• 제목/요약/키워드: The types of error

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신뢰타원에 의한 삼변망의 오차해석 (Error Analysis of Trilateration Network by Confidence Ellipse)

  • 백은기;구재동
    • 한국측량학회지
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    • 제13권1호
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    • pp.13-20
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    • 1995
  • 수평위치 결정에서 오차해석은 중요하다. 오차해석의 경우 표준오차타원이 정밀도의 척도로써 사용되나, 오차한계의 설정이나 측정치의 합격기준과 상대오차를 비교하는데 한계가 있어, 캐나다나 미국에서는 작업규정 에 95%신뢰타원을 오차한계로 설정하고 있다. 본 연구에서는 수평위치 결정시 신뢰타원을 오차해석에 적용하여 분석하였다. 최소제곱법과 오차해석이론에 대해 검토하였으며 , 컴퓨터 프로그램으로 E.D.M 삼변망에 대해 오차분석을 하였다. 본 연구결과 오차한계의 설정 , 측정치의 합격기준, 상대오차를 비교할 때 95%신뢰타원이 합리적이므로 작업규정에 95%신뢰타원을 도입하는 것이 필요하다. 또한 경제성있는 최적망 설계를 위해 측량망의 예비분석에도 95%신뢰타원이 효과적으로 적용될 수 있다고 사료된다.

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3차원 안면자동분석 사상체질진단기의 Hardware 오차분석 (An Error Analysis of the 3D Automatic Face Recognition Apparatus (3D-AFRA) Hardware)

  • 곽창규;석재화;송정훈;김현진;황민우;유정희;고병희;김종원;이의주
    • 사상체질의학회지
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    • 제19권2호
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    • pp.22-29
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    • 2007
  • 1. Objectives Sasang Contitutional Medicine, a part of the traditional Korean medical lore, treats illness through a constitutional typing system that categorizespeople into four constitutional types. A few of the important criteria for differentiating the constitutional types are external appearances, inner state of mind, and pathological patterns. We had been developing a 3D Automatic Face Recognition Apparatus (3D-AFRA) in order to evaluate the external appearances with more objectivity. This apparatus provides a 3D image and numerical data on facial configuration, and this study aims to evaluate the mechanical accuracy of the 3D-AFRA hardware. 2. Methods Several objects of different shapes (cube, cylinder, cone, pyramid) were each scanned 10 times using the 3D Automatic Face Recognition Apparatus (3D-AFRA). The results were then compared and analyzed with data retrieved through a laser scanner known for its high accuracy. The error rates were analyzed for each grid point of facial contour scanned with Rapidform2006 (Rapidform2006 is a 3D scanning software that collects grid point data for contours of various products and products and product parts through 3D scanners and other 3D measuring devices; the grid point data thusly acquired is then used to reconstruct highly precise polygon and curvature models). 3. Results and Conclusions The average error rate was 0.22mm for the cube, 0.22mm for the cylinder, 0.125mm for the cone, and 0.172mm for the pyramid. The visual data comparing error rates for measurement figures retrieved with Rapidform2006 is shown in $Fig.3{\sim}Fig.6$. Blue tendency indicates smaller error rates, while red indicates greater error rates The protruding corners of the cube display red, indicating greater error rates. The cylinder shows greater error rates on the edges. The pyramid displays greater error rates on the base surface and around the vertex. The cone also shows greater error around the protruding edge.

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깊은신경망을 이용한 회전객체 분류 연구 (A Study on Rotating Object Classification using Deep Neural Networks)

  • 이용규;이일병
    • 한국지능시스템학회논문지
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    • 제25권5호
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    • pp.425-430
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    • 2015
  • 본 논문은 딥러닝 알고리즘을 적용한 깊은신경망을 이용하여 회전 객체의 분류 효율성을 높이기 위한 연구이다. 회전객체의 분류 실험을 위하여 데이터는 COIL-20을 사용하며 객체의 2/3영역을 학습시키고 1/3영역을 유추하여 분류한다. 연구에 이용된 3가지 분류기는 주성분 분석법을 이용해 데이터의 차원을 축소하면서 특징값을 추출하고 유클리디안 거리를 이용하여 분류하는 PCA분류기와 오류역전파 알고리즘을 이용하여 오류 에너지를 줄여가는 방식의 MLP분류기, 마지막으로 pre-training을 통하여 학습데이터의 관찰될 확률을 높여주고 fine-tuning으로 오류에너지를 줄여가는 방식의 딥러닝을 적용한 DBN분류기이다. 깊은신경망의 구조별 오류율을 확인하기 위하여 은닉층의 개수와 은닉뉴런의 개수를 변경해가며 실험하고 실제로 가장 낮은 오류율을 나타내는 구조를 기술한다. 가장 낮은 오류율을 보였던 분류기는 DBN을 이용한 분류기이다. 은닉층을 2개 갖는 깊은신경망의 구조로 매개 변수들을 인식에 도움이 되는 곳으로 이동 시켜 높은 인식률을 보여줬다.

