• Title/Summary/Keyword: 목표 모델링

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Depressurization Modeling Methodology for Thrust Variable Solid Propulsion System (고체추진 추력조절 시스템에 적용가능한 감압률 모델링 방법론 연구)

  • Yoon, Jisu;Heo, Junyoung;Oh, Seokjin
    • Journal of the Korean Society of Propulsion Engineers
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    • v.26 no.4
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    • pp.44-53
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    • 2022
  • The depressurization rate in a thrust variable solid rocket motor is the major factor that has the greatest influence on the thrust termination performance. In this study, the depressurization rates range of model solid rocket motor was identified and major factors affecting the depressurization rate were found. It is important for actual system design to understand the depressurization rate of the system that can satisfy the target performance as well as the extinguishing characteristics of the solid propellant. The methodology for obtaining the depressurization rate model in this study is considered to be applicable to the optimal design of the thrust terminable propulsion system.

A stratified random sampling design for paddy fields: Optimized stratification and sample allocation for effective spatial modeling and mapping of the impact of climate changes on agricultural system in Korea (농지 공간격자 자료의 층화랜덤샘플링: 농업시스템 기후변화 영향 공간모델링을 위한 국내 농지 최적 층화 및 샘플 수 최적화 연구)

  • Minyoung Lee;Yongeun Kim;Jinsol Hong;Kijong Cho
    • Korean Journal of Environmental Biology
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    • v.39 no.4
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    • pp.526-535
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    • 2021
  • Spatial sampling design plays an important role in GIS-based modeling studies because it increases modeling efficiency while reducing the cost of sampling. In the field of agricultural systems, research demand for high-resolution spatial databased modeling to predict and evaluate climate change impacts is growing rapidly. Accordingly, the need and importance of spatial sampling design are increasing. The purpose of this study was to design spatial sampling of paddy fields (11,386 grids with 1 km spatial resolution) in Korea for use in agricultural spatial modeling. A stratified random sampling design was developed and applied in 2030s, 2050s, and 2080s under two RCP scenarios of 4.5 and 8.5. Twenty-five weather and four soil characteristics were used as stratification variables. Stratification and sample allocation were optimized to ensure minimum sample size under given precision constraints for 16 target variables such as crop yield, greenhouse gas emission, and pest distribution. Precision and accuracy of the sampling were evaluated through sampling simulations based on coefficient of variation (CV) and relative bias, respectively. As a result, the paddy field could be optimized in the range of 5 to 21 strata and 46 to 69 samples. Evaluation results showed that target variables were within precision constraints (CV<0.05 except for crop yield) with low bias values (below 3%). These results can contribute to reducing sampling cost and computation time while having high predictive power. It is expected to be widely used as a representative sample grid in various agriculture spatial modeling studies.

A study on the classification of research topics based on COVID-19 academic research using Topic modeling (토픽모델링을 활용한 COVID-19 학술 연구 기반 연구 주제 분류에 관한 연구)

  • Yoo, So-yeon;Lim, Gyoo-gun
    • Journal of Intelligence and Information Systems
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    • v.28 no.1
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    • pp.155-174
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    • 2022
  • From January 2020 to October 2021, more than 500,000 academic studies related to COVID-19 (Coronavirus-2, a fatal respiratory syndrome) have been published. The rapid increase in the number of papers related to COVID-19 is putting time and technical constraints on healthcare professionals and policy makers to quickly find important research. Therefore, in this study, we propose a method of extracting useful information from text data of extensive literature using LDA and Word2vec algorithm. Papers related to keywords to be searched were extracted from papers related to COVID-19, and detailed topics were identified. The data used the CORD-19 data set on Kaggle, a free academic resource prepared by major research groups and the White House to respond to the COVID-19 pandemic, updated weekly. The research methods are divided into two main categories. First, 41,062 articles were collected through data filtering and pre-processing of the abstracts of 47,110 academic papers including full text. For this purpose, the number of publications related to COVID-19 by year was analyzed through exploratory data analysis using a Python program, and the top 10 journals under active research were identified. LDA and Word2vec algorithm were used to derive research topics related to COVID-19, and after analyzing related words, similarity was measured. Second, papers containing 'vaccine' and 'treatment' were extracted from among the topics derived from all papers, and a total of 4,555 papers related to 'vaccine' and 5,971 papers related to 'treatment' were extracted. did For each collected paper, detailed topics were analyzed using LDA and Word2vec algorithms, and a clustering method through PCA dimension reduction was applied to visualize groups of papers with similar themes using the t-SNE algorithm. A noteworthy point from the results of this study is that the topics that were not derived from the topics derived for all papers being researched in relation to COVID-19 (

