• Journal of the military operations research society of Korea
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• v.26 no.2
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• pp.75-89
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• 2000

This paper deals with complex system theory to describe guerrilla warfare situation using EINSTein (Enhanced ISAAC Neural Simulation Tool) simulation model. EINSTein model is an agent-based artificial "laboratory" for exploring self-organized emergent behavior in land combat. Many studies have shown that existing Lanchester equations used in most guerrilla warfare models do not describe changes of combat units, real guerrilla warfare situation and qualitative factors in combat. Future warfare will be information warfare with various weapon system and complex combat units. We have compared and tested results with Lanchester models and EINSTein model. And the EINSTein model has been applied and analyzed to guerrilla warfare model (C4I facilities, coastal, urbanized terrain critical facilities defense). The results show that the EINSTein model has a possibility to apply and analyze guerrilla warfare more properly than Lanchester models.

• Journal of the Korean Institute of Electrical and Electronic Material Engineers
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• v.15 no.1
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• pp.7-14
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• 2002

In this paper, neutral networks are used to build models of oxide film etched In CHF$_3$/CF$_4$ with a magnetically enhanced reactive ion etcher(MERIE). A statistical 2$\^$4-1/ experimental design plus one center point was used to characterize relationships between process factors and etch responses. The factors that were varied include radio frequence(rf) power, pressure, CHF$_3$ and CF$_4$ flow rates. Resultant 9 experiments were used to train neural networks and trained networks were subsequently tested on its appropriateness using additionally conducted 8 experiments. A total of 17 experiments were thus conducted for this modeling. The etch responses modeled are dc bias voltage, etch rate and etch uniformity A qualitative, good agreement was obtained between predicted and observed behaviors.

• Journal of KIISE:Computing Practices and Letters
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• v.6 no.1
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• pp.45-57
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• 2000

Traditional network management technologies don't have interoperability to use differentprotocols or management information models each other. Many researchers have tried to find solutions of these problems to use distributed paradigms. But the benefits of existing models are mainly supported only by qualitative evidences rather than by quantitative evidences. In this paper, we present a quantitative evidence of the efficiency of network management model using mobile agent paradigm. To compare distributed paradigms and proposed model, we use parameterized traffic models for measuring the amount of whole traffic generated by each model.

• Korean Journal of Cognitive Science
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• v.10 no.4
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• pp.63-70
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• 1999

Reconstruction of collision accidents is to analyze the cause of accidents and collision behavior using available information from vehicle accident circumstances. This paper introduces a collision reconstruction system which is developed to be applicable to traffic accident reconstruction. Our System combines both quantitative and qualitative collision models so as to compensate for weaknesses in each with strengths of each other. I It provides accurate predictions and causal explanations of the collision behavior. During r reverse analysis of collision. qualitative simulation is used to verify a hypothesis and to detect any conflict in early stage of reconstruction. It is implemented and applied to real car-to-car collision accidents. The test results verify the reliabilities of our techniques.

• Human Ecology Research
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• v.55 no.6
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• pp.581-592
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• 2017

This study investigated the occupational experiences of social workers in child care facilities. The participants of the study were six social workers in child care facilities. This qualitative research used a Consensual Qualitative Research (CQR) method that and classified the main findings into five categories and twelve sub-themes. This study revealed that child care professionals define themselves as "caregivers" and "role models." Positive effects of institutional life on a child were forming peer relationships and being able to use diverse services while negative effects included acquiring a social stigma, having problems in developing attachment between a child and a surrogate caregiver, developing passive attitude and weak will power from communal living. Meanwhile, conflicts with children and poor working conditions led to burnout for caregivers. Our recommendations on the direction of change for the facilities are: categorizing admitted children, supporting restoration of family functions, reinforcing support for children's preparation for an independent life, and developing expertise. This paper provides a better understanding of child care facilities as well as encourages further social discourse on institutionalized children in order to promote policy making and implementation.

