• Journal of the Korean Society for Industrial and Applied Mathematics
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• v.19 no.3
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• pp.217-234
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• 2015

In this tutorial the theoretical background of LQ optimal guidance is reviewed, starting from calculus of variations. LQ optimal control is then introduced and applied to missile guidance to obtain the basic form of LQ optimal guidance laws. Extension of LQ optimal guidance methodology for handling weighted cost function, dynamic lag associated with the missile dynamics and the autopilot, constrained impact angle, and constrained impact time is also described with a brief discussion on the asymptotic properties of the optimal guidance laws. Furthermore, an introduction to polynomial guidance and generalized impactangle-control guidance, which are closed related with LQ optimal guidance, is provided to demonstrate the current status of missile guidance techniques.

• Translational and Clinical Pharmacology
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• v.26 no.3
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• pp.115-117
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• 2018

This tutorial explains the basic principles of mechanistic ligand-receptor interaction model, which is an operational model of agonism. A growing number of agonist drugs, especially immune oncology drugs, is currently being developed. In this tutorial, time-dependent ordinary differential equation for simple $E_{max}$ operational model of agonism was derived step by step. The differential equation could be applied in a pharmacodynamic modeling software, such as NONMEM, for use in non-steady state experiments, in which experimental data are generated while the interaction between ligand and receptor changes over time. Making the most of the non-steady state experimental data would simplify the experimental processes, and furthermore allow us to identify more detailed kinetics of a potential drug. The operational model of agonism could be useful to predict the optimal dose for agonistic drugs from in vitro and in vivo animal pharmacology experiments at the very early phase of drug development.

• Knowledge Management Research
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• v.20 no.1
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• pp.1-26
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• 2019

This tutorial introduces procedures and methods for performing structural equation modeling using R. For this, we present the whole process of analyzing the structural equations model from the confirmatory factor analysis to the path diagram generation using the lavaan package, which is relatively well evaluated among the R packages supporting the structural equation modeling, together with the R program codes. Considering that research applying structural equation modeling techniques is the mainstream in a variety of social sciences, including business administration, and that there is growing interest in open source R, this tutorial focuses on researchers who are looking for alternatives to traditional commercial statistical packages and is expected that it will be a useful guidebook for them.

• Knowledge Management Research
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• v.20 no.2
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• pp.1-24
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• 2019

This tutorial introduces procedures and methods for performing structural equation modeling using R. To do this, we present advanced analysis methods based on structural equation model such as mediation effect analysis, moderation effect analysis, moderated mediation effect analysis, and multiple-group analysis with R program code using R lavaan package that supports structural equation modeling. R is flexible and scalable, unlike traditional commercial statistical packages. Therefore, new analytical techniques are likely to be implemented ahead of any other statistical package. From this point of view, R will be a very appropriate choice for applying new analytical techniques or advanced techniques that researchers need. Considering that various studies in the social sciences are applying structural equations modeling techniques and increasing interest in open source R, this tutorial is expected to be useful for researchers who are looking for alternatives to existing commercial statistical packages.

• Journal of Preventive Medicine and Public Health
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• v.55 no.2
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• pp.116-124
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• 2022

Epidemiological studies typically examine the causal effect of exposure on a health outcome. Standardization is one of the most straightforward methods for estimating causal estimands. However, compared to inverse probability weighting, there is a lack of user-centric explanations for implementing standardization to estimate causal estimands. This paper explains the standardization method using basic R functions only and how it is linked to the R package stdReg, which can be used to implement the same procedure. We provide a step-by-step tutorial for estimating causal risk differences, causal risk ratios, and causal odds ratios based on standardization. We also discuss how to carry out subgroup analysis in detail.

• Journal of the Korean Statistical Society
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• v.30 no.2
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• pp.291-325
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• 2001

The paper is a tutorial introduction to quantum information theory, developing the basic model and emphasizing the role of statistics and probability.

• Proceedings of the Korean Institute of Communication Sciences Conference
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• 2006.07a
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• pp.39-55
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• 2006

• 한국초전도학회:학술대회논문집
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• v.11
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• pp.14-14
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• 2001

• Proceedings of the Korean Vacuum Society Conference
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• 2011.02a
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• pp.4-4
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• 2011

In this tutorial, I will review a brief history of graphene research, summarize current research status, and discuss impacts on various fields in future.

• The Journal of Korean Association of Computer Education
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• v.9 no.3
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• pp.75-84
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• 2006

Usually, the purpose of tutorial courseware is to improve studies accomplishment degree of students. These coursewares must include enough contents of subject and characteristics of subject matter. And should support utilization to keep learning motivation continuously. In this paper, we proposed tutorial courseware for elementary student that reflect above elements. The subject is 'animal feature' in elementary. Applied in class that the proposed program. On the basis of the result that apply in class, compare with traditional courseware and analyzed about assessment and utilization. As a result, assessment is meaning all statistically, but assessment of our courseware is improved most. also usefulness is a good. Therefore, we confirmed that influence to assessment according to composition method and contents of courseware.