• The Journal of the Acoustical Society of Korea
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• v.33 no.3
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• pp.153-162
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• 2014

Empirical prediction method of the acoustic load on the fairing is based on jet experimental data on the basis of similarity principle. Representative empirical prediction method, DSM-II(Distributed Source Method-II), is a distributing source method along the jet plume. But the empirical prediction model is limited to reflect the impingement source in real environment because it is based on the free jet data. So, we propose a empirical prediction method considering the impinging jet effect by adding a impingement source in the existing prediction method. Considering the additional source's displacement, spectrum, strength and directivity, we calculate the acoustic load on the KSR-III(Korean Sounding Rocket-III) rocket and compare the results with the existing method and experiment data.

• Honam Mathematical Journal
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• v.32 no.3
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• pp.481-491
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• 2010

In this paper, we investigate a generalization of the Adams-Bashforth method by using the Taylor's series. In case of m-step method, the local truncation error can be expressed in terms of m - 1 coefficients. With an appropriate choice of coefficients, the proposed method has produced much smaller error than the original Adams-Bashforth method. As an application of the generalized Adams-Bashforth method, the accuracy performance is demonstrated in the satellite orbit prediction problem. This implies that the generalized Adams-Bashforth method is applied to the orbit prediction of a low-altitude satellite. This numerical example shows that the prediction of the satellite trajectories is improved one order of magnitude.

• Structural Engineering and Mechanics
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• v.73 no.4
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• pp.455-462
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• 2020

The hybrid method using the extended finite element method (XFEM) and the forward Euler approach is widely employed to predict the fatigue life of plate structures. Due to the accuracy of the forward Euler approach is determined by a small step size, the performance of fatigue life prediction of the hybrid method is not agreeable. Instead the forward Euler approach, a prediction method using midpoint method and support vector regression (SVR) is presented to evaluate the stress intensity factors (SIFs) and the fatigue life. Firstly, the XFEM is employed to calculate the SIFs with given crack sizes. Then use the history of SIFs as a function of either number of fatigue life cycles or crack sizes within the current cycle to build a prediction model. Finally, according to the prediction model predict the SIFs at different crack sizes or different cycles. Three numerical cases composed by a homogeneous plate with edge crack, a composite plate with edge crack and center crack are introduced to verify the performance of the proposed method. The results show that the proposed method enables large step sizes without sacrificing accuracy. The method is expected to predict the fatigue life of complex structures.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.15 no.9
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• pp.1881-1888
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• 2011

Red tide is a natural phenomenon to bloom harmful algal, which fish and shellfish die en masse. Red tide damage with respect to sea farming has been occurred each year. Red tide damage can be minimized by means of prediction of red tide blooms. Red tide prediction using naive bayes classifier can be achieve good prediction results. The result of naive bayes method only determine red tide blooms, whereas the method can not know how increasing of red tide algae density. In this paper, we proposed the red tide blooms prediction method using fuzzy reasoning and naive bayes classifier. The proposed method can enhance the precision of red tide prediction and forecast the increasing density of red tide algae.

• Journal of KIISE:Computing Practices and Letters
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• v.15 no.4
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• pp.280-283
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• 2009

To improve coding performance of scalable video coding which is an emerging video coding standard as an extension of H.264/AVC, SVC uses not only intra prediction and inter prediction but inter-layer prediction. This causes a problem that computational complexity is increased. In this paper, we propose an efficient intra prediction mode decision method in spatial enhancement layer to reduce the computational complexity. The proposed method selects Inra_BL mode using RD cost of Intra_BL in advance. After that, intra mode is decided by only comparing DC modes. Experimental results show that the proposed method reduces 59% of the computation complexity of intra prediction coding, while the degradation in video quality is negligible.

