, Christoph; Peixoto, Tiago P; Drossel, Barbara


    We construct and investigate Boolean networks that follow a given reliable trajectory in state space, which is insensitive to fluctuations in the updating schedule and which is also robust against noise. Robustness is quantified as the probability that the dynamics return to the reliable trajectory after a perturbation of the state of a single node. In order to achieve high robustness, we navigate through the space of possible update functions by using an evolutionary algorithm. We constrain the networks to those having the minimum number of connections required to obtain the reliable trajectory. Surprisingly, we find that robustness always reaches values close to 100% during the evolutionary optimization process. The set of update functions can be evolved such that it differs only slightly from that of networks that were not optimized with respect to robustness. The state space of the optimized networks is dominated by the basin of attraction of the reliable trajectory.

  5. Automatic Recognition of fMRI-derived Functional Networks using 3D Convolutional Neural Networks. (United States)

    Zhao, Yu; Dong, Qinglin; Zhang, Shu; Zhang, Wei; Chen, Hanbo; Jiang, Xi; Guo, Lei; Hu, Xintao; Han, Junwei; Liu, Tianming


    Current fMRI data modeling techniques such as Independent Component Analysis (ICA) and Sparse Coding methods can effectively reconstruct dozens or hundreds of concurrent interacting functional brain networks simultaneously from the whole brain fMRI signals. However, such reconstructed networks have no correspondences across different subjects. Thus, automatic, effective and accurate classification and recognition of these large numbers of fMRI-derived functional brain networks are very important for subsequent steps of functional brain analysis in cognitive and clinical neuroscience applications. However, this task is still a challenging and open problem due to the tremendous variability of various types of functional brain networks and the presence of various sources of noises. In recognition of the fact that convolutional neural networks (CNN) has superior capability of representing spatial patterns with huge variability and dealing with large noises, in this paper, we design, apply and evaluate a deep 3D CNN framework for automatic, effective and accurate classification and recognition of large number of functional brain networks reconstructed by sparse representation of whole-brain fMRI signals. Our extensive experimental results based on the Human Connectome Project (HCP) fMRI data showed that the proposed deep 3D CNN can effectively and robustly perform functional networks classification and recognition tasks, while maintaining a high tolerance for mistakenly labelled training instances. Our work provides a new deep learning approach for modeling functional connectomes based on fMRI data.

  6. A Fast and Robust Method for Measuring Optical Channel Gain

    DEFF Research Database (Denmark)

    Harbo, Anders La-Cour; Stoustrup, Jakob; Villemoes, L.F.


    We present a numerically stable and computational simple method for fast and robust measurement of optical channel gain. By transmitting adaptively designed signals through the channel, good accuracy is possible even in severe noise conditions......We present a numerically stable and computational simple method for fast and robust measurement of optical channel gain. By transmitting adaptively designed signals through the channel, good accuracy is possible even in severe noise conditions...

  7. Robustness: confronting lessons from physics and biology. (United States)

    Lesne, Annick


    The term robustness is encountered in very different scientific fields, from engineering and control theory to dynamical systems to biology. The main question addressed herein is whether the notion of robustness and its correlates (stability, resilience, self-organisation) developed in physics are relevant to biology, or whether specific extensions and novel frameworks are required to account for the robustness properties of living systems. To clarify this issue, the different meanings covered by this unique term are discussed; it is argued that they crucially depend on the kind of perturbations that a robust system should by definition withstand. Possible mechanisms underlying robust behaviours are examined, either encountered in all natural systems (symmetries, conservation laws, dynamic stability) or specific to biological systems (feedbacks and regulatory networks). Special attention is devoted to the (sometimes counterintuitive) interrelations between robustness and noise. A distinction between dynamic selection and natural selection in the establishment of a robust behaviour is underlined. It is finally argued that nested notions of robustness, relevant to different time scales and different levels of organisation, allow one to reconcile the seemingly contradictory requirements for robustness and adaptability in living systems.

  8. Robust image segmentation using local robust statistics and correntropy-based K-means clustering (United States)

    Huang, Chencheng; Zeng, Li


    It is an important work to segment the real world images with intensity inhomogeneity such as magnetic resonance (MR) and computer tomography (CT) images. In practice, such images are often polluted by noise which make them difficult to be segmented by traditional level set based segmentation models. In this paper, we propose a robust level set image segmentation model combining local with global fitting energies to segment noised images. In the proposed model, the local fitting energy is based on the local robust statistics (LRS) information of an input image, which can efficiently reduce the effects of the noise, and the global fitting energy utilizes the correntropy-based K-means (CK) method, which can adaptively emphasize the samples that are close to their corresponding cluster centers. By integrating the advantages of global information and local robust statistics characteristics, the proposed model can efficiently segment images with intensity inhomogeneity and noise. Then, a level set regularization term is used to avoid re-initialization procedures in the process of curve evolution. In addition, the Gaussian filter is utilized to keep the level set smoothing in the curve evolution process. The proposed model first appeared as a two-phase model and then extended to a multi-phase one. Experimental results show the advantages of our model in terms of accuracy and robustness to the noise. In particular, our method has been applied on some synthetic and real images with desirable results.

  9. Improving Robustness of Deep Neural Network Acoustic Models via Speech Separation and Joint Adaptive Training. (United States)

    Narayanan, Arun; Wang, DeLiang


    Although deep neural network (DNN) acoustic models are known to be inherently noise robust, especially with matched training and testing data, the use of speech separation as a frontend and for deriving alternative feature representations has been shown to improve performance in challenging environments. We first present a supervised speech separation system that significantly improves automatic speech recognition (ASR) performance in realistic noise conditions. The system performs separation via ratio time-frequency masking; the ideal ratio mask (IRM) is estimated using DNNs. We then propose a framework that unifies separation and acoustic modeling via joint adaptive training. Since the modules for acoustic modeling and speech separation are implemented using DNNs, unification is done by introducing additional hidden layers with fixed weights and appropriate network architecture. On the CHiME-2 medium-large vocabulary ASR task, and with log mel spectral features as input to the acoustic model, an independently trained ratio masking frontend improves word error rates by 10.9% (relative) compared to the noisy baseline. In comparison, the jointly trained system improves performance by 14.4%. We also experiment with alternative feature representations to augment the standard log mel features, like the noise and speech estimates obtained from the separation module, and the standard feature set used for IRM estimation. Our best system obtains a word error rate of 15.4% (absolute), an improvement of 4.6 percentage points over the next best result on this corpus.

  10. Ensemble of randomized soft decision trees for robust classification

    Indian Academy of Sciences (India)

    It is found that an ensembleof randomized soft decision trees has outperformed the related existing soft decision tree. Robustness against the presence of noise is shown by injecting various levels of noise into the training set and a comparison is drawnwith other related methods which favors the proposed method.

  11. Drone noise (United States)

    Tinney, Charles; Sirohi, Jayant; University of Texas at Austin Team


    A basic understanding of the noise produced by single and multirotor drones operating at static thrust conditions is presented. This work acts as an extension to previous efforts conducted at The University of Texas at Austin (Tinney et al. 2017, AHS Forum 73). Propeller diameters ranging from 8 inch to 12 inch are examined for configurations comprising an isolated rotor, a quadcopter configuration and a hexacopter configuration, and with a constant drone pitch of 2.25. An azimuthal array of half-inch microphones, placed between 2 and 3 hub-center diameters from the drone center, are used to assess the acoustic near-field. Thrust levels, acquired using a six degree-of-freedom load cell, are then used to correlate acoustic noise levels to aerodynamic performance for each drone configuration. The findings reveal a nearly logarithmic increase in noise with increasing thrust. However, for the same thrust condition, considerable noise reduction is achieved by increasing the number of propeller blades thereby reducing the blade passage frequency and both the thickness and loading noise sources that accompany it.

  12. Automatically identifying scatter in fluorescence data using robust techniques

    DEFF Research Database (Denmark)

    Engelen, S.; Frosch, Stina; Hubert, M.


    First and second order Rayleigh and Raman scatter is a common problem when fitting Parallel Factor Analysis (PARAFAC) to fluorescence excitation-emission data (EEM). The scatter does not contain any relevant chemical information and does not conform to the low-rank trilinear model. The scatter...

  13. Noise and vibration analysis system

    International Nuclear Information System (INIS)

    Johnsen, J.R.; Williams, R.L.


    The analysis of noise and vibration data from an operating nuclear plant can provide valuable information that can identify and characterize abnormal conditions. Existing plant monitoring equipment, such as loose parts monitoring systems (LPMS) and neutron flux detectors, may be capable of gathering noise data, but may lack the analytical capability to extract useful meanings hidden in the noise. By analyzing neutron noise signals, the structural motion and integrity of core components can be assessed. Computer analysis makes trending of frequency spectra within a fuel cycle and from one cycle to another a practical means of core internals monitoring. The Babcock and Wilcox Noise and Vibration Analysis System (NVAS) is a powerful, compact system that can automatically perform complex data analysis. The system can acquire, process, and store data, then produce report-quality plots of the important parameter. Software to perform neutron noise analysis and loose parts analysis operates on the same hardware package. Since the system is compact, inexpensive, and easy to operate, it allows utilities to perform more frequency analyses without incurring high costs and provides immediate results

  14. Pavement noise measurements in Poland (United States)

    Zofka, Ewa; Zofka, Adam; Mechowski, Tomasz


    The objective of this study is to investigate the feasibility of the On-Board Sound Intensity (OBSI) system to measure tire-pavement noise in Poland. In general, sources of noise emitted by the modern vehicles are the propulsion noise, aerodynamic resistance and noise generated at the tire-pavement interface. In order to capture tire-pavement noise, the OBSI system uses a noise intensity probe installed in the close proximity of that interface. In this study, OBSI measurements were performed at different types of pavement surfaces such as stone mastic asphalt (SMA), regular asphalt concrete (HMA) as well as Portland cement concrete (PCC). The influence of several necessary OBSI measurement conditions were recognized as: testing speed, air temperature, tire pressure and tire type. The results of this study demonstrate that the OBSI system is a viable and robust tool that can be used for the quality evaluation of newly built asphalt pavements in Poland. It can be also applied to generate reliable input parameters for the noise propagation models that are used to assess the environmental impact of new and existing highway corridors.

  15. Automaticity of walking: functional significance, mechanisms, measurement and rehabilitation strategies

    Directory of Open Access Journals (Sweden)

    David J Clark


    Full Text Available Automaticity is a hallmark feature of walking in adults who are healthy and well-functioning. In the context of walking, ‘automaticity’ refers to the ability of the nervous system to successfully control typical steady state walking with minimal use of attention-demanding executive control resources. Converging lines of evidence indicate that walking deficits and disorders are characterized in part by a shift in the locomotor control strategy from healthy automaticity to compensatory executive control. This is potentially detrimental to walking performance, as an executive control strategy is not optimized for locomotor control. Furthermore, it places excessive demands on a limited pool of executive reserves. The result is compromised ability to perform basic and complex walking tasks and heightened risk for adverse mobility outcomes including falls. Strategies for rehabilitation of automaticity are not well defined, which is due to both a lack of systematic research into the causes of impaired automaticity and to a lack of robust neurophysiological assessments by which to gauge automaticity. These gaps in knowledge are concerning given the serious functional implications of compromised automaticity. Therefore, the objective of this article is to advance the science of automaticity of walking by consolidating evidence and identifying gaps in knowledge regarding: a functional significance of automaticity; b neurophysiology of automaticity; c measurement of automaticity; d mechanistic factors that compromise automaticity; and e strategies for rehabilitation of automaticity.

  16. Robust Stabilization of Jet Engine Compressor In The Presence of ...

    African Journals Online (AJOL)

    In this work, first we modify the Moore and Grietzer three-state model for compressors to include disturbance (noise signals) and then use the method of integrator backstepping, coupled with saturation functions to develop robust controllers for the stabilization of the compressor. Also, we develop robust observers for ...

  17. Phase noise of dispersion-managed solitons

    International Nuclear Information System (INIS)

    Spiller, Elaine T.; Biondini, Gino


    We quantify noise-induced phase deviations of dispersion-managed solitons (DMS) in optical fiber communications and femtosecond lasers. We first develop a perturbation theory for the dispersion-managed nonlinear Schroedinger equation (DMNLSE) in order to compute the noise-induced mean and variance of the soliton parameters. We then use the analytical results to guide importance-sampled Monte Carlo simulations of the noise-driven DMNLSE. Comparison of these results with those from the original unaveraged governing equations confirms the validity of the DMNLSE as a model for many dispersion-managed systems and quantify the increased robustness of DMS with respect to noise-induced phase jitter.

  18. Automatic fluid dispenser (United States)

    Sakellaris, P. C. (Inventor)


    Fluid automatically flows to individual dispensing units at predetermined times from a fluid supply and is available only for a predetermined interval of time after which an automatic control causes the fluid to drain from the individual dispensing units. Fluid deprivation continues until the beginning of a new cycle when the fluid is once again automatically made available at the individual dispensing units.

  19. Automatic segmentation of clinical texts. (United States)

    Apostolova, Emilia; Channin, David S; Demner-Fushman, Dina; Furst, Jacob; Lytinen, Steven; Raicu, Daniela


    Clinical narratives, such as radiology and pathology reports, are commonly available in electronic form. However, they are also commonly entered and stored as free text. Knowledge of the structure of clinical narratives is necessary for enhancing the productivity of healthcare departments and facilitating research. This study attempts to automatically segment medical reports into semantic sections. Our goal is to develop a robust and scalable medical report segmentation system requiring minimum user input for efficient retrieval and extraction of information from free-text clinical narratives. Hand-crafted rules were used to automatically identify a high-confidence training set. This automatically created training dataset was later used to develop metrics and an algorithm that determines the semantic structure of the medical reports. A word-vector cosine similarity metric combined with several heuristics was used to classify each report sentence into one of several pre-defined semantic sections. This baseline algorithm achieved 79% accuracy. A Support Vector Machine (SVM) classifier trained on additional formatting and contextual features was able to achieve 90% accuracy. Plans for future work include developing a configurable system that could accommodate various medical report formatting and content standards.

  20. Hybrid model decomposition of speech and noise in a radial basis function neural model framework

    DEFF Research Database (Denmark)

    Sørensen, Helge Bjarup Dissing; Hartmann, Uwe


    The aim of the paper is to focus on a new approach to automatic speech recognition in noisy environments where the noise has either stationary or non-stationary statistical characteristics. The aim is to perform automatic recognition of speech in the presence of additive car noise. The technique...

  1. Robustness of Structural Systems

    DEFF Research Database (Denmark)

    Canisius, T.D.G.; Sørensen, John Dalsgaard; Baker, J.W.


    The importance of robustness as a property of structural systems has been recognised following several structural failures, such as that at Ronan Point in 1968,where the consequenceswere deemed unacceptable relative to the initiating damage. A variety of research efforts in the past decades have ...... will be proposed. The document adopts a probabilistic risk assessment framework and includes guidance for decision-making related to robustness....... attempted to quantify aspects of robustness such as redundancy and identify design principles that can improve robustness. This paper outlines the progress of recent work by the Joint Committee on Structural Safety (JCSS) to develop comprehensive guidance on assessing and providing robustness in structural...... systems. Guidance is provided regarding the assessment of robustness in a framework that considers potential hazards to the system, vulnerability of system components, and failure consequences. Several proposed methods for quantifying robustness are reviewed, and guidelines for robust design...

  2. A Robust Parallel Algorithm for Combinatorial Compressed Sensing (United States)

    Mendoza-Smith, Rodrigo; Tanner, Jared W.; Wechsung, Florian


    In previous work two of the authors have shown that a vector $x \\in \\mathbb{R}^n$ with at most $k Parallel-$\\ell_0$ decoding algorithm, where $\\mathrm{nnz}(A)$ denotes the number of nonzero entries in $A \\in \\mathbb{R}^{m \\times n}$. In this paper we present the Robust-$\\ell_0$ decoding algorithm, which robustifies Parallel-$\\ell_0$ when the sketch $Ax$ is corrupted by additive noise. This robustness is achieved by approximating the asymptotic posterior distribution of values in the sketch given its corrupted measurements. We provide analytic expressions that approximate these posteriors under the assumptions that the nonzero entries in the signal and the noise are drawn from continuous distributions. Numerical experiments presented show that Robust-$\\ell_0$ is superior to existing greedy and combinatorial compressed sensing algorithms in the presence of small to moderate signal-to-noise ratios in the setting of Gaussian signals and Gaussian additive noise.

  3. Robustness and Eurocodes

    NARCIS (Netherlands)

    Gulvanessian, H.; Vrouwenvelder, A.C.W.M.


    The topic of robustness is essentially covered by two Eurocodes, EN 1990: Euro-code: Basis of Structural Design [5] which provides the high level principles for achieving robustness and EN 1991-1-7 Eurocode 1: Part 1-7 Accidental Actions [6] which provides strategies and methods to obtain robustness

  4. Robustness of Structures

    DEFF Research Database (Denmark)

    Faber, Michael Havbro; Vrouwenvelder, A.C.W.M.; Sørensen, John Dalsgaard


    the development of a joint European project on structural robustness under the COST (European Cooperation in Science and Technology) programme and the decision to develop a more elaborate document on structural robustness in collaboration between experts from the JCSS and the IABSE. Accordingly, a project titled...... ‘COST TU0601: Robustness of Structures’ was initiated in February 2007, aiming to provide a platform for exchanging and promoting research in the area of structural robustness and to provide a basic framework, together with methods, strategies and guidelines enhancing robustness of structures...

  5. Robust-mode analysis of hydrodynamic flows (United States)

    Roy, Sukesh; Gord, James R.; Hua, Jia-Chen; Gunaratne, Gemunu H.


    The emergence of techniques to extract high-frequency high-resolution data introduces a new avenue for modal decomposition to assess the underlying dynamics, especially of complex flows. However, this task requires the differentiation of robust, repeatable flow constituents from noise and other irregular features of a flow. Traditional approaches involving low-pass filtering and principle components analysis have shortcomings. The approach outlined here, referred to as robust-mode analysis, is based on Koopman decomposition. Three applications to (a) a counter-rotating cellular flame state, (b) variations in financial markets, and (c) turbulent injector flows are provided.

  6. Robust multivariate analysis

    CERN Document Server

    J Olive, David


    This text presents methods that are robust to the assumption of a multivariate normal distribution or methods that are robust to certain types of outliers. Instead of using exact theory based on the multivariate normal distribution, the simpler and more applicable large sample theory is given.  The text develops among the first practical robust regression and robust multivariate location and dispersion estimators backed by theory.   The robust techniques  are illustrated for methods such as principal component analysis, canonical correlation analysis, and factor analysis.  A simple way to bootstrap confidence regions is also provided. Much of the research on robust multivariate analysis in this book is being published for the first time. The text is suitable for a first course in Multivariate Statistical Analysis or a first course in Robust Statistics. This graduate text is also useful for people who are familiar with the traditional multivariate topics, but want to know more about handling data sets with...

  7. Occupational Noise Exposure (United States)

    ... Safety and Health Topics / Occupational Noise Exposure Occupational Noise Exposure This page requires that javascript be enabled ... interprets the signal as sound. x What is noise? Noise and vibration are both fluctuations in the ...

  8. Noise in Optical Amplifiers

    DEFF Research Database (Denmark)

    Jeppesen, Palle


    Noise in optical amplifiers is discussed on the basis of photons and electromagntic fields. Formulas for quantum noise from spontaneous emission, signal-spontaneous beat noise and spontaneous-spontaneous beat noise are derived.......Noise in optical amplifiers is discussed on the basis of photons and electromagntic fields. Formulas for quantum noise from spontaneous emission, signal-spontaneous beat noise and spontaneous-spontaneous beat noise are derived....

  9. Automatic document navigation for digital content remastering (United States)

    Lin, Xiaofan; Simske, Steven J.


    This paper presents a novel method of automatically adding navigation capabilities to re-mastered electronic books. We first analyze the need for a generic and robust system to automatically construct navigation links into re-mastered books. We then introduce the core algorithm based on text matching for building the links. The proposed method utilizes the tree-structured dictionary and directional graph of the table of contents to efficiently conduct the text matching. Information fusion further increases the robustness of the algorithm. The experimental results on the MIT Press digital library project are discussed and the key functional features of the system are illustrated. We have also investigated how the quality of the OCR engine affects the linking algorithm. In addition, the analogy between this work and Web link mining has been pointed out.

  10. Robust non-local median filter (United States)

    Matsuoka, Jyohei; Koga, Takanori; Suetake, Noriaki; Uchino, Eiji


    This paper describes a novel image filter with superior performance on detail-preserving removal of random-valued impulse noise superimposed on natural gray-scale images. The non-local means filter is in the limelight as a way of Gaussian noise removal with superior performance on detail preservation. By referring the fundamental concept of the non-local means, we had proposed a non-local median filter as a specialized way for random-valued impulse noise removal so far. In the non-local processing, the output of a filter is calculated from pixels in blocks which are similar to the block centered at a pixel of interest. As a result, aggressive noise removal is conducted without destroying the detailed structures in an original image. However, the performance of non-local processing decreases enormously in the case of high noise occurrence probability. A cause of this problem is that the superimposed noise disturbs accurate calculation of the similarity between the blocks. To cope with this problem, we propose an improved non-local median filter which is robust to the high level of corruption by introducing a new similarity measure considering possibility of being the original signal. The effectiveness and validity of the proposed method are verified in a series of experiments using natural gray-scale images.

  11. Robust Object Tracking Using Valid Fragments Selection. (United States)

    Zheng, Jin; Li, Bo; Tian, Peng; Luo, Gang

    Local features are widely used in visual tracking to improve robustness in cases of partial occlusion, deformation and rotation. This paper proposes a local fragment-based object tracking algorithm. Unlike many existing fragment-based algorithms that allocate the weights to each fragment, this method firstly defines discrimination and uniqueness for local fragment, and builds an automatic pre-selection of useful fragments for tracking. Then, a Harris-SIFT filter is used to choose the current valid fragments, excluding occluded or highly deformed fragments. Based on those valid fragments, fragment-based color histogram provides a structured and effective description for the object. Finally, the object is tracked using a valid fragment template combining the displacement constraint and similarity of each valid fragment. The object template is updated by fusing feature similarity and valid fragments, which is scale-adaptive and robust to partial occlusion. The experimental results show that the proposed algorithm is accurate and robust in challenging scenarios.

  12. Noise in Neuronal and Electronic Circuits: A General Modeling Framework and Non-Monte Carlo Simulation Techniques. (United States)

    Kilinc, Deniz; Demir, Alper


    The brain is extremely energy efficient and remarkably robust in what it does despite the considerable variability and noise caused by the stochastic mechanisms in neurons and synapses. Computational modeling is a powerful tool that can help us gain insight into this important aspect of brain mechanism. A deep understanding and computational design tools can help develop robust neuromorphic electronic circuits and hybrid neuroelectronic systems. In this paper, we present a general modeling framework for biological neuronal circuits that systematically captures the nonstationary stochastic behavior of ion channels and synaptic processes. In this framework, fine-grained, discrete-state, continuous-time Markov chain models of both ion channels and synaptic processes are treated in a unified manner. Our modeling framework features a mechanism for the automatic generation of the corresponding coarse-grained, continuous-state, continuous-time stochastic differential equation models for neuronal variability and noise. Furthermore, we repurpose non-Monte Carlo noise analysis techniques, which were previously developed for analog electronic circuits, for the stochastic characterization of neuronal circuits both in time and frequency domain. We verify that the fast non-Monte Carlo analysis methods produce results with the same accuracy as computationally expensive Monte Carlo simulations. We have implemented the proposed techniques in a prototype simulator, where both biological neuronal and analog electronic circuits can be simulated together in a coupled manner.

  13. Unification of automatic target tracking and automatic target recognition (United States)

    Schachter, Bruce J.


    The subject being addressed is how an automatic target tracker (ATT) and an automatic target recognizer (ATR) can be fused together so tightly and so well that their distinctiveness becomes lost in the merger. This has historically not been the case outside of biology and a few academic papers. The biological model of ATT∪ATR arises from dynamic patterns of activity distributed across many neural circuits and structures (including retina). The information that the brain receives from the eyes is "old news" at the time that it receives it. The eyes and brain forecast a tracked object's future position, rather than relying on received retinal position. Anticipation of the next moment - building up a consistent perception - is accomplished under difficult conditions: motion (eyes, head, body, scene background, target) and processing limitations (neural noise, delays, eye jitter, distractions). Not only does the human vision system surmount these problems, but it has innate mechanisms to exploit motion in support of target detection and classification. Biological vision doesn't normally operate on snapshots. Feature extraction, detection and recognition are spatiotemporal. When vision is viewed as a spatiotemporal process, target detection, recognition, tracking, event detection and activity recognition, do not seem as distinct as they are in current ATT and ATR designs. They appear as similar mechanism taking place at varying time scales. A framework is provided for unifying ATT and ATR.

  14. Yesterday's noise - today's signal

    International Nuclear Information System (INIS)

    Serdula, K.J.


    Plant performance can be improved by noise analysis. This paper describes noise characteristics, imposed noise and response functions, a case history of cost benefits derived from application of noise analysis techniques, areas for application of noise analysis techniques with special reference to the Gentilly-1 nuclear generating station, and the validity of noise measurement results. (E.C.B.)

  15. Automatic Fiscal Stabilizers

    Directory of Open Access Journals (Sweden)

    Narcis Eduard Mitu


    Full Text Available Policies or institutions (built into an economic system that automatically tend to dampen economic cycle fluctuations in income, employment, etc., without direct government intervention. For example, in boom times, progressive income tax automatically reduces money supply as incomes and spendings rise. Similarly, in recessionary times, payment of unemployment benefits injects more money in the system and stimulates demand. Also called automatic stabilizers or built-in stabilizers.

  16. Noise Abatement (United States)


    SMART, Sound Modification and Regulated Temperature compound, is a liquid plastic mixture with exceptional energy and sound absorbing qualities. It is derived from a very elastic plastic which was an effective noise abatement material in the Apollo Guidance System. Discovered by a NASA employee, it is marketed by Environmental Health Systems, Inc. (EHS). The product has been successfully employed by a diaper company with noisy dryers and a sugar company with noisy blowers. The company also manufactures an audiometric test booth and acoustical office partitions.

  17. Automatic differentiation bibliography

    Energy Technology Data Exchange (ETDEWEB)

    Corliss, G.F. (comp.)


    This is a bibliography of work related to automatic differentiation. Automatic differentiation is a technique for the fast, accurate propagation of derivative values using the chain rule. It is neither symbolic nor numeric. Automatic differentiation is a fundamental tool for scientific computation, with applications in optimization, nonlinear equations, nonlinear least squares approximation, stiff ordinary differential equation, partial differential equations, continuation methods, and sensitivity analysis. This report is an updated version of the bibliography which originally appeared in Automatic Differentiation of Algorithms: Theory, Implementation, and Application.

  18. Quantum Noise

    International Nuclear Information System (INIS)

    Beenakker, C W J


    Quantum Noise is advertised as a handbook, and this is indeed how it functions for me these days: it is a book that I keep within hand's reach, ready to be consulted on the proper use of quantum stochastic methods in the course of my research on quantum dots. I should point out that quantum optics, the target field for this book, is not my field by training. So I have much to learn, and find this handbook to be a reliable and helpful guide. Crispin Gardiner previously wrote the Handbook of Stochastic Methods (also published by Springer), which provides an overview of methods in classical statistical physics. Quantum Noise, written jointly with Peter Zoller, is the counterpart for quantum statistical physics, and indeed the two books rely on each other by frequent cross referencing. The fundamental problem addressed by Quantum Noise is how the quantum dynamics of an open system can be described statistically by treating the environment as a source of noise. This is a general problem in condensed matter physics (in particular in the context of Josephson junctions) and in quantum optics. The emphasis in this book in on the optical applications (for condensed matter applications one could consult Quantum Dissipative Systems by Ulrich Weiss, published by World Scientific). The optical applications centre around the interaction of light with atoms, where the atoms represent the open system and the light is the noisy environment. A complete description of the production and detection of non-classical states of radiation (such as squeezed states) can be obtained using one of the equivalent quantum stochastic formulations: the quantum Langevin equation for the field operators (in either the Ito or the Stratonovich form), the Master equation for the density matrix, or the stochastic Schroedinger equation for the wave functions. Each formulation is fully developed here (as one would expect from a handbook), with detailed instructions on how to go from one to the other. The

  19. Robust distributed cognitive relay beamforming

    KAUST Repository

    Pandarakkottilil, Ubaidulla


    In this paper, we present a distributed relay beamformer design for a cognitive radio network in which a cognitive (or secondary) transmit node communicates with a secondary receive node assisted by a set of cognitive non-regenerative relays. The secondary nodes share the spectrum with a licensed primary user (PU) node, and each node is assumed to be equipped with a single transmit/receive antenna. The interference to the PU resulting from the transmission from the cognitive nodes is kept below a specified limit. The proposed robust cognitive relay beamformer design seeks to minimize the total relay transmit power while ensuring that the transceiver signal-to-interference- plus-noise ratio and PU interference constraints are satisfied. The proposed design takes into account a parameter of the error in the channel state information (CSI) to render the performance of the beamformer robust in the presence of imperfect CSI. Though the original problem is non-convex, we show that the proposed design can be reformulated as a tractable convex optimization problem that can be solved efficiently. Numerical results are provided and illustrate the performance of the proposed designs for different network operating conditions and parameters. © 2012 IEEE.

  20. Robust Pitch Estimation Using an Optimal Filter on Frequency Estimates

    DEFF Research Database (Denmark)

    Karimian-Azari, Sam; Jensen, Jesper Rindom; Christensen, Mads Græsbøll


    In many scenarios, a periodic signal of interest is often contaminated by different types of noise that may render many existing pitch estimation methods suboptimal, e.g., due to an incorrect white Gaussian noise assumption. In this paper, a method is established to estimate the pitch of such sig......In many scenarios, a periodic signal of interest is often contaminated by different types of noise that may render many existing pitch estimation methods suboptimal, e.g., due to an incorrect white Gaussian noise assumption. In this paper, a method is established to estimate the pitch...... against different noise situations. The simulation results confirm that the proposed MVDR method outperforms the state-of-the-art weighted least squares (WLS) pitch estimator in colored noise and has robust pitch estimates against missing harmonics in some time-frames....

  1. A low noise clock generator for high-resolution time-to-digital convertors

    International Nuclear Information System (INIS)

    Prinzie, J.; Leroux, P.; Christiaensen, J.; Moreira, P.; Steyaert, M.


    A robust PLL clock generator has been designed for the harsh environment in high-energy physics applications. The PLL operates with a reference clock frequency of 40 MHz to 50 MHz and performs a multiplication by 64. An LC tank VCO with low internal phase noise can generate a frequency from 2.2 GHz up to 3.2 GHz with internal discrete bank switching. The PLL includes an automatic bank selection algorithm to correctly select the correct range of the oscillator. The PLL has been fabricated in a 65 nm CMOS technology and consumes less than 30 mW. The additive jitter of the PLL has been measured to be less than 400 fs RMS

  2. A low noise clock generator for high-resolution time-to-digital convertors (United States)

    Prinzie, J.; Christiaensen, J.; Moreira, P.; Steyaert, M.; Leroux, P.


