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Academic literature on the topic 'NOISEX database'

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Published: 6 September 2023

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Journal articles on the topic "NOISEX database"

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Zhang, Yan, Zhen-min Tang, Yan-ping Li, and Yang Luo. "A Hierarchical Framework Approach for Voice Activity Detection and Speech Enhancement." Scientific World Journal 2014 (2014): 1–8. http://dx.doi.org/10.1155/2014/723643.

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Accurate and effective voice activity detection (VAD) is a fundamental step for robust speech or speaker recognition. In this study, we proposed a hierarchical framework approach for VAD and speech enhancement. The modified Wiener filter (MWF) approach is utilized for noise reduction in the speech enhancement block. For the feature selection and voting block, several discriminating features were employed in a voting paradigm for the consideration of reliability and discriminative power. Effectiveness of the proposed approach is compared and evaluated to other VAD techniques by using two well-known databases, namely, TIMIT database and NOISEX-92 database. Experimental results show that the proposed method performs well under a variety of noisy conditions.
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Qi, Yingmei, Heming Huang, and Huiyun Zhang. "Research on Speech Emotion Recognition Method Based A-CapsNet." Applied Sciences 12, no. 24 (December 17, 2022): 12983. http://dx.doi.org/10.3390/app122412983.

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Speech emotion recognition is a crucial work direction in speech recognition. To increase the performance of speech emotion detection, researchers have worked relentlessly to improve data augmentation, feature extraction, and pattern formation. To address the concerns of limited speech data resources and model training overfitting, A-CapsNet, a neural network model based on data augmentation methodologies, is proposed in this research. In order to solve the issue of data scarcity and achieve the goal of data augmentation, the noise from the Noisex-92 database is first combined with four different data division methods (emotion-independent random-division, emotion-dependent random-division, emotion-independent cross-validation and emotion-dependent cross-validation methods, abbreviated as EIRD, EDRD, EICV and EDCV, respectively). The database EMODB is then used to analyze and compare the performance of the model proposed in this paper under different signal-to-noise ratios, and the results show that the proposed model and data augmentation are effective.
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FAROOQ, O., S. DATTA, and M. C. SHROTRIYA. "WAVELET SUB-BAND BASED TEMPORAL FEATURES FOR ROBUST HINDI PHONEME RECOGNITION." International Journal of Wavelets, Multiresolution and Information Processing 08, no. 06 (November 2010): 847–59. http://dx.doi.org/10.1142/s0219691310003845.

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This paper proposes the use of wavelet transform-based feature extraction technique for Hindi speech recognition application. The new proposed features take into account temporal as well as frequency band energy variations for the task of Hindi phoneme recognition. The recognition performance achieved by the proposed features is compared with the standard MFCC and 24-band admissible wavelet packet-based features using a linear discriminant function based classifier. To evaluate robustness of these features, the NOISEX database is used to add different types of noise into phonemes to achieve signal-to-noise ratios in the range of 20 dB to -5 dB. The recognition results show that under noisy background the proposed technique always achieves a better performance over MFCC-based features.
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Rudramurthy, M. S., V. Kamakshi Prasad, and R. Kumaraswamy. "Speaker Verification Under Degraded Conditions Using Empirical Mode Decomposition Based Voice Activity Detection Algorithm." Journal of Intelligent Systems 23, no. 4 (December 1, 2014): 359–78. http://dx.doi.org/10.1515/jisys-2013-0085.

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AbstractThe performance of most of the state-of-the-art speaker recognition (SR) systems deteriorates under degraded conditions, owing to mismatch between the training and testing sessions. This study focuses on the front end of the speaker verification (SV) system to reduce the mismatch between training and testing. An adaptive voice activity detection (VAD) algorithm using zero-frequency filter assisted peaking resonator (ZFFPR) was integrated into the front end of the SV system. The performance of this proposed SV system was studied under degraded conditions with 50 selected speakers from the NIST 2003 database. The degraded condition was simulated by adding different types of noises to the original speech utterances. The different types of noises were chosen from the NOISEX-92 database to simulate degraded conditions at signal-to-noise ratio levels from 0 to 20 dB. In this study, widely used 39-dimension Mel frequency cepstral coefficient (MFCC; i.e., 13-dimension MFCCs augmented with 13-dimension velocity and 13-dimension acceleration coefficients) features were used, and Gaussian mixture model–universal background model was used for speaker modeling. The proposed system’s performance was studied against the energy-based VAD used as the front end of the SV system. The proposed SV system showed some encouraging results when EMD-based VAD was used at its front end.
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Yang, Jie. "Combining Speech Enhancement and Cepstral Mean Normalization for LPC Cepstral Coefficients." Key Engineering Materials 474-476 (April 2011): 349–54. http://dx.doi.org/10.4028/www.scientific.net/kem.474-476.349.