미래 작물생산량 추정을 위한 EPIC 모형의 국내 적용과 평가 (Assessing the EPIC Model for Estimation of Future Crops Yield in South Korea)

  • 임철희;이우균;송용호;엄기철
    • 한국기후변화학회지
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    • 제6권1호
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    • pp.21-31
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    • 2015
  • Various crop models have been extensively used for estimation of the crop yields. Compared to the other models, the EPIC model uses a unified approach to simulate more than 100 types of crops. It has been successfully applied in simulating crop yields for various combinations of weather conditions, soil properties, crops, and management schemes in many countries. The objective of this study was to estimate the rice and maize yield in South Korea using the EPIC model. The input datasets for the 30 types in the 11 categories were created for the EPIC model. The EPIC model simulated rice and maize yields. The performance of the EPIC model was evaluated with the goodness-of-fit measures including Root Mean Square Error (RMSE), Relative Error (RE), Nash-Sutcliffe Efficiency Coefficient (NSEC), Mean Absolute Error (MAE), and Pearson Correelation Coefficient (r). The rice yield showed to more high accuracy than maize yield on four type of method without NSEC. Theses results showed that the EPIC model better simulated rice yields than maize yields. The results suggest that the EPIC crop model can be useful to estimate crop yield in South Korea.

Twitter를 활용한 기상예보서비스에 대한 사용자들의 만족도 분석 (Public Satisfaction Analysis of Weather Forecast Service by Using Twitter)

  • 이기광
    • 산업경영시스템학회지
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    • 제41권2호
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    • pp.9-15
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    • 2018
  • This study is intended to investigate that it is possible to analyze the public awareness and satisfaction of the weather forecast service provided by the Korea Meteorological Administration (KMA) through social media data as a way to overcome limitations of the questionnaire-based survey in the previous research. Sentiment analysis and association rule mining were used for Twitter data containing opinions about the weather forecast service. As a result of sentiment analysis, the frequency of negative opinions was very high, about 75%, relative to positive opinions because of the nature of public services. The detailed analysis shows that a large portion of users are dissatisfied with precipitation forecast and that it is needed to analyze the two kinds of error types of the precipitation forecast, namely, 'False alarm' and 'Miss' in more detail. Therefore, association rule mining was performed on negative tweets for each of these error types. As a result, it was found that a considerable number of complaints occurred when preventive actions were useless because the forecast predicting rain had a 'False alarm' error. In addition, this study found that people's dissatisfaction increased when they experienced inconveniences due to either unpredictable high winds and heavy rains in summer or severe cold in winter, which were missed by weather forecast. This study suggests that the analysis of social media data can provide detailed information about forecast users' opinion in almost real time, which is impossible through survey or interview.

FEM을 이용한 유정압테이블의 운동정밀도 해서(1. 단면지지형 테이블의 해석 및 실험적 검증) (Finite Element Analysis on the Motion Accuracy of Hydrostatic Table(1.st. Analysis and Experimental Verification on Single-side Table))

  • 박천홍;정재훈;이후상;김수태
    • 한국정밀공학회지
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    • 제17권12호
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    • pp.137-144
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    • 2000
  • In order to achieve systematical method for improving motion accuracy of hydrostatic table, an algorithm using finite element method is proposed in this paper. Quantification of averaging effect of oil film on motion error is performed theoretically by analysis on the relationship between spacial frequency of rail form error and motion error of table. Influences of film stiffness and pocket size on the motion error of table are also analyzed theoretically. Validity of the algorithm is verified experimentally from the test on the motion error of table with three types of rail which have different form profile. Experimental results show that the algorithm is very effective to analyze theoretically the motion error of hydrostatic table.

