• Journal of Information Technology Services
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• v.4 no.2
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• pp.125-133
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• 2005

Because of paradigm change to web service, numerous institutes have been suggested supporting solution about web service, and actively developed system using web service but it is hard to find out a systematic study for web service performance enhancement. Generally, there are SOAP message processing improvement and configuration optimization of server viewpoint for web service performance enhancement. Web service performance enhancement through SOAP message processing improvement have been studied related research but configuration optimization of server is hard to find out a systematic tuning model and performance criteria. In this paper, I suggested performance testing based tuning model and criteria of configuration optimization of server viewpoint. We executed practical analysis using tuning model about web service in internet. This paper show that the proposed tuning model and performance criteria is applicable to web service performance enhancement.

• Speech Sciences
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• v.14 no.2
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• pp.115-126
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• 2007

There have been many research efforts to improve the performance of the speech recognizer in noisy conditions. Among them, the model compensation method and the speech enhancement approach have been used widely. In this paper, we propose to combine the two different approaches to further enhance the recognition rates in the noisy speech recognition. For the speech enhancement, the minimum mean square error-short time spectral amplitude (MMSE-STSA) has been adopted and the parallel model combination (PMC) and Jacobian adaptation (JA) have been used as the model compensation approaches. From the experimental results, we could find that the hybrid approach that applies the model compensation methods to the enhanced speech produce better results than just using only one of the two approaches.

• Journal of Korea Multimedia Society
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• v.22 no.7
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• pp.749-758
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• 2019

This paper proposes a data augmentation algorithm to improve the performance of DNN(Deep Neural Network) based speech enhancement. Many deep learning models are exploring algorithms to maximize the performance in limited amount of data. The most commonly used algorithm is the data augmentation which is the technique artificially increases the amount of data. For the effective data augmentation algorithm, we used a formant enhancement method that assign the different weights to the formant frequencies. The DNN model which is trained using the proposed data augmentation algorithm was evaluated in various noise environments. The speech enhancement performance of the DNN model with the proposed data augmentation algorithm was compared with the algorithms which are the DNN model with the conventional data augmentation and without the data augmentation. As a result, the proposed data augmentation algorithm showed the higher speech enhancement performance than the other algorithms.

• Proceedings of the Acoustical Society of Korea Conference
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• spring
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• pp.337-338
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• 2000

The perceptual filter for speech enhancement was analytically derived where the frequency content of the input noisy signal was made the same as that of the estimated clean signal in auditory domain. However, the analytical derivation should rely on the deconvolution associated with the spreading function in the psychoacoustic model, which results in an ill-conditioned problem. In order to cope with the problem associated with the deconvolution, we propose a novel psychoacoustic model based speech enhancement filter whose principle is the same as the perceptual filter, however the filter is derived by a constrained optimization which provides solutions to the ill-conditioned problem.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2001.12a
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• pp.279-282
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• 2001

This paper presents an image contrast enhancement technique for improving the low contrast images using the improved IAFC(Integrated Adaptive Fuzzy Clustering) Model. The low pictorial information of a low contrast image is due to the vagueness or fuzziness of the multivalued levels of brightness rather than randomness. Fuzzy image processing has three main stages, namely, image fuzzification, modification of membership values, and image defuzzification. Using a new model of automatic crossover point selection, optimal crossover point is selected automatically. The problem of crossover point selection can be considered as the two-category classification problem. The improved MEC can classify the image into two classes with unsupervised teaming rule. The proposed method is applied to some experimental images with 256 gray levels and the results are compared with those of the histogram equalization technique. We utilized the index of fuzziness as a measure of image quality. The results show that the proposed method is better than the histogram equalization technique.

• Speech Sciences
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• v.11 no.2
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• pp.259-269
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• 2004

In this paper, we propose a new excitation enhancement technique to improve the speech quality of low bit-rate code-excited linear prediction (CELP) coders. The proposed technique is based on a harmonic model and it is employed only in the decoding process of speech coders without any additional bits. We develop the procedure of harmonic model parameter estimation and harmonic generation, and apply this technique to a current state-of-the-art low bit rate speech coder, ITU-T G.729 Annex D. Also, its performance is measured by using the ITU-T P.862 PESQ score and compared to those of the phase dispersion filter and the long-term postfilter applied to the decoded excitation. It is shown that the proposed excitation enhancement technique can improve the quality of decoded speech and provide better quality for male speech than other techniques.

• Journal of Information Processing Systems
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• v.19 no.4
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• pp.465-473
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• 2023

An image enhancement algorithm and image defogging method are studied in this paper. The formation of fog and the characteristics of fog image are analyzed, and the fog image is preprocessed by histogram equalization method; then the additive white noise is removed by foggy image attenuation model, the atmospheric scattering physical model is constructed, the image detail characteristics are enhanced by image enhancement method, and the visual effect of defogging image is enhanced by guided filtering method. The proposed method has a good defogging effect on the image. When the number of training iterations is 3,000, the peak signal-to-noise ratio of the proposed method is 43.29 dB and the image structure similarity is 0.9616, indicating excellent image defogging effect.

• The Journal of the Acoustical Society of Korea
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• v.43 no.2
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• pp.253-259
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• 2024

This paper proposes a new speech enhancement model based on a complex nested U-Net with a dual-branch decoder. The proposed model consists of a complex nested U-Net to simultaneously estimate the magnitude and phase components of the speech signal, and the decoder has a dual-branch decoder structure that performs spectral mapping and time-frequency masking in each branch. At this time, compared to the single-branch decoder structure, the dual-branch decoder structure allows noise to be effectively removed while minimizing the loss of speech information. The experiment was conducted on the VoiceBank + DEMAND database, commonly used for speech enhancement model training, and was evaluated through various objective evaluation metrics. As a result of the experiment, the complex nested U-Net-based speech enhancement model using a dual-branch decoder increased the Perceptual Evaluation of Speech Quality (PESQ) score by about 0.13 compared to the baseline, and showed a higher objective evaluation score than recently proposed speech enhancement models.

• Journal of radiological science and technology
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• v.24 no.1
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• pp.67-73
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• 2001

In digital image processing, the homomorphic filtering approach is derived from an illumination-reflectance model of the image. It can also be used with an illumination-transillumnation model of X-ray film. Several X-ray images were applied to enhancement with histogram equalization and homomorphic filter based on an illumination-transillumination model. The homomorphic filter has proven theoretical claim of image density range compression and balanced contrast enhancement, and also was found a valuable tool to process analog X-ray images to digital images.

• Transactions of the Korean Society of Mechanical Engineers B
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• v.24 no.4
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• pp.495-503
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• 2000

The present numerical study investigates flow characteristics and heat transfer enhancement of the viscoelastic non-Newtonian fluid in a 2:1 rectangular duct. The combined effect of temperature-dependent viscosity, buoyancy and secondary flow caused by second normal stress difference are all considered. The Reiner-Rivlin model is used as a viscoelastic fluid model to simulate the secondary flow and temperature-dependent viscosity model is adopted. Three types of thermal boundary conditions involving different combinations of heated walls and adiabatic walls are considered in this study. Calculated Nusselt numbers are in good agreement with experimental results in both the thermal developing and thermally developed regions. The heat transfer enhancement can be explained by the combined viscoelasticity-driven secondary flow, buoyancy-induced secondary flow and temperature-dependent viscosity.