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A mismatch between the training and testing in noisy circumstance often causes a drastic decrease in the performance of speech recognition system. The robust feature coefficients might suppress this sensitivity of mismatch during the recognition stage. In this paper, we investigate the noise robustness of LPC Cepstral Coefficients (LPCC) by using speech enhancement with feature post-processing. At front-end, speech enhancement in the wavelet domain is used to remove noise components from noisy signals. This enhanced processing adopts the combination of discrete wavelet transform (DWT), wavelet packet decomposition (WPD), multi-thresholds processing etc to obtain the estimated speech. The feature post-processing employs cepstral mean normalization (CMN) to compensate the signal distortion and residual noise of enhanced signals in the cepstral domain. The performance of digit speech recognition systems is evaluated under noisy environments based on NOISEX-92 database. The experimental results show that the presented method exhibits performance improvements in the adverse noise environment compared with the previous features.
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Upadhyaya, Prashant, Omar Farooq, M. R. Abidi, and Priyanka Varshney. "Comparative Study of Visual Feature for Bimodal Hindi Speech Recognition." Archives of Acoustics 40, no. 4 (December 1, 2015): 609–19. http://dx.doi.org/10.1515/aoa-2015-0061.

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Abstract In building speech recognition based applications, robustness to different noisy background condition is an important challenge. In this paper bimodal approach is proposed to improve the robustness of Hindi speech recognition system. Also an importance of different types of visual features is studied for audio visual automatic speech recognition (AVASR) system under diverse noisy audio conditions. Four sets of visual feature based on Two-Dimensional Discrete Cosine Transform feature (2D-DCT), Principal Component Analysis (PCA), Two-Dimensional Discrete Wavelet Transform followed by DCT (2D-DWT- DCT) and Two-Dimensional Discrete Wavelet Transform followed by PCA (2D-DWT-PCA) are reported. The audio features are extracted using Mel Frequency Cepstral coefficients (MFCC) followed by static and dynamic feature. Overall, 48 features, i.e. 39 audio features and 9 visual features are used for measuring the performance of the AVASR system. Also, the performance of the AVASR using noisy speech signal generated by using NOISEX database is evaluated for different Signal to Noise ratio (SNR: 30 dB to −10 dB) using Aligarh Muslim University Audio Visual (AMUAV) Hindi corpus. AMUAV corpus is Hindi continuous speech high quality audio visual databases of Hindi sentences spoken by different subjects.
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Varga, Andrew, and Herman J. M. Steeneken. "Assessment for automatic speech recognition: II. NOISEX-92: A database and an experiment to study the effect of additive noise on speech recognition systems." Speech Communication 12, no. 3 (July 1993): 247–51. http://dx.doi.org/10.1016/0167-6393(93)90095-3.

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Yang, Ren Di, and Yan Li Zhang. "Denoising of ECG Signal Based on Empirical Mode Decomposition and Adaptive Noise Cancellation." Applied Mechanics and Materials 40-41 (November 2010): 140–45. http://dx.doi.org/10.4028/www.scientific.net/amm.40-41.140.

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To remove the noises in ECG and to overcome the disadvantage of the denoising method only based on empirical mode decomposition (EMD), a combination of EMD and adaptive noise cancellation is introduced in this paper. The noisy ECG signals are firstly decomposed into intrinsic mode functions (IMFs) by EMD. Then the IMFs corresponding to noises are used to reconstruct signal. The reconstructed signal as the reference input of adaptive noise cancellation and the noisy ECG as the basic input, the de-noised ECG signal is obtained after adaptive filtering. The de-noised ECG has high signal-to-noise ratio, preferable correlation coefficient and lower mean square error. Through analyzing these performance parameters and testing the denoising method using MIT-BIH Database, the conclusion can be drawn that the combination of EMD and adaptive noise cancellation has considered the frequency distribution of ECG and noises, eliminate the noises effectively and need not to select a proper threshold.
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Ataeyan, Mahdieh, and Negin Daneshpour. "Automated Noise Detection in a Database Based on a Combined Method." Statistics, Optimization & Information Computing 9, no. 3 (June 9, 2021): 665–80. http://dx.doi.org/10.19139/soic-2310-5070-879.

