• Nuclear Engineering and Technology
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• 제56권5호
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• pp.1762-1776
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• 2024

A spent nuclear fuel (SNF) analysis module for the Vodo-Vodyanoi Energetichesky Reactor (VVER) was developed and validated in this study. This advancement expands the application area of the existing nodal diffusion code, RAST-V, and reduces the need for additional code during 3D core simulations for SNF analysis, leading to increased efficiency in simulation time. RAST-V uses Lagrange interpolation and a power correction factor derived from the Bateman equation to bypass the re-depletion calculations, which are used to solve the microdepletion chain. This approach improved the efficiency of analysis. To mirror the conditions during the 3D core simulations, the module used history indices related to the moderator temperature, fuel temperature, and boron concentration. The module can predict 1620 isotopes. This paper presents the validation of this isotope inventory prediction and the application of burnup credit. The VVER analysis module was validated using 28 samples discharged from the Novovoronezh-4. Most isotopes were within 10 % of the boundaries of the measurements. This study successfully offers verification results using VVER benchmarks and discusses the application of burnup credit using a VVER-440 cask.

• 한국멀티미디어학회논문지
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• 제8권6호
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• pp.844-855
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• 2005

This paper proposes a human action recognition scheme for Intelligent Web Browser. Based on the principle that a human action can be defined as a combination of multiple articulation movements, the inference of stochastic grammars is applied to recognize each action. Human actions in 3 dimensional (3D) world coordinate are measured, quantized and made into two sets of 4-chain-code for xy and zy projection planes, consequently they are appropriate for applying the stochastic grammar inference method. We confirm this method by experiments, that various physical actions can be classified correctly against a set of real world 3D temporal data. The result revealed a comparatively successful achievement of $93.8\%$ recognition rate through the experiments of 8 movements of human head and $84.9\%$ recognition rate of 60 movements of human upper body. We expect that this scheme can be used for human-machine interaction commands in a web browser.

• 정보처리학회논문지D
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• 제8D권4호
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• pp.439-450
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• 2001

Mobile agent is one of the promising ways of overcoming network load and latency. It is also a new software paradigm including those concepts of client/server, applet/servelet, and code-on-demand. In this paper, a new mobile agent concept with flexible replay scheme is proposed, which can deal with embarrassing situation when replying results should be accomplished in various distributed applications. For example, they are 1) a burden of bulky result, 2) a need of different replay scheme dependent on work type, 3) connection failure to the target node, and 4) a need of fast migration to next node to keep the itinerary. Regarding the source node, there may be another situation that it wants to be aware of whether its wi가 is completed or not. Three kinds of reply schemes are proposed for dealing flexibly with such situations. They are based on priority reply list where nodes to be replied are stored according to their priorities. An experimental supply chain management model using the proposed reply schemes is designed and implemented. It is one of good distributed applications appropriate for our reply schemes, because it requires different reply schemes according to work types and it is important to gather required information in time.

• 한국측량학회지
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• 제30권6_2호
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• pp.643-651
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• 2012

Object recognition belongs to high-level processing that is one of the difficult and challenging tasks in computer vision. Digital photogrammetry based on the computer vision paradigm has begun to emerge in the middle of 1980s. However, the ultimate goal of digital photogrammetry - intelligent and autonomous processing of surface reconstruction - is not achieved yet. Object recognition requires a robust shape description about objects. However, most of the shape descriptors aim to apply 2D space for image data. Therefore, such descriptors have to be extended to deal with 3D data such as LiDAR(Light Detection and Ranging) data obtained from ALS(Airborne Laser Scanner) system. This paper introduces extension of chain code to 3D object space with hierarchical approach for segmenting point cloud data. The experiment demonstrates effectiveness and robustness of the proposed method for shape description and point cloud data segmentation. Geometric characteristics of various roof types are well described that will be eventually base for the object modeling. Segmentation accuracy of the simulated data was evaluated by measuring coordinates of the corners on the segmented patch boundaries. The overall RMSE(Root Mean Square Error) is equivalent to the average distance between points, i.e., GSD(Ground Sampling Distance).

• 천문학회보
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• 제41권2호
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• pp.62.2-62.2
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• 2016

We present a newly developed algorithm based on a Bayesian method for 2D tilted-ring analysis of disk galaxies which operates on velocity fields. Compared to the conventional ones based on a chi-squared minimisation procedure, this new Bayesian-based algorithm less suffers from local minima of the model parameters even with high multi-modality of their posterior distributions. Moreover, the Bayesian analysis implemented via Markov Chain Monte Carlo (MCMC) sampling only requires broad ranges of posterior distributions of the parameters, which makes the fitting procedure fully automated. This feature is essential for performing kinematic analysis of an unprecedented number of resolved galaxies from the upcoming Square Kilometre Array (SKA) pathfinders' galaxy surveys. A standalone code, the so-called '2D Bayesian Automated Tilted-ring fitter' (2DBAT) that implements the Bayesian fits of 2D tilted-ring models is developed for deriving rotation curves of galaxies that are at least marginally resolved (> 3 beams across the semi-major axis) and moderately inclined (20 < i < 70 degree). The main layout of 2DBAT and its performance test are discussed using sample galaxies from Australia Telescope Compact Array (ATCA) observations as well as artificial data cubes built based on representative rotation curves of intermediate-mass and massive spiral galaxies.