    A robust PLL clock generator has been designed for the harsh environment in high-energy physics applications. The PLL operates with a reference clock frequency of 40 MHz to 50 MHz and performs a multiplication by 64. An LC tank VCO with low internal phase noise can generate a frequency from 2.2 GHz up to 3.2 GHz with internal discrete bank switching. The PLL includes an automatic bank selection algorithm to correctly select the correct range of the oscillator. The PLL has been fabricated in a 65 nm CMOS technology and consumes less than 30 mW. The additive jitter of the PLL has been measured to be less than 400 fs RMS.


    Directory of Open Access Journals (Sweden)

    Jan Kalina


    Full Text Available This paper is devoted to highly robust methods for information extraction from data, with a special attention paid to methods suitable for management applications. The sensitivity of availabledata mining methods to the presence of outlying measurements in the observed data is discussed as a major drawback of available data mining methods. The paper proposes several newhighly robustmethods for data mining, which are based on the idea of implicit weighting of individual data values.Particularly it propose a novel robust method of hierarchical cluster analysis, which is a popular data mining method of unsupervised learning. Further, a robust method for estimating parameters in thelogistic regression was proposed. This idea is extended to a robust multinomial logistic classification analysis. Finally, the sensitivity of neural networks to the presence of noise and outlying measurements in the data was discussed. The method for robust training of neural networks for the task of function approximation, which has the form of a robust estimator in nonlinear regression, was proposed.

  4. Brain MR Image Restoration Using an Automatic Trilateral Filter With GPU-Based Acceleration. (United States)

    Chang, Herng-Hua; Li, Cheng-Yuan; Gallogly, Audrey Haihong


    Noise reduction in brain magnetic resonance (MR) images has been a challenging and demanding task. This study develops a new trilateral filter that aims to achieve robust and efficient image restoration. Extended from the bilateral filter, the proposed algorithm contains one additional intensity similarity funct-ion, which compensates for the unique characteristics of noise in brain MR images. An entropy function adaptive to intensity variations is introduced to regulate the contributions of the weighting components. To hasten the computation, parallel computing based on the graphics processing unit (GPU) strategy is explored with emphasis on memory allocations and thread distributions. To automate the filtration, image texture feature analysis associated with machine learning is investigated. Among the 98 candidate features, the sequential forward floating selection scheme is employed to acquire the optimal texture features for regularization. Subsequently, a two-stage classifier that consists of support vector machines and artificial neural networks is established to predict the filter parameters for automation. A speedup gain of 757 was reached to process an entire MR image volume of 256 × 256 × 256 pixels, which completed within 0.5 s. Automatic restoration results revealed high accuracy with an ensemble average relative error of 0.53 ± 0.85% in terms of the peak signal-to-noise ratio. This self-regulating trilateral filter outperformed many state-of-the-art noise reduction methods both qualitatively and quantitatively. We believe that this new image restoration algorithm is of potential in many brain MR image processing applications that require expedition and automation.

  5. Estimating the coherence of noise (United States)

    Wallman, Joel

    To harness the advantages of quantum information processing, quantum systems have to be controlled to within some maximum threshold error. Certifying whether the error is below the threshold is possible by performing full quantum process tomography, however, quantum process tomography is inefficient in the number of qubits and is sensitive to state-preparation and measurement errors (SPAM). Randomized benchmarking has been developed as an efficient method for estimating the average infidelity of noise to the identity. However, the worst-case error, as quantified by the diamond distance from the identity, can be more relevant to determining whether an experimental implementation is at the threshold for fault-tolerant quantum computation. The best possible bound on the worst-case error (without further assumptions on the noise) scales as the square root of the infidelity and can be orders of magnitude greater than the reported average error. We define a new quantification of the coherence of a general noise channel, the unitarity, and show that it can be estimated using an efficient protocol that is robust to SPAM. Furthermore, we also show how the unitarity can be used with the infidelity obtained from randomized benchmarking to obtain improved estimates of the diamond distance and to efficiently determine whether experimental noise is close to stochastic Pauli noise.

  6. Automatic control systems engineering

    International Nuclear Information System (INIS)

    Shin, Yun Gi


    This book gives descriptions of automatic control for electrical electronics, which indicates history of automatic control, Laplace transform, block diagram and signal flow diagram, electrometer, linearization of system, space of situation, state space analysis of electric system, sensor, hydro controlling system, stability, time response of linear dynamic system, conception of root locus, procedure to draw root locus, frequency response, and design of control system.

  7. Neural Bases of Automaticity (United States)

    Servant, Mathieu; Cassey, Peter; Woodman, Geoffrey F.; Logan, Gordon D.


    Automaticity allows us to perform tasks in a fast, efficient, and effortless manner after sufficient practice. Theories of automaticity propose that across practice processing transitions from being controlled by working memory to being controlled by long-term memory retrieval. Recent event-related potential (ERP) studies have sought to test this…

  8. Focusing Automatic Code Inspections

    NARCIS (Netherlands)

    Boogerd, C.J.


    Automatic Code Inspection tools help developers in early detection of defects in software. A well-known drawback of many automatic inspection approaches is that they yield too many warnings and require a clearer focus. In this thesis, we provide such focus by proposing two methods to prioritize

  9. Automatic differentiation of functions

    International Nuclear Information System (INIS)

    Douglas, S.R.


    Automatic differentiation is a method of computing derivatives of functions to any order in any number of variables. The functions must be expressible as combinations of elementary functions. When evaluated at specific numerical points, the derivatives have no truncation error and are automatically found. The method is illustrated by simple examples. Source code in FORTRAN is provided


    African Journals Online (AJOL)

    Both the nursing staff shortage and the need for precise control in the administration of dangerous drugs intra- venously have led to the development of various devices to achieve an automatic system. The continuous automatic control of the drip rate eliminates errors due to any physical effect such as movement of the ...

  11. Automatic Camera Control

    DEFF Research Database (Denmark)

    Burelli, Paolo; Preuss, Mike


    Automatically generating computer animations is a challenging and complex problem with applications in games and film production. In this paper, we investigate howto translate a shot list for a virtual scene into a series of virtual camera configurations — i.e automatically controlling the virtual...

  12. Noise resistant quantum control using dynamical invariants (United States)

    Levy, Amikam; Kiely, A.; Muga, J. G.; Kosloff, R.; Torrontegui, E.


    A systematic approach to design robust control protocols against the influence of different types of noise is introduced. We present control schemes which protect the decay of the populations avoiding dissipation in the adiabatic and nonadiabatic regimes and minimize the effect of dephasing. The effectiveness of the protocols is demonstrated in two different systems. Firstly, we present the case of population inversion of a two-level system in the presence of either one or two simultaneous noise sources. Secondly, we present an example of the expansion of coherent and thermal states in harmonic traps, subject to noise arising from monitoring and modulation of the control, respectively.

  13. Iterative robust multiprocessor scheduling

    NARCIS (Netherlands)

    Adyanthaya, S.; Geilen, M.; Basten, T.; Voeten, J.; Schiffelers, R.


    General purpose platforms are characterized by unpredictable timing behavior. Real-time schedules of tasks on general purpose platforms need to be robust against variations in task execution times. We define robustness in terms of the expected number of tasks that miss deadlines. We present an

  14. Robustness to strategic uncertainty

    NARCIS (Netherlands)

    Andersson, O.; Argenton, C.; Weibull, J.W.

    We introduce a criterion for robustness to strategic uncertainty in games with continuum strategy sets. We model a player's uncertainty about another player's strategy as an atomless probability distribution over that player's strategy set. We call a strategy profile robust to strategic uncertainty

  15. Robustness - theoretical framework

    DEFF Research Database (Denmark)

    Sørensen, John Dalsgaard; Rizzuto, Enrico; Faber, Michael H.


    not be disproportional to the causes of the damages'. However, despite the importance of robustness for structural design such requirements are not substantiated in more detail, nor have the engineering profession been able to agree on an interpretation of robustness which facilitates for its quantification. The ain...

  16. Mechanisms for Robust Cognition (United States)

    Walsh, Matthew M.; Gluck, Kevin A.


    To function well in an unpredictable environment using unreliable components, a system must have a high degree of robustness. Robustness is fundamental to biological systems and is an objective in the design of engineered systems such as airplane engines and buildings. Cognitive systems, like biological and engineered systems, exist within…

  17. Automatic delineation of functional volumes in emission tomography for oncology applications

    International Nuclear Information System (INIS)

    Hatt, M.


    One of the main factors of error for semi-quantitative analysis in positron emission tomography (PET) imaging for diagnosis and patient follow up, as well as new flourishing applications like image guided radiotherapy, is the methodology used to define the volumes of interest in the functional images. This is explained by poor image quality in emission tomography resulting from noise and partial volume effects induced blurring, as well as the variability of acquisition protocols, scanner models and image reconstruction procedures. The large number of proposed methodologies for the definition of a PET volume of interest does not help either. The majority of such proposed approaches are based on deterministic binary thresholding that are not robust to contrast variation and noise. In addition, these methodologies are usually unable to correctly handle heterogeneous uptake inside tumours. The objective of this thesis is to develop an automatic, robust, accurate and reproducible 3D image segmentation approach for the functional volumes determination of tumours of all sizes and shapes, and whose activity distribution may be strongly heterogeneous. The approach we have developed is based on a statistical image segmentation framework, combined with a fuzzy measure, which allows to take into account both noisy and blurry properties of nuclear medicine images. It uses a stochastic iterative parameters estimation and a locally adaptive model of the voxel and its neighbours for the estimation and segmentation. The developed approaches have been evaluated using a large array of datasets, comprising both simulated and real acquisitions of phantoms and tumours. The results obtained on phantom acquisitions allowed to validate the accuracy of the segmentation with respect to the size of considered structures, down to 13 mm in diameter (about twice the spatial resolution of a typical PET scanner), as well as its robustness with respect to noise, contrast variation, acquisition

  18. Quaternion Wiener Deconvolution for Noise Robust Color Image Registration

    Czech Academy of Sciences Publication Activity Database

    Pedone, M.; Bayro-Corrochano, E.; Flusser, Jan; Heikkilä, J.


    Roč. 22, č. 9 (2015), s. 1278-1282 ISSN 1070-9908 R&D Projects: GA ČR GA13-29225S Keywords : Clifford algebra * multivector derivative * phase correlation * quaternion * Wiener filter Subject RIV: JD - Computer Applications, Robotics Impact factor: 1.661, year: 2015

  19. Noise thermometer

    International Nuclear Information System (INIS)

    Von Brixy, H.; Kakuta, Tsunemi.


    The noise thermometry (NT) is a temperature measuring method by which the absolute temperature measurement can be performed with a very high accuracy and without any influence of ambient environments and of the thermal history of its NT sensor (electric resistor). Hence it is quite suitable for application as a standard thermometry to the in-situ temperature calibration of incore thermocouples. The KFA Juelich had played a pioneering role in the development of NT and applied the results successfully to the AVR for testing its feasibility. In this report, all about the NT including its principle, sensor elements and system configurations are presented together with the experiences in the AVR and the results of investigation to apply it to high temperature measurement. The NT can be adopted as a standard method for incore temperature measurement and in situ temperature calibration in the HTTR. (author). 85 refs

  20. Noise thermometer

    Energy Technology Data Exchange (ETDEWEB)

    Von Brixy, H. [Forschungszentrum Juelich GmbH (Germany); Kakuta, Tsunemi


    The noise thermometry (NT) is a temperature measuring method by which the absolute temperature measurement can be performed with a very high accuracy and without any influence of ambient environments and of the thermal history of its NT sensor (electric resistor). Hence it is quite suitable for application as a standard thermometry to the in-situ temperature calibration of incore thermocouples. The KFA Juelich had played a pioneering role in the development of NT and applied the results successfully to the AVR for testing its feasibility. In this report, all about the NT including its principle, sensor elements and system configurations are presented together with the experiences in the AVR and the results of investigation to apply it to high temperature measurement. The NT can be adopted as a standard method for incore temperature measurement and in situ temperature calibration in the HTTR. (author). 85 refs.

  1. Design optimization for cost and quality: The robust design approach (United States)

    Unal, Resit


    Designing reliable, low cost, and operable space systems has become the key to future space operations. Designing high quality space systems at low cost is an economic and technological challenge to the designer. A systematic and efficient way to meet this challenge is a new method of design optimization for performance, quality, and cost, called Robust Design. Robust Design is an approach for design optimization. It consists of: making system performance insensitive to material and subsystem variation, thus allowing the use of less costly materials and components; making designs less sensitive to the variations in the operating environment, thus improving reliability and reducing operating costs; and using a new structured development process so that engineering time is used most productively. The objective in Robust Design is to select the best combination of controllable design parameters so that the system is most robust to uncontrollable noise factors. The robust design methodology uses a mathematical tool called an orthogonal array, from design of experiments theory, to study a large number of decision variables with a significantly small number of experiments. Robust design also uses a statistical measure of performance, called a signal-to-noise ratio, from electrical control theory, to evaluate the level of performance and the effect of noise factors. The purpose is to investigate the Robust Design methodology for improving quality and cost, demonstrate its application by the use of an example, and suggest its use as an integral part of space system design process.

  2. Non-Linear Metamodeling Extensions to the Robust Parameter Design of Computer Simulations (United States)


    Pacific Grove, CA: Brooks/Cole Publishing Company, 1995. [78] G. Casella and R. L. Berger, Statistical Inference (2nd Edition), Pacific Grove, CA... probability distributions. The noise factors introduce undesirable variation in the system’s outputs. When noise factors are present, robust random variables with specific probability distributions. The noise factors introduce undesirable variation in the system’s output. When noise

  3. Robust and intelligent algorithms for TDOA localization in distributed sensor networks (United States)

    Fang, Jiaqi; He, Zhiyi; Jian, Cui


    Passive source localization utilizing time difference of arrival (TDOA) has widely application in radar, navigation, surveillance, wireless communication, distributed sensor network, etc. This paper presents two robust algorithms named Modified Taylor-seriesmethod (MTS) and Modified Newton (MNT) method. The proposed algorithms are the improvement of the Taylor-series (TS) and Newton (NT) methods for solving the convergent problem which is critical in the iterative methods. The key component of the proposed algorithms is to produce a new modified Hessian matrix intelligently using the Regularization theory which can turn the ill-posed Hessian matrix into a well-conditioned matrix. The regularization parameter which controls the properties of the regularized solution can be automatically determined by the L-curve method. With this procedure, the proposed methods are robust to make the iteration convergence with a bad initial. Simulation results show that the proposed methods improve the convergent probability and have better capability to distinguish the local minimums from the global solutions compared with the TS and NT methods. The proposed methods give superiorperformances of the location accuracy comparing with the closed-form algorithms at large measurement noises.

  4. Adaptive and robust statistical methods for processing near-field scanning microwave microscopy images. (United States)

    Coakley, K J; Imtiaz, A; Wallis, T M; Weber, J C; Berweger, S; Kabos, P


    Near-field scanning microwave microscopy offers great potential to facilitate characterization, development and modeling of materials. By acquiring microwave images at multiple frequencies and amplitudes (along with the other modalities) one can study material and device physics at different lateral and depth scales. Images are typically noisy and contaminated by artifacts that can vary from scan line to scan line and planar-like trends due to sample tilt errors. Here, we level images based on an estimate of a smooth 2-d trend determined with a robust implementation of a local regression method. In this robust approach, features and outliers which are not due to the trend are automatically downweighted. We denoise images with the Adaptive Weights Smoothing method. This method smooths out additive noise while preserving edge-like features in images. We demonstrate the feasibility of our methods on topography images and microwave |S11| images. For one challenging test case, we demonstrate that our method outperforms alternative methods from the scanning probe microscopy data analysis software package Gwyddion. Our methods should be useful for massive image data sets where manual selection of landmarks or image subsets by a user is impractical. Published by Elsevier B.V.

  5. A robust recognition and accurate locating method for circular coded diagonal target (United States)

    Bao, Yunna; Shang, Yang; Sun, Xiaoliang; Zhou, Jiexin


    As a category of special control points which can be automatically identified, artificial coded targets have been widely developed in the field of computer vision, photogrammetry, augmented reality, etc. In this paper, a new circular coded target designed by RockeTech technology Corp. Ltd is analyzed and studied, which is called circular coded diagonal target (CCDT). A novel detection and recognition method with good robustness is proposed in the paper, and implemented on Visual Studio. In this algorithm, firstly, the ellipse features of the center circle are used for rough positioning. Then, according to the characteristics of the center diagonal target, a circular frequency filter is designed to choose the correct center circle and eliminates non-target noise. The precise positioning of the coded target is done by the correlation coefficient fitting extreme value method. Finally, the coded target recognition is achieved by decoding the binary sequence in the outer ring of the extracted target. To test the proposed algorithm, this paper has carried out simulation experiments and real experiments. The results show that the CCDT recognition and accurate locating method proposed in this paper can robustly recognize and accurately locate the targets in complex and noisy background.

  6. Robust stability analysis of adaptation algorithms for single perceptron. (United States)

    Hui, S; Zak, S H


    The problem of robust stability and convergence of learning parameters of adaptation algorithms in a noisy environment for the single preceptron is addressed. The case in which the same input pattern is presented in the adaptation cycle is analyzed. The algorithm proposed is of the Widrow-Hoff type. It is concluded that this algorithm is robust. However, the weight vectors do not necessarily converge in the presence of measurement noise. A modified version of this algorithm in which the reduction factors are allowed to vary with time is proposed, and it is shown that this algorithm is robust and that the weight vectors converge in the presence of bounded noise. Only deterministic-type arguments are used in the analysis. An ultimate bound on the error in terms of a convex combination of the initial error and the bound on the noise is obtained.

  7. Noise-driven phenomena in hysteretic systems

    CERN Document Server

    Dimian, Mihai


    Noise-Driven Phenomena in Hysteretic Systems provides a general approach to nonlinear systems with hysteresis driven by noisy inputs, which leads to a unitary framework for the analysis of various stochastic aspects of hysteresis. This book includes integral, differential and algebraic models that are used to describe scalar and vector hysteretic nonlinearities originating from various areas of science and engineering. The universality of the authors approach is also reflected by the diversity of the models used to portray the input noise, from the classical Gaussian white noise to its impulsive forms, often encountered in economics and biological systems, and pink noise, ubiquitous in multi-stable electronic systems. The book is accompanied by HysterSoft© - a robust simulation environment designed to perform complex hysteresis modeling – that can be used by the reader to reproduce many of the results presented in the book as well as to research both disruptive and constructive effects of noise in hysteret...

  8. Automatic fringe enhancement with novel bidimensional sinusoids-assisted empirical mode decomposition. (United States)

    Wang, Chenxing; Kemao, Qian; Da, Feipeng


    Fringe-based optical measurement techniques require reliable fringe analysis methods, where empirical mode decomposition (EMD) is an outstanding one due to its ability of analyzing complex signals and the merit of being data-driven. However, two challenging issues hinder the application of EMD in practical measurement. One is the tricky mode mixing problem (MMP), making the decomposed intrinsic mode functions (IMFs) have equivocal physical meaning; the other is the automatic and accurate extraction of the sinusoidal fringe from the IMFs when unpredictable and unavoidable background and noise exist in real measurements. Accordingly, in this paper, a novel bidimensional sinusoids-assisted EMD (BSEMD) is proposed to decompose a fringe pattern into mono-component bidimensional IMFs (BIMFs), with the MMP solved; properties of the resulted BIMFs are then analyzed to recognize and enhance the useful fringe component. The decomposition and the fringe recognition are integrated and the latter provides a feedback to the former, helping to automatically stop the decomposition to make the algorithm simpler and more reliable. A series of experiments show that the proposed method is accurate, efficient and robust to various fringe patterns even with poor quality, rendering it a potential tool for practical use.

  9. An automatic microseismic or acoustic emission arrival identification scheme with deep recurrent neural networks (United States)

    Zheng, Jing; Lu, Jiren; Peng, Suping; Jiang, Tianqi


    The conventional arrival pick-up algorithms cannot avoid the manual modification of the parameters for the simultaneous identification of multiple events under different signal-to-noise ratios (SNRs). Therefore, in order to automatically obtain the arrivals of multiple events with high precision under different SNRs, in this study an algorithm was proposed which had the ability to pick up the arrival of microseismic or acoustic emission events based on deep recurrent neural networks. The arrival identification was performed using two important steps, which included a training phase and a testing phase. The training process was mathematically modelled by deep recurrent neural networks using Long Short-Term Memory architecture. During the testing phase, the learned weights were utilized to identify the arrivals through the microseismic/acoustic emission data sets. The data sets were obtained by rock physics experiments of the acoustic emission. In order to obtain the data sets under different SNRs, this study added random noise to the raw experiments' data sets. The results showed that the outcome of the proposed method was able to attain an above 80 per cent hit-rate at SNR 0 dB, and an approximately 70 per cent hit-rate at SNR -5 dB, with an absolute error in 10 sampling points. These results indicated that the proposed method had high selection precision and robustness.

  10. FliPer: checking the reliability of global seismic parameters from automatic pipelines (United States)

    Bugnet, L.; García, R. A.; Davies, G. R.; Mathur, S.; Corsaro, E.


    Our understanding of stars through asteroseismic data analysis is limited by our ability to take advantage of the huge amount of observed stars provided by space missions such as CoRoT, \\keplerp, \\ktop, and soon TESS and PLATO. Global seismic pipelines provide global stellar parameters such as mass and radius using the mean seismic parameters, as well as the effective temperature. These pipelines are commonly used automatically on thousands of stars observed by K2 for 3 months (and soon TESS for at least ˜ 1 month). However, pipelines are not immune from misidentifying noise peaks and stellar oscillations. Therefore, new validation techniques are required to assess the quality of these results. We present a new metric called FliPer (Flicker in Power), which takes into account the average variability at all measured time scales. The proper calibration of \\powvar enables us to obtain good estimations of global stellar parameters such as surface gravity that are robust against the influence of noise peaks and hence are an excellent way to find faults in asteroseismic pipelines.

  11. Robustness Beamforming Algorithms

    Directory of Open Access Journals (Sweden)

    Sajad Dehghani


    Full Text Available Adaptive beamforming methods are known to degrade in the presence of steering vector and covariance matrix uncertinity. In this paper, a new approach is presented to robust adaptive minimum variance distortionless response beamforming make robust against both uncertainties in steering vector and covariance matrix. This method minimize a optimization problem that contains a quadratic objective function and a quadratic constraint. The optimization problem is nonconvex but is converted to a convex optimization problem in this paper. It is solved by the interior-point method and optimum weight vector to robust beamforming is achieved.

  12. User evaluation of a communication system that automatically generates captions to improve telephone communication

    NARCIS (Netherlands)

    Zekveld, A.A.; Kramer, S.E.; Kessens, J.M.; Vlaming, M.S.M.G.; Houtgast, T.


    This study examined the subjective benefit obtained from automatically generated captions during telephone-speech comprehension in the presence of babble noise. Short stories were presented by telephone either with or without captions that were generated offline by an automatic speech recognition

  13. Noise and Hearing Protection (United States)

    ... ENTCareers Marketplace Find an ENT Doctor Near You Noise and Hearing Protection Noise and Hearing Protection Patient ... it is. How can I tell if a noise is dangerous? People differ in their sensitivity to ...

  14. Inhibitory noise

    Directory of Open Access Journals (Sweden)

    Alain Destexhe


    Full Text Available Cortical neurons in vivo may operate in high-conductance states, in which the major part of the neuron's input conductance is due to synaptic activity, sometimes several-fold larger than the resting conductance. We examine here the contribution of inhibition in such high-conductance states. At the level of the absolute conductance values, several studies have shown that cortical neurons in vivo are characterized by strong inhibitory conductances. However, conductances are balanced and spiking activity is mostly determined by fluctuations, but not much is known about excitatory and inhibitory contributions to these fluctuations. Models and dynamic-clamp experiments show that, during high-conductance states, spikes are mainly determined by fluctuations of inhibition, or by inhibitory noise. This stands in contrast to low-conductance states, in which excitatory conductances determine spiking activity. To determine these contributions from experimental data, maximum likelihood methods can be designed and applied to intracellular recordings in vivo. Such methods indicate that action potentials are indeed mostly correlated with inhibitory fluctuations in awake animals. These results argue for a determinant role for inhibitory fluctuations in evoking spikes, and do not support feed-forward modes of processing, for which opposite patterns are predicted.

  15. Perceptual Robust Design

    DEFF Research Database (Denmark)

    Pedersen, Søren Nygaard

    are just a few examples of cost drivers. In general, the earlier quality issues are addressed the less costs they impose. Robust design methodology seeks to anticipate many of these quality issues by making product designs less sensitive to variation. The approach was first introduced by Genichi Taguchi......The research presented in this PhD thesis has focused on a perceptual approach to robust design. The results of the research and the original contribution to knowledge is a preliminary framework for understanding, positioning, and applying perceptual robust design. Product quality is a topic...... in the 1980s and has since been expanded and refined. In more recent contributions, the notion of visual robustness has been introduced to the field of design research. However, contributions have only addressed the visual domain and no underlying theory on which to position or understand these studies have...

  16. Robust FIR Beamforming Applied TO Medical Ultrasound (United States)

    Guenther, Drake A.; Walker, William F.


    We previously described a beamformer architecture that replaces the single apodization weights on each receive channel with channel-unique finite impulse response (FIR) filters. The filter weights are designed to optimize the contrast resolution performance of the imaging system. While the FIR beamformer offers significant gains in contrast resolution, the beamformer suffers from low sensitivity and its performance rapidly degrades in the presence of noise. In this paper a new method is presented to improve the robustness of the FIR beamformer to electronic noise as well as variation or uncertainty in the array response. A method is also described, which controls the sidelobe levels of the FIR beamformer’s spatial response by applying an arbitrary weighting function in the filter design algorithm. The robust FIR beamformer is analyzed using a generalized cystic resolution metric that quantifies a beamformer’s clinical imaging performance as a function of cyst size and channel input signal-to-noise ratio (SNR). Fundamental performance limits are compared between two robust FIR beamformers (the dynamic focus FIR (DF-FIR) beamformer and the group focus FIR (GF-FIR) beamformer), the conventional delay-and-sum (DAS) beamformer, and the spatial matched filter (SMF) beamformer. Results from this study show that the new DF- and GF-FIR beamformers are more robust to electronic noise compared to the optimal contrast resolution FIR beamformer. Furthermore, the added robustness only comes with a slight loss in cystic resolution. Results from the generalized cystic resolution metric show that a 9-tap robust FIR beamformer outperforms the SMF and DAS beamformer until receive channel input SNR drops below −5 dB; whereas, the 9-tap optimal contrast resolution beamformer’s performance deteriorates around 50 dB SNR. The effects of moderate phase aberrations, characterized by an a priori root-mean-square strength of 28 ns and an a priori full-width at half-maximum correlation

  17. Noise-Measuring Method

    DEFF Research Database (Denmark)

    Diamond, J. M.


    A noise-measuring method based on the use of a calibrated noise generator and an output meter with a special scale is described. The method eliminates the effect of noise contributions occurring in the circuits following the device under test.......A noise-measuring method based on the use of a calibrated noise generator and an output meter with a special scale is described. The method eliminates the effect of noise contributions occurring in the circuits following the device under test....

  18. A robust WENO scheme for nonlinear waves in a moving reference frame

    DEFF Research Database (Denmark)

    Kontos, Stavros; Bingham, Harry B.; Lindberg, Ole


    For robust nonlinear wave simulation in a moving reference frame, we recast the free surface problem in Hamilton-Jacobi form and propose a Weighted Essentially Non-Oscillatory (WENO) scheme to automatically handle the upwinding of the convective term. A new automatic procedure for deriving the li...

  19. Robust Crane Control


    Marek Hičár; Juraj Ritók


    The paper presents robust crane design by asynchronnous motor with frequencyconvertor at ensuring system robustness against load weight and rope length variation.Exact position control and elimination of swinging in the final position are required too.Firstly were assemblied mathematical models of main crane components: crab, bridge anduplift by real model of double beamed bridge experimental crane. Was designed robustcontrol for defined interval variation of weight and rope length for real c...

  20. Automatic Test Systems Aquisition

    National Research Council Canada - National Science Library


    We are providing this final memorandum report for your information and use. This report discusses the efforts to achieve commonality in standards among the Military Departments as part of the DoD policy for automatic test systems (ATS...

  1. Objective and subjective rating of tonal noise radiated from UK wind farms: Pt. 2

    International Nuclear Information System (INIS)


    This final report provides data on the assessment of tonal noise radiation from wind turbines in the United Kingdom. Both objective and subjective assessments of the noise pollution from various wind farms are incorporated in the study. Previous subjective tests are verified here using a larger subject and sample size compared to the initial study. The study also aims to produce an objective automatic tonal assessment procedure which identifies tones and broad band masking noise in wind farm radiated noise spectra. (UK)

  2. Automatic requirements traceability


    Andžiulytė, Justė


    This paper focuses on automatic requirements traceability and algorithms that automatically find recommendation links for requirements. The main objective of this paper is the evaluation of these algorithms and preparation of the method defining algorithms to be used in different cases. This paper presents and examines probabilistic, vector space and latent semantic indexing models of information retrieval and association rule mining using authors own implementations of these algorithms and o...

  3. Position automatic determination technology

    International Nuclear Information System (INIS)


    This book tells of method of position determination and characteristic, control method of position determination and point of design, point of sensor choice for position detector, position determination of digital control system, application of clutch break in high frequency position determination, automation technique of position determination, position determination by electromagnetic clutch and break, air cylinder, cam and solenoid, stop position control of automatic guide vehicle, stacker crane and automatic transfer control.

  4. Internal noise-sustained circadian rhythms in a Drosophila model. (United States)

    Li, Qianshu; Lang, Xiufeng


    Circadian rhythmic processes, mainly regulated by gene expression at the molecular level, have inherent stochasticity. Their robustness or resistance to internal noise has been extensively investigated by most of the previous studies. This work focuses on the constructive roles of internal noise in a reduced Drosophila model, which incorporates negative and positive feedback loops, each with a time delay. It is shown that internal noise sustains reliable oscillations with periods close to 24 h in a region of parameter space, where the deterministic kinetics would evolve to a stable steady state. The amplitudes of noise-sustained oscillations are significantly affected by the variation of internal noise level, and the best performance of the oscillations could be found at an optimal noise intensity, indicating the occurrence of intrinsic coherence resonance. In the oscillatory region of the deterministic model, the coherence of noisy circadian oscillations is suppressed by internal noise, while the period remains nearly constant over a large range of noise intensity, demonstrating robustness of the Drosophila model for circadian rhythms to intrinsic noise. In addition, the effects of time delay in the positive feedback on the oscillations are also investigated. It is found that the time delay could efficiently tune the performance of the noise-sustained oscillations. These results might aid understanding of the exploitation of intracellular noise in biochemical and genetic regulatory systems.

  5. Fully automatic and precise data analysis developed for time-of-flight mass spectrometry. (United States)

    Meyer, Stefan; Riedo, Andreas; Neuland, Maike B; Tulej, Marek; Wurz, Peter


    Scientific objectives of current and future space missions are focused on the investigation of the origin and evolution of the solar system with the particular emphasis on habitability and signatures of past and present life. For in situ measurements of the chemical composition of solid samples on planetary surfaces, the neutral atmospheric gas and the thermal plasma of planetary atmospheres, the application of mass spectrometers making use of time-of-flight mass analysers is a technique widely used. However, such investigations imply measurements with good statistics and, thus, a large amount of data to be analysed. Therefore, faster and especially robust automated data analysis with enhanced accuracy is required. In this contribution, an automatic data analysis software, which allows fast and precise quantitative data analysis of time-of-flight mass spectrometric data, is presented and discussed in detail. A crucial part of this software is a robust and fast peak finding algorithm with a consecutive numerical integration method allowing precise data analysis. We tested our analysis software with data from different time-of-flight mass spectrometers and different measurement campaigns thereof. The quantitative analysis of isotopes, using automatic data analysis, yields results with an accuracy of isotope ratios up to 100 ppm for a signal-to-noise ratio (SNR) of 10 4 . We show that the accuracy of isotope ratios is in fact proportional to SNR -1 . Furthermore, we observe that the accuracy of isotope ratios is inversely proportional to the mass resolution. Additionally, we show that the accuracy of isotope ratios is depending on the sample width T s by T s 0.5 . Copyright © 2017 John Wiley & Sons, Ltd. Copyright © 2017 John Wiley & Sons, Ltd.

