• Journal of the Korea Society of Computer and Information
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• v.24 no.7
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• pp.153-160
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• 2019

This study aims to analyze the mutual influences between adolescents' multicultural acceptability and school adjustment. Research problems for research are as follows. First, is multicultural acceptability and school adjustment stable over time? Second, what is the longitudinal impact of school adjustment on multicultural acceptability over time? Third, what is the longitudinal impact of multicultural acceptability on school adjustment over time? The results of analyzing the research problems by applying the autoregressive cross-lagged model are as follows. First, the autoregressive model of school adjustment has a significant effect on the future time point and is stable over time. Second, the autoregressive model of multicultural acceptability have a significant effect on the future time point and is stable over time. Third, cross-lagged effect from school adjustment to multicultural acceptability has a statistically significant effect on the multicultural acceptability at a later time, and is stable over time. Fourth, cross-lagged effect from multicultural acceptability to school adjustment was not statistically significant at the time of multicultural acceptability, and there was no change with time. This study is meaningful to provide the theoretical and practical implications by verifying the influence of the three - year term data over time.

• Journal of KIISE:Computer Systems and Theory
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• v.27 no.3
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• pp.300-312
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• 2000

The application areas of embedded real-time systems are very wide and so are the requirements for real-time processing and reliability of the systems. To develop embedded real-time systems effectively with its real-time and reliability properties guaranteed, an appropriate real-time model is needed. Recently, the research on real-time object-oriented model is active, which graft the concept of object-orientation on real-time systems modeling and development. In this paper, we propose dRTO (dependable Real-Time Object) model, with 5 primitive classes. These allow designers to effectively model the characteristics of real-time systems, i.e., object-orientation, real-time-ness and dependability. The dRTO model has three main features. First, it is able to model and implement the timing constraints imposed on real-time objects as well as interactions among the objects. Second, hardware and software components (including kernel) of embedded systems can be modeled in one frame. Third, it is able to represent fault detection and recovery mechanisms explicitly.

• Proceedings of the KOSOMBE Conference
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• v.1997 no.05
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• pp.150-155
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• 1997

Modelling and Simulation of the activation process for the myocardium is meaningful to understand special excitation conduction system in the heart and to study cardiac functions. In this paper, we propose two dimensional cellular automata model for the activation process of the myocardium and simulated by means of discrete time and discrete event algorithm. In the model, cells are classified into anatomically similar characteristic parts of heart; SA node, internodal tracks, AV node, His bundle, bundle branch and four layers of the ventricular muscle, each of which has a set of cells with preassigned properties, that is, activation time, refractory duration and conduction time between neighbor cell. Each cell in this model has state variables to represent the state of the cell and has some simple state transition rules to change values of state variables executed by state transition function. Simulation results are as follows. First, simulation of the normal and abnormal activation process for the myocardium has been done with discrete time and discrete event formalism. Next, we show that the simulation results of discrete time and discrete event cell space model is the same. Finally, we compare the simulation time of discrete event myocardium model with discrete time myocardium models and show that the discrete event myocardium model spends much less simulation time than discrete time myocardium model and conclude the discrete event simulation method Is excellent in the simulation time aspect if the interval deviation of event time is large.

• Proceedings of the KSR Conference
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• 2011.10a
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• pp.1722-1729
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• 2011

This paper presents an optimization model for revising train timetable based on an existing timetable to improve transfer time at each station. The transfer time consists of walking and waiting time. The model is formulated as a mixed integer programming. The objective function is to minimize the transfer time from one train to another train at each station. To reflect real situations, range of revising departure time is considered as major condition in the model. To validate the effectiveness of the model, rudimentary computational results are included, and the results are analyzed in terms of transfer time.

• Journal of the Korean Society of Marine Environment & Safety
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• v.20 no.3
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• pp.285-291
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• 2014

This study applied regression analysis to evaluate the impact of hourly average congestion calculated by bumper model in the congested area of each passage of each port on the peak time congestion, to suggest the model formula that can predict the peak time congestion. This study conducted regression analysis of hourly average congestion and peak time congestion based on the AIS survey study of 20 ports in Korea. As a result of analysis, it was found that the hourly average congestion has a significant impact on the peak time congestion and the prediction model formula was derived. This formula($C_p=4.457C_a+29.202$) can be used to calculate the peak time congestion based on the predicted hourly average congestion.