    ) were the topic modeling results for each research topic (
    ) was found to be derived from For example, as a result of topic modeling for papers related to 'vaccine', a new topic titled Topic 05 'neutralizing antibodies' was extracted. A neutralizing antibody is an antibody that protects cells from infection when a virus enters the body, and is said to play an important role in the production of therapeutic agents and vaccine development. In addition, as a result of extracting topics from papers related to 'treatment', a new topic called Topic 05 'cytokine' was discovered. A cytokine storm is when the immune cells of our body do not defend against attacks, but attack normal cells. Hidden topics that could not be found for the entire thesis were classified according to keywords, and topic modeling was performed to find detailed topics. In this study, we proposed a method of extracting topics from a large amount of literature using the LDA algorithm and extracting similar words using the Skip-gram method that predicts the similar words as the central word among the Word2vec models. The combination of the LDA model and the Word2vec model tried to show better performance by identifying the relationship between the document and the LDA subject and the relationship between the Word2vec document. In addition, as a clustering method through PCA dimension reduction, a method for intuitively classifying documents by using the t-SNE technique to classify documents with similar themes and forming groups into a structured organization of documents was presented. In a situation where the efforts of many researchers to overcome COVID-19 cannot keep up with the rapid publication of academic papers related to COVID-19, it will reduce the precious time and effort of healthcare professionals and policy makers, and rapidly gain new insights. We hope to help you get It is also expected to be used as basic data for researchers to explore new research directions.

  • Lifting Work Process Optimization Method in High-rise Building Construction Through Improvement of CYCLONE Modeling Method (CYCLONE 모델링 기법 개선을 통한 초고층 공사의 자재 양중 작업 프로세스 최적화 연구)

    • Hawng, Doowon;Kwon, Okyung;Choi, Yoonki
      • Korean Journal of Construction Engineering and Management
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      • v.18 no.2
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      • pp.58-70
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      • 2017
    • The planning for material lifting operations is one of the key processes in high-rise building construction. Several previous studies have used rough calculations by referring to existing practices or establishing a target value for lifting cycle time or operating rate. Therefore, the purpose of this study is to propose a material lifting process optimization method for reducing the lifting cycle time and increasing the operating rate. In this study, we improve the cyclic operation network (CYCLONE) modeling method that considers the duration and zone information of each work task. This method can be used to hand over work tasks to another crew group in the work process. According to this methodology, this study optimizes the material lifting process, performs a sensitivity analysis, and evaluates the field applicability of the proposed material lifting process optimization method. Therefore, the optimized process was then applied to a high-rise building construction site. The lifting work process time and operating rate for the simulated as - is lifting process data, optimized process data, and field application result data were compared for each lifting height. From this comparison, the effectiveness of the optimization methodology was confirmed.

    Effect of Hydraulic Parameters on Water Quality Predictions (수리매개변수가 수질예측에 미치는 영향분석)

