• Title/Summary/Keyword: Accuracy Rate

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Region Growing Method for Calculating Unmeasured Rate of Aerial LiDAR Data (항공라이다의 결측률 산출을 위한 영역확장 기법)

  • Han, Soung-Man;Kim, Ji-Yong
    • Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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    • v.28 no.1
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    • pp.29-38
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    • 2010
  • The airborne LiDAR which was introduced in the early 2000's provides the point data. The new methods for the verification of LiDAR materials with high accuracy which is different from the existing airborne survey are needed. In accordance with the rules of airborne laser survey which were enacted in 2009, the verifications by three methods of Unmeasured Rate and point accuracy, point density have been executed, and Unmeasured Rate is to evaluate the rate for the presence of points within uniform grids except non-reflective areas such as watershed areas. For the calculation of Unmeasured Rate, non-reflective areas should be removed by all means, and in case of normal LiDAR materials, as there are scant points for watershed areas, watershed areas should be divided by additional spatial information. So, in this study, the watershed areas were extracted using domain extension technique from the high resolution CIR images of 0.3m grade. In addition, in order to compare the accuracy of Unmeasured Rate calculated, the comparative analysis of the Unmeasured Rate calculated by digital maps has been done. In conclusion, we found that 1I1e accuracy of Unmeasured Rate extracted by domain extension technique is similar to the value extracted by digitizing technique.

Analysis of Operational Availability under Changing Failure Rate and Supportability (무기체계의 고장률과 지원수준의 변화에 따른 운용가용도 변화 분석)

  • Tak, Jung Ho;Jung, Won
    • Journal of Applied Reliability
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    • v.18 no.1
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    • pp.1-7
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    • 2018
  • Purpose: Maintaining appropriate operational availability (Ao) is a key element of combat victory, but estimates vary according to estimation methods. The purpose of this study is to improve the accuracy of estimating operational availability by tracing the changes of the weapon system's failure rate, repair rate, and the level of logistic support. Methods: In order to track the change in the operating availability, the MDT (mean down time) is modeled by adding the repair time and the ALDT (administration and logistic delay time) to the service time. Results: Using the field data of the weapon system A operated by the ROKAF, the failure rate follows a non-homogeneous Poisson process that changes with time, and it is modeled considering the changing repair rate and the logistic support time. Conclusion: The accuracy of the analytical results was verified by comparing the actual operating data with the estimated availability. The results of this study can be used to track and evaluate the availability in a realistic situation where the failure rate and maintenance rate continuously change in operating environment.

A Study on the Improvement of Machining Accuracy in High Speed Machining using Design of Experiments (실험계획법을 이용한 고속가공의 가공정밀도 향상에 관한 연구)

  • 권병두;고태조;정종윤;정원지;이춘만
    • Proceedings of the Korean Society of Precision Engineering Conference
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    • 1997.10a
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    • pp.393-396
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    • 1997
  • High-speed machining is one of the most effective technologies to improve productivity. Because of the high speed and high feed rate, high-speed machining can give great advantages for the machining of dies and molds. This paper describes on the improvement of machining accuracy in high-speed machining. Depth of cut and feed rate are control factors. The effect of the control factors on machining accuracy is investigated using two-way factorial design.

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A Study on the Improvement of Machining Accuracy in High Speed Machining using Design of Experiments (실험계획법을 이용한 고속가공의 가공정밀도 향상에 관한 연구)

  • Lee, Chun-Man;Gwon, Byeong-Du;Go, Tae-Jo;Jeong, Jong-Yun;Jeong, Won-Ji
    • Journal of the Korean Society for Precision Engineering
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    • v.19 no.7
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    • pp.88-96
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    • 2002
  • High-speed machining is one of the most effective technologies to improve productivity. Because of the high speed and high feed rate, high-speed machining can give great advantages for the machining of dies and molds. This paper describes on the improvement of machining accuracy in high-speed machining. Depth of cut, feed rate and spindle revolution are control factors. The effect of the control factors on machining accuracy is investigated using two-way factorial design.

A Study on the Improvement of Machining Accuracy in High Speed Machining of STD11 (STD11 금형강의 고속가공에서 가공정밀도 향상에 관한 연구)

  • 이춘만;최치혁;정원지;정종윤;고태조;김태형
    • Proceedings of the Korean Society of Machine Tool Engineers Conference
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    • 2002.10a
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    • pp.329-334
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    • 2002
  • High-speed machining is one of the most effective technology to improve productivity. Because of the high speed and high feed rate, high-speed machining can give great advantages for the machining of dies and molds. This paper describes on the improvement of machining accuracy in high-speed machining. Depth of cut, feed rate, spindle revolution and cutting force are control factors. The effect of the control factors on machining accuracy is discussed for the results of surface roughness and machining error in Z-direction for the high speed machining of STD11.

