• The Journal of Korean Institute of Communications and Information Sciences
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• v.21 no.2
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• pp.435-446
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• 1996

In this paper, we present database model of directory systems that perform a task for distributed information repositories in communication network environments. A new model is developed through four phase: (1) A diretory database information is classified that would be stored in directory database as user, administrative, and supplementary information. (2) The modeling criteria are captured that would be used to model information classified. (3) Object-Oriented concepts are used in modeling classified information according to modeling criteria captured. (4) Methods applied to developed model are grouped, and active-based mechanisms such as trigger and constraints are developed. These selected methods and attributes are encapsulated into objects. Consequently they compose an Active Object-Oriented Directory Database Model.

• Journal of The Korean Association of Information Education
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• v.1 no.2
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• pp.1-15
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• 1997

In this paper we present database model for Intelligent Peripheral (IP) of Advanced Intelligent Network (AIN). The new model is developed through four phase. (1) An information of AIN IP is classified that would be stored in AIN IP database as specialized resources, service. schema and system information. (2) The modeling criteria are developed that would be used to model information classified. (3) Object-oriented concepts are used in modelifl8 classified information according to modeling criteria captured. (4) Methods applied to developed model are grouped, and active-based mechnisms such as trigger and constraints are developed. These selected methods and attributes are encapsulated into objects. Consequently they compose an active object-oriented AIN IP database model.

• Journal of Korea Water Resources Association
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• v.35 no.5
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• pp.501-510
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• 2002

During drought or impending drought period, the reservoir operation method is required to incorporate demand-management policy rule. The objective of this study is focused to the development of demand reduction rule by incorporating hedging-effect for a single reservoir system. To improve the performance measure of the objective function and constraints, we could incorporate three risk performance criteria proposed by Hashimoto et al. (1982) by mixed-integer programming and also incorporate successive linear programming to overcome nonlinear hedging term from the previous study(Shih et al., 1994). To verify this model, this hedging rule was applied to the Daechung multi-purpose dam. As a result, we could evaluate optimal hedging parameters and monthly trigger volumes.

• Asia pacific journal of information systems
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• v.26 no.2
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• pp.268-289
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• 2016

While most of studies have paid attention to the initial adoption of a specific application, research on applications has not focused on an individual's update decision process. This study draws upon both dual information processing and status quo bias perspectives as a comprehensive theoretical lens to explain why individuals do not update their applications. This study assumes that individuals' inertia could be the main reason for their reluctance to update the applications. Based on a survey of 186 smartphone users, this study demonstrated that both habit as an affective trigger of system 1 thinking and sunk cost as a cognitive trigger of system 2 thinking promoted the two types of inertia (i.e., affective and cognitive based inertia) in individuals, which have a negative effect on their willingness to update their applications. By grounding the research model in a theoretical view, such as dual information processing and status quo bias, this study provides a unique theoretical lens from which to view individuals' behaviors, thereby gaining a better understanding of their decision not to update to the current version of applications. This study also investigates the moderating effect of the types of applications on the relationships between affective/cognitive-based inertia and willingness to update. Results show that both habit and sunk cost decrease the willingness to update because they increase both affective and cognitive-based inertia. This study also found that the effects of affective/cognitive based inertia differed depending on the type of applications.

• Atmosphere
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• v.30 no.4
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• pp.335-346
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• 2020

Three free parameters included in a cumulus parameterization are optimized by using micro-genetic algorithm for three precipitation cases occurred in the Korea Peninsula during the summer season in order to reduce biases in a regional model associated with the uncertainties of the parameters and thus to improve the predictability of precipitation. The first parameter is the one that determines the threshold in convective trigger condition. The second parameter is the one that determines boundary layer forcing in convective closure. Finally, the third parameter is the one used in calculating conversion parameter determining the fraction of condensate converted to convective precipitation. Optimized parameters reduce the occurrence of convections by suppressing the trigger of convection. The reduced convection occurrence decreases light precipitation but increases heavy precipitation. The sensitivity experiments are conducted to examine the effects of the optimized parameters on the predictability of precipitation. The predictability of precipitation is the best when the three optimized parameters are applied to the parameterization at the same time. The first parameter most dominantly affects the predictability of precipitation. Short-range forecasts for July 2018 are also conducted to statistically assess the precipitation predictability. It is found that the predictability of precipitation is consistently improved with the optimized parameters.

