• Journal of the Korean Solar Energy Society
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• v.37 no.5
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• pp.1-11
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• 2017

A study on Nacelle Lidar (Light detection and ranging) measurement error and the data reliability verification was carried out at Haengwon wind farm on Jeju Island. For measurement data error processing, the characteristics of Nacelle Lidar measurements were analyzed by dividing into three parts, which are weather conditions (temperature, humidity, atmosphere, amount of precipitation), mechanical movement (rotation of wind turbine blades, tilt variation of Nacelle Lidar) and Nacelle Lidar data availability. After processing the measurement error, the reliability of Nacelle Lidar data was assessed by comparing with wind data by an anemometer on a met mast, which is located at a distance of 200m from the wind turbine with Nacelle Lidar. As a result, various weather conditions and mechanical movement did not disturb reliable data measurement. Nacelle Lidar data with availability of 95% or more could be used for checking Nacelle Lidar wind data reliability. The reliability of Nacelle Lidar data was very high with regression coefficient of 98% and coefficient of determination of 97%.

• The Journal of Information Technology
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• v.8 no.3
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• pp.105-115
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• 2005

The CMA and MMA blind equalization algorithm has the inevitable large residual error caused by mismatching between the symbol constellation at a steady state after convergence. Stop-and-Go algorithm has a very superior residual error characteristics at a steady state but a relatively slow convergence characteristics. In this paper, we propose a SAG-Flagged MMA as a new adaptive blind equalization algorithm with a Stop-and-Go flag which follows a flagged MMA in update scheme of tap weights as appling the flag obtaining from Stop-and-Go algorithm to MMA. Using computer simulation, it is confirmed that the proposed algorithm has an enhancing performance from the viewpoint of residual ISI, residual error and convergence speed in comparison with MMA and Stop-and-Go algorithm. Algorithm has a new error function using the decided original constellation instead of the reduced constellation. By computer simulation, it is confirmed that the proposed algorithm has the performance superiority in terms of residual ISI and convergence speed compared with the adaptive blind equalization algorithm of CMA family, Constant Modulus Algorithm with Carrier Phase Recovery and Modified CMA(MCMA).

• Journal of Advanced Navigation Technology
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• v.19 no.3
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• pp.244-249
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• 2015

High-altitude electromagnetic pulse (HEMP) is generated from a nuclear burst at high altitudes above the Earth, the electromagnetic fields reach the ground nearly simultaneously with regard to the operation time of systems. The aim of this analysis is to inquire about HEMP characteristics and to analyze about effect in orthogonal frequency division multiplexing (OFDM) system. Specifically, HEMP characteristics are classified field sources, spatial coverage, time domain behavior, frequency spectrum and field intensities in this study. Bits error rate (BER) of the receiver with the software simulation is confirmed for the HEMP effect. Q-factor made a difference about interference duration by transfer characteristics of system. When Q factor is smaller, the recovery time from HEMP interference is short. To the contrary, if the Q factor is larger, the recovery duration is lasted longer by 300-600%.

• Transactions of the Korean Society of Mechanical Engineers
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• v.10 no.1
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• pp.157-163
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• 1986

A method to improve the Finite Elements Model and to identify structure stiffness damages utilizing measured dynamic characteristics is suggested. In order to show the effectiveness of the proposed method, a sample structure is adopted and tested. It is found that; (1) the Finite Elements Model can be improved with experimentally obtained dynamic characteristics satisfactorily and (2) the test results are also very helpful to search the stiffness damaged part of the sample structure via plotting the error matrix[E], especially it is aboved that the weighted error matrix is very effective to detect even the stiffness changes are relatively small.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.52 no.12
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• pp.696-701
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• 2003

This paper presents a systematic method of probing channel characteristics and communication reliabilities of home power line communication network applied to the Internet accessed control of home appliances. The effects of the three performance deterioating factors, i.e., additive noise, channel attenuation, and intersymbol interference, can be systematically measured by applying the channel probing waveform in the frequency range from 100KHz to 450KHz. Probability of bit error is derived with the probed channel parameters of the signal attenuation, noise and signal-to-interference ratio read in the frequency domain. The agreement between the derived probability of bit error and the measured probability of bit error supports the validity of the proposed approach of probing home power line channel characteristics. The experimental results performed with the constructed test-bed applying the proposed channel probing method also support the feasibility of commercially deploying the PLC modem installed home appliances and their services for the Internet accessed home automation.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.7 no.8
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• pp.1612-1620
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• 2003

