• Journal of Navigation and Port Research
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• v.35 no.4
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• pp.343-349
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• 2011

The forecasting of container volume which is the basis of port logistics facilities expansion has a great influence on development of an port. Based on this importance, various previous studies have presented methodology on container volume forecasting. The results of many previous studies pointed out the limitations of future forecasting based on past container volume and emphasized that more various factors should be considered to compensate this. Taking notice of this point, this study forecasted future container volume by using ARIMA model, time series analysis and System Dynamics (SD) method, a dynamic analysis technique and performed the comparative review with the forecast of the Ministry of Land, Transport and Maritime affairs. Recently with rapid changes in economic and social environment, the non-linear change tendency for forecasting container traffic is presented as a new alternative to the country.

• Proceedings of the Korean Society of Computer Information Conference
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• 2021.07a
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• pp.395-398
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• 2021

최근 방대한 양의 텍스트 정보가 인터넷에 유통되면서 정보의 핵심 내용을 파악하기가 더욱 어려워졌으며, 이로 인해 자동으로 텍스트를 요약하려는 연구가 활발하게 이루어지고 있다. 텍스트 자동 요약을 위한 다양한 기법 중 특히 트랜스포머(Transformer) 기반의 모델은 추상 요약(Abstractive Summarization) 과제에서 매우 우수한 성능을 보이며, 해당 분야의 SOTA(State of the Art)를 달성하고 있다. 하지만 트랜스포머 모델은 매우 많은 수의 매개변수들(Parameters)로 구성되어 있어서, 충분한 양의 데이터가 확보되지 않으면 이들 매개변수에 대한 충분한 학습이 이루어지지 않아서 양질의 요약문을 생성하기 어렵다는 한계를 갖는다. 이러한 한계를 극복하기 위해 본 연구는 소량의 데이터가 주어진 환경에서도 양질의 요약문을 생성할 수 있는 문서 요약 방법론을 제안한다. 구체적으로 제안 방법론은 한국어 사전학습 언어 모델인 KoBERT의 임베딩 행렬을 트랜스포머 모델에 적용하는 방식으로 문서 요약을 수행하며, 제안 방법론의 우수성은 Dacon 한국어 문서 생성 요약 데이터셋에 대한 실험을 통해 ROUGE 지표를 기준으로 평가하였다.

• Korea Trade Review
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• v.47 no.6
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• pp.291-305
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• 2022

In this study, the volume of Pohang Port was predicted. All cargo of Pohang port, iron ore, steel, and bituminous coals were selected as prediction targets. SARIMA, Prophet, and Neural Prophet were used as analysis methods. The predictive power of each model was verified, and a predictive model with high performance was used to predict the volume of goods in Pohang port. As a result of the analysis, it was found that Neural Prophet showed the highest performance in all predictive power. As a result of predicting the future volume of goods until August 2027 using Neural Prophet, it was found that the volume of all items in Pohang port was decreasing. In particular, it was analyzed that the decline in steel cargo was steep. In order to increase the volume of cargo at Pohang port, it is necessary to diversify the cargo handled at Pohang port and check the policy of increasing the volume of cargo.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.3
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• pp.1100-1118
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• 2021

In a wide range of ML applications, the training data contains privacy-sensitive information that should be kept secure. Training the ML systems by privacy-sensitive data makes the ML model inherent to the data. As the structure of the model has been fine-tuned by training data, the model can be abused for accessing the data by the estimation in a reverse process called model inversion attack (MIA). Although, MIA has been applied to shallow neural network models of recognizers in literature and its threat in privacy violation has been approved, in the case of a deep learning (DL) model, its efficiency was under question. It was due to the complexity of a DL model structure, big number of DL model parameters, the huge size of training data, big number of registered users to a DL model and thereof big number of class labels. This research work first analyses the possibility of MIA on a deep learning model of a recognition system, namely a face recognizer. Second, despite the conventional MIA under the white box scenario of having partial access to the users' non-sensitive information in addition to the model structure, the MIA is implemented on a deep face recognition system by just having the model structure and parameters but not any user information. In this aspect, it is under a semi-white box scenario or in other words a gray-box scenario. The experimental results in targeting five registered users of a CNN-based face recognition system approve the possibility of regeneration of users' face images even for a deep model by MIA under a gray box scenario. Although, for some images the evaluation recognition score is low and the generated images are not easily recognizable, but for some other images the score is high and facial features of the targeted identities are observable. The objective and subjective evaluations demonstrate that privacy cyber-attack by MIA on a deep recognition system not only is feasible but also is a serious threat with increasing alert state in the future as there is considerable potential for integration more advanced ML techniques to MIA.