• 한국정보과학회논문지:컴퓨팅의 실제 및 레터
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• 제7권3호
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• pp.248-259
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• 2001

이 논문은 사람의 비언어적 행동을 자동적으로 분석하는 것을 목적으로 60 가지의 기본적인 사람의 윗몸 동작들을 인식하는 방법을 제안한다. 사람 몸동작을 인식하기 위한 방법으로 확률적 문법 추론법을 이용하였으며 모든 관절의 움직임 분석으로 임의의 동작을 인식하는 방법을 사용하였다. 시스템의 입력 데이타로 쓰여지는 각 관절의 실세계 3 차원 좌표들을 일정간격으로 양자화한 후, 각각 xy, zy, 평면에 투영하고, 이들을 다시 4방향 코딩하여 확률적 문법 추론법에 적합한 입력형식으로 변환한다. 또한 비언어적 행동 분석을 위한 사람의 동작 인식에는 손과 다른 부위와의 관계인 근접 정보가 동작 구분의 중요한 요소가 됨을 감안하여, 확률 문법 추론 방법을 확장하고, 일반적인 확률 문법 추론 방법과 비교하여 인식률이 향상됨을 실험결과를 통해 확인하였다.

• 대한의용생체공학회:의공학회지
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• 제28권4호
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• pp.549-555
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• 2007

In order to study cortical properties in human, it is necessary to obtain an accurate and explicit representation of the cortical surface in individual subjects. Among many approaches, surface-based method that reconstructs a 3-D model from contour lines on cross-section images is widely used. In general, however, medical brain imaging has some problems such as the complexity of the images, non-linear gain artifacts and so on. Due these limitations, therefore, extracting anatomical structures from imaging data is very a complicated and time-consuming task. In this paper, we present an improved method for extracting contour lines of cortical surface from magnetic resonance images that simplifies procedures of a conventional method. The conventional method obtains contour lines through thinning and chain code process. On the other hand, the proposed method can extract contour lines from comparison between boundary data and labeling image without supplementary processes. The usefulness of the proposed method has been verified using brain image.

• 해양환경안전학회지
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• 제25권2호
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• pp.201-211
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• 2019

선박의 안전과 보안의 유지는 공급망의 각 단계에서 화물운송 및 여객의 인명 안전을 보장하는데 중추적인 역할을 한다. ISPS Code는 선원과 선박을 보안 위협으로부터 보호하기 위해 SOLAS 협약에 채택되었고, STCW 2010 마닐라 개정에 따라 선원은 반드시 보안 교육을 이수해야 한다. 효과적인 선원의 교육과 훈련은 선박의 보안 관련한 위험을 최소화하기 위한 적절한 이행활동의 수준을 보장하는데 중요하다. 이 연구의 목적은 선원들이 이수한 보안교육과 선원의 보안인식 및 선박의 보안성과 사이의 관계를 실증 분석하는데 있다. 연구 결과에 따르면 (1) 선박 보안 교육을 이수한 선원들은 선박 보안에 대한 인식이 높고 (2) 이러한 보안 교육 및 보안 인식은 선박의 보안성과에 긍정적 영향을 미치며, (3) 보안 인식은 보안 교육과 보안성과 관계에서 매개 효과가 있는 것으로 분석되었다. 따라서 보안 교육과 훈련은 선원의 보안인식과 보안성과에 중요한 영향을 미치며, 이는 결과적으로 해운산업에서 보다 경제적 운영적 및 이미지 측면에서 주요 이점으로 해석될 수 있을 것이다.

• Journal of Radiation Protection and Research
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• 제30권3호
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• pp.121-130
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• 2005

고리 원전 주변 지역에서 가상사고 시에 발생하는 핵종 방출 후 토양 또는 농작물에서 시간 경과에 따라 변화하는 핵종 농도분포를 도식적으로 표현하기 위한 GIS를 구축하였다. 이를 위해 ESRI 사의 GIS 구축용 상용 프로그램인 ArcView를 도입하였다. 미리 고리원전 주변의 북서방향 $20km{\times}20km$ 구역에 대한 1:5000 축적의 지도 데이터를 구축하였다. 표현 대상 농작물 및 방출핵종은 주민의 주식인 쌀과 $^{131}I$로 정하였다. 총 100개의 cell에서 $^{131}I$의 침적량으로부터 토양 및 농작물 부분에 대한 $^{131}I$의 시간에 따른 양을 ECOREA-II코드를 통해 계산하였다. 계산결과를 ArcView에서 미리 준비된 polygon cell의 속성 자료에 각각의 cell id와 일치시켜 데이터 병합(join) 작업을 수행하였다. 시간이 경과됨에 따라 낮아지는 $^{131}I$ 농도값을 일관성있는 색상 변화로 나타내기 위해 ArcView의 color lamp에 대한 RGB 값을 조절하였다. 이 방법을 이용하여 고리주변의 북서방향 $10km{\times}10km$ 지역에서 $^{131}I$의 침적 후 쌀에서 시간에 따라 변하는 $^{131}I$ 농도분포를 일관성있는 색상 변화로 쉽게 구분이 되도록 나타낼 수 있었다.