• Journal of Korean Society for Atmospheric Environment
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• v.29 no.4
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• pp.447-458
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• 2013

The present operating system for the atmospheric monitoring network in the city of Seoul, Korea, has been established since the late 90s by the Korean Ministry of Environment (KMOE). In this research, it was evaluated by the multi-statistical approaches through combinations of time series analysis, correlation matrix, and multiple cluster analysis. Finally, road traffic including resuspended materials can be one of the main sources of particulate matter in the atmosphere. Based on its importance, it will be significant challenges in quantitative evaluation of its contribution to airborne concentrations. The future directions for their amendments such as a new management plan for the source of road dust (including car emissions) were devised and proposed based on the statistical judgements derived in this research.

• Communications for Statistical Applications and Methods
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• v.18 no.5
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• pp.595-601
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• 2011

A community of the social network refers to the subset of nodes linked more densely among them than to others. In this study, we propose a Monte-Carlo method for generating random social unipartite and bipartite networks with two or more communities. Proposed random networks can be used to verify the small world phenomenon of the social networks with several communities.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.25 no.6B
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• pp.1120-1126
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• 2000

Recently, in order to analyze the time series problems that occur in the nature word, and analyzing method using a neural electric network is being studied more than a typical statistical analysis method. A neural electric network has a generalization performance that is possible to estimate and analyze about non-learning data through the learning of a population. In this paper, after collecting weather datum that was collected from 1987 to 1996 and learning a population established, it suggests the weather forecasting system for an estimation and analysis the future weather. The suggested weather forecasting system uses 28*30*1 neural network structure, raises the total learning numbers and accuracy letting the selecting concentration learning about the pattern, that is not collected, using the descending epsilon learning method. Also, the weather forecasting system, that is suggested through a comparative experiment of the typical time series analysis method shows more superior than the existing statistical analysis method in the part of future estimation capacity.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.11 no.2
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• pp.169-174
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• 2018

In general, the methods of the analysis of variance(ANOVA) for the continuous data and the chi-square test for the discrete data are used for statistical analysis of the effect and the association. In multidimensional data, analysis of hierarchical structure is required and statistical linear model is adopted. The structure of the linear model requires the normality of the data. A multidimensional categorical data analysis methods are used for causal relations, interactions, and correlation analysis. In this paper, Bayesian network model using probability distribution is proposed to reduce analysis procedure and analyze interactions and causal relationships in categorical data analysis.

• Journal of the Korean Statistical Society
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• v.30 no.2
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• pp.265-280
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• 2001

Estimation of the edge of a distribution has many important applications. It is related to classification, cluster analysis, neural network, and statistical image recovering. The problem also arises in measuring production efficiency in economic systems. Three most promising nonparametric estimators in the existing literature are introduced. Their statistical properties are provided, some of which are new. Themes of future study are also discussed.

• The Journal of Industrial Distribution & Business
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• v.13 no.6
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• pp.9-18
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• 2022

Purpose: The government around the world is still highlighting the effect of the new variant of Covid-19. The government continues to make efforts to restore the economy through several programs, one of them is National Economic Recovery. This program is expected to increase public and investor confidence in handling Covid-19. This study aims to capture public sentiment on the economic growth rate in Indonesia, especially during the third wave of the omicron variant of the covid-19 virus, that is at the time in the fourth quarter of 2021. Research design, data, and methodology: The approach used in this research is to collect crowdsourcing data from twitter, in the range of 1st to 10th October 2021. The analysis is done by building model using Deep Learning Neural Network method. Results: The result of the sentiment analysis is that most of the tweets have a neutral sentiment on the Economic Growth discussion. Several central figures who discussed were Minister of Coordinating for the Economy of Indonesia, Minister of State-Owned Enterprises. Conclusions: Data from social media can be used by the government to capture public responses, especially public sentiment regarding economic growth. This can be used by policy makers, for example entrepreneurs to anticipate economic movements under certain conditions.

• Proceedings of the Korean Geotechical Society Conference
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• 2002.03a
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• pp.651-656
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• 2002

In general, the most important problem in slope stability analysis is that there is no definite way to describe the natural three-dimensional Joint network. Therefore, the many approaches were tried to anlayze the slope stability. Numerical modeling approach is one of the branch to resolve the complexity of natural system. UDEC, FLAC, and SWEDGE are widely used commercial code for the purpose on stability analysis. For the purpose on the more appropriate application of these kind of code, however, three-dimensional distribution of joint network must be identified in more explicit way. Remaining problem is to definitely describe the three dimensional network of joint and bedding, but it is almost impossible in practical sense. Three dimensional joint generation method with random number generation and the results of generation to UDEC have been applied to settle the refered problems in field site. However, this approach also has a important problem, and it is that joint network is generated only once. This problem lead to the limitation on the application to field case, in practical sense. To get rid of this limitation, Monte Carlo Simulation is proposed in this study 1) statistical analysis of input values and definition of the applied system with statistical parameter, 2) instead of the consideration of generated network as a real system, generated system is just taken as one reliable system, 3) present the design parameters, through the statistical analysis of ouput values Results of this study are not only the probability of failure, but also area of failure block, shear strength, normal strength and failure pattern, and all of these results are described in statistical parameters. The results of this study, shear strength, failure area, pattern etc, can provide the direct basement on the design, cutoff angle, support pattern, support strength and etc.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.42 no.4
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• pp.923-931
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• 2017

A power grid is one of the most complex networks and is critical infrastructure for society. To understand the characteristics of a power grid, complex network analysis has been used from the early 2000s mainly for US and European power grids. However, since the power grids of different countries might have different structures, the Korean power grid needs to be examined through complex network analysis. This paper performs the analysis for the Korean power grid, especially for high-voltage transmission networks. In addition, statistical and small-world characteristics for the Korean power grid are analyzed. Generally, the Korean power grid has similar characteristics to other power grids, but some characteristics differ because the Korean power grid is concentrated in the capital area.

• The Korean Journal of Applied Statistics
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• v.36 no.1
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• pp.1-19
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• 2023

The purpose of this study was to find out what attributes are valid for the edge between students through longitudinal network analysis, and the results of TERGM (temporal exponential random graph model) and SAOM (stochastic actor-oriented model) statistical models were compared. The TERGM model interprets the research results based on the edge formation of the entire network, and the SAOM model interprets the research results on the surrounding networks formed by specific actors. The TERGM model expressed the influence of a previous time through a time term, and the SAOM model considered temporal dependence by implementing a network that evolves by an actor's opportunity as a ratio function.

• Proceedings of the Korean Society for Rock Mechanics Conference
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• 2000.09a
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• pp.129-137
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• 2000

This paper presents groundwater flow characteristics in discontinuous rock mass using fracture network program(NAPSAC) by statistical approach. Equivalent permeability coefficients are estimated from borehole data around Mabuk test tunnel site and fracture map on the arch of the tunnel. The reliability of fracture network model is obtained from determination of input data for statistical fracture network analysis from the real data(data of fracture network, data of hydraulic tests). The variation of permeability and mean anisotropic permeability coefficients are calculated from the realized model by increasing the size. As a result of analysis, a strong anisotropy of permeability is observed according to the direction of the fracture sets around the test tunnel.