• Journal of Advanced Marine Engineering and Technology
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• v.33 no.5
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• pp.738-745
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• 2009

Underwater acoustic communication has multipath error because of reflection by sea-level and sea-bottom. The multipath of underwater channel causes receive signal to make error floor. In this paper, we propose the underwater communication system using various channel coding schemes such as RS coding, convolutional code, turbo code and concatenated code for overcoming the multipath effect in underwater channel. As shown in simulation results, characteristic of multipath error is similar to that of random error. So interleaver has not effect on error correcting. For correcting of error floor by multipath, it is necessary to use strong channel codes like turbo code. Turbo code is one of the iterative codes. And the performance of concatenated codes including RS code has better performance than using singular channel codes.

• Journal of Wetlands Research
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• v.13 no.1
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• pp.13-23
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• 2011

In this study, Mike11 will be used as the numerical model where a data assimilation method will be applied to it. This paper aims to gain an insight and understanding of data assimilation in flood forecasting models. It will start with a general discussion of data assimilation, followed by a description of the methodology and discussion of the statistical error forecast model used, which in this case is the linear regression. This error forecast model is applied to the water level forecast simulated by MIKE11 to produced improved forecast and validated against real measurements. It is found that there exists a phase error in the improved forecasts. Hence, 2 general formula are used to account for this phase error and they have shown improvement to the accuracy of the forecasts, where one improved the immediate forecast of up to 5 hours while the other improved the estimation of the peak discharge.

• Journal of the Korea Safety Management & Science
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• v.13 no.4
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• pp.53-60
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• 2011

Job stress weakens physical ability causing the diseases related to working condition, decreases a production level, and increases mistakes and accidents. This study examined the relationship between job stress and human error, and focused on the moderating effect of age and maintenance type on the relationship between job stress and human error. The study used a quantitative design based on the 450 questionnaires of maintenance personnel in the Air force. The results of multiple regression analysis showed that physiological and psychological stress responses have positively related with human error. In moderating effect test, age appeared to impact on the relationship between physiological/behavioral stress and human error.

• The Journal of the Acoustical Society of Korea
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• v.26 no.1E
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• pp.21-26
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• 2007

In this paper, we propose a modified Viterbi algorithm to compensate for endpoint detection error during the decoding phase of an isolated word recognition task. Since the conventional Viterbi algorithm explores only the search space whose boundaries are fixed to the endpoints of the segmented utterance by the endpoint detector, the recognition performance is highly dependent on the accuracy level of endpoint detection. Inaccurately segmented word boundaries lead directly to recognition error. In order to relax the degradation of recognition accuracy due to endpoint detection error, we describe an unconstrained search of word boundaries and present an algorithm to explore the search space with efficiency. The proposed algorithm was evaluated by performing a variety of simulated endpoint detection error cases on an isolated word recognition task. The proposed algorithm reduced the Word Error Rate (WER) considerably, from 84.4% to 10.6%, while consuming only a little more computation power.

• Journal of the Optical Society of Korea
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• v.14 no.1
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• pp.22-27
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• 2010

Bit error rate (BER) monitoring is the ultimate goal of performance monitoring in all digital transmission systems as well as optical fiber transmission systems. To achieve this goal, optimization of the decision threshold must also be considered because BER is dependent on the level of decision threshold. In this paper, we analyze a pseudo-error counting scheme and propose an algorithm to achieve both BER monitoring and adaptive decision threshold optimization in optical fiber transmission systems. To verify the effectiveness of the proposed algorithm, we conduct computer simulations in both Gaussian and non-Gaussian distribution cases. According to the simulation results, BER and the optimum decision threshold can be estimated with the errors of < 20% and < 10 mV, respectively, within 0.1-s processing time in > 40-Gb/s transmission systems.

