• 제목/요약/키워드: random fields

검색결과 418건 처리시간 0.024초

탄성파 속성 분석을 위한 탄성파 자료 무작위 잡음 제거 연구 (Study on the Seismic Random Noise Attenuation for the Seismic Attribute Analysis)

  • 원종필;신정균;하지호;전형구
    • 자원환경지질
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    • 제57권1호
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    • pp.51-71
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    • 2024
  • 탄성파 탐사는 지하자원 개발, 지반 조사, 지층 모니터링 등에 널리 사용되고 있는 지구물리탐사 방법으로 정확한 지층 구조 영상을 제공해주기 때문에 지층의 지질학적 특성 해석에 필수적으로 활용된다. 일반적으로는 탄성파 구조 보정 영상을 시각적으로 분석하여 지질학적 특성을 해석하지만 최근에는 탄성파 구조 보정 자료에 대한 정량적인 분석을 통해 원하는 지질학적 특성을 정확하게 추출하고 해석하는 탄성파 속성 분석이 널리 연구되고 있다. 탄성파 속성 분석은 탄성파 자료에 기반한 지질학적 해석에 정량적인 근거를 제시해줄 수 있기 때문에 석유 및 가스 저류층 분석, 단층 및 균열대 조사, 지층 가스 분포 파악 등의 다양한 분야에서 활용되고 있다. 하지만 탄성파 속성 분석은 탄성파 자료 내 잡음에 취약하므로 속성 분석의 정확도 향상을 위해서는 중합 후 탄성파 자료에 대한 추가적인 잡음 제거가 수반되어야 한다. 본 연구에서는 중합 후 탄성파 자료에 대한 무작위 잡음 제거 및 및 탄성파 속성 분석 정확도 개선을 위해 4가지의 잡음 제거 방법을 적용하고 비교한다. FX 디콘볼루션, DSMF, Noise2Noiose, DnCNN을 각각 포항 영일만 고해상 탄성파 자료에 적용하여 탄성파 무작위 잡음을 제거하고 잡음이 제거된 탄성파 자료로부터 에너지, 스위트니스, 유사도 속성을 계산한다. 그리고 각 잡음 제거 방법의 특성, 잡음 제거 결과, 탄성파 속성 분석 결과를 정성적 및 정량적으로 분석한 후, 이를 기반으로 탄성파 속성 분석 결과 향상을 위한 최적의 잡음 제거 방법을 제안한다.

Domain Adaptation 방법을 이용한 기계학습 기반의 미세먼지 농도 예측 (Machine Learning-based Estimation of the Concentration of Fine Particulate Matter Using Domain Adaptation Method)

  • 강태천;강행봉
    • 한국멀티미디어학회논문지
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    • 제20권8호
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    • pp.1208-1215
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    • 2017
  • Recently, people's attention and worries about fine particulate matter have been increasing. Due to the construction and maintenance costs, there are insufficient air quality monitoring stations. As a result, people have limited information about the concentration of fine particulate matter, depending on the location. Studies have been undertaken to estimate the fine particle concentrations in areas without a measurement station. Yet there are limitations in that the estimate cannot take account of other factors that affect the concentration of fine particle. In order to solve these problems, we propose a framework for estimating the concentration of fine particulate matter of a specific area using meteorological data and traffic data. Since there are more grids without a monitor station than grids with a monitor station, we used a domain adversarial neural network based on the domain adaptation method. The features extracted from meteorological data and traffic data are learned in the network, and the air quality index of the corresponding area is then predicted by the generated model. Experimental results demonstrate that the proposed method performs better as the number of source data increases than the method using conditional random fields.

Genetic variation of Phytophthora infestans by RAPD analysis

  • Lee, Yun-Soo;Jeong young Song;Kim, Nam-Kyu;Nam Moon;Park, Hye-Jin;Kim, Hong-Gi
    • 한국식물병리학회:학술대회논문집
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    • 한국식물병리학회 2003년도 정기총회 및 추계학술발표회
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    • pp.116.2-117
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    • 2003
  • Late blight, caused by Phytophthora infestans, is one of the most destructive disease on potato and tomato cultivation. To analysis genetic diversity P. infeatans isolates were collected from potato and tomato fields in Korea. These pathogens contained both Al and A2 mating type with metalaxyl-resistant and sensitive isolates. Polymorphisms showed base on RAPD (Random Amplified Polymorphic DNA) in both potato and tomato isolates of P. infestans. Cluster analysis showed high level genetic variation in potato isolates of P. infestans than tomato isolates. P. infestans isolates were observed genetic diversity among them but not grouped among isolates related mating type and metalaxyl response. These results exhibited that P. infestans isolates showing genetic difference among them were distributed in Korea.

