• Title/Summary/Keyword: set-up accuracy

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Accuracy improvement of laser interferometer with neural network (신경회로망을 이용한 레이저 간섭계 정밀도 향상)

  • Lee, Woo-Ram;Heo, Gun-Hang;Hong, Min-Suk;Choi, In-Sung;You, Kwan-Ho
    • Proceedings of the KIEE Conference
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    • 2006.10c
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    • pp.597-599
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    • 2006
  • In this paper, we propose an artificial intelligence method to compensate the nonlinearity error which occurs in the heterodyne laser interferometer. Some superior properties such as long measurement range, ultra-precise resolution and various system set-up lead the laser interferometer to be a practical displacement measurement apparatus in various industry and research area. In ultra-precise measurement such as nanometer or subnanometer scale, however, the accuracy is limited by the nonlinearity error caused by the optical parts. The feedforward neural network trained by back-propagation with a capacitive sensor as a reference signal minimizes the nonlinearity error and we demonstrate the effectiveness of our proppsed algorithm through some experimental results.

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Evaluation of Attribute Selection Methods and Prior Discretization in Supervised Learning

  • Cha, Woon Ock;Huh, Moon Yul
    • Communications for Statistical Applications and Methods
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    • v.10 no.3
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    • pp.879-894
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    • 2003
  • We evaluated the efficiencies of applying attribute selection methods and prior discretization to supervised learning, modelled by C4.5 and Naive Bayes. Three databases were obtained from UCI data archive, which consisted of continuous attributes except for one decision attribute. Four methods were used for attribute selection : MDI, ReliefF, Gain Ratio and Consistency-based method. MDI and ReliefF can be used for both continuous and discrete attributes, but the other two methods can be used only for discrete attributes. Discretization was performed using the Fayyad and Irani method. To investigate the effect of noise included in the database, noises were introduced into the data sets up to the extents of 10 or 20%, and then the data, including those either containing the noises or not, were processed through the steps of attribute selection, discretization and classification. The results of this study indicate that classification of the data based on selected attributes yields higher accuracy than in the case of classifying the full data set, and prior discretization does not lower the accuracy.

A Swing-Arm On-Machine Inspection Method for Profile Measurement of Large Optical Surface in Lapping Process

  • Sung In Kyoung;Oh Chang Jin;Lee Eung Suk;Kim Ock Hyun
    • Journal of Mechanical Science and Technology
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    • v.19 no.8
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    • pp.1576-1581
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    • 2005
  • Generally, the optical components are fabricated by grinding, lapping, and polishing. And, those processes take long time to obtain such a high surface quality. Therefore, in the case of large optical component, the on-machine inspection (OMI) is essential. Because, the work piece is fragile and difficult to set up for fabricating and measuring. This paper is concerned about a swing-arm method for measuring surface profile of large optical concave mirror. The measuring accuracy and uncertainty for suggested method are studied. The experimental results show that this method is useful specially in lapping process with the accuracy of $3\~5\;{\mu}m$. Those inspection data are provided for correcting the residual figuring error in lapping or polishing processes.

A Study on Deep Reinforcement Learning Framework for DME Pulse Design

  • Lee, Jungyeon;Kim, Euiho
    • Journal of Positioning, Navigation, and Timing
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    • v.10 no.2
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    • pp.113-120
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    • 2021
  • The Distance Measuring Equipment (DME) is a ground-based aircraft navigation system and is considered as an infrastructure that ensures resilient aircraft navigation capability during the event of a Global Navigation Satellite System (GNSS) outage. The main problem of DME as a GNSS back up is a poor positioning accuracy that often reaches over 100 m. In this paper, a novel approach of applying deep reinforcement learning to a DME pulse design is introduced to improve the DME distance measuring accuracy. This method is designed to develop multipath-resistant DME pulses that comply with current DME specifications. In the research, a Markov Decision Process (MDP) for DME pulse design is set using pulse shape requirements and a timing error. Based on the designed MDP, we created an Environment called PulseEnv, which allows the agent representing a DME pulse shape to explore continuous space using the Soft Actor Critical (SAC) reinforcement learning algorithm.

Assessment of Flash Flood Forecasting based on SURR model using Predicted Radar Rainfall in the TaeHwa River Basin

  • Duong, Ngoc Tien;Heo, Jae-Yeong;Kim, Jeong-Bae;Bae, Deg-Hyo
    • Proceedings of the Korea Water Resources Association Conference
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    • 2022.05a
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    • pp.146-146
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    • 2022
  • A flash flood is one of the most hazardous natural events caused by heavy rainfall in a short period of time in mountainous areas with steep slopes. Early warning of flash flood is vital to minimize damage, but challenges remain in the enhancing accuracy and reliability of flash flood forecasts. The forecasters can easily determine whether flash flood is occurred using the flash flood guidance (FFG) comparing to rainfall volume of the same duration. In terms of this, the hydrological model that can consider the basin characteristics in real time can increase the accuracy of flash flood forecasting. Also, the predicted radar rainfall has a strength for short-lead time can be useful for flash flood forecasting. Therefore, using both hydrological models and radar rainfall forecasts can improve the accuracy of flash flood forecasts. In this study, FFG was applied to simulate some flash flood events in the Taehwa river basin by using of SURR model to consider soil moisture, and applied to the flash flood forecasting using predicted radar rainfall. The hydrometeorological data are gathered from 2011 to 2021. Furthermore, radar rainfall is forecasted up to 6-hours has been used to forecast flash flood during heavy rain in August 2021, Wulsan area. The accuracy of the predicted rainfall is evaluated and the correlation between observed and predicted rainfall is analyzed for quantitative evaluation. The results show that with a short lead time (1-3hr) the result of forecast flash flood events was very close to collected information, but with a larger lead time big difference was observed. The results obtained from this study are expected to use for set up the emergency planning to prevent the damage of flash flood.