• Proceedings of the Korean System Dynamics Society
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• 1999.08a
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• pp.105-132
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• 1999

If a system such as a port has a large boundary and complexity, and the system's substance is considered as a black box, forecast accuracy will be very low. Furthermore various components in a port exert significant influence on each other. To copy with these problem the form of structure models were introduced by using SD method. The Competitive Ports Model had several sub-systems consisting of each Unit Port models, and each Unit Port model was made by quantitative, qualitative factors and their feedback loops. The fact that all components of one port have influence on the components of the other ports should be taken into account to construct Competitive Port Models. However, with the current approach that is impossible, and in this paper, therefore, models were simplified by HFP adapted to integrate level variables of unit port models. Although many studies on modelling of port competitive situation have been conducted, both theoretical frame and methodology are still very weak. In this study, a new algorithm called ESD(Extensional System Dynamics) for the evaluation of port competition was presented, and applied to simulate port systems in northeast Asia.

• Water for future
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• v.23 no.4
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• pp.487-497
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• 1990

The qualitative and quantitative prediction for the dispersion of thermal discharge from nuclear / fossil power plant, steel works etc. has significant roles for the cooling system. Design and environmental management. In this study, the several important physical properties for the behavior of a thermal discharge with strong turbulent and buoyant effects are described. The comparative evaluation between MIT and PDS models is carried out, which have the different model structures. In general, MIT and PDS models are commonly used to calculate the thermal discharge behavior with considering the ambient current and the angle of jet in an unstratified water body. The simulated results by these models have great discrepancies due to the different assumptions in modling.

• Structural Engineering and Mechanics
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• v.71 no.6
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• pp.739-749
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• 2019

This article deals with the application of reliability analysis for determining the safety of simply supported beam under the uniformly distributed load. The uncertainties of the existing methods were taken into account and hence reliability analysis has been adopted. To accomplish this aim, Generalized Regression Neural Network (GRNN), Extreme Learning Machine (ELM) and Gaussian Process Regression (GPR) models are developed. Reliability analysis is the probabilistic style to determine the possibility of failure free operation of a structure. The application of probabilistic mathematics into the quantitative aspects of a structure and improve the qualitative aspects of a structure. In order to construct the GRNN, ELM and GPR models, the dataset contains Modulus of Elasticity (E), Load intensity (w) and performance function (${\delta}$) in which E and w are inputs and ${\delta}$ is the output. The achievement of the developed models was weighed by various statistical parameters; one among the most primitive parameter is Coefficient of Determination ($R^2$) which has 0.998 for training and 0.989 for testing. The GRNN outperforms the other ELM and GPR models. Other different statistical computations have been carried out, which speaks out the errors and prediction performance in order to justify the capability of the developed models.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2003.05a
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• pp.1142-1149
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• 2003

Various organizational factors effect successful implementation of IT enabled business transformation. Among them, the most critical success factor is deemed to overcoming change management problem. Lots of studies have been made on Implementation methodologies and business process formalizations to encourage organizational members to accept new business process changes. However, the logic or process redesign still depends on qualitative problem solving techniques mostly depending on basically human intuition such as brainstorming. cause-and-effect analysis. and so on. In this paper, we focused on developing analytic framework to design to-be business process structure. which can complement qualitative problem solving procedures. With effective use of IT as an enabler, we provide algorithmic framework applicable to designing various business process changes such as process automation, business process resequencing, and more radical process integration. The framework follows dynamic programming approach in the literature, which is based on the decision making paradigm of organizations to abstract business processes as quantitative decision models. As such, our research ran fill the gap of limited development of theory based analytic methodologies for business process design, by providing objective rationale to reach the consensus among the organizational members including senior management.

• Journal of Information Processing Systems
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• v.15 no.6
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• pp.1489-1502
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• 2019

This work introduces a novel unweighted combination method (UCSS) for business failure perdition (BFP). With considering features of BFP in the age of big data, UCSS integrates the quantitative and qualitative analysis by utilizing soft set theory (SS). We adopt the conventional expert system (ES) as the basic qualitative classifier, the logistic regression model (LR) and the support vector machine (SVM) as basic quantitative classifiers. Unlike other traditional combination methods, we employ soft set theory to integrate the results of each basic classifier without weighting. In this way, UCSS inherits the advantages of ES, LR, SVM, and SS. To verify the performance of UCSS, it is applied to real datasets. We adopt ES, LR, SVM, combination models utilizing the equal weight approach (CMEW), neural network algorithm (CMNN), rough set and D-S evidence theory (CMRD), and the receiver operating characteristic curve (ROC) and SS (CFBSS) as benchmarks. The superior performance of UCSS has been verified by the empirical experiments.