    • Kim, Sang-Dan;Kang, Doo-Kee;Shin, Hyun-Suk
      • Proceedings of the Korea Water Resources Association Conference
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      • 2006.05a
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      • pp.1641-1645
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      • 2006
    • 수문순환과 수질오염과정의 제반 기작들이 완벽하게 규명되지 않은 상황에서 인위적 또는 자연적 조건에 따른 수질의 평가는 수질모형으로서 추정하는 것이 유일한 대안이며, 다양한 관리대안에 따른 수질환경변화를 예측함으로서 합리적인 관리방안을 도출하는데 유용한 수단이 되고 있다. 현재 시행 중인 수질오염총량관리제에서 또한 수질모형은 핵심적인 역할을 담당하고 있으며, 보다 구체적으로는 단위유역의 목표수질을 결정하는 것에서부터 기본계획 또는 시행계획에 따른 오염부하량 등 환경요인의 변화와 이에 따른 목표수질 설정지점의 수질 변화 등을 모의하는데 이용되고 있다. 그러나 모형에 사용되는 입력 매개변수의 불확실성과 이에 관련된 수질 모형 자체의 불확실성은 수질오염총량관리제와 같이 많은 이해당사자가 관여된 정책의 결정 시에는 공학적으로 많은 부담으로 작용하고 있는 것 또한 현실이다. 실제로 미국의 오염총량관리제의 경우를 살펴보면 모형의 불확실성 분석이 전체 과정의 진행에서 가장 핵심적인 지위를 차지하고 있다고 볼 수 있다. 많은 연구들이 수질모형에 있어서의 불확실성을 정량화하기 위하여 수행되어 왔으며, 특히 미국의 오염총량관리계획의 수립 시에는 이러한 불확실성 분석을 토대로 하여 안전율을 산정하도록 되어있다. 그러나 이러한 연구들의 대부분은 수질모형의 매개변수 중 수질기작에 관련된 매개변수들(예를 들어, DO, BOD, N, P 등에 대한 반응계수)에 대한 연구에 집중되어 있다. 하천의 수질을 적절하게 모델링하기 위해서는 이러한 수질에 직접적으로 관련한 매개변수들 이외에 하천의 수리특성에 관한 올바른 이해를 바탕으로 그와 관련된 수리학적 매개변수들에 대한 연구가 뒷받침되어야 한다. 그동안 수행되어온 수질 모델링의 적용 사례를 살펴본 바에 따르면 하천을 모델링하기 위해서는 현장 특성 자료의 중요성, 특히 하천수리특성에 관련된 기초 자료의 가용성 여부가 모형의 성패에 매우 중요한 역할을 함을 알 수 있다. 이는 유량, 유속 및 폭과 깊이로 대변되는 하천 지형은 물질 이송에 대한 주요 외력 함수이며, 다른 모든 예측치들은 이들에 의존적일 수밖에 없기 때문이다. 따라서 이들의 정확한 표현은 올바른 수질 예측에 있어서 필수적일 수밖에 없다. 많은 모형매개변수들이 유속과 깊이에 의존적이나, 이들에 관한 정보는 종종 현장관측에서 조차 무시되는 경우가 많다. 이에 본 연구에서는 수질모형의 매개변수 중 특히 수리특성에 관련된 매개변수들이 수질에 미치는 영향을 파악하는 것을 목적으로 하고 있다. 이를 위해 적용된 수질모형은 QualKo를 사용하였으며, 대상 하천은 낙동강 본류 경남구간 시점 부근인 회천 합류 전부터 낙동강 본류 경남구간 종점 부근인 밀양강 합류 전까지의 경남 오염총량관리 기본계획 시 구축된 모형 매개변수를 바탕으로 분석을 수행하였다. 일차오차분석을 이용하여 수리매개변수와 수질매개변수의 수질항목별 상대적 기여도를 파악해 본 결과, 수리매개변수는 DO, BOD, 유기질소, 유기인 모든 항목에 일정 정도의 상대적 기여도를 가지고 있는 것을 알 수 있었다. 이로부터 수질 모형의 적용 시 수리 매개변수 또한 수질 매개변수의 추정 시와 같이 보다 세심한 주의를 기울여 추정할 필요가 있을 것으로 판단된다.

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    Iguana motion synthesis using soft body simulation (연체 시뮬레이션 기반 이구아나 동작 생성)

    • Moon, Jaeseok;Kwon, Taesoo
      • Journal of the Korea Computer Graphics Society
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      • v.23 no.1
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      • pp.33-38
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      • 2017
    • In this paper, we suggest a method to simulate high-quality iguana animation by using low-quality motion capture data. Iguana motion data captured using a small number of markers cannot express its movement precisely, and even with a realistic skin mesh, it shows unnatural movement because of limited degrees of freedom. In order to solve this problem, we propose to simulate a natural and flexible movement by applying a soft-body simulation technique which models the movement of an iguana according to muscle forces and body's elastic forces. We construct a motion graph from the motion capture data to describe the iguana's various movements, and utilize it to select appropriate movements when the iguana moves. A target point on a terrain is set from the user's input, and a graph path is planned based on it. As a result, the input movement of iguana walking on a flat ground transforms to a movement that is adapted in an online manner to the irregular heights of the terrain. Such a movement is used to calculate the ideal muscle lengths that are needed for soft-body simulation. Lastly, a tetrahedral mesh of the iguana is physically simulated to adapt to various situations by applying a soft-body simulation technique.

