1、外文资料翻译资料来源文章名：A unied framework for peak detection and alignment:application to HR-MAS 2D NMR spectroscopyAudio watermarking robust against D/A and A/D conversions书刊名： Signal,Image,Video Processing EURASIP Journal on Advances in Signal Processing作 者：Rumbach l 、j - p cot ArmspachShijun Xiang出版社：Sprin
2、ger，2011章 节：Volume7,Issue5页 码：pp. 833-842文 章 译 名： 峰值检测系统 姓 名： 学 号： 指导教师(职称)： 副教授 专 业： 自动化 班 级： 所 在 学 院： 文章一：A unied framework for peak detection and alignment:application to HR-MAS 2D NMR spectroscopy*Akram Belghith ? Christophe Collet ?Lucien Rumbach ? Jean-Paul ArmspachReceived: 18 March 2011 / Re
3、vised: 11 October 2011 / Accepted: 12 October 2011 / Published online: 30 October 2011?Springer-Verlag London Limited 2011*Abstract In this paper, we propose a new scheme to detect and align simultaneously peaks that correspond to differentmetabolites within a biopsy. The proposed peak detection and
4、 alignment scheme is based on the use of evidence theory,which is well suited to model uncertainty and imprecision characterizing the 2D NMR HR-MAS spectra. Consequently,we propose the coupling use of Bayesian and fuzzy set theories to model and quantify the imprecision degree, which isthen exploite
5、d to dene the mass function. We particularly show that our new mass function definition and the use of evi-dence theory for peak detection and alignment achieve consistently high performance compared to a Bayesian schemeon both synthetic and real spectra. The high quality of peak alignment precision
6、 reached by the use of evidence theoryallows us to efciently detect reliable biomarkers, which is an essential step for a better therapeutic and human com-plement system management in case of multiple sclerosis disease, cancer, etc.*KeywordsEvidence theory ? Fuzzy membership function ? Bayesian infe
7、rence ? HSQC HR-MAS 2D NMR ?Peak alignmentA. Belghith (B)? C. ColletUniversity of Strasbourg, LSIIT-CNRS UMR-7005,Strasbourg, Francee-mail: belghithunistra.frC. Collete-mail: c.colletunistra.frL. Rumbach ? J.-P. ArmspachUniversity of Strasbourg, LINC-CNRS UMR-7237,Strasbourg, Francee-mail: lucien.ru
8、mbachunistra.frJ.-P. Armspache-mail: jparmspachunistra.frIntroductionIn the last decade, cancer has become the leading cause of death for people under the age of 85 1. According to theAmerican Cancer Society, a total of 1,479,350 cancer casesand 562,340 deaths from cancer were occurred in the United
9、States in 2009 1. Generally, tumors are identied according to histological features characteristic of the assumed cellof origin. Nevertheless, diagnosis is frequently controversial since tumors do not follow classic histology enabling path-ological diagnosis to be established. Therefore, an objectiv
10、e diagnostic approach that identies informative cancerbiomarkers is needed to improve the tumor identication accuracy.NMR spectroscopy can be used to provide statistically differentiable molecular biomarkers for tumor identication 2.Indeed, NMR offers the potential to study molecular structures and
11、their associations and interactions. To remove thespectral line broadening resulting from chemical shift anisotropy in the NMR spectroscopy, the High Resolution MagicAngle Spinning (HR-MAS) NMR was developed 3. 2D1H13C Heteronuclear Single Quantum Coherence (HSQC)NMR spectra is widely used in metabo
12、lic studies. Indeed,almost metabolites contain carbon and hydrogen, and theaddition of a second dimension (13C or1H) improves the resolution and enables the identication of a large numberof metabolites that are not resolvable in a standard 1D1H or1D13C NMR spectrum. Nevertheless, this spectrum analy
13、sisrequires new image processing tools able to detect the presence of different metabolites in a 2D new framework. Suchtools need to be unsupervised to help medical diagnosis.The analysis of metabolite proling requires comparison of metabolite proles obtained from multiple replicates ofsamples expos
14、ed to different experimental conditions. What adds difculty to automating this analysis process is that eachopeak a given metabolite can be shifted slightly from one sample to the next. The primary causes of chemical shift inpeak positions are variations in the pH and the temperature of the sample 4
15、.Many peak alignment methods have been used to solve problems of 1D NMR spectroscopy 4 such as the pointmatching 5 and the Beam search 6. Nevertheless, due to the complexity and the insufcient prior knowledge on theNMR HR-MAS spectra, these methods are no more effective and to this end, a new method
16、 of peak alignment wasproposed in 4. It consists in the extraction of all metabolites and then measures the similarity between peaks fromdifferent spectra based on an objective function. However,although this method is successfully applied to 2D NMR, itsuse is constrained by specic prerequisites (e.
