• Title/Summary/Keyword: post data processing

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A Study on Error Correction Using Phoneme Similarity in Post-Processing of Speech Recognition (음성인식 후처리에서 음소 유사율을 이용한 오류보정에 관한 연구)

  • Han, Dong-Jo;Choi, Ki-Ho
    • The Journal of The Korea Institute of Intelligent Transport Systems
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    • v.6 no.3
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    • pp.77-86
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    • 2007
  • Recently, systems based on speech recognition interface such as telematics terminals are being developed. However, many errors still exist in speech recognition and then studies about error correction are actively conducting. This paper proposes an error correction in post-processing of the speech recognition based on features of Korean phoneme. To support this algorithm, we used the phoneme similarity considering features of Korean phoneme. The phoneme similarity, which is utilized in this paper, rams data by mono-phoneme, and uses MFCC and LPC to extract feature in each Korean phoneme. In addition, the phoneme similarity uses a Bhattacharrya distance measure to get the similarity between one phoneme and the other. By using the phoneme similarity, the error of eo-jeol that may not be morphologically analyzed could be corrected. Also, the syllable recovery and morphological analysis are performed again. The results of the experiment show the improvement of 7.5% and 5.3% for each of MFCC and LPC.

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MRI Artifact Correction due to Unknown Respiratory Motion (미지 호흡운동에 의한 MRI 아티팩트의 수정)

  • 김응규
    • Journal of the Institute of Electronics Engineers of Korea SP
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    • v.41 no.5
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    • pp.53-62
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    • 2004
  • In this study, an improved post-processing technique for correcting MRI artifact due to the unknown respiratory motion in the imaging plane is presented. Respiratory motion is modeled by a two-Dimensional linear expending-shrinking movement. Assuming that the body tissues are incompressible fluid like materials, the proton density per unit volume of the imaging object is kept constant. According to the introduced model, respiratory motion imposes phase error, non-uniform sampling and amplitude modulation distortions on the acquired MRI data. When the motion parameters are known or can be estimatead a reconstruction algorithm based on biliner superposition method was used to correct the MRI artifact. In the case of motion parameters are unknown, first, the spectrum shift method is applied to find the respiratory fluctuation function, x directional expansion coefficient and x directional expansion center. Next, y directional expansion coefficient and y directional expansion center are estimated by using the minimum energy method. Finally, the validity of this proposed method is shown to be effective by using the simulated motion images.

Reconstructing Flaw Image Using Dataset of Full Matrix Capture Technique (Full Matrix Capture 데이터를 이용한 균열 영상화)

  • Lee, Tae-Hun;Kim, Yong-Sik;Lee, Jeong-Seok
    • Journal of the Korean Society for Nondestructive Testing
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    • v.37 no.1
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    • pp.13-20
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    • 2017
  • A conventional phased array ultrasonic system offers the ability to steer an ultrasonic beam by applying independent time delays of individual elements in the array and produce an ultrasonic image. In contrast, full matrix capture (FMC) is a data acquisition process that collects a complete matrix of A-scans from every possible independent transmit-receive combination in a phased array transducer and makes it possible to reconstruct various images that cannot be produced by conventional phased array with the post processing as well as images equivalent to a conventional phased array image. In this paper, a basic algorithm based on the LLL mode total focusing method (TFM) that can image crack type flaws is described. And this technique was applied to reconstruct flaw images from the FMC dataset obtained from the experiments and ultrasonic simulation.

Calculation Model of Time Varying Loudness by Using the Critical-banded Filters (임계 대역 필터를 이용한 과도음의 라우드니스 계산 모델)

  • Jeong, Hyuk;Ih, Jeong-Guon
    • The Journal of the Acoustical Society of Korea
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    • v.19 no.5
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    • pp.65-70
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    • 2000
  • It is blown that the loudness is one of the most important metrics in assessing the sound quality and a calculation method for loudness has been standardized for steady sounds. In this study, a new loudness model is suggested for dealing with the transient sound for a unified analysis of various practical sounds. A signal processing technique is introduced for this purpose, which is required for the band subdivision and the prediction of band-level change of transient sounds. In addition, models for the post-masking and the temporal integration are adopted in the analysis of the loudness of transient sounds. In order to solve the problem of the conventional loudness model in the pure-tone signal processing, a critical band filter is employed in the analysis, which consists of 47 critical filters having a filter spacing of a half of the critical bandwidth. For testing the effectiveness of the present model, the predicted responses are compared with the experimental data and it is observed that they are in good agreements.