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Data quality has diverse dimensions, from which accuracy is the most important one. Data cleaning is one of the preprocessing steps in data mining which consists of detecting errors and repairing them. Noise is a common type of error, that occur in database. This paper proposes an automated method based on the k-means clustering for noise detection. At first, each attribute (Aj) is temporarily removed from data and the k-means clustering is applied to other attributes. Thereafter, the k-nearest neighbors is used in each cluster. After that a value is predicted for Aj in each record by the nearest neighbors. The proposed method detects noisy attributes using predicted values. Our method is able to identify several noises in a record. In addition, this method can detect noise in fields with different data types, too. Experiments show that this method can averagely detect 92% of the noises existing in the data. The proposed method is compared with a noise detection method using association rules. The results indicate that the proposed method have improved noise detection averagely by 13%.
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Ma, Lilong, Tuanwei Xu, Kai Cao, Yinghao Jiang, Dimin Deng, and Fang Li. "Signal Activity Detection for Fiber Optic Distributed Acoustic Sensing with Adaptive-Calculated Threshold." Sensors 22, no. 4 (February 21, 2022): 1670. http://dx.doi.org/10.3390/s22041670.

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The key point on analyzing the data stream measured by fiber optic distributed acoustic sensing (DAS) is signal activity detection separating measured signals from environmental noise. The inability to calculate the threshold for signal activity detection accurately and efficiently without affecting the measured signals is a bottleneck problem for current methods. In this article, a novel signal activity detection method with the adaptive-calculated threshold is proposed to solve the problem. With the analysis of the time-varying random noise’s statistical commonality and the short-term energy (STE) of real-time data stream, the top range of the total STE distribution of the noise is found accurately for real-time data stream’s ascending STE, thus the adaptive dividing level of signals and noise is obtained as the threshold. Experiments are implemented with simulated database and urban field database with complex noise. The average detection accuracies of the two databases are 97.34% and 90.94% only consuming 0.0057 s for a data stream of 10 s, which demonstrates the proposed method is accurate and high efficiency for signal activity detection.
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Dissertations / Theses on the topic "NOISEX database"

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Smital, Lukáš. "Vlnková filtrace elektrokardiogramů." Doctoral thesis, Vysoké učení technické v Brně. Fakulta elektrotechniky a komunikačních technologií, 2013. http://www.nusl.cz/ntk/nusl-233607.

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This dissertation deals with possibilities of using wavelet transforms for elimination of broadband muscle noise in ECG signals. In this work, the characteristics of ECG signals and particularly the most frequently occurring type of interference are discussed firstly. The theory of wavelet transforms is also introduced and followed by design of the simple wavelet filter and the more sophisticated version with wiener filtering of wavelet coefficients. Next part is devoted to the design of our filter, which is based on wavelet wiener filtering and is complemented by algorithms that ensure full adaptability of its parameters when the properties of the input signal are changing. Suitable parameters of the proposed system are searched automatically and the algorithm is tested on the complete standard electrocardiograms database CSE, where it achieves significantly better results than other published methods.
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Terz, Marek. "Databáze akustických nahrávek." Master's thesis, Vysoké učení technické v Brně. Fakulta elektrotechniky a komunikačních technologií, 2008. http://www.nusl.cz/ntk/nusl-217314.

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The databsae of accoustical recordings is a web-based application, which is accessible with an usual web browser. There were used technologies, that are ussually used in web applications. This ensures, that the application is open for using by wide range of users. The application enables uploading WAWE files to the server and allows the user to add various description of the recordings. The application allows also comparing the quality of recordings, which were processed with some method for highlighting the accoustical signal from noise. This function is established by listening tests, which are open for every user, who wants to join the tests.
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NAKAMURA, Satoshi, Kazuya TAKEDA, and Masakiyo FUJIMOTO. "CENSREC-3: An Evaluation Framework for Japanese Speech Recognition in Real Car-Driving Environments." Institute of Electronics, Information and Communication Engineers, 2006. http://hdl.handle.net/2237/15050.

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Wu, Ruimeng. "UTILIZATION OF EMPIRICAL MODELS TO DETERMINE THE BULK PROPERTIES OF COMPRESSED SOUND ABSORPTIVE MATERIALS." UKnowledge, 2017. https://uknowledge.uky.edu/me_etds/106.