    A Study on Residual Strength Assessment of Damaged Oil Tanker by Smith Method (Smith법에 의한 손상 유조선의 잔류강도 평가 연구)

    • Ahn, Hyung-Joon;Baek, Deok-Pyo;Lee, Tak-Kee
      • Journal of Navigation and Port Research
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      • v.35 no.10
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      • pp.823-827
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      • 2011
    • The present Common Structural Rules for double hull oil tanker is not included the residual strength, which is one of the functional requirements in design part of Goal-based new ship construction standards (GBS). The GBS will be enforced after July 1, 2016. The requirement related residual strength has the goal to build safe ship even if she has the specified damages due to marine accidents including collision and grounding. In order to assess the residual strength based on risk for structural damages according to GBS, tons of nonlinear FE analysis work taking into account various types of damage will be needed. The Smith's method, a kind of simplified method for the strength analysis is very useful for this purpose. In this paper, the residual strength assessments based on ultimate strength using Smith's method were carried out. The objected ship is VLCC with stranding damage in bottom structures. Also, the results were compared with that of nonlinear FE analysis using three cargo hold model.

    An Approach to Generation Monitoring Module using UML Model (UML모델을 이용한 모니터링 모듈 생성 방법)

    • Park, Jeong-Min;Jeong, Ok-Ran
      • Journal of the Korea Society of Computer and Information
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      • v.16 no.9
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      • pp.57-68
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      • 2011
    • Self-healing is an approach to evaluating constraints defined in target system and to applying an appropriate strategy when violating the constrains. Today, the computing environment is very complex, so researches that endow a system with the self-healing's ability that recognizes problem arising in a target system are being an important issues. However, most of the existing researches are that self-healing developers need much effort and time to analyze and model constraints. Thus, in order to improve these problems, this paper proposes the method that automatically generates monitoring module by using UML models for self-healing. The approach proposes: 1) defining system knowledge required for self-healing from UML model, 2) process for generating monitor, by using monitor generated, and process for monitoring the problems. Through these, we can reduce the efforts of self-healing developers to analyze target system, and secure monitoring scope based on information of system knowledge. Also we can minimize the efforts to develop the monitoring environment automatically. to evaluate the proposed approach, we apply proposed approach to ATM prototype system for qualitative result, and perform quantitative evaluation through video conference system in our existing research.

    Test Input Sequence Generation Strategy for Timing Diagram using Linear Programming (선형 계획법을 이용한 Timing Diagram의 테스트 입력 시퀀스 자동 생성 전략)

    • Lee, Hong-Seok;Chung, Ki-Hyun;Choi, Kyung-Hee
      • The KIPS Transactions:PartD
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      • v.17D no.5
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      • pp.337-346
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      • 2010
    • Timing diagram is popularly utilized for the reason of its advantages; it is convenient for timing diagram to describe behavior of system and it is simple for described behaviors to recognize it. Various techniques are needed to test systems described in timing diagram. One of them is a technique to derive the system into a certain condition under which a test case is effective. This paper proposes a technique to automatically generate the test input sequence to reach the condition for systems described in timing diagram. It requires a proper input set which satisfy transition condition restricted by input waveform and timing constraints to generate a test input sequence automatically. To solve the problem, this paper chooses an approach utilizing the linear programming, and solving procedure is as follows: 1) Get a Timing diagram model as an input, and transforms the timing diagram model into a linear programming problem. 2) Solve the linear programming problem using a linear programming tool. 3) Generate test input sequences of a timing diagram model from the solution of linear programming problem. This paper addresses the formal method to drive the linear programming model from a given timing diagram, shows the feasibility of our approach by prove it, and demonstrates the usability of our paper by showing that our implemented tool solves an example of a timing diagram model.

    Simulating Group Movement on a Roadmap-based Path (로드맵 기반 경로에서의 그룹 이동 시뮬레이션)

    • Yu, Kyeon-Ah;Cho, Su-Jin;Kim, Kyung-Hye
      • Journal of the Korea Society for Simulation
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      • v.20 no.4
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      • pp.105-114
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      • 2011
    • The roadmap-based planning is a path planning method which is used widely for a goal-directed movement in Robotics and has been applied to the world of computer animation such as computer games. However it is unnatural for computer characters to follow the path planned by the roadmap method as it is performed in Robotics. Flocking which is used for realistic and natural movements in computer animation enables character's movement by using a few simple rules without planning unlike the roadmap method. However it is impossible to achieve a goal-directed movement with flocking only because it does not keep states. In this paper we propose a simulation method which combines planning based on the road map with reactive actions for natural movements along the path planned. We define and implement steering behaviors for a leader which are needed to follow the trajectory naturally by analysing characteristics of roadmap-based paths and for the rest of members which follow the leader in various manners by detecting obstacles. The simulations are performed and demonstrated by using the implemented steering behaviors on every possible combination of roadmap-based path planning methods and models of configuration spaces. We also show that the detection of obstacle-collisions can be done effectively because paths are planned in the configuration space in which a moving object is reduced to a point.


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