• The Transactions of the Korean Institute of Electrical Engineers C
• /
• v.49 no.8
• /
• pp.477-486
• /
• 2000

This paper presents Pspice modeling methods for spark gaps and ZnO varistors and describes the application for the two-stage surge suppression circuit which was composed of the nonlinear components. The simulation modelings of nonlinear components were conducted on the basis of the voltage and current curves measured by the impulse current with the time-to-crest of $1~50 \mus$ and the impulse voltage with the rate of the time-to-crest of 10, 100 and 1000 V/\mus$. The firing voltages of the spark gap increased with increasing the rate of the time-to-crest of impulse voltage and the measured data were in good agreement with the simulated data. The I-V curves of the ZnO varistor were measured by applying the impulse currents of which time-to-crests range from 1 to $50 \mus$ and peak amplitudes from 10 A to 2 kA. The simulation modeling was based on the I-V curves replotted by taking away the inductive effects of the test circuit and leads. The meximum difference between the measured and calculated data was of the order of 3%. Also the two-stage surge suppression circuit made of the spark gap and the ZnO varistor was investigated with the impulse voltage of $10/1000\mus$$mutextrm{s}$ wave shape. The overall agreement between the theoretical and experimental results seems to be acceptable. As a consequence, it was known that the proposed simulation techniques could effectively be used to design the surge suppression circuits combined with nonlinear components.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
• /
• v.7 no.4
• /
• pp.151-158
• /
• 2014

In this paper, we introduce an inference system using hard scatter partition method and model the nonlinear process. To do this, we use the hard scatter partition method that partition the input space in the scatter form with the value of the membership degree of 0 or 1. The proposed method is implemented by C-Means clustering algorithm. and is used for the initial center values by means of binary split. by applying the LBG algorithm to compensate for shortcomings in the sensitive initial center value. Hard-scatter-partitioned input space forms the rules in the rule-based system modeling. The premise parameters of the rules are determined by membership matrix by means of C-Means clustering algorithm. The consequence part of the rules is expressed in the form of polynomial functions and the coefficient parameters of each rule are determined by the standard least-squares method. The data widely used in nonlinear process is used to model the nonlinear process and evaluate the characteristics of nonlinear process.

• Journal of the Korea Academia-Industrial cooperation Society
• /
• v.13 no.11
• /
• pp.5379-5388
• /
• 2012

In fuzzy modeling for nonlinear process, the fuzzy rules are typically formed by selection of the input variables, the number of space division and membership functions. The Generation of fuzzy rules for nonlinear processes have the problem that the number of fuzzy rules exponentially increases. To solve this problem, complex nonlinear process can be modeled by generating the fuzzy rules by means of fuzzy division of input space. Therefore, in this paper, rules of non-fuzzy inference systems are generated by partitioning the input space in the scatter form using HCM clustering algorithm. The premise parameters of the rules are determined by membership matrix by means of HCM clustering algorithm. The consequence part of the rules is represented in the form of polynomial functions and the consequence parameters of each rule are identified by the standard least-squares method. And lastly, we evaluate the performance and the nonlinear characteristics using the data widely used in nonlinear process. Through this experiment, we showed that high-dimensional nonlinear systems can be modeled by a very small number of rules.

• Journal of Korean Academy of Nursing
• /
• v.47 no.5
• /
• pp.663-675
• /
• 2017

Purpose: The purpose of this study was to construct and test a structural equation model of self-management of liver transplant recipients based on self-determination theory. Methods: Participants were 275 outpatients who received liver transplantation. A structured self-report questionnaire was used to assess health care providers' autonomy support, transplant-related characteristics, illness consequence perception, autonomy, competence, family relatedness, depression and self-management. Collected data were analyzed using SPSS/WIN 24.0 and AMOS 24.0 program. Results: The modified model showed a good fitness with the data: GFI=.96, RMSEA=.06, CFI=.96, NFI=.93, TLI=.93, PGFI=.43, PNFI=.49. The health care providers' autonomy support, competence, family relatedness and depression were factors with a direct influence on the self-management of liver transplant recipients. The health care providers' autonomy support and illness consequence perception had an indirect influence through competence, family relatedness and depression. However, the transplant-related characteristics and autonomy did not have a significant effect on self-management. This model explained 59.4% of the variance in self-management. Conclusion: The result suggests that continuous education must be done to promote the competence of liver transplant recipients and to encourage the patient to positively perceive their current health condition with a view that enhances one's self-management. Additionally, the liver transplant recipients should be screened for depression, which would affect self-management. Most of all, health care providers, who have the most influence on self-management, should improve therapeutic communication and try to form a therapeutic relationship with the liver transplant recipients.