• International Journal of Concrete Structures and Materials
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• v.6 no.3
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• pp.155-163
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• 2012

In order to predict the neutralization of concrete which is the reaction of carbonation dioxide from the outside and cement hydration product, such as calcium hydroxide and C-S-H, it was studied the numerical analysis method considering change of the pore structure and relative humidity during the neutralization reaction. Diffusion-reaction neutralization model was developed to predict the neutralization depth of concrete with coating finishing material. In order to build numerical analysis models considering outdoor environment and finishing materials, the adaption of proposed model was shown the results of existing outdoor exposure test results and accelerated carbonation test.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2005.05a
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• pp.188-191
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• 2005

Taguchi method is used to determine the optimal configuration of PZT (Lead Zirconate-Titanate) patch on the host structure for improving the performance of piezoelectric shunt system. The charges generated on the surface of PZT patch are selected to be the objective function in the Taguchi method. Full three dimensional finite element models are used to simulate vibration of smart panel and to obtain the admittance of the piezoelectric shunt system. Using Taguchi method in Minitab, the optimal model is obtained. The experiment with piezoelectric shunt circuit is performed to verify the validity of the optimal model comparing with initial model.

• Journal of Advanced Navigation Technology
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• v.13 no.6
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• pp.943-949
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• 2009

In this paper, the 5.9GHz WAVE(Wireless Access in Vehicular Environments) channel modeling is used by the Jakes channel model for the suitability of the fast wireless channel fluctuation. The performance analysed the fading signal constellation and the spectrum in the IEEE 802.11p spectrum mask, the Doppler effect, the modulation scheme. In addition, the vehicular speed, exactly the performance analysis the WAVE communication systems follow the Doppler effect.

• Bulletin of the Korean Chemical Society
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• v.34 no.10
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• pp.2909-2914
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• 2013

p-Hydroxyphenylpyruvate dioxygenase (HPPD) is a potent herbicide target that is in current use. In this study, we developed a predictive pharmacophore model that uses known HPPD inhibitors based on a theoretically constructed HPPD homology model. The pharmacophore model derived from the three-dimensional (3D) structure of a target protein provides helpful information for analyzing protein-ligand interactions, leading to further improvement of the ligand binding affinity.

• The KSFM Journal of Fluid Machinery
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• v.18 no.6
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• pp.76-80
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• 2015

The purpose of this study is to understand the cavitation phenomena in centrifugal pumps through computational fluid dynamics method. NPSH characteristic curve is measured from different flow operating conditions. Steady state, liquid-vapor homogeneous method with two equations transport turbulence model is employed to estimate the NPSH curve in centrifugal pumps. The Rayleigh-Plesset cavitation model is adapted as source term for inter-phase mass transfer in order to understand cavitation phenomena in centrifugal pumps. The cavitation incipient curve is clearly estimated at different flows operating conditions. A relationship is made between cavitation incipient and NPSH curve. Also the effects on water vapor volume fraction and pressure load distributions on the impeller blade are also described.

• Journal of Intelligence and Information Systems
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• v.1 no.1
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• pp.91-109
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• 1995

This paper compared four knowledge acquisition methods (namely, neural network, case-based reasoning, discriminant analysis, and covariance structure modeling) for allergic rhinitis. The data were collected from 444 patients with suspected allergic rhinitis who visited the Otorlaryngology Deduring 1991-1993. Among four knowledge acquisition methods, the discriminant model had the best overall diagnostic capability (78%) and the neural network had slightly lower rate(76%). This may be explained by the fact that neural network is essentially non-linear discriminant model. The discriminant model was also most accurate in predicting allergic rhinitis (88%). On the other hand, the CSM had the lowest overall accuracy rate (44%) perhaps due to smaller input data set. However, it was most accuate in predicting non-allergic rhinitis (82%).