17、g., it requires the identication and the extraction of all peaks for the align-ment algorithm, which are not always available in the highly complex spectra such as HSQC spectrum).In this paper, we propose a new method able to simultaneously detect and align different peaks. In this approach,each pea
18、k is parameterized by its position and its shape.These characteristics that are theoretically invariable for thesame metabolite are in practice corrupted by a variation of the position and shape. In fact, it corresponds to an impre-cision, which is added to the spectra in practice. We will model thi
19、s imprecision and the uncertainty always presenton the observed HR-MAS 2D data so as to obtain optimal peak alignment results.Two notions of uncertainty and imprecision are distinct,and they must be now clearly dened 7. On the one hand,the uncertainty presents the belief or the doubt we have on*the
20、existence or on the validity of the data. This uncertainty comes from the reliability or the unreliability of the observation made by the system: This observation can be uncertain or erroneous 8,9. On the other hand, when we have not enough knowledge on the data, we describe it with vague terms but
21、its realization is sure: In this case, we speak about imprecision. This phenomenon is due to sensor imperfection where data acquisition process is always corrupted and leads to an error associated with every measurements.In order to take into account both imprecision and uncertainty of the spectra,
22、we propose the use of the evidence the-ory, which can be well suited to deal with raw data. Moreover,this theory offers combination tools to merge data issued from sources (sseveral pectra exposed to different experimental conditions) while taking into account their compleminterity,they redundency a
23、nd they possible opposition (conict information).Evidential peak alignment scheme proposed in this paper is also based on the fuzzy set theory 10,11 to model and quantify the imprecision degree presented in the spectra. In particular we show that this modeling, used in the mass function definition,
24、increases the performance of the alignment scheme in comparison with the Bayesian scheme This paper is organized as follows: In the next section, the analytical model of a 2D-NMR spectroscopy image formation is exposed. In Sect. 3, we model the imprecision degree present in the spectra by dening thr
25、ee main hypotheses required for imprecision quantication. In Sect. 4, we present the peak alignment scheme based on the imprecision degree previously dened. In Sect. 5, we develop the hyperparam eter estimation procedure. Finally, in Sect. 6, some results obtained from synthetic and real spectra are
26、 presented and we show, in particular, the robustness and the efciency of this novel proposed approach in comparison with a Bayesian scheme2.ConclusionIn this paper, we proposed a new evidential peak detection and alignment scheme. This method combines the modelingof the knowledge through the eviden
27、ce theory and the quantication of the imprecision degree through the fuzzy theory.The handling of both imprecision and uncertainty by the evidence theory increased the robustness of the proposed align-ment scheme compared to the Bayesian scheme. In addition,we have used the deconvolution model to ac
28、hieve a better tof the HSQC spectrum and the multivariate Gaussian distribution to model the noise correlation. The synthetic valida-tion of the proposed approach has shown its features such as its robustness to the high level of noise, one of the delicateissues in HSQC spectra and its ability to al
29、ign peaks even if they are inseparable manually. This method was validated onreal spectra with the collaboration of NMR experts.*Acknowledgments The authors would like to thank the Region Alsace and ARSEP for support of this research project and Mr.cde Chimie University of strasbourg and Dr Izzie Ja
30、cque Namer 文 章 二 ： Audio watermarking robust against D/A and A/D conversionsEURASIP Journal on Advances in Signal Processing Xiang; licensee Springer. 2011This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http:/creativecommons.org/licenses/by/2.0
31、), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.10.1186/1687-2011-3Shijun Xiang1, 2 (1)School of Information Science and Technology,Jinan Universety,Guangzhou,China (2)State Key Laboratory of Information Security (Institut
32、e of Software, Chinese Academy of Sciences), Beijing, China Shijun XiangEmail: Received: 10 November 2010Accepted: 13 May 2011Published online: 13 May 2011AbstractDigital audio watermarking robust against digital-to-analog (D/A) and analog-to-digital (A/D) conversions is an important issue. In a num
