• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2015.10a
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• pp.165-166
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• 2015

Due to the international economic downturn and the increasing competition, container terminals have been trying to achieve cost effectiveness and high service levels. Shipping companies want to get better services from container terminals but container terminals only have limited space and equipment. Frequently, too many external trucks come to the terminal at the same time, and create bottle necks at the terminals. Ouside the container terminals traffic jams occur as well. As a result, stakeholders need a vehicle booking system. By VBS, container terminals can plan efficiently in advance to avoid work delay and the truck drivers can finish their jobs quickly. This paper aims to search efficient models for the container terminals by using VBS.

• Asian-Australasian Journal of Animal Sciences
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• v.20 no.4
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• pp.569-576
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• 2007

Four hundred and fifty tilapias ($6.77{\pm}0.23$ g) were assigned randomly to six groups to evaluate the feasibility of the tested antibacterial peptides (ABPs) and oligosaccharides as substitutes for antibiotics. The control group was fed with a commercial tilapia diet; other five groups were fed with the same commercial diet supplemented with konjac glucomannan (KGLM), cluster bean galactomannan (CBGAM), and three animal intestinal ABPs derived from chicken, pig and rabbit at 100 mg/kg respectively. After 21 days of feeding, growth, disease resistance, and in vivo anti-adherence were determined. Furthermore, the inhibitory effect of tested agents on adhesion of Aeromonas veronii biovar sobria (A.vbs) strain BJCP-5 to tilapia enteric epithelia in vitro was assessed by cell-ELISA system. As a result, the tested agents supplemented at 100 mg/kg show significant benefit to tilapia growth and disease resistance (p<0.05), and the benefit may be correlated with their interfering in the contact of bacteria with host mucosal surface. Although none of the tested agents did inhibit the growth of BJCP-5 in tryptic soy broth at $100{\mu}g/ml$, all of them did inhibit the adhesion of A.vbs to tilapia enteric epithelia in vivo and in vitro. In vitro mimic assays show that three ABPs at low concentrations of $25{\mu}g/ml$ and $2.5{\mu}g/ml$ have the reciprocal dose-dependent anti-adherence effect. The inhibition of ABPs may be correlated with a cation bridging and/or receptor-ligand binding, but not with hydrophobicity. The KGLM and CBGAM inhibited the adherence of BJCP-5 to tilapia enteric epithelia with dose-dependent manner in vitro, and this may be through altering bacterial hydrophobicity and interfering with receptor-ligand binding. Our results indicate that the anti-adherence of the tested ABPs and oligosaccharides may be one of the mechanisms in promoting tilapia growth and resistance to A.vbs.

• Journal of Intelligence and Information Systems
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• v.29 no.1
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• pp.377-396
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• 2023

As the cryptocurrency market continues to grow, it has developed into a new financial market. The need for investment strategy research on the cryptocurrency market is also emerging. This study aims to conduct an empirical analysis on an investment methodology of cryptocurrency that combines short-term trading strategy and deep learning. Daily price data of the Ethereum was collected through the API of Upbit, the Korean cryptocurrency exchange. The investment performance of the experimental model was analyzed by finding the optimal parameters based on past data. The experimental model is a volatility breakout strategy(VBS), a Long Short Term Memory(LSTM) model, moving average cross strategy and a combined model. VBS is a short-term trading strategy that buys when volatility rises significantly on a daily basis and sells at the closing price of the day. LSTM is suitable for time series data among deep learning models, and the predicted closing price obtained through the prediction model was applied to the simple trading rule. The moving average cross strategy determines whether to buy or sell when the moving average crosses. The combined model is a trading rule made by using derived variables of the VBS and LSTM model using AND/OR for the buy conditions. The result shows that combined model is better investment performance than the single model. This study has academic significance in that it goes beyond simple deep learning-based cryptocurrency price prediction and improves investment performance by combining deep learning and short-term trading strategies, and has practical significance in that it shows the applicability in actual investment.

• Proceedings of the Korea Information Processing Society Conference
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• 2001.04a
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• pp.337-340
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• 2001

A major impediment in using the Dempster-Shafer evidence combination scheme is its computational complexity, which in general is exponential since DS scheme allows any subsets over the frame of discernment as focal elements. To avoid this problem, we propose a method called approximate evidence combination scheme. This scheme is applied to a few sample applications and the experiment results are compared with those of VBS. The results show that the approximation scheme achieves a great amount of computational speedup and produces belief values within the range of deviation that the expert allows.

