重复社会中的音乐及其解放——以阿达利《噪音:音乐的政治经济学》为中心

阿达利的《噪音:音乐的政治经济学》对音乐的政治经济学和意识形态属性做了较为深刻的说明。它采用历史性与建构性相结合的模式,将音乐的发展概括为牺牲、再现和重复三个阶段。其最重要的理论贡献在于揭示了重复阶段音乐的一致性这一根本属性,并提出了重复社会理论。重复社会除表现为集体的无差异性,还借由众声喧哗达到沉寂状态。最后,阿达利提出了作为破局之道的“作曲”。然而,《噪音》在研究范式方面有其局限,它没有实现音乐的形式—本体分析与社会—历史分析的有机结合。

噪音和权力——孔子音乐美学解读

文章结合贾克·阿达利的《噪音:音乐的政治经济学》的理论,从音乐人类学和政治学视角出发,重新观照孔子,从诗教即乐教、音乐即秩序、尽善尽美的审美理念、崇雅乐斥郑声的艺术评判四个方面展开论述,深入剖析孔子音乐美学的政治内核。

噪音,你等着吧

从小到大，我的烦恼数不胜数。但是，有一个烦恼却天天来烦我，它就是在我家门前的噪音。

A comparative study of the denoising methods of Thematic Mapper images for forest areas

The noises of remote sensing images, caused by imaging system and ground environment, negatively affect the accuracy and efficiency in extracting forest information from remote sensing images. The denoising is critical for image classifications for forest areas. The objective of this research is to assess the effectiveness of currently used spatial filtering methods for extracting with forest information related from Landsat 5 TM images. Five spatial filtering methods including low-pass filter, median filter, mean filter, sigma filter and enhanced self-adaptive filter were examined. A set of evaluation indices was designed to assess the ability of each denoising method for flatness, edge/boundary retention and enhancement. Based on the designed evaluation indices and visual assessment, it was found that sigma filter （D=1） and enhanced self-adaptive filter were the most effective denoising methods in classifying TM images for forest areas.

Whisper intelligibility enhancement based on noise robust feature and SVM

A machine learning based speech enhancement method is proposed to improve the intelligibility of whispered speech. A binary mask estimated by a two-class support vector machine （SVM） classifier is used to synthesize the enhanced whisper. A novel noise robust feature called Gammatone feature cosine coefficients （GFCCs） extracted by an auditory periphery model is derived and used for the binary mask estimation. The intelligibility performance of the proposed method is evaluated and compared with the traditional speech enhancement methods. Objective and subjective evaluation results indicate that the proposed method can effectively improve the intelligibility of whispered speech which is contaminated by noise. Compared with the power subtract algorithm and the log-MMSE algorithm, both of which do not improve the intelligibility in lower signal-to-noise ratio （SNR） environments, the proposed method has good performance in improving the intelligibility of noisy whisper. Additionally, the intelligibility of the enhanced whispered speech using the proposed method also outperforms that of the corresponding unprocessed noisy whispered speech.

SPEECH ENHANCEMENT METHOD FOR LPC AUTOREGRESSIVE MODEL AND SYSTEM IMPLEMENTATION OF COMMAND WORD RECOGNITION USED IN NOISY ENVIRONMENT

At present, almost all the systems and products for speech recognition are working in quiet environment and their performances are degraded or even can′t work when they are operated in high noisy environment. In this paper, after analyzing the features of speech and noise, a speech enhancement method for LPC autoregressive model for command words recognition used in noisy environment is proposed, and an experimental system is realized. In different background noisy environments, we conduct experiments about SNR, basic accuracy, noise resistant ability and system environment adaptability with different microphones. The experimental results show that the system has good recognition performance in high noisy environments. The system can resist many kinds of noises and meet the needs of application areas on the whole such as military, traffic, marketplace and factory etc.

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Seismic data denoising based on learning-type overcomplete dictionaries

The transform base function method is one of the most commonly used techniques for seismic denoising, which achieves the purpose of removing noise by utilizing the sparseness and separateness of seismic data in the transform base function domain. However, the effect is not satisfactory because it needs to pre-select a set of fixed transform-base functions and process the corresponding transform. In order to find a new approach, we introduce learning-type overcomplete dictionaries, i.e., optimally sparse data representation is achieved through learning and training driven by seismic modeling data, instead of using a single set of fixed transform bases. In this paper, we combine dictionary learning with total variation （TV） minimization to suppress pseudo-Gibbs artifacts and describe the effects of non-uniform dictionary sub-block scale on removing noises. Taking the discrete cosine transform and random noise as an example, we made comparisons between a single transform base, non-learning-type, overcomplete dictionary and a learning-type overcomplete dictionary and also compare the results with uniform and nonuniform size dictionary atoms. The results show that, when seismic data is represented sparsely using the learning-type overcomplete dictionary, noise is also removed and visibility and signal to noise ratio is markedly increased. We also compare the results with uniform and nonuniform size dictionary atoms, which demonstrate that a nonuniform dictionary atom is more suitable for seismic denoising.

