• 제목/요약/키워드: Model merging.

검색결과 249건 처리시간 0.028초

Mock Galaxy Catalogs from the Horizon Run 4 Simulation with the Most Bound Halo Particle - Galaxy orrespondence Method

  • 홍성욱;박창범;김주한
    • 천문학회보
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    • 제40권2호
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    • pp.29.3-30
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    • 2015
  • We introduce an advanced one-to-one galaxy correspondence method that populates dark matter halos with galaxies by tracing merging histories of most bound member particles (MBPs) identified in simulated virialized halos. To estimate the survival time of a satellite galaxy, we adopt several models of tidal-destruction time derived from an analytic calculation, isolated galaxy simulations, and cosmological simulations. We build mock galaxy samples for each model by using a merging tree information of MBPs from our new Horizon Run 4 N-body simulation from z = 12 to 0. For models of galaxy survival time derived from cosmological and isolated galaxy simulations, about 40% of satellites galaxies merged into a certain halo are survived until z = 0. We compare mock galaxy samples from our MBP-galaxy correspondence scheme and the subhalo-galaxy scheme with SDSS volume-limited galaxy samples around z = 0 with $M_r-5{\log}h$ < -21 and -20. Compared to the subhalo-galaxy correspondence method, our method predicts more satellite galaxies close to their host halo center and larger pairwise peculiar velocity of galaxies. As a result, our method reproduces the observed galaxy group mass function, the number of member galaxies, and the two-point correlation functions while the subhalo-galaxy correspondence method underestimates them.

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Tidal Stripping Substructure on Spatial Distribution of Stars in Several Globular Clusters from UKIRT Observation

  • Sohn, Young-Jong;Chun, Sang-Hyun;Kang, Minhee
    • 천문학회보
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    • 제38권2호
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    • pp.78.1-78.1
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    • 2013
  • The hierarchical model of galaxy formation predicts that galaxy halos contain merger relics in the form of long stellar stream. Thus, tidal substructure of stars around globular clusters, such as tidal tails, could be an essential evidence of the merging scenario in the formation of the Galaxy. From April 2010 to December 2012, we obtained $45^{\prime}{\times}45^{\prime}$ wide-field JHKs near-infrared photometric imaging data for about 20 globular clusters in the Milky Way, and examined the stellar density distribution around globular clusters. Here, we introduce the preliminary results of stellar spatial distributions and radial surface density profiles of four globular clusters. In order to minimize the field star contamination and identify the cluster's member candidates stars, we used a statistical filtering algorithm and gave weights on the CMDs of globular clusters. In two-dimensional stellar density maps, we could found tidal stripping structures for some globular clusters. The orientation of tidal substructure seems to associate with the effects of dynamical interactions with the Galaxy and cluster's orbit. Indeed, the radial surface density profile accurately describes this stripping structures as a break in the slope of profile. The observational results could give us further observational evidence of merging scenario of the formation of the Galaxy.

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차량 군집주행을 위한 제어 네트워크의 변수 추정 및 제어 (State Estimation and Control in a Network for Vehicle Platooning Control)

  • 최재원;황태현;김영호
    • 제어로봇시스템학회논문지
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    • 제6권8호
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    • pp.659-665
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    • 2000
  • In this paper a platoon merging control system is considered as a remotely located system with state represented by a stochastic process. in the system it is common to encounter situations where a single decision maker controls a large number of subsystems and observation and control signals are sent over a communication channel with finite capacity and significant transmission delays. Unlike a classical estimation problem where the observation is a continuous process corrupted by additive noise there is a constraint that the observation must be coded and transmitted over a digital communication channel with fintie capacity. A recursive coder-estimator sequence is a state estimation scheme based on observations transmitted with finite communication capacity constraint. in this paper we introduce a stochastic model for the lead vehicle in a platoon of vehicles in a lane considering the angle between the road surface and a horizontal plane as a stochastic process. In order to merge two platoons the lead vehicle of the following platoon is controlled by a remote control station. Using the observation transmitted over communication channel the remote control station designs the feedback controller. The simulation results show that the intervehicle spacings and the deviations from the desired intervehicle spacing are well regulated.

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Acceleration of Cosmic Ray Electrons at Weak Shocks in Galaxy Clusters

  • Kang, Hyesung;Ryu, Dongsu;Jones, T.W.
    • 천문학회보
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    • 제42권2호
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    • pp.69.1-69.1
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    • 2017
  • According to structure formation simulations, weak shocks with typical Mach number, M<3, are expected to form in merging galaxy clusters. The presence of such shocks has been indicated by X-ray and radio observations of many merging clusters. In particular, diffuse radio sources known as radio relics could be explained by synchrotron-emitting electrons accelerated via diffusive shock acceleration (Fermi I) at quasi-perpendicular shocks. Here we also consider possible roles of stochastic acceleration (Fermi II) by compressive MHD turbulence downstream of the shock. Then we explore a puzzling discrepancy that for some radio relics, the shock Mach number inferred from the radio spectral index is substantially larger than that estimated from X-ray observations. This problem could be understood, if shock surfaces associated with radio relics consist of multiple shocks with different strengths. In that case, X-ray observations tend to pick up the part of shocks with lower Mach numbers and higher kinetic energy flux, while radio emissions come preferentially from the part of shocks with higher Mach numbers and higher cosmic ray (CR) production. We also show that the Fermi I reacceleration model with preexisting fossil electrons supplemented by Fermi II acceleration due to postshock turbulence could reproduce observed profiles of radio flux densities and integrated radio spectra of two giant radio relics. This study demonstrates the CR electrons can be accelerated at collisionless shocks in galaxy clusters just like supernova remnant shock in the interstellar medium and interplanetary shocks in the solar wind.

