• International Journal of Contents
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• v.14 no.4
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• pp.57-64
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• 2018

Among many UNESCO world heritage sites in Korea, "Historic Village: Hahoe" is adjacent to Nakdong River and it is imperative to monitor the water level near the village in a bid to forecast floods and prevent disasters resulting from floods.. In this paper, we propose a recurrent neural network with multiple hidden layers to predict the water level near the village. For training purposes on the proposed model, we adopt the sixth-order error function to improve learning for rare events as well as to prevent overspecialization to abundant events. Multiple hidden layers with recurrent and crosstalk links are helpful in acquiring the time dynamics of the relationship between rainfalls and water levels. In addition, we chose hidden nodes with linear rectifier activation functions for training on multiple hidden layers. Through simulations, we verified that the proposed model precisely predicts the water level with high peaks during the rainy season and attains better performance than the conventional multi-layer perceptron.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.32 no.4B
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• pp.208-216
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• 2007

Wireless Sensor Networks (WSNs) are characterized by low capacity on each nodes and links. Wireless links have high bit error rate (BER) parameter that changes frequently due to the changes on network topology, interference, etc. To guarantee reliability in an error-prone environment, a retransmission mechanism can be used. In this mechanism, the number of retransmissions is used as a parameter that controls reliability requirement level. In this paper, we propose an Error Adaptive Transport Protocol (EATP) for WSNs that updates the number of retransmissions regularly to guarantee reliability during bit error rate changes as well as to utilize energy effectively. The said algorithm uses local information, thus, it does not create overhead problem.

• Journal of information and communication convergence engineering
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• v.9 no.3
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• pp.319-324
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• 2011

In computing the optical flow. Horn and Schunck's method which is a representative algorithm is based on differentiation. But it is difficult to estimate the velocity for a large displacement by this algorithm. To cope with this problem multigrid method has been proposed. In this paper, we have proposed a scaled multigrid algorithm which the initial flow for a level is calculated by the summation of the optimally scaled flow and error flow. The optimally scaled flow is the scaled expanded flow of the previous level, which can generate an estimated second image having the least RMS error with respect to the original second image, and the error flow is the flow between the estimated second image (generated by the optimally scaled flow) and the original second image. The flow for this level is then estimated using the original first and second images and the initial flow for that level. From among the various coarsest starting levels of the multigrid algorithm, we select the one that finally gives the best estimated flow. Better results were achieved using our proposed method compared with Horn and Schunck's method and a conventional multigrid algorithm.

• Geomechanics and Engineering
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• v.35 no.5
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• pp.499-509
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• 2023

The objective of this study is to perform outlier analysis to obtain the distribution of groundwater levels through the best model. The groundwater levels are measured in 10, 25 and 30 piezometers in Seoul, Daejeon and Suncheon in South Korea. Fifty-eight empirical distribution functions were applied to determine a suitable fit for the measured groundwater levels. The best fitted models based on the measured values are determined as the Generalized Pareto distribution, the Johnson SB distribution and the Normal distribution for Seoul, Daejeon and Suncheon, respectively; the reliability is estimated through the Anderson-Darling method. In this study, to choose the appropriate confidence interval, the relationship between the amount of outlier data and the confidence level is demonstrated, and then the 95% is selected at a reasonable confidence level. The best model shows a smaller error ratio than the GEV while the Mahalanobis distance and outlier labelling methods results are compared and validated. The outlier labelling and Mahalanobis distance based on median shown higher validated error ratios compared to their mean equivalent suggesting, the methods sensitivity to data structure.

• International Journal of Reliability and Applications
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• v.17 no.1
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• pp.51-63
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• 2016

Stress function of ball bearing is function of multiple stochastic factors and this system is so complex that analytical expression for reliability is difficult to obtain. To address this pressing problem, in this article, we have made an attempt to approximate system reliability of this important item based on reliability bounds under the stress strength setup. This article also provides level of error of this item. Numerical analysis has been adopted to show the closeness between the upper and lower bounds of this item.

• Journal of the Korean Statistical Society
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• v.36 no.3
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• pp.397-410
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• 2007

For the two groups data from multivariate binomial distribution, we consider a bootstrap approach to inferring the simultaneous confidence level and its standard error of a collection of the dependent confidence intervals for the difference of proportions with an experimentwise error rate at the a level are presented. The bootstrap method is used to estimate the simultaneous confidence probability for the difference of proportions.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.25 no.6A
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• pp.782-793
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• 2000

This paper presents a simple dynamical prediction scheme of the signal level which is attenuated and varied due to rain fading in satellite communication links using above 10GHz frequency bands. The proposed prediction scheme has four functional blocks for discrete-time low-pass filtering, slope-based prediction, mean-error correction and hybrid fixed/variable prediction margin allocation. Through simulations using Ka-band attenuation data obtained from the data measured over Ku-band by frequency-scaling, it is shown that the slope-based prediction with the mean-error correction has as small standard deviation of prediction error as below 1 dB, and that the error is about 1.5 to 2.5 times as small as that without the mean-error correction. The hybrid prediction margin allocation requires smaller average margin than those of both fixed and variable methods.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.13 no.4
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• pp.285-301
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• 1988

The symbol error rate equations of multi-level quadrature PRS(QPRS) system have been derived in the individual and composite environment of Gaussian/impulsive noise, cochannel CW interference, carrier offset, phase jitter and fading. And using the derived error rate equations, the probability of error has been evaluated and shown in graphs as functions of carrier to noise power ratio, carrier to interference power ratio, phase error, impulsive index, the ration of Gaussian noise to impulsive noise power component, signal to noise power ration in phase locked loop(PLL), and fading figures. The rseults show that the error rate performances are generally more more degraded by impulsive noise than by Gaussian noise. But on the contrary the erors occurred more frequently by Gaussian noise than impulsive noise in a fading environment.

• Journal of KIISE:Computer Systems and Theory
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• v.27 no.3
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• pp.245-254
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• 2000

This paper proposes a new discrete curvature error metric to generate LOD meshes. For mesh simplification, discrete curvatures are defined with geometric attributes, such as angles and areas of triangular polygonal model, and dihedral angles without any smooth approximation. They can represent characteristics of polygonal surface well. The new error metric based on them, discrete curvature error metric, increases the accuracy of simplified model by preserving the geometric information of original model and can be used as a global error metric. Also we suggest that LOD should be generated not by a simplification ratio but by an error metric. Because LOD means the degree of closeness between original and each level's simplified model. Therefore discrete curvature error metric needs relatively more computations than known other error metrics, but it can efficiently generate and control LOD meshes which preserve overall appearance of original shape and are recognizable explicitly with each level.

• The KIPS Transactions:PartC
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• v.9C no.3
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• pp.375-384
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• 2002

In the current Internet, the QoS of interactive applications is hardly guaranteed because of variable bandwidth, packet loss and delay. Moreover, VoIP which is becoming an important part of the information infra-structure in these days, is susceptible to network packet loss and end-to-end delay. Therefore, it needs error control mechanisms in network level or application level. The FEC-based error control mechanisms are used for interactive audio application such as VoIP. The FEC sends a main information along with redundant information to recover the lost packets and adjusts redundant information depending on network conditions to reduce the bandwidth overhead. However, because most of the error control mechanisms do not consider end-to-end delay but packet loss rate, their performances are poor. In this paper, we propose a new error control algorithm, SCCRP, considering packet loss rate as well as end-to-end delay. Through experiments, we confirm that the SCCRP has a lower packet loss rate and a lower end-to-end delay after reconstruction.