• Journal of Broadcast Engineering
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• v.21 no.6
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• pp.889-898
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• 2016

Virtual Bass System (VBS) is widely used to extend the lower frequency limit of small loudspeakers, which generates harmonics of a fundamental frequency. The perceptual quality of the VBS is highly dependent on the harmonic weighting strategy. There have been several weighting methods, including exponential attenuation and timbre matching. However, it is essential to match phases between harmonics in the original signal and generate harmonics to precisely convey the weighting strategy. This paper shows the limitations of the previous harmonic weighting schemes and proposes a new harmonic weighting scheme. The proposed weighting scheme proposes phase matching between the original and generated harmonics and varies the slope of the attenuation weighting dynamically according to the missing fundamental frequency. Objective and subjective tests show that the proposed harmonic weighting scheme provides more natural and effective bass perception in a limited situation than the conventional schemes, which implies that the phase matching is essential for the high quality bass enhancement.

• Journal of the Korea Society of Computer and Information
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• v.11 no.4 s.42
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• pp.147-154
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• 2006

Effective and efficient representation of color features of multiple video frames is an important vet challenging task for visual information management systems. This paper Proposes a Video Browsing Service(VBS) that provides both the video content retrieval and the video browsing by the real-time user interface on Web. For the scene segmentation and key frame extraction of video sequence, we proposes an efficient scene change detection method that combine the RGB color histogram with the X2 (Chi Square) histogram. Resulting key frames are linked by both physical and logical indexing. This system involves the video editing and retrieval function of a VCR's. Three elements that are the date, the need and the subject are used for video browsing. A Video Browsing Service is implemented with MySQL, PHP and JMF under Apache Web Server.

• Journal of Navigation and Port Research
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• v.46 no.4
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• pp.344-350
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• 2022

Due to the increase in container cargo volume, the congestion of container terminals is increasing and the waiting time of gate in-out trucks has significantly lengthened at container yards and gates, resulting in severe inefficiency in gate in-out truck operations as well as port operations. To resolve this problem, the Busan Port Authority and terminal operator provide services such VBS, terminal congestion information, and expected operation processing time information. However, the visible effect remains insufficient, as it may differ from actual waiting time.. Thus, as basic data to resolve this problem, this study presents deep learning based average gate in-out truck waiting time prediction models, using container gate in-out information at Busan New Port. As a result of verifying the predictive rate through comparison with the actual average waiting time, it was confirmed that the proposed predictive models showed high predictive rate.

• Journal of Navigation and Port Research
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• v.48 no.1
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• pp.27-33
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• 2024

Following the COVID-19 pandemic, congestion within container terminals has led to a significant increase in waiting time and turnaround time for external trucks, resulting in a severe inefficiency in gate-in and gate-out operations. In response, port authorities have implemented a Vehicle Booking System (VBS) for external trucks. It is currently in a pilot operation. However, due to issues such as information sharing among stakeholders and lukewarm participation from container transport entities, its improvement effects are not pronounced. Therefore, this study proposed a deep learning-based predictive model for external trucks turnaround time as a foundational dataset for addressing problems of waiting time for external trucks' turnaround time. We experimented with the presented predictive model using actual operational data from a container terminal, verifying its predictive accuracy by comparing it with real data. Results confirmed that the proposed predictive model exhibited a high level of accuracy in its predictions.

• Proceedings of the IEEK Conference
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• 2001.09a
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• pp.279-282
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• 2001

본 논문에서는 가상의 블루스크린(Virtual Blue Screens, VBS)을 이용한 반자동 영상분할 기법을 제안한다. 가상 블루스크린은 동영상에서 배경영역을 특정한 값으로 채워 만든 참조영상으로 정의한다. 반자동 영상 분할 기법은 크게 화면내 영상분할과 화면간 영상분할의 두 단계로 이루어진다. 화면내 영상분할은 VBS와 원영상의 형태학적 분할 기법을 사용하고, 화면간 영상 분할은 두개의 연속하는 화면에서 변화검출(Change Detection)로 이루어진다 [1]. 본 논문에서는 효과적인 변화검출을 위하여 제안된 VBS를 사용한다. VBS를 이용한 영상분할에서는 우선, 이전화면에서 만들어진 VBS를 참조하여 다음화면에서 움직임 영역을 예측한다. 이렇게 예측된 영상과 원영상에 대해 형태학적 분할 기법(Morphological Segmentation Technique)을 이용해서 각각에 대한 레이블 마스크(Label Mask)를 얻는다 [2]. 두개의 레이블 마스크 사이에는 서로 공통된 영역들이 존재하게 되는데, 이런 공통된 영역을 추출함으로써 움직임 객체를 검출한다. 현재화면에서 검출된 움직임 객체는 다음화면을 위한 가상의 블루 스크린을 만드는데 사용한다.

• The KIPS Transactions:PartB
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• v.9B no.1
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• pp.17-22
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• 2002

A major impediment in using the Dempster-chafer evidence combination scheme is its computational complexity, which in general is exponential since DS scheme allows any subsets over the frame of discernment as focal elements. To avoid this problem, we propose a method called approximate evidence combination scheme. This scheme is applied to a few sample applications and the experiment results are compared with those of VBS. The results show that the approximation scheme achieves a great amount of computational speedup and produces belief values within the range of deviation that the expert allows.