• Title/Summary/Keyword: Korean normalization

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Effect of dimensionless number and analysis of gait pattern by gender -spatiotemporal variables- (보행 분석시 Dimensionless number의 효과 및 성별간 보행패턴 분석 -시공간변인-)

  • Lee, Hyun-Seob
    • 한국체육학회지인문사회과학편
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    • v.53 no.5
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    • pp.521-531
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    • 2014
  • The purposes of this study were to evaluate the effect of normalization by dimensionless number of Hof(1996) and to analysis the gait pattern for 20s Korean males and females. Subjects are selected in accordance with classification system of Korean standard body figure and age. Experimental equipment is the Motion capture system. Subjects who are walked at a self-selected normal walking speed were photographed using the Motion capture system and analyzed using 3D motion analysis method with OrthoTrak, Cortex, Matlab and SPSS for a statistical test. When used to normalize data, there are no differences of statistical significances between gender in all spatiotemporal variables. I concluded that gait research for mutual comparison requires a normalization by dimensionless number to eliminate the effects of the body size and to accurate statistical analysis.

Change Detection Comparison of Multitemporal Infrared Satellite Imagery Using Relative Radiometric Normalization (상대 방사 정규화를 이용한 다시기 적외 위성영상의 변화탐지 비교)

  • Han, Dongyeob;Song, Jeongheon;Byun, Younggi
    • Korean Journal of Remote Sensing
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    • v.33 no.6_3
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    • pp.1179-1185
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    • 2017
  • The KOMPSAT-3A satellite acquires high-resolution MWIR images twice a day compared to conventional Earth observing satellites. New radiometric information of Earth's surface can be provided due to different characteristics from existing SWIR images or TIR images. In this study, the difference image of multitemporal images was generated and compared with existing infrared images to find the characteristics of KOMPSAT-3A MWIR satellite images. A co-registration was performed and the difference between pixel values was minimized by using PIFs (Pseudo Invariant Features) pixel-based relative normalization. The experiment using Sentinel-2 SWIR image, Landsat 8 TIR image, and KOMPSAT-3A MWIR image showed that the distinction between artifacts in the difference image of KOMPSAT-3A is prominent. It is believed that the utilization of KOMPSAT-3A MWIR images can be improved by using the characteristics of IR image.

Implementation of Driver Fatigue Monitoring System (운전자 졸음 인식 시스템 구현)

  • Choi, Jin-Mo;Song, Hyok;Park, Sang-Hyun;Lee, Chul-Dong
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.37 no.8C
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    • pp.711-720
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    • 2012
  • In this paper, we introduce the implementation of driver fatigue monitering system and its result. Input video device is selected commercially available web-cam camera. Haar transform is used to face detection and adopted illumination normalization is used for arbitrary illumination conditions. Facial image through illumination normalization is extracted using Haar face features easily. Eye candidate area through illumination normalization can be reduced by anthropometric measurement and eye detection is performed by PCA and Circle Mask mixture model. This methods achieve robust eye detection on arbitrary illumination changing conditions. Drowsiness state is determined by the level on illumination normalize eye images by a simple calculation. Our system alarms and operates seatbelt on vibration through controller area network(CAN) when the driver's doze level is detected. Our algorithm is implemented with low computation complexity and high recognition rate. We achieve 97% of correct detection rate through in-car environment experiments.

Evaluation of Candidate Housekeeping Genes for the Normalization of RT-qPCR Analysis using Developing Embryos and Prolarvae in Russian Sturgeon Acipenser gueldenstaedtii (러시아 철갑상어(Acipenser gueldenstaedtii) 발생 시료의 RT-qPCR 분석을 위한 내재 대조군 유전자의 선정)