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Performance Evaluation of Radial Error of a Rotary Table at Five-axis Machine Tool (5축 공작기계에서 회전 테이블의 반경 오차 성능 평가)

  • Lee, Kwang-Il;Yang, Seung-Han
    • Journal of the Korean Society of Manufacturing Technology Engineers
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    • v.21 no.2
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    • pp.208-213
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    • 2012
  • In this paper, the radial error of a rotary table at five-axis machine tool is evaluated by utilizing ISO 230-2 and estimation method using double ball-bar. The geometric error of a rotary table is defined as position dependent geometric errors or position independent geometric errors according to their physical character. Then estimation method of geometric errors using double ball-bar is simply summarized including measurement path, parametric modeling and least squares approach. To estimate representative radial error, offset error, set-up error which affect to the double ball-bar data, mean value of measured data including CCW/CW-direction are used at estimation process. Radial errors are separated from measured data and used for evaluation with ISO 230-2. Finally, suggested evaluation method is applied to a rotary table at five-axis machine tool and its result is analyzed to improve the accuracy of the rotary table.

Real-time Location Tracking System Using Ultrasonic Wireless Sensor Nodes (초음파 무선 센서노드를 이용한 실시간 위치 추적 시스템)

  • Park, Jong-Hyun;Choo, Young-Yeol
    • Journal of Institute of Control, Robotics and Systems
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    • v.13 no.7
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    • pp.711-717
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    • 2007
  • Location information will become increasingly important for future Pervasive Computing applications. Location tracking system of a moving device can be classified into two types of architectures: an active mobile architecture and a passive mobile architecture. In the former, a mobile device actively transmits signals for estimating distances to listeners. In the latter, a mobile device listens signals from beacons passively. Although the passive architecture such as Cricket location system is inexpensive, easy to set up, and safe, it is less precise than the active one. In this paper, we present a passive location system using Cricket Mote sensors which use RF and ultrasonic signals to estimate distances. In order to improve accuracy of the passive system, the transmission speed of ultrasound was compensated according to air temperature at the moment. Upper and lower bounds of a distance estimation were set up through measuring minimum and maximum distances that ultrasonic signal can reach to. Distance estimations beyond the upper and the lower bounds were filtered off as errors in our scheme. With collecting distance estimation data at various locations and comparing each distance estimation with real distance respectively, we proposed an equation to compensate the deviation at each point. Equations for proposed algorithm were derived to calculate relative coordinates of a moving device. At indoor and outdoor tests, average location error and average location tracking period were 3.5 cm and 0.5 second, respectively, which outperformed Cricket location system of MIT.

Content-Based Video Retrieval System Using Color and Motion Features (색상과 움직임 정보를 이용한 내용기반 동영상 검색 시스템)

  • 김소희;김형준;정연구;김회율
    • Proceedings of the IEEK Conference
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    • 2001.06c
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    • pp.133-136
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    • 2001
  • Numerous challenges have been made to retrieve video using the contents. Recently MPEG-7 had set up a set of visual descriptors for such purpose of searching and retrieving multimedia data. Among them, color and motion descriptors are employed to develop a content-based video retrieval system to search for videos that have similar characteristics in terms of color and motion features of the video sequence. In this paper, the performance of the proposed system is analyzed and evaluated. Experimental results indicate that the processing time required for a retrieval using MPEG-7 descriptors is relatively short at the expense of the retrieval accuracy.

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Modality-Based Sentence-Final Intonation Prediction for Korean Conversational-Style Text-to-Speech Systems

  • Oh, Seung-Shin;Kim, Sang-Hun
    • ETRI Journal
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    • v.28 no.6
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    • pp.807-810
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    • 2006
  • This letter presents a prediction model for sentence-final intonations for Korean conversational-style text-to-speech systems in which we introduce the linguistic feature of 'modality' as a new parameter. Based on their function and meaning, we classify tonal forms in speech data into tone types meaningful for speech synthesis and use the result of this classification to build our prediction model using a tree structured classification algorithm. In order to show that modality is more effective for the prediction model than features such as sentence type or speech act, an experiment is performed on a test set of 970 utterances with a training set of 3,883 utterances. The results show that modality makes a higher contribution to the determination of sentence-final intonation than sentence type or speech act, and that prediction accuracy improves up to 25% when the feature of modality is introduced.

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Comparative studies of density functionals in modelling hydrogen bonding energetics of acrylamide dimers

  • Lin, Yi-De;Wang, Yi-Siang;Chao, Sheng D.
    • Coupled systems mechanics
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    • v.6 no.3
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    • pp.369-376
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    • 2017
  • Intermolecular interaction energies and conformer geometries of the hydrogen bonded acrylamide dimers have been studied by using the second-order Møller-Plesset (MP2) perturbation theory and the density functional theory (DFT) with 17 density functionals. Dunning's correlation consistent basis sets (up to aug-cc-pVTZ) have been used to study the basis set effects. The DFT calculated interaction energies are compared to the reference energy data calculated by the MP2 method and the coupled cluster method at the complete basis set (CCSD(T)/CBS) limit in order to determine the relative performance of the studied density functionals. Overall, dispersion-energy-corrected density functionals outperform uncorrected ones. The ${\omega}B97XD$ density functional is particularly effective in terms of both accuracy and computational cost in estimating the reference energy values using small basis sets and is highly recommended for similar calculations for larger systems.