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Empirical models based on flow resistivity are commonly used to determine the bulk properties of porous sound absorbing materials. The bulk properties include the complex wavenumber and complex characteristic impedance which can be used directly in simulation models. Moreover, the bulk properties can also be utilized to determine the normal incidence sound absorption and specific acoustic impedance for sound absorbing materials of any thickness and for design of layered materials. The sound absorption coefficient of sound absorbing materials is measured in an impedance tube using wave decomposition and the measured data is used to determine the flow resistivity of the materials by least squares curve fitting to empirical equations. Results for several commonly used foams and fibers are tabulated to form a rudimentary materials database. The same approach is then used to determine the flow resistivity of compressed sound absorbing materials. The flow resistivities of the compressed materials are determined as a function of the compression ratio. Results are then used in conjunction with transfer matrix theory to predict the sound absorptive performance of layered compressed absorbers with good agreement to measurement.
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Guédon, Stéphane. "Système à base de connaissances pour l'aide à la surveillance océanique à partir d'un réseau de magnétomètres." Grenoble INPG, 1994. http://www.theses.fr/1994INPG0132.

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Cet ouvrage etudie la faisabilite d'un systeme a base de connaissances pour l'aide a la surveillance oceanique a partir d'un reseau de magnetometres. La detection de la signature magnetique au passage d'une cible sous le reseau necessite un savoir faire qui releve de la connaissance experte du systeme de mesure, des proprietes des phenomenes naturels perturbateurs et des methodes de traitement specifiques. L'objectif a terme est de fournir a l'operateur, une assistance informatique lui communiquant les elements utiles pour l'aider a prendre des decisions optimales, en prenant en compte toute l'information a priori disponible, meme imparfaite et en pilotant les codes de calcul. L'etude s'effectue en trois etapes. La premiere repertorie l'ensemble des connaissances: l'environnement des mesures (phenomenes, sources, proprietes) ; les methodes de traitement des signaux (mono et bidimensionnels) pour l'extraction de caracteristiques et leur interpretation (en temps et frequences) ; les strategies pour la detection magnetique sous-marine. La seconde propose une architecture distribuee (blackboard) pour l'integration et la modelisation des connaissances expertes. Une base de donnees orientee objet symbolise l'etat de la resolution et l'organisation de l'environnement des mesures. Un controleur reactif a l'environnement planifie le declenchement de codes de calcul declares par les sources de connaissances. La decision dans le controle est realisee par une methode a base de regles floues. Elle associe les informations numeriques et symboliques. L'operateur communique avec la machine sur une base lexicale de qualificatifs. La troisieme etape presente un demonstrateur. Il fournit des avis directement interpretables par l'operateur en adequation avec le manque d'information. Il prend en compte l'acquisition des informations, l'apprentissage des bruits, la surveillance de la zone, la reduction des bruits et la detection d'une cible mobile
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Ramos, Camila Davi. "Caracterização do eletroencefalograma normal em situação de vigília: elaboração da base de dados e análise quantitativa." Universidade Federal de Uberlândia, 2017. https://repositorio.ufu.br/handle/123456789/19571.

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O sinal EEG, cujas informações descrevem o comportamento elétrico do córtex cerebral, apesar de ser bastante utilizado para diagnósticos, principalmente de patologias como epilepsia, no Brasil ainda não é usual o monitoramento contínuo em ambiente de UTI em hospitais públicos. Diante disso, e partindo do pressuposto que estudos sobre o EEG normal, registrado em pessoas sem problemas neurológicos, são escassos, a criação de uma base de registros de EEG normal e análise quantitativa da mesma se faz necessária para que, por meio dos resultados obtidos, padrões normais possam ser estabelecidos e por meio deles a identificação de parâmetros patológicos se torne mais eficaz. Nesse projeto foi elaborada uma base de dados de EEG, com total de 100 registros válidos, advindos de voluntários normais e saudáveis. E a partir desses registros a situação de vigília e olhos fechados foi analisada sob o aspecto de três quantificadores distintos, sendo eles, Porcentagem de Contribuição de Potência (PCP), Frequência Mediana (FM) e Coerência, ambos avaliando o sinal no domínio da frequência. A fim de obter comparações para os resultados obtidos pela análise dos dados do EEG normal, foram utilizados 128 registros de EEG em situação de coma, com diferentes tipos de etiologias e desfechos. Os ritmos que apresentaram maiores distinções entre normal e coma foram Delta e Alfa, principalmente para o quantificador FM. Notou-se que o PCP avaliou características de potência e portanto sintetizou as informações de energia de cada ritmo cerebral tanto em EEG normal quanto em EEG coma. Já FM traz informações de valores de frequências em que há maior concentração de potência, e por fim o quantificador coerência informa o grau de semelhança entre o hemisfério direito e o esquerdo do cérebro. Sendo assim não foi possível afirmar qual dos quantificadores apresentou melhores resultados, visto que cada um trata-se de uma características distintas.
The EEG signal, whose information describes the electrical behavior of the cerebral cortex, although it is widely used for diagnoses, mainly of pathologies such as epilepsy, in Brazil it is still not usual to monitor the ICU environment in public hospitals. Considering this, and assuming that studies on normal EEG, registered in people without neurological problems, are scarce, the creation of a base of normal EEG registers and quantitative analysis of it is necessary so that, through the obtained results, Normal patterns can be established and through them, the identification of pathological parameters becomes more effective. In this project, an EEG database was developed, with 100 valid records from normal and healthy volunteers. In addition, from these records, the waking and closed eyes situation was analyzed under the aspect of three distinct quantifiers, being: Power Contribution Percentage (PCP), Median Frequency (FM) and Coherence, both evaluating the signal in the frequency domain. In order to obtain comparisons for the results obtained by the analysis of the normal EEG data, 128 EEG records were used in coma, with different types of etiologies and outcomes. The rhythms that presented the highest distinctions between normal and coma were Delta and Alpha, mainly for the FM quantifier. It was noted that PCP evaluated power characteristics and therefore synthesized the energy information of each brain rhythm in both normal EEG and EEG coma. Already FM brings information of values of frequencies in which there is greater concentration of power, and finally the quantifier coherence informs the degree of similarity between the right and left hemisphere of the brain. Thus, it was not possible to say which of the quantifiers presented better results, since each one is a distinct characterization.
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Wu, Chih-Hao, and 吳誌豪. "Development and Applications of Ocean Ambient Noise Database around Taiwan." Thesis, 2009. http://ndltd.ncl.edu.tw/handle/3f68gn.