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Wavelet Shift Keying System Using a Binary Matching Filter (2진 정합필터를 이용한 웨이브릿 편이변조 시스템)

  • Oh, Hyoung-Jin;Jeong, Tae-Il;Lee, Tae-Oh
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.12 no.11
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    • pp.1933-1938
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    • 2008
  • There are the frequency shift keying(FSK), phase shift keying(PSK) and amplitude shift keying(ASK) in the conventional digital communications method. In this parer, We proposed the algorithm for wavelet shift keying system using a binary matching filter in the digital communication. Wavelet shift keying system are used to a scaling function(low frequency) and wavelet(high frequency) coefficients. The binary data is encoded by modulator which assigned the scaling function to 1(one), and wavelet to zero(0). Wavelet shift keying of the conventional method needs to a post-processing for the decoding. In this paper, wavelet shift keying signal is reconstructed by the decoder using a binary matching filter. So, it was able to the decoding without the post-processing. It was demonstrated by the experiment that the proposed algorithm is a validity.

Wildfire-induced Change Detection Using Post-fire VHR Satellite Images and GIS Data (산불 발생 후 VHR 위성영상과 GIS 데이터를 이용한 산불 피해 지역 변화 탐지)

  • Chung, Minkyung;Kim, Yongil
    • Korean Journal of Remote Sensing
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    • v.37 no.5_3
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    • pp.1389-1403
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    • 2021
  • Disaster management using VHR (very high resolution) satellite images supports rapid damage assessment and also offers detailed information of the damages. However, the acquisition of pre-event VHR satellite images is usually limited due to the long revisit time of VHR satellites. The absence of the pre-event data can reduce the accuracy of damage assessment since it is difficult to distinguish the changed region from the unchanged region with only post-event data. To address this limitation, in this study, we conducted the wildfire-induced change detection on national wildfire cases using post-fire VHR satellite images and GIS (Geographic Information System) data. For GIS data, a national land cover map was selected to simulate the pre-fire NIR (near-infrared) images using the spatial information of the pre-fire land cover. Then, the simulated pre-fire NIR images were used to analyze bi-temporal NDVI (Normalized Difference Vegetation Index) correlation for unsupervised change detection. The whole process of change detection was performed on a superpixel basis considering the advantages of superpixels being able to reduce the complexity of the image processing while preserving the details of the VHR images. The proposed method was validated on the 2019 Gangwon wildfire cases and showed a high overall accuracy over 98% and a high F1-score over 0.97 for both study sites.

How image-processing parameters can influence the assessment of dental materials using micro-CT

  • Torres, Fernanda Ferrari Esteves;Jacobs, Reinhilde;EzEldeen, Mostafa;de Faria-Vasconcelos, Karla;Guerreiro-Tanomaru, Juliane Maria;dos Santos, Bernardo Camargo;Tanomaru-Filho, Mario
    • Imaging Science in Dentistry
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    • v.50 no.2
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    • pp.161-168
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    • 2020
  • Purpose: The aim of this study was to evaluate the influence of voxel size and different post-processing algorithms on the analysis of dental materials using micro-computed tomography (micro-CT). Materials and Methods: Root-end cavities were prepared in extracted maxillary premolars, filled with mineral trioxide aggregate (MTA), Biodentine, and Intermediate Restorative Material (IRM), and scanned using micro-CT. The volume and porosity of materials were evaluated and compared using voxel sizes of 5, 10, and 20 ㎛, as well as different software tools(post-processing algorithms). The CTAn or MeVisLab/Materialise 3-matic software package was used to perform volume and morphological analyses, and the CTAn or MeVisLab/Amira software was used to evaluate porosity. Data were analyzed using 1-way ANOVA and the Tukey test(P<0.05). Results: Using MeVisLab/Materialise 3-matic, a consistent tendency was observed for volume to increase at larger voxel sizes. CTAn showed higher volumes for MTA and IRM at 20 ㎛. Using CTAn, porosity values decreased as voxel size increased, with statistically significant differences for all materials. MeVisLab/Amira showed a difference for MTA and IRM at 5 ㎛, and for Biodentine at 20 ㎛. Significant differences in volume and porosity were observed in all software packages for Biodentine across all voxel sizes. Conclusion: Some differences in volume and porosity were found according to voxel size, image-processing software, and the radiopacity of the material. Consistent protocols are needed for research evaluating dental materials.