• The Transactions of the Korean Institute of Electrical Engineers D
• /
• v.53 no.8
• /
• pp.561-570
• /
• 2004

In this paper, new architectures and comprehensive design methodologies of Genetic Algorithms(GAs) based Genetically optimized Neurofuzzy Networks(GoNFN) are introduced, and a series of numeric experiments are carried out. The proposed GoNFN is based on the rule-based Neurofuzzy Networks(NFN) with the extended structure of the premise and the consequence parts of fuzzy rules being formed within the networks. The premise part of the fuzzy rules are designed by using space partitioning in terms of fuzzy sets defined in individual variables. In the consequence part of the fuzzy rules, three different forms of the regression polynomials such as constant, linear and quadratic are taken into consideration. The structure and parameters of the proposed GoNFN are optimized by GAs. GAs being a global optimization technique determines optimal parameters in a vast search space. But it cannot effectively avoid a large amount of time-consuming iteration because GAs finds optimal parameters by using a given space. To alleviate the problems, the dynamic search-based GAs is introduced to lead to rapidly optimal convergence over a limited region or a boundary condition. In a nutshell, the objective of this study is to develop a general design methodology o GAs-based GoNFN modeling, come up a logic-based structure of such model and propose a comprehensive evolutionary development environment in which the optimization of the model can be efficiently carried out both at the structural as well as parametric level for overall optimization by utilizing the separate or consecutive tuning technology. To evaluate the performance of the proposed GoNFN, the models are experimented with the use of several representative numerical examples.

• Journal of KIISE:Computing Practices and Letters
• /
• v.7 no.5
• /
• pp.498-509
• /
• 2001

Collaborative systems allow users, who may be far removed from each other geographically, to do collaborative work such as 3D animation, computer game, and industrial design in a single virtual space. This paper describes our experience to develop a collaborative system framework that aims at expanding the some functions of a stand-alone visual modeling tool, called 3D Studio Max, into those of the distributed collaborative working environments. The paper mainly deals with design and implementation of a 3D shared-object Plug-In with respect to the 3D Studio Max Plug-In Software Development Kit in the distributed collaborative system developed by the authors. There are two major functions of the proposed scheme; one is to write 3D object-information to the shared memory after extracting it from the 3D Studio Max, the other is to create 3D objects after retrieving them from the shared memory. Also, the proposed scheme provides a simple way of storing 3D objects that have variable size, by means of shared memory which located in between the collaborative system clients and 3D studio Max. One of the remarkable virtures of the Plug-In is to reduce a considerable amount of shared object data which in consequence can mitigate the network overhead. This can be achieved by the fact that the system is able to extract a minimum amount of 3D objects that are required to transmit. Also, using the proposed scheme, user can facilitate 3D Studio Max into distributed collaborative working environments. This, in consequence give many benefits such as saving time as well as eliminating space constraints in the course of 3D modeling when we are under industrial design process.

• Journal of Distribution Science
• /
• v.14 no.6
• /
• pp.65-73
• /
• 2016

Purpose - Recently, the management conditions of small independent retailers are getting worse everyday as large-scale marts and franchised convenience stores are increasing. The objective of this research is to find out the antecedents and consequences of cooperation in voluntary chain in order to enhance small independent retailer's competitiveness. Voluntary chains, also called affiliation or symbol groups, or allied group represent a high market shared in some European countries like Italy, France, and Germany. Nevertheless, there are still limitations in this research from academic fields. Drawing from network theory, the author investigates the relationship between antecedent factors in voluntary chain cooperation, such as participation benefits, justice of compensation, and autonomy in voluntary chain, and relationship specific asset. The author also attempts to examine the relationship between the relationship specific asset and cooperation of voluntary chain member shop and cooperation and consequence factors of voluntary chain cooperation, such as efficiency, group cohesiveness, and long-term relationship. Research design, data, and methodology - The author presented conceptual framework integrating the major antecedents and consequences of voluntary chain cooperation. The data were collected from 174 independent small retailers who joined K-voluntary chain. K-voluntary chain consists of small independent retailers. In accordance with their status, each entrepreneur associated with the voluntary group can own one or more outlets and can be a part of the life and the decision-making process of the group. This participation is not based on company turnover or on the number of outlets, but based on a one member, one vote system. To verify the research model and test hypotheses, the author carefully investigated the reliability, content validity, convergent validity, and discriminant validity of the proposed model. The data were analyzed by using SPSS 18.0 and AMOS structural equation modeling program. Results - The results of this study are as follows. First, as antecedent variables, participation benefits and justice of compensation have positive effect on the relationship specific assets of voluntary chain members. Second, voluntary chain members' relationship specific asset also directly related to the level of its cooperation to chain headquarter. Third, cooperation of voluntary chain member shop facilitates efficiency, group cohesiveness, and long-term relationship. Unexpectedly, there are no effect autonomy in voluntary chain to relationship specific asset. Conclusions - This research shows several theoretical and practical implications to both marketing scholars and marketers. In terms of theoretical implications, this study applies to network theory and network theory variables to explain the antecedent and consequence factors of cooperation in voluntary chain. From the point of view from business management, most of all, this study shows the way how to reinforce competitiveness of voluntary chain. Specifically, it is necessary for voluntary chain headquarter to give higher level of participation benefit and justice of compensation to its members. Second, the results also indicate what the consequence factors of cooperation in voluntary chain. In other words, to increase the level of marketing efficiency, group cohesiveness, long-term orientation in retail voluntary chain, and chain headquarter need to facilitate participants' cooperation.