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碩士
國立中山大學
海下科技暨應用海洋物理研究所
97
Ocean ambient noise is one of the important parameters which affect sonar system performance. If the ocean ambient noise is estimated accurately, the prediction accuracy of sonar system performance can be promoted significantly. Ocean ambient noise includes various and diverse sources, so the characteristics of the ocean ambient noise should be analyzed by long-term observations and statistical methods. Therefore, ocean ambient noise database was developed to facilitate management, preservation, and application of these datasets which increase with time. There were two datasets of acoustic and three datasets of wind speed in this database at this point. To develop this database systematically, this study applied Entity-Relationship Model to describe the relationship between different data and Relational Model to design the required categories. The database was constructed based on Microsoft Office Access, and user-friendly graphical interfaces based on MATLAB were provided for users: wind speed regression, time series, spectrogram, and spectrum tendency for users to query the database. As the results of analysis, the intermittent, unknown, and high-level sources at southwestern sea of Taiwan in spring and summer made the noise level of low frequency about 8 to 10 dB higher in the night-time than that in the day-time. According to wind speed regression analysis, if there were sufficient data, the method would be practicable to pick a wind speed data nearby the location of acoustic data for noise estimation. As the results of the typhoon effects analysis, the noise level of 1 to 8 kHz was increased significantly by typhoons. Besides, the noise level didn’t decrease immediately and significantly after the pass of typhoon because of southwestern air current caused typhoon. After the database was developed, new acoustic data will keep being measured and collected, and the network capability will be integrated into the database to make the database more accessible to users.
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Qahwaji, Rami S. R. "Detecting edges in noisy face database images." 2003. http://hdl.handle.net/10454/4069.

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Wu, Jen-You, and 吳禎祐. "Using Noise Addition on Protecting Partially Open, Sensitive and Static Databases." Thesis, 2009. http://ndltd.ncl.edu.tw/handle/81322433987641906676.

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碩士
國立成功大學
工程科學系專班
97
With the growth of electronic commerce, paperless operations are gradually replacing traditional operations. The computing speed progresses substantially along with the advancement of hardware. Fast and instant access is not a difficult issue under this background. However, databases with sensitive data might be broken through by the intruders by combining anonymous sensitive databases with disclosure databases. If this should happen to medical and military databases and it would cause damages that can not be recovered. Besides, the convenience that Internet brings is also accompanied with the phenomenon of increasing network crimes. It is a dilemma to either give the exact data or “perturbed’ data for the users. For example, if we export the “perturbed” data, it might be happen that a doctor cannot make emergency rescue rapidly due to the low accuracy of patients’ case history. This thesis is to remove the uniqueness of sensitive data in databases under the premise of keeping the accuracy of statistical data. We propose two new algorithms: Reducing Noise Addition and Random Noise Interval Addition. Reducing Noise Addition combines tradition noise addition and group noise reducing to generalize the data in groups and removes the uniqueness of each tuple. Random Interval Noise Addition adds noise to the random values in groups and calculates an interval to cover the original data values. At last, but not the least, we implemented our algorithms in a web-based system to analyze its feasibility.
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Pullin, Eric D. ""Noise and flutter" : India, propaganda, and global conflict, 1942-1963 /." 2009. http://www.library.wisc.edu/databases/connect/dissertations.html.