  • Nam, Yoon Kwon;Lee, Sang Yoon;Kim, Eun Jeong
    • Korean Journal of Fisheries and Aquatic Sciences
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    • v.51 no.1
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    • pp.95-106
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    • 2018
  • To evaluate appropriate reference genes for the normalization of quantitative reverse transcription PCR (RT-qPCR) data with embryonic and larval samples from Russian sturgeon Acipenser gueldenstaedtii, the expression stability of eight candidate housekeeping genes, including beta-actin (ACTB), elongation factor-1A (EF1A), glyceraldehyde-3-phosphate dehydrogenase (GAPDH), histone 2A (H2A), ribosomal protein L5 (RPL5), ribosomal protein L7 (RPL7), succinate dehydrogenase (SDHA), and ubiquitin-conjugating enzyme E2 (UBE2A), were tested using embryonic samples from 12 developmental stages and larval samples from 11 ontogenic stages. Based on the stability rankings from three statistic software packages, geNorm, NormFinder, and BestKeeper, the expression stability of the embryonic subset was ranked as UBE2A>H2A>SDHA>GAPDH>RPL5>EF1A>ACTB>RPL7. On the other hand, the ranking in the larval subset was determined as UBE2A>GAPDH>SDHA>RPL5>RPL7>H2A>EF1A>AC TB. When the two subsets were combined, the overall ranking was UBE2A>SDHA>H2A>RPL5>GAPDH>EF1A>ACTB>RPL7. Taken together, our data suggest that UBE2A and SDHA are recommended as suitable references for developmental and ontogenic samples of this sturgeon species, whereas traditional housekeepers such as ACTB and GAPDH may not be suitable candidates.

An Efficiency Assessment for Reflectance Normalization of RapidEye Employing BRD Components of Wide-Swath satellite

  • Kim, Sang-Il;Han, Kyung-Soo;Yeom, Jong-Min
    • Korean Journal of Remote Sensing
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    • v.27 no.3
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    • pp.303-314
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    • 2011
  • Surface albedo is an important parameter of the surface energy budget, and its accurate quantification is of major interest to the global climate modeling community. Therefore, in this paper, we consider the direct solution of kernel based bidirectional reflectance distribution function (BRDF) models for retrieval of normalized reflectance of high resolution satellite. The BRD effects can be seen in satellite data having a wide swath such as SPOT/VGT (VEGETATION) have sufficient angular sampling, but high resolution satellites are impossible to obtain sufficient angular sampling over a pixel during short period because of their narrow swath scanning when applying semi-empirical model. This gives a difficulty to run BRDF model inferring the reflectance normalization of high resolution satellites. The principal purpose of the study is to estimate normalized reflectance of high resolution satellite (RapidEye) through BRDF components from SPOT/VGT. We use semi-empirical BRDF model to estimated BRDF components from SPOT/VGT and reflectance normalization of RapidEye. This study used SPOT/VGT satellite data acquired in the S1 (daily) data, and within this study is the multispectral sensor RapidEye. Isotropic value such as the normalized reflectance was closely related to the BRDF parameters and the kernels. Also, we show scatter plot of the SPOT/VGT and RapidEye isotropic value relationship. The linear relationship between the two linear regression analysis is performed by using the parameters of SPOTNGT like as isotropic value, geometric value and volumetric scattering value, and the kernel values of RapidEye like as geometric and volumetric scattering kernel Because BRDF parameters are difficult to directly calculate from high resolution satellites, we use to BRDF parameter of SPOT/VGT. Also, we make a decision of weighting for geometric value, volumetric scattering value and error through regression models. As a result, the weighting through linear regression analysis produced good agreement. For all sites, the SPOT/VGT isotropic and RapidEye isotropic values had the high correlation (RMSE, bias), and generally are very consistent.

Robust Speech Recognition using Vocal Tract Normalization for Emotional Variation (성도 정규화를 이용한 감정 변화에 강인한 음성 인식)

  • Kim, Weon-Goo;Bang, Hyun-Jin
    • Journal of the Korean Institute of Intelligent Systems
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    • v.19 no.6
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    • pp.773-778
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    • 2009
  • This paper studied the training methods less affected by the emotional variation for the development of the robust speech recognition system. For this purpose, the effect of emotional variations on the speech signal were studied using speech database containing various emotions. The performance of the speech recognition system trained by using the speech signal containing no emotion is deteriorated if the test speech signal contains the emotions because of the emotional difference between the test and training data. In this study, it is observed that vocal tract length of the speaker is affected by the emotional variation and this effect is one of the reasons that makes the performance of the speech recognition system worse. In this paper, vocal tract normalization method is used to develop the robust speech recognition system for emotional variations. Experimental results from the isolated word recognition using HMM showed that the vocal tract normalization method reduced the error rate of the conventional recognition system by 41.9% when emotional test data was used.

