• Journal of KIISE:Computer Systems and Theory
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• v.33 no.7
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• pp.448-453
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• 2006

We extend a parallel depth-first search (DFS) algorithm for planar graphs to deal with (non-planar) solid grid graphs, a subclass of non-planar grid graphs. The proposed algorithm takes time O(log n) with $O(n/sqrt{log\;n})$ processors in Priority PRAM model. In our knowledge, this is the first deterministic NC algorithm for a non-planar graph class.

• Proceedings of the KIEE Conference
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• 2000.07d
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• pp.2525-2527
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• 2000

The analysis of distribution line faults is essential to the proper protection of power system. A high impedance fault(HIF) dose not make enough current to cause conventional protective device operating, so it is well known that undesirable operating conditions and certain types of faults on electric distribution feeders cannot be detected by using conventional protection system. In this paper, we prove that the nature of the high impedance faults is indeed a deterministic chaos, not a random motion. Algorithms for estimating Lyapunov spectrum and the largest Lyapunov exponent are applied to various fault currents detections in order to evaluate the orbital instability peculiar to deterministic chaos dynamically, and fractal dimensions of fault currents which represent geometrical self-similarity are calculated. Wavelet transform analysis is applied the time-scale information to fault signal. Time-scale representation of high impedance faults can detect easily and localize correctly the fault waveform.

• JSTS:Journal of Semiconductor Technology and Science
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• v.15 no.3
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• pp.397-403
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• 2015

This paper presents a new SOC test compression scheme in Embedded Deterministic Test (EDT) compression environment. Compressed test data is brought over the TAM from the tester to the cores in SOC and decompressed in the cores. The proposed scheme allows cores tested at the same time to share some test channels. By sharing free variables in these channels across test cubes of different cores decompressed at the same time, high encoding efficiency is achieved. Moreover, no excess control data is required in this scheme. The ability to reuse excess free variables eliminates the need for high precision in matching the number of test channels with the number of care bits for every core. Experimental results obtained for some SOC designs illustrate effectiveness of the proposed test application scheme.

• Investigative Magnetic Resonance Imaging
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• v.6 no.2
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• pp.137-146
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• 2002

Purpose : This paper introduces an improved classification approach which adopts a deterministic relaxation method and an agglomerative clustering technique for the classification of MRI using neural network. The proposed approach can solve the problems of convergency to local optima and computational burden caused by a large number of input patterns when a neural network is used for image classification. Materials and methods : Application of Hopfield neural network has been solving various optimization problems. However, major problem of mapping an image classification problem into a neural network is that network is opt to converge to local optima and its convergency toward the global solution with a standard stochastic relaxation spends much time. Therefore, to avoid local solutions and to achieve fast convergency toward a global optimization, we adopt MFA to a Hopfield network during the classification. MFA replaces the stochastic nature of simulated annealing method with a set of deterministic update rules that act on the average value of the variable. By minimizing averages, it is possible to converge to an equilibrium state considerably faster than standard simulated annealing method. Moreover, the proposed agglomerative clustering algorithm which determines the underlying clusters of the image provides initial input values of Hopfield neural network. Results : The proposed approach which uses agglomerative clustering and deterministic relaxation approach resolves the problem of local optimization and achieves fast convergency toward a global optimization when a neural network is used for MRI classification. Conclusion : In this paper, we introduce a new paradigm to classify MRI using clustering analysis and deterministic relaxation for neural network to improve the classification results.

• The Journal of Korea Robotics Society
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• v.7 no.4
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• pp.292-298
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• 2012

It is a real-time system that the system correctness depends not only on the correctness of the logical result of the computation but also on the result delivery time. Real-time Operating System (RTOS) is a software that manages the time of a microprocessor to ensure that the most important code runs first so that it is a good building block to design the real-time system. The real-time performance is achieved by using real-time mechanisms through data communication and synchronization of inter-task communication (ITC) between tasks. Therefore, test on the response time of real-time mechanisms is a good measure to predict the performance of real-time systems. This paper aims to analysis the response characteristics of real-time mechanisms in kernel space for real-time embedded Linux: RTAI and Xenomai. The performance evaluations of real-time mechanism depending on the changes of task periods are conducted. Test metrics are jitter of periodic tasks and response time of real-time mechanisms including semaphore, real-time FIFO, Mailbox and Message queue. The periodicity of tasks is relatively consistent for Xenomai but RTAI reveals smaller jitter as an average result. As for real-time mechanisms, semaphore and message transfer mechanism of Xenomai has a superior response to estimate deterministic real-time task execution. But real-time FIFO in RTAI shows faster response. The results are promising to estimate deterministic real-time task execution in implementing real-time systems using real-time embedded Linux.

• Journal of Electrical Engineering and Technology
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• v.12 no.5
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• pp.1709-1718
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• 2017

This paper presents a hybrid stochastic deterministic multi-timescale scheduling (SDMS) approach for generation scheduling of a power grid. SDMS considers flexible resource options including conventional generation flexibility in a chance-constrained day-ahead scheduling optimization (DASO). The prime objective of the DASO is the minimization of the daily production cost in power systems with high penetration scenarios of variable generation. Furthermore, energy storage is scheduled in an hourly-ahead deterministic real-time scheduling optimization (RTSO). DASO simulation results are used as the base starting-point values in the hour-ahead online rolling RTSO with a 15-minute time interval. RTSO considers energy storage as another source of grid flexibility, to balance out the deviation between predicted and actual net load demand values. Numerical simulations, on the IEEE RTS test system with high wind penetration levels, indicate the effectiveness of the proposed SDMS framework for managing the grid flexibility to meet the net load demand, in both day-ahead and real-time timescales. Results also highlight the adequacy of the framework to adjust the scheduling, in real-time, to cope with large prediction errors of wind forecasting.