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Prediction of Barge Ship Roll Response Amplitude Operator Using Machine Learning Techniques

  • Lim, Jae Hwan;Jo, Hyo Jae
    • 한국해양공학회지
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    • 제34권3호
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    • pp.167-179
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    • 2020
  • Recently, the increasing importance of artificial intelligence (AI) technology has led to its increased use in various fields in the shipbuilding and marine industries. For example, typical scenarios for AI include production management, analyses of ships on a voyage, and motion prediction. Therefore, this study was conducted to predict a response amplitude operator (RAO) through AI technology. It used a neural network based on one of the types of AI methods. The data used in the neural network consisted of the properties of the vessel and RAO values, based on simulating the in-house code. The learning model consisted of an input layer, hidden layer, and output layer. The input layer comprised eight neurons, the hidden layer comprised the variables, and the output layer comprised 20 neurons. The RAO predicted with the neural network and an RAO created with the in-house code were compared. The accuracy was assessed and reviewed based on the root mean square error (RMSE), standard deviation (SD), random number change, correlation coefficient, and scatter plot. Finally, the optimal model was selected, and the conclusion was drawn. The ultimate goals of this study were to reduce the difficulty in the modeling work required to obtain the RAO, to reduce the difficulty in using commercial tools, and to enable an assessment of the stability of medium/small vessels in waves.

한국(韓國) 상용식품(常用食品) 영양가(營養價) 조사보고(調査報告) (제 5 보)(第 5 報) (Studies on the Nutritive Value of Korean Foods (Report 5))

  • 유정열;윤사노;김기경;권혁희;김인복;안경옥
    • Journal of Nutrition and Health
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    • 제6권1호
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    • pp.11-13
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    • 1973
  • The nutritive value of foods is the most essential and fundamental data in food administration, nutrition surveys, dietary clinic, and in the conduct of nutritional education. The nutritive values of 283 different kinds of selected Korean foods were investigated and reported in our previous reports already. In this report, another 21 kinds of Korean foods are studied for their proximate components, minerals and vitamins. The foods were sampled at random from the markets or from cultivating fields. The methods of sampling and of chemical analysis were same as employed in the previous reports. The results are shown in the table. The nutritive value of the rest of Korean foods will be studied continuously.

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구형좌표계에서 음향 홀로그래피의 적용 (The implementation of spherical acoustical holography)

  • 김용조;조용성
    • 한국소음진동공학회:학술대회논문집
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    • 한국소음진동공학회 2002년도 추계학술대회논문집
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    • pp.410-415
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    • 2002
  • In this article, spatial filtering procedures with application to spherical acoustical holography are discussed. Planar and cylindrical holography are the most widely used amongst the various nearfield acoustical holography techniques. However, when the geometry of a source is similar to a sphere, spherical holography may yield better results than other types of holography since there are no errors due to truncation of the sound field in the spherical case. Spatial filtering affects the accuracy of spherical acoustical holography critically, especially in the case of backward projection. Thus spatial filtering is essential for successful application of spherical holography. In the present work, various filtering methods were evaluated in simulations made using sound pressure fields of various types and with different levels of random spatial noise. It was found that a procedure based on eliminating spherical harmonic coefficients that contribute insignificantly to the total sound power of the source gave the best results on average of the different procedures considered here. Spherical holography procedures were also verified experimentally. Reliable results were obtained using the power filtering algorithm. Thus it was concluded that spherical holography combined with power filtering may prove to be a useful tool for noise source identification.

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Wake galloping phenomena between two parallel/unparallel cylinders

  • Kim, Sunjoong;Kim, Ho-Kyung
    • Wind and Structures
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    • 제18권5호
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    • pp.511-528
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    • 2014
  • The characteristics of wake galloping phenomenon for two parallel/unparallel circular cylinders were investigated via wind tunnel tests. The two cylinders were initially deployed in parallel and wake galloping phenomena were observed by varying the center-to-center distance. The effect of an unparallel arrangement of two cylinders was next investigated by fixing the spacing ratio of one side of the cylinders at 5.0D and the other side at 3.0D, in which D represents the diameter of the cylinder. For the unparallel disposition, the 5.0D side showed a small, limited vibration while the 3.0D side produced much larger amplitude of vibration, resulting in a rolling motion. However, the overall amplitude appeared to decrease in unparallel disposition when compared with the amplitude of the 3.0D - 3.0D parallel case. This represents the mitigation effect of wake galloping due to the unparallel disposition between two cylinders. Flow visualization tests with particle image velocimetry were conducted to identify flow fields between two cylinders. The test results demonstrate the existence of a complex interaction of the downstream cylinder with the shear layer generated by the upstream cylinder. When the spacing ratio was large enough, the shear layer was not observed and the downstream cylinder showed only limited random vibration.

