• 제목/요약/키워드: Data validation

검색결과 3,255건 처리시간 0.031초

Deformable image registration in radiation therapy

  • Oh, Seungjong;Kim, Siyong
    • Radiation Oncology Journal
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    • 제35권2호
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    • pp.101-111
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    • 2017
  • The number of imaging data sets has significantly increased during radiation treatment after introducing a diverse range of advanced techniques into the field of radiation oncology. As a consequence, there have been many studies proposing meaningful applications of imaging data set use. These applications commonly require a method to align the data sets at a reference. Deformable image registration (DIR) is a process which satisfies this requirement by locally registering image data sets into a reference image set. DIR identifies the spatial correspondence in order to minimize the differences between two or among multiple sets of images. This article describes clinical applications, validation, and algorithms of DIR techniques. Applications of DIR in radiation treatment include dose accumulation, mathematical modeling, automatic segmentation, and functional imaging. Validation methods discussed are based on anatomical landmarks, physical phantoms, digital phantoms, and per application purpose. DIR algorithms are also briefly reviewed with respect to two algorithmic components: similarity index and deformation models.

근적외분광분석법을 사용한 암브록솔 정제의 비파괴적 정량분석 (Nondestructive Quantification of Intact Ambroxol Tablet using Near-infrared Spectroscopy)

  • 임현량;우영아;김도형;김효진;강신정;최현철;최한곤
    • 약학회지
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    • 제48권1호
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    • pp.60-64
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    • 2004
  • Near-infrared (NIR) spectroscopy was used to determine rapidly and nondestructively the content of ambroxol in intact ambroxol tablets containing 30 mg (12.5% m/m nominal concentration) by collecting NIR spectra in range 1100-1750 nm. The laboratory-made samples had 10.3∼15.9% m/m nominal ambroxol concentration. The measurements were made by reflection using a fiber-optic probe and calibration was carried out by partial least square regression (PLSR) with autoscaling. Model validation was performed by randomly splitting the data set into calibration and validation data set (7 samples as a calibration data set and 5 samples as a validation data set). The developed NIR method gave results comparable to the known values of tablets in a laboratorial manufacturing Process, standard error of calibration (SEC) and standard error of prediction (SEP) being 0.49% and 0.49% m/m respectively. The method showed good accuracy and repeatability NIR spectroscopic determination in intact tablets allowed the potential use of real time monitoring for a running production process.

Header Data Interpreting S/W Design for MSC(Multi-Spectral Camera) image data

  • Kong Jong-Pil;Heo Haeng-Pal;Kim YoungSun;Park Jong-Euk;Youn Heong-Sik
    • 대한원격탐사학회:학술대회논문집
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    • 대한원격탐사학회 2004년도 Proceedings of ISRS 2004
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    • pp.436-439
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    • 2004
  • Output data streams of the MSC contain flags, Headers and image data according to the established protocols and data formats. Especially the Header added to each data lines contain information of a line sync, a line counter and, ancillary data which consist of ancillary identification bit and one ancillary data byte. This information is used by ground station to calculate the geographic coordinates of the image and get the on-board time and several EOS(Electro-Optical Subsystem) parameters used at the time of imaging. Therefore, the EGSE(Electrical Ground Supporting Equipment) that is used for testing MSC has to have functions of interpreting and displaying this Header information correctly following the protocols. This paper describes the design of the header data processing module which is in EOS­EGSE. This module provides users with various test functions such as header validation, ancillary block validation, line-counter and In-line counter validation checks which allow convenient and fast test on imagery data.

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Satellite data validation system using RC helicopter

  • Honda, Yoshiaki;Kajiwara, Koji
    • 대한원격탐사학회:학술대회논문집
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    • 대한원격탐사학회 2002년도 Proceedings of International Symposium on Remote Sensing
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    • pp.746-749
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    • 2002
  • This paper is introducing a radio control helicopter as a new platform of ground truth measurement. This helicopter is normally used for spraying an agricultural chemical. It can do pinpoint hovering and programing flight using DGPS etc., A spectrometer with dual port can measure ground surface and white reference plate at the same time. And it can also take digital images by digital camera. It is needed to collect ground reflectance information as satellite sensor footprint size for satellite data validation. Generally it is possible to get such ground reflectance by an airplane measurement. But it is high cost and not so easy to make a measurement by airplane. Developed validation system can provide such ground reflectance in low cost and easy.

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Estimating Prediction Errors in Binary Classification Problem: Cross-Validation versus Bootstrap

  • Kim Ji-Hyun;Cha Eun-Song
    • Communications for Statistical Applications and Methods
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    • 제13권1호
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    • pp.151-165
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    • 2006
  • It is important to estimate the true misclassification rate of a given classifier when an independent set of test data is not available. Cross-validation and bootstrap are two possible approaches in this case. In related literature bootstrap estimators of the true misclassification rate were asserted to have better performance for small samples than cross-validation estimators. We compare the two estimators empirically when the classification rule is so adaptive to training data that its apparent misclassification rate is close to zero. We confirm that bootstrap estimators have better performance for small samples because of small variance, and we have found a new fact that their bias tends to be significant even for moderate to large samples, in which case cross-validation estimators have better performance with less computation.