• Proceedings of the Korea Information Processing Society Conference
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• 2001.10a
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• pp.535-538
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• 2001

Since 1990s, many literatures have shown that connectionist models, such as back propagation, recurrent network, and RBF (Radial Basis Function) outperform the traditional models, MA (Moving Average), AR (Auto Regressive), and ARIMA (Auto Regressive Integrated Moving Average) in time series prediction. Neural based approaches to time series prediction require the enough length of historical measurements to generate the enough number of training patterns. The more training patterns, the better the generalization of MLP is. The researches about the schemes of generating artificial training patterns and adding to the original ones have been progressed and gave me the motivation of developing VTG schemes in 1996. Virtual term is an estimated measurement, X(t+0.5) between X(t) and X(t+1), while the given measurements in the series are called actual terms. VTG (Virtual Tern Generation) is the process of estimating of X(t+0.5), and VTG schemes are the techniques for the estimation of virtual terms. In this paper, the alternative VTG schemes to the VTG schemes proposed in 1996 will be proposed and applied to multivariate time series prediction. The VTG schemes proposed in 1996 are called deterministic VTG schemes, while the alternative ones are called stochastic VTG schemes in this paper.

• Journal of Preventive Medicine and Public Health
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• v.27 no.1 s.45
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• pp.135-144
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• 1994

The purpose of this study compares determinants of eldery medical cost inflation with those of other age groups by analysing aggregated data with a deterministic model. The deterministic model of per capita medical cost inflation consists of increases in price, intensity of services, and medical utilization. We used a time series data($1985{\sim}1991$) from National Medical Insurance and analyzed by age groups. In total population, the average increase rates of inpatient and outpatient medical costs were respectively 9.5% and 8.8% during 6 years and the major cause of inflation was the increase in service intensity in both of inpatient and outpatient cases. But in the population of 65 years old and over, the average increase rates of inpatient and outpatient medical costs were respectively 13.8% and 14.8% and the major cause of inflation was the increase in per-capita medical utilization in both of inpatient and outpatient cases. Also, the increase in service intensity of 65 years old and over was the highest of other age groups. This pattern was similar during study periods. We concluded that the level of medical cost-inflation and the determinants in eldery was the highest-especially in per capita medical utilization, therfore, the inflation of medical costs in eldery will be higher than other age groups for the furture in Korea.

• Journal of the Architectural Institute of Korea Structure & Construction
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• v.34 no.2
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• pp.41-48
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• 2018

Carbonation is one of the major detrimental factors to the reinforced concrete structures owing to penetration of atmospheric CO2 through the micro pores, thereby it reduces the durability of the concrete. The maintenance periods and cost for concrete according to the coefficient variation of different finishing materials is documented in literature. However, it is required to carry out the systematic and well planned studies. Therefore, keeping them in mind, surface repair was carried out to the carbonated concrete and the maintenance cost was calculated to measure the durability life after repair with different variable. The deterministic and probabilistic methods were applied for durability and repair cost of the concrete. In the existing deterministic model, the cost of repair materials increases significantly when the concrete structure reaches its service life. In present study using a stochastic model, the maintenance period and cost was evaluated. According to obtained results, there was no significant difference in the number of maintenance of the coefficient variation. The initial durability has a great influence on the maintenance time and cost of the structure. Unlike the deterministic model, the probabilistic cost estimating model reduces the number of maintenance to the target service life expectancy.

• Journal of the Korean Society of Systems Engineering
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• v.19 no.2
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• pp.46-58
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• 2023

Deterministic safety analysis is a crucial part of safety assessment, particularly when it comes to demonstrating the safety of nuclear power plant designs. The traditional approach to deterministic safety analysis models is to model the nuclear core using point kinetics. However, this simplified approach does not fully reflect the real core behavior with proper moderator and fuel reactivity feedbacks during the transient. The use of Multi-Physics approach allows more precise simulation reflecting the inherent three-dimensionality (3D) of the problem by representing the detailed 3D core, with instantaneous updates of feedback mechanisms due to changes of important reactivity parameters like fuel temperature coefficient (FTC) and moderator temperature coefficient (MTC). This paper addresses a CEA ejection accident at hot full power (HFP), in which the underlying strong and un-symmetric feedback between thermal-hydraulics and reactor kinetics exist. For this purpose, a multi-physics analysis tool has been selected with the nodal kinetics code, 3DKIN, implicitly coupled to the thermal-hydraulic code, RELAP5, for real-time communication and data exchange. This coupled approach enables high fidelity three-dimensional simulation and is therefore especially relevant to reactivity initiated accident (RIA) scenarios and power distribution anomalies with strong feedback mechanisms and/or un-symmetrical characteristics as in the CEA ejection accident. The Systems Engineering approach is employed to provide guidance in developing the work in a systematic and efficient fashion.