CAN을 이용한 자동화 사격장 시스템 개발 (The Development of an Automatic Shooting Range System Using CAN)

  • 허화라;최승욱;권구남
    • 한국산학기술학회논문지
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    • 제1권2호
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    • pp.41-48
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    • 2000
  • 최근 산업현장의 모든 부분에서 자동화의 요구가 급격하게 증가되고 있다. 지금까지의 사격장 시스템은 정적인 환경을 중심으로 설계되어져 왔다. 그러나, 실제의 사격상황은 목표물이 동적이므로 다른 사격 환경 변화가 요구된다. 본 연구에서는 동적인 사격환경을 구현하기 위해 1개 사로에 4대의 타겟을 설치하여 사격순서를 순차 및 비순차로 구분하고 사격시간을 가변적으로 조정할 수 있게 하였다. 그리고. 자동차 및 빌딩 자동화에 많이 응용되고 있는 CAN(Controller Area Network)을 이용함으로써 효율적인 통신을 가능하게 하였다. CAN은 높은 데이터 전송률과 안정성을 제공할 수 있어 다수의 ECU(Electric Control Unit)를 상호 연결하여 분산된 실시간 제어를 효율적으로 지원할 수 있다.

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CRFs와 Bi-LSTM/CRFs의 비교 분석: 자동 띄어쓰기 관점에서 (CRFs versus Bi-LSTM/CRFs: Automatic Word Spacing Perspective)

  • 윤호;김창현;천민아;박호민;남궁영;최민석;김재훈
    • 한국정보과학회 언어공학연구회:학술대회논문집(한글 및 한국어 정보처리)
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    • 한국정보과학회언어공학연구회 2018년도 제30회 한글 및 한국어 정보처리 학술대회
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    • pp.189-192
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    • 2018
  • 자동 띄어쓰기란 컴퓨터를 사용하여 띄어쓰기가 수행되어 있지 않은 문장에 대해 띄어쓰기를 수행하는 것이다. 이는 자연언어처리 분야에서 형태소 분석 전에 수행되는 과정으로, 띄어쓰기에 오류가 발생할 경우, 형태소 분석이나 구문 분석 등에 영향을 주어 그 결과의 모호성을 높이기 때문에 매우 중요한 전처리 과정 중 하나이다. 본 논문에서는 기계학습의 방법 중 하나인 CRFs(Conditional Random Fields)를 이용하여 자동 띄어쓰기를 수행하고 심층 학습의 방법 중 하나인 양방향 LSTM/CRFs (Bidirectional Long Short Term Memory/CRFs)를 이용하여 자동 띄어쓰기를 수행한 뒤 각 모델의 성능을 비교하고 분석한다. CRFs 모델이 양방향 LSTM/CRFs모델보다 성능이 약간 더 높은 모습을 보였다. 따라서 소형 기기와 같은 환경에서는 CRF와 같은 모델을 적용하여 모델의 경량화 및 시간복잡도를 개선하는 것이 훨씬 더 효과적인 것으로 생각된다.

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On the usefulness of discrete element computer modeling of particle packing for material characterization in concrete technology

  • Stroeven, P.;Hu, J.;Stroeven, M.
    • Computers and Concrete
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    • 제6권2호
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    • pp.133-153
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    • 2009
  • Discrete element modeling (DEM) in concrete technology is concerned with design and use of models that constitute a schematization of reality with operational potentials. This paper discusses the material science principles governing the design of DEM systems and evaluates the consequences for their operational potentials. It surveys the two families in physical discrete element modeling in concrete technology, only touching upon probabilistic DEM concepts as alternatives. Many common DEM systems are based on random sequential addition (RSA) procedures; their operational potentials are limited to low configuration-sensitivity features of material structure, underlying material performance characteristics of low structure-sensitivity. The second family of DEM systems employs concurrent algorithms, involving particle interaction mechanisms. Static and dynamic solutions are realized to solve particle overlap. This second family offers a far more realistic schematization of reality as to particle configuration. The operational potentials of this family involve valid approaches to structure-sensitive mechanical or durability properties. Illustrative 2D examples of fresh cement particle packing and pore formation during maturation are elaborated to demonstrate this. Mainstream fields of present day and expected application of DEM are sketched. Violation of the scientific knowledge of to day underlying these operational potentials will give rise to unreliable solutions.