• Title/Summary/Keyword: Location prediction

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Reduction and Evaluation of Subway Induced Vibration Effects on Surrounding Buildings (지하철 운행에 의한 인접건물의 진동영향 평가 연구)

  • Park, Ji-Hun;Min, Kyung-Won;Lee, Roo-Jee;Choi, Seok-Joo;Yum, Sung-Kon
    • Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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    • 2005.05a
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    • pp.738-742
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    • 2005
  • Ground vibration at Gil-dong in Seoul induced by the 5th ling of Seoul Subway is predicted using various prediction methods and compared with measured vibration. Also, several issues on the improvement of prediction methods are discussed. Furthermore, as an alternative vibration source, measured vibration acceleration level(VAL) on the tunnel wall of the Bundang line of Seoul Subway is applied to the prediction of the VAL at the location mentioned previously. Then requirements accompanied to the suggestion of the new vibration source appropriate to the condition of Seoul Subway.

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Quantification of Acoustic Pressure Estimation Error due to Sensor and Position Mismatch in Planar Acoustic Holography (평면 음향 홀로그래피에서 센서간 특성 차이와 측정 위치의 부정확성에 의한 음압 추정 오차의 정량화)

  • 남경욱;김양한
    • Journal of KSNVE
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    • v.8 no.6
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    • pp.1023-1029
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    • 1998
  • When one attempts to construct a hologram. one finds that there are many sources of measurement errors. These errors are even amplified if one predicts the pressures close to the sources. The pressure estimation errors depend on the following parameters: the measurement spacing on the hologram plane. the prediction spacing on the prediction plane. and the distance between the hologram and the prediction plane. This raper analyzes quantitatively the errors when these are distributed irregularly on the hologram plane The sensor mismatch and inaccurate measurement location. position mismatch. are mainly addressed. In these cases. one can assume that the measurement is a sample of many measurement events. The bias and random error are derived theoretically. Then the relationship between the random error amplification ratio and the parameters mentioned above is examined quantitatively in terms of energy.

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Rapid Tidal Predictions for the Inchon Bay (인천항 조석의 신속 예보)

  • 최병호
    • Journal of Korean Society of Coastal and Ocean Engineers
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    • v.7 no.4
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    • pp.355-367
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    • 1995
  • Tidal prediction at a given location has been conventionally made by harmonic method. Another means of tidal prediction is through numerical modeling of tides. Present research focussed on whether prediction of tides and tidal currents can be made everywhere in the Inchon Bay using the numerical model directly or by harmonic constants of tides and tidal currents of the whole Bay derived from the extended model run.

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Partial Least Squares-discriminant Analysis for the Prediction of Hemodynamic Changes Using Near Infrared Spectroscopy

  • Seo, Youngwook;Lee, Seungduk;Koh, Dalkwon;Kim, Beop-Min
    • Journal of the Optical Society of Korea
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    • v.16 no.1
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    • pp.57-62
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    • 2012
  • Using continuous wave near-infrared spectroscopy, we measured time-resolved concentration changes of oxy-hemoglobin and deoxy-hemoglobin from the primary motor cortex following finger tapping tasks. These data were processed using partial least squares-discriminant analysis (PLS-DA) to develop a prediction model for a brain-computer interface. The tasks were composed of a series of finger tapping for 15 sec and relaxation for 45 sec. The location of the motor cortex was confirmed by the anti-phasic behavior of the oxy- and deoxy-hemoglobin changes. The results were compared with those obtained using the hidden Markov model (HMM) which has been known to produce the best prediction model. Our data imply that PLS-DA makes better judgments in determining the onset of the events than HMM.

Smart support system for diagnosing severe accidents in nuclear power plants

  • Yoo, Kwae Hwan;Back, Ju Hyun;Na, Man Gyun;Hur, Seop;Kim, Hyeonmin
    • Nuclear Engineering and Technology
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    • v.50 no.4
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    • pp.562-569
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    • 2018
  • Recently, human errors have very rarely occurred during power generation at nuclear power plants. For this reason, many countries are conducting research on smart support systems of nuclear power plants. Smart support systems can help with operator decisions in severe accident occurrences. In this study, a smart support system was developed by integrating accident prediction functions from previous research and enhancing their prediction capability. Through this system, operators can predict accident scenarios, accident locations, and accident information in advance. In addition, it is possible to decide on the integrity of instruments and predict the life of instruments. The data were obtained using Modular Accident Analysis Program code to simulate severe accident scenarios for the Optimized Power Reactor 1000. The prediction of the accident scenario, accident location, and accident information was conducted using artificial intelligence methods.