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Books on the topic "NOISEX database"

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Gerhold, Carl H. Database of inlet and exhaust noise shielding for wedge-shaped airframe. Hampton, Va: National Aeronautics and Space Administration, Langley Research Center, 2001.

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Page, Juliet, Chris Hobbs, and Phil Gliebe. Enhanced Modeling of Aircraft Taxiway Noise, Volume 2: Aircraft Taxi Noise Database and Development Process. Washington, D.C.: Transportation Research Board, 2013. http://dx.doi.org/10.17226/22606.

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United States. National Aeronautics and Space Administration. and Dryden Flight Research Facility, eds. Engine exhaust characteristics evaluation in support of aircraft acoustic testing. [Washington, D.C.?]: National Aeronautics and Space Administration, 1993.

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N, Dalton William, and NASA Glenn Research Center, eds. Lobed mixer design for noise suppression: Acoustic and aerodynamic test data analysis. [Cleveland, Ohio]: National Aeronautics and Space Administration, Glenn Research Center, 2002.

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A, Boxwell D., Spencer R. H, Ames Research Center, and United States. Army Aviation Research and Technology Activity., eds. Review and analysis of the DNW/model 360 rotor acoustic data base. Moffett Field, Calif: National Aeronautics and Space Administration, Ames Research Center, 1989.

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ICA 2004 (2004 Granada, Spain). Database and expert systems applications: 5th international conference, ICA 2004, Granada, Spain, September 22-24, 2004 : proceedings. Berlin: Springer, 2004.

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Database of inlet and exhaust noise shielding for wedge-shaped airframe. Hampton, Va: National Aeronautics and Space Administration, Langley Research Center, 2001.

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National Aeronautics and Space Administration (NASA) Staff. Database of Inlet and Exhaust Noise Shielding for Wedge-Shaped Airframe. Independently Published, 2018.

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Mode Propagation Database Suitable for Code Validation Utilizing the NASA Glenn Advanced Noise Control Fan and Artificial Sources. Independently Published, 2019.

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Taberlet, Pierre, Aurélie Bonin, Lucie Zinger, and Eric Coissac. DNA metabarcoding data analysis. Oxford University Press, 2018. http://dx.doi.org/10.1093/oso/9780198767220.003.0008.

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DNA metabarcoding generates huge amounts of data containing noise introduced by molecular methods. Chapter 8 “DNA metabarcoding data analysis” discusses the analytic steps and available software to curate and evaluate DNA metabarcoding data prior to final ecological analyses. It provides command lines to perform primary analyses of Illumina sequencing data with the OBITools, ranging from read assignment to samples to the formation of molecular operational taxonomic units (MOTUs) and their assignment to a taxon through comparison against reference databases. Chapter 8 also develops several methods to further curate sequencing data from contaminants or dysfunctional PCRs by using DNA extraction, PCR, and sequencing blank controls as well as PCR/biological replicates. It also presents several classical analyses to ensure that the diversity of the sample or the study site is appropriately covered. Finally, this chapter considers what conclusions on biodiversity and ecological processes can be really drawn from metabarcoding data.
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Book chapters on the topic "NOISEX database"

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Domingo-Ferrer, Josep. "Noise Addition." In Encyclopedia of Database Systems, 1–2. New York, NY: Springer New York, 2014. http://dx.doi.org/10.1007/978-1-4899-7993-3_1495-2.

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Domingo-Ferrer, Josep. "Noise Addition." In Encyclopedia of Database Systems, 1911. Boston, MA: Springer US, 2009. http://dx.doi.org/10.1007/978-0-387-39940-9_1495.

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Domingo-Ferrer, Josep. "Noise Addition." In Encyclopedia of Database Systems, 2502–3. New York, NY: Springer New York, 2018. http://dx.doi.org/10.1007/978-1-4614-8265-9_1495.

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De Muer, Tom, Andy Verkeyn, and Dick Botteldooren. "Noise Annoyance Mapping." In Spatio-Temporal Databases, 369–92. Berlin, Heidelberg: Springer Berlin Heidelberg, 2004. http://dx.doi.org/10.1007/978-3-662-09968-1_17.

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Oganian, Anna. "Multiplicative Noise Protocols." In Privacy in Statistical Databases, 107–17. Berlin, Heidelberg: Springer Berlin Heidelberg, 2010. http://dx.doi.org/10.1007/978-3-642-15838-4_10.