Improvement of precipitation forecasting skill of ECMWF data using multi-layer perceptron technique (다층퍼셉트론 기법을 이용한 ECMWF 예측자료의 강수예측 정확도 향상)

  • Lee, Seungsoo;Kim, Gayoung;Yoon, Soonjo;An, Hyunuk
    • Journal of Korea Water Resources Association
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    • v.52 no.7
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    • pp.475-482
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    • 2019
  • Subseasonal-to-Seasonal (S2S) prediction information which have 2 weeks to 2 months lead time are expected to be used through many parts of industry fields, but utilizability is not reached to expectation because of lower predictability than weather forecast and mid- /long-term forecast. In this study, we used multi-layer perceptron (MLP) which is one of machine learning technique that was built for regression training in order to improve predictability of S2S precipitation data at South Korea through post-processing. Hindcast information of ECMWF was used for MLP training and the original data were compared with trained outputs based on dichotomous forecast technique. As a result, Bias score, accuracy, and Critical Success Index (CSI) of trained output were improved on average by 59.7%, 124.3% and 88.5%, respectively. Probability of detection (POD) score was decreased on average by 9.5% and the reason was analyzed that ECMWF's model excessively predicted precipitation days. In this study, we confirmed that predictability of ECMWF's S2S information can be improved by post-processing using MLP even the predictability of original data was low. The results of this study can be used to increase the capability of S2S information in water resource and agricultural fields.

Using noise filtering and sufficient dimension reduction method on unstructured economic data (노이즈 필터링과 충분차원축소를 이용한 비정형 경제 데이터 활용에 대한 연구)

  • Jae Keun Yoo;Yujin Park;Beomseok Seo
    • The Korean Journal of Applied Statistics
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    • v.37 no.2
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    • pp.119-138
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    • 2024
  • Text indicators are increasingly valuable in economic forecasting, but are often hindered by noise and high dimensionality. This study aims to explore post-processing techniques, specifically noise filtering and dimensionality reduction, to normalize text indicators and enhance their utility through empirical analysis. Predictive target variables for the empirical analysis include monthly leading index cyclical variations, BSI (business survey index) All industry sales performance, BSI All industry sales outlook, as well as quarterly real GDP SA (seasonally adjusted) growth rate and real GDP YoY (year-on-year) growth rate. This study explores the Hodrick and Prescott filter, which is widely used in econometrics for noise filtering, and employs sufficient dimension reduction, a nonparametric dimensionality reduction methodology, in conjunction with unstructured text data. The analysis results reveal that noise filtering of text indicators significantly improves predictive accuracy for both monthly and quarterly variables, particularly when the dataset is large. Moreover, this study demonstrated that applying dimensionality reduction further enhances predictive performance. These findings imply that post-processing techniques, such as noise filtering and dimensionality reduction, are crucial for enhancing the utility of text indicators and can contribute to improving the accuracy of economic forecasts.

Kirchhoff prestack depth migration for gas hydrate seismic data set (가스 하이드레이트 자료에 대한 중합전 키르히호프 심도 구조보정)

  • Hien, Doan Huy;Jang, Seong-Hyung;Kim, Young-Wan;Suh, Sang-Yong
    • 한국신재생에너지학회:학술대회논문집
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    • 2007.06a
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    • pp.493-496
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    • 2007
  • Korean Institute of Geosciences and Mineral Resources (KIGAM) has studied on gas hydrate in the Ulleung Basin, East sea of Korea since 1997. Most of all, a evidence for existence of gas hydrate, possible new energy resources, in seismic reflection data is bottom simulating reflection (BSR) which parallel to the sea bottom. Here we conducted the conventional data processing for gas hydrate data and Kirchhoff prestack depth migration. Kirchhoff migration is widely used for pre- and post-stack migration might be helpful to better image as well as to get the geological information. The processed stack image by GEOBIT showed some geological structures such as faults and shallow gas hydrate seeping area indicated by strong BSR. The BSR in the stack image showed at TWT 3.07s between shot gather No 3940 to No 4120. The estimated gas seeping area occurred at the shot point No 4187 to No 4203 and it seems to have some minor faults at shot point No 3735, 3791, 3947 and 4120. According to the result of depth migration, the BSR showed as 2.3km below the sea bottom.

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