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조건부 합성기법과 GPM 위성강우자료를 이용한 분포형 강우유출모형 KIMSTORM2의 홍수모의 적용성 평가 (The Applicability of KIMSTORM2 for Flood Simulation Using Conditional Merging Method and GPM Satellite Rainfall Data)

  • 김세훈;정충길;장원진;김성준
    • 한국수자원학회:학술대회논문집
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    • 한국수자원학회 2018년도 학술발표회
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    • pp.111-111
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    • 2018
  • 본 연구의 목적은 조건부 합성 기법(Conditional Merging, CM) 기법을 활용하여 GPM(Global Precipitation Measurement) 위성 자료를 보정하고, 이를 격자기반 분포형 강우-유출 모형(KIneMatic wave STOrm Runoff Model2, KIMSTORM2)에 적용하여 보정된 자료의 효율성을 검토하는데 있다. 모형의 유출 해석은 남강댐 유역($2,293km^2$)을 대상으로 하였으며, 2016년 10월에 발생한 태풍 차바에 대하여 GPM 자료와 CM 기법을 적용한 GPM 자료를 각각 활용하여 결과를 비교하였다. 이 때, 강우자료의 보정은 유역 내 위치한 21개 지점의 지상강우자료를 활용하였으며, 각각의 위성강우자료에 유출 검보정은 남강댐 유역 내 3개의 수위관측 지점(산청, 창촌, 남강댐)을 대상으로 실시하였다. 유출 결과는 결정계수(Coefficient of determination, $R^2$), 모형 효율성 계수(Nash-Sutcliffe efficiency, NSE) 및 유출용적지수(Volume conservation index, VCI)를 이용하여 산정하였다. 지상강우자료와 CM 기법을 통해 보정한 강우자료는 대기의 많은 영향을 받는 위성자료의 특성을 보정하여 공간유출 및 첨두유출을 합리적으로 재현할 수 있을 것으로 예상된다.

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Evaluation performance of machine learning in merging multiple satellite-based precipitation with gauge observation data

  • Nhuyen, Giang V.;Le, Xuan-hien;Jung, Sungho;Lee, Giha
    • 한국수자원학회:학술대회논문집
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    • 한국수자원학회 2022년도 학술발표회
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    • pp.143-143
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    • 2022
  • Precipitation plays an essential role in water resources management and disaster prevention. Therefore, the understanding related to spatiotemporal characteristics of rainfall is necessary. Nowadays, highly accurate precipitation is mainly obtained from gauge observation systems. However, the density of gauge stations is a sparse and uneven distribution in mountainous areas. With the proliferation of technology, satellite-based precipitation sources are becoming increasingly common and can provide rainfall information in regions with complex topography. Nevertheless, satellite-based data is that it still remains uncertain. To overcome the above limitation, this study aims to take the strengthens of machine learning to generate a new reanalysis of precipitation data by fusion of multiple satellite precipitation products (SPPs) with gauge observation data. Several machine learning algorithms (i.e., Random Forest, Support Vector Regression, and Artificial Neural Network) have been adopted. To investigate the robustness of the new reanalysis product, observed data were collected to evaluate the accuracy of the products through Kling-Gupta efficiency (KGE), probability of detection (POD), false alarm rate (FAR), and critical success index (CSI). As a result, the new precipitation generated through the machine learning model showed higher accuracy than original satellite rainfall products, and its spatiotemporal variability was better reflected than others. Thus, reanalysis of satellite precipitation product based on machine learning can be useful source input data for hydrological simulations in ungauged river basins.

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Improved Acoustic Modeling Based on Selective Data-driven PMC

  • Kim, Woo-Il;Kang, Sun-Mee;Ko, Han-Seok
    • 음성과학
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    • 제9권1호
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    • pp.39-47
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    • 2002
  • This paper proposes an effective method to remedy the acoustic modeling problem inherent in the usual log-normal Parallel Model Composition intended for achieving robust speech recognition. In particular, the Gaussian kernels under the prescribed log-normal PMC cannot sufficiently express the corrupted speech distributions. The proposed scheme corrects this deficiency by judiciously selecting the 'fairly' corrupted component and by re-estimating it as a mixture of two distributions using data-driven PMC. As a result, some components become merged while equal number of components split. The determination for splitting or merging is achieved by means of measuring the similarity of the corrupted speech model to those of the clean model and the noise model. The experimental results indicate that the suggested algorithm is effective in representing the corrupted speech distributions and attains consistent improvement over various SNR and noise cases.