Noise-reducing Capability of 13 Kinds of Colorleaf Plants in Rizhao

[Objective] This study aimed to explore the noise-reducing effect of different species of color-leaf trees and the correlation between structural characteristics of trees and relative amount of noise reduction.[Method] The noise-reducing capability of 13 kinds of color-leaf trees in Xincheng District,Rizhao City was determined with sound level meter（TES1353H）,leaf area meter（CI-202） and hand-held weather station.[Result] There were certain differences in noise-reducing capability among the 13 kinds of color-leaf trees,of which the reduction capability for A-level noise ranged from 0.25 to 1.17 d B/m with reduction rates in the range of 8.61%-29.26%.Cotinus coggygria showed the best noise-reducing effect,while Acer platanoictes showed the worst.The relative amount of noise reduction was positively related to the canopy characteristics of trees,and it was affected by leaf thickness and the first branch height.[Conclusion] This study will lay a theoretical foundation for correct understanding on noise-reducing capacity of color-leaf trees and relevant influencing factors,and provide certain reference for the selection of noise-reducing tree species.

Study of engine noise based on independent component analysis

Independent component analysis was applied to analyze the acoustic signals from diesel engine. First the basic prin-ciple of independent component analysis (ICA) was reviewed. Diesel engine acoustic signal was decomposed into several inde-pendent components (ICs); Fourier transform and continuous wavelet transform (CWT) were applied to analyze the independent components. Different noise sources of the diesel engine were separated, based on the characteristics of different component in time-frequency domain.

Cavity noise sensitivity analysis of tire contour design factors and application of contour optimization methodology

Cavity resonance noise of passenger car tires is generated by interacting excitation between a tire structure and the fill gas (air), and generally lies in a frequency range of 200?250 Hz. As such, this noise is strongly perceived and may be a serious source of driver annoyance. Thus, many studies regarding the cavity noise mechanism and its reduction have already been conducted. In this work, a vibro-acoustic coupled analysis was conducted between a tire structure and air cavity. Using this analysis, we can more accurately simulate the tire noise performance in the region of the cavity resonance frequency. An analysis of the effects of variation of tire contour design factors was conducted, using design-of-experiments methods. Finally, a multi-objective optimization was performed using in-house codes to reduce the cavity noise level while minimizing the loss of other performances, such as diminished ride comfort and handling caused by the variations of contour. As a result of this optimization, an optimized contour shape was derived, which satisfied the multi-objective performances.

The most homogeneous dip-scanning method using edgepreserving smoothing for seismic noise attenuation

Highlighting and analyzing the geological features of faults and fractures in seismic data is particularly important for hydrocarbon exploration and exploitation since they are often essential for finding and delineating reservoirs. We apply edge-preserving smoothing （EPS） to seismic processing and propose a most homogeneous dip-scanning method. The method preserves the geological features, eliminate random noise efficiently, obtain dip information, and improve the accuracy of identifying the oil and gas traps.

oncausal spatial prediction filtering based on an ARMA model

Conventional f-x prediction filtering methods are based on an autoregressive model. The error section is first computed as a source noise but is removed as additive noise to obtain the signal, which results in an assumption inconsistency before and after filtering. In this paper, an autoregressive, moving-average model is employed to avoid the model inconsistency. Based on the ARMA model, a noncasual prediction filter is computed and a self-deconvolved projection filter is used for estimating additive noise in order to suppress random noise. The 1-D ARMA model is also extended to the 2-D spatial domain, which is the basis for noncasual spatial prediction filtering for random noise attenuation on 3-D seismic data. Synthetic and field data processing indicate this method can suppress random noise more effectively and preserve the signal simultaneously and does much better than other conventional prediction filtering methods.

Virtual design and performance prediction of a silencing air cleaner used in an I.C.engine intake system

This paper reports results of the authors’ studies on the virtual design method used in the development of low noise intake system of I.C. engine. The resulting high pass-by noise at level above the legislative target at full throttle when engine speed was around 5200 r/min necessitated a BEM-aided redesign task, following the typical process of design and development of an intake system. During the initial design, based on the acoustic theory and the requirements (1. The air flux of the redesigned should equal to or exceed the value of the original flux; 2. The filtering area must not be degraded), and considering the constraint of space in the engine compartment, total volume and rough internal dimensions were determined. During the detailed design, the exact internal dimensions of the air cleaner were determined, and an effective method was applied to improve the acoustic performance at low frequency. The predicted sound power of the intake system indicated that the objective of reducing the overall engine noise by minimizing intake system noise was achieved.

