• 산경연구논집
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• 제11권5호
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• pp.27-34
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• 2020

Purpose: North Korea is a very close country geographically and culturally, but the nation has been one of the most secretive countries in the world. However, in recent years, North Korean society has been known to rapidly change its economic environment as well as its diplomatic and political environment. Since the gaining power of Jong-un, Kim in 2012, the North Korean government has implemented a new set of economic policies. North Korea has embraced limited market systems and mechanisms that have become a part of the formal planned economy. This study is concerned with the recent changes in the market and marketing activities of the communist country. It also seeks to gain an understanding of the changing market behavior of North Korean consumers. The purpose of this study is to enhance understanding of the market environments of North Korea and to provide appropriate implications for practitioners and researchers. Research design, data and methodology: Academic access to information that can understand North Korea's reality is minimal. Therefore, this study was conducted based on a qualitative analysis of secondary data. The existing literature on North Korea, related news and reports were the basis of the analysis. Analysis of secondary data related to North Korea was the main methodology of the study. Results: The official ideology of North Korea rejected most aspects of marketing, and yet there were marketing activities in North Korea. This article focuses on the development of market and marketing activities in North Korea during the recent years. This study indirectly confirmed that the market function is being activated in North Korea, and the basic functions of marketing such as advertisement, price, and distribution are being formed. In this process, the activation of the 'Jangmadang(market)' played a significant role. Conclusions: Research shows that North Korea is rapidly developing its own market function. In addition, marketing activities such as advertising and pricing strategies seem to be unprecedentedly active. However, due to changes in the political environment, the future development of North Korea's marketing is still in flux. Efforts to improve mutual understanding through continuous research are required.

• 한국전산유체공학회지
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• 제16권2호
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• pp.49-55
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• 2011

Turbulent flows with wavy wall are simulated using Residual-based Variational Multiscale Method (RB-VMS) which is proposed by Bazilves et al(2007) as new Large Eddy Simulation methodology. Incompressible Navier-Stokes equations are integrated using Isogeometric analysis which adopt the basis function as NURBS. The Reynolds number is 6760 based on the bulk velocity and averaged channel height. And the amplitude (${\alpha}/{\lambda}$) of wavy wall is 0.05. The computational domain is $2{\lambda}{\times}1.05{\lambda}{\times}{\lambda}$ in the streamwise, wall normal and spanwise direction. Mean quantities and turbulent statistics near wavy wall are compared with DNS results of Cherukat et al.(1998). The predicted results show good agreement with reference data.

• 한국정밀공학회지
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• 제8권4호
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• pp.84-94
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• 1991

In order to achieve high accuracy of teaching and increase productivity using industrial robots in polishing process of dies, an off-line task programming system was developed on IBM-PC/386 under WINDOWS 3.0 operating system. The internal structure and the machematical basis of CAMPoli are described. Surface modeling technique of polishing dies with sculptured surfaces is introduced by poing data interpolation methodology through the use of CL-data transmitted from conventional CAM system. Tool selection, polishing speed, polishing pressure and kinds of tool motions can be determined and selected by user specified polishing variables. Task creation and verification of polishing path via computer graphics simulation of polishing tool can be done by the menu- driven function of CAMPoli system. Post-processing module is attached to generate robot language. Some simulation results are provided as verification means of the system.

• Journal of Mechanical Science and Technology
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• 제15권8호
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• pp.1108-1118
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• 2001

The purpose of this study is to establish a CAD (Computer Aided Design) system for research and development(R&D) of a new product. In the R&D process of a new product, the design objects are frequently redesigned based on the experimental results obtained with prototypes. The CAD/CAE systems (which is based on computer simulation of physical phenomena) are effective in reducing the number of useless prototypes of a new product. These kinds of conventional CAD/CAE systems do not provide a function to reflect the experimental results to the redesign process, however. This paper proposes a methodology to establish the CAD system, which possesses the engineering model of a designed object in the model database, and refines the model on the basis of experimental results of prototype. The blackboard inference model has been applied to infer model refinement and redesign counterplan by using insufficient knowledge of R&D process of new products.

• 한국전기전자재료학회:학술대회논문집
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• 한국전기전자재료학회 2003년도 하계학술대회 논문집 Vol.4 No.1
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• pp.252-255
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• 2003

The pulsed laser deposition process modeling is investigated using neural networks based on radial basis function networks and multi-layer perceptron. Two input factors are examined with respect to the PL intensity. In order to minimize the joint confidence region of fabrication process with varying the conditions, D-optimal experimental design technique is performed and photoluminescence intensity is characterized by neural networks. The statistical results were then used to verify the fitness of the nonlinear process model. Based on the results, this modeling methodology can be optimized process conditions for pulsed laser deposition process.

