• Title/Summary/Keyword: 상태 변화 예측

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Evaluation of Thermal Insulation and Hypothermia for Development of Life Raft (해상 구명정의 단열성능평가 및 저체온증 예측 수치해석 연구)

  • Hwang, Se-Yun;Jang, Ho-Sang;Kim, Kyung-Woo;Lee, Jang-Hyun
    • Journal of Navigation and Port Research
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    • v.39 no.6
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    • pp.485-491
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    • 2015
  • The technology review about risk of hypothermia of victim according to heat transfer characteristic of life raft and sea state can use accident correspondence of standing and sinking of ship. This study studied heat transfer characteristics required for the design of life raft and thermal insulation property analysis and evaluation methods. In addition, it is study for comprehend the risk of hypothermia and suggest analysis result that is experiment of thermal insulation property and body temperature property for decide of prediction the body temperature decline Thermal Analysis apply the finite element analysis method is comprehended the property of heat conductivity, convective effect of sea water and properties changes according to property of insulation material. it measure the heat flux with attach temperature sensor on body in order to comprehend the variation of body temperature with boarding a life raft experiment on a human body. This study validate results by comparing variation of temperature measured from experiment on a body with variation of temperature from finite element analysis model. Also, the criteria of hypothermia was discussed through result of finite element analysis.

Performance Improvement on Adaptive OFDM System with a Multi-Step Channel Predictor over Mobile Fading Channels (이동 페이딩 채널하의 멀티 스텝 채널 예측기를 이용한 적응 OFDM 시스템의 성능개선)

  • Ahn, Hyun-Jun;Kim, Hyun-Dong;Choe, Sang-Ho
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.31 no.12A
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    • pp.1182-1188
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    • 2006
  • Adaptive OFDM(Orthogonal Frequency Division Multiplexing) improves data capacity and system performance over multipath fading by adaptively changing modulation schemes according to channel state information(CSI). To achieve a good performance in adaptive OFDM systems, CSI should be transmitted from receiver to transmitter in real time through feedback channel. However, practically, the CSI feedback delay d which is the sum of the data processing delay and the propagation delay is not negligible and damages to the reliability of CSI such that the performance of adaptive OFDM is degraded. This paper presents an adaptive OFDM system with a multistep predictor on the frequency axis to effectively compensate the multiple feedback delays $d(\geq2)$. Via computer simulation we compare the proposed scheme and existing adaptive OFDM schemes with respect to data capacity and system performance.

An Investigation on Structural Analysis of Feldspars by Electron Diffraction Patterns (전자회절도형을 이용한 장석의 구조 분석에 대한 고찰)

  • 김윤중;이영부;박병규;이정후
    • Journal of the Mineralogical Society of Korea
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    • v.17 no.2
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    • pp.177-187
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    • 2004
  • Measurements of the lattice parameters of albite and oligoclase from electron diffraction patterns with the Au internal standard resulted in errors of less than 1 %. An electron diffraction map for natural oligoclase samples was constructed and 11 stations of zone-axes diffraction patterns were obtained. This process is indispensible for reliable TEM studies of triclinic feldspars. Utilizing the [001] cleavage plane of feldspar and the double-tilting TEM holder the following information is obtainable: Si-Al ordering and chemistry of alkali feldspars could be estimated from the $\alpha$* - * plot, where * is measured from the [001] orientation, while $\alpha$* is measured from the [100] orientation. Si-Al ordering of Na-rich plagioclase could be estimated from * [001] patterns. Structure and chemistry or Na-poor plagioclase could be estimated from existence of e-reflections, their intensity variations as well as their positional changes.

Assessment of the Models for Predicting the Thermal Conductivity of Saturated Kaolinite (포화된 카올리나이트를 이용한 열전도계수 예측모델의 신뢰성 검토)

  • Lee, Jangguen;Kim, Hakseung;Kang, Jaemo;Kim, Youngseok;Bae, Gyujin
    • Journal of the Korean GEO-environmental Society
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    • v.13 no.3
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    • pp.21-27
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    • 2012
  • Estimating the thermal conductivity of clayey soils is important for enhancing the performance of geoengineering structures in cold regions and clay barriers for nuclear waste repositories, but specimen disturbance, saturation, and heat boundary conditions of the test apparatus hinder reliable measurements of the thermal conductivity of saturated clayey soils. This paper presents the results of an experimental study carried out using modified consolidation tests with the needle probe method to measure thermal conductivity. Experimental consolidation tests with saturated kaolinite were performed to investigate the effect of effective stress and dry density on thermal conductivity for saturated kaolinite. In addition, thermal conductivity of soil particles were thoroughly investigated and experimental results were used to evaluate the accuracy of the models to predict thermal conductivity.

