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SUBSPACE GAUSSIAN MIXTURE MODEL FOR COMPUTER-ASSISTED LANGUAGE LEARNING

SUBSPACE GAUSSIAN MIXTURE MODEL FOR COMPUTER-ASSISTED LANGUA...

引用

IEEE International conference on Acoustics, Speech and signal processing

作者： Rong Tong Boon Pang Lim Nancy F. Chen Bin Ma Haizhou Li Institute for Infocomm Research Singapore

ISBN: (纸本)9781479928941

In computer-assisted language learning (CALL), speech data from non-native speakers are usually insufficient for acoustic modeling. Subspace Gaussian Mixture Models (SGMM) have been effective in training automatic speech recognition (ASR) systems with limited amounts of training data. Therefore, in this work, we propose to use SGMM to improve the fluency assessment performance. In particular, the contributions of this work are: (i) The proposed SGMM acoustic model trained with native data outperforms the MMI-GMM/HMM baseline by 25% relative, (ii) when incorporating a small amount of non-native training data, the SGMM acoustic model further improves the performance of fluency assessment by 47% relative.

关键词： Acoustic models Gauss Speech recognition Verbal Fluency Training data Introduced species Language Development acoustic modeling CHL1 gene

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Copyright protection in named data networking

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International conference on Wireless Communications and signal processing (WCSP)

作者： Xiaobin Tan Zifei Zhou Cliff Zou Yukun Niu Xin Chen CAS Key Laboratory of Technology in Geo-spatial Information Processing and Application System University of Science and Technology of China China Department of Electrical Engineering and Computer Science University of Central Florida USA

As a new Internet architecture, Named data Networking (NDN) decouples location from the data itself to achieve security, scalability, and mobility. Although router-side data caching used in NDN reduces data acquisition delay, it introduces a new copyright protection challenge: how to prevent unauthorized users to retrieve data cached in routers that are out of the control of its publisher? Current approaches that rely on a common encryption key among authorized users cannot protect copyright well since if one authorized user secretly leaks the key, we cannot tell who has leaked the key out. In this paper, we present a split-based scheme to solve this copyright protection problem for large-sized data. The data is split into a large part that could be cached in routers for all users to retrieve, and a small part that is unique for each authorized user. This scheme exploits the fact that in the bit-wise OR operation, both bit 0 and bit 1 can OR with 1 to generate the same result of bit 1. The analysis of our scheme shows that it has a good performance in terms of copyright protection, data retrieval efficiency, and overhead.

关键词： Copyright protection Encryption Watermarking Internet Computer architecture Receivers

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Assessing the risk induced by sloshing using Generalized Pareto distributions

Assessing the risk induced by sloshing using Generalized Par...

引用

24th International Ocean and Polar Engineering conference, ISOPE 2014 Busan

作者： Dematteo, A. Gervaise, E. Liquid Motion Department Saint-Rémy-lès-Chevreuse France Télécom Paristech Signal and Image Processing Department Paris France

ISBN: (纸本)9781880653913

GTT (GazTransport & Technigaz) studies sloshing pressure loads within the tanks of LNG carriers by means of small-scale tanks (1:40) instrumented with arrays of pressure sensors. Several sea conditions, likely to be met by the vessels, are tested. The risk induced by sloshing is then assessed with an in-house methodology relying on Weibull distributions. These distributions have been proven to be efficient for reliability purposes on a large variety of data sets on various fields. However, the focus of risk assessment is on the largest observations recorded by the sensors. The Extreme Value Theory suggests Generalized Pareto (GP) distributions may describe accurately the extremal behaviour of such measurements. Nevertheless, reliability methods based on GP distributions are difficult to carry out in practice due to a large sensitivity to the estimation of the tail index γ. In addition, the estimation of γ itself depends overwhelmingly on the setting of a threshold value used to discriminate between extreme and non extreme observations. It is the objective of this paper to investigate if GP distributions could be implemented for the risk assessment in the LNG shipping industry in spite of the inherent caveat. Using several simulation procedures, we show the influence of a misestimation of γ. Copyright © 2014 by the International Society of Offshore and Polar Engineers (ISOPE).

关键词： Weibull distribution

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Circular target detection algorithm on satellite images based on radial transformation

Circular target detection algorithm on satellite images base...