• Journal of Aerospace System Engineering
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• v.14 no.2
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• pp.50-56
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• 2020

In this study, we investigated whether long short-term memory (LSTM) can be used in the future to predict F10.7 index data; the F10.7 index is a space environment factor affecting atomic oxygen erosion. Based on this, we compared the prediction performances of LSTM, the Autoregressive integrated moving average (ARIMA) model (which is a traditional statistical prediction model), and the similar pattern searching method used for long-term prediction. The LSTM model yielded superior results compared to the other techniques in the prediction period starting from the max/min points, but presented inferior results in the prediction period including the inflection points. It was found that efficient learning was not achieved, owing to the lack of currently available learning data in the prediction period including the maximum points. To overcome this, we proposed a method to increase the size of the learning samples using the sunspot data and to upgrade the LSTM model.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.46 no.2
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• pp.1-9
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• 2009

This paper develops a fast method performing intra prediction which only restores block boundary pixels without decoding all blocks in an I slice of H.264/AVC. To accomplish this, we develop a fast integer inverse DCT scheme that quickly decodes residual block boundary which can be consisted of references pixels. we add the restored block boundary pixels and appropriate calculated prediction pixels for each intra prediction mode and consist of needed reference pixels. The experiments showed that the proposed method produces the reliable performance with reducing the computational complexity, compared to conventional method when applied to H.264/AVC integer DCT.

• Journal of the Korea Institute of Building Construction
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• v.2 no.4
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• pp.177-182
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• 2002

The purpose of this study is to develope the strength prediction model by Maturity Method. A maturity function is a mathematical expression to account for the combined effects of time and temperature on the strength development of a cementious mixture. The method of equivalent ages is to use Arrhenius equation which indicates the influence of curing temperature on the initial hydration ratio of cement. For the experimental factors of this study, we selected the concrete mixing of W/C ratio 45, 50, 55 and 60% and curing temperature 5, 10, 20 and $30^{\circ}C$. And we compare and evaluate with logistic model that is existing strength prediction model, because we have to verify adaption possibility of new strength prediction model which is proposed by maturity method. As the results, it is found that investigation of the activation energy that are used to calculate equivalent age is necessary, and new strength prediction model was proved to be more accurate in the strength prediction than logistic model in the early age. Moreover, the use of new model was more reasonable because it has low SSE and high decisive factor.

• The Journal of Korean Institute of Information Technology
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• v.17 no.12
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• pp.29-38
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• 2019

A path prediction method using lifelog requires a large amount of training data for accurate path prediction, and the path prediction performance is degraded when the training data is insufficient. The lack of training data can be solved using data of other users having similar user movement patterns. Therefore, this paper proposes a path prediction algorithm based on user similarity. The proposed algorithm learns the path in a triple grid pattern and measures the similarity between users using the cosine similarity technique. Then, it predicts the path with applying measured similarity to the learned model. For the evaluation, we measure and compare the path prediction accuracy of proposed method with the existing algorithms. As a result, the proposed method has 66.6% accuracy, and it is evaluated that its accuracy is 1.8% higher than other methods.

• Journal of the Korean Data and Information Science Society
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• v.17 no.4
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• pp.1151-1160
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• 2006

The similarity weight, the pearson's correlation coefficient, which is used in the recommender system has a weak point that it cannot predict all of the prediction value. The similarity weight, the vector similarity, has a weak point of the high MAE although the prediction coverage using the vector similarity is higher than that using the pearson's correlation coefficient. The purpose of this study is to suggest how to raise the prediction coverage. Also, the MAE using the suggested method in this study was compared both with the MAE using the pearson's correlation coefficient and with the MAE using the vector similarity, so was the prediction coverage. As a result, it was found that the low of the MAE in the case of using the suggested method was higher than that using the pearson's correlation coefficient. However, it was also shown that it was lower than that using the vector similarity. In terms of the prediction coverage, when the suggested method was compared with two similarity weights as I mentioned above, it was found that its prediction coverage was higher than that pearson's correlation coefficient as well as vector similarity.