Improvement Plan of Excavation Performance Based on Shield TBM Performance Prediction Models and Field Data (쉴드 TBM 성능예측모델과 굴진자료 분석을 통한 굴진성능 개선방안)

  • Jung, Hyuksang;Kang, Hyoungnam;Choi, Jungmyung;Chun, Byungsik
    • Journal of the Korean GEO-environmental Society
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    • v.11 no.2
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    • pp.43-52
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    • 2010
  • Shield method is the tunnel boring method that propels a steel cylinder in the ground and excavates tunnels at once. After Marc Isambard Brunel started using the method for the Thames Riverbed Tunnel excavation in London, many kinds of TBM (Tunnel Boring Machine) developed and applied for the construction of road, railway, electricity channel, pipeline, etc. In comparison with NATM concept that allows to observe ground condition and copes with difficulty. The machine selected before starting construction is not able to be changed during construction in shield TBM. Therefore the machine should be designed based on the ground survey result and experiment, so that the tunnel might be excavated effectively by controlling penetration speed, excavation depth and cutter head speed according to the ground condition change. This research was conducted to estimate penetration depth, excavate speed, wear of disc cutter on Boondang Railway of the Han Riverbed Tunnel ground condition by TBM performance prediction models such as NTNU, $Q_{TBM}$, Total Hardness, KICT-SNU and compare the estimated value with the field data. The estimation method is also used to analyze the reason of poor excavation efficiency at south bound tunnel.

Development of an AI-based Early Warning System for Water Meter Freeze-Burst Detection Using AI Models (AI기반 물공급 시스템내 동파위험 조기경보를 위한 AI모델 개발 연구)

  • So Ryung Lee;Hyeon June Jang;Jin Wook Lee;Sung Hoon Kim
    • Proceedings of the Korea Water Resources Association Conference
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    • 2023.05a
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    • pp.511-511
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    • 2023
  • 기후변화로 동절기 기온 저하에 따른 수도계량기의 동파는 지속적으로 심화되고 있으며, 이는 계량기 교체 비용, 누수, 누수량 동결에 의한 2차 피해, 단수 등 사회적 문제를 야기한다. 이와같은 문제를 해결하고자 구조적 대책으로 개별 가정에서 동파 방지형 계량기를 설치할 수 있으나 이를 위한 비용발생이 상당하고, 비구조적 대책으로는 기상청의 동파 지도 알림 서비스를 활용하여 사전적으로 대응하고자 하나, 기상청자료는 대기 온도를 중심으로 제공하고 있기 때문에 해당서비스만으로는 계량기의 동파를 예측하는데 필요한 추가적인 다양한 변수를 활용하는데 한계가 있다. 최근 정부와 공공부문에서 22개 지역, 110개소 이상의 수도계량기함내 IoT 온도센서를 시범 설치하여 계량기 함내의 상태 등을 확인할 수 있는 사업을 수행했다. 전국적인 계량기 상태의 예측과 진단을 위해서는 추가적인 센서 설치가 필요할 것이나, IoT센서 설치 비용 등의 문제로 추가 설치가 더딘 실정이다. 본 연구에서는 겨울 동파 예방을 위해 실제 온도센서를 기반으로 가상센서를 구축하고, 이를 혼합한 하이브리드 방식으로 동파위험 기준에 따라 전국 동파위험 지도를 구축하였다. 가상센서 개발을 위해 독립변수로 위경도, 고도, 음·양지, 보온재 여부 및 기상정보(기온, 강수량, 풍속, 습도)를 활용하고, 종속변수로 실제 센서의 온도를 사용하여 기계학습 모델을 개발하였다. 지역 특성에 따라 정확한 모델을 구축하기 위해 위치정보 및 보온재여부 등의 변수를 활용하여 K-means 방법으로 군집화 하였으며, 각 군집별로 3가지의 기계학습 회귀모델을 적용하였다. 최적의 군집 수를 검토한 결과 4개가 적정한 것으로 판단되었다. 군집의 특성은 지역별 구분과 유사한 패턴을 보이며, 모든 군집에서 Gradient Boosting 회귀모델을 적용하는 것이 적합한 것으로 나타났다. 본 연구에서 개발한 모델을 바탕으로 조건에 따라 동파 예측 알람서비스에 실무적으로 활용할 수 있도록 양호·주의·위험·매우위험 총 4개의 기준을 설정하였다. 실제 본 연구에서 개발된 알고리즘을 국가상수도정보 시스템에 반영하여 테스트 수행중에 있으며, 향후 지속 검증을 할 예정에 있다. 이를 통해 동파 예방 및 피해 최소화, 물절약 등 직간접적 편익이 기대된다.