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IEEE signal processing and Communications Applications (SIU)

作者： Emin Zerman Emrecan Batı Gözde Bozdağı Akar Emre Başeski Şebnem Düzgün Elektrik ve Elektronik Mühendisliği Bölümü Orta Doğu Teknik Üniversitesi Ankara Türkiye HAVELSAN A.Ş Ankara Türkiye Maden Mühendisliği Bölümü Orta Doğu Teknik Üniversitesi Ankara Türkiye

Remote sensing is used in a spreading manner by many governmental and industrial institutions worldwide in recent years. Target detection has an important place among the applications developed using satellite imagery. In this paper, an original circular target detection algorithm has been proposed based on a radial transformation. The algorithm consists of three stages such as pre-processing, target detection, and postprocessing. In the pre-processing stage, bilateral noise reduction filtering and vegetation detection operations are completed which they are required by target detection step. The target detection stage finds the circular target by a radial transformation algorithm and variables obtained from the training, and postprocessing stage carries out the elimination of falsely detected targets by utilizing the vegetation information. The Petroleum Oil Lubricants (POL) depots in the industrial areas and harbors have been chosen as an application area of the proposed algorithm. The algorithm has been trained and tested on a data set which includes 4-band images with Near-Infrared band. Proposed algorithm is able to detect many circular targets with different types and sizes as a consequence of using a full radial transformation search as well as it gives rewarding results on industrial areas and harbors in the experiments conducted.

关键词： conferences Petroleum signal processing Object detection Satellites Remote sensing Lubricants

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AN EFFICIENT MOTION VECTOR PREDICTION METHOD FOR AVOIDING AMVP data DEPENDENCY FOR HEVC

AN EFFICIENT MOTION VECTOR PREDICTION METHOD FOR AVOIDING AM...

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IEEE International conference on Acoustics, Speech and signal processing

作者： Gwo-Long Li Chuen-Ching Wang Kuang-Hung Chiang Dept. of Video Coding Core Technology Industrial Technology Research Institute Taiwan Dept. of Information Technology Kao Yuan University Taiwan Dept. of Computer Science and Information Engineering National Central University Taiwan

ISBN: (纸本)9781479928941

To achieve higher coding efficiency, the latest video coding standard called High Efficiency Video Coding (HEVC) has adopted the mechanism of Advanced Motion Vector Prediction (AMVP) to further improve the accuracy of motion vector predictor. However, the adoption of AMVP significantly increases the hardware realization overhead as well as the data access bandwidth requirements. In addition, the dependency between different coding units (CUs) or prediction units (PUs) for predicting AMVP also noticeably degrades the overall hardware coding throughput. To deal with this problem, this paper proposes an efficient motion vector prediction method for avoiding AMVP data dependency. By modeling the relationship between motion vector predictors of largest coding unit (LCU) and other small CU and PU sizes, the motion vectors of small CUs and PUs are estimated directly from the motion vectors of LCU. Furthermore, the predicted motion vectors of small CUs and PUs are also used to pre-fetch the corresponding reference data from external memory in advanced so that the data access time can be hided. Simulation results demonstrate that the proposed motion vector prediction method can achieve at least 53.8% coding throughput improvement with only 1.04% BD-rate increasing when compared to direct AMVP realization.

关键词： Vectors Encoding Video coding Hardware Throughput Predictive models

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ATALA: Accelerator of TRLs for algorithms & advanced processing: Application to ground radars

ATALA: Accelerator of TRLs for algorithms & advanced process...

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IEEE International conference on Radar

作者： Frederic Barbaresco Nicolas Millet Mathieu Klein Patrick Bruchec Alexis Decurninge François-Xavier Archambault Nicolas Ferrandez François Giersch Rémi Peyregne Jean-Paul Guyvarch Surface Radar THALES AIR SYSTEMS Limours France

ATALA objective is to break TRL4/5 Wall to speed up insertion of innovative algorithms in Radar Sensors Products. ATALA is also a derisking tool for Engineering Teams & Customers. We will illustrate validation of ATALA with 2 Use-Cases results: monitoring of commercial aircraft wake-vortex, detection of small/slow synthetic targets on relevant clutter environment. ATALA is based on two main principles: SDR4U (Software Defined Radar for You), PAR4U (Automatic Parallelization for You).

关键词： MATLAB Real-time systems Clutter Radar applications Software algorithms signal processing algorithms

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Gene expression profiling by estimating parameters of gene regulatory network using meta-heuristics: A comparative study

Gene expression profiling by estimating parameters of gene r...

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International conference on signal processing and Integrated Networks (SPIN)

作者： Surama Biswas Sriyankar Acharyya Computer Science and Engineering West Bengal University of Technology Kolkata India

Genes are present in the nucleus of every cell in an organism. Genes, metabolites, proteins and other by-products of cellular activity form a signaling pathway or network which is called a Gene Regulatory Network. Computational reconstruction of the network may uncover potential genetic causes of diseases and may aid drug detection. Advancements in biotechnology and image processing tools have made time series gene expression data available to researchers of computational biology. Reconstruction of Gene Regulatory Network has found a new direction with the availability of this data. After being processed by different statistical methods, the time series data may be considered as a matrix with each row representing a gene and each column representing a time point. The data suffers from an insufficiency of number of columns in relation to number of rows. This makes the reconstruction process more tedious. The problem is known as Curse of Dimensionality problem. The methods which are described here take processed microarray gene expression data as the input and produce the simulated gene expression time series with larger number of columns having regular small intervals. Gene Regulatory Network is reconstructed in the framework of Recurrent Neural Network. The parameters of the network are iteratively optimized using efficient local search optimization algorithms, namely two variants of Simulated Annealing and Tabu Search. The optimized parameters are used for the comparative study between the three methods in producing the time behavior or expression profiles of the genes. For almost all genes, the simulated profiles closely correspond to the original profiles.