  6. A robust nonlinear filter for image restoration. (United States)

    Koivunen, V


    A class of nonlinear regression filters based on robust estimation theory is introduced. The goal of the filtering is to recover a high-quality image from degraded observations. Models for desired image structures and contaminating processes are employed, but deviations from strict assumptions are allowed since the assumptions on signal and noise are typically only approximately true. The robustness of filters is usually addressed only in a distributional sense, i.e., the actual error distribution deviates from the nominal one. In this paper, the robustness is considered in a broad sense since the outliers may also be due to inappropriate signal model, or there may be more than one statistical population present in the processing window, causing biased estimates. Two filtering algorithms minimizing a least trimmed squares criterion are provided. The design of the filters is simple since no scale parameters or context-dependent threshold values are required. Experimental results using both real and simulated data are presented. The filters effectively attenuate both impulsive and nonimpulsive noise while recovering the signal structure and preserving interesting details.

  7. Underwater noise levels in UK waters. (United States)

    Merchant, Nathan D; Brookes, Kate L; Faulkner, Rebecca C; Bicknell, Anthony W J; Godley, Brendan J; Witt, Matthew J


    Underwater noise from human activities appears to be rising, with ramifications for acoustically sensitive marine organisms and the functioning of marine ecosystems. Policymakers are beginning to address the risk of ecological impact, but are constrained by a lack of data on current and historic noise levels. Here, we present the first nationally coordinated effort to quantify underwater noise levels, in support of UK policy objectives under the EU Marine Strategy Framework Directive (MSFD). Field measurements were made during 2013-2014 at twelve sites around the UK. Median noise levels ranged from 81.5-95.5 dB re 1 μPa for one-third octave bands from 63-500 Hz. Noise exposure varied considerably, with little anthropogenic influence at the Celtic Sea site, to several North Sea sites with persistent vessel noise. Comparison of acoustic metrics found that the RMS level (conventionally used to represent the mean) was highly skewed by outliers, exceeding the 97 th percentile at some frequencies. We conclude that environmental indicators of anthropogenic noise should instead use percentiles, to ensure statistical robustness. Power analysis indicated that at least three decades of continuous monitoring would be required to detect trends of similar magnitude to historic rises in noise levels observed in the Northeast Pacific.

  8. Robust and sparse correlation matrix estimation for the analysis of high-dimensional genomics data. (United States)

    Serra, Angela; Coretto, Pietro; Fratello, Michele; Tagliaferri, Roberto; Stegle, Oliver


    Microarray technology can be used to study the expression of thousands of genes across a number of different experimental conditions, usually hundreds. The underlying principle is that genes sharing similar expression patterns, across different samples, can be part of the same co-expression system, or they may share the same biological functions. Groups of genes are usually identified based on cluster analysis. Clustering methods rely on the similarity matrix between genes. A common choice to measure similarity is to compute the sample correlation matrix. Dimensionality reduction is another popular data analysis task which is also based on covariance/correlation matrix estimates. Unfortunately, covariance/correlation matrix estimation suffers from the intrinsic noise present in high-dimensional data. Sources of noise are: sampling variations, presents of outlying sample units, and the fact that in most cases the number of units is much larger than the number of genes. In this paper, we propose a robust correlation matrix estimator that is regularized based on adaptive thresholding. The resulting method jointly tames the effects of the high-dimensionality, and data contamination. Computations are easy to implement and do not require hand tunings. Both simulated and real data are analyzed. A Monte Carlo experiment shows that the proposed method is capable of remarkable performances. Our correlation metric is more robust to outliers compared with the existing alternatives in two gene expression datasets. It is also shown how the regularization allows to automatically detect and filter spurious correlations. The same regularization is also extended to other less robust correlation measures. Finally, we apply the ARACNE algorithm on the SyNTreN gene expression data. Sensitivity and specificity of the reconstructed network is compared with the gold standard. We show that ARACNE performs better when it takes the proposed correlation matrix estimator as input. The R

  9. A new algorithm for automatic Outlier Detection in GPS Time Series (United States)

    Cannavo', Flavio; Mattia, Mario; Rossi, Massimo; Palano, Mimmo; Bruno, Valentina


    Nowadays continuous GPS time series are considered a crucial product of GPS permanent networks, useful in many geo-science fields, such as active tectonics, seismology, crustal deformation and volcano monitoring (Altamimi et al. 2002, Elósegui et al. 2006, Aloisi et al. 2009). Although the GPS data elaboration software has increased in reliability, the time series are still affected by different kind of noise, from the intrinsic noise (e.g. thropospheric delay) to the un-modeled noise (e.g. cycle slips, satellite faults, parameters changing). Typically GPS Time Series present characteristic noise that is a linear combination of white noise and correlated colored noise, and this characteristic is fractal in the sense that is evident for every considered time scale or sampling rate. The un-modeled noise sources result in spikes, outliers and steps. These kind of errors can appreciably influence the estimation of velocities of the monitored sites. The outlier detection in generic time series is a widely treated problem in literature (Wei, 2005), while is not fully developed for the specific kind of GPS series. We propose a robust automatic procedure for cleaning the GPS time series from the outliers and, especially for long daily series, steps due to strong seismic or volcanic events or merely instrumentation changing such as antenna and receiver upgrades. The procedure is basically divided in two steps: a first step for the colored noise reduction and a second step for outlier detection through adaptive series segmentation. Both algorithms present novel ideas and are nearly unsupervised. In particular, we propose an algorithm to estimate an autoregressive model for colored noise in GPS time series in order to subtract the effect of non Gaussian noise on the series. This step is useful for the subsequent step (i.e. adaptive segmentation) which requires the hypothesis of Gaussian noise. The proposed algorithms are tested in a benchmark case study and the results

  10. Robustness in econometrics

    CERN Document Server

    Sriboonchitta, Songsak; Huynh, Van-Nam


    This book presents recent research on robustness in econometrics. Robust data processing techniques – i.e., techniques that yield results minimally affected by outliers – and their applications to real-life economic and financial situations are the main focus of this book. The book also discusses applications of more traditional statistical techniques to econometric problems. Econometrics is a branch of economics that uses mathematical (especially statistical) methods to analyze economic systems, to forecast economic and financial dynamics, and to develop strategies for achieving desirable economic performance. In day-by-day data, we often encounter outliers that do not reflect the long-term economic trends, e.g., unexpected and abrupt fluctuations. As such, it is important to develop robust data processing techniques that can accommodate these fluctuations.

  11. Robust Manufacturing Control

    CERN Document Server


    This contributed volume collects research papers, presented at the CIRP Sponsored Conference Robust Manufacturing Control: Innovative and Interdisciplinary Approaches for Global Networks (RoMaC 2012, Jacobs University, Bremen, Germany, June 18th-20th 2012). These research papers present the latest developments and new ideas focusing on robust manufacturing control for global networks. Today, Global Production Networks (i.e. the nexus of interconnected material and information flows through which products and services are manufactured, assembled and distributed) are confronted with and expected to adapt to: sudden and unpredictable large-scale changes of important parameters which are occurring more and more frequently, event propagation in networks with high degree of interconnectivity which leads to unforeseen fluctuations, and non-equilibrium states which increasingly characterize daily business. These multi-scale changes deeply influence logistic target achievement and call for robust planning and control ...

  12. Fast and robust shape diameter function. (United States)

    Chen, Shuangmin; Liu, Taijun; Shu, Zhenyu; Xin, Shiqing; He, Ying; Tu, Changhe


    The shape diameter function (SDF) is a scalar function defined on a closed manifold surface, measuring the neighborhood diameter of the object at each point. Due to its pose oblivious property, SDF is widely used in shape analysis, segmentation and retrieval. However, computing SDF is computationally expensive since one has to place an inverted cone at each point and then average the penetration distances for a number of rays inside the cone. Furthermore, the shape diameters are highly sensitive to local geometric features as well as the normal vectors, hence diminishing their applications to real-world meshes which often contain rich geometric details and/or various types of defects, such as noise and gaps. In order to increase the robustness of SDF and promote it to a wide range of 3D models, we define SDF by offsetting the input object a little bit. This seemingly minor change brings three significant benefits: First, it allows us to compute SDF in a robust manner since the offset surface is able to give reliable normal vectors. Second, it runs many times faster since at each point we only need to compute the penetration distance along a single direction, rather than tens of directions. Third, our method does not require watertight surfaces as the input-it supports both point clouds and meshes with noise and gaps. Extensive experimental results show that the offset-surface based SDF is robust to noise and insensitive to geometric details, and it also runs about 10 times faster than the existing method. We also exhibit its usefulness using two typical applications including shape retrieval and shape segmentation, and observe a significant improvement over the existing SDF.

  13. Disentangling Complexity in Bayesian Automatic Adaptive Quadrature (United States)

    Adam, Gheorghe; Adam, Sanda


    The paper describes a Bayesian automatic adaptive quadrature (BAAQ) solution for numerical integration which is simultaneously robust, reliable, and efficient. Detailed discussion is provided of three main factors which contribute to the enhancement of these features: (1) refinement of the m-panel automatic adaptive scheme through the use of integration-domain-length-scale-adapted quadrature sums; (2) fast early problem complexity assessment - enables the non-transitive choice among three execution paths: (i) immediate termination (exceptional cases); (ii) pessimistic - involves time and resource consuming Bayesian inference resulting in radical reformulation of the problem to be solved; (iii) optimistic - asks exclusively for subrange subdivision by bisection; (3) use of the weaker accuracy target from the two possible ones (the input accuracy specifications and the intrinsic integrand properties respectively) - results in maximum possible solution accuracy under minimum possible computing time.

  14. Training shortest-path tractography: Automatic learning of spatial priors

    DEFF Research Database (Denmark)

    Kasenburg, Niklas; Liptrot, Matthew George; Reislev, Nina Linde


    knowledge. Here we demonstrate how such prior knowledge, or indeed any prior spatial information, can be automatically incorporated into a shortest-path tractography approach to produce more robust results. We describe how such a prior can be automatically generated (learned) from a population, and we......Tractography is the standard tool for automatic delineation of white matter tracts from diffusion weighted images. However, the output of tractography often requires post-processing to remove false positives and ensure a robust delineation of the studied tract, and this demands expert prior...... demonstrate that our framework also retains support for conventional interactive constraints such as waypoint regions. We apply our approach to the open access, high quality Human Connectome Project data, as well as a dataset acquired on a typical clinical scanner. Our results show that the use of a learned...

  15. Robust plasmonic substrates

    DEFF Research Database (Denmark)

    Kostiučenko, Oksana; Fiutowski, Jacek; Tamulevicius, Tomas


    Robustness is a key issue for the applications of plasmonic substrates such as tip-enhanced Raman spectroscopy, surface-enhanced spectroscopies, enhanced optical biosensing, optical and optoelectronic plasmonic nanosensors and others. A novel approach for the fabrication of robust plasmonic...... substrates is presented, which relies on the coverage of gold nanostructures with diamond-like carbon (DLC) thin films of thicknesses 25, 55 and 105 nm. DLC thin films were grown by direct hydrocarbon ion beam deposition. In order to find the optimum balance between optical and mechanical properties...

  16. Robust Self Tuning Controllers

    DEFF Research Database (Denmark)

    Poulsen, Niels Kjølstad


    The present thesis concerns robustness properties of adaptive controllers. It is addressed to methods for robustifying self tuning controllers with respect to abrupt changes in the plant parameters. In the thesis an algorithm for estimating abruptly changing parameters is presented. The estimator...... has several operation modes and a detector for controlling the mode. A special self tuning controller has been developed to regulate plant with changing time delay.......The present thesis concerns robustness properties of adaptive controllers. It is addressed to methods for robustifying self tuning controllers with respect to abrupt changes in the plant parameters. In the thesis an algorithm for estimating abruptly changing parameters is presented. The estimator...

  17. Non-Markovian noise

    International Nuclear Information System (INIS)

    Fulinski, A.


    The properties of non-Markovian noises with exponentially correlated memory are discussed. Considered are dichotomic noise, white shot noise, Gaussian white noise, and Gaussian colored noise. The stationary correlation functions of the non-Markovian versions of these noises are given by linear combinations of two or three exponential functions (colored noises) or of the δ function and exponential function (white noises). The non-Markovian white noises are well defined only when the kernel of the non-Markovian master equation contains a nonzero admixture of a Markovian term. Approximate equations governing the probability densities for processes driven by such non-Markovian noises are derived, including non-Markovian versions of the Fokker-Planck equation and the telegrapher's equation. As an example, it is shown how the non-Markovian nature changes the behavior of the driven linear process

  18. Efficient robust conditional random fields. (United States)

    Song, Dongjin; Liu, Wei; Zhou, Tianyi; Tao, Dacheng; Meyer, David A


    Conditional random fields (CRFs) are a flexible yet powerful probabilistic approach and have shown advantages for popular applications in various areas, including text analysis, bioinformatics, and computer vision. Traditional CRF models, however, are incapable of selecting relevant features as well as suppressing noise from noisy original features. Moreover, conventional optimization methods often converge slowly in solving the training procedure of CRFs, and will degrade significantly for tasks with a large number of samples and features. In this paper, we propose robust CRFs (RCRFs) to simultaneously select relevant features. An optimal gradient method (OGM) is further designed to train RCRFs efficiently. Specifically, the proposed RCRFs employ the l1 norm of the model parameters to regularize the objective used by traditional CRFs, therefore enabling discovery of the relevant unary features and pairwise features of CRFs. In each iteration of OGM, the gradient direction is determined jointly by the current gradient together with the historical gradients, and the Lipschitz constant is leveraged to specify the proper step size. We show that an OGM can tackle the RCRF model training very efficiently, achieving the optimal convergence rate [Formula: see text] (where k is the number of iterations). This convergence rate is theoretically superior to the convergence rate O(1/k) of previous first-order optimization methods. Extensive experiments performed on three practical image segmentation tasks demonstrate the efficacy of OGM in training our proposed RCRFs.

  19. Robust laser frequency stabilization by serrodyne modulation. (United States)

    Kohlhaas, Ralf; Vanderbruggen, Thomas; Bernon, Simon; Bertoldi, Andrea; Landragin, Arnaud; Bouyer, Philippe


    We report the relative frequency stabilization of a distributed feedback erbium-doped fiber laser on an optical cavity by serrodyne frequency shifting. A correction bandwidth of 2.3 MHz and a dynamic range of 220 MHz are achieved, which leads to a strong robustness against large disturbances up to high frequencies. We demonstrate that serrodyne frequency shifting reaches a higher correction bandwidth and lower relative frequency noise level compared to a standard acousto-optical modulator based scheme. Our results allow us to consider promising applications in the absolute frequency stabilization of lasers on optical cavities.

  20. Robust Neural Sliding Mode Control of Robot Manipulators

    International Nuclear Information System (INIS)

    Nguyen Tran Hiep; Pham Thuong Cat


    This paper proposes a robust neural sliding mode control method for robot tracking problem to overcome the noises and large uncertainties in robot dynamics. The Lyapunov direct method has been used to prove the stability of the overall system. Simulation results are given to illustrate the applicability of the proposed method

  1. DWT-based blind and robust watermarking using SPIHT algorithm ...

    Indian Academy of Sciences (India)

    DWT-based blind and robust watermarking using SPIHT algorithm with applications in tele-medicine. TOSHANLAL MEENPAL. Volume 43 Issue 1 January 2018 ... Keywords. Arnold transform; discrete wavelet transform (DWT); tele-medicine; Noise Visibility Function (NVF); Set Partitioning In Hierarchical Trees (SPIHT).

  2. Robust Adaptive Speed Control of Induction Motor Drives

    DEFF Research Database (Denmark)

    Bidstrup, N.

    was little in practice. The seccond approach was only to update the controller parameters when excitation in load occurred. This was achieved by incorporating a dead zone in the estimator. This approach had significant effect on the robustness against output noise both in simulations and in practice...

  3. assessment of noise pollutio noise pollutio noise pollution

    African Journals Online (AJOL)


    1DEPARTMENT OF WATER RESOURCES ... challenges. Symptoms of short or long periods exposure to noise include auditory effects such auditory fatigue and hearing loss, and indirect n auditory effects such as speech interfere .... ASSESSMENT OF NOISE POLLUTION FROM SAWMILL ACTIVITIES IN ILORIN, NIGERIA.

  4. assessment of noise pollutio noise pollutio noise pollution

    African Journals Online (AJOL)


    This study examine. This study examined noise pollution pollution pollution from sawmillin from sawmillin using HD600 digital data l using HD600 digital data logging sound level me ogging sound level me designed to elicit noise related information. The res sawmills was 58.1 sawmills was 58.1-64.86 dB(A) while machine ...

  5. Robust Reed Solomon Coded MPSK Modulation

    Directory of Open Access Journals (Sweden)

    Emir M. Husni


    Full Text Available In this paper, construction of partitioned Reed Solomon coded modulation (RSCM, which is robust for the additive white Gaussian noise channel and a Rayleigh fading channel, is investigated. By matching configuration of component codes with the channel characteristics, it is shown that this system is robust for the Gaussian and a Rayleigh fading channel. This approach is compared with non-partitioned RSCM, a Reed Solomon code combined with an MPSK signal set using Gray mapping; and block coded MPSK modulation using binary codes, Reed Muller codes. All codes use hard decision decoding algorithm. Simulation results for these schemes show that RSCM based on set partitioning performs better than those that are not based on set partitioning and Reed Muller Coded Modulation across a wide range of conditions. The novel idea here is that in the receiver, we use a rotated 2^(m+1-PSK detector if the transmitter uses a 2^m-PSK modulator.

  6. FluxFix: automatic isotopologue normalization for metabolic tracer analysis. (United States)

    Trefely, Sophie; Ashwell, Peter; Snyder, Nathaniel W


    Isotopic tracer analysis by mass spectrometry is a core technique for the study of metabolism. Isotopically labeled atoms from substrates, such as [ 13 C]-labeled glucose, can be traced by their incorporation over time into specific metabolic products. Mass spectrometry is often used for the detection and differentiation of the isotopologues of each metabolite of interest. For meaningful interpretation, mass spectrometry data from metabolic tracer experiments must be corrected to account for the naturally occurring isotopologue distribution. The calculations required for this correction are time consuming and error prone and existing programs are often platform specific, non-intuitive, commercially licensed and/or limited in accuracy by using theoretical isotopologue distributions, which are prone to artifacts from noise or unresolved interfering signals. Here we present FluxFix ( ), an application freely available on the internet that quickly and reliably transforms signal intensity values into percent mole enrichment for each isotopologue measured. 'Unlabeled' data, representing the measured natural isotopologue distribution for a chosen analyte, is entered by the user. This data is used to generate a correction matrix according to a well-established algorithm. The correction matrix is applied to labeled data, also entered by the user, thus generating the corrected output data. FluxFix is compatible with direct copy and paste from spreadsheet applications including Excel (Microsoft) and Google sheets and automatically adjusts to account for input data dimensions. The program is simple, easy to use, agnostic to the mass spectrometry platform, generalizable to known or unknown metabolites, and can take input data from either a theoretical natural isotopologue distribution or an experimentally measured one. Our freely available web-based calculator, FluxFix ( ), quickly and reliably corrects metabolic tracer data for

  7. Traffic Noise Assessment at Residential Areas in Skudai, Johor (United States)

    Sulaiman, F. S.; Darus, N.; Mashros, N.; Haron, Z.; Yahya, K.


    Vehicles passing by on roadways in residential areas may produce unpleasant traffic noise that affects the residents. This paper presents the traffic noise assessment of three selected residential areas located in Skudai, Johor. The objectives of this study are to evaluate traffic characteristics at selected residential areas, determine related noise indices, and assess impact of traffic noise. Traffic characteristics such as daily traffic volume and vehicle speed were evaluated using automatic traffic counter (ATC). Meanwhile, noise indices like equivalent continuous sound pressure level (LAeq), noise level exceeded 10% (L10) and 90% (L90) of measurement time were determined using sound level meter (SLM). Besides that, traffic noise index (TNI) and noise pollution level (LNP) were calculated based on the measured noise indices. The results showed an increase in noise level of 60 to 70 dBA maximum due to increase in traffic volume. There was also a significant change in noise level of more than 70 dBA even though average vehicle speed did not vary significantly. Nevertheless, LAeq, TNI, and LNP values for all sites during daytime were lower than the maximum recommended levels. Thus, residents in the three studied areas were not affected in terms of quality of life and health.

  8. Robust surgery loading

    NARCIS (Netherlands)

    Hans, Elias W.; Wullink, Gerhard; van Houdenhoven, Mark; Kazemier, Geert


    We consider the robust surgery loading problem for a hospital’s operating theatre department, which concerns assigning surgeries and sufficient planned slack to operating room days. The objective is to maximize capacity utilization and minimize the risk of overtime, and thus cancelled patients. This

  9. Robustness of structures

    DEFF Research Database (Denmark)

    Vrouwenvelder, T.; Sørensen, John Dalsgaard


    robustness is still an issue of controversy and poses difficulties in regard to interpretation as well as regulation. Typically modern structural design codes require that ‘the consequence of damages to structures should not be disproportional to the causes of the damages'. However, despite the importance...

  10. Robustness of Structures

    DEFF Research Database (Denmark)

    Faber, Michael Havbro; Vrouwenvelder, A.C.W.M.; Sørensen, John Dalsgaard


    In 2005, the Joint Committee on Structural Safety (JCSS) together with Working Commission (WC) 1 of the International Association of Bridge and Structural Engineering (IABSE) organized a workshop on robustness of structures. Two important decisions resulted from this workshop, namely the developm...

  11. Robustness of spatial micronetworks (United States)

    McAndrew, Thomas C.; Danforth, Christopher M.; Bagrow, James P.


    Power lines, roadways, pipelines, and other physical infrastructure are critical to modern society. These structures may be viewed as spatial networks where geographic distances play a role in the functionality and construction cost of links. Traditionally, studies of network robustness have primarily considered the connectedness of large, random networks. Yet for spatial infrastructure, physical distances must also play a role in network robustness. Understanding the robustness of small spatial networks is particularly important with the increasing interest in microgrids, i.e., small-area distributed power grids that are well suited to using renewable energy resources. We study the random failures of links in small networks where functionality depends on both spatial distance and topological connectedness. By introducing a percolation model where the failure of each link is proportional to its spatial length, we find that when failures depend on spatial distances, networks are more fragile than expected. Accounting for spatial effects in both construction and robustness is important for designing efficient microgrids and other network infrastructure.

  12. A Context Dependent Automatic Target Recognition System (United States)

    Kim, J. H.; Payton, D. W.; Olin, K. E.; Tseng, D. Y.


    This paper describes a new approach to automatic target recognizer (ATR) development utilizing artificial intelligent techniques. The ATR system exploits contextual information in its detection and classification processes to provide a high degree of robustness and adaptability. In the system, knowledge about domain objects and their contextual relationships is encoded in frames, separating it from low level image processing algorithms. This knowledge-based system demonstrates an improvement over the conventional statistical approach through the exploitation of diverse forms of knowledge in its decision-making process.

  13. Two Systems for Automatic Music Genre Recognition

    DEFF Research Database (Denmark)

    Sturm, Bob L.


    We re-implement and test two state-of-the-art systems for automatic music genre classification; but unlike past works in this area, we look closer than ever before at their behavior. First, we look at specific instances where each system consistently applies the same wrong label across multiple...... trials of cross-validation. Second, we test the robustness of each system to spectral equalization. Finally, we test how well human subjects recognize the genres of music excerpts composed by each system to be highly genre representative. Our results suggest that neither high-performing system has...... a capacity to recognize music genre....

  14. Neuromorphic Configurable Architecture for Robust Motion Estimation

    Directory of Open Access Journals (Sweden)

    Guillermo Botella


    Full Text Available The robustness of the human visual system recovering motion estimation in almost any visual situation is enviable, performing enormous calculation tasks continuously, robustly, efficiently, and effortlessly. There is obviously a great deal we can learn from our own visual system. Currently, there are several optical flow algorithms, although none of them deals efficiently with noise, illumination changes, second-order motion, occlusions, and so on. The main contribution of this work is the efficient implementation of a biologically inspired motion algorithm that borrows nature templates as inspiration in the design of architectures and makes use of a specific model of human visual motion perception: Multichannel Gradient Model (McGM. This novel customizable architecture of a neuromorphic robust optical flow can be constructed with FPGA or ASIC device using properties of the cortical motion pathway, constituting a useful framework for building future complex bioinspired systems running in real time with high computational complexity. This work includes the resource usage and performance data, and the comparison with actual systems. This hardware has many application fields like object recognition, navigation, or tracking in difficult environments due to its bioinspired and robustness properties.

  15. Automatic text summarization

    CERN Document Server

    Torres Moreno, Juan Manuel


    This new textbook examines the motivations and the different algorithms for automatic document summarization (ADS). We performed a recent state of the art. The book shows the main problems of ADS, difficulties and the solutions provided by the community. It presents recent advances in ADS, as well as current applications and trends. The approaches are statistical, linguistic and symbolic. Several exemples are included in order to clarify the theoretical concepts.  The books currently available in the area of Automatic Document Summarization are not recent. Powerful algorithms have been develop

  16. Automatic Ultrasound Scanning

    DEFF Research Database (Denmark)

    Moshavegh, Ramin

    on the scanners, and to improve the computer-aided diagnosis (CAD) in ultrasound by introducing new quantitative measures. Thus, four major issues concerning automation of the medical ultrasound are addressed in this PhD project. They touch upon gain adjustments in ultrasound, automatic synthetic aperture image...... on the user adjustments on the scanner interface to optimize the scan settings. This explains the huge interest in the subject of this PhD project entitled “AUTOMATIC ULTRASOUND SCANNING”. The key goals of the project have been to develop automated techniques to minimize the unnecessary settings...

  17. Robust Adaptive Speed Control of Induction Motor Drives

    DEFF Research Database (Denmark)

    Bidstrup, N.

    , (LS) identification and generalized predictive control (GPC) has been implemented and tested on the CVC drive. Allthough GPC is a robust control method, it was not possible to maintain specified controller performance in the entire operating range. This was the main reason for investigating truly...... adaptive speed control of the CVC drive. A direct truly adaptive speed controller has been implemented. The adaptive controller is a moving Average Self-Tuning Regulator which is abbreviated MASTR throughout the thesis. Two practical implementations of this controller were proposed. They were denoted MASTR...... and measurement noise in general, were the major reasons for the drifting parameters. Two approaches was proposed to robustify MASTR2 against the output noise. The first approach consists of filtering the output. Output filtering had a significant effect in simulations, but the robustness against the output noise...

  18. Underwater radiated noise from modern commercial ships. (United States)

    McKenna, Megan F; Ross, Donald; Wiggins, Sean M; Hildebrand, John A


    Underwater radiated noise measurements for seven types of modern commercial ships during normal operating conditions are presented. Calibrated acoustic data (autonomous seafloor-mounted acoustic recorder were combined with ship passage information from the Automatic Identification System. This approach allowed for detailed measurements (i.e., source level, sound exposure level, and transmission range) on ships of opportunity. A key result was different acoustic levels and spectral shapes observed from different ship-types. A 54 kGT container ship had the highest broadband source level at 188 dB re 1 μPa@1m; a 26 kGT chemical tanker had the lowest at 177 dB re 1 μPa@1m. Bulk carriers had higher source levels near 100 Hz, while container ship and tanker noise was predominantly below 40 Hz. Simple models to predict source levels of modern merchant ships as a group from particular ship characteristics (e.g., length, gross tonnage, and speed) were not possible given individual ship-type differences. Furthermore, ship noise was observed to radiate asymmetrically. Stern aspect noise levels are 5 to 10 dB higher than bow aspect noise levels. Collectively, these results emphasize the importance of including modern ship-types in quantifying shipping noise for predictive models of global, regional, and local marine environments. © 2012 Acoustical Society of America.

  19. A Developed Graphical User Interface for Power System Stability and Robustness Studies


    GHOURAF Djamel Eddine; NACERI Abdellatif; ABID Mohamed; KABI Wahiba


    This paper present the realization and development of a graphical user interface (GUI) to studied the stability and robustness of power systems (analysis and synthesis), using Conventional Power System Stabilizers (CPSS - realized on PID scheme) or advanced controllers (based on adaptive and robust control), and applied on automatic excitation control of powerful synchronous generators, to improve dynamic performances and robustness. The GUI is a useful average to facilitate stability study o...

  20. Noise-dependent optimal strategies for quantum metrology (United States)

    Huang, Zixin; Macchiavello, Chiara; Maccone, Lorenzo


    For phase estimation using qubits, we show that for some noise channels, the optimal entanglement-assisted strategy depends on the noise level. We note that there is a nontrivial crossover between the parallel-entangled strategy and the ancilla-assisted strategy: in the former the probes are all entangled; in the latter the probes are entangled with a noiseless ancilla but not among themselves. The transition can be explained by the fact that separable states are more robust against noise and therefore are optimal in the high-noise limit, but they are in turn outperformed by ancilla-assisted ones.

  1. Aviation noise effects (United States)

    Newman, J. S.; Beattie, K. R.


    This report summarizes the effects of aviation noise in many areas, ranging from human annoyance to impact on real estate values. It also synthesizes the findings of literature on several topics. Included in the literature were many original studies carried out under FAA and other Federal funding over the past two decades. Efforts have been made to present the critical findings and conclusions of pertinent research, providing, when possible, a bottom line conclusion, criterion or perspective. Issues related to aviation noise are highlighted, and current policy is presented. Specific topic addressed include: annoyance; Hearing and hearing loss; noise metrics; human response to noise; speech interference; sleep interference; non-auditory health effects of noise; effects of noise on wild and domesticated animals; low frequency acoustical energy; impulsive noise; time of day weightings; noise contours; land use compatibility; and real estate values. This document is designed for a variety of users, from the individual completely unfamiliar with aviation noise to experts in the field.

  2. Efficient algorithms for robust recovery of images from compressed data. (United States)

    Pham, Duc-Son; Venkatesh, Svetha


    Compressed sensing (CS) is an important theory for sub-Nyquist sampling and recovery of compressible data. Recently, it has been extended to cope with the case where corruption to the CS data is modeled as impulsive noise. The new formulation, termed as robust CS, combines robust statistics and CS into a single framework to suppress outliers in the CS recovery. To solve the newly formulated robust CS problem, a scheme that iteratively solves a number of CS problems--the solutions from which provably converge to the true robust CS solution--is suggested. This scheme is, however, rather inefficient as it has to use existing CS solvers as a proxy. To overcome limitations with the original robust CS algorithm, we propose in this paper more computationally efficient algorithms by following latest advances in large-scale convex optimization for nonsmooth regularization. Furthermore, we also extend the robust CS formulation to various settings, including additional affine constraints, l1-norm loss function, mix-norm regularization, and multitasking, so as to further improve robust CS and derive simple but effective algorithms to solve these extensions. We demonstrate that the new algorithms provide much better computational advantage over the original robust CS method on the original robust CS formulation, and effectively solve more sophisticated extensions where the original methods simply cannot. We demonstrate the usefulness of the extensions on several imaging tasks.