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Miodragović, Tanja, Mladen Rasinac, Jelena Tomić, and Branko Radičević. "Online Database of Industrial Noise Sources." In Springer Proceedings in Physics, 165–71. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-54136-1_16.

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Ma, Yue, Yan-Xia Lin, Pavel N. Krivitsky, and Bradley Wakefield. "Quantifying the Protection Level of a Noise Candidate for Noise Multiplication Masking Scheme." In Privacy in Statistical Databases, 279–93. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-99771-1_19.

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Cheah, You-Wei, Beth Plale, Joey Kendall-Morwick, David Leake, and Lavanya Ramakrishnan. "A Noisy 10GB Provenance Database." In Business Process Management Workshops, 370–81. Berlin, Heidelberg: Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-642-28115-0_35.

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Liu, Rey-Long. "Reduction of Training Noises for Text Classifiers." In Intelligent Information and Database Systems, 30–39. Berlin, Heidelberg: Springer Berlin Heidelberg, 2013. http://dx.doi.org/10.1007/978-3-642-36543-0_4.

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Brand, Ruth. "Microdata Protection through Noise Addition." In Inference Control in Statistical Databases, 97–116. Berlin, Heidelberg: Springer Berlin Heidelberg, 2002. http://dx.doi.org/10.1007/3-540-47804-3_8.

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Conference papers on the topic "NOISEX database"

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Feng, John, and Josef Hobelsberger. "ASAM-ODS: An Open Standards Engineering Database for NVH Activities." In SAE 2003 Noise & Vibration Conference and Exhibition. 400 Commonwealth Drive, Warrendale, PA, United States: SAE International, 2003. http://dx.doi.org/10.4271/2003-01-1441.

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Thiemann, Joachim, Nobutaka Ito, and Emmanuel Vincent. "The Diverse Environments Multi-channel Acoustic Noise Database (DEMAND): A database of multichannel environmental noise recordings." In ICA 2013 Montreal. ASA, 2013. http://dx.doi.org/10.1121/1.4799597.

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Folino, Francesco, Gianluigi Greco, Antonella Guzzo, and Luigi Pontieri. "Discovering expressive process models from noised log data." In the 2009 International Database Engineering & Applications Symposium. New York, New York, USA: ACM Press, 2009. http://dx.doi.org/10.1145/1620432.1620449.

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Birdsong, Charles, and Clark Radcliffe. "Development of a Comparison Index and a Database for Sea Model Results." In SAE Noise and Vibration Conference and Exposition. 400 Commonwealth Drive, Warrendale, PA, United States: SAE International, 1997. http://dx.doi.org/10.4271/972008.

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Ognedal, Tønnes A., and Reidulf Klovning. "Noise and Vibration Database on Handheld Tools." In SPE International Conference and Exhibition on Health, Safety, Security, Environment, and Social Responsibility. Society of Petroleum Engineers, 2016. http://dx.doi.org/10.2118/179237-ms.

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Liu, Hai, Yanyi Zhang, Dong Hao, Yong Chen, Xiang Ji, and Changyin Wei. "Objective Evaluation of FCV Interior Sound Quality During Acceleration." In ASME 2018 International Mechanical Engineering Congress and Exposition. American Society of Mechanical Engineers, 2018. http://dx.doi.org/10.1115/imece2018-87011.

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While driving a FCV during acceleration, many sorts of sounds could be heard, which influence the interior sound quality. A typical FCV is taken as a sample, four interior noises generated under the acceleration operation are collected in the whole vehicle semi-anechoic chamber, and the noise sample database of diesel engine radiation noise is established after preprocessing. Based on sound quality theory (physical and psychoacoustic features), the Kernel Principal Component Analysis (KPCA) is used to extract the key objective features mainly influencing the sound quality, which realize the dimension reduction target; the variations of objective features are analyzed to qualitatively analyze the law of the sound quality varying during acceleration. According to the objective evaluation of FCV interior sound quality, combining with FCV operating parameters, the influencing law of the FCV sound quality could be obtained.
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Van den Nieuwenhof, Benoît, Grégory Lielens, Jean-Pierre Coyette, Jean-Louis Guyader, Nicolas Totaro, and Pascal Bouvet. "Making Sense of Large FEA NVH Databases using SEA Concepts." In SAE 2007 Noise and Vibration Conference and Exhibition. 400 Commonwealth Drive, Warrendale, PA, United States: SAE International, 2007. http://dx.doi.org/10.4271/2007-01-2183.