关键词： Time series analysis signal processing algorithms Simulated annealing Mathematical model Proteins Gene expression signal processing

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Assessment of statistical-based clutter reduction techniques on ground-coupled GPR data for the detection of buried objects in soils

Assessment of statistical-based clutter reduction techniques...

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Proceedings of the International conference on Ground Penetrating Radar, GPR

作者： E. Tebchrany F. Sagnard V. Baltazart J-P. Tarel X. Dérobert IFSTTAR Champs-sur-Marne France

A bi-static Ground Penetrating Radar (GPR) has been developed for the detection of cracks and buried pipes in urban grounds. It is made of two shielded Ultra Wide Band (UWB) bowtie-slot antennas operating in the frequency band [0.3;4] GHz. GPR signals contain not only responses of targets, but also unwanted effects from antenna coupling in air and in the soil, system ringing, and soil reflections that can mask the proper detection of useful information. Thus, it appears necessary to propose and assess several clutter reduction techniques as pre-processing techniques to improve the signal-to-noise ratio, discriminate overlapping responses issued from the targets and the clutter, and ease the use of data processing algorithms for target detection, identification or reconstruction. In this work, we have evaluated on Bscan profiles three different statistical data analysis such as mean subtraction, Principal Component Analysis (PCA), and Independent Component Analysis (ICA) considering a shallow and a medium depth target. The receiver operating characteristics (ROC) graph has allowed to evaluate the performance of each data processing in simulations and measurements to further draw a comparison in order to select the technique most adapted to a given soil structure with its radar probing system.

关键词： Ground penetrating radar Diffraction Radar detection Radar measurements Frequency estimation

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Normalized residual-based outlier detection

Normalized residual-based outlier detection

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IEEE International conference on signal processing, Communications and Computing (ICSPCC)

作者： Xiaohu Ru Zheng Liu Wenli Jiang College of Electronic Science and Engineering National University of Defense Technology Changsha Hunan CN

Outlier detection is an important issue in data mining and knowledge discovery. The aim is to find the patterns that deviate too much from others. In this paper, a universal outlier detection method based on normalized residual is proposed. Different from previous methods, the residual of a pattern is calculated corresponding to its nearest normal patterns, so that the interaction between outliers is eliminated. To implement this, the method first estimates the center of normal patterns and derives the initial set of them, and then iteratively calculates the residual of the nearest pattern outside the set. Those with small residuals will be added to the set of normal patterns, and others are picked out as outliers. An effective distance weighting is also introduced to the calculation of the normalized residual. Simulation results show that the proposed method is efficient in detecting outliers and can hold a high detection probability even when 30% outliers appear in the dataset.

关键词： data mining Computational modeling Vectors Runtime Educational institutions Knowledge discovery

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10th International conference on Simulated Evolution and Learning, SEAL 2014

10th International Conference on Simulated Evolution and Lea...

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10th International conference on Simulated Evolution and Learning, SEAL 2014

ISBN: (纸本)9783319135625

The proceedings contain 71 papers. The special focus in this conference is on Simulated Evolution and Learning. The topics include: Solving dynamic optimisation problem with variable dimensions;a probabilistic evolutionary optimization approach to compute quasiparticle braids;adaptive system design by a simultaneous evolution of morphology and information processing;generating software test data by particle swarm optimization;a steady-state genetic algorithm for the dominating tree problem;evolution of developmental timing for solving hierarchically dependent deceptive problems;the introduction of asymmetry on traditional 2-parent crossover operators for crowding and its effects;the performance effects of interaction frequency in parallel cooperative coevolution;customized selection in estimation of distribution algorithms;a hybrid GP-tabu approach to QoS-aware data intensive web service composition;a modified screening estimation of distribution algorithm for large-scale continuous optimization;clustering problems for more useful benchmarking of optimization algorithms;fuzzy clustering with fitness predator optimizer for multivariate data problems;effects of mutation and crossover operators in the optimization of traffic signal parameters;a GP approach to QoS -aware web service composition and selection;user preferences for approximation-guided multi-objective evolution;multi-objective optimisation, software effort estimation and linear models;adaptive update range of solutions in MOEA/D for multi and many-objective optimization;classification of lumbar ultrasound images with machine learning;schemata bandits for binary encoded combinatorial optimisation problems;anomaly detection using replicator neural networks trained on examples of one class and genetic programming for multiclass texture classification using a small number of instances.

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