• Molecules and Cells
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• 제44권6호
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• pp.377-383
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• 2021

Severe acute respiratory syndrome-coronavirus 2 (SARS-CoV-2) is a novel virus that causes coronavirus disease 2019 (COVID-19). To understand the identity, functional characteristics and therapeutic targets of the virus and the diseases, appropriate infection models that recapitulate the in vivo pathophysiology of the viral infection are necessary. This article reviews the various infection models, including Vero cells, human cell lines, organoids, and animal models, and discusses their advantages and disadvantages. This knowledge will be helpful for establishing an efficient system for defense against emerging infectious diseases.

• ETRI Journal
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• 제40권2호
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• pp.188-196
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• 2018

This paper presents a pulse radar system to detect drones based on a target fluctuation model, specifically the Swerling target model. Because drones are small atypical objects and are mainly composed of non-conducting materials, their radar cross-section value is low and fluctuating. Therefore, determining the target fluctuation model and applying a proper integration method are important. The proposed system is herein experimentally verified and the results are discussed. A prototype design of the pulse radar system is based on radar equations. It adopts three different pulse modes and a coherent pulse integration to ensure a high signal-to-noise ratio. Outdoor measurements are performed with a prototype radar system to detect Doppler frequencies from both the drone frame and blades. The results indicate that the drone frame and blades are detected within an instrumental maximum range. Additionally, the results show that the drone's frame and blades are close to the Swerling 3 and 4 target models, respectively. By the analysis of the Swerling target models, proper integration methods for detecting drones are verified and can thus contribute to increasing in detectability.

• Journal of the Korean Statistical Society
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• 제3권2호
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• pp.103-115
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• 1974

During the last few years there has been an interest in models for qualitative attributes, where complex signifies that affection may be caused in two or more ways [1-3]. These models have in common the prediction of variable recurrence risks among families with given parental phenotpes. Segregation analysis has covered only a few cases [4,5]. The present paper extends segregation analysis to three complex models under two mode of ascertainment.

• Steel and Composite Structures
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• 제17권6호
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• pp.835-850
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• 2014

The fire resistance of composite steel and concrete structures may be determined by using the simplified methods provided in EN 1994-1-2. For the particular situations not covered by the standard, an advanced calculation model might be applied, using special purpose programs for the analysis of structures in fire. The validation of these programs has always been an important issue for software developers, but also for designers and authorities. Clause 4.4.4 from EN 1994-1-2 refers to the validation of the advanced calculation models and states that these models must be validated through relevant test results. The paper presents the calculation of fire resistance of the composite columns in a high-rise building built in Romania, and focusses on the validation of the calculation model (computer program SAFIR), for this particular case. This validation, asked by the Romanian authorities, considers the available experimental results of a fire test, performed on a similar composite steel-concrete column.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1989년도 한국자동제어학술회의논문집; Seoul, Korea; 27-28 Oct. 1989
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• pp.643-648
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• 1989

This paper presents a theoretic study and computer simulation of models and approaches for dynamical obstacle avoidance by mobile robots. The movement of obstacles in unknown environment is described by any one or a combination of three models. The control strategy of the mobile robots is formulated based on one of three approaches. A trajectory-guided control strategy for dynamical obstacle avoidance has been developed. The method greatly simplifies the control process of mobile robots, and is computationally attractive.

• 한국전산구조공학회:학술대회논문집
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• 한국전산구조공학회 2002년도 가을 학술발표회 논문집
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• pp.139-145
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• 2002

In this study, the geometric modeling has been conducted for 2 models of lower end fitting of advanced LWR fuel using three-dimensional solid modeler, Solidworks. Then, the optimization and the three-dimensional stress analysis using the finite element method has been peformed. The evaluation for the mechanical integrity of 2 models has been peformed based on the stress distribution obtained from the finite element analysis.

• 한국지능정보시스템학회:학술대회논문집
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• 한국지능정보시스템학회 2000년도 춘계정기학술대회 e-Business를 위한 지능형 정보기술 / 한국지능정보시스템학회
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• pp.235-241
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• 2000

This article suggests integrated neural network models for the interest rate forecasting using change point detection. The basic concept of proposed model is to obtain intervals divided by change point, to identify them as change-point groups, and to involve them in interest rate forecasting. the proposed models consist of three stages. The first stage is to detect successive change points in interest rate dataset. The second stage is to forecast change-point group with data mining classifiers. The final stage is to forecast the desired output with BPN. Based on this structure, we propose three integrated neural network models in terms of data mining classifier: (1) multivariate discriminant analysis (MDA)-supported neural network model, (2) case based reasoning (CBR)-supported neural network model and (3) backpropagation neural networks (BPN)-supported neural network model. Subsequently, we compare these models with a neural networks (BPN)-supported neural network model. Subsequently, we compare these models with a neural network model alone and, in addition, determine which of three classifiers (MDA, CBR and BPN) can perform better. This article is then to examine the predictability of integrated neural network models for interest rate forecasting using change-point detection.

• 한국산학기술학회:학술대회논문집
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• 한국산학기술학회 2003년도 Proceeding
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• pp.65-69
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• 2003

As complex mathematical models are increasingly adopted for business decision-making, difficulties arise in reusing solvers (i.e., model solving algorithms) against diverse models and data sets and thus the collaboration among users (model/solver builders and decision makers) in multiple departments becomes very difficult. To facilitate the solver reuse, this paper adopts the Web services technologies as the base technologies for linking the solvers to the models, both of which are created on different modeling paradigms and different system platforms, in unified system architecture. Specifically, this paper focuses on designing an ontology that represents the interfacing semantics of the model-solver interactions in a general and standardized form. By referring to the ontology, a model management system (MMS) can autonomously suggest a set of compatible solvers and apply them to individual models even though the decision makers are not knowledgeable enough about all the details of the models and the solvers. Thus, this Web services based MMS would improve the reusability of the solvers by relieving the decision makers from the risk of erroneous application of a solver to syntactically and semantically incompatible models and the burden of considerable understanding of model and solver semantics.

• 한국경영과학회:학술대회논문집
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• 대한산업공학회/한국경영과학회 2000년도 춘계공동학술대회 논문집
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• pp.284-284
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• 2000

• 한국전산유체공학회:학술대회논문집
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• 한국전산유체공학회 2003년도 The Fifth Asian Computational Fluid Dynamics Conference
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• pp.67-69
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• 2003