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Dynamic Capacity Concept and its Determination for Managing Congested Flow (혼잡교통류 관리를 위한 동적 용량의 개념 및 산정방법)

  • Park, Eun-Mi
    • Journal of Korean Society of Transportation
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    • v.22 no.3 s.74
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    • pp.159-166
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    • 2004
  • The capacity concept presented in the Highway Capacity Manual is for steady-state traffic flow assuming that there is no restriction in downstream flowing, which is traditionally used for planning, design, and operational analyses. In the congested traffic condition, the control objective should be to keep the congested regime from growing and to recover the normal traffic condition as soon as possible. In this control case, it is important to predict the spatial-temporal pattern of congestion evolution or dissipation and to estimate the throughput reduction according to the spatial-temporal pattern. In this context, the new concept of dynamic capacity for managing congested traffic is developed in terms of spatial-temporal evolution of downstream traffic congestion and in view of the 'input' concept assuming that flow is restricted by downstream condition rather than the 'output' concept assuming that there is no restriction in downstream flowing (e.g. the mean queue discharge flow rate). This new capacity is defined as the Maximum Sustainable Throughput that is determined based on the spatial-temporal evolution pattern of downstream congestion. And the spatial-temporal evolution pattern is estimated using the Newell's simplified q-k model.

HDTV Image Compression Algorithm Using Leak Factor and Human Visual System (누설요소와 인간 시각 시스템을 이용한 HDTV 영상 압축 알고리듬)

  • 김용하;최진수;이광천;하영호
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.19 no.5
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    • pp.822-832
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    • 1994
  • DSC-HDTV image compression algorithm removes spatial, temporal, and amplitude redundancies of an image by using transform coding, motion-compensated predictive coding, and adaptive quantization, respectively. In this paper, leak processing method which is used to recover image quality quickly from scene change and transmission error and adaptive quantization using perceptual weighting factor obtained by HVS are proposed. Perceptual weighting factor is calculated by contrast sensitivity, spatio-temporal masking and frequency sensitivity. Adaptive quantization uses the perceptual weighting factor and global distortion level from buffer history state. Redundant bits according to adaptation of HVS are used for the next image coding. In the case of scene change, DFD using motion compensated predictive coding has high value, large bit rate and unstabilized buffer states since reconstructed image has large quantization noise. Thus, leak factor is set to 0 for scene change frame and leak factor to 15/16 for next frame, and global distortion level is calculated by using standard deviation. Experimental results show that image quality of the proposed method is recovered after several frames and then buffer status is stabilized.

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Parameter Sensitivity Analysis of SWAT Model for Prediction of Pollutants Fate in Joman River Basin (조만강 유역의 오염물질 거동 예측을 위한 SWAT 모형의 매개변수 민감도 분석)

  • Kang, Deok-Ho;Kim, Tae-Won;Kim, Young-Do;Kwon, Jae-Hyun
    • 한국방재학회:학술대회논문집
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    • 2008.02a
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    • pp.787-790
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    • 2008
  • The SWAT(Soil and Water Assesment Tool) is a relatively large scale model for the complicated watershed or river basin. The model was developed to predict the effect of land management practices on water, sediment and agricultural chemical yields in large complex watershed with varying soils, land use and management conditions over long periods of time. Usually streams are divided into urban stream and natural stream in accordance with the development level. In case of urban stream, according to urbanization, as impermeable areas are increasing due to the change of land use condition and land cover condition, dry stream phenomenon at urban stream is rapidly progressed. In this study, long term run-off simulations in urban stream are performed by using SWAT model. Especially, the model is applied in small scale water shed, Joman River basin. The optimization by the sensitivity analysis is also performed for the model parameter estimations.

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Traffic Congestion Estimation by Adopting Recurrent Neural Network (순환인공신경망(RNN)을 이용한 대도시 도심부 교통혼잡 예측)

  • Jung, Hee jin;Yoon, Jin su;Bae, Sang hoon
    • The Journal of The Korea Institute of Intelligent Transport Systems
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    • v.16 no.6
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    • pp.67-78
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    • 2017
  • Traffic congestion cost is increasing annually. Specifically congestion caused by the CDB traffic contains more than a half of the total congestion cost. Recent advancement in the field of Big Data, AI paved the way to industry revolution 4.0. And, these new technologies creates tremendous changes in the traffic information dissemination. Eventually, accurate and timely traffic information will give a positive impact on decreasing traffic congestion cost. This study, therefore, focused on developing both recurrent and non-recurrent congestion prediction models on urban roads by adopting Recurrent Neural Network(RNN), a tribe in machine learning. Two hidden layers with scaled conjugate gradient backpropagation algorithm were selected, and tested. Result of the analysis driven the authors to 25 meaningful links out of 33 total links that have appropriate mean square errors. Authors concluded that RNN model is a feasible model to predict congestion.