• Journal of Korea Multimedia Society
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• v.19 no.10
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• pp.1808-1815
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• 2016

TPSN(Timing-sync Protocol for Sensor Networks), the representative of time synchronization protocol, has been already developed to provide time synchronization among nodes in wireless sensor networks. Even though the TPSN's method has been referenced by so many other time synchronization schemes for resource-constrained networks like wireless sensor networks or low power personal area networks, it has some inefficiency in terms of power consumption and network-wide synchronization time (or called convergence time). The main reason is that each node in TPSN needs waiting delay to solve the collision problem due to simultaneous transmission among competing nodes, which causes more power consumption and longer network convergence time for a network-wide synchronization. In this paper an improved scheme is proposed by changing message exchange method among nodes. The proposed scheme not only shortens network-wide synchronization time, but also reduce collision traffic which lead to needless power consumption. The proposed scheme's performance has been evaluated and compared with an original scheme by simulation. The results are shown to be better than the original algorithm used in TPSN.

• Journal of the Korea Convergence Society
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• v.6 no.4
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• pp.161-167
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• 2015

It is very difficult to predict time-series data. This is because data obtained from the signal having a non-linear characteristic has an uncertainty. In this paper, By differentiating time-series data is the average of the past data under the premise that change depending on what pattern, and find the soft look of time-series change pattern. This paper also apply the probability variables to generalize time-series data having a specific data according to the reflection ratio of the differentiation. The predicted value is estimated by removing cyclic movement and seasonal fluctuation, and reflect the trend by extracting the irregular fluctuation. Predicted value has demonstrated the superiority of the proposed algorithm and compared with the best results by a simple moving average and the moving average.

• Convergence Security Journal
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• v.8 no.2
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• pp.35-40
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• 2008

Software failure time presented in the literature exhibit either constant, monotonic increasing or monotonic decreasing. For data analysis of software reliability model, data scale tools of trend analysis are developed. The methods of trend analysis are arithmetic mean test and Laplace trend test. Trend analysis only offer information of outline content. In this paper, we discuss forecasting failure time case of failure time censoring. The used software failure time data for forecasting failure time is random number of Weibull distribution(shaper parameter 1, scale parameter 0.5), Using this data, we are proposed to ARIMA(AR(1)) and simulation method for forecasting failure time. The practical ARIMA method is presented.

• Convergence Security Journal
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• v.12 no.3
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• pp.115-121
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• 2012

Software failure time presented in the literature exhibit either constant, monotonic increasing or monotonic decreasing. For data analysis of software reliability model, data scale tools of trend analysis are developed. The methods of trend analysis are arithmetic mean test and Laplace trend test. Trend analysis only offers information of outline content. In this paper, we discuss forecasting failure time case of failure time censoring. In this study, we predict the future failure time by using the curve regression analysis where the s-curve, growth, and Logistic model is used. The proposed prediction method analysis used failure time for the prediction of this model. Model selection using the coefficient of determination and the mean square error were presented for effective comparison.

• The Korean Journal of Food & Health Convergence
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• v.8 no.6
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• pp.11-17
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• 2022

Emergency transport is directly related to the life of the patient, and rapid transport to the hospital is crucial. However, external environmental factors such as traffic or weather, interfere with hospital transport. In this study, we investigated the external environment affecting hospital transport time. We examined the transfer time and patient treatment time of emergency patients in an area of northern Gyeonggi-do from 2018 to 2020. Diagnosis after arrival at the hospital was used, and on-site treatment time was measured from paramedic arrival time at the scene to departure. Furthermore, we examined whether there was a correlation between the time paramedics left the scene and hospital arrival time through the reason for the delay as recorded in the emergency log. Traffic jams had the greatest impact on patient transport, while transport delays occurred due to heavy rain, but not snow. Among injured patients, electrical accidents were the most problematic in terms of on-site treatment time. This was because a lot of first aid is needed in electrical accidents. It must be necessary to mobilize two ambulances in an emergency through the expansion of infrastructure, prepare a plan for rapid transport in heavy rain, and implement strong laws against transport obstruction.

• ETRI Journal
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• v.37 no.2
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• pp.317-327
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• 2015

A reliable analysis of consumer preference from a large amount of purchase data acquired in real time and an accurate customer characterization technique are essential for successful direct marketing campaigns. In this study, an optimal segmentation of post office customers in Korea is performed using a subspace projection-based clustering method to generate an accurate customer characterization from a high-dimensional census dataset. Moreover, a traditional temporal mining method is extended to an algorithm using the MapReduce framework for a consumer preference analysis. The experimental results show that it is possible to use parallel mining through a MapReduce-based algorithm and that the execution time of the algorithm is faster than that of a traditional method.

• Proceedings of the KIEE Conference
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• 1991.11a
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• pp.357-360
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• 1991

In this paper, we have introduced a network and showed how this can be realised as an adaptive equalizer. The walsh equlizer is built from a set of Walsh-Block pulse functions and LMS algorithms with the optimal convergence factor(C.F.). The convergence and the adaptation speed of this algorithms depends on the proper choice of a design factor $\mu$ called the C.F.. Conventional adaptation techniques use the fixed time constant C.F. by the method of trial and error. In this paper, we propose to adaptive C.F. which are optimally tailored to adapt C.F. in real time so that their values are kept optimum for a new set of input variables.

• The Transactions of the Korean Institute of Electrical Engineers
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• v.41 no.9
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• pp.1021-1030
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• 1992

When using a least squares estimator with exponential forgetting factor to identify continuous-time deterministic system, the problem of determining minimum eigenvalue is described in this paper. It is well known fact that the convergence rate of parameter estimates relies on various factors consisting of the estimator and especially, theirproperties can be directly affected by all eigenvalues in the parameter error differential equation. Fortunately, there exists only one adjusting eigenvalue in the given estimator and then, the parameter convergence rates depend on this minimum eigenvalue. In this note, a new result to determine the minimum eigenvalue is proposed. Under the assumption that the input has as many spectral lines as the number of parameter estimates, it can be proven that the minimum eigenvalue converges to a constant value, which is a function of the forgetting factor and the parameter estimates number.

• Journal of the Korean Society for Precision Engineering
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• v.21 no.2
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• pp.116-121
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• 2004

In rigid-plastic finite element method, there is a heavy computation time and convergence problem. In this study, static-explicit rigid-plastic finite element method will be introduced. This method is the way that restrict the convergence interval. It is expected that various results from the numerical analysis will give very useful information for the design of tools in sheet metal forming process.

• Journal of the Korean Institute of Telematics and Electronics S
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• v.35S no.3
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• pp.93-101
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• 1998

In Integrated Tube Components(ITC) process in themanufacturing of color display tube, we describe the necessity of the convergence measurement method using photo sensors. Compared with methods using 1D or 2D cameras, its characteristics is to use of moving image patterns and fixed sensors. This measurement method is formulated as the measurement problem of the phase difference in phase changing periodic signals. The convergence measurement system using photo sensors, for the good performance, must have a small standard deviation for the repetitive measurement in the same condition and a fast measurement time for thecovergence change. By above two conditions, we proposed the real time measurement algorithm of the pahse difference using fundametal and harmonic in phase changing periodic signals. And, the proposed algorithm is applied to the convergence measurement system.