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Basis Set Superposition Error on Structures and Complexation Energies of Organo-Alkali Metal Iodides

  • Kim, Chang-Kon;Zhang, Hui;Yoon, Sung-Hoon;Won, Jon-Gok;Kim, Chan-Kyung
    • Bulletin of the Korean Chemical Society
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    • 제31권8호
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    • pp.2228-2234
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    • 2010
  • Theoretical studies have been performed to study the binding characteristics of the alkali metal iodides, M-I (M = Li, Na, K), to poly(ethylene oxide) (PEO, I), poly(ethylene amine) (PEA, II) and poly(ethylene N-methylamine) (PEMA, III) via the B3LYP method. In this study, two types of complexes, singly-coordinated systems (SCS) and doubly-coordinated systems (DCS), were considered, and dissociation energies (${\Delta}E_D$) were calculated both with and without basis set superposition error (BSSE). Two types of counterpoise (CP) approach were investigated in this work, but the ${\Delta}E_D$ values corrected by using the function CP (fCP) correction exhibited an unusual trend in some cases due to deformation of the sub-units. This problem was solved by including geometry relaxation in the CP-corrected (GCP) interaction energy. On the other hand, the effects of the BSSE on the structures were very small when the complexes were re-optimized on the CP-corrected (RCP) potential energy surface (PES), even if the bond lengths between X and $M^+$ ($d_{{X-M}^+}$) and between $M^+$ and $I^-$ ($d_{M^+-I^-}$) were slightly lengthened. Therefore, neither the GCP nor RCP corrections made much difference to the dissociation energies.

대학에서의 영어 말하기 오류수정 피드백과 학습자 반응: 교사와 학습자의 태도를 중심으로 (An analysis of corrective feedback and learner uptake in college EFL class: With a focus on teachers' and learners' attitude)

  • 김나연;이은주
    • 영어어문교육
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    • 제15권4호
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    • pp.237-264
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    • 2009
  • The present study explores patterns of teachers' corrective feedback and learners' uptake in Korean EFL undergraduate classroom setting. It also examines consistencies and discrepancies in the perception of corrective feedback by teachers and learners. Teachers' and learners' preferences and perception of corrective feedback are further analyzed to determine whether or not those differ from actual practices in English language learning classrooms. The results of the study are as follows. First of all, teachers' corrective feedback type varied according to the learners' error type and English proficiency level. There was a lack of consistency between the teachers' feedback practices and the learners' error types. Second, for the phonological errors, learners' data witnessed the most frequent uptake on recast. For the other error types, however, the learners' uptake rates were high for the explicit corrective feedback. Third, the teachers' explicit knowledge of corrective feedback was rather low and the preferences differed from teacher to teacher. The teachers' feedback perception and preferences did not consistently reflect their actual practices. Finally, patterns of the learners' expectations of corrective feedback varied according to learners' proficiency level. Teachers' and learners' expectations of corrective feedback were also compared and some mismatches were detected.

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Effects of Corpus Use on Error Identification in L2 Writing

  • Yoshiho Satake
    • 아시아태평양코퍼스연구
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    • 제4권1호
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    • pp.61-71
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    • 2023
  • This study examines the effects of data-driven learning (DDL)-an approach employing corpora for inductive language pattern learning-on error identification in second language (L2) writing. The data consists of error identification instances from fifty-five participants, compared across different reference materials: the Corpus of Contemporary American English (COCA), dictionaries, and no use of reference materials. There are three significant findings. First, the use of COCA effectively identified collocational and form-related errors due to inductive inference drawn from multiple example sentences. Secondly, dictionaries were beneficial for identifying lexical errors, where providing meaning information was helpful. Finally, the participants often employed a strategic approach, identifying many simple errors without reference materials. However, while maximizing error identification, this strategy also led to mislabeling correct expressions as errors. The author has concluded that the strategic selection of reference materials can significantly enhance the effectiveness of error identification in L2 writing. The use of a corpus offers advantages such as easy access to target phrases and frequency information-features especially useful given that most errors were collocational and form-related. The findings suggest that teachers should guide learners to effectively use appropriate reference materials to identify errors based on error types.

최소자승법을 이용한 적응형 데이터 윈도우의 거리계전 알고리즘 (Distance Relaying Algorithm Based on An Adaptive Data Window Using Least Square Error Method)

  • 정호성;최상열;신명철
    • 대한전기학회논문지:전력기술부문A
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    • 제51권8호
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    • pp.371-378
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    • 2002
  • This paper presents the rapid and accurate algorithm for fault detection and location estimation in the transmission line. This algorithm uses wavelet transform for fault detection and harmonics elimination and utilizes least square error method for fault impedance estimation. Wavelet transform decomposes fault signals into high frequence component Dl and low frequence component A3. The former is used for fault phase detection and fault types classification and the latter is used for harmonics elimination. After fault detection, an adaptive data window technique using LSE estimates fault impedance. It can find a optimal data window length and estimate fault impedance rapidly, because it changes the length according to the fault disturbance. To prove the performance of the algorithm, the authors test relaying signals obtained from EMTP simulation. Test results show that the proposed algorithm estimates fault location within a half cycle after fault irrelevant to fault types and various fault conditions.