• Journal of the Korea Society of Computer and Information
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• v.13 no.2
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• pp.19-29
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• 2008

In case of unit testing, White-box test can be used to closely check source code and to analyze logic and statement errors. On the other hand, in case of function testing of system level, Black-box test can be mainly used to compare actual and expected results by inputting test data because the scale of function is large. This Black-Box test in system testing level has problem in tracing errors in source code when we find errors. Moreover applying White-box test is not easy for system testing level because the levels of test target are different. Therefore this paper suggests the vertical test method of a practical and integrated system level which can checks up to source code level using White-box test style although it aims to test the highly abstract level like a system function. In addition, the experiment explains how to apply the vertical test by displaying an example which traces from UML specification model to the source code and also shows efficiency of error trace.

• Proceedings of the Korea Water Resources Association Conference
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• 2023.05a
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• pp.179-179
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• 2023

This study suggests a new approach of water level forecasting for extended lead times using original data preprocessing with variational mode decomposition (VMD). Here, two machine learning algorithms including light gradient boosting machine (LGBM) and random forest (RF) were considered to incorporate extended lead times (i.e., 5, 10, 15, 20, 25, 30, 40, and 50 days) forecasting of water levels. At first, the original data at two water level stations (i.e., SW173 and SW269 in Bangladesh) and their decomposed data from VMD were prepared on antecedent lag times to analyze in the datasets of different lead times. Mean absolute error (MAE), root mean squared error (RMSE), and mean squared error (MSE) were used to evaluate the performance of the machine learning models in water level forecasting. As results, it represents that the errors were minimized when the decomposed datasets were considered to predict water levels, rather than the use of original data standalone. It was also noted that LGBM produced lower MAE, RMSE, and MSE values than RF, indicating better performance. For instance, at the SW173 station, LGBM outperformed RF in both decomposed and original data with MAE values of 0.511 and 1.566, compared to RF's MAE values of 0.719 and 1.644, respectively, in a 30-day lead time. The models' performance decreased with increasing lead time, as per the study findings. In summary, preprocessing original data and utilizing machine learning models with decomposed techniques have shown promising results for water level forecasting in higher lead times. It is expected that the approach of this study can assist water management authorities in taking precautionary measures based on forecasted water levels, which is crucial for sustainable water resource utilization.

• The Journal of the Korea Contents Association
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• v.21 no.6
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• pp.19-34
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• 2021

The aim of this study is verifying the effects of chatbot's error types and structures of error message on attitude, behavior intention towards the chatbot and perceived usability of the chatbot. The error types of chatbot are divided into 'experience' error and 'agency' error, which set different expectancy level, according to mind perception theory. The structures of error message were either unstructured condition composed of error specification only or structured condition composed of apology, explanation and willingness of improvement. It was found that score of perceived usability was higher in experience error condition than agency error condition. Also, all three scores of dependent variables were higher in structured error message condition than unstructured error message condition. Furthermore, expectation gap of experience didn't predict the dependent variables but expectation gap of agency predicted all three dependent variables. Finally, the tendency of interaction effect between the error type and the structure of the error message on expectation gap of agency was observed. This study confirmed the mitigating effect of structured error messages and the possibility that these effects may vary by the type of error. The result is expected to be applicable to design of error coping strategies that enhance user experience.

• 제어로봇시스템학회:학술대회논문집
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• 1993.10a
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• pp.699-703
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• 1993

When the error path can be modeled as a pure delay, an adaptive algorithm for slowly time varying system is proposed to minimize the sound pressure level. This algorithm makes it possible to use the fittered-x LMS algorithm with on-line delay modeling of the error path. Another simple adaptive algorithm for pure tone noise is proposed which eliminates the cross term in the multiple error filtered-x LMS algorithm.

• 제어로봇시스템학회:학술대회논문집
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• 1992.10a
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• pp.123-128
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• 1992

This paper presents an autotuning algorithm of scaling factor in order to improve system performance. We define the scaling factor of fuzzy controller as a function of error and error change. This function is tuned by the output of performance evaluation level utilizing the error of overshoot and rising time. Simulation results show that the proposed algorithm has good tuning performance for a system with parameter change.