  3. Matrix sentence intelligibility prediction using an automatic speech recognition system. (United States)

    Schädler, Marc René; Warzybok, Anna; Hochmuth, Sabine; Kollmeier, Birger


    The feasibility of predicting the outcome of the German matrix sentence test for different types of stationary background noise using an automatic speech recognition (ASR) system was studied. Speech reception thresholds (SRT) of 50% intelligibility were predicted in seven noise conditions. The ASR system used Mel-frequency cepstral coefficients as a front-end and employed whole-word Hidden Markov models on the back-end side. The ASR system was trained and tested with noisy matrix sentences on a broad range of signal-to-noise ratios. The ASR-based predictions were compared to data from the literature ( Hochmuth et al, 2015 ) obtained with 10 native German listeners with normal hearing and predictions of the speech intelligibility index (SII). The ASR-based predictions showed a high and significant correlation (R² = 0.95, p speech and noise signals. Minimum assumptions were made about human speech processing already incorporated in a reference-free ordinary ASR system.

  4. Total variation with automatic hyper-parameter estimation. (United States)

    Nascimento, Jacinto; Sanches, João


    Medical diagnosis is often hampered by the quality of the images. This happens in a wide range of image modalities. Image noise reduction is a crucial step, however difficult to be accomplished. Bayesian algorithms have been commonly used with success, namely with additive white Gaussian noise (AWGN) model. In fact, the noise corrupting some of the most used medical imaging modalities is not additive neither Gaussian but multiplicative described by Poisson or Rayleigh distributions. This paper proposes a unified framework with automatic hyper parameters estimation. The proposed framework deals with AWGN but also with both Poisson and Rayleigh distributions. The algorithm proposed herein, is based on a maximum a posteriori (MAP) criterion with the edge preserving prior based on the total variation (TV), which avoids the distortion of relevant anatomical details. The denoising technique is performed via single parametric iterative scheme parameterized for each noise model considered. Tests with real data from several medical imaging modalities testify the performance of the algorithm.

  5. Automatic online spike sorting with singular value decomposition and fuzzy C-mean clustering

    Directory of Open Access Journals (Sweden)

    Oliynyk Andriy


    Full Text Available Abstract Background Understanding how neurons contribute to perception, motor functions and cognition requires the reliable detection of spiking activity of individual neurons during a number of different experimental conditions. An important problem in computational neuroscience is thus to develop algorithms to automatically detect and sort the spiking activity of individual neurons from extracellular recordings. While many algorithms for spike sorting exist, the problem of accurate and fast online sorting still remains a challenging issue. Results Here we present a novel software tool, called FSPS (Fuzzy SPike Sorting, which is designed to optimize: (i fast and accurate detection, (ii offline sorting and (iii online classification of neuronal spikes with very limited or null human intervention. The method is based on a combination of Singular Value Decomposition for fast and highly accurate pre-processing of spike shapes, unsupervised Fuzzy C-mean, high-resolution alignment of extracted spike waveforms, optimal selection of the number of features to retain, automatic identification the number of clusters, and quantitative quality assessment of resulting clusters independent on their size. After being trained on a short testing data stream, the method can reliably perform supervised online classification and monitoring of single neuron activity. The generalized procedure has been implemented in our FSPS spike sorting software (available free for non-commercial academic applications at the address: using LabVIEW (National Instruments, USA. We evaluated the performance of our algorithm both on benchmark simulated datasets with different levels of background noise and on real extracellular recordings from premotor cortex of Macaque monkeys. The results of these tests showed an excellent accuracy in discriminating low-amplitude and overlapping spikes under strong background noise. The performance of our method is

  6. Automatic online spike sorting with singular value decomposition and fuzzy C-mean clustering. (United States)

    Oliynyk, Andriy; Bonifazzi, Claudio; Montani, Fernando; Fadiga, Luciano


    Understanding how neurons contribute to perception, motor functions and cognition requires the reliable detection of spiking activity of individual neurons during a number of different experimental conditions. An important problem in computational neuroscience is thus to develop algorithms to automatically detect and sort the spiking activity of individual neurons from extracellular recordings. While many algorithms for spike sorting exist, the problem of accurate and fast online sorting still remains a challenging issue. Here we present a novel software tool, called FSPS (Fuzzy SPike Sorting), which is designed to optimize: (i) fast and accurate detection, (ii) offline sorting and (iii) online classification of neuronal spikes with very limited or null human intervention. The method is based on a combination of Singular Value Decomposition for fast and highly accurate pre-processing of spike shapes, unsupervised Fuzzy C-mean, high-resolution alignment of extracted spike waveforms, optimal selection of the number of features to retain, automatic identification the number of clusters, and quantitative quality assessment of resulting clusters independent on their size. After being trained on a short testing data stream, the method can reliably perform supervised online classification and monitoring of single neuron activity. The generalized procedure has been implemented in our FSPS spike sorting software (available free for non-commercial academic applications at the address: using LabVIEW (National Instruments, USA). We evaluated the performance of our algorithm both on benchmark simulated datasets with different levels of background noise and on real extracellular recordings from premotor cortex of Macaque monkeys. The results of these tests showed an excellent accuracy in discriminating low-amplitude and overlapping spikes under strong background noise. The performance of our method is competitive with respect to other robust spike

  7. Reactor component automatic grapple

    International Nuclear Information System (INIS)

    Greenaway, P.R.


    A grapple for handling nuclear reactor components in a medium such as liquid sodium which, upon proper seating and alignment of the grapple with the component as sensed by a mechanical logic integral to the grapple, automatically seizes the component. The mechanical logic system also precludes seizure in the absence of proper seating and alignment. (author)

  8. Automatic Commercial Permit Sets

    Energy Technology Data Exchange (ETDEWEB)

    Grana, Paul [Folsom Labs, Inc., San Francisco, CA (United States)


    Final report for Folsom Labs’ Solar Permit Generator project, which has successfully completed, resulting in the development and commercialization of a software toolkit within the cloud-based HelioScope software environment that enables solar engineers to automatically generate and manage draft documents for permit submission.

  9. Automatic Complexity Analysis

    DEFF Research Database (Denmark)

    Rosendahl, Mads


    One way to analyse programs is to to derive expressions for their computational behaviour. A time bound function (or worst-case complexity) gives an upper bound for the computation time as a function of the size of input. We describe a system to derive such time bounds automatically using abstrac...

  10. Solar noise storms

    CERN Document Server

    Elgaroy, E O


    Solar Noise Storms examines the properties and features of solar noise storm phenomenon. The book also presents some theories that can be used to gain a better understanding of the phenomenon. The coverage of the text includes topics that cover the features and behavior of noise storms, such as the observable features of noise storms; the relationship between noise storms and the observable features on the sun; and ordered behavior of storm bursts in the time-frequency plane. The book also covers the spectrum, polarization, and directivity of noise storms. The text will be of great use to astr

  11. Automatically operated maglev public transport line in Nagoya

    Energy Technology Data Exchange (ETDEWEB)

    Hibi, Osamu [Aichi Rapid Transit Co., Aichi Prefecture (Japan). Engineering Dept.


    Tobu-Kyuryo-Line in Nagoya (Japan) is a mid-size automatically operated passenger line which adopts the HSST (high-speed surface transport) system. The vehicles are levitated with normal conducting electromagnets and propelled by a linear induction motor. Low noise by levitation and stable acceleration by the linear induction motor improve the riding comfort and ensure a faster transportation. Automatic operation is indispensable for stable operation and reduction of running costs. In the opening year, the Tobu-Kyuryo-Line played an important role as an access to EXPO2005 by carrying 20 million passengers. So far it had no serious trouble and has been operated safely. (orig.)

  12. Robustness in Feedback Systems. (United States)


    Horowitz [1%3]). A central focus of robust control theory over the years has been an attempt to generalize these results to multiinput. multioutput ... multioutput systems. These include uniformly (or li.-) optimal control (see Zames [1981]. Zames and Francis [19831. Francis and Zames [1984], and...describes a computable upper bound for multiinput multioutput two-disk problems which requires only the solution of several one-disk prob!ems. To begin

  13. Robust Airline Schedules


    Eggenberg, Niklaus; Salani, Matteo; Bierlaire, Michel


    Due to economic pressure industries, when planning, tend to focus on optimizing the expected profit or the yield. The consequence of highly optimized solutions is an increased sensitivity to uncertainty. This generates additional "operational" costs, incurred by possible modifications of the original plan to be performed when reality does not reflect what was expected in the planning phase. The modern research trend focuses on "robustness" of solutions instead of yield or profit. Although ro...

  14. Robustness for Dummies


    Vincenzo Verardi; Marjorie Gassner; Darwin Ugarte Ontiveros


    In the robust statistics literature, a wide variety of models have been devel- oped to cope with outliers in a rather large number of scenarios. Nevertheless, a recurrent problem for the empirical implementation of these estimators is that optimization algorithms generally do not perform well when dummy vari- ables are present. What we propose in this paper is a simple solution to this involving the replacement of the sub-sampling step of the maximization procedures by a projection-based meth...

  15. Robustness of metabolic networks (United States)

    Jeong, Hawoong


    We investigated the robustness of cellular metabolism by simulating the system-level computational models, and also performed the corresponding experiments to validate our predictions. We address the cellular robustness from the ``metabolite''-framework by using the novel concept of ``flux-sum,'' which is the sum of all incoming or outgoing fluxes (they are the same under the pseudo-steady state assumption). By estimating the changes of the flux-sum under various genetic and environmental perturbations, we were able to clearly decipher the metabolic robustness; the flux-sum around an essential metabolite does not change much under various perturbations. We also identified the list of the metabolites essential to cell survival, and then ``acclimator'' metabolites that can control the cell growth were discovered. Furthermore, this concept of ``metabolite essentiality'' should be useful in developing new metabolic engineering strategies for improved production of various bioproducts and designing new drugs that can fight against multi-antibiotic resistant superbacteria by knocking-down the enzyme activities around an essential metabolite. Finally, we combined a regulatory network with the metabolic network to investigate its effect on dynamic properties of cellular metabolism.

  16. The Crane Robust Control

    Directory of Open Access Journals (Sweden)

    Marek Hicar


    Full Text Available The article is about a control design for complete structure of the crane: crab, bridge and crane uplift.The most important unknown parameters for simulations are burden weight and length of hanging rope. We will use robustcontrol for crab and bridge control to ensure adaptivity for burden weight and rope length. Robust control will be designed for current control of the crab and bridge, necessary is to know the range of unknown parameters. Whole robust will be splitto subintervals and after correct identification of unknown parameters the most suitable robust controllers will be chosen.The most important condition at the crab and bridge motion is avoiding from burden swinging in the final position. Crab and bridge drive is designed by asynchronous motor fed from frequency converter. We will use crane uplift with burden weightobserver in combination for uplift, crab and bridge drive with cooperation of their parameters: burden weight, rope length and crab and bridge position. Controllers are designed by state control method. We will use preferably a disturbance observerwhich will identify burden weight as a disturbance. The system will be working in both modes at empty hook as well asat maximum load: burden uplifting and dropping down.

  17. Helicopter Noise And Noise Abatement Procedures

    Directory of Open Access Journals (Sweden)

    Borivoj Galović


    Full Text Available The helicopter generated noise at and around the airports islower than the noise generated by aeroplanes, since their numberof operations, i. e. the number of takeoffs and landings ismuch lower than the takeoffs and landings of the aeroplanes.Out of some hundred operations a day, helicopters participatewith approximately 15%, but the very impact of noise is by nomeans negligible, since the number of helicopter flights aboveurban areas is constantly increasing.This paper attempts to analyse this phenomenon and thetype of helicopter generated noise, its negative impacts, to explainthe flight procedures and the operative procedures duringtakeoff, landing and overflight of helicopters in operations inthe vicinity and outside airports, as well as the methods of measuringand determining the limit of noise [eve~ and the resultingproblems.

  18. Synchronization of Time-Delay Chaotic System in Presence of Noise

    Directory of Open Access Journals (Sweden)

    Min Lei


    Full Text Available Chaotic synchronization, as a key technique of chaotic secure communication, has received much attention in recent years. This paper proposes a nonlinear synchronization scheme for the time-delay chaotic system in the presence of noise. In this scheme, an integrator is introduced to suppress the influence of channel noise in the synchronization process. The experimental results demonstrate the effectiveness and feasibility of the proposed scheme which is strongly robust against noises, especially the high-frequency noises.

  19. Noise Radar Technology Basics

    National Research Council Canada - National Science Library

    Thayaparan, T; Wernik, C


    .... In this report, the basic theory of noise radar design is treated. The theory supports the use of noise waveforms for radar detection and imaging in such applications as covert military surveillance and reconnaissance...

  20. NASA Jet Noise Research (United States)

    Henderson, Brenda


    The presentation highlights NASA's jet noise research for 2016. Jet-noise modeling efforts, jet-surface interactions results, acoustic characteristics of multi-stream jets, and N+2 Supersonic Aircraft system studies are presented.

  1. Noise-invariant Neurons in the Avian Auditory Cortex: Hearing the Song in Noise (United States)

    Moore, R. Channing; Lee, Tyler; Theunissen, Frédéric E.


    Given the extraordinary ability of humans and animals to recognize communication signals over a background of noise, describing noise invariant neural responses is critical not only to pinpoint the brain regions that are mediating our robust perceptions but also to understand the neural computations that are performing these tasks and the underlying circuitry. Although invariant neural responses, such as rotation-invariant face cells, are well described in the visual system, high-level auditory neurons that can represent the same behaviorally relevant signal in a range of listening conditions have yet to be discovered. Here we found neurons in a secondary area of the avian auditory cortex that exhibit noise-invariant responses in the sense that they responded with similar spike patterns to song stimuli presented in silence and over a background of naturalistic noise. By characterizing the neurons' tuning in terms of their responses to modulations in the temporal and spectral envelope of the sound, we then show that noise invariance is partly achieved by selectively responding to long sounds with sharp spectral structure. Finally, to demonstrate that such computations could explain noise invariance, we designed a biologically inspired noise-filtering algorithm that can be used to separate song or speech from noise. This novel noise-filtering method performs as well as other state-of-the-art de-noising algorithms and could be used in clinical or consumer oriented applications. Our biologically inspired model also shows how high-level noise-invariant responses could be created from neural responses typically found in primary auditory cortex. PMID:23505354

  2. Noise Gating Solar Images (United States)

    DeForest, Craig; Seaton, Daniel B.; Darnell, John A.


    I present and demonstrate a new, general purpose post-processing technique, "3D noise gating", that can reduce image noise by an order of magnitude or more without effective loss of spatial or temporal resolution in typical solar applications.Nearly all scientific images are, ultimately, limited by noise. Noise can be direct Poisson "shot noise" from photon counting effects, or introduced by other means such as detector read noise. Noise is typically represented as a random variable (perhaps with location- or image-dependent characteristics) that is sampled once per pixel or once per resolution element of an image sequence. Noise limits many aspects of image analysis, including photometry, spatiotemporal resolution, feature identification, morphology extraction, and background modeling and separation.Identifying and separating noise from image signal is difficult. The common practice of blurring in space and/or time works because most image "signal" is concentrated in the low Fourier components of an image, while noise is evenly distributed. Blurring in space and/or time attenuates the high spatial and temporal frequencies, reducing noise at the expense of also attenuating image detail. Noise-gating exploits the same property -- "coherence" -- that we use to identify features in images, to separate image features from noise.Processing image sequences through 3-D noise gating results in spectacular (more than 10x) improvements in signal-to-noise ratio, while not blurring bright, resolved features in either space or time. This improves most types of image analysis, including feature identification, time sequence extraction, absolute and relative photometry (including differential emission measure analysis), feature tracking, computer vision, correlation tracking, background modeling, cross-scale analysis, visual display/presentation, and image compression.I will introduce noise gating, describe the method, and show examples from several instruments (including SDO

  3. Noise Reduction Techniques (United States)

    Hallas, Tony

    There are two distinct kinds of noise - structural and color. Each requires a specific method of attack to minimize. The great challenge is to reduce the noise without reducing the faint and delicate detail in the image. My most-used and favorite noise suppression is found in Photoshop CS 5 Camera Raw. If I cannot get the desired results with the first choice, I will use Noise Ninja, which has certain advantages in some situations that we will cover.

  4. Robust decentralized power system controller design: Integrated approach (United States)

    Veselý, Vojtech


    A unique approach to the design of gain scheduled controller (GSC) is presented. The proposed design procedure is based on the Bellman-Lyapunov equation, guaranteed cost and robust stability conditions using the parameter dependent quadratic stability approach. The obtained feasible design procedures for robust GSC design are in the form of BMI with guaranteed convex stability conditions. The obtained design results and their properties are illustrated in the simultaneously design of controllers for simple model (6-order) turbogenerator. The results of the obtained design procedure are a PI automatic voltage regulator (AVR) for synchronous generator, a PI governor controller and a power system stabilizer for excitation system.

  5. Robust face detection based on components and their topology (United States)

    Goldmann, Lutz; Mönich, Ullrich; Sikora, Thomas


    This paper presents a novel approach for automatic and robust object detection. It utilizes a component-based approach that combines techniques from both statistical and structural pattern recognition domain. While the component detection relies on Haar-like features and an AdaBoost trained classifier cascade, the topology verification is based on graph matching techniques. The system was applied to face detection and the experiments show its outstanding performance in comparison to other face detection approaches. Especially in the presence of partial occlusions, uneven illumination and out-of-plane rotations it yields higher robustness.

  6. Enabling Rapid and Robust Structural Analysis During Conceptual Design (United States)

    Eldred, Lloyd B.; Padula, Sharon L.; Li, Wu


    This paper describes a multi-year effort to add a structural analysis subprocess to a supersonic aircraft conceptual design process. The desired capabilities include parametric geometry, automatic finite element mesh generation, static and aeroelastic analysis, and structural sizing. The paper discusses implementation details of the new subprocess, captures lessons learned, and suggests future improvements. The subprocess quickly compares concepts and robustly handles large changes in wing or fuselage geometry. The subprocess can rank concepts with regard to their structural feasibility and can identify promising regions of the design space. The automated structural analysis subprocess is deemed robust and rapid enough to be included in multidisciplinary conceptual design and optimization studies.

  7. Equation for Combustion Noise (United States)

    Liu, T. M.


    Mathematical relationship derived for interactions between turbulent flame and combustion noise. Relationship is rigorous theoretical correlation of combustion noise and combustion process. Establishes foundation for acoustic measurements as tool for investigating structure of turbulent flames. Mathematical relationship is expected to aid researchers in field of noise generated by combustion.

  8. Introductory guide to noise

    CSIR Research Space (South Africa)

    Ferreira, T.M


    Full Text Available The difference between sound and noise varies from one human being to another. Noise, then, is simply unwanted sound and to understand how it can be combatted we must know more about its nature. A guide of acceptable levels of noise are investigated....

  9. Noise at the Interface

    DEFF Research Database (Denmark)

    Prior, Andrew


    The notion of noise occupies a contested territory, in which it is framed as pollution and detritus even as it makes its opposite a possibility - noise is always defined in opposition to something else, even if this ‘other’ is not quite clear. This paper explores noise in the context of ‘the...

  10. Noise equalization for detection of microcalcification clusters in direct digital mammogram images.

    NARCIS (Netherlands)

    McLoughlin, K.J.; Bones, P.J.; Karssemeijer, N.


    Equalizing image noise is shown to be an important step in the automatic detection of microcalcifications in digital mammography. This study extends a well established film-screen noise equalization scheme developed by Veldkamp et al. for application to full-field digital mammogram (FFDM) images. A

  11. Automatic trend estimation

    CERN Document Server

    Vamos¸, C˘alin


    Our book introduces a method to evaluate the accuracy of trend estimation algorithms under conditions similar to those encountered in real time series processing. This method is based on Monte Carlo experiments with artificial time series numerically generated by an original algorithm. The second part of the book contains several automatic algorithms for trend estimation and time series partitioning. The source codes of the computer programs implementing these original automatic algorithms are given in the appendix and will be freely available on the web. The book contains clear statement of the conditions and the approximations under which the algorithms work, as well as the proper interpretation of their results. We illustrate the functioning of the analyzed algorithms by processing time series from astrophysics, finance, biophysics, and paleoclimatology. The numerical experiment method extensively used in our book is already in common use in computational and statistical physics.

  12. Automatic Program Development

    DEFF Research Database (Denmark)

    Automatic Program Development is a tribute to Robert Paige (1947-1999), our accomplished and respected colleague, and moreover our good friend, whose untimely passing was a loss to our academic and research community. We have collected the revised, updated versions of the papers published in his ...... a renewed stimulus for continuing and deepening Bob's research visions. A familiar touch is given to the book by some pictures kindly provided to us by his wife Nieba, the personal recollections of his brother Gary and some of his colleagues and friends....... honor in the Higher-Order and Symbolic Computation Journal in the years 2003 and 2005. Among them there are two papers by Bob: (i) a retrospective view of his research lines, and (ii) a proposal for future studies in the area of the automatic program derivation. The book also includes some papers...

  13. Automaticity or active control

    DEFF Research Database (Denmark)

    Tudoran, Ana Alina; Olsen, Svein Ottar

    This study addresses the quasi-moderating role of habit strength in explaining action loyalty. A model of loyalty behaviour is proposed that extends the traditional satisfaction–intention–action loyalty network. Habit strength is conceptualised as a cognitive construct to refer to the psychological...... aspects of the construct, such as routine, inertia, automaticity, or very little conscious deliberation. The data consist of 2962 consumers participating in a large European survey. The results show that habit strength significantly moderates the association between satisfaction and action loyalty, and......, respectively, between intended loyalty and action loyalty. At high levels of habit strength, consumers are more likely to free up cognitive resources and incline the balance from controlled to routine and automatic-like responses....

  14. Robust drone detection for day/night counter-UAV with static VIS and SWIR cameras (United States)

    Müller, Thomas


    Recent progress in the development of unmanned aerial vehicles (UAVs) has led to more and more situations in which drones like quadrocopters or octocopters pose a potential serious thread or could be used as a powerful tool for illegal activities. Therefore, counter-UAV systems are required in a lot of applications to detect approaching drones as early as possible. In this paper, an efficient and robust algorithm is presented for UAV detection using static VIS and SWIR cameras. Whereas VIS cameras with a high resolution enable to detect UAVs in the daytime in further distances, surveillance at night can be performed with a SWIR camera. First, a background estimation and structural adaptive change detection process detects movements and other changes in the observed scene. Afterwards, the local density of changes is computed used for background density learning and to build up the foreground model which are compared in order to finally get the UAV alarm result. The density model is used to filter out noise effects, on the one hand. On the other hand, moving scene parts like moving leaves in the wind or driving cars on a street can easily be learned in order to mask such areas out and suppress false alarms there. This scene learning is done automatically simply by processing without UAVs in order to capture the normal situation. The given results document the performance of the presented approach in VIS and SWIR in different situations.

  15. Continuous robust sound event classification using time-frequency features and deep learning. (United States)

    McLoughlin, Ian; Zhang, Haomin; Xie, Zhipeng; Song, Yan; Xiao, Wei; Phan, Huy


    The automatic detection and recognition of sound events by computers is a requirement for a number of emerging sensing and human computer interaction technologies. Recent advances in this field have been achieved by machine learning classifiers working in conjunction with time-frequency feature representations. This combination has achieved excellent accuracy for classification of discrete sounds. The ability to recognise sounds under real-world noisy conditions, called robust sound event classification, is an especially challenging task that has attracted recent research attention. Another aspect of real-word conditions is the classification of continuous, occluded or overlapping sounds, rather than classification of short isolated sound recordings. This paper addresses the classification of noise-corrupted, occluded, overlapped, continuous sound recordings. It first proposes a standard evaluation task for such sounds based upon a common existing method for evaluating isolated sound classification. It then benchmarks several high performing isolated sound classifiers to operate with continuous sound data by incorporating an energy-based event detection front end. Results are reported for each tested system using the new task, to provide the first analysis of their performance for continuous sound event detection. In addition it proposes and evaluates a novel Bayesian-inspired front end for the segmentation and detection of continuous sound recordings prior to classification.

  16. An efficient global energy optimization approach for robust 3D plane segmentation of point clouds (United States)

    Dong, Zhen; Yang, Bisheng; Hu, Pingbo; Scherer, Sebastian


    Automatic 3D plane segmentation is necessary for many applications including point cloud registration, building information model (BIM) reconstruction, simultaneous localization and mapping (SLAM), and point cloud compression. However, most of the existing 3D plane segmentation methods still suffer from low precision and recall, and inaccurate and incomplete boundaries, especially for low-quality point clouds collected by RGB-D sensors. To overcome these challenges, this paper formulates the plane segmentation problem as a global energy optimization because it is robust to high levels of noise and clutter. First, the proposed method divides the raw point cloud into multiscale supervoxels, and considers planar supervoxels and individual points corresponding to nonplanar supervoxels as basic units. Then, an efficient hybrid region growing algorithm is utilized to generate initial plane set by incrementally merging adjacent basic units with similar features. Next, the initial plane set is further enriched and refined in a mutually reinforcing manner under the framework of global energy optimization. Finally, the performances of the proposed method are evaluated with respect to six metrics (i.e., plane precision, plane recall, under-segmentation rate, over-segmentation rate, boundary precision, and boundary recall) on two benchmark datasets. Comprehensive experiments demonstrate that the proposed method obtained good performances both in high-quality TLS point clouds (i.e., http://SEMANTIC3D.NET)

  17. Automatic food decisions

    DEFF Research Database (Denmark)

    Mueller Loose, Simone

    Consumers' food decisions are to a large extent shaped by automatic processes, which are either internally directed through learned habits and routines or externally influenced by context factors and visual information triggers. Innovative research methods such as eye tracking, choice experiments...... and food diaries allow us to better understand the impact of unconscious processes on consumers' food choices. Simone Mueller Loose will provide an overview of recent research insights into the effects of habit and context on consumers' food choices....

  18. Automatic Language Identification (United States)


    hundreds guish one language from another. The reader is referred of input languages would need to be supported , the cost of to the linguistics literature...eventually obtained bet- 108 TRAINING FRENCH GERMAN ITRAIING FRENCH M- ALGORITHM - __ GERMAN NHSPANISH TRAINING SPEECH SET OF MODELS: UTTERANCES ONE MODEL...i.e. vowels ) for each speech utterance are located malized to be insensitive to overall amplitude, pitch and automatically. Next, feature vectors

  19. Active noise control in a duct to cancel broadband noise (United States)

    Chen, Kuan-Chun; Chang, Cheng-Yuan; Kuo, Sen M.


    The paper presents cancelling duct noises by using the active noise control (ANC) techniques. We use the single channel feed forward algorithm with feedback neutralization to realize ANC. Several kinds of ducts noises including tonal noises, sweep tonal signals, and white noise had investigated. Experimental results show that the proposed ANC system can cancel these noises in a PVC duct very well. The noise reduction of white noise can be up to 20 dB.

  20. Classical noise, quantum noise and secure communication

    International Nuclear Information System (INIS)

    Tannous, C; Langlois, J


    Secure communication based on message encryption might be performed by combining the message with controlled noise (called pseudo-noise) as performed in spread-spectrum communication used presently in Wi-Fi and smartphone telecommunication systems. Quantum communication based on entanglement is another route for securing communications as demonstrated by several important experiments described in this work. The central role played by the photon in unifying the description of classical and quantum noise as major ingredients of secure communication systems is highlighted and described on the basis of the classical and quantum fluctuation dissipation theorems. (review)

  1. Adaptive robust Kalman filtering for precise point positioning

    International Nuclear Information System (INIS)

    Guo, Fei; Zhang, Xiaohong


    The optimality of precise point postioning (PPP) solution using a Kalman filter is closely connected to the quality of the a priori information about the process noise and the updated mesurement noise, which are sometimes difficult to obtain. Also, the estimation enviroment in the case of dynamic or kinematic applications is not always fixed but is subject to change. To overcome these problems, an adaptive robust Kalman filtering algorithm, the main feature of which introduces an equivalent covariance matrix to resist the unexpected outliers and an adaptive factor to balance the contribution of observational information and predicted information from the system dynamic model, is applied for PPP processing. The basic models of PPP including the observation model, dynamic model and stochastic model are provided first. Then an adaptive robust Kalmam filter is developed for PPP. Compared with the conventional robust estimator, only the observation with largest standardized residual will be operated by the IGG III function in each iteration to avoid reducing the contribution of the normal observations or even filter divergence. Finally, tests carried out in both static and kinematic modes have confirmed that the adaptive robust Kalman filter outperforms the classic Kalman filter by turning either the equivalent variance matrix or the adaptive factor or both of them. This becomes evident when analyzing the positioning errors in flight tests at the turns due to the target maneuvering and unknown process/measurement noises. (paper)

  2. Adaptive robust Kalman filtering for precise point positioning (United States)

    Guo, Fei; Zhang, Xiaohong


    The optimality of precise point postioning (PPP) solution using a Kalman filter is closely connected to the quality of the a priori information about the process noise and the updated mesurement noise, which are sometimes difficult to obtain. Also, the estimation enviroment in the case of dynamic or kinematic applications is not always fixed but is subject to change. To overcome these problems, an adaptive robust Kalman filtering algorithm, the main feature of which introduces an equivalent covariance matrix to resist the unexpected outliers and an adaptive factor to balance the contribution of observational information and predicted information from the system dynamic model, is applied for PPP processing. The basic models of PPP including the observation model, dynamic model and stochastic model are provided first. Then an adaptive robust Kalmam filter is developed for PPP. Compared with the conventional robust estimator, only the observation with largest standardized residual will be operated by the IGG III function in each iteration to avoid reducing the contribution of the normal observations or even filter divergence. Finally, tests carried out in both static and kinematic modes have confirmed that the adaptive robust Kalman filter outperforms the classic Kalman filter by turning either the equivalent variance matrix or the adaptive factor or both of them. This becomes evident when analyzing the positioning errors in flight tests at the turns due to the target maneuvering and unknown process/measurement noises.

  3. Direct-reading dial for noise temperature and noise resistance

    DEFF Research Database (Denmark)

    Diamond, J.M.


    An attenuator arrangement for a noise generator is described. The scheme permits direct reading of both noise resistance and noise temperature¿the latter with a choice of source resistance.......An attenuator arrangement for a noise generator is described. The scheme permits direct reading of both noise resistance and noise temperature¿the latter with a choice of source resistance....

  4. Optical Johnson noise thermometry (United States)

    Shepard, R. L.; Blalock, T. V.; Maxey, L. C.; Roberts, M. J.; Simpson, M. L.


    A concept is being explored that an optical analog of the electrical Johnson noise may be used to measure temperature independently of emissivity. The concept is that a laser beam may be modulated on reflection from a hot surface by interaction of the laser photons with the thermally agitated conduction electrons or the lattice phonons, thereby adding noise to the reflected laser beam. If the reflectance noise can be detected and quantified in a background of other noise in the optical and signal processing systems, the reflectance noise may provide a noncontact measurement of the absolute surface temperature and may be independent of the surface's emissivity.