• Korean Chemical Engineering Research
• /
• v.57 no.1
• /
• pp.42-50
• /
• 2019

As the industry develops in Korea, the use of hazardous chemicals is increasing rapidly and chemical accidents are increasing accordingly. Most of the chemical accidents are caused by leaks of hazardous chemicals, but there are also accidents in which all the substances are released instantaneously due to sudden high temperature/pressure or defection of the storage tanks. This is called catastrophic failure and its frequency is very low, but consequence is very huge when it occurs. In Korea, there were 15 casualties including three deaths due to catastrophic rupture of water tank in 2013, and 64 instances of failures from 1919 to 2004 worldwide. In case of catastrophic failure, it would be able to overflow outside the bund that reduces the evaporation rate and following consequence. This incident is called overtopping. Overseas, some researchers have been studying the amount of external overflow depending on bund conditions in the event of such an accident. Based on the previous research, this study identified overtopping fraction by condition of bund in accordance with Korea Chemicals Controls Act Using CFD simulation. As a result, as the height increases and the distance to the facility decreases while meeting the minimum standard of the bund capacity, the overtopping effect has decreased. In addition, by identifying the effects of overtopping according to atmospheric conditions, types of materials and shapes of bunds, this study proposes the design of the bund considering the effect of overtopping caused by catastrophic failure with different bund conditions.

• Journal of Digital Convergence
• /
• v.12 no.4
• /
• pp.277-283
• /
• 2014

Fuzzy modeling is generally using the given data and the fuzzy rules are established by the input variables and the space division by selecting the input variable and dividing the input space for each input variables. The premise part of the fuzzy rule is presented by selection of the input variables, the number of space division and membership functions and in this paper the consequent part of the fuzzy rule is identified by polynomial functions in the form of linear inference and modified quadratic. Parameter identification in the premise part devides input space Min-Max method using the minimum and maximum values of input data set and C-Means clustering algorithm forming input data into the hard clusters. The identification of the consequence parameters, namely polynomial coefficients, of each rule are carried out by the standard least square method. In this paper, membership function of the premise part is dividing input space by using trapezoid-type membership function and by using gas furnace process which is widely used in nonlinear process we evaluate the performance.

• Journal of Korean Society on Water Environment
• /
• v.28 no.1
• /
• pp.84-93
• /
• 2012

The study was conducted to analyze the spatio-temporal changes in water quality of the major 36 sampling stations of Nakdong River, depending on each station, season using the 17 water quality variables from 2000 to 2010. The result was verified to interpret the characteristics of water quality variables in a more accurate manners. According to the Principal component analysis (PCA) and Exploratory factor analysis (EFA) results; the results of these analyses were identified 4 factors, Factor 1 (nutrients) included the concentrations of T-N, T-P, $NO_{3}-N$, $PO_{4}-P$, DTN, DTP for sampling station and season, Factor 2 (organic pollutants) included the concentrations of BOD, COD, Chl-a, Factor 3 (microbes) included the concentrations of F.Coli, T.Coli, and Factor 4 (others) included the concentrations of pH, DO. The results of a Cluster analysis indicated that Geumhogang 6 was the most contaminated site, while tributaries and most of the down stream sites of Nakdong River were mainly affected by each nutrients (Factor 1) and organic pollutants (Factor 2). The verification consequence of Confirmatory factor analysis (CFA) from Exploratory factor analysis (EFA) result can be summarized as follows: we could find additional relations between variables besides the structure from EFA, which we obtained through the second-order final modeling adopted in CFA. Nutrients had the biggest impact on water pollution for each sampling station and season. In particular, It was analyzed that P-series pollutant should be controlled during spring and winter and N-series pollutant should be controlled during summer and fall.