• Water Engineering Research
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• v.2 no.1
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• pp.63-72
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• 2001

The variation of sampling errors was characterized using the Waymire-Gupta-Rodriguez-Iturbe multi-dimensional rainfall model(WGR model). The parameters used for this study are those derived by Jung et al. (2000) for the Han River Basin using a genetic algorithm technique. The sampling error problems considered are those for using raingauge network, satellite observation and also for both combined. The characterization of sampling errors was done for each month and also for the downstream plain area and the upstream mountain area, separately. As results of the study we conclude: (1) The pattern of sampling errors estimated are obviously different from the seasonal pattern of monthly rainfall amounts. This result may be understood from the fact that the sampling error is estimated not simply by considering the rainfall amounts, but by considering all the mechanisms controlling the rainfall propagation along with its generation and decay. As the major mechanism of moisture source to the Korean Peninsula is obviously different each month, it seems rather normal to provide different pattern of sampling errors from that of monthly rainfall amounts. (2) The sampling errors estimated for the upstream mountain area is about twice higher than those for the down stream plain area. It is believed to be because of the higher variability of rainfall in the upstream mountain arean than in the down stream plain area.

• Journal of the Korean Society of Fisheries and Ocean Technology
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• v.55 no.3
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• pp.206-216
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• 2019

This study is aimed to compare stock assessment models depending on how the models fit to observed data. Process-error model, Observation-error model, and Bayesian state-space model for the Korean Western coast fisheries were applied for comparison. Analytical results show that there is the least error between the estimated CPUE and the observed CPUE with the Bayesian state-space model; consequently, results of the Bayesian state-space model are the most reliable. According to the Bayesian State-space model, potential yield of fishery resources in the West Sea of Korea is estimated to be 231,949 tons per year. However, the results show that the fishery resources of West Sea have been decreasing since 1967. In addition, the amounts of stock in 2013 are assessed to be only 36% of the stock biomass at MSY level. Therefore, policy efforts are needed to recover the fishery resources of West Sea of Korea.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.21 no.4
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• pp.846-854
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• 2017

In this paper, we proposed a method to reduce the error of compass by combining the ceiling technique used in the past with modern IT technology. We combined an encoder and the Azimuth Circle for applying an algorithm. The algorithm is able to calculate the true north by using astronomical observation. Finally, we implemented the embedded system possible to indicate various situations and perform calculations. As a result, it isn't only able to calculate the true north with an error of about $0.2^{\circ}$ but also takes less than 5 seconds. Originally, using astronomical observation requires more than 5minutes. So it is analyzed as convenient by solving the problem of taking lots of time. Especially, we present the tolerance less than $0.5^{\circ}$ by the analysis of the existing gyrocompass and the bearing standard of IMO. In conclusion, we clearly confirm that the results of this paper are possible to reduce the error of various compasses in a real world.

• Speech Sciences
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• v.14 no.1
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• pp.163-174
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• 2007

All observation has uncertainty due to noise or channel characteristics. This uncertainty should be counted in the modeling of observation. In this paper we propose a modified optimization object function of a GMM training considering inexact observation. The object function is modified by introducing the concept of observation confidence as a weighting factor of probabilities. The optimization of the proposed criterion is solved using a common EM algorithm. To verify the proposed method we apply it to the speaker recognition domain. The experimental results of text-independent speaker identification with VidTimit DB show that the error rate is reduced from 14.8% to 11.7% by the modified GMM training.

• Proceedings of the Korean Society of Surveying, Geodesy, Photogrammetry, and Cartography Conference
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• 2010.04a
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• pp.187-190
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• 2010

GPS survey came into wide use, but there are inefficient parts in related laws and regulations. Especially, to get GPS surveying results under 1.5cm permissible error the observation time must be longer than 8 hours in triangulation points surveying regulations. However, GPS surveying technology is developing now, so results could be acceptable under 4 hours observation time. Therefore, this study made a stable standard of observation time in GPS survey by comparing the errors due to observation time, and used PAJU, DOND and YANP's GPS data and 6 cadastral points' survey data. Also, to analyze the variations of results due to baseline distance, applied each GPS site as a fixed point and compared the positions. As a result, the stable satisfactory results were calculated under 4 hour survey, when the baseline distances were under 30km.