This papers describes a nonlinear transfer function modelling of designed GaAs FET power amplifier by measured and simulated values of designed PA amplifier for multi­carrier transmission system, With the results of PA nonlinearity characteristic, we can estimates AM­AM and AM­PM of designed PA. According to the estimated nonlinear characteristics, we can analysis the ACPR of PA for spectral regrowth, the error vector measurement(EVM) of constallation signals and bit error rate of QPSK and 64­QAM. The suggested nonlinear modelling results are used to get an accurate estimate of digital characteristics between PA amplifier and wireless multi­carrier transmission system using OFDM.

• Geomechanics and Engineering
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• v.34 no.5
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• pp.547-559
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• 2023

We evaluated the applicability of machine learning techniques and the Kuz-Ram model for predicting the mean fragmentation size in open-pit mines. The characteristics of the in-situ rock considered here were uniaxial compressive strength, tensile strength, rock factor, and mean in-situ block size. Seventy field datasets that included these characteristics were collected to predict the mean fragmentation size. Deep neural network, support vector machine, and extreme gradient boosting (XGBoost) models were trained using the data. The performance was evaluated using the root mean squared error (RMSE) and the coefficient of determination (r²). The XGBoost model had the smallest RMSE and the highest r² value compared with the other models. Additionally, when analyzing the error rate between the measured and predicted values, XGBoost had the lowest error rate. When the Kuz-Ram model was applied, low accuracy was observed owing to the differences in the characteristics of data used for model development. Consequently, the proposed XGBoost model predicted the mean fragmentation size more accurately than other models. If its performance is improved by securing sufficient data in the future, it will be useful for improving the blasting efficiency at the target site.

• Korean Journal of Construction Engineering and Management
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• v.18 no.6
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• pp.98-108
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• 2017

Recently, the development of middle and high-rise building technology using modular construction method has emphasized the importance of site construction error management. The modular construction method is very limited to adjust the construction error in the field because of the factory production characteristics. Therefore, in order to prevent the construction error in advance, a management plan reflecting the characteristics of the modular construction method is required, and it is important to make the decision of the construction participant at each stage. This study analyzed the factor of construction error of modular construction and suggested a decision support model for construction error management based on construction process. The result of this study is expected to be a guideline for the modular construction participant to derive the construction error management plan.

• Journal of Korea Entertainment Industry Association
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• v.14 no.8
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• pp.213-219
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• 2020

The purpose of this study was to investigate the characteristics of error types in naming task for 8 questionable demeatia groups, 9 definite dementia groups, and 10 normal groups. The items of naming error analysis were classified into visual perception errors, semantic association errors, semantic non-correlation errors, phoneme errors, Don't Know, and No Response. For the analysis, descriptive statistics analysis, analysis of variance, and multivariate analysis of variance were conducted using SPSS 21.0. As a result, there was a significant difference in the error rate between groups according to the error type. The errors that showed significant differences between the normal group and the other two groups were visual perception errors and semantic non-related errors. The error of non-response was different from the dementia confirmation group, but there was no significant difference from the dementia suspicion group. These results showed that Alzheimer's patients had a defect in confrontation naming ability. Also, it was found that it is appropriate to provid other clues when the defects caused by the degeneration of a specific step during the information processing process become severe.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 2001.10a
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• pp.214-219
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• 2001

One of the major limitations of productivity and quality in metal cutting is the machining accuracy of machine tools. The machining accuracy is affected by geometric errors, thermally-induced errors, and the deterioration of the machine tools. Geometric and thermal errors of machine tools should be measured and compensated to manufacture high quality products. In metal cutting, the machining accuracy is more affected by thermal errors than by geometric errors. In this study, the compensation device and temperature-based algorithm have been presented in order to compensate thermal error of machine tools under the real-time. The thermal error is modeled by means of angularity errors of a column and thermal drift error of the spindle unit which are measured by the touch probe unit with a star type styluses, a designed spherical ball artifact, and five gap sensors. In order to compensate thermal characteristics under several operating conditions, experiments performed with five gap sensors and manufactured compensation device on the horizontal machining center.