Assessment of noise and ground vibration induced during blasting operations in an open pit mine——A case study on Ewekoro limestone quarry,Nigeria

Our study was carried out to assess the level of noise generated and ground vibrations induced during blasting operations at the Ewekoro limestone quarry in Nigeria.To achieve this objective,vibro monitor equipment was used to take readings related to noise generated and ground vibrations during all blasting operations that took place in the quarry for a period of one month.As well,a digital camera was used to take photographs of residential structures within villages near the quarry.The results obtained indicate that the ground vibration readings fall between 0.5 mm/s and 2.1 mm/s and the noise generated during the blasting operations between 82 dB and 89 dB.These readings when compared with the limits set by FEPA(Federal Environmental Protection Agency) of 5.0 mm/s and 150 dB) all fall within the permissible limits.However the photographs of most structures near the quarry reveal cracks and dilapidated building walls.Recommendations are made on how to sustain and improve current blasting techniques.

Eavesdropping on Quantum Secure Direct Communication with W State in Noisy Channel

Security of the quantum secure direct communication protocol （i.e., the C-S QSDC protocol） recently proposed by Cao and Song [Chin. Phys. Lett. 23 （2006） 290] is analyzed in the case of considerable quantum channel noise. The eavesdropping scheme is presented, which reveals that the C-S QSDC protocol is not secure if the quantum bit error rate （QBER） caused by quantum channel noise is higher than 4.17%. Our eavesdropping scheme induces about 4.17% QBER for those check qubits. However, such QBER can be hidden in the counterpart induced by the noisy quantum channel if the eavesdropper Eve replaces the original noisy channel by an ideal one. Furthermore, if the QBER induced by quantum channel noise is lower than 4.17%, then in the eavesdropping scheme Eve still can eavesdrop part of the secret messages by safely attacking a fraction of the transmitted qubits. Finally, an improvement on the C-S QSDC protocol is put forward.

Flow-induced Noise and Vibration Analysis of a Piping Elbow with/without a Guide Vane

The effect of a guide vane installed at the elbow on flow-induced noise and vibration is investigated in the range of Reynolds numbers from 1.70×10^5 to 6.81×10^5, and the position of guide vane is determined by publications. The turbulent flow in the piping elbow is simulated with large eddy simulation （LES）. Following this, a hybrid method of combining LES and Lighthill＇s acoustic analogy theory is used to simulate the hydrodynamic noise and sound sources are solved as volume sources in code Actran. In addition, the flow-induced vibration of the piping elbow is investigated based on a fluid-structure interaction （FSI） code. The LES results indicate that the range of vortex zone in the elbow without the guide vane is larger than the case with the guide vane, and the guide vane is effective in reducing flow-induced noise and vibration in the 90° piping elbow at different Reynolds numbers.

Reverse-time migration using multidirectional wavefield decomposition method

Reverse-time migration has attracted more and more attention owing to the advantages of high imaging accuracy, no dip restriction, and adaptation to complex velocity models. Cross-correlation imaging method is typically used in conventional reverse-time migration that produces images with strong low-frequency noise. Wavefield decomposition imaging can suppress such noise; however, some residual noise persists in the imaging results. We propose a 2D multidirectional wavefield decomposition method based on the traditional wavefield decomposition method. First, source wavefields and receiver wavefields are separated into eight subwavefields, respectively. Second, cross-correlation imaging is applied to selected subwavefields to produce subimages. Finally, the subimages are stacked to generate the final image. Numerical examples suggest that the proposed method can eliminate the low-frequency noise effectively and produce high-quality imaging profiles.

Subjective annoyance caused by indoor low-level and low frequency noise and control method

The influence of low_level noise has not been widely noticed. This paper discovered that low_level and low frequency noise(A_weighted equivalent level L eq <45 dB) causes higher probability of subjective annoyance. The fuzzy mathematic principle was applied to deal with the threshold level of subjective annoyance from noise in this study; there is preferable relationship between the indoor noise and noise annoyance at low frequency noise level. Study indicated at the same centered noise level, the change of annoyance probability is mainly caused by the change of the frequency spectrum characteristic of the indoor noise. Under low noise level environment, without change of the medium_low frequency noise, the slight increase of medium_high frequency noise level with the help of noise sheltering effect can significantly reduce the noise annoyance. This discovery brings a new resolution on how to improve the environmental quality of working or living places. A noise control model is given in this study according to the acoustic analysis.