• Atmosphere
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• v.30 no.2
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• pp.103-113
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• 2020

In this study, we analyzed and developed the monitoring system in order to confirm the effect of observations on forecast sensitivity on ensemble-based data assimilation. For this purpose, we developed the Ensemble Forecast Sensitivity to observation (EFSO) monitoring system based on Local Ensemble Transform Kalman Filter (LETKF) system coupled with Korean Integrated Model (KIM). We calculated 24 h error variance of each of observations and then classified as beneficial or detrimental effects. In details, the relative rankings were according to their magnitude and analyzed the forecast sensitivity by region for north, south hemisphere and tropics. We performed cycle experiment in order to confirm the EFSO result whether reliable or not. According to the evaluation of the EFSO monitoring, GPSRO was classified as detrimental observation during the specified period and reanalyzed by data-denial experiment. Data-denial experiment means that we detect detrimental observation using the EFSO and then repeat the analysis and forecast without using the detrimental observations. The accuracy of forecast in the denial of detrimental GPSRO observation is better than that in the default experiment using all of the GPSRO observation. It means that forecast skill score can be improved by not assimilating observation classified as detrimental one by the EFSO monitoring system.

• Communications for Statistical Applications and Methods
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• v.16 no.4
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• pp.675-686
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• 2009

In this paper, it will be assumed that there are two distinct populations which are multivariate normal with equal covariance matrix. We also assume that the two populations are equally likely and the costs of misclassification are equal. The classification rule depends on the situation when the training samples include missing values or not. We consider the bootstrap confidence intervals for classification error rate when a block of observation is missing.

• Journal of information and communication convergence engineering
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• v.19 no.1
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• pp.22-28
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• 2021

Convolutional neural networks (CNNs) are one of the most frequently used artificial intelligence techniques. Among CNN-based applications, small and timing-sensitive applications have emerged, which must be reliable to prevent severe accidents. However, as the small and timing-sensitive systems do not have sufficient system resources, they do not possess proper error protection schemes. In this paper, we propose MATE, which is a low-cost CNN weight error correction technique. Based on the observation that all mantissa bits are not closely related to the accuracy, MATE replaces some mantissa bits in the weight with error correction codes. Therefore, MATE can provide high data protection without requiring additional memory space or modifying the memory architecture. The experimental results demonstrate that MATE retains nearly the same accuracy as the ideal error-free case on erroneous DRAM and has approximately 60% accuracy, even with extremely high bit error rates.

• Journal of Korea Water Resources Association
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• v.40 no.11
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• pp.841-849
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• 2007

This study evaluated the effect of combined rainfall observation of using rain gauge and rain radar. The effect of combined observations is to be evaluated by considering the decrease of measurement error due to combined use of design orthogonal observation methods. As an example, this study evaluated the rain gauge network of the Keum river basin, and showed how the density of rain gauges could be decreased by combining the radar observation. This study applied the researches on sampling error by North and Nakamoto(1989), Yoo et al. (1996) and Yoo (1997), also the simple NFD model for representing the rainfall field. The model parameters were decided using the rainfall characteristics (correlation time and length) estimated using the data collected in the Keum River Basin by 28 rain gauges and the operation rule of radar was assumed arbitrarily. This study considered the rain gauge density criteria provided by WMO(1994) and the rain gauge density installed in the Keum river basin to decrease the rain gauge density under the condition of introducing the radar.

• Journal of the Institute of Electronics and Information Engineers
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• v.53 no.3
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• pp.99-106
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• 2016

In this paper, we will discuss about correction method of missing data on noisy observation matrix and uncertainty analysis for the potential noise. In situations without missing data in an observation matrix, this solution is known to be accurately induced by SVD (Singular Value Decomposition). However, usually the several entries of observation matrix have not been observed and other entries have been perturbed by the influence of noise. In this case, it is difficult to find the solution as well as cause the 3D reconstruction error. Therefore, in order to minimize the 3D reconstruction error, above all things, it is necessary to correct reliably the missing data under noise distribution and to give a quantitative evaluation for the corrected results. This paper focuses on a method for correcting missing data using geometrical properties between 2D projected object and 3D reconstructed shape and for estimating a noise level of the observation matrix using ranks of SVD in order to quantitatively evaluate the performance of the correction algorithm.