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Ensemble Deep Learning Features for Real-World Image Steganalysis

  • Zhou, Ziling;Tan, Shunquan;Zeng, Jishen;Chen, Han;Hong, Shaobin
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • 제14권11호
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    • pp.4557-4572
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    • 2020
  • The Alaska competition provides an opportunity to study the practical problems of real-world steganalysis. Participants are required to solve steganalysis involving various embedding schemes, inconsistency JPEG Quality Factor and various processing pipelines. In this paper, we propose a method to ensemble multiple deep learning steganalyzers. We select SRNet and RESDET as our base models. Then we design a three-layers model ensemble network to fuse these base models and output the final prediction. By separating the three colors channels for base model training and feature replacement strategy instead of simply merging features, the performance of the model ensemble is greatly improved. The proposed method won second place in the Alaska 1 competition in the end.

컬러 영상에서 평균 이동 클러스터링과 단계별 영역 병합을 이용한 자동 원료 분류 알고리즘 (Automatic Classification Algorithm for Raw Materials using Mean Shift Clustering and Stepwise Region Merging in Color)

  • 김상준;곽준영;고병철
    • 방송공학회논문지
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    • 제21권3호
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    • pp.425-435
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    • 2016
  • 본 논문에서는 카메라로부터 입력된 영상으로부터 쌀, 커피, 녹차 등 다양한 원료를 양품과 불량품으로 자동 분류하기 위한 분류 모델을 제안한다. 현재 농산물 원료 분류를 위해서 주로 숙달된 노동력의 육안 선택에 의존하고 있지만 작업시간이 길어질수록 반복적인 작업에 의해 분류 능력이 현저히 떨어지는 문제점이 있다. 노동력에 부분적으로 의존하는 기존 제품의 문제점을 해결하기 위해, 본 논문에서는 평균-이동 클러스터링 알고리즘과 단계별 영역 병합 알고리즘을 결합하는 비전기반 자동 원료 분류 알고리즘을 제안한다. 우선 입력 원료 영상에서 평균-이동 클러스터링 알고리즘을 적용하여 영상을 N개의 클러스터 영역으로 분할한다. 다음단계에서 N개의 클러스터 영역 중에서 대표 영역을 선택하고 이웃 영역들의 영역의 색상과 위치 근접성을 기반으로 단계별 영역 병합 알고리즘을 적용하여 유사한 클러스터 영역을 병합한다. 병합된 원료 객체는 RG, GB, BR의 2D 색상 분표로 표현되고, 병합된 원료 객체에 대해 색상 분포 타원을 만든다. 이후 미리 실험적으로 설정된 임계값을 적용하여 원료를 양품과 불량품을 구분한다. 다양한 원료 영상에 대해 본 논문에서 제안하는 알고리즘을 적용한 결과 기존의 클러스터링 알고리즘이나 상업용 분류 방법에 비해 사용자의 인위적 조작이 덜 필요하고 분류성능이 우수한 결과를 나타냄을 알 수 있었다.

$M^2$ MAC(Message Merging): 수중음파통신 기반의 실시간 로봇 제어 시스템을 위한 MAC 프로토콜 ($M^2$ MAC: MAC protocol for Real Time Robot Control System based on Underwater Acoustic Communication)

  • 김영표;박수현
    • 전자공학회논문지CI
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    • 제48권6호
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    • pp.88-96
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    • 2011
  • 수중 음파 통신은 해양 데이터 수집, 해저 탐사 및 개발, 군사 전술 감시 등 다양한 분야에 활용 가능하다. 이와 같이 다양한 분야에 Autonomous Underwater Vehicle(AUV)나 Remotely Operated Vehicle(ROV)와 같은 수중 로봇을 이용한 로봇 제어 시스템 구축은 필수적이다. 본 논문에서는 수중 음파 센서 네트워크 구성에서 중요한 부분인 에너지 효율적인 면을 고려하는 동시에 실시간 로봇 제어 시스템 구축에 적합한 Message Merging MAC($M^2$-MAC) 프로토콜을 제안한다. 제안된 Media Access Control(MAC) 프로토콜에서는 미리 할당된 타임 슬롯에 따라 로봇 노드들로부터 데이터를 수신하고, 베이스 스테이션으로부터 전달받은 메시지들을 버퍼링 과정을 거쳐 하나의 MAC 프레임으로 생성한 후 클러스터 내 모든 로봇 노드들에게 브로드 캐스팅 하게 된다. 또한 새로운 노드 진입 및 탈퇴 시 Maintenance&Sleep(M&S) 구간을 통해 관련 절차가 이루어짐으로써 경쟁과 비경쟁 방식이 혼합된 복합형 MAC 프로토콜의 형태를 이룬다. 본 논문에서는 실시간 로봇 제어 시스템 구축에 중요한 요소인 종단 간 지연과 에너지 소모량에 관련된 수학적 분석 모델을 제시하고 기존의 MAC 프로토콜과 비교함으로써 성능의 우수성을 검증한다.