33、ber of watermark application scenarios, D/A and A/D conversions are involved. In this article, we first investigate the degradation due to DA/AD conversions via sound cards, which can be decomposed into volume change, additional noise, and time-scale modification (TSM). Then, we propose a solution f
34、or DA/AD conversions by considering the effect of the volume change, additional noise and TSM. For the volume change, we introduce relation-based watermarking method by modifying groups of the energy relation of three adjacent DWT coefficient sections. For the additional noise, we pick up the lowest
35、-frequency coefficients for watermarking. For the TSM, the synchronization technique (with synchronization codes and an interpolation processing operation) is exploited. Simulation tests show the proposed audio watermarking algorithm provides a satisfactory performance to DA/AD conversions and those
36、 common audio processing manipulations.Audio watermarking D/A and A/D conversions Synchronization Magnitude distortion Time scaling Wavelet transformIntroductionWith the development of the Internet, illegal copying of digital audio has become more widespread. As a traditional data protection method,
37、 encryption cannot be applied in that the content must be played back in the original style. There is a potential solution to the problem that is to mark the audio signal with an imperceptible and robust watermark 1-3.In the past 10 years, attacks against audio watermarking are becoming more and mor
38、e complicated with the development of watermarking technique. According to International Federation of the Phonographic Industry (IFPI) 4, in a desired audio watermarking system, the watermark should be robust to content-preserving attacks including desynchronization attacks and audio processing ope
39、rations. From the audio watermarking point of view, desynchronizaiton attacks (such as cropping and time-scale modification) mainly introduce synchronization problems between encoder and decoder. The watermark is still present, but the detector is no longer able to extract it. Different from desynch
40、ronization attacks, audio processing operations (including requantization, the addition of noises, MP3 lossy compression, and low-pass filtering operations) do not cause synchronization problems, but will reduce the watermark energy.The problem of audio watermarking against common audio processing o
41、perations can be solved by embedding the watermark in the frequency domain instead of in the time domain. The time domain-based solutions (such as LSB schemes 5 and echo hiding 6) usually have a low computational cost but somewhat sensitive to additive noises, while the frequency domain watermarking
42、 methods provide a satisfactory resistance to audio processing operations by watermarking low-frequency component of the signal. There are three dominant frequency domain watermarking methods: Discrete Fourier Transform (DFT) based 7, 8, Discrete Wavelet Transform (DWT) based 9, 10, and Discrete Cos
43、ine Transform (DCT) based 11. They have shown satisfactory robustness performance to MP3 lossy compression, additive noise and low-pass filtering operations.In the literature, there are a few algorithms aiming at solving desynchronization attacks. For cropping (such as editing, signal interruption i
44、n wireless transmission, and data packet loss in IP network), researchers repeatedly embedded a template into different regions of the signal 9-13, such as synchronization code-based self synchronization methods 9-11 and the use of multiple redundant watermarks 14, 15. Though the template based wate
45、rmarking can combat cropping but cannot cope with TSM operations, even for the scaling amount of 1%. In the audio watermarking community, there exist some TSM-resilient watermarking strategies, such as peak points based 16-18 and recently reported histogram based 19, 20. In 16, a bit can be hidden b
46、y quantizing the length of each two adjacent peak points. In 17, the watermark was repeatedly embedded into the edges of an audio signal by viewing pitch-invariant TSM as a special form of random cropping, removing and adding some portions of the audio signal while preserving the pitch. In 18, the i
47、nvariance of dyadic wavelet transform to linear scaling was exploited to design audio watermarking by modulating the wave shape. The three dominant peak point-based watermarking methods are resistant to TSM because the peaks can still be detected before and after a TSM operation. The histogram-based
48、 methods 19, 20 are robust to TSM operations because the shape of histogram of an audio signal is provably invariant to temporal linear scaling. In addition, the histogram is independent of a samples position in the time domain.We can see that the above existing audio watermarking algorithms only consider the watermark attacks in the digital environment. The effect of the analog transmission channel via DA/AD conversions is little mentioned. Toward this direction, in this ar