• Journal of Power System Engineering
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• v.11 no.3
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• pp.66-72
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• 2007

This study proposed new method to decide the reference model necessary for design PID controller. In generally, control design problems using the reference model have the following two factors. One factor is that numerical model of the controlled system can be obtained extremely, and the other is that specification for the closed-loop dynamic performance is pure moderate. Therefore, the control design procedure is essentially based on the partial reference model matching which offers a reasonable method to simplify the design and the controller configuration under the controlled system uncertainty. ITAE(Integral of time-multiplied absolute error) performance index and Kitamori method etc. which were used a reference model method had a limit to settling time and rising time of reference model that it arrived to steady state response according to the controlled system. On this study, if it only knew peak time of overshoot and settling time by measurement signal of the controlled system, it can be made the reference model easily. We proposed new method to improve performance index of the reference model superior to existing reference model index and illustrate the numerical simulation results to show the effectiveness of proposed control method design.

• Journal of Korean Institute of Industrial Engineers
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• v.27 no.1
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• pp.18-24
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• 2001

This paper presents a model and a heuristic algorithm for the Traveling Salesman Problem with Time Windows(TSPTW). The main difference of our model compared with the previous ones lies in that the time windows we are concerned are more flexible and realistic than the previous ones. In the typical TSPTW, the service at a node must begin within the time grid called the time window that is defined by the earliest and the latest time to start the service at each node. But, in real business practice, a lateness cost is usually penalized rather than the service is prohibited at all when a vehicle arrives after the latest time. Considering this situation, we develop a model with a new time window that allows an arrival after the latest time and penalizes the late arrival by charging a lateness cost. A two-phased heuristic algorithm is proposed for the model and is extensively tested to verify the accuracy and efficiency of the algorithm.

• Communications for Statistical Applications and Methods
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• v.18 no.1
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• pp.79-87
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• 2011

A spatial time series model was used for analyzing the method of spatial time series (not the ARIMA model that is popular for analyzing spatial time series) by using chicken pox data which is a highly contagious disease and grid data due to ARIMA not reflecting the spatial processes. Time series model contains a weighting matrix, because that spatial time series model influences the time variation as well as the spatial location. The weighting matrix reflects that the more geographically contiguous region has the higher spatial dependence. It is hypothesized that the weighting matrix gives neighboring areas the same influence in the study of the spatial time series model. Therefore, we try to present the conclusion with a weighting matrix in a way that gives the same weight to existing neighboring areas in the study of the suitability of the STARMA model, spatial time series model and STBL model, in the comparative study of the predictive power for statistical inference, and the results. Furthermore, through the Kalman-Filter method we try to show the superiority of the Kalman-Filter method through a parameter assumption and the processes of prediction.

• Journal of Information Processing Systems
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• v.15 no.6
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• pp.1335-1349
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• 2019

Crowdsensing technologies can improve the efficiency of smart parking system in comparison with present sensor based smart parking system because of low install price and no restriction caused by sensor installation. A lot of sensing data is necessary to predict parking lot saturation in real-time. However in real world, it is hard to reach the required number of sensing data. In this paper, we model a saturation predication combining a time-based prediction model and a sensing data-based prediction model. The time-based model predicts saturation in aspects of parking lot location and time. The sensing data-based model predicts the degree of saturation of the parking lot with high accuracy based on the degree of saturation predicted from the first model, the saturation information in the sensing data, and the number of parking spaces in the sensing data. We perform prediction model learning with real sensing data gathered from a specific parking lot. We also evaluate the performance of the predictive model and show its efficiency and feasibility.

• Journal of the Korea Society for Simulation
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• v.13 no.2
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• pp.13-21
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• 2004

The thermal-hydraulic model ARTS which was based on the RETRAN-3D code adopted in the domestic full-scope power plant simulator which was provided in 1998 by KEPRI. Since ARTS is a generalized code to model the components with control volumes, the smaller time-step size should be used even if converged solution could not get in a single volume. Therefore, dedicated models which do not force to reduce the time-step size are sometimes more suitable in terms of a real-time calculation and robustness. In the case of PRT(Pressurizer Relief Tank) model, it is consist of subcooled water in bottom and non-condensable gas in top. The sparger merged under subcooled water enhances condensation. The complicated thermal-hydraulic phenomena such as condensation, phase separation with existence of non-condensable gas makes difficult to simulate. Therefore, the PRT volume can limit the time-step size if we model it with a general control volume. To prevent the time-step size reduction due to convergence failure for simulating this component, we developed a dedicated model for PRT. The dedicated model was expected to provide substantially more accurate predictions in the analysis of the system transients. The results were resonable in terms of accuracy, real-time simulation, robustness and education of operators, complying with the ANSI/ANS-3.5-1998 simulator software performance criteria and RETRAN-3D results.