Validation of Loads Analysis for a Slowed Rotor at High Advance Ratios

  • Park, Jae-Sang
    • International Journal of Aeronautical and Space Sciences
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    • 제18권3호
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    • pp.498-511
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    • 2017
  • This work conducts a validation study for loads analysis of the UH-60A slowed rotor at high advance ratios. The nonlinear flexible multibody dynamics analysis code, DYMORE II, is used with a freewake model for the rotorcraft comprehensive analysis. Wind tunnel test data of airloads and structural loads of a full-scale UH-60A slowed rotor are used for this validation study. This analysis predicts well the thrust reversal phenomenon at the advance ratio of 1.0. The section airloads such as normal forces and pitching moments and the oscillatory blade structural moments in this analysis are compared well or moderately with the measured data, although the higher harmonics components of blade torsion moments are not captured well. This validation study assesses the prediction accuracy and investigates the unique aeromechanics characteristics of a slowed rotor at high advance ratio.

Computation and Smoothing Parameter Selection In Penalized Likelihood Regression

  • Kim Young-Ju
    • Communications for Statistical Applications and Methods
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    • 제12권3호
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    • pp.743-758
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    • 2005
  • This paper consider penalized likelihood regression with data from exponential family. The fast computation method applied to Gaussian data(Kim and Gu, 2004) is extended to non Gaussian data through asymptotically efficient low dimensional approximations and corresponding algorithm is proposed. Also smoothing parameter selection is explored for various exponential families, which extends the existing cross validation method of Xiang and Wahba evaluated only with Bernoulli data.

크라우드소싱 드론 영상의 기하학적 품질 자동 검증 (Automatic Validation of the Geometric Quality of Crowdsourcing Drone Imagery)

  • 이동호;최경아
    • 대한원격탐사학회지
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    • 제39권5_1호
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    • pp.577-587
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    • 2023
  • 크라우드소싱(crowdsourcing) 공간 데이터 활용 연구가 활발히 진행되고 있으나 데이터 품질의 불확실성으로 인한 문제점이 제기되고 있다. 특히 드론 영상 데이터셋에 품질이 낮은 데이터가 포함될 경우, 출력되는 공간 정보의 품질이 저하될 수 있다. 이를 위해 본 연구에서는 크라우드소싱된 영상의 기하학적 품질을 자동으로 검증하는 방법론을 제안하였다. 주요 품질 요소로는 영상의 공간해상도, 해상도 변화량, 매칭점 재투영 오차, 번들 조정 결과 등을 입력변수로 활용하였다. 공간 정보 생성에 적합한 영상을 분류하기 위해 학습 및 검증 데이터를 구축하고, radial basis function (RBF) 기반의 support vector machine (SVM) 모델로 학습을 진행하였다. 학습된 SVM 모델의 분류 정확도는 99.1%를 기록하였다. 품질 검증 모델 효과를 확인하기 위해 학습 및 검증에 사용하지 않은 드론 영상에 대하여 해당 모델을 적용하기 전후의 영상 데이터셋으로 각각 정사영상을 생성하고 비교하였다. 그 결과 모델 적용을 통하여 정사영상에 포함될 수 있는 다양한 왜곡을 줄이고 객체 식별력을 증대시키는 것을 확인하였다. 제안된 품질 검증 방법론은 다양한 품질의 크라우드소싱 데이터를 입력으로 받아 양질의 정보만을 자동 선별하게 함으로써 공간정보 생성에서의 활용 가능성을 증대시킬 것으로 기대한다.

DARC 기반에서의 실시간 인증서 유효성 검증에 관한 연구 (A Study on the Realtime Cert-Validation of Certification based on DARC)

  • 장흥종;이성은;이정현
    • 정보처리학회논문지C
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    • 제8C권5호
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    • pp.517-524
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    • 2001
  • 공개키 기반 인증시스템에서 사용자의 실수로 비밀키가 노출되었거나 자격의 박탈, 유효기간 만료 등의 이유로 인증서를 폐지해야 할 경우가 있다. 이에 따라서 각 사용자는 수신한 인증서가 유효한 것인지를 확인해야만 한다. 이 인증서 폐지 여부를 확인하는 방법으로는 CRL. Delta- CRL, OCSP 등의 방식이 개발되었다. 하지만 이 모든 방식에서의 인증서 유효성 검증은 실시간으로 처리해야 하므로 많은 통신량을 발생시키는 문제점을 가지고 있다. 본 논문에서는 CRL관리의 문제점인 전송시점 차이에 따른 무결성 문제와 실시간 처리로 인한 서버와 네트웍의 과도한 트래픽 발생을 해결한 DARC(DAta Radio Channel)를 이용한 효율적인 CRL 구축 방안을 제안하였다.

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CROSS-VALIDATION OF ARTIFICIAL NEURAL NETWORK FOR LANDSLIDE SUSCEPTIBILITY ANALYSIS: A CASE STUDY OF KOREA

  • LEE SARO;LEE MOUNG-JIN;WON JOONG-SUN
    • 대한원격탐사학회:학술대회논문집
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    • 대한원격탐사학회 2004년도 Proceedings of ISRS 2004
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    • pp.298-301
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    • 2004
  • The aim of this study is to cross-validate of spatial probability model, artificial neural network at Boun, Korea, using a Geographic Information System (GIS). Landslide locations were identified in the Boun, Janghung and Youngin areas from interpretation of aerial photographs, field surveys, and maps of the topography, soil type, forest cover and land use were constructed to spatial data-sets. The factors that influence landslide occurrence, such as slope, aspect and curvature of topography, were calculated from the topographic database. Topographic type, texture, material, drainage and effective soil thickness were extracted from the soil database, and type, diameter, age and density of forest were extracted from the forest database. Lithology was extracted from the geological database, and land use was classified from the Landsat TM image satellite image. Landslide susceptibility was analyzed using the landslide­occurrence factors by artificial neural network model. For the validation and cross-validation, the result of the analysis was applied to each study areas. The validation and cross-validate results showed satisfactory agreement between the susceptibility map and the existing data on landslide locations.

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