• The Journal of the Korea institute of electronic communication sciences
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• v.18 no.3
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• pp.433-440
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• 2023

When the reflector is hit by a vehicle or returned by a storm, an event is generated by the impact sensor and a trigger is operated. The trigger processing algorithm of this paper compares the X, Y, and Z values of the gyro sensor with the registered values and proposes to drive them to the original values by the operation of the 3-axis driving motor. And by recognizing the vehicle license plate, if the vehicle is stolen or a social problem, information is provided to the police operation network. When the reflector is stolen or moved, it has a registered GPS value, so it operates the theft monitoring function to process it.

• 한국전산유체공학회:학술대회논문집
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• 2004.03a
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• pp.172-177
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• 2004

In the present work, we have interests on the modification of parallel implemented with MPI(Message Passing Interface) programming method, 3-Dimensional, unsteady, incompressible Navier-Stokes equation solver to analyze the low-Reynolds number flow In order to accurate calculation aerodynamic coefficients in low-Reynolds number flow field, we modified the two-equation turbulence model. This paper describes the development and validation of a new two-equation model for the prediction of flow transition. It is based on Mentor's low Reynolds $\kappa-\omega$ model with modifications to include Total Stresses Limitation (TSL) and Separation Transition Trigger (STT)

• 한국컴퓨터산업교육학회:학술대회논문집
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• 2003.11a
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• pp.33-38
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• 2003

Reports have a significant meaning in time-constrained large transaction environments, such as airplane control systems or wargame simulations. This is due to the necessity of generating reports within a limited scope of time without restraining the operation performance of large transaction environments. In order to generate reports in large transaction environments while satisfying time - constrained requirements, this paper propose a model which combines the incremental operation mechanism and materialized view mechanism using triggers and stored procedures. Further, the implementation and evaluation of the preposed model provides analysis for model characteristics.

• ETRI Journal
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• v.45 no.4
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• pp.594-602
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• 2023

Internet of things (IoT) is commonly employed to detect different kinds of diseases in the health sector. Systemic lupus erythematosus (SLE) is an autoimmune illness that occurs when the body's immune system attacks its own connective tissues and organs. Because of the complicated interconnections between illness trigger exposure levels across time, humans have trouble predicting SLE symptom severity levels. An effective automated machine learning model that intakes IoT data was created to forecast SLE symptoms to solve this issue. IoT has several advantages in the healthcare industry, including interoperability, information exchange, machine-to-machine networking, and data transmission. An SLE symptom-predicting machine learning model was designed by integrating the hybrid marine predator algorithm and atom search optimization with an artificial neural network. The network is trained by the Gene Expression Omnibus dataset as input, and the patients' data are used as input to predict symptoms. The experimental results demonstrate that the proposed model's accuracy is higher than state-of-the-art prediction models at approximately 99.70%.

• Environmental and Resource Economics Review
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• v.27 no.4
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• pp.639-666
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• 2018

This paper analyses the investment options of groundwater development project under water price uncertainty. The optimal investment threshold price which trigger the investment are calibrated base on monopolistic real options model. Stochastic dynamic model is set to reflect the uncertainty of water price which follows the GBM (Geometric Brownian Motion) process. Our finding from non-cooperative investment decision model is that uncertainty of water price could deter the groundwater investment by considering the existence of option values. For policy markers, it is easy to manage 'charges for utilization of groundwater' rather than 'performance guarantee ratio' when managing groundwater investment with pricing policy. And it is necessary to make comprehensive and well-designed policies considering the characteristics of regional groundwater reservoir and groundwater developers.