  5. On the Interplay between Entropy and Robustness of Gene Regulatory Networks

    Directory of Open Access Journals (Sweden)

    Bor-Sen Chen


    Full Text Available The interplay between entropy and robustness of gene network is a core mechanism of systems biology. The entropy is a measure of randomness or disorder of a physical system due to random parameter fluctuation and environmental noises in gene regulatory networks. The robustness of a gene regulatory network, which can be measured as the ability to tolerate the random parameter fluctuation and to attenuate the effect of environmental noise, will be discussed from the robust H∞ stabilization and filtering perspective. In this review, we will also discuss their balancing roles in evolution and potential applications in systems and synthetic biology.

  6. A Robust Zero-Watermarking Algorithm for Audio

    Directory of Open Access Journals (Sweden)

    Jie Zhu


    Full Text Available In traditional watermarking algorithms, the insertion of watermark into the host signal inevitably introduces some perceptible quality degradation. Another problem is the inherent conflict between imperceptibility and robustness. Zero-watermarking technique can solve these problems successfully. Instead of embedding watermark, the zero-watermarking technique extracts some essential characteristics from the host signal and uses them for watermark detection. However, most of the available zero-watermarking schemes are designed for still image and their robustness is not satisfactory. In this paper, an efficient and robust zero-watermarking technique for audio signal is presented. The multiresolution characteristic of discrete wavelet transform (DWT, the energy compression characteristic of discrete cosine transform (DCT, and the Gaussian noise suppression property of higher-order cumulant are combined to extract essential features from the host audio signal and they are then used for watermark recovery. Simulation results demonstrate the effectiveness of our scheme in terms of inaudibility, detection reliability, and robustness.

  7. Correntropy Maximization via ADMM: Application to Robust Hyperspectral Unmixing (United States)

    Zhu, Fei; Halimi, Abderrahim; Honeine, Paul; Chen, Badong; Zheng, Nanning


    In hyperspectral images, some spectral bands suffer from low signal-to-noise ratio due to noisy acquisition and atmospheric effects, thus requiring robust techniques for the unmixing problem. This paper presents a robust supervised spectral unmixing approach for hyperspectral images. The robustness is achieved by writing the unmixing problem as the maximization of the correntropy criterion subject to the most commonly used constraints. Two unmixing problems are derived: the first problem considers the fully-constrained unmixing, with both the non-negativity and sum-to-one constraints, while the second one deals with the non-negativity and the sparsity-promoting of the abundances. The corresponding optimization problems are solved efficiently using an alternating direction method of multipliers (ADMM) approach. Experiments on synthetic and real hyperspectral images validate the performance of the proposed algorithms for different scenarios, demonstrating that the correntropy-based unmixing is robust to outlier bands.

  8. Background noise exerts diverse effects on the cortical encoding of foreground sounds. (United States)

    Malone, B J; Heiser, Marc A; Beitel, Ralph E; Schreiner, Christoph E


    In natural listening conditions, many sounds must be detected and identified in the context of competing sound sources, which function as background noise. Traditionally, noise is thought to degrade the cortical representation of sounds by suppressing responses and increasing response variability. However, recent studies of neural network models and brain slices have shown that background synaptic noise can improve the detection of signals. Because acoustic noise affects the synaptic background activity of cortical networks, it may improve the cortical responses to signals. We used spike train decoding techniques to determine the functional effects of a continuous white noise background on the responses of clusters of neurons in auditory cortex to foreground signals, specifically frequency-modulated sweeps (FMs) of different velocities, directions, and amplitudes. Whereas the addition of noise progressively suppressed the FM responses of some cortical sites in the core fields with decreasing signal-to-noise ratios (SNRs), the stimulus representation remained robust or was even significantly enhanced at specific SNRs in many others. Even though the background noise level was typically not explicitly encoded in cortical responses, significant information about noise context could be decoded from cortical responses on the basis of how the neural representation of the foreground sweeps was affected. These findings demonstrate significant diversity in signal in noise processing even within the core auditory fields that could support noise-robust hearing across a wide range of listening conditions. NEW & NOTEWORTHY The ability to detect and discriminate sounds in background noise is critical for our ability to communicate. The neural basis of robust perceptual performance in noise is not well understood. We identified neuronal populations in core auditory cortex of squirrel monkeys that differ in how they process foreground signals in background noise and that may

  9. Robust efficient video fingerprinting (United States)

    Puri, Manika; Lubin, Jeffrey


    We have developed a video fingerprinting system with robustness and efficiency as the primary and secondary design criteria. In extensive testing, the system has shown robustness to cropping, letter-boxing, sub-titling, blur, drastic compression, frame rate changes, size changes and color changes, as well as to the geometric distortions often associated with camcorder capture in cinema settings. Efficiency is afforded by a novel two-stage detection process in which a fast matching process first computes a number of likely candidates, which are then passed to a second slower process that computes the overall best match with minimal false alarm probability. One key component of the algorithm is a maximally stable volume computation - a three-dimensional generalization of maximally stable extremal regions - that provides a content-centric coordinate system for subsequent hash function computation, independent of any affine transformation or extensive cropping. Other key features include an efficient bin-based polling strategy for initial candidate selection, and a final SIFT feature-based computation for final verification. We describe the algorithm and its performance, and then discuss additional modifications that can provide further improvement to efficiency and accuracy.

  10. Robust Cultural Pluralism

    Directory of Open Access Journals (Sweden)

    Richard A. Shweder


    Full Text Available In this wide ranging interview, Professor Richard A. Shweder from the Department of Comparative Human Development at the University of Chicago, discusses whether it is or is not possible to be a robust cultural pluralist and a dedicated political liberal at the same time. In this discussion, Professor Shweder offers his insights - based on over 40 years of research - on issues related to the history and re-emergence of cultural psychology; moral anthropology and psychology; the experimental method in psychological investigation and its philosophical basis; contemporary and historical cultural collisions – most notably conflicting representations of female genital surgeries; cultural diversity and inequality; and the dissemination of ideas through open access publishing and Twitter. Professor Shweder ends by offering valuable advice to young researchers in the field of cultural psychology as well as a glimpse into the larger themes of his forthcoming book, which seeks to provide answers to the question of what forms of political liberalism are most compatible with robust cultural pluralism and which are not.

  11. Noise suppression in duct

    International Nuclear Information System (INIS)

    Ahmed, A.; Barfeh, M.A.G.


    In air-conditioning system the noise generated by supply fan is carried by conditioned air through the ductwork. The noise created in ductwork run may be transmission, regenerative and ductborne. Transmission noise is fan noise, regenerative noise is due to turbulence in flow and ductborne noise is the noise radiating from duct to surroundings. Some noise is attenuated in ducts also but if noise level is high then it needs to be attenuated. A simple mitre bend can attenuate-noise. This principle is extended to V and M-shape ducts with inside lining of fibreglass, which gave maximum attenuation of 77 dB and 62 dB respectively corresponding to 8 kHz frequency as compared to mitre, bend giving maximum 18 dB attenuation. Sound level meter measured sound levels with octave band filter and tests were conducted in anechoic room. A V-shape attenuator can be used at fan outlet and high frequency noise can be minimized greatly. (author)

  12. Active3 noise reduction

    International Nuclear Information System (INIS)

    Holzfuss, J.


    Noise reduction is a problem being encountered in a variety of applications, such as environmental noise cancellation, signal recovery and separation. Passive noise reduction is done with the help of absorbers. Active noise reduction includes the transmission of phase inverted signals for the cancellation. This paper is about a threefold active approach to noise reduction. It includes the separation of a combined source, which consists of both a noise and a signal part. With the help of interaction with the source by scanning it and recording its response, modeling as a nonlinear dynamical system is achieved. The analysis includes phase space analysis and global radial basis functions as tools for the prediction used in a subsequent cancellation procedure. Examples are given which include noise reduction of speech. copyright 1996 American Institute of Physics

  13. Highly noise resistant multiqubit quantum correlations (United States)

    Laskowski, Wiesław; Vértesi, Tamás; Wieśniak, Marcin


    We analyze robustness of correlations of the N-qubit GHZ and Dicke states against white noise admixture. For sufficiently large N, the Dicke states (for any number of excitations) lead to more robust violation of local realism than the GHZ states (e.g. for N > 8 for the W state). We also identify states that are the most resistant to white noise. Surprisingly, it turns out that these states are the GHZ states augmented with fully product states. Based on our numerical analysis conducted up to N = 8, and an analytical formula derived for any N parties, we conjecture that the three-qubit GHZ state augmented with a product of (N - 3) pure qubits is the most robust against white noise admixture among any N-qubit state. As a by-product, we derive a single Bell inequality and show that it is violated by all pure entangled states of a given number of parties. This gives an alternative proof of Gisin’s theorem.

  14. Robust estimation of seismic coda shape (United States)

    Nikkilä, Mikko; Polishchuk, Valentin; Krasnoshchekov, Dmitry


    We present a new method for estimation of seismic coda shape. It falls into the same class of methods as non-parametric shape reconstruction with the use of neural network techniques where data are split into a training and validation data sets. We particularly pursue the well-known problem of image reconstruction formulated in this case as shape isolation in the presence of a broadly defined noise. This combined approach is enabled by the intrinsic feature of seismogram which can be divided objectively into a pre-signal seismic noise with lack of the target shape, and the remainder that contains scattered waveforms compounding the coda shape. In short, we separately apply shape restoration procedure to pre-signal seismic noise and the event record, which provides successful delineation of the coda shape in the form of a smooth almost non-oscillating function of time. The new algorithm uses a recently developed generalization of classical computational-geometry tool of α-shape. The generalization essentially yields robust shape estimation by ignoring locally a number of points treated as extreme values, noise or non-relevant data. Our algorithm is conceptually simple and enables the desired or pre-determined level of shape detail, constrainable by an arbitrary data fit criteria. The proposed tool for coda shape delineation provides an alternative to moving averaging and/or other smoothing techniques frequently used for this purpose. The new algorithm is illustrated with an application to the problem of estimating the coda duration after a local event. The obtained relation coefficient between coda duration and epicentral distance is consistent with the earlier findings in the region of interest.

  15. Robust online Hamiltonian learning

    International Nuclear Information System (INIS)

    Granade, Christopher E; Ferrie, Christopher; Wiebe, Nathan; Cory, D G


    In this work we combine two distinct machine learning methodologies, sequential Monte Carlo and Bayesian experimental design, and apply them to the problem of inferring the dynamical parameters of a quantum system. We design the algorithm with practicality in mind by including parameters that control trade-offs between the requirements on computational and experimental resources. The algorithm can be implemented online (during experimental data collection), avoiding the need for storage and post-processing. Most importantly, our algorithm is capable of learning Hamiltonian parameters even when the parameters change from experiment-to-experiment, and also when additional noise processes are present and unknown. The algorithm also numerically estimates the Cramer–Rao lower bound, certifying its own performance. (paper)

  16. Robustness Metrics: Consolidating the multiple approaches to quantify Robustness

    DEFF Research Database (Denmark)

    Göhler, Simon Moritz; Eifler, Tobias; Howard, Thomas J.


    determined to be conceptually different from one another. The metrics were classified by their meaning and interpretation based on the types of information necessary to calculate the metrics. Four different classes were identified: 1) Sensitivity robustness metrics; 2) Size of feasible design space......, this ambiguity can have significant influence on the strategies used to combat variability, the way it is quantified and ultimately, the quality of the final design. In this contribution the literature for robustness metrics was systematically reviewed. From the 108 relevant publications found, 38 metrics were...... robustness metrics; 3) Functional expectancy and dispersion robustness metrics; and 4) Probability of conformance robustness metrics. The goal was to give a comprehensive overview of robustness metrics and guidance to scholars and practitioners to understand the different types of robustness metrics...

  17. Seismic noise attenuation using an online subspace tracking algorithm (United States)

    Zhou, Yatong; Li, Shuhua; Zhang, Dong; Chen, Yangkang


    We propose a new low-rank based noise attenuation method using an efficient algorithm for tracking subspaces from highly corrupted seismic observations. The subspace tracking algorithm requires only basic linear algebraic manipulations. The algorithm is derived by analysing incremental gradient descent on the Grassmannian manifold of subspaces. When the multidimensional seismic data are mapped to a low-rank space, the subspace tracking algorithm can be directly applied to the input low-rank matrix to estimate the useful signals. Since the subspace tracking algorithm is an online algorithm, it is more robust to random noise than traditional truncated singular value decomposition (TSVD) based subspace tracking algorithm. Compared with the state-of-the-art algorithms, the proposed denoising method can obtain better performance. More specifically, the proposed method outperforms the TSVD-based singular spectrum analysis method in causing less residual noise and also in saving half of the computational cost. Several synthetic and field data examples with different levels of complexities demonstrate the effectiveness and robustness of the presented algorithm in rejecting different types of noise including random noise, spiky noise, blending noise, and coherent noise.

  18. Automatic delamination defect detection in radiographic sequence of rocket boosters

    International Nuclear Information System (INIS)

    Rebuffel, V.; Pires, S.; Caplier, A.; Lamarque, P.


    Solid rocket motors are routinely examined in real-time X-ray radioscopic mode. The large and cylindrical boosters are rotating between a high energy source and a two dimensional detector. The purpose of this control is to detect possible defects all through the sample. In the tangential configuration, the part of the object that intersects the X-rays beam is the peripheral one, allowing to detect the delamination defect between the propellant and the external metal envelope. But the defect detectability is very poor due to the strong attenuation of the X-rays through the motors. During the rotation of the booster, the system acquires a sequence of radiographs where the defects are visible over several successive instants. We have previously developed a real-time tomo-synthesis system, processing the radiographs on line, and based on a tomo-synthesis reconstruction algorithm in order to improve the signal-to-noise ratio. This system is installed at the industrial site of Kourou, and is currently used by the operators in charge of the visual inspection of the boosters. In this paper, we present a method that processes the digital images obtained by the system in the purpose of automatically extracting the delamination defects. Due to the size and the poor contrast of the defects, a single image is not sufficient to perform this detection. A spatio-temporal aspect is required for the algorithm to be robust and efficient. In a first step, the proposed method computes the apparent local displacement between the current radiograph and a reference one. This reference image is acquired at the beginning of the rotation, with few noise, and is supposed to be defect free. The apparent displacement is due to the non-perfect rotation positioning. It may be uniform or not, depending on the deformation of the insulation liner of the metallic wall. The images are then registered and compared. On the resulting difference image we apply a smoothed threshold to obtain an

  19. Automatic cell object extraction of red tide algae in microscopic images (United States)

    Yu, Kun; Ji, Guangrong; Zheng, Haiyong


    Extracting the cell objects of red tide algae is the most important step in the construction of an automatic microscopic image recognition system for harmful algal blooms. This paper describes a set of composite methods for the automatic segmentation of cells of red tide algae from microscopic images. Depending on the existence of setae, we classify the common marine red tide algae into non-setae algae species and Chaetoceros, and design segmentation strategies for these two categories according to their morphological characteristics. In view of the varied forms and fuzzy edges of non-setae algae, we propose a new multi-scale detection algorithm for algal cell regions based on border- correlation, and further combine this with morphological operations and an improved GrabCut algorithm to segment single-cell and multicell objects. In this process, similarity detection is introduced to eliminate the pseudo cellular regions. For Chaetoceros, owing to the weak grayscale information of their setae and the low contrast between the setae and background, we propose a cell extraction method based on a gray surface orientation angle model. This method constructs a gray surface vector model, and executes the gray mapping of the orientation angles. The obtained gray values are then reconstructed and linearly stretched. Finally, appropriate morphological processing is conducted to preserve the orientation information and tiny features of the setae. Experimental results demonstrate that the proposed methods can effectively remove noise and accurately extract both categories of algae cell objects possessing a complete shape, regular contour, and clear edge. Compared with other advanced segmentation techniques, our methods are more robust when considering images with different appearances and achieve more satisfactory segmentation effects.

  20. Gap-free segmentation of vascular networks with automatic image processing pipeline. (United States)

    Hsu, Chih-Yang; Ghaffari, Mahsa; Alaraj, Ali; Flannery, Michael; Zhou, Xiaohong Joe; Linninger, Andreas


    Current image processing techniques capture large vessels reliably but often fail to preserve connectivity in bifurcations and small vessels. Imaging artifacts and noise can create gaps and discontinuity of intensity that hinders segmentation of vascular trees. However, topological analysis of vascular trees require proper connectivity without gaps, loops or dangling segments. Proper tree connectivity is also important for high quality rendering of surface meshes for scientific visualization or 3D printing. We present a fully automated vessel enhancement pipeline with automated parameter settings for vessel enhancement of tree-like structures from customary imaging sources, including 3D rotational angiography, magnetic resonance angiography, magnetic resonance venography, and computed tomography angiography. The output of the filter pipeline is a vessel-enhanced image which is ideal for generating anatomical consistent network representations of the cerebral angioarchitecture for further topological or statistical analysis. The filter pipeline combined with computational modeling can potentially improve computer-aided diagnosis of cerebrovascular diseases by delivering biometrics and anatomy of the vasculature. It may serve as the first step in fully automatic epidemiological analysis of large clinical datasets. The automatic analysis would enable rigorous statistical comparison of biometrics in subject-specific vascular trees. The robust and accurate image segmentation using a validated filter pipeline would also eliminate operator dependency that has been observed in manual segmentation. Moreover, manual segmentation is time prohibitive given that vascular trees have more than thousands of segments and bifurcations so that interactive segmentation consumes excessive human resources. Subject-specific trees are a first step toward patient-specific hemodynamic simulations for assessing treatment outcomes. Copyright © 2017 Elsevier Ltd. All rights reserved.

  1. Scale invariant SURF detector and automatic clustering segmentation for infrared small targets detection (United States)

    Zhang, Haiying; Bai, Jiaojiao; Li, Zhengjie; Liu, Yan; Liu, Kunhong


    The detection and discrimination of infrared small dim targets is a challenge in automatic target recognition (ATR), because there is no salient information of size, shape and texture. Many researchers focus on mining more discriminative information of targets in temporal-spatial. However, such information may not be available with the change of imaging environments, and the targets size and intensity keep changing in different imaging distance. So in this paper, we propose a novel research scheme using density-based clustering and backtracking strategy. In this scheme, the speeded up robust feature (SURF) detector is applied to capture candidate targets in single frame at first. And then, these points are mapped into one frame, so that target traces form a local aggregation pattern. In order to isolate the targets from noises, a newly proposed density-based clustering algorithm, fast search and find of density peak (FSFDP for short), is employed to cluster targets by the spatial intensive distribution. Two important factors of the algorithm, percent and γ , are exploited fully to determine the clustering scale automatically, so as to extract the trace with highest clutter suppression ratio. And at the final step, a backtracking algorithm is designed to detect and discriminate target trace as well as to eliminate clutter. The consistence and continuity of the short-time target trajectory in temporal-spatial is incorporated into the bounding function to speed up the pruning. Compared with several state-of-arts methods, our algorithm is more effective for the dim targets with lower signal-to clutter ratio (SCR). Furthermore, it avoids constructing the candidate target trajectory searching space, so its time complexity is limited to a polynomial level. The extensive experimental results show that it has superior performance in probability of detection (Pd) and false alarm suppressing rate aiming at variety of complex backgrounds.

  2. Fully automatic segmentation of arbitrarily shaped fiducial markers in cone-beam CT projections. (United States)

    Bertholet, J; Wan, H; Toftegaard, J; Schmidt, M L; Chotard, F; Parikh, P J; Poulsen, P R


    Radio-opaque fiducial markers of different shapes are often implanted in or near abdominal or thoracic tumors to act as surrogates for the tumor position during radiotherapy. They can be used for real-time treatment adaptation, but this requires a robust, automatic segmentation method able to handle arbitrarily shaped markers in a rotational imaging geometry such as cone-beam computed tomography (CBCT) projection images and intra-treatment images. In this study, we propose a fully automatic dynamic programming (DP) assisted template-based (TB) segmentation method. Based on an initial DP segmentation, the DPTB algorithm generates and uses a 3D marker model to create 2D templates at any projection angle. The 2D templates are used to segment the marker position as the position with highest normalized cross-correlation in a search area centered at the DP segmented position. The accuracy of the DP algorithm and the new DPTB algorithm was quantified as the 2D segmentation error (pixels) compared to a manual ground truth segmentation for 97 markers in the projection images of CBCT scans of 40 patients. Also the fraction of wrong segmentations, defined as 2D errors larger than 5 pixels, was calculated. The mean 2D segmentation error of DP was reduced from 4.1 pixels to 3.0 pixels by DPTB, while the fraction of wrong segmentations was reduced from 17.4% to 6.8%. DPTB allowed rejection of uncertain segmentations as deemed by a low normalized cross-correlation coefficient and contrast-to-noise ratio. For a rejection rate of 9.97%, the sensitivity in detecting wrong segmentations was 67% and the specificity was 94%. The accepted segmentations had a mean segmentation error of 1.8 pixels and 2.5% wrong segmentations.

  3. Automatic first-arrival picking based on extended super-virtual interferometry with quality control procedure (United States)

    An, Shengpei; Hu, Tianyue; Liu, Yimou; Peng, Gengxin; Liang, Xianghao


    Static correction is a crucial step of seismic data processing for onshore play, which frequently has a complex near-surface condition. The effectiveness of the static correction depends on an accurate determination of first-arrival traveltimes. However, it is difficult to accurately auto-pick the first arrivals for data with low signal-to-noise ratios (SNR), especially for those measured in the area of the complex near-surface. The technique of the super-virtual interferometry (SVI) has the potential to enhance the SNR of first arrivals. In this paper, we develop the extended SVI with (1) the application of the reverse correlation to improve the capability of SNR enhancement at near-offset, and (2) the usage of the multi-domain method to partially overcome the limitation of current method, given insufficient available source-receiver combinations. Compared to the standard SVI, the SNR enhancement of the extended SVI can be up to 40%. In addition, we propose a quality control procedure, which is based on the statistical characteristics of multichannel recordings of first arrivals. It can auto-correct the mispicks, which might be spurious events generated by the SVI. This procedure is very robust, highly automatic and it can accommodate large data in batches. Finally, we develop one automatic first-arrival picking method to combine the extended SVI and the quality control procedure. Both the synthetic and the field data examples demonstrate that the proposed method is able to accurately auto-pick first arrivals in seismic traces with low SNR. The quality of the stacked seismic sections obtained from this method is much better than those obtained from an auto-picking method, which is commonly employed by the commercial software.

  4. Active control of environmental noise, VIII: increasing the response to primary source changes including unpredictable noise (United States)

    Wright, S. E.; Atmoko, H.; Vuksanovic, B.


    Conventional adaptive cancellation systems using traditional transverse finite impulse response (FIR) filters, together with least mean square (LMS) adaptive algorithms, well known in active noise control, are slow to adapt to primary source changes. This makes them inappropriate for cancelling rapidly changing noise, including unpredictable noise such as speech and music. Secondly, the cancelling structures require considerable computational processing effort to adapt to primary source and plant changes, particularly for multi-channel systems. This paper describes methods to increase the adaptive speed to primary source changes in large enclosed spaces and outdoor environments. A method is described that increases the response to time varying periodic noise using traditional transverse FIR filters. Here a multi-passband filter, with individual variable adaptive step sizes for each passband is automatically adjusted according to the signal level in each band. This creates a similar adaptive response for all frequencies within the total pass-band, irrespective of amplitude, minimizing the signal distortion and increasing the combined adaptive speed. Unfortunately, there is a limit to the adaptive speed using the above method as classical transverse FIR filters have a finite adaptive speed given by the stability band zero bandwidth. For rapidly changing periodic noise and unpredictable non-stationary noise, a rapid to instantaneous response is required. In this case the on-line adaptive FIR filters are dispensed with and replaced by a time domain solution that gives virtually instantaneous cancellation response (infinite adaptive speed) to primary source changes, and is computationally efficient.

  5. Genetic noise control via protein oligomerization

    Energy Technology Data Exchange (ETDEWEB)

    Ghim, C; Almaas, E


    Gene expression in a cell entails random reaction events occurring over disparate time scales. Thus, molecular noise that often results in phenotypic and population-dynamic consequences sets a fundamental limit to biochemical signaling. While there have been numerous studies correlating the architecture of cellular reaction networks with noise tolerance, only a limited effort has been made to understand the dynamical role of protein-protein associations. We have developed a fully stochastic model for the positive feedback control of a single gene, as well as a pair of genes (toggle switch), integrating quantitative results from previous in vivo and in vitro studies. In particular, we explicitly account for the fast protein binding-unbinding kinetics, RNA polymerases, and the promoter/operator sequences of DNA. We find that the overall noise-level is reduced and the frequency content of the noise is dramatically shifted to the physiologically irrelevant high-frequency regime in the presence of protein dimerization. This is independent of the choice of monomer or dimer as transcription factor and persists throughout the multiple model topologies considered. For the toggle switch, we additionally find that the presence of a protein dimer, either homodimer or heterodimer, may significantly reduce its intrinsic switching rate. Hence, the dimer promotes the robust function of bistable switches by preventing the uninduced (induced) state from randomly being induced (uninduced). The specific binding between regulatory proteins provides a buffer that may prevent the propagation of fluctuations in genetic activity. The capacity of the buffer is a non-monotonic function of association-dissociation rates. Since the protein oligomerization per se does not require extra protein components to be expressed, it provides a basis for the rapid control of intrinsic or extrinsic noise. The stabilization of phenotypically important toggle switches, and nested positive feedback loops in

  6. Practical signal-dependent noise parameter estimation from a single noisy image. (United States)

    Liu, Xinhao; Tanaka, Masayuki; Okutomi, Masatoshi


    The additive white Gaussian noise is widely assumed in many image processing algorithms. However, in the real world, the noise from actual cameras is better modeled as signal-dependent noise (SDN). In this paper, we focus on the SDN model and propose an algorithm to automatically estimate its parameters from a single noisy image. The proposed algorithm identifies the noise level function of signal-dependent noise assuming the generalized signal-dependent noise model and is also applicable to the Poisson-Gaussian noise model. The accuracy is achieved by improved estimation of local mean and local noise variance from the selected low-rank patches. We evaluate the proposed algorithm with both synthetic and real noisy images. Experiments demonstrate that the proposed estimation algorithm outperforms the state-of-the-art methods.

  7. Global Distribution Adjustment and Nonlinear Feature Transformation for Automatic Colorization

    Directory of Open Access Journals (Sweden)

    Terumasa Aoki


    Full Text Available Automatic colorization is generally classified into two groups: propagation-based methods and reference-based methods. In reference-based automatic colorization methods, color image(s are used as reference(s to reconstruct original color of a gray target image. The most important task here is to find the best matching pairs for all pixels between reference and target images in order to transfer color information from reference to target pixels. A lot of attractive local feature-based image matching methods have already been developed for the last two decades. Unfortunately, as far as we know, there are no optimal matching methods for automatic colorization because the requirements for pixel matching in automatic colorization are wholly different from those for traditional image matching. To design an efficient matching algorithm for automatic colorization, clustering pixel with low computational cost and generating descriptive feature vector are the most important challenges to be solved. In this paper, we present a novel method to address these two problems. In particular, our work concentrates on solving the second problem (designing a descriptive feature vector; namely, we will discuss how to learn a descriptive texture feature using scaled sparse texture feature combining with a nonlinear transformation to construct an optimal feature descriptor. Our experimental results show our proposed method outperforms the state-of-the-art methods in terms of robustness for color reconstruction for automatic colorization applications.

  8. Ambient Noise in an Urbanized Tidal Channel (United States)

    Bassett, Christopher

    In coastal environments, when topographic and bathymetric constrictions are combined with large tidal amplitudes, strong currents (> 2 m/s) can occur. Because such environments are relatively rare and difficult to study, until recently, they have received little attention from the scientific community. However, in recent years, interest in developing tidal hydrokinetic power projects in these environments has motivated studies to improve this understanding. In order to support an analysis of the acoustic effects of tidal power generation, a multi-year study was conducted at a proposed project site in Puget Sound (WA) are analyzed at a site where peak currents exceeded 3.5 m/s. From these analyses, three noise sources are shown to dominate the observed variability in ambient noise between 0.02-30 kHz: anthropogenic noise from vessel traffic, sediment-generated noise during periods of strong currents, and flow-noise resulting from turbulence advected over the hydrophones. To assess the contribution of vessel traffic noise, one calendar year of Automatic Identification System (AIS) ship-traffic data was paired with hydrophone recordings. The study region included inland waters of the Salish Sea within a 20 km radius of the hydrophone deployment site in northern Admiralty Inlet. The variability in spectra and hourly, daily, and monthly ambient noise statistics for unweighted broadband and M-weighted sound pressure levels is driven largely by vessel traffic. Within the one-year study period, at least one AIS transmitting vessel is present in the study area 90% of the time and over 1,363 unique vessels are recorded. A noise budget for vessels equipped with AIS transponders identifies cargo ships, tugs, and passenger vessels as the largest contributors to noise levels. A simple model to predict received levels at the site based on an incoherent summation of noise from different vessel types yields a cumulative probability density function of broadband sound pressure

  9. International Conference on Robust Statistics

    CERN Document Server

    Filzmoser, Peter; Gather, Ursula; Rousseeuw, Peter


    Aspects of Robust Statistics are important in many areas. Based on the International Conference on Robust Statistics 2001 (ICORS 2001) in Vorau, Austria, this volume discusses future directions of the discipline, bringing together leading scientists, experienced researchers and practitioners, as well as younger researchers. The papers cover a multitude of different aspects of Robust Statistics. For instance, the fundamental problem of data summary (weights of evidence) is considered and its robustness properties are studied. Further theoretical subjects include e.g.: robust methods for skewness, time series, longitudinal data, multivariate methods, and tests. Some papers deal with computational aspects and algorithms. Finally, the aspects of application and programming tools complete the volume.

  10. Robust procedures in chemometrics

    DEFF Research Database (Denmark)

    Kotwa, Ewelina

    -way chemometrical methods, such as PCA and PARAFAC models for analysing spatial and depth profiles of sea water samples, defined by three data modes: depth, variables and geographical location. Emphasis was also put on predicting fluorescence values, as being a natural measure of biological activity, by applying...... if contamination in the data is present. For this becoming a standard procedure, further work is required, aiming at implementing reliable robust algorithms into standard statistical programs.......The general aim of the thesis was to contribute to the improvement of data analytical techniques within the chemometric field. Regardless the multivariate structure of the data, it is still common in some fields to perform uni-variate data analysis using only simple statistics such as sample mean...

  11. Robust automated knowledge capture.

    Energy Technology Data Exchange (ETDEWEB)

    Stevens-Adams, Susan Marie; Abbott, Robert G.; Forsythe, James Chris; Trumbo, Michael Christopher Stefan; Haass, Michael Joseph; Hendrickson, Stacey M. Langfitt


    This report summarizes research conducted through the Sandia National Laboratories Robust Automated Knowledge Capture Laboratory Directed Research and Development project. The objective of this project was to advance scientific understanding of the influence of individual cognitive attributes on decision making. The project has developed a quantitative model known as RumRunner that has proven effective in predicting the propensity of an individual to shift strategies on the basis of task and experience related parameters. Three separate studies are described which have validated the basic RumRunner model. This work provides a basis for better understanding human decision making in high consequent national security applications, and in particular, the individual characteristics that underlie adaptive thinking.