Multi-Frame-Based Super Resolution Algorithm by Using Motion Vector Normalization and Edge Pattern Analysis (움직임 벡터의 정규화 및 에지의 패턴 분석을 이용한 복수 영상 기반 초해상도 영상 생성 기법)

  • Kwon, Soon-Chan;Yoo, Jisang
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.38A no.2
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    • pp.164-173
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    • 2013
  • In this paper, we propose multi-frame based super resolution algorithm by using motion vector normalization and edge pattern analysis. Existing algorithms have constraints of sub-pixel motion and global translation between frames. Thus, applying of algorithms is limited. And single-frame based super resolution algorithm by using discrete wavelet transform which robust to these problems is proposed but it has another problem that quantity of information for interpolation is limited. To solve these problems, we propose motion vector normalization and edge pattern analysis for 2*2 block motion estimation. The experimental results show that the proposed algorithm has better performance than other conventional algorithms.

A Study on the Training Optimization Using Genetic Algorithm -In case of Statistical Classification considering Normal Distribution- (유전자 알고리즘을 이용한 트레이닝 최적화 기법 연구 - 정규분포를 고려한 통계적 영상분류의 경우 -)

  • 어양담;조봉환;이용웅;김용일
    • Korean Journal of Remote Sensing
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    • v.15 no.3
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    • pp.195-208
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    • 1999
  • In the classification of satellite images, the representative of training of classes is very important factor that affects the classification accuracy. Hence, in order to improve the classification accuracy, it is required to optimize pre-classification stage which determines classification parameters rather than to develop classifiers alone. In this study, the normality of training are calculated at the preclassification stage using SPOT XS and LANDSAT TM. A correlation coefficient of multivariate Q-Q plot with 5% significance level and a variance of initial training are considered as an object function of genetic algorithm in the training normalization process. As a result of normalization of training using the genetic algorithm, it was proved that, for the study area, the mean and variance of each class shifted to the population, and the result showed the possibility of prediction of the distribution of each class.

Yield Load Interpretation for Drilled Shaft Foundations by Hyperbolic Approximation (쌍곡선 근사에 의한 현장타설말뚝의 항복하중 판정)

  • Won, Sang-Yeon;Hwang, Seong-Il;Jo, Nam-Jun
    • Geotechnical Engineering
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    • v.12 no.6
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    • pp.79-86
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    • 1996
  • This study develops a new method for interpreting the yield load from load tests on drilled shaft foundations ended on general soils, which is defined as a point where the maximum curvature on the hyperbolic-approximated load-settlement curve occurs. How ever, the point of maximum curvature is a variable depending on the units and scales of the load and settlement. Therefore, to obtain a unique maximum curvature point, both the load and settlement must be normalized by proper parameters, respectively, and be expressed on the same scaled arses(1:1). Normalization has been processed so that the yield load by the new interpretation is to be close to the average of yield loads interpreted by other methods investigated in this study. The quantitative comparison between the new criterion and other conventitonal methods is presented.

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Data Cleaning and Integration of Multi-year Dietary Survey in the Korea National Health and Nutrition Examination Survey (KNHANES) using Database Normalization Theory (데이터베이스 정규화 이론을 이용한 국민건강영양조사 중 다년도 식이조사 자료 정제 및 통합)

  • Kwon, Namji;Suh, Jihye;Lee, Hunjoo
    • Journal of Environmental Health Sciences
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    • v.43 no.4
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    • pp.298-306
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    • 2017
  • Objectives: Since 1998, the Korea National Health and Nutrition Examination Survey (KNHANES) has been conducted in order to investigate the health and nutritional status of Koreans. The food intake data of individuals in the KNHANES has also been utilized as source dataset for risk assessment of chemicals via food. To improve the reliability of intake estimation and prevent missing data for less-responded foods, the structure of integrated long-standing datasets is significant. However, it is difficult to merge multi-year survey datasets due to ineffective cleaning processes for handling extensive numbers of codes for each food item along with changes in dietary habits over time. Therefore, this study aims at 1) cleaning the process of abnormal data 2) generation of integrated long-standing raw data, and 3) contributing to the production of consistent dietary exposure factors. Methods: Codebooks, the guideline book, and raw intake data from KNHANES V and VI were used for analysis. The violation of the primary key constraint and the $1^{st}-3rd$ normal form in relational database theory were tested for the codebook and the structure of the raw data, respectively. Afterwards, the cleaning process was executed for the raw data by using these integrated codes. Results: Duplication of key records and abnormality in table structures were observed. However, after adjusting according to the suggested method above, the codes were corrected and integrated codes were newly created. Finally, we were able to clean the raw data provided by respondents to the KNHANES survey. Conclusion: The results of this study will contribute to the integration of the multi-year datasets and help improve the data production system by clarifying, testing, and verifying the primary key, integrity of the code, and primitive data structure according to the database normalization theory in the national health data.