• 의료ㆍ복지 건축 : 한국의료복지건축학회 논문집
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• 제13권3호
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• pp.35-46
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• 2007

Hospital architectures, as a function-oriented architecture, have a great influences on the functional program and spacial allocation for a great number of rooms and departments. Particularly, spacial allocating analysis is depends on various external forces, such as hospital-size, relationships for the others, ownerships, operating methods, long-term masterplan as well as researchers' methods. Furthermore, as there is focusing on architectural design basis rather than architectural planning In recent Korean architectural field, adequate analysing methodology of spacial allocation for the design process is needed. This paper analyzes architectural drawings for 8 Korean hospitals which constructed in recent 20 years in aspects of the spacial allocation for inner spaces and then, presents areal composition and pattern of spacial allocation for researching hospitals.

• Computers and Concrete
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• 제16권4호
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• pp.569-585
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• 2015

Various computational tools are available for modeling highly nonlinear structural engineering problems that lack a precise analytical theory or understanding of the phenomena involved. This paper adopts a fairly simple nonparametric adaptive regression algorithm known as multivariate adaptive regression splines (MARS) to model the nonlinear interactions between variables. The MARS method makes no specific assumptions about the underlying functional relationship between the input variables and the response. Details of MARS methodology and its associated procedures are introduced first, followed by a number of examples including three practical structural engineering problems. These examples indicate that accuracy of the MARS prediction approach. Additionally, MARS is able to assess the relative importance of the designed variables. As MARS explicitly defines the intervals for the input variables, the model enables engineers to have an insight and understanding of where significant changes in the data may occur. An example is also presented to demonstrate how the MARS developed model can be used to carry out structural reliability analysis.

• Journal of Electrical Engineering and Technology
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• 제8권6호
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• pp.1615-1625
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• 2013

Modelling and simulating the wind power intermittent behaviour are the basis of the planning and scheduling studies concerning wind power integration. The wind power outputs are evidently correlated in space and time and bring challenges in characterizing their behaviour. This paper provides a methodology to model and simulate the clustered wind power considering its spatio-temporal correlations using the theory of copula. The sampling approach captures the complex spatio-temporal connections among the wind farms by employing a conditional density function calculated using multidimensional copula function. The empirical study of real wind power measurement shows how the wind power outputs are correlated and how these correlations affect the overall uncertainty of clustered wind power output. The case study validates the simulation technique by comparing the simulated results with the real measurements.

• Communications for Statistical Applications and Methods
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• 제28권5호
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• pp.425-445
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• 2021

A generalization of the log-logistic (LL) distribution called exponentiated log-logistic (ELL) distribution on lines of exponentiated Weibull distribution is considered. In this paper, based on progressive type-II censored samples, we have derived the maximum likelihood estimators and Bayes estimators for three parameters, the survival function and hazard function of the ELL distribution. Then, under the balanced squared error loss (BSEL) and the balanced linex loss (BLEL) functions, their corresponding Bayes estimators are obtained using Lindley's approximation (see Jung and Chung, 2018; Lindley, 1980), Tierney-Kadane approximation (see Tierney and Kadane, 1986) and Markov Chain Monte Carlo methods (see Hastings, 1970; Gelfand and Smith, 1990). Here, to check the convergence of MCMC chains, the Gelman and Rubin diagnostic (see Gelman and Rubin, 1992; Brooks and Gelman, 1997) was used. On the basis of their risks, the performances of their Bayes estimators are compared with maximum likelihood estimators in the simulation studies. In this paper, research supports the conclusion that ELL distribution is an efficient distribution to modeling data in the analysis of survival data. On top of that, Bayes estimators under various loss functions are useful for many estimation problems.

• 전기학회논문지
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• 제63권4호
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• pp.526-533
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• 2014

In this study, we introduce design methodology to develop a guidance for issuing heavy rainfall warning by using both RBFNNs(Radial basis function neural networks) and SVR(Support vector regression) model, and then carry out the comparative studies between two pattern classifiers. Individual classifiers are designed as architecture realized with the aid of optimization and pre-processing algorithm. Because the predictive performance of the existing heavy rainfall forecast system is commonly affected from diverse processing techniques of meteorological data, under-sampling method as the pre-processing method of input data is used, and also data discretization and feature extraction method for SVR and FCM clustering and PSO method for RBFNNs are exploited respectively. The observed data, AWS(Automatic weather wtation), supplied from KMA(korea meteorological administration), is used for training and testing of the proposed classifiers. The proposed classifiers offer the related information to issue a heavy rain warning in advance before 1 to 3 hours by using the selected meteorological data and the cumulated precipitation amount accumulated for 1 to 12 hours from AWS data. For performance evaluation of each classifier, ETS(Equitable Threat Score) method is used as standard verification method for predictive ability. Through the comparative studies of two classifiers, neuro-fuzzy method is effectively used for improved performance and to show stable predictive result of guidance to issue heavy rainfall warning.