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O'Mahony, Michael P., Neil J. Hurley, and Guénolé C. M. Silvestre. "Detecting noise in recommender system databases." In the 11th international conference. New York, New York, USA: ACM Press, 2006. http://dx.doi.org/10.1145/1111449.1111477.

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Yin, Hua, Hongbin Dong, and Yuxuan Li. "A Cluster-Based Noise Detection Algorithm." In 2009 First International Workshop on Database Technology and Applications, DBTA. IEEE, 2009. http://dx.doi.org/10.1109/dbta.2009.39.

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Sayigh, Laela, Mary Ann Daher, Julie Allen, Helen Gordon, Katherine Joyce, Claire Stuhlmann, and Peter Tyack. "The Watkins Marine Mammal Sound Database: An online, freely accessible resource." In Fourth International Conference on the Effects of Noise on Aquatic Life. Acoustical Society of America, 2016. http://dx.doi.org/10.1121/2.0000358.

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Reports on the topic "NOISEX database"

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EDGEMON, G. L. Status of Database for Electrochemical Noise Based Corrosion Monitoring. Office of Scientific and Technical Information (OSTI), August 1999. http://dx.doi.org/10.2172/797750.

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Firon, Nurit, Prem Chourey, Etan Pressman, Allen Hartwell, and Kenneth J. Boote. Molecular Identification and Characterization of Heat-Stress-Responsive Microgametogenesis Genes in Tomato and Sorghum - A Feasibility Study. United States Department of Agriculture, October 2007. http://dx.doi.org/10.32747/2007.7591741.bard.

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Exposure to higher than optimal temperatures - heat-stress (HS) - is becoming increasingly common to all crop plants worldwide. Heat stress coinciding with microgametogenesis, especially during the post-meiotic phase that is marked by starch biosynthesis, is often associated with starch-deficient pollen and male sterility and ultimately, greatly reduced crop yields. The molecular basis for the high sensitivity of developing pollen grains, on one hand, and factors involved in pollen heat-tolerance, on the other, is poorly understood. The long-term goal of this project is to provide a better understanding of the genes that control pollen quality under heat-stress conditions. The specific objectives of this project were: (1) Determination of the threshold heat stress temperature(s) that affects tomato and sorghum pollen quality whether: a) Chronic mild heat stress conditions (CMHS), or b) Acute heat stress (AHS). (2) Isolation of heat-responsive, microgametogenesis-specific sequences. During our one-year feasibility project, we have accomplished the proposed objectives as follows: Objectrive 1: We have determined the threshold HS conditions in tomato and sorghum. This was essential for achieving the 2nd objective, since our accumulated experience (both Israeli and US labs) indicate that when temperature is raised too high above "threshold HS levels" it may cause massive death of the developing pollen grains. Above-threshold conditions have additional major disadvantages including the "noise" caused by induced expression of genes involved in cell death and masking of the differences between heatsensitive and heat-tolerant pollen grains. Two different types of HS conditions were determined: a) Season-long CMHS conditions: 32/26°C day/night temperatures confirmed in tomato and 36/26°C day maximum/night minimum temperatures in sorghum. b) Short-term AHS: In tomato, 2 hour exposure to 42-45°C (at 7 to 3 days before anthesis) followed by transfer to 28/22±2oC day/night temperatures until flower opening and pollen maturation, caused 50% reduced germinating pollen in the heat-sensitive 3017 cv.. In sorghum, 36/26°C day/night temperatures 10 to 5 days prior to panicle emergence, occurring at 35 days after sowing (DAS) in cv. DeKalb28E, produced starch-deficient and sterile pollen. Objective 2: We have established protocols for the high throughput transcriptomic approach, cDNA-AFLP, for identifying and isolating genes exhibiting differential expression in developing microspores exposed to either ambient or HS conditions and created a databank of HS-responsivemicrogametogenesis-expressed genes. A subset of differentially displayed Transcript-Derived Fragments (TDFs) that were cloned and sequenced (35 & 23 TDFs in tomato and sorghum, respectively) show close sequence similarities with metabolic genes, genes involved in regulation of carbohydrate metabolism, genes implicated in thermotolerance (heat shock proteins), genes involved in long chain fatty acids elongation, genes involved in proteolysis, in oxidation-reduction, vesicle-mediated transport, cell division and transcription factors. T-DNA-tagged Arabidopsis mutants for part of these genes were obtained to be used for their functional analysis. These studies are planned for a continuation project. Following functional analyses of these genes under HS – a valuable resource of genes, engaged in the HS-response of developing pollen grains, that could be modulated for the improvement of pollen quality under HS in both dicots and monocots and/or used to look for natural variability of such genes for selecting heat-tolerant germplasm - is expected.
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