  12. Robust Optical Flow Estimation

    Directory of Open Access Journals (Sweden)

    Javier Sánchez Pérez


    Full Text Available n this work, we describe an implementation of the variational method proposed by Brox etal. in 2004, which yields accurate optical flows with low running times. It has several benefitswith respect to the method of Horn and Schunck: it is more robust to the presence of outliers,produces piecewise-smooth flow fields and can cope with constant brightness changes. Thismethod relies on the brightness and gradient constancy assumptions, using the information ofthe image intensities and the image gradients to find correspondences. It also generalizes theuse of continuous L1 functionals, which help mitigate the effect of outliers and create a TotalVariation (TV regularization. Additionally, it introduces a simple temporal regularizationscheme that enforces a continuous temporal coherence of the flow fields.

  13. Robust snapshot interferometric spectropolarimetry. (United States)

    Kim, Daesuk; Seo, Yoonho; Yoon, Yonghee; Dembele, Vamara; Yoon, Jae Woong; Lee, Kyu Jin; Magnusson, Robert


    This Letter describes a Stokes vector measurement method based on a snapshot interferometric common-path spectropolarimeter. The proposed scheme, which employs an interferometric polarization-modulation module, can extract the spectral polarimetric parameters Ψ(k) and Δ(k) of a transmissive anisotropic object by which an accurate Stokes vector can be calculated in the spectral domain. It is inherently strongly robust to the object 3D pose variation, since it is designed distinctly so that the measured object can be placed outside of the interferometric module. Experiments are conducted to verify the feasibility of the proposed system. The proposed snapshot scheme enables us to extract the spectral Stokes vector of a transmissive anisotropic object within tens of msec with high accuracy.

  14. Automatic Soccer Video Analysis and Summarization (United States)

    Ekin, Ahmet; Tekalp, A. Murat


    We propose a fully automatic and computationally efficient framework for analysis and summarization of soccer videos using cinematic and object-based features. The proposed framework includes some novel low-level soccer video processing algorithms, such as dominant color region detection, robust shot boundary detection, and shot classification, as well as some higher-level algorithms for goal detection, referee detection, and penalty-box detection. The system can output three types of summaries: i) all slow-motion segments in a game, ii) all goals in a game, and iii) slow-motion segments classified according to object-based features. The first two types of summaries are based on cinematic features only for speedy processing, while the summaries of the last type contain higher-level semantics. The proposed framework is efficient, effective, and robust for soccer video processing. It is efficient in the sense that there is no need to compute object-based features when cinematic features are sufficient for the detection of certain events, e.g. goals in soccer. It is effective in the sense that the framework can also employ object-based features when needed to increase accuracy (at the expense of more computation). The efficiency, effectiveness, and the robustness of the proposed framework are demonstrated over a large data set, consisting of more than 13 hours of soccer video, captured at different countries and conditions.

  15. A new approach to control noise from entertainment facilities: Active control and measurement of amplified community noise (United States)

    Peppin, Richard J.; Casamajó, Joan


    While traffic noise is perhaps the most pervasive of community noises, much of the contribution now comes from amplified sound: live music, discos, theme parks, and exercise studios. Those producing the sound or music want it loud and those not interested want to be protected against noise. Noise limits at the receiving or producing property line must be met for the minimum community acceptance. However the time-, and perhaps the spatially-, varying sound in entertainment facilities is often constantly modified (and maybe monitored) near the source of the sound. Hence it is hard to relate and to control the sound at the property line. This paper presents a unique noise control device. It is based on the octave band ``transfer function'' between the sound produced in the entertainment area and the noise received at the property line. The overall insulation can be measured and is input to the instrument. When a noise level limit is exceeded at the receiver, due to the amplified interior noise at the facility, the sound output of the device is automatically controlled to reduce the noise. The paper provides details of the design and possible abatement scenarios with examples.

  16. Description of Anomalous Noise Events for Reliable Dynamic Traffic Noise Mapping in Real-Life Urban and Suburban Soundscapes

    Directory of Open Access Journals (Sweden)

    Francesc Alías


    Full Text Available Traffic noise is one of the main pollutants in urban and suburban areas. European authorities have driven several initiatives to study, prevent and reduce the effects of exposure of population to traffic. Recent technological advances have allowed the dynamic computation of noise levels by means of Wireless Acoustic Sensor Networks (WASN such as that developed within the European LIFE DYNAMAP project. Those WASN should be capable of detecting and discarding non-desired sound sources from road traffic noise, denoted as anomalous noise events (ANE, in order to generate reliable noise level maps. Due to the local, occasional and diverse nature of ANE, some works have opted to artificially build ANE databases at the cost of misrepresentation. This work presents the production and analysis of a real-life environmental audio database in two urban and suburban areas specifically conceived for anomalous noise events’ collection. A total of 9 h 8 min of labelled audio data is obtained differentiating among road traffic noise, background city noise and ANE. After delimiting their boundaries manually, the acoustic salience of the ANE samples is automatically computed as a contextual signal-to-noise ratio (SNR. The analysis of the real-life environmental database shows high diversity of ANEs in terms of occurrences, durations and SNRs, as well as confirming both the expected differences between the urban and suburban soundscapes in terms of occurrences and SNRs, and the rare nature of ANE.

  17. Robust Hammerstein Adaptive Filtering under Maximum Correntropy Criterion

    Directory of Open Access Journals (Sweden)

    Zongze Wu


    Full Text Available The maximum correntropy criterion (MCC has recently been successfully applied to adaptive filtering. Adaptive algorithms under MCC show strong robustness against large outliers. In this work, we apply the MCC criterion to develop a robust Hammerstein adaptive filter. Compared with the traditional Hammerstein adaptive filters, which are usually derived based on the well-known mean square error (MSE criterion, the proposed algorithm can achieve better convergence performance especially in the presence of impulsive non-Gaussian (e.g., α-stable noises. Additionally, some theoretical results concerning the convergence behavior are also obtained. Simulation examples are presented to confirm the superior performance of the new algorithm.

  18. Automatic Evaluation Of Interferograms (United States)

    Becker, Friedhelm; Meier, Gerd E. A.; Wegner, Horst


    A system for the automatic evaluation of interference patterns has been developed. After digitizing the interferograms from classical and holografic interferometers with a television digitizer and performing different picture enhancement operations the fringe loci are extracted by use of a floating-threshold method. The fringes are numbered using a special scheme after the removal of any fringe disconnections which might appear if there was insufficient contrast in the interferograms. The reconstruction of the object function from the numbered fringe field is achieved by a local polynomial least-squares approximation. Applications are given, demonstrating the evaluation of interferograms of supersonic flow fields and the analysis of holografic interferograms of car-tyres.

  19. Robust video object cosegmentation. (United States)

    Wang, Wenguan; Shen, Jianbing; Li, Xuelong; Porikli, Fatih


    With ever-increasing volumes of video data, automatic extraction of salient object regions became even more significant for visual analytic solutions. This surge has also opened up opportunities for taking advantage of collective cues encapsulated in multiple videos in a cooperative manner. However, it also brings up major challenges, such as handling of drastic appearance, motion pattern, and pose variations, of foreground objects as well as indiscriminate backgrounds. Here, we present a cosegmentation framework to discover and segment out common object regions across multiple frames and multiple videos in a joint fashion. We incorporate three types of cues, i.e., intraframe saliency, interframe consistency, and across-video similarity into an energy optimization framework that does not make restrictive assumptions on foreground appearance and motion model, and does not require objects to be visible in all frames. We also introduce a spatio-temporal scale-invariant feature transform (SIFT) flow descriptor to integrate across-video correspondence from the conventional SIFT-flow into interframe motion flow from optical flow. This novel spatio-temporal SIFT flow generates reliable estimations of common foregrounds over the entire video data set. Experimental results show that our method outperforms the state-of-the-art on a new extensive data set (ViCoSeg).

  20. Automatic detection of alpine rockslides in continuous seismic data using hidden Markov models (United States)

    Dammeier, Franziska; Moore, Jeffrey R.; Hammer, Conny; Haslinger, Florian; Loew, Simon


    Data from continuously recording permanent seismic networks can contain information about rockslide occurrence and timing complementary to eyewitness observations and thus aid in construction of robust event catalogs. However, detecting infrequent rockslide signals within large volumes of continuous seismic waveform data remains challenging and often requires demanding manual intervention. We adapted an automatic classification method using hidden Markov models to detect rockslide signals in seismic data from two stations in central Switzerland. We first processed 21 known rockslides, with event volumes spanning 3 orders of magnitude and station event distances varying by 1 order of magnitude, which resulted in 13 and 19 successfully classified events at the two stations. Retraining the models to incorporate seismic noise from the day of the event improved the respective results to 16 and 19 successful classifications. The missed events generally had low signal-to-noise ratio and small to medium volumes. We then processed nearly 14 years of continuous seismic data from the same two stations to detect previously unknown events. After postprocessing, we classified 30 new events as rockslides, of which we could verify three through independent observation. In particular, the largest new event, with estimated volume of 500,000 m3, was not generally known within the Swiss landslide community, highlighting the importance of regional seismic data analysis even in densely populated mountainous regions. Our method can be easily implemented as part of existing earthquake monitoring systems, and with an average event detection rate of about two per month, manual verification would not significantly increase operational workload.

  1. A systematic molecular circuit design method for gene networks under biochemical time delays and molecular noises

    Directory of Open Access Journals (Sweden)

    Chang Yu-Te


    Full Text Available Abstract Background Gene networks in nanoscale are of nonlinear stochastic process. Time delays are common and substantial in these biochemical processes due to gene transcription, translation, posttranslation protein modification and diffusion. Molecular noises in gene networks come from intrinsic fluctuations, transmitted noise from upstream genes, and the global noise affecting all genes. Knowledge of molecular noise filtering and biochemical process delay compensation in gene networks is crucial to understand the signal processing in gene networks and the design of noise-tolerant and delay-robust gene circuits for synthetic biology. Results A nonlinear stochastic dynamic model with multiple time delays is proposed for describing a gene network under process delays, intrinsic molecular fluctuations, and extrinsic molecular noises. Then, the stochastic biochemical processing scheme of gene regulatory networks for attenuating these molecular noises and compensating process delays is investigated from the nonlinear signal processing perspective. In order to improve the robust stability for delay toleration and noise filtering, a robust gene circuit for nonlinear stochastic time-delay gene networks is engineered based on the nonlinear robust H∞ stochastic filtering scheme. Further, in order to avoid solving these complicated noise-tolerant and delay-robust design problems, based on Takagi-Sugeno (T-S fuzzy time-delay model and linear matrix inequalities (LMIs technique, a systematic gene circuit design method is proposed to simplify the design procedure. Conclusion The proposed gene circuit design method has much potential for application to systems biology, synthetic biology and drug design when a gene regulatory network has to be designed for improving its robust stability and filtering ability of disease-perturbed gene network or when a synthetic gene network needs to perform robustly under process delays and molecular noises.

  2. Adaptive noise cancellation

    International Nuclear Information System (INIS)

    Akram, N.


    In this report we describe the concept of adaptive noise canceling, an alternative method of estimating signals corrupted by additive noise of interference. The method uses 'primary' input containing the corrupted signal and a 'reference' input containing noise correlated in some unknown way with the primary noise, the reference input is adaptively filtered and subtracted from the primary input to obtain the signal estimate. Adaptive filtering before subtraction allows the treatment of inputs that are deterministic or stochastic, stationary or time variable. When the reference input is free of signal and certain other conditions are met then noise in the primary input can be essentially eliminated without signal distortion. It is further shown that the adaptive filter also acts as notch filter. Simulated results illustrate the usefulness of the adaptive noise canceling technique. (author)

  3. Automatic readout micrometer (United States)

    Lauritzen, T.

    A measuring system is described for surveying and very accurately positioning objects with respect to a reference line. A principle use of this surveying system is for accurately aligning the electromagnets which direct a particle beam emitted from a particle accelerator. Prior art surveying systems require highly skilled surveyors. Prior art systems include, for example, optical surveying systems which are susceptible to operator reading errors, and celestial navigation-type surveying systems, with their inherent complexities. The present invention provides an automatic readout micrometer which can very accurately measure distances. The invention has a simplicity of operation which practically eliminates the possibilities of operator optical reading error, owning to the elimination of traditional optical alignments for making measurements. The invention has an extendable arm which carries a laser surveying target. The extendable arm can be continuously positioned over its entire length of travel by either a coarse of fine adjustment without having the fine adjustment outrun the coarse adjustment until a reference laser beam is centered on the target as indicated by a digital readout. The length of the micrometer can then be accurately and automatically read by a computer and compared with a standardized set of alignment measurements. Due to its construction, the micrometer eliminates any errors due to temperature changes when the system is operated within a standard operating temperature range.

  4. Automatic personnel contamination monitor

    International Nuclear Information System (INIS)

    Lattin, Kenneth R.


    United Nuclear Industries, Inc. (UNI) has developed an automatic personnel contamination monitor (APCM), which uniquely combines the design features of both portal and hand and shoe monitors. In addition, this prototype system also has a number of new features, including: micro computer control and readout, nineteen large area gas flow detectors, real-time background compensation, self-checking for system failures, and card reader identification and control. UNI's experience in operating the Hanford N Reactor, located in Richland, Washington, has shown the necessity of automatically monitoring plant personnel for contamination after they have passed through the procedurally controlled radiation zones. This final check ensures that each radiation zone worker has been properly checked before leaving company controlled boundaries. Investigation of the commercially available portal and hand and shoe monitors indicated that they did not have the sensitivity or sophistication required for UNI's application, therefore, a development program was initiated, resulting in the subject monitor. Field testing shows good sensitivity to personnel contamination with the majority of alarms showing contaminants on clothing, face and head areas. In general, the APCM has sensitivity comparable to portal survey instrumentation. The inherit stand-in, walk-on feature of the APCM not only makes it easy to use, but makes it difficult to bypass. (author)

  5. Acceptable noise level

    DEFF Research Database (Denmark)

    Olsen, Steen Østergaard; Nielsen, Lars Holme; Lantz, Johannes


    The acceptable noise level (ANL) is used to quantify the amount of background noise that subjects can accept while listening to speech, and is suggested for prediction of individual hearing-aid use. The aim of this study was to assess the repeatability of the ANL measured in normal-hearing subjects...... using running Danish and non-semantic speech materials as stimuli and modulated speech-spectrum and multi-talker babble noises as competing stimuli....

  6. Automatic Segmentation of Vessels in In-Vivo Ultrasound Scans

    DEFF Research Database (Denmark)

    Tamimi-Sarnikowski, Philip; Brink-Kjær, Andreas; Moshavegh, Ramin


    was evaluated empirically and applied to a dataset of in-vivo 1770 images recorded from 8 healthy subjects. The segmentation results were compared to manual delineation performed by two experienced users. The results showed a sensitivity and specificity of 90.41 ± 11.2 % and 97.93 ± 5.7 % (mean ± standard......Ultrasound has become highly popular to monitor atherosclerosis, by scanning the carotid artery. The screening involves measuring the thickness of the vessel wall and diameter of the lumen. An automatic segmentation of the vessel lumen, can enable the determination of lumen diameter. This paper...... presents a fully automatic segmentation algorithm, for robustly segmenting the vessel lumen in longitudinal B-mode ultrasound images. The automatic segmentation is performed using a combination of B-mode and power Doppler images. The proposed algorithm includes a series of preprocessing steps, and performs...

  7. Formal Specification Based Automatic Test Generation for Embedded Network Systems

    Directory of Open Access Journals (Sweden)

    Eun Hye Choi


    Full Text Available Embedded systems have become increasingly connected and communicate with each other, forming large-scaled and complicated network systems. To make their design and testing more reliable and robust, this paper proposes a formal specification language called SENS and a SENS-based automatic test generation tool called TGSENS. Our approach is summarized as follows: (1 A user describes requirements of target embedded network systems by logical property-based constraints using SENS. (2 Given SENS specifications, test cases are automatically generated using a SAT-based solver. Filtering mechanisms to select efficient test cases are also available in our tool. (3 In addition, given a testing goal by the user, test sequences are automatically extracted from exhaustive test cases. We’ve implemented our approach and conducted several experiments on practical case studies. Through the experiments, we confirmed the efficiency of our approach in design and test generation of real embedded air-conditioning network systems.

  8. Automatic segmentation of the wire frame of stent grafts from CT data. (United States)

    Klein, Almar; van der Vliet, J Adam; Oostveen, Luuk J; Hoogeveen, Yvonne; Kool, Leo J Schultze; Renema, W Klaas Jan; Slump, Cornelis H


    Endovascular aortic replacement (EVAR) is an established technique, which uses stent grafts to treat aortic aneurysms in patients at risk of aneurysm rupture. Late stent graft failure is a serious complication in endovascular repair of aortic aneurysms. Better understanding of the motion characteristics of stent grafts will be beneficial for designing future devices. In addition, analysis of stent graft movement in individual patients in vivo can be valuable for predicting stent graft failure in these patients. To be able to gather information on stent graft motion in a quick and robust fashion, we propose an automatic method to segment stent grafts from CT data, consisting of three steps: the detection of seed points, finding the connections between these points to produce a graph, and graph processing to obtain the final geometric model in the form of an undirected graph. Using annotated reference data, the method was optimized and its accuracy was evaluated. The experiments were performed using data containing the AneuRx and Zenith stent grafts. The algorithm is robust for noise and small variations in the used parameter values, does not require much memory according to modern standards, and is fast enough to be used in a clinical setting (65 and 30s for the two stent types, respectively). Further, it is shown that the resulting graphs have a 95% (AneuRx) and 92% (Zenith) correspondence with the annotated data. The geometric model produced by the algorithm allows incorporation of high level information and material properties. This enables us to study the in vivo motions and forces that act on the frame of the stent. We believe that such studies will provide new insights into the behavior of the stent graft in vivo, enables the detection and prediction of stent failure in individual patients, and can help in designing better stent grafts in the future. Copyright © 2011 Elsevier B.V. All rights reserved.

  9. Robust Schur Stability and Robust H^2 Performance

    DEFF Research Database (Denmark)

    Stoustrup, Jakob; Zhao, K.-Y.


    In this paper we address the problems of robust stability androbust QTR H^2 performance for uncertain discrete time systemswith nonlinear parametric uncertainties. We consider two families ofsystems with parametric uncertainties described by state space modelswhich offer a fairly general...... providea line search algorithm for the these two problems in case of two parameters.Both for the robust stability and the robust performance probelm, explicitnecessary and sufficient conditions are derived. An illustrative exampledemonstrates the algorithms....

  10. Landing gear noise attenuation (United States)

    Moe, Jeffrey W. (Inventor); Whitmire, Julia (Inventor); Kwan, Hwa-Wan (Inventor); Abeysinghe, Amal (Inventor)


    A landing gear noise attenuator mitigates noise generated by airframe deployable landing gear. The noise attenuator can have a first position when the landing gear is in its deployed or down position, and a second position when the landing gear is in its up or stowed position. The noise attenuator may be an inflatable fairing that does not compromise limited space constraints associated with landing gear retraction and stowage. A truck fairing mounted under a truck beam can have a compliant edge to allow for non-destructive impingement of a deflected fire during certain conditions.

  11. Noise in biological circuits. (United States)

    Simpson, Michael L; Cox, Chris D; Allen, Michael S; McCollum, James M; Dar, Roy D; Karig, David K; Cooke, John F


    Noise biology focuses on the sources, processing, and biological consequences of the inherent stochastic fluctuations in molecular transitions or interactions that control cellular behavior. These fluctuations are especially pronounced in small systems where the magnitudes of the fluctuations approach or exceed the mean value of the molecular population. Noise biology is an essential component of nanomedicine where the communication of information is across a boundary that separates small synthetic and biological systems that are bound by their size to reside in environments of large fluctuations. Here we review the fundamentals of the computational, analytical, and experimental approaches to noise biology. We review results that show that the competition between the benefits of low noise and those of low population has resulted in the evolution of genetic system architectures that produce an uneven distribution of stochasticity across the molecular components of cells and, in some cases, use noise to drive biological function. We review the exact and approximate approaches to gene circuit noise analysis and simulation, and review many of the key experimental results obtained using flow cytometry and time-lapse fluorescent microscopy. In addition, we consider the probative value of noise with a discussion of using measured noise properties to elucidate the structure and function of the underlying gene circuit. We conclude with a discussion of the frontiers of and significant future challenges for noise biology. (c) 2009 John Wiley & Sons, Inc.

  12. Noise upon the Sinusoids

    DEFF Research Database (Denmark)

    Jensen, Karl Kristoffer


    Sinusoids are used for making harmonic and other sounds. In order to having life in the sounds and adding a wide variety of noises, irregularities are inserted in the frequency and amplitudes. A simple and intuitive noise model is presented, consisting of a low-pass filtered noise, and having...... control for strength and bandwidth. The noise is added on the frequency and amplitudes of the sinusoids, and the resulting irregularity’s (jitter and shimmer) bandwidth is derived. This, together with an overview of investigation methods of the jitter and shimmer results in an analysis of the necessary...

  13. Reachability Games on Automatic Graphs (United States)

    Neider, Daniel

    In this work we study two-person reachability games on finite and infinite automatic graphs. For the finite case we empirically show that automatic game encodings are competitive to well-known symbolic techniques such as BDDs, SAT and QBF formulas. For the infinite case we present a novel algorithm utilizing algorithmic learning techniques, which allows to solve huge classes of automatic reachability games.

  14. Automatic reactor protection system tester

    International Nuclear Information System (INIS)

    Deliant, J.D.; Jahnke, S.; Raimondo, E.


    The object of this paper is to present the automatic tester of reactor protection systems designed and developed by EDF and Framatome. In order, the following points are discussed: . The necessity for reactor protection system testing, . The drawbacks of manual testing, . The description and use of the Framatome automatic tester, . On-site installation of this system, . The positive results obtained using the Framatome automatic tester in France

  15. Robustness Analysis of an Outranking Model Parameters’ Elicitation Method in the Presence of Noisy Examples

    Directory of Open Access Journals (Sweden)

    Nelson Rangel-Valdez


    Full Text Available One of the main concerns in Multicriteria Decision Aid (MCDA is robustness analysis. Some of the most important approaches to model decision maker preferences are based on fuzzy outranking models whose parameters (e.g., weights and veto thresholds must be elicited. The so-called preference-disaggregation analysis (PDA has been successfully carried out by means of metaheuristics, but this kind of works lacks a robustness analysis. Based on the above, the present research studies the robustness of a PDA metaheuristic method to estimate model parameters of an outranking-based relational system of preferences. The method is considered robust if the solutions obtained in the presence of noise can maintain the same performance in predicting preference judgments in a new reference set. The research shows experimental evidence that the PDA method keeps the same performance in situations with up to 10% of noise level, making it robust.

  16. Optimal and robust control of transition (United States)

    Bewley, T. R.; Agarwal, R.


    Optimal and robust control theories are used to determine feedback control rules that effectively stabilize a linearly unstable flow in a plane channel. Wall transpiration (unsteady blowing/suction) with zero net mass flux is used as the control. Control algorithms are considered that depend both on full flowfield information and on estimates of that flowfield based on wall skin-friction measurements only. The development of these control algorithms accounts for modeling errors and measurement noise in a rigorous fashion; these disturbances are considered in both a structured (Gaussian) and unstructured ('worst case') sense. The performance of these algorithms is analyzed in terms of the eigenmodes of the resulting controlled systems, and the sensitivity of individual eigenmodes to both control and observation is quantified.

  17. Robust Design Based Optimisation of Waterjet Cutting

    Directory of Open Access Journals (Sweden)

    Deaconescu Tudor


    Full Text Available The most important input quantities of waterjet cutting are the jet pressure, feed speed, stand-off distance, abrasive graining, mass flow, etc. Other quantities contributing to machining efficiency are the type of utilized abrasive or the tilt of the jet. Each of these quantities can be assigned different set points. The roughness of the machined surfaces and the thickness of the cut part are output quantities of the system, their values depending on the input parameters and the influence of various disturbing factors (noises. The paper discusses surface roughness obtained consequently to abrasive jet cutting. Optimisation of the machining system was achieved by intervening on five selected input quantities (factors, with two set points considered for each. Upon applying Taguchi methods, eventually the combination of factor set points was determined that ensures robust behaviour of the system.

  18. Seismic noise level variation in South Korea (United States)

    Sheen, D.; Shin, J.


    The variations of seismic background noise in South Korea have been investigated by means of power spectral analysis. The Korea Institute of Geoscience and Mineral Resources (KIGAM) and the Korea Meteorological Administation (KMA) have national wide seismic networks in South Korea, and, in the end of 2007, there are 30 broadband stations which have been operating for more than a year. In this study, we have estimated the power spectral density of seismic noise for 30 broadband stations from 2005 to 2007. Since we estimate PSDs from a large dataset of continuous waveform in this study, a robust PSD estimate of McNamara and Buland (2004) is used. In the frequency range 1-5 Hz, the diurnal variations of noise are observed at most of stations, which are especially larger at coastal stations and at insular than at inland. Some stations shows daily difference of diurnal variations, which represents that cultural activities contribute to the noise level of a station. The variation of number of triggered stations, however, shows that cultural noise has little influence on the detection capability of seismic network in South Korea. Seasonal variations are observed well in the range 0.1-0.5 Hz, while much less found in the frequency range 1-5 Hz. We observed that strong peaks in the range 0.1-0.5 Hz occur at the summer when Pacific typhoons are close to the Korean Peninsula.

  19. Automatic sets and Delone sets

    International Nuclear Information System (INIS)

    Barbe, A; Haeseler, F von


    Automatic sets D part of Z m are characterized by having a finite number of decimations. They are equivalently generated by fixed points of certain substitution systems, or by certain finite automata. As examples, two-dimensional versions of the Thue-Morse, Baum-Sweet, Rudin-Shapiro and paperfolding sequences are presented. We give a necessary and sufficient condition for an automatic set D part of Z m to be a Delone set in R m . The result is then extended to automatic sets that are defined as fixed points of certain substitutions. The morphology of automatic sets is discussed by means of examples

  20. Training shortest-path tractography: Automatic learning of spatial priors. (United States)

    Kasenburg, Niklas; Liptrot, Matthew; Reislev, Nina Linde; Ørting, Silas N; Nielsen, Mads; Garde, Ellen; Feragen, Aasa


    Tractography is the standard tool for automatic delineation of white matter tracts from diffusion weighted images. However, the output of tractography often requires post-processing to remove false positives and ensure a robust delineation of the studied tract, and this demands expert prior knowledge. Here we demonstrate how such prior knowledge, or indeed any prior spatial information, can be automatically incorporated into a shortest-path tractography approach to produce more robust results. We describe how such a prior can be automatically generated (learned) from a population, and we demonstrate that our framework also retains support for conventional interactive constraints such as waypoint regions. We apply our approach to the open access, high quality Human Connectome Project data, as well as a dataset acquired on a typical clinical scanner. Our results show that the use of a learned prior substantially increases the overlap of tractography output with a reference atlas on both populations, and this is confirmed by visual inspection. Furthermore, we demonstrate how a prior learned on the high quality dataset significantly increases the overlap with the reference for the more typical yet lower quality data acquired on a clinical scanner. We hope that such automatic incorporation of prior knowledge and the obviation of expert interactive tract delineation on every subject, will improve the feasibility of large clinical tractography studies. Copyright © 2016 Elsevier Inc. All rights reserved.

  1. Robust cognitive change. (United States)

    Salthouse, Timothy A


    Two major challenges facing researchers interested in cognitive change are that measures of change are often not very reliable, and they may reflect effects of prior test experience in addition to the factors of primary interest. One approach to dealing with these problems is to obtain multiple measures of change on parallel versions of the same tests in a measurement burst design. A total of 783 adults performed three parallel versions of cognitive tests on two occasions separated by an average of 2.6 years. Performance increased substantially across the three sessions within each occasion, and for all but vocabulary ability these within-occasion improvements were considerably larger than the between-occasion changes. Reliabilities of the changes in composite scores were low, but averages of the three changes had larger, albeit still quite modest, reliabilities. In some cognitive abilities individual differences were evident in the relation of prior test experience and the magnitude of longitudinal change. Although multiple assessments are more time consuming than traditional measurement procedures, the resulting estimates of change are more robust than those from conventional methods, and also allow the influence of practice on change to be systematically investigated.

  2. Robust continuous clustering. (United States)

    Shah, Sohil Atul; Koltun, Vladlen


    Clustering is a fundamental procedure in the analysis of scientific data. It is used ubiquitously across the sciences. Despite decades of research, existing clustering algorithms have limited effectiveness in high dimensions and often require tuning parameters for different domains and datasets. We present a clustering algorithm that achieves high accuracy across multiple domains and scales efficiently to high dimensions and large datasets. The presented algorithm optimizes a smooth continuous objective, which is based on robust statistics and allows heavily mixed clusters to be untangled. The continuous nature of the objective also allows clustering to be integrated as a module in end-to-end feature learning pipelines. We demonstrate this by extending the algorithm to perform joint clustering and dimensionality reduction by efficiently optimizing a continuous global objective. The presented approach is evaluated on large datasets of faces, hand-written digits, objects, newswire articles, sensor readings from the Space Shuttle, and protein expression levels. Our method achieves high accuracy across all datasets, outperforming the best prior algorithm by a factor of 3 in average rank.

  3. Sounds and Noises. A Position Paper on Noise Pollution. (United States)

    Chapman, Thomas L.

    This position paper focuses on noise pollution and the problems and solutions associated with this form of pollution. The paper is divided into the following five sections: Noise and the Ear, Noise Measurement, III Effects of Noise, Acoustics and Action, and Programs and Activities. The first section identifies noise and sound, the beginnings of…

  4. Noise and Health: How does noise affect us?

    NARCIS (Netherlands)

    Miedema, H.M.E.


    Noise annoyance is a primary indication that noise is a problem, and by itself noise annoyance means that the quality of life is adversely affected. Results from noise annoyance research are presented that make possible a detailed evaluation of noise exposures with respect to the annoyance induced.

  5. Automatic design of digital synthetic gene circuits.

    Directory of Open Access Journals (Sweden)

    Mario A Marchisio


    Full Text Available De novo computational design of synthetic gene circuits that achieve well-defined target functions is a hard task. Existing, brute-force approaches run optimization algorithms on the structure and on the kinetic parameter values of the network. However, more direct rational methods for automatic circuit design are lacking. Focusing on digital synthetic gene circuits, we developed a methodology and a corresponding tool for in silico automatic design. For a given truth table that specifies a circuit's input-output relations, our algorithm generates and ranks several possible circuit schemes without the need for any optimization. Logic behavior is reproduced by the action of regulatory factors and chemicals on the promoters and on the ribosome binding sites of biological Boolean gates. Simulations of circuits with up to four inputs show a faithful and unequivocal truth table representation, even under parametric perturbations and stochastic noise. A comparison with already implemented circuits, in addition, reveals the potential for simpler designs with the same function. Therefore, we expect the method to help both in devising new circuits and in simplifying existing solutions.

  6. Process and device for automatically surveying complex installations

    International Nuclear Information System (INIS)

    Pekrul, P.J.; Thiele, A.W.


