• Bulletin of the Korean Chemical Society
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• v.26 no.12
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• pp.2007-2016
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• 2005

An artificial neural network (ANN) is successfully presented for prediction acidity constant (pKa) of various benzoic acids and phenols with diverse chemical structures using a nonlinear quantitative structure-property relationship. A three-layered feed forward ANN with back-propagation of error was generated using six molecular descriptors appearing in the multi-parameter linear regression (MLR) model. The polarizability term $(\pi_1)$, most positive charge of acidic hydrogen atom $(q^+)$, molecular weight (MW), most negative charge of the acidic oxygen atom $(q^-)$, the hydrogen-bond accepting ability $(\epsilon_B)$ and partial charge weighted topological electronic (PCWTE) descriptors are inputs and its output is pKa. It was found that properly selected and trained neural network with 205 compounds could fairly represent dependence of the acidity constant on molecular descriptors. For evaluation of the predictive power of the generated ANN, an optimized network was applied for prediction pKa values of 37 compounds in the prediction set, which were not used in the optimization procedure. Squared correlation coefficient $(R^2)$ and root mean square error (RMSE) of 0.9147 and 0.9388 for prediction set by the MLR model should be compared with the values of 0.9939 and 0.2575 by the ANN model. These improvements are due to the fact that acidity constant of benzoic acids and phenols in water shows nonlinear correlations with the molecular descriptors.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2003.11a
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• pp.885-891
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• 2003

Effects of each acoustic property on absorption characteristics of polyester fiber materials has been studied in this paper. It would be impossible for us to measure effects of each acoustic property by experimental method since we cannot make sound-absorbing materials in which only one of the properties is changed. We have adopted a numerical prediction method to carry out parameter studies for each acoustic property. And to get a general behavior of acoustic performance of the materials, the numerical simulation has been repeated to several cases of different bulk density. Finally we have obtained frequency-dependent control factors in the absorption performance which gives us design capability of acoustic absorbing materials.

• Proceedings of the Korea Concrete Institute Conference
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• 2000.10a
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• pp.511-516
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• 2000

A Hybrid Wall System(HWS) building, Kolon Bundang Tripolis was instrumented to measure the vertical deformation of core-walls and columns. The vertical shortening of individual members were measured at selected floor levels such as 1F, 12F, 25F, and 34F. The measurement has been taken during one year after the construction was started. Together with the measurement, concrete property tests were performed in the laboratory using the concrete obtained in the field. The measured vertical shortenings were compared with the calculated prediction values and the satisfactory agreement was obtained.

• Communications for Statistical Applications and Methods
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• v.9 no.2
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• pp.411-423
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• 2002

In this paper, we propose a split criterion for binary decision trees. The proposed criterion selects the optimal split by measuring the prediction success of the candidate splits at a given node. The criterion is shown to have the property of exclusive preference. Examples are given to demonstrate the properties of the criterion.

• Fibers and Polymers
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• v.6 no.3
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• pp.269-276
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• 2005

In this study, cross-cultural comparison of sound sensation for Korean traditional silk fabrics between Korea and America was performed and prediction models for sound sensation by objective measurements including sound parameters such as level pressure of total sound (LPT), Zwicker's psychoacoustic characteristics, and mechanical properties by Kawabata Evaluation System were established for each nation to explore the objective parameters explaining sound sensation of the Korean traditional silk. As results, Koreans felt the silk fabric sounds soft and smooth while Americans were revealed as perceiving them hard and rough. Both Koreans and Americans were pleasant with sounds of Gongdan and Newttong and especially Newttong was preferred more by Americans in terms of sound sensation. In prediction models, some of subjective sensation were found as being related mainly with mechanical properties of traditional silk fabrics such as surface and compressional characteristics.

• Computers and Concrete
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• v.6 no.2
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• pp.155-165
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• 2009

Splitting tensile strength (STS) of high-performance concrete (HPC) is one of the important mechanical properties for structural design. This property is related to compressive strength (CS), water/binder (W/B) ratio and concrete age. This paper presents a clustering-based fuzzy model for the prediction of STS based on the CS and (W/B) at a fixed age (28 days). The data driven fuzzy model consists of three main steps: fuzzy clustering, inference system, and prediction. The system can be analyzed directly by the model from measured data. The performance evaluations showed that the fuzzy model is more accurate than the other prediction models concerned.

• ETRI Journal
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• v.29 no.6
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• pp.823-825
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• 2007

In this letter, we propose a novel algorithm to predict MPEG-coded real-time variable bit rate (VBR) video traffic. From the frame size measurement, the algorithm extracts the statistical property of video traffic and utilizes it for the prediction of the next frame for I-, P-, and B- frames. The simulation results conducted with real-world MPEG-4 VBR video traces show that the proposed algorithm is capable of providing more accurate prediction than those in the research literature.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.21 no.5
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• pp.1172-1179
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• 1996

General adaptive noise canceller(ANC) suffers from the misadjustment of adaptive filter weights, because of the gradient-estimate noise at steady state. In this paper, an adaptive noise cancellation algorithm with speech detector which is distinguishing speech from silence and adaptation-transient region is proposed. The speech detector uses property of adaptive prediction-error filter which can filter the highly correlated speech. To detect speech region, estimation error which is the output of the adaptive filter is applied to the adaptive prediction-error filter. When speech signal apears at the input of the adaptive prediction-error filter. The ratio of input and output energy of adaptive prediction-error filter becomes relatively lower. The ratio becomes large when the white noise appears at the input. So the region of speech is detected by the ratio. Sign algorithm is applied at speech region to prevent the weights from perturbing by output speech of ANC. As results of computer simulation, the proposed algorithm improves segmental SNR and SNR up to about 4 dBand 11 dB, respectively.

• Proceedings of the KSR Conference
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• 2010.06a
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• pp.942-946
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• 2010

As the major sources of interior noise of train at running condition are the wheel/rail contact noise, the traction motor's noise and the driving gear's noise and these noise sources are transmitted through the car body, the noises of HVAC and air duct can be ignored. But the interior noise of train at standstill condition is decided by HVAC's noise and noise from the diffuser through the air duct. the interior noise prediction of train at standstill condition should be performed considering the shape of air duct, the air velocity and noise reduction property inside the air duct. But it is hard to estimate the interior noise level by the numerical method. Therefore train maker predict the interior noise level using The commercial noise prediction program. This paper introduce the noise prediction method of the train at standstill condition using the commercial program appling the ray tracing method and statistical energy analysis.

• Journal of Ocean Engineering and Technology
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• v.37 no.4
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• pp.145-157
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• 2023

Due to a recent increase in maritime activities in South Korea, the frequency of maritime distress is escalating and poses a significant threat to lives and property. The aim of this study was to validate a drift trajectory prediction technique to help mitigate the damages caused by maritime distress incidents. In this study, OpenDrift was verified using satellite drifter data from the Korea Hydrographic and Oceanographic Agency. OpenDrift is a Monte-Carlo-based Lagrangian trajectory modeling framework that allows for considering leeway, an important factor in predicting the movement of floating marine objects. The simulation results showed no significant differences in the performance of drift trajectory prediction when considering leeway using four evaluation methods (normalized cumulative Lagrangian separation, root mean squared error, mean absolute error, and Euclidean distance). However, leeway improved the performance in an analysis of location prediction conformance for maritime search and rescue operations. Therefore, the findings of this study suggest that it is important to consider leeway in drift trajectory prediction for effective maritime search and rescue operations. The results could help with future research on drift trajectory prediction of various floating objects, including marine debris, satellite drifters, and sea ice.