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A Method of Bank Telemarketing Customer Prediction based on Hybrid Sampling and Stacked Deep Networks (혼성 표본 추출과 적층 딥 네트워크에 기반한 은행 텔레마케팅 고객 예측 방법)

  • Lee, Hyunjin
    • Journal of Korea Society of Digital Industry and Information Management
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    • v.15 no.3
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    • pp.197-206
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    • 2019
  • Telemarketing has been used in finance due to the reduction of offline channels. In order to select telemarketing target customers, various machine learning techniques have emerged to maximize the effect of minimum cost. However, there are problems that the class imbalance, which the number of marketing success customers is smaller than the number of failed customers, and the recall rate is lower than accuracy. In this paper, we propose a method that solve the imbalanced class problem and increase the recall rate to improve the efficiency. The hybrid sampling method is applied to balance the data in the class, and the stacked deep network is applied to improve the recall and precision as well as the accuracy. The proposed method is applied to actual bank telemarketing data. As a result of the comparison experiment, the accuracy, the recall, and the precision is improved higher than that of the conventional methods.

Fixed-accuracy confidence interval estimation of P(X > c) for a two-parameter gamma population

  • Zhuang, Yan;Hu, Jun;Zou, Yixuan
    • Communications for Statistical Applications and Methods
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    • v.27 no.6
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    • pp.625-639
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    • 2020
  • The gamma distribution is a flexible right-skewed distribution widely used in many areas, and it is of great interest to estimate the probability of a random variable exceeding a specified value in survival and reliability analysis. Therefore, the study develops a fixed-accuracy confidence interval for P(X > c) when X follows a gamma distribution, Γ(α, β), and c is a preassigned positive constant through: 1) a purely sequential procedure with known shape parameter α and unknown rate parameter β; and 2) a nonparametric purely sequential procedure with both shape and rate parameters unknown. Both procedures enjoy appealing asymptotic first-order efficiency and asymptotic consistency properties. Extensive simulations validate the theoretical findings. Three real-life data examples from health studies and steel manufacturing study are discussed to illustrate the practical applicability of both procedures.

Alternative accuracy for multiple ROC analysis

  • Hong, Chong Sun;Wu, Zhi Qiang
    • Journal of the Korean Data and Information Science Society
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    • v.25 no.6
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    • pp.1521-1530
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    • 2014
  • The ROC analysis is considered for multiple class diagnosis. There exist many criteria to find optimal thresholds and measure the accuracy of diagnostic tests for k dimensional ROC analysis. In this paper, we proposed a diagnostic accuracy measure called the correct classification simple rate, which is defined as the summation of true rates for each classification distribution and expressed as a function of summation of sequential true rates for two consecutive distributions. This measure does not weight accuracy across categories by the category prevalence and is comparable across populations for multiple class diagnosis. It is found that this accuracy measure does not only have a relationship with Kolmogorov - Smirnov statistics, but also can be represented as a linear function of some optimal threshold criteria. With these facts, the suggested measure could be applied to test for comparing multiple distributions.

Interpolation Technique to Improve the Accuracy of RR-interval in Portable ECG Device (휴대형 심전계 장치의 RR 간격의 정확도 개선을 위한 보간법 개발)

  • Lee, Eun-Mi;Hong, Joo-Hyun;Cha, Eun-Jong;Lee, Tae-Soo
    • Journal of Biomedical Engineering Research
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    • v.31 no.4
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    • pp.316-320
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    • 2010
  • HRV(Heart rate variability) analysis parameter is widely used as an index to evaluate the autonomic nervous system and cardiac function. For reliable HRV analysis, we need to acquire the accurate ECG signals. Most of commercially available portable ECG devices have low sampling rate because of low power consumption and small size issues, which make it difficult to measure RR-interval accurately. This study is to improve the accuracy of RR-interval by developing R-wave interpolation technique, based on the morphological characteristics of the QRS complex. When the developed method was applied to ECG obtained at 200 Hz and the results were compared with 1000 Hz reference device, the error range decreased by 1.33 times in sitting and by 2.38 times in cycling exercise. Therefore, the proposed interpolation technique is thought to be useful to improve the accuracy of R-R interval in the portable ECG device with low sampling rate.

A Neuro-Fuzzy Pedestrian Detection Method Using Convolutional Multiblock HOG (컨볼루션 멀티블럭 HOG를 이용한 퍼지신경망 보행자 검출 방법)

  • Myung, Kun-Woo;Qu, Le-Tao;Lim, Joon-Shik
    • The Transactions of The Korean Institute of Electrical Engineers
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    • v.66 no.7
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    • pp.1117-1122
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    • 2017
  • Pedestrian detection is a very important and valuable part of artificial intelligence and computer vision. It can be used in various areas for example automatic drive, video analysis and others. Many works have been done for the pedestrian detection. The accuracy of pedestrian detection on multiple pedestrian image has reached high level. It is not easily get more progress now. This paper proposes a new structure based on the idea of HOG and convolutional filters to do the pedestrian detection in single pedestrian image. It can be a method to increase the accuracy depend on the high accuracy in single pedestrian detection. In this paper, we use Multiblock HOG and magnitude of the pixel as the feature and use convolutional filter to do the to extract the feature. And then use NEWFM to be the classifier for training and testing. We use single pedestrian image of the INRIA data set as the data set. The result shows that the Convolutional Multiblock HOG we proposed get better performance which is 0.015 miss rate at 10-4 false positive than the other detection methods for example HOGLBP which is 0.03 miss rate and ChnFtrs which is 0.075 miss rate.