    A description is given of a process for automatically analysing separate signal processing channels in real time, one channel per signal, in a facility with significant background noise in signals varying in time and coming from transducers at selected points for the continuous monitoring of the operating conditions of the various components of the installation. The signals are intended to determine potential breakdowns, determine conclusions as to the severity of these potential breakdowns and indicate to an operator the measures to be taken in consequence. The feature of this process is that it comprises the automatic and successive selection of each channel for the purpose of spectral analysis, the automatic processing of the signal of each selected channel to show energy spectrum density data at pre-determined frequencies, the automatic comparison of the energy spectrum density data of each channel with pre-determined sets of limits varying with the frequency, and the automatic indication to the operator of the condition of the various components of the installation associated to each channel and the measures to be taken depending on the set of limits [fr

  7. Robust modal curvature features for identifying multiple damage in beams (United States)

    Ostachowicz, Wiesław; Xu, Wei; Bai, Runbo; Radzieński, Maciej; Cao, Maosen


    Curvature mode shape is an effective feature for damage detection in beams. However, it is susceptible to measurement noise, easily impairing its advantage of sensitivity to damage. To deal with this deficiency, this study formulates an improved curvature mode shape for multiple damage detection in beams based on integrating a wavelet transform (WT) and a Teager energy operator (TEO). The improved curvature mode shape, termed the WT - TEO curvature mode shape, has inherent capabilities of immunity to noise and sensitivity to damage. The proposed method is experimentally validated by identifying multiple cracks in cantilever steel beams with the mode shapes acquired using a scanning laser vibrometer. The results demonstrate that the improved curvature mode shape can identify multiple damage accurately and reliably, and it is fairly robust to measurement noise.

  8. Automatic quantitative metallography

    International Nuclear Information System (INIS)

    Barcelos, E.J.B.V.; Ambrozio Filho, F.; Cunha, R.C.


    The quantitative determination of metallographic parameters is analysed through the description of Micro-Videomat automatic image analysis system and volumetric percentage of perlite in nodular cast irons, porosity and average grain size in high-density sintered pellets of UO 2 , and grain size of ferritic steel. Techniques adopted are described and results obtained are compared with the corresponding ones by the direct counting process: counting of systematic points (grid) to measure volume and intersections method, by utilizing a circunference of known radius for the average grain size. The adopted technique for nodular cast iron resulted from the small difference of optical reflectivity of graphite and perlite. Porosity evaluation of sintered UO 2 pellets is also analyzed [pt

  9. Semi-automatic fluoroscope

    International Nuclear Information System (INIS)

    Tarpley, M.W.


    Extruded aluminum-clad uranium-aluminum alloy fuel tubes must pass many quality control tests before irradiation in Savannah River Plant nuclear reactors. Nondestructive test equipment has been built to automatically detect high and low density areas in the fuel tubes using x-ray absorption techniques with a video analysis system. The equipment detects areas as small as 0.060-in. dia with 2 percent penetrameter sensitivity. These areas are graded as to size and density by an operator using electronic gages. Video image enhancement techniques permit inspection of ribbed cylindrical tubes and make possible the testing of areas under the ribs. Operation of the testing machine, the special low light level television camera, and analysis and enhancement techniques are discussed


    Directory of Open Access Journals (Sweden)

    M. Mathias


    Full Text Available Procedural modeling has proven to be a very valuable tool in the field of architecture. In the last few years, research has soared to automatically create procedural models from images. However, current algorithms for this process of inverse procedural modeling rely on the assumption that the building style is known. So far, the determination of the building style has remained a manual task. In this paper, we propose an algorithm which automates this process through classification of architectural styles from facade images. Our classifier first identifies the images containing buildings, then separates individual facades within an image and determines the building style. This information could then be used to initialize the building reconstruction process. We have trained our classifier to distinguish between several distinct architectural styles, namely Flemish Renaissance, Haussmannian and Neoclassical. Finally, we demonstrate our approach on various street-side images.

  11. Automatic surveying techniques

    International Nuclear Information System (INIS)

    Sah, R.


    In order to investigate the feasibility of automatic surveying methods in a more systematic manner, the PEP organization signed a contract in late 1975 for TRW Systems Group to undertake a feasibility study. The completion of this study resulted in TRW Report 6452.10-75-101, dated December 29, 1975, which was largely devoted to an analysis of a survey system based on an Inertial Navigation System. This PEP note is a review and, in some instances, an extension of that TRW report. A second survey system which employed an ''Image Processing System'' was also considered by TRW, and it will be reviewed in the last section of this note. 5 refs., 5 figs., 3 tabs

  12. Automatic detection and visualisation of MEG ripple oscillations in epilepsy

    Directory of Open Access Journals (Sweden)

    Nicole van Klink


    Full Text Available High frequency oscillations (HFOs, 80–500 Hz in invasive EEG are a biomarker for the epileptic focus. Ripples (80–250 Hz have also been identified in non-invasive MEG, yet detection is impeded by noise, their low occurrence rates, and the workload of visual analysis. We propose a method that identifies ripples in MEG through noise reduction, beamforming and automatic detection with minimal user effort. We analysed 15 min of presurgical resting-state interictal MEG data of 25 patients with epilepsy. The MEG signal-to-noise was improved by using a cross-validation signal space separation method, and by calculating ~2400 beamformer-based virtual sensors in the grey matter. Ripples in these sensors were automatically detected by an algorithm optimized for MEG. A small subset of the identified ripples was visually checked. Ripple locations were compared with MEG spike dipole locations and the resection area if available. Running the automatic detection algorithm resulted in on average 905 ripples per patient, of which on average 148 ripples were visually reviewed. Reviewing took approximately 5 min per patient, and identified ripples in 16 out of 25 patients. In 14 patients the ripple locations showed good or moderate concordance with the MEG spikes. For six out of eight patients who had surgery, the ripple locations showed concordance with the resection area: 4/5 with good outcome and 2/3 with poor outcome. Automatic ripple detection in beamformer-based virtual sensors is a feasible non-invasive tool for the identification of ripples in MEG. Our method requires minimal user effort and is easily applicable in a clinical setting.

  13. Automatic alkaloid removal system. (United States)

    Yahaya, Muhammad Rizuwan; Hj Razali, Mohd Hudzari; Abu Bakar, Che Abdullah; Ismail, Wan Ishak Wan; Muda, Wan Musa Wan; Mat, Nashriyah; Zakaria, Abd


    This alkaloid automated removal machine was developed at Instrumentation Laboratory, Universiti Sultan Zainal Abidin Malaysia that purposely for removing the alkaloid toxicity from Dioscorea hispida (DH) tuber. It is a poisonous plant where scientific study has shown that its tubers contain toxic alkaloid constituents, dioscorine. The tubers can only be consumed after it poisonous is removed. In this experiment, the tubers are needed to blend as powder form before inserting into machine basket. The user is need to push the START button on machine controller for switching the water pump ON by then creating turbulence wave of water in machine tank. The water will stop automatically by triggering the outlet solenoid valve. The powders of tubers are washed for 10 minutes while 1 liter of contaminated water due toxin mixture is flowing out. At this time, the controller will automatically triggered inlet solenoid valve and the new water will flow in machine tank until achieve the desire level that which determined by ultra sonic sensor. This process will repeated for 7 h and the positive result is achieved and shows it significant according to the several parameters of biological character ofpH, temperature, dissolve oxygen, turbidity, conductivity and fish survival rate or time. From that parameter, it also shows the positive result which is near or same with control water and assuming was made that the toxin is fully removed when the pH of DH powder is near with control water. For control water, the pH is about 5.3 while water from this experiment process is 6.0 and before run the machine the pH of contaminated water is about 3.8 which are too acid. This automated machine can save time for removing toxicity from DH compared with a traditional method while less observation of the user.

  14. A fully automatic nerve segmentation and morphometric parameter quantification system for early diagnosis of diabetic neuropathy in corneal images. (United States)

    Al-Fahdawi, Shumoos; Qahwaji, Rami; Al-Waisy, Alaa S; Ipson, Stanley; Malik, Rayaz A; Brahma, Arun; Chen, Xin


    Diabetic Peripheral Neuropathy (DPN) is one of the most common types of diabetes that can affect the cornea. An accurate analysis of the nerve structures can assist the early diagnosis of this disease. This paper proposes a robust, fast and fully automatic nerve segmentation and morphometric parameter quantification system for corneal confocal microscope images. The segmentation part consists of three main steps. First, a preprocessing step is applied to enhance the visibility of the nerves and remove noise using anisotropic diffusion filtering, specifically a Coherence filter followed by Gaussian filtering. Second, morphological operations are applied to remove unwanted objects in the input image such as epithelial cells and small nerve segments. Finally, an edge detection step is applied to detect all the nerves in the input image. In this step, an efficient algorithm for connecting discontinuous nerves is proposed. In the morphometric parameters quantification part, a number of features are extracted, including thickness, tortuosity and length of nerve, which may be used for the early diagnosis of diabetic polyneuropathy and when planning Laser-Assisted in situ Keratomileusis (LASIK) or Photorefractive keratectomy (PRK). The performance of the proposed segmentation system is evaluated against manually traced ground-truth images based on a database consisting of 498 corneal sub-basal nerve images (238 are normal and 260 are abnormal). In addition, the robustness and efficiency of the proposed system in extracting morphometric features with clinical utility was evaluated in 919 images taken from healthy subjects and diabetic patients with and without neuropathy. We demonstrate rapid (13 seconds/image), robust and effective automated corneal nerve quantification. The proposed system will be deployed as a useful clinical tool to support the expertise of ophthalmologists and save the clinician time in a busy clinical setting. Copyright © 2016 Elsevier Ireland Ltd

  15. Robustness Evaluation of Timber Structures

    DEFF Research Database (Denmark)

    Kirkegaard, Poul Henning; Sørensen, John Dalsgaard


    The present paper considers robustness evaluation of a Norwegian sports arena with a structural system of glulam frames. The robustness evaluation is based on the framework for robustness analysis introduced in the Danish Code of Practice for the Safety of Structures and a probabilistic modelling...... of the timber material proposed in the Probabilistic Model Code (PMC) of the Joint Committee on Structural Safety (JCSS). The results show that the requirements for robustness of the structure are highly related to the modelling of the snow load used on the structures when ‘removal of a limited part...

  16. Model tracking dual stochastic controller design under irregular internal noises

    International Nuclear Information System (INIS)

    Lee, Jong Bok; Heo, Hoon; Cho, Yun Hyun; Ji, Tae Young


    Although many methods about the control of irregular external noise have been introduced and implemented, it is still necessary to design a controller that will be more effective and efficient methods to exclude for various noises. Accumulation of errors due to model tracking, internal noises (thermal noise, shot noise and l/f noise) that come from elements such as resistor, diode and transistor etc. in the circuit system and numerical errors due to digital process often destabilize the system and reduce the system performance. New stochastic controller is adopted to remove those noises using conventional controller simultaneously. Design method of a model tracking dual controller is proposed to improve the stability of system while removing external and internal noises. In the study, design process of the model tracking dual stochastic controller is introduced that improves system performance and guarantees robustness under irregular internal noises which can be created internally. The model tracking dual stochastic controller utilizing F-P-K stochastic control technique developed earlier is implemented to reveal its performance via simulation

  17. The impact of different background noises on the Production Effect. (United States)

    Mama, Yaniv; Fostick, Leah; Icht, Michal


    The presence of background noise has been previously shown to disrupt cognitive performance, especially memory. The amount of interference is derived from the acoustic characteristics of the noise; energetic vs. informational, steady-state vs. fluctuating. However, the literature is inconsistent concerning the effects of different types of noise on long-term memory free recall. In the present study, we tested the impact of different noises on recall of items that were learned under two conditions - silent or aloud reading, a Production Effect (PE) paradigm. As the PE represents enhanced memory for words read aloud relative to words read silently during study, we focused on the effect of noise on this robust memory phenomenon. The results showed that (a) steady-state energetic noise did not affect memory, with a recall advantage for aloud words (PE), comparable to a no-noise condition, (b) fluctuating-energetic noise and fluctuating-informational (eight-talkers babble) noise eliminated the PE, with similar recall for aloud and silent items. These results are discussed in light of their theoretical implications, stressing the role of attention in the PE. Ecological implications regarding studying in noisy environments are suggested. Copyright © 2018 Elsevier B.V. All rights reserved.

  18. Evolution of Robustness and Plasticity under Environmental Fluctuation: Formulation in Terms of Phenotypic Variances (United States)

    Kaneko, Kunihiko


    The characterization of plasticity, robustness, and evolvability, an important issue in biology, is studied in terms of phenotypic fluctuations. By numerically evolving gene regulatory networks, the proportionality between the phenotypic variances of epigenetic and genetic origins is confirmed. The former is given by the variance of the phenotypic fluctuation due to noise in the developmental process; and the latter, by the variance of the phenotypic fluctuation due to genetic mutation. The relationship suggests a link between robustness to noise and to mutation, since robustness can be defined by the sharpness of the distribution of the phenotype. Next, the proportionality between the variances is demonstrated to also hold over expressions of different genes (phenotypic traits) when the system acquires robustness through the evolution. Then, evolution under environmental variation is numerically investigated and it is found that both the adaptability to a novel environment and the robustness are made compatible when a certain degree of phenotypic fluctuations exists due to noise. The highest adaptability is achieved at a certain noise level at which the gene expression dynamics are near the critical state to lose the robustness. Based on our results, we revisit Waddington's canalization and genetic assimilation with regard to the two types of phenotypic fluctuations.

  19. Noise in miniature microphones. (United States)

    Thompson, Stephen C; LoPresti, Janice L; Ring, Eugene M; Nepomuceno, Henry G; Beard, John J; Ballad, William J; Carlson, Elmer V


    The internal noise spectrum in miniature electret microphones of the type used in the manufacture of hearing aids is measured. An analogous circuit model of the microphone is empirically fit to the measured data and used to determine the important sources of noise within the microphone. The dominant noise source is found to depend on the frequency. Below 40 Hz and above 9 kHz, the dominant source is electrical noise from the amplifier circuit needed to buffer the electrical signal from the microphone diaphragm. Between approximately 40 Hz and 1 kHz, the dominant source is thermal noise originating in the acoustic flow resistance of the small hole pierced in the diaphragm to equalize barometric pressure. Between approximately 1 kHz and 9 kHz, the noise originates in the acoustic flow resistances of sound entering the microphone and propagating to the diaphragm. To further reduce the microphone internal noise in the audio band requires attacking these sources. A prototype microphone having reduced acoustical noise is measured and discussed.

  20. Effects of traffic noise

    Energy Technology Data Exchange (ETDEWEB)

    Gottlob, D.


    One of the main sources of noise is road traffic. In 1984 there were over 25 million cars, 1.2 million lorries, 1.3 million motor cycles and 1.6 million mopeds using our roads. Opinion polls showed that 21% of the population felt that they were affected by traffic noise as a nuisance factor. An outline of the effects of this noise on the affected population is given, illustrated by diagrams. Details about noise emissions (drive-past level) of the different types of vehicles in city traffic are stated and the effects of noise described. The author goes into the nuisance effect (noise is not a physical factor, but a psychosocial one), changes in behaviour (ways of speaking, reduction of stress on households in proportion to rising income and higher educational levels) and the consequences for health (the reaction of the body to noise is primarily a consequence of the psychosomatic organisation of ow bodies). In conclusion, the author deals with the subjective efficiency of noise protection measures. (HWJ).

  1. Mediality is Noise

    DEFF Research Database (Denmark)

    Prior, Andrew

    This PhD is concerned with the use of noise as a material within media arts practice, especially in ‘post-digital’ contexts such as glitch electronica, glitch art and uses of old media. It examines the relationship between informational culture and noise, exploring the ways in which the structuring...

  2. Acceptable noise level

    DEFF Research Database (Denmark)

    Olsen, Steen Østergaard; Nielsen, Lars Holme; Lantz, Johannes


    The acceptable noise level (ANL) is used to quantify the amount of background noise that subjects can accept while listening to speech, and is suggested for prediction of individual hearing-aid use. The aim of this study was to assess the repeatability of the ANL measured in normal-hearing subjects...

  3. An Advanced Robust AVR-PSS Based H2 and H∞ Frequency Approachs Simulated Under a Realized GUI


    KABI Wahiba; GHOURAF Djamel Eddine; NACERI Abdellatif


    This article present a comparative study between two advanced robust frequency control strategies and their implementation using our realised Graphical User Interface ‘GUI’ under MATLAB software: the first method based on loop-shaping H∞ optimization technique and the second on robust H2 control method (LQG controller associated with KALMAN filter), and applied on automatic excitation control of synchronous generators, to improve transient stability and robustness of a single machine- infinit...

  4. Laser confocal microscope noise evaluation on injection compression moulded (ICM) transparent polymer Fresnel lenses

    DEFF Research Database (Denmark)

    Loaldi, D.; Calaon, Matteo; Quagliotti, Danilo

    The evaluation of an adequate and robust measuring strategy, for roughness assessment of polymer Fresnel lenses is put under assessment. An ‘on-sample’ measurement noise, is evaluated using a laser confocal microscope (OLYMPUS © Lext). Secondly, the lowest-noise roughness measuring procedure...... is performed by comparing ‘on-sample’ noise with the one calculated on an optical flat. Noise is investigated by means of established methods, i.e. subtraction and averaging methods. Afterwards, the lowest-noise analysis is structured following a 23 full factorial experimental planning, whose factors...

  5. Signal model of noise in open-loop fiber-optic gyros. (United States)

    He, K; Ye, W; He, Z


    The characteristics of noise in fiber-optic gyros are analyzed quantitatively. Based on its physical characteristics and on autocorrelation function evidence, the noise is modeled as the addition of fractal Brownian motion (FBM) and Gaussian white noise (GWN). The value of self-similarlity parameter H in FBM and the intensity of GWN, sigma(w), in the model are robustly determined with an algorithm based on an orthonormal wavelet transform, which demonstrates well the coexistence of the long- and short-term correlation components of the gyro noise. Moreover, it is revealed that FBM dominates the gyro noise, whereas the GWN is minor.

  6. Noise from wind turbines

    International Nuclear Information System (INIS)

    Andersen, B.; Jakobsen, J.


    Based on a previous project concerning the calculation of the amount of noise emanating from wind turbine arrays, this one examines the subject further by investigating whether there could be significant differences in the amount of noise made by individual wind turbines in an array, and whether the noise is transmitted in varying directions - so that when it is carried in the same direction as the wind blows it would appear to be louder. The aim was also to determine whether the previously used method of calculation lacked precision. It was found that differences in noise niveaux related to individual wind turbines were insignificant and that noise was not so loud when it was not borne in the direction of the wind. It was necessary to change the method of calculation as reckoning should include the influence of the terrain, wind velocity and distance. The measuring and calculation methods are exemplified and the resulting measurements are presented in detail. (AB)

  7. Noise from wind turbines

    International Nuclear Information System (INIS)

    Andersen, B.; Larsen, P.


    Denmark has 3200 wind turbines with an installed maximum capacity of 418MW. The most important Danish research projects into wind turbine noise and the main results are listed. These date from 1983. Two comprehensive studies are currently in progress. The first is an analytical and empirical investigation of aerodynamic noise from wind turbine rotors and has so far dealt mainly with tip noise. The measurement method, using a hard board mounted microphone on the ground near the turbine, is described. Four different tip designs have been tested. Some examples of reference sound power level spectra for three of the designs are presented. During the past two years a computerbased data acquisition system has been used for real-time determination of sound power levels. The second study, which has just commenced, is on annoyance from wind turbine noise. It will include noise measurements, masking calculations and a social survey on the perceived nuisance. (UK)

  8. [Urban noise pollution]. (United States)

    Chouard, C H


    Noise is responsible for cochlear and general damages. Hearing loss and tinnitus greatly depend on sound intensity and duration. Short-duration sound of sufficient intensity (gunshot or explosion) will not be described because they are not currently encountered in our normal urban environment. Sound levels of less than 75 d (A) are unlikely to cause permanent hearing loss, while sound levels of about 85 d (A) with exposures of 8 h per day will produce permanent hearing loss after many years. Popular and largely amplified music is today one of the most dangerous causes of noise induced hearing loss. The intensity of noises (airport, highway) responsible for stress and general consequences (cardiovascular) is generally lower. Individual noise sensibility depends on several factors. Strategies to prevent damage from sound exposure should include the use of individual hearing protection devices, education programs beginning with school-age children, consumer guidance, increased product noise labelling, and hearing conservation programs for occupational settings.

  9. Noise data management using commercially available data-base software

    International Nuclear Information System (INIS)

    Damiano, B.; Thie, J.A.


    A data base has been created using commercially available software to manage the data collected by an automated noise data acquisition system operated by Oak Ridge National Laboratory at the Fast Flux Test Facility (FFTF). The data base was created to store, organize, and retrieve selected features of the nuclear and process signal noise data, because the large volume of data collected by the automated system makes manual data handling and interpretation based on visual examination of noise signatures impractical. Compared with manual data handling, use of the data base allows the automatically collected data to be utilized more fully and effectively. The FFTF noise data base uses the Oracle Relational Data Base Management System implemented on a desktop personal computer

  10. Maximum Correntropy Criterion for Robust Face Recognition. (United States)

    He, Ran; Zheng, Wei-Shi; Hu, Bao-Gang


    In this paper, we present a sparse correntropy framework for computing robust sparse representations of face images for recognition. Compared with the state-of-the-art l(1)norm-based sparse representation classifier (SRC), which assumes that noise also has a sparse representation, our sparse algorithm is developed based on the maximum correntropy criterion, which is much more insensitive to outliers. In order to develop a more tractable and practical approach, we in particular impose nonnegativity constraint on the variables in the maximum correntropy criterion and develop a half-quadratic optimization technique to approximately maximize the objective function in an alternating way so that the complex optimization problem is reduced to learning a sparse representation through a weighted linear least squares problem with nonnegativity constraint at each iteration. Our extensive experiments demonstrate that the proposed method is more robust and efficient in dealing with the occlusion and corruption problems in face recognition as compared to the related state-of-the-art methods. In particular, it shows that the proposed method can improve both recognition accuracy and receiver operator characteristic (ROC) curves, while the computational cost is much lower than the SRC algorithms.

  11. Classifying visemes for automatic lipreading

    NARCIS (Netherlands)

    Visser, Michiel; Poel, Mannes; Nijholt, Antinus; Matousek, Vaclav; Mautner, Pavel; Ocelikovi, Jana; Sojka, Petr


    Automatic lipreading is automatic speech recognition that uses only visual information. The relevant data in a video signal is isolated and features are extracted from it. From a sequence of feature vectors, where every vector represents one video image, a sequence of higher level semantic elements

  12. Copyright Protection of Color Imaging Using Robust-Encoded Watermarking

    Directory of Open Access Journals (Sweden)

    M. Cedillo-Hernandez


    Full Text Available In this paper we present a robust-encoded watermarking method applied to color images for copyright protection, which presents robustness against several geometric and signal processing distortions. Trade-off between payload, robustness and imperceptibility is a very important aspect which has to be considered when a watermark algorithm is designed. In our proposed scheme, previously to be embedded into the image, the watermark signal is encoded using a convolutional encoder, which can perform forward error correction achieving better robustness performance. Then, the embedding process is carried out through the discrete cosine transform domain (DCT of an image using the image normalization technique to accomplish robustness against geometric and signal processing distortions. The embedded watermark coded bits are extracted and decoded using the Viterbi algorithm. In order to determine the presence or absence of the watermark into the image we compute the bit error rate (BER between the recovered and the original watermark data sequence. The quality of the watermarked image is measured using the well-known indices: Peak Signal to Noise Ratio (PSNR, Visual Information Fidelity (VIF and Structural Similarity Index (SSIM. The color difference between the watermarked and original images is obtained by using the Normalized Color Difference (NCD measure. The experimental results show that the proposed method provides good performance in terms of imperceptibility and robustness. The comparison among the proposed and previously reported methods based on different techniques is also provided.

  13. Timing robustness in the budding and fission yeast cell cycles.

    KAUST Repository

    Mangla, Karan


    Robustness of biological models has emerged as an important principle in systems biology. Many past analyses of Boolean models update all pending changes in signals simultaneously (i.e., synchronously), making it impossible to consider robustness to variations in timing that result from noise and different environmental conditions. We checked previously published mathematical models of the cell cycles of budding and fission yeast for robustness to timing variations by constructing Boolean models and analyzing them using model-checking software for the property of speed independence. Surprisingly, the models are nearly, but not totally, speed-independent. In some cases, examination of timing problems discovered in the analysis exposes apparent inaccuracies in the model. Biologically justified revisions to the model eliminate the timing problems. Furthermore, in silico random mutations in the regulatory interactions of a speed-independent Boolean model are shown to be unlikely to preserve speed independence, even in models that are otherwise functional, providing evidence for selection pressure to maintain timing robustness. Multiple cell cycle models exhibit strong robustness to timing variation, apparently due to evolutionary pressure. Thus, timing robustness can be a basis for generating testable hypotheses and can focus attention on aspects of a model that may need refinement.

  14. The sequentially discounting autoregressive (SDAR) method for on-line automatic seismic event detecting on long term observation (United States)

    Wang, L.; Toshioka, T.; Nakajima, T.; Narita, A.; Xue, Z.


    In recent years, more and more Carbon Capture and Storage (CCS) studies focus on seismicity monitoring. For the safety management of geological CO2 storage at Tomakomai, Hokkaido, Japan, an Advanced Traffic Light System (ATLS) combined different seismic messages (magnitudes, phases, distributions et al.) is proposed for injection controlling. The primary task for ATLS is the seismic events detection in a long-term sustained time series record. Considering the time-varying characteristics of Signal to Noise Ratio (SNR) of a long-term record and the uneven energy distributions of seismic event waveforms will increase the difficulty in automatic seismic detecting, in this work, an improved probability autoregressive (AR) method for automatic seismic event detecting is applied. This algorithm, called sequentially discounting AR learning (SDAR), can identify the effective seismic event in the time series through the Change Point detection (CPD) of the seismic record. In this method, an anomaly signal (seismic event) can be designed as a change point on the time series (seismic record). The statistical model of the signal in the neighborhood of event point will change, because of the seismic event occurrence. This means the SDAR aims to find the statistical irregularities of the record thought CPD. There are 3 advantages of SDAR. 1. Anti-noise ability. The SDAR does not use waveform messages (such as amplitude, energy, polarization) for signal detecting. Therefore, it is an appropriate technique for low SNR data. 2. Real-time estimation. When new data appears in the record, the probability distribution models can be automatic updated by SDAR for on-line processing. 3. Discounting property. the SDAR introduces a discounting parameter to decrease the influence of present statistic value on future data. It makes SDAR as a robust algorithm for non-stationary signal processing. Within these 3 advantages, the SDAR method can handle the non-stationary time-varying long

  15. Improving automatic cooperation between UAVs through co-evolution (United States)

    Smith, James F., III


    A fuzzy logic resource manager (RM) that enables a collection of unmanned aerial vehicles (UAVs) to automatically cooperate to make meteorological measurements will be discussed. The RM renders the UAVs autonomous allowing them to change paths and cooperate without human intervention. Innovations related to the "priority for helping" (PH) fuzzy decision tree (FDT) used by the RM will be discussed. The PH FDT permits three types of automatic cooperation between the UAVs. A subroutine of the communications routing algorithm (CRA) used by the RM is also examined. The CRA allows the UAVs to reestablish communications if needed by changing their behavior. A genetic program (GP) based procedure for automatically creating FDTs is briefly described. A GP is an algorithm based on the theory of evolution that automatically evolves mathematical expressions or computer algorithms. The GP data mines a scenario database to automatically create the FDTs. A recently invented co-evolutionary process that allows improvement of the initially data mined FDT will be discussed. Co-evolution uses a genetic algorithm (GA) to evolve scenarios to augment the GP's scenario database. The GP data mines the augmented database to discover an improved FDT. The process is iterated ultimately evolving a very robust FDT. Improvements to the PH FDT offered through co-evolution are discussed. UAV simulations using the improved PH FDT and CRA are provided.

  16. Robust spatiotemporal matching of electronic slides to presentation videos. (United States)

    Fan, Quanfu; Barnard, Kobus; Amir, Arnon; Efrat, Alon


    We describe a robust and efficient method for automatically matching and time-aligning electronic slides to videos of corresponding presentations. Matching electronic slides to videos provides new methods for indexing, searching, and browsing videos in distance-learning applications. However, robust automatic matching is challenging due to varied frame composition, slide distortion, camera movement, low-quality video capture, and arbitrary slides sequence. Our fully automatic approach combines image-based matching of slide to video frames with a temporal model for slide changes and camera events. To address these challenges, we begin by extracting scale-invariant feature-transformation (SIFT) keypoints from both slides and video frames, and matching them subject to a consistent projective transformation (homography) by using random sample consensus (RANSAC). We use the initial set of matches to construct a background model and a binary classifier for separating video frames showing slides from those without. We then introduce a new matching scheme for exploiting less distinctive SIFT keypoints that enables us to tackle more difficult images. Finally, we improve upon the matching based on visual information by using estimated matching probabilities as part of a hidden Markov model (HMM) that integrates temporal information and detected camera operations. Detailed quantitative experiments characterize each part of our approach and demonstrate an average accuracy of over 95% in 13 presentation videos.

  17. Effects of background noise on total noise annoyance (United States)

    Willshire, K. F.


    Two experiments were conducted to assess the effects of combined community noise sources on annoyance. The first experiment baseline relationships between annoyance and noise level for three community noise sources (jet aircraft flyovers, traffic and air conditioners) presented individually. Forty eight subjects evaluated the annoyance of each noise source presented at four different noise levels. Results indicated the slope of the linear relationship between annoyance and noise level for the traffic noise was significantly different from that of aircraft and of air conditioner noise, which had equal slopes. The second experiment investigated annoyance response to combined noise sources, with aircraft noise defined as the major noise source and traffic and air conditioner noise as background noise sources. Effects on annoyance of noise level differences between aircraft and background noise for three total noise levels and for both background noise sources were determined. A total of 216 subjects were required to make either total or source specific annoyance judgements, or a combination of the two, for a wide range of combined noise conditions.

  18. Robust and distributed hypothesis testing

    CERN Document Server

    Gül, Gökhan


    This book generalizes and extends the available theory in robust and decentralized hypothesis testing. In particular, it presents a robust test for modeling errors which is independent from the assumptions that a sufficiently large number of samples is available, and that the distance is the KL-divergence. Here, the distance can be chosen from a much general model, which includes the KL-divergence as a very special case. This is then extended by various means. A minimax robust test that is robust against both outliers as well as modeling errors is presented. Minimax robustness properties of the given tests are also explicitly proven for fixed sample size and sequential probability ratio tests. The theory of robust detection is extended to robust estimation and the theory of robust distributed detection is extended to classes of distributions, which are not necessarily stochastically bounded. It is shown that the quantization functions for the decision rules can also be chosen as non-monotone. Finally, the boo...

  19. Robustness Evaluation of Timber Structures

    DEFF Research Database (Denmark)

    Kirkegaard, Poul Henning; Sørensen, John Dalsgaard


    Robustness of structural systems has obtained a renewed interest due to a much more frequent use of advanced types of structures with limited redundancy and serious consequences in case of failure.......Robustness of structural systems has obtained a renewed interest due to a much more frequent use of advanced types of structures with limited redundancy and serious consequences in case of failure....

  20. Robustness of IPTV business models

    NARCIS (Netherlands)

    Bouwman, H.; Zhengjia, M.; Duin, P. van der; Limonard, S.


    The final stage in the STOF method is an evaluation of the robustness of the design, for which the method provides some guidelines. For many innovative services, the future holds numerous uncertainties, which makes evaluating the robustness of a business model a difficult task. In this chapter, we

  1. Noise and Hearing Loss Prevention (United States)

    ... message, please visit this page: About . NOISE AND HEARING LOSS PREVENTION Language: English (US) Español ( ... when hazardous noise levels cannot be adequately reduced. Noise and Hearing Loss on the NIOSH Science Blog ...