Development of Hybrid Methods for the Prediction of Internal Flow-Induced Noise and Its Application to Throttle Valve Noise in an Automotive Engine (내부공력소음해석기법의 개발과 자동차용 엔진 흡기 시스템의 기류음 예측을 위한 적용)

  • 정철웅;김성태;김재헌;이수갑
    • Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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    • 2003.11a
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    • pp.78-83
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    • 2003
  • General algorithm is developed for the prediction of internal flow-induced noise. This algorithm is based on the integral formula derived by using the General Green Function, Lighthills acoustic analogy and Curls extension of Lighthills. Novel approach of this algorithm is that the integral formula is so arranged as to predict frequency-domain acoustic signal at any location in a duct by using unsteady flow data in space and time, which can be provided by the Computational Fluid Dynamics Techniques. This semi-analytic model is applied to the prediction of internal aerodynamic noise from a throttle valve in an automotive engine. The predicted noise levels from the throttle valve are compared with actual measurements. This illustrative computation shows that the current method permits generalized predictions of flow noise generated by bluff bodies and turbulence in flow ducts.

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Noise Prediction and Design of Soundproof Facilities for the High Speed Train (고속열차(TGV) 주행시 연변에서의 소음예측 및 방음시설설계)

  • ;J. P. Clairbois
    • Journal of KSNVE
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    • v.9 no.6
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    • pp.1106-1115
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    • 1999
  • This paper sums up the study of the soundproof facilities (noise barriers) to be placed on the test track section within the Seoul-Pusan H.S.T. project. The objective of this study is to determine optimum design of soundproof including height, length, location, sound absorbing materials for test track(chonan-taejon). This paper shows the model to design the shape and materials of noise barrier for high speed trains(TGV, ICE, ect). The design of soundproof facilities is to be conducted by MITHRA for the prediction of noise impact of the TGV and for optimising noise barriers in order to reduce the noise generated by high speed trains. A number of computer simulations are carried out in order to determine the specification of noise barrier on test track.

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인공위성 노치예측해석 및 정현파가진시험 입력도출

  • Kim, Sung-Hoon;Kim, Jin-Hee;Hwang, Do-Soon;Lee, Ju-Hun;Jin, Ik-Min
    • Aerospace Engineering and Technology
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    • v.1 no.2
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    • pp.75-82
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    • 2002
  • This paper presents a summary of the input data, requirements and notch prediction analysis for sinusoidal excitation test of a satellite. In the notch prediction analysis, the loads at excitation points and internal loads at the important locations on satellite structure were obtained. After checking of limit loads and margin of safety for each location, the notched sinusoidal test inputs were generated using the results of the notch prediction analysis.

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Machine Learning Based Architecture and Urban Data Analysis - Construction of Floating Population Model Using Deep Learning - (머신러닝을 통한 건축 도시 데이터 분석의 기초적 연구 - 딥러닝을 이용한 유동인구 모델 구축 -)

  • Shin, Dong-Youn
    • Journal of KIBIM
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    • v.9 no.1
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    • pp.22-31
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    • 2019
  • In this paper, we construct a prototype model for city data prediction by using time series data of floating population, and use machine learning to analyze urban data of complex structure. A correlation prediction model was constructed using three of the 10 data (total flow population, male flow population, and Monday flow population), and the result was compared with the actual data. The results of the accuracy were evaluated. The results of this study show that the predicted model of the floating population predicts the correlation between the predicted floating population and the current state of commerce. It is expected that it will help efficient and objective design in the planning stages of architecture, landscape, and urban areas such as tree environment design and layout of trails. Also, it is expected that the dynamic population prediction using multivariate time series data and collected location data will be able to perform integrated simulation with time series data of various fields.

A Study on the Risk Prediction System Using System Support Load Monitoring Sensor (시스템 서포트 하중 모니터링 센서를 이용한 위험 예측시스템 연구)

  • Shim, Hak-Bo;Seok, Won-Kyun;Park, Soon-Jeon
    • Proceedings of the Korean Institute of Building Construction Conference
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    • 2020.11a
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    • pp.186-187
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    • 2020
  • Damage to temporary facilities and structural members caused by excessive loads in the field continue to occur. If the load can be monitored in advance, the risk can be prevented. In this study, a load cell sensor is installed under the system support, and load data is wirelessly transmitted through a Bluetooth AP(wireless). Risk prediction system is proposed through an construction alarm when an abnormal load occurs through real-time multi-point monitoring by sensor location.

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