  2. Robustness Analysis of Kinetic Structures

    DEFF Research Database (Denmark)

    Kirkegaard, Poul Henning; Sørensen, John Dalsgaard


    The present paper considers robustness of kinetic structures. Robustness of structures has obtained a renewed interest due to a much more frequent use of advanced types of structures with limited redundancy and serious consequences in case of failure. Especially for these types of structural syst...... systems, it is of interest to investigate how robust the structures are, or what happens if a structural element is added to or removed from the original structure. The present paper discusses this issue for kinetic structures in architecture.......The present paper considers robustness of kinetic structures. Robustness of structures has obtained a renewed interest due to a much more frequent use of advanced types of structures with limited redundancy and serious consequences in case of failure. Especially for these types of structural...

  3. Comparison of robust input shapers (United States)

    Vaughan, Joshua; Yano, Aika; Singhose, William


    The rapid movement of machines is a challenging control problem because it often results in high levels of vibration. As a result, flexible machines are typically moved relatively slowly. Input shaping is a control method that allows much higher speeds of motion by limiting vibration induced by the reference command. To design an input-shaping controller, estimates of the system natural frequency and damping ratio are required. However, real world systems cannot be modeled exactly, making the robustness to modeling errors an important consideration. Many robust input shapers have been developed, but robust shapers typically have longer durations that slow the system response. This creates a compromise between shaper robustness and rise time. This paper analyzes the compromise between rapidity of motion and shaper robustness for several input-shaping methods. Experimental results from a portable bridge crane verify the theoretical predictions.

  4. Automatic Speech Acquisition and Recognition for Spacesuit Audio Systems (United States)

    Ye, Sherry


    NASA has a widely recognized but unmet need for novel human-machine interface technologies that can facilitate communication during astronaut extravehicular activities (EVAs), when loud noises and strong reverberations inside spacesuits make communication challenging. WeVoice, Inc., has developed a multichannel signal-processing method for speech acquisition in noisy and reverberant environments that enables automatic speech recognition (ASR) technology inside spacesuits. The technology reduces noise by exploiting differences between the statistical nature of signals (i.e., speech) and noise that exists in the spatial and temporal domains. As a result, ASR accuracy can be improved to the level at which crewmembers will find the speech interface useful. System components and features include beam forming/multichannel noise reduction, single-channel noise reduction, speech feature extraction, feature transformation and normalization, feature compression, and ASR decoding. Arithmetic complexity models were developed and will help designers of real-time ASR systems select proper tasks when confronted with constraints in computational resources. In Phase I of the project, WeVoice validated the technology. The company further refined the technology in Phase II and developed a prototype for testing and use by suited astronauts.

  5. Handbook Of Noise And Vibration

    International Nuclear Information System (INIS)


    This book is about noise and vibration. The first chapter has explanations of noise such as basic of sound, influence of noise, assessment of noise, measurement of prevention of noise and technology, case of noise measurement and soundproof. The second chapter describes vibration with outline, theory of vibration, interpretation of vibration, measurement for reduction of vibration, case of design of protection against vibration. It deals with related regulation and method of measurement.

  6. Controlled Noise Seismology

    KAUST Repository

    Hanafy, Sherif M.


    We use controlled noise seismology (CNS) to generate surface waves, where we continuously record seismic data while generating artificial noise along the profile line. To generate the CNS data we drove a vehicle around the geophone line and continuously recorded the generated noise. The recorded data set is then correlated over different time windows and the correlograms are stacked together to generate the surface waves. The virtual shot gathers reveal surface waves with moveout velocities that closely approximate those from active source shot gathers.

  7. Automatic exposure for xeromammography

    International Nuclear Information System (INIS)

    Aichinger, H.


    During mammography without intensifying screens, exposure measurements are carried out behind the film. It is, however, difficult to construct an absolutely shadow-free ionization chamber of adequate sensitivity working in the necessary range of 25 to 50 kV. Repeated attempts have been made to utilize the advantages of automatic exposure for xero-mammography. In this case also the ionization chamber was placed behind the Xerox plate. Depending on tube filtration, object thickness and tube voltage, more than 80%, sometimes even 90%, of the radiation is absorbed by the Xerox plate. Particularly the characteristic Mo radiation of 17.4 keV and 19.6 keV is almost totally absorbed by the plate and cannot therefore be registered by the ionization chamber. This results in a considerable dependence of the exposure on kV and object thickness. Dependence on tube voltage and object thickness have been examined dosimetrically and spectroscopically with a Ge(Li)-spectrometer. Finally, the successful use of a shadow-free chamber is described; this has been particularly adapted for xero-mammography and is placed in front of the plate. (orig) [de

  8. Historical Review and Perspective on Automatic Journalizing


    Kato, Masaki


    ContentsIntroduction1. EDP Accounting and Automatic Journalizing2. Learning System of Automatic Journalizing3. Automatic Journalizing by the Artificial Intelligence4. Direction of the Progress of the Accounting Information System

  9. Design of the automatic landing inversion flight control system based on neural network compensation for UAV (United States)

    Chen, Yinchao; Yang, Wei


    A dynamic inversion control method based on neural network compensation for UAV automatic landing is introduced. Aimed at the nonlinear characteristic of automatic landing procedure, the dynamic inversion method is used for feedback linearization. The on-line neural network is introduced to compensation dynamic inversion error caused by the disturbance factors during automatic landing and improves the controller performance. Numerical simulation presents that the control method can make the UAV follow the expected trace properly and have good dynamic performance and robust performance.

  10. Low noise omnidirectional optical receiver for the mobile FSO networks (United States)

    Witas, Karel; Hejduk, Stanislav; Vasinek, Vladimir; Vitasek, Jan; Latal, Jan


    A high sensitive optical receiver design for the mobile free space optical (FSO) networks is presented. There is an array of photo-detectors and preamplifiers working into same load. It is the second stage sum amplifier getting all signals together. This topology creates a parallel amplifier with an excellent signal to noise ratio (SNR). An automatic gain control (AGC) feature is included also. As a result, the effective noise suppression at the receiver side increases optical signal coverage even with the transmitter power being constant. The design has been verified on the model car which was able to respond beyond the line of sight (LOS).

  11. Data preprocessing methods for robust Fourier ptychographic microscopy (United States)

    Zhang, Yan; Pan, An; Lei, Ming; Yao, Baoli


    Fourier ptychographic microscopy (FPM) is a recently developed computational imaging technique that achieves gigapixel images with both high resolution and large field-of-view. In the current FPM experimental setup, the dark-field images with high-angle illuminations are easily overwhelmed by stray lights and background noises due to the low signal-to-noise ratio, thus significantly degrading the achievable resolution of the FPM approach. We provide an overall and systematic data preprocessing scheme to enhance the FPM's performance, which involves sampling analysis, underexposed/overexposed treatments, background noises suppression, and stray lights elimination. It is demonstrated experimentally with both US Air Force (USAF) 1951 resolution target and biological samples that the benefit of the noise removal by these methods far outweighs the defect of the accompanying signal loss, as part of the lost signals can be compensated by the improved consistencies among the captured raw images. In addition, the reported nonparametric scheme could be further cooperated with the existing state-of-the-art algorithms with a great flexibility, facilitating a stronger noise-robust capability of the FPM approach in various applications.

  12. Automatic Atrial Fibrillation Detection: A Novel Approach Using Discrete Wavelet Transform and Heart Rate Variabilit

    DEFF Research Database (Denmark)

    Bruun, Iben H.; Hissabu, Semira M. S.; Poulsen, Erik S.


    be used as a screening tool for patients suspected to have AF. The method includes an automatic peak detection prior to the feature extraction, as well as a noise cancellation technique followed by a bagged tree classification. Simulation studies on the MIT-BIH Atrial Fibrillation database was performed...

  13. The impact of auditory white noise on semantic priming. (United States)

    Angwin, Anthony J; Wilson, Wayne J; Copland, David A; Barry, Robert J; Myatt, Grace; Arnott, Wendy L


    It has been proposed that white noise can improve cognitive performance for some individuals, particularly those with lower attention, and that this effect may be mediated by dopaminergic circuitry. Given existing evidence that semantic priming is modulated by dopamine, this study investigated whether white noise can facilitate semantic priming. Seventy-eight adults completed an auditory semantic priming task with and without white noise, at either a short or long inter-stimulus interval (ISI). Measures of both direct and indirect semantic priming were examined. Analysis of the results revealed significant direct and indirect priming effects at each ISI in noise and silence, however noise significantly reduced the magnitude of indirect priming. Analyses of subgroups with higher versus lower attention revealed a reduction to indirect priming in noise relative to silence for participants with lower executive and orienting attention. These findings suggest that white noise focuses automatic spreading activation, which may be driven by modulation of dopaminergic circuitry. Copyright © 2018 Elsevier Inc. All rights reserved.

  14. Electronic amplifiers for automatic compensators

    CERN Document Server

    Polonnikov, D Ye


    Electronic Amplifiers for Automatic Compensators presents the design and operation of electronic amplifiers for use in automatic control and measuring systems. This book is composed of eight chapters that consider the problems of constructing input and output circuits of amplifiers, suppression of interference and ensuring high sensitivity.This work begins with a survey of the operating principles of electronic amplifiers in automatic compensator systems. The succeeding chapters deal with circuit selection and the calculation and determination of the principal characteristics of amplifiers, as

  15. Accurate estimation of camera shot noise in the real-time (United States)

    Cheremkhin, Pavel A.; Evtikhiev, Nikolay N.; Krasnov, Vitaly V.; Rodin, Vladislav G.; Starikov, Rostislav S.


    Nowadays digital cameras are essential parts of various technological processes and daily tasks. They are widely used in optics and photonics, astronomy, biology and other various fields of science and technology such as control systems and video-surveillance monitoring. One of the main information limitations of photo- and videocameras are noises of photosensor pixels. Camera's photosensor noise can be divided into random and pattern components. Temporal noise includes random noise component while spatial noise includes pattern noise component. Temporal noise can be divided into signal-dependent shot noise and signal-nondependent dark temporal noise. For measurement of camera noise characteristics, the most widely used methods are standards (for example, EMVA Standard 1288). It allows precise shot and dark temporal noise measurement but difficult in implementation and time-consuming. Earlier we proposed method for measurement of temporal noise of photo- and videocameras. It is based on the automatic segmentation of nonuniform targets (ASNT). Only two frames are sufficient for noise measurement with the modified method. In this paper, we registered frames and estimated shot and dark temporal noises of cameras consistently in the real-time. The modified ASNT method is used. Estimation was performed for the cameras: consumer photocamera Canon EOS 400D (CMOS, 10.1 MP, 12 bit ADC), scientific camera MegaPlus II ES11000 (CCD, 10.7 MP, 12 bit ADC), industrial camera PixeLink PL-B781F (CMOS, 6.6 MP, 10 bit ADC) and video-surveillance camera Watec LCL-902C (CCD, 0.47 MP, external 8 bit ADC). Experimental dependencies of temporal noise on signal value are in good agreement with fitted curves based on a Poisson distribution excluding areas near saturation. Time of registering and processing of frames used for temporal noise estimation was measured. Using standard computer, frames were registered and processed during a fraction of second to several seconds only. Also the

  16. Frequently updated noise threat maps created with use of supercomputing grid

    Directory of Open Access Journals (Sweden)

    Szczodrak Maciej


    Full Text Available An innovative supercomputing grid services devoted to noise threat evaluation were presented. The services described in this paper concern two issues, first is related to the noise mapping, while the second one focuses on assessment of the noise dose and its influence on the human hearing system. The discussed serviceswere developed within the PL-Grid Plus Infrastructure which accumulates Polish academic supercomputer centers. Selected experimental results achieved by the usage of the services proposed were presented. The assessment of the environmental noise threats includes creation of the noise maps using either ofline or online data, acquired through a grid of the monitoring stations. A concept of estimation of the source model parameters based on the measured sound level for the purpose of creating frequently updated noise maps was presented. Connecting the noise mapping grid service with a distributed sensor network enables to automatically update noise maps for a specified time period. Moreover, a unique attribute of the developed software is the estimation of the auditory effects evoked by the exposure to noise. The estimation method uses a modified psychoacoustic model of hearing and is based on the calculated noise level values and on the given exposure period. Potential use scenarios of the grid services for research or educational purpose were introduced. Presentation of the results of predicted hearing threshold shift caused by exposure to excessive noise can raise the public awareness of the noise threats.

  17. Acoustics Noise Test Cell (United States)

    Federal Laboratory Consortium — The Acoustic Noise Test Cell at the NASA/Caltech Jet Propulsion Laboratory (JPL) is located adjacent to the large vibration system; both are located in a class 10K...

  18. Alien Noise Cancellation

    Indian Academy of Sciences (India)

    First page Back Continue Last page Overview Graphics. Full FEXT Cancellation. Expectation Maximization based Algorithms. Partial Cancellation. Optimal Choice of what to Cancel and what not to! Alien Noise Cancellation. Efficient Crosstalk channel estimation. In addition:

  19. Airframe noise prediction evaluation (United States)

    Yamamoto, Kingo J.; Donelson, Michael J.; Huang, Shumei C.; Joshi, Mahendra C.


    The objective of this study is to evaluate the accuracy and adequacy of current airframe noise prediction methods using available airframe noise measurements from tests of a narrow body transport (DC-9) and a wide body transport (DC-10) in addition to scale model test data. General features of the airframe noise from these aircraft and models are outlined. The results of the assessment of two airframe prediction methods, Fink's and Munson's methods, against flight test data of these aircraft and scale model wind tunnel test data are presented. These methods were extensively evaluated against measured data from several configurations including clean, slat deployed, landing gear-deployed, flap deployed, and landing configurations of both DC-9 and DC-10. They were also assessed against a limited number of configurations of scale models. The evaluation was conducted in terms of overall sound pressure level (OASPL), tone corrected perceived noise level (PNLT), and one-third-octave band sound pressure level (SPL).

  20. Approximations to camera sensor noise (United States)

    Jin, Xiaodan; Hirakawa, Keigo


    Noise is present in all image sensor data. Poisson distribution is said to model the stochastic nature of the photon arrival process, while it is common to approximate readout/thermal noise by additive white Gaussian noise (AWGN). Other sources of signal-dependent noise such as Fano and quantization also contribute to the overall noise profile. Question remains, however, about how best to model the combined sensor noise. Though additive Gaussian noise with signal-dependent noise variance (SD-AWGN) and Poisson corruption are two widely used models to approximate the actual sensor noise distribution, the justification given to these types of models are based on limited evidence. The goal of this paper is to provide a more comprehensive characterization of random noise. We concluded by presenting concrete evidence that Poisson model is a better approximation to real camera model than SD-AWGN. We suggest further modification to Poisson that may improve the noise model.

  1. Advances in Modal Analysis Using a Robust and Multiscale Method

    Directory of Open Access Journals (Sweden)

    Frisson Christian


    Full Text Available Abstract This paper presents a new approach to modal synthesis for rendering sounds of virtual objects. We propose a generic method that preserves sound variety across the surface of an object at different scales of resolution and for a variety of complex geometries. The technique performs automatic voxelization of a surface model and automatic tuning of the parameters of hexahedral finite elements, based on the distribution of material in each cell. The voxelization is performed using a sparse regular grid embedding of the object, which permits the construction of plausible lower resolution approximations of the modal model. We can compute the audible impulse response of a variety of objects. Our solution is robust and can handle nonmanifold geometries that include both volumetric and surface parts. We present a system which allows us to manipulate and tune sounding objects in an appropriate way for games, training simulations, and other interactive virtual environments.

  2. Theoretical Framework for Robustness Evaluation

    DEFF Research Database (Denmark)

    Sørensen, John Dalsgaard


    This paper presents a theoretical framework for evaluation of robustness of structural systems, incl. bridges and buildings. Typically modern structural design codes require that ‘the consequence of damages to structures should not be disproportional to the causes of the damages’. However, although...... the importance of robustness for structural design is widely recognized the code requirements are not specified in detail, which makes the practical use difficult. This paper describes a theoretical and risk based framework to form the basis for quantification of robustness and for pre-normative guidelines...

  3. Robustness of airline route networks (United States)

    Lordan, Oriol; Sallan, Jose M.; Escorihuela, Nuria; Gonzalez-Prieto, David


    Airlines shape their route network by defining their routes through supply and demand considerations, paying little attention to network performance indicators, such as network robustness. However, the collapse of an airline network can produce high financial costs for the airline and all its geographical area of influence. The aim of this study is to analyze the topology and robustness of the network route of airlines following Low Cost Carriers (LCCs) and Full Service Carriers (FSCs) business models. Results show that FSC hubs are more central than LCC bases in their route network. As a result, LCC route networks are more robust than FSC networks.

  4. A robust Correntropy-based method for analyzing multisample aCGH data. (United States)

    Mohammadi, Majid; Hodtani, Ghosheh Abed; Yassi, Maryam


    This paper presents a new method for analyzing array comparative genomic hybridization (aCGH) data based on Correntropy. A new formulation based on low-rank aCGH data and Correntropy is proposed and its solution is presented based on Half-Quadratic method. Compared to existing methods, the proposed method is more robust to high corruptions and various kinds of noise. Moreover, it analyzes all aCGH profiles relating to a data set simultaneously. Experimental results illustrate the robustness of the proposed method when the noise is non-Gaussian and show its excellent performance in other cases. Copyright © 2015 Elsevier Inc. All rights reserved.

  5. Noise Abatement Materials (United States)


    A former NASA employee who discovered a kind of plastic that soaked up energy, dampened vibrations, and was a good noise abatement material, founded a company to market noise deadening adhesives, sheets, panels and enclosures. Known as SMART products, they are 75-80% lighter than ordinary soundproofing material and have demonstrated a high degree of effectiveness. The company, Varian Associates, makes enclosures for high voltage terminals and other electronic system components, and easily transportable audiometric test booths.

  6. Active noise control primer

    CERN Document Server

    Snyder, Scott D


    Active noise control - the reduction of noise by generating an acoustic signal that actively interferes with the noise - has become an active area of basic research and engineering applications. The aim of this book is to present all of the basic knowledge one needs for assessing how useful active noise control will be for a given problem and then to provide some guidance for designing, setting up, and tuning an active noise-control system. Written for students who have no prior knowledge of acoustics, signal processing, or noise control but who do have a reasonable grasp of basic physics and mathematics, the book is short and descriptive. It leaves for more advanced texts or research monographs all mathematical details and proofs concerning vibrations, signal processing and the like. The book can thus be used in independent study, in a classroom with laboratories, or in conjunction with a kit for experiment or demonstration. Topics covered include: basic acoustics; human perception and sound; sound intensity...

  7. Interframe DPCM with robust median-based predictors for transmission of image sequences over noisy channels. (United States)

    Song, X; Viero, T; Neuvo, Y


    A new image sequence coding technique based on robust median-based predictors is presented for the transmission of image sequences over noisy channels. We analyze the robustness of median-based predictors against channel errors. A heuristic algorithm for the design of a robust predictor from a given median-based predictor is presented. It is shown that with small modifications in terms of a necessary requirement for a median-based predictor to be robust against channel errors, the robustness of a given median-based predictor can be considerably improved. Simulations on a real image sequence show significant improvement over the conventional differential pulse code modulation (DPCM) at high bit error rate (BER) using this new technique. The technique does not increase the transmission rate. It is shown that the quality of reconstructed images obtained by robust median-based predictors can be further improved by postprocessing the image using a nonlinear detail-preserving noise-smoothing filter.

  8. Investigation of Adaptive Robust Kalman Filtering Algorithms for GPS/DR Navigation System Filters (United States)

    Elzoghby, MOSTAFA; Arif, USMAN; Li, FU; Zhi Yu, XI


    The conventional Kalman filter (KF) algorithm is suitable if the characteristic noise covariance for states as well as measurements is readily known but in most cases these are unknown. Similarly robustness is required instead of smoothing if states are changing abruptly. Such an adaptive as well as robust Kalman filter is vital for many real time applications, like target tracking and navigating aerial vehicles. A number of adaptive as well as robust Kalman filtering methods are available in the literature. In order to investigate the performance of some of these methods, we have selected three different Kalman filters, namely Sage Husa KF, Modified Adaptive Robust KF and Adaptively Robust KF, which are easily simulate able as well as implementable for real time applications. These methods are simulated for land based vehicle and the results are compared with conventional Kalman filter. Results show that the Modified Adaptive Robust KF is best amongst the selected methods and can be used for Navigation applications.

  9. A robust moving mesh finite volume method applied to 1D hyperbolic conservation laws from magnetohydrodynamics

    NARCIS (Netherlands)

    Dam, A. van; Zegeling, P.A.


    In this paper we describe a one-dimensional adaptive moving mesh method and its application to hyperbolic conservation laws from magnetohydrodynamics (MHD). The method is robust, because it employs automatic control of mesh adaptation when a new model is considered, without manually-set

  10. Robust structural damage detection and localization based on joint approximate diagonalization technique in frequency domain (United States)

    Cao, Shancheng; Ouyang, Huajiang


    The structural characteristic deflection shapes (CDS’s) such as mode shapes and operational deflection shapes are highly sensitive to structural damage in beam- or plate-type structures. Nevertheless, they are vulnerable to measurement noise and could result in unacceptable identification errors. In order to increase the accuracy and noise robustness of damage identification based on CDS’s using vibration responses of random excitation, joint approximate diagonalization (JAD) technique and gapped smoothing method (GSM) are combined to form a sensitive and robust damage index (DI), which can simultaneously detect the existence of damage and localize its position. In addition, it is possible to apply this approach to damage identification of structures under ambient excitation. First, JAD method which is an essential technique of blind source separation is investigated to simultaneously diagonalize a set of power spectral density matrices corresponding to frequencies near a certain natural frequency to estimate a joint unitary diagonalizer. The columns of this joint diagonalizer contain dominant CDS’s. With the identified dominant CDS’s around different natural frequencies, GSM is used to extract damage features and a robust damage identification index is then proposed. Numerical and experimental examples of beams with cracks are used to verify the validity and noise robustness of JAD based CDS estimation and the proposed DI. Furthermore, damage identification using dominant CDS’s estimated by JAD method is demonstrated to be more accurate and noise robust than by the commonly used singular value decomposition method.

  11. Robustness Analysis of Gene Regulatory Networks (United States)

    Kadelka, Claus T.

    Cells generally manage to maintain stable phenotypes in the face of widely varying environmental conditions. This fact is particularly surprising since the key step of gene expression is fundamentally a stochastic process. Many hypotheses have been suggested to explain this robustness. First, the special topology of gene regulatory networks (GRNs) seems to be an important factor as they possess feedforward loops and certain other topological features much more frequently than expected. Second, genes often regulate each other in a canalizing fashion: there exists a dominance order amidst the regulators of a gene, which in silico leads to very robust phenotypes. Lastly, an entirely novel gene regulatory mechanism, discovered and studied during the last two decades, which is believed to play an important role in cancer, is shedding some light on how canalization may in fact take place as part of a cell's gene regulatory program. Short segments of single-stranded RNA, so-called microRNAs, which are embedded in several different types of feedforward loops, help smooth out noise and generate canalizing effects in gene regulation by overriding the effect of certain genes on others. Boolean networks and their multi-state extensions have been successfully used to model GRNs for many years. In this dissertation, GRNs are represented in the time- and state-discrete framework of Stochastic Discrete Dynamical Systems (SDDS), which captures the cell-inherent stochasticity. Each gene has finitely many different concentration levels and its concentration at the next time step is determined by a gene-specific update rule that depends on the current concentration of the gene's regulators. The update rules in published gene regulatory networks are often nested canalizing functions. In Chapter 2, this class of functions is introduced, generalized and analyzed with respect to its potential to confer robustness. Chapter 3 describes a simulation study, which supports the hypothesis that

  12. Robust surface roughness indices and morphological interpretation (United States)

    Trevisani, Sebastiano; Rocca, Michele


    Geostatistical-based image/surface texture indices based on variogram (Atkison and Lewis, 2000; Herzfeld and Higginson, 1996; Trevisani et al., 2012) and on its robust variant MAD (median absolute differences, Trevisani and Rocca, 2015) offer powerful tools for the analysis and interpretation of surface morphology (potentially not limited to solid earth). In particular, the proposed robust index (Trevisani and Rocca, 2015) with its implementation based on local kernels permits the derivation of a wide set of robust and customizable geomorphometric indices capable to outline specific aspects of surface texture. The stability of MAD in presence of signal noise and abrupt changes in spatial variability is well suited for the analysis of high-resolution digital terrain models. Moreover, the implementation of MAD by means of a pixel-centered perspective based on local kernels, with some analogies to the local binary pattern approach (Lucieer and Stein, 2005; Ojala et al., 2002), permits to create custom roughness indices capable to outline different aspects of surface roughness (Grohmann et al., 2011; Smith, 2015). In the proposed poster, some potentialities of the new indices in the context of geomorphometry and landscape analysis will be presented. At same time, challenges and future developments related to the proposed indices will be outlined. Atkinson, P.M., Lewis, P., 2000. Geostatistical classification for remote sensing: an introduction. Computers & Geosciences 26, 361-371. Grohmann, C.H., Smith, M.J., Riccomini, C., 2011. Multiscale Analysis of Topographic Surface Roughness in the Midland Valley, Scotland. IEEE Transactions on Geoscience and Remote Sensing 49, 1220-1213. Herzfeld, U.C., Higginson, C.A., 1996. Automated geostatistical seafloor classification - Principles, parameters, feature vectors, and discrimination criteria. Computers and Geosciences, 22 (1), pp. 35-52. Lucieer, A., Stein, A., 2005. Texture-based landform segmentation of LiDAR imagery

  13. Automatic analysis of multiparty meetings

    Indian Academy of Sciences (India)

    AMI) meeting corpus, the development of a meeting speech recognition system, and systems for the automatic segmentation, summarization and social processing of meetings, together with some example applications based on these systems.

  14. AVID: Automatic Visualization Interface Designer

    National Research Council Canada - National Science Library

    Chuah, Mei


    .... Automatic generation offers great flexibility in performing data and information analysis tasks, because new designs are generated on a case by case basis to suit current and changing future needs...

  15. Clothes Dryer Automatic Termination Evaluation

    Energy Technology Data Exchange (ETDEWEB)

    TeGrotenhuis, Ward E.


    Volume 2: Improved Sensor and Control Designs Many residential clothes dryers on the market today provide automatic cycles that are intended to stop when the clothes are dry, as determined by the final remaining moisture content (RMC). However, testing of automatic termination cycles has shown that many dryers are susceptible to over-drying of loads, leading to excess energy consumption. In particular, tests performed using the DOE Test Procedure in Appendix D2 of 10 CFR 430 subpart B have shown that as much as 62% of the energy used in a cycle may be from over-drying. Volume 1 of this report shows an average of 20% excess energy from over-drying when running automatic cycles with various load compositions and dryer settings. Consequently, improving automatic termination sensors and algorithms has the potential for substantial energy savings in the U.S.

  16. Is fMRI "noise" really noise? Resting state nuisance regressors remove variance with network structure. (United States)

    Bright, Molly G; Murphy, Kevin


    Noise correction is a critical step towards accurate mapping of resting state BOLD fMRI connectivity. Noise sources related to head motion or physiology are typically modelled by nuisance regressors, and a generalised linear model is applied to regress out the associated signal variance. In this study, we use independent component analysis (ICA) to characterise the data variance typically discarded in this pre-processing stage in a cohort of 12 healthy volunteers. The signal variance removed by 24, 12, 6, or only 3 head motion parameters demonstrated network structure typically associated with functional connectivity, and certain networks were discernable in the variance extracted by as few as 2 physiologic regressors. Simulated nuisance regressors, unrelated to the true data noise, also removed variance with network structure, indicating that any group of regressors that randomly sample variance may remove highly structured "signal" as well as "noise." Furthermore, to support this we demonstrate that random sampling of the original data variance continues to exhibit robust network structure, even when as few as 10% of the original volumes are considered. Finally, we examine the diminishing returns of increasing the number of nuisance regressors used in pre-processing, showing that excessive use of motion regressors may do little better than chance in removing variance within a functional network. It remains an open challenge to understand the balance between the benefits and confounds of noise correction using nuisance regressors. Copyright © 2015. Published by Elsevier Inc.

  17. Efficient and robust gradient enhanced Kriging emulators.

    Energy Technology Data Exchange (ETDEWEB)

    Dalbey, Keith R.


    %E2%80%9CNaive%E2%80%9D or straight-forward Kriging implementations can often perform poorly in practice. The relevant features of the robustly accurate and efficient Kriging and Gradient Enhanced Kriging (GEK) implementations in the DAKOTA software package are detailed herein. The principal contribution is a novel, effective, and efficient approach to handle ill-conditioning of GEK's %E2%80%9Ccorrelation%E2%80%9D matrix, RN%CC%83, based on a pivoted Cholesky factorization of Kriging's (not GEK's) correlation matrix, R, which is a small sub-matrix within GEK's RN%CC%83 matrix. The approach discards sample points/equations that contribute the least %E2%80%9Cnew%E2%80%9D information to RN%CC%83. Since these points contain the least new information, they are the ones which when discarded are both the easiest to predict and provide maximum improvement of RN%CC%83's conditioning. Prior to this work, handling ill-conditioned correlation matrices was a major, perhaps the principal, unsolved challenge necessary for robust and efficient GEK emulators. Numerical results demonstrate that GEK predictions can be significantly more accurate when GEK is allowed to discard points by the presented method. Numerical results also indicate that GEK can be used to break the curse of dimensionality by exploiting inexpensive derivatives (such as those provided by automatic differentiation or adjoint techniques), smoothness in the response being modeled, and adaptive sampling. Development of a suitable adaptive sampling algorithm was beyond the scope of this work; instead adaptive sampling was approximated by omitting the cost of samples discarded by the presented pivoted Cholesky approach.

  18. An automatic image recognition approach

    Directory of Open Access Journals (Sweden)

    Tudor Barbu


    Full Text Available Our paper focuses on the graphical analysis domain. We propose an automatic image recognition technique. This approach consists of two main pattern recognition steps. First, it performs an image feature extraction operation on an input image set, using statistical dispersion features. Then, an unsupervised classification process is performed on the previously obtained graphical feature vectors. An automatic region-growing based clustering procedure is proposed and utilized in the classification stage.

  19. Robust methods for data reduction

    CERN Document Server

    Farcomeni, Alessio


    Robust Methods for Data Reduction gives a non-technical overview of robust data reduction techniques, encouraging the use of these important and useful methods in practical applications. The main areas covered include principal components analysis, sparse principal component analysis, canonical correlation analysis, factor analysis, clustering, double clustering, and discriminant analysis.The first part of the book illustrates how dimension reduction techniques synthesize available information by reducing the dimensionality of the data. The second part focuses on cluster and discriminant analy

  20. Automatic measurement of the radioactive mercury uptake by the kidney

    International Nuclear Information System (INIS)

    Zurowski, S.; Raynaud, C.; CEA, 91 - Orsay


    An entirely automatic method to measure the Hg uptake by the kidney is proposed. The following operations are carried out in succession: measurement of extrarenal activity, demarcation of uptake areas, anatomical identification of uptake areas, separation of overlapping organ images and measurement of kidney depth. The first results thus calculated on 30 patients are very close to those obtained with a standard manual method and are highly encouraging. Two important points should be stressed: a broad demarcation of the uptake areas is necessary and an original method, that of standard errors, is useful for the background noise determination and uptake area demarcation. This automatic measurement technique is so designed that it can be applied to other special cases [fr