• Journal of Korean Port Research
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• v.11 no.2
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• pp.203-214
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• 1997

Hydraulic dredgers(Hopper dredger) are the most important piece of equipment in the entire harbor engineering field, and most suitable for the removal of sand and weakly consloidated sediment such as silt. In maintenance dredging, specially confined harbor or congested passage area, Hopper dredger is user most popularly because less obstruction and danger to navigation than other mostly stationary dredgers. Investigation of the physical behave of dredged material disposal in coastal water from the Hopper dredger includes estimations of pattern as well as thickness of material on the bottom. Calculation based on vertical settling and horizontal advection of single particles ignore the effects of bulk properties of the disposed marterial, vertical and horizontal diffusion. and material dilution due to the entrainment of ambient water during descent. This paper focuses on the analysis of dredging and dumping characteristics and the spatial and temporal changes in the dumping fields for the water column and bottom at a hypothetically confined coastal water. This model accounts the behavior of material after release from the hopper dredger. It is shown that the model describes the qualitative feature of prototype dumping process and its response.

• Journal of the Korean Institute of Telematics and Electronics
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• v.23 no.2
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• pp.249-256
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• 1986

In this paper, we propose the MDM algorithm by which one can desing an FIR filter that is maximally flat and requires no multiplication. We use the modified MAXFLAT subroutive of Kaiser to achieve the maximally-flat characteristics. The filter coefficients are encoded in MDM-code and the optimal stepsize is determined the steepest- descent method. Simulation results shows that the FIR filter designed is almost maximally-flat in passband, but has about -30dB ripples in stopband due to MDM quantization error.

• Proceedings of the Korea Information Processing Society Conference
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• 2022.11a
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• pp.574-576
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• 2022

최근 여러 분야에서 그래프 신경망(graph neural network, GNN)이 활발히 연구되고 있다. 하지만 지금까지 대부분의 GNN 연구는 단일 GNN 모델의 성능을 향상하는 데 집중되었다. 본 논문에서는 앙상블(ensemble) 기법의 대표적 기법인 그래디언트 부스팅(gradient boosting)을 이용하여 GNN의 앙상블 모델을 만드는 방법을 제안한다. 제안 방법은 앞서 만들어진 GNN의 오차를 경사 하강법(gradient descent)을 이용하여 감소시키는 방향으로 다음 GNN을 생성한다. 이 과정을 반복하여 GNN의 최종 앙상블 모델을 얻는다. 실험에서 GNN의 대표적인 모델인 그래프 합성곱 신경망(graph convolutional network, GCN)에 제안 방법을 적용하여 앙상블 모델을 생성한 결과, 단일 GCN 모델에 비해 노드 분류 정확도가 11.3%p까지 증가하였음을 확인하였다.

• Proceedings of the Korean Society of Disaster Information Conference
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• 2023.11a
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• pp.219-220
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• 2023

본 논문에서는 건축물의 고층화, 대형화로 외벽 청소, 도장, 견출, 검사등 작업시 손쉽고, 빠르며 경제적으로 작업을 위한 방법으로 작업의자형 달비계를 사용 하고 있으나 최근 3년간 유지·보수공사 작업시 근로자의 중대재해가 36명으로 신축·증축·재건축공사 2명으로 유지·보수공사에서 많은 중대재해가 발생되고 있는 실정으로 50억이상 신축 작업에서는 산업안전보건법에 의하여 관리감독자 및 안전관리자가 선임 되어 현장의 전반적인 안전관리 활동을 하고 있으나 50억 이하 소규모 작업장에서는 안전관리 할동이 전무한 실정이고 저가수주, 적정 공사기간 불가 및 산업안전보건관리비 미계상 등 근로자들에 대한 안전대책이 없고 외부 안전점검기관의 사각지대로 근로자의 안전 확보에 어려움이 있은 실정으로 사업주 및 근로자에 대한 안전교육 및 관리감독이 철저히 이루어져야 할 것이다

• Journal of Electrical Engineering and information Science
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• v.1 no.2
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• pp.67-76
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• 1996

In the present paper we propose two new improved iterative restoration algorithms. One is to accelerate convergence of the steepest descent method using the improved search directions, while the other accelerates convergence by using preconditioners. It is also shown that the proposed preconditioned algorithm can accelerate iteration-adaptive iterative image restoration algorithm. The preconditioner in the proposed algorithm can be implemented by using the FIR filter structure, so it can be applied to practical application with manageable amount of computation. Experimental results of the proposed methods show good perfomance improvement in the sense of both convergence speed and quality of the restored image. Although the proposed methods cannot be directly included in spatially-adaptive restoration, they can be used as pre-processing for iteration-adaptive algorithms.

• Journal of the Korean Mathematical Society
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• v.61 no.2
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• pp.395-408
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• 2024

There have been numerous studies on the characteristics of the solutions of ordinary differential equations for optimization methods, including gradient descent methods and alternating direction methods of multipliers. To investigate computer simulation of ODE solutions, we need to trace pseudo-orbits by real orbits and it is called shadowing property in dynamics. In this paper, we demonstrate that the flow induced by the alternating direction methods of multipliers (ADMM) for a C² strongly convex objective function has the eventual shadowing property. For the converse, we partially answer that convexity with the eventual shadowing property guarantees a unique minimizer. In contrast, we show that the flow generated by a second-order ODE, which is related to the accelerated version of ADMM, does not have the eventual shadowing property.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.18 no.7
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• pp.2010-2026
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• 2024

This work investigates the hybrid precoder scheme in a millimeter wave (mmWave) multi-user MIMO system. We study a sum rate maximization scheme by jointly designing the digital precoder and the analog precoder. To handle the non-convex problem, a block coordinate descent (BCD) method is formulated, where the digital precoder is solved by a bisection search and the analog precoder is addressed by the penalty dual decomposition (PDD) alternately. Then, we extend the proposed algorithm to the sub-connected schemes. Besides, the proposed algorithm enjoys lower computational complexity when compared with other benchmarks. Simulation results verify the performance of the proposed scheme and provide some meaningful insight.

• Korean Journal of Medicinal Crop Science
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• v.14 no.3
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• pp.139-142
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• 2006

This study was conducted to develop antibacterial hand towel and dishcloth against food poisoning bacteria, and to examine the dyeability and the antibacterial activity of cotton fabrics against food poisoning bacteria, which was dyed with 1 % extracts of Geranium nepalense at $50\;to\;60^{\circ}C$ minutes. Surface colors of cotton fabrics treated nothing, alum $[AIK(SO_4)_2{\cdot}nH_2O]$, and calcium hydroxide $[Ca(OH)_2]$ with mordants showed grayed-yellow group, that treated copper sulfate $(CUSO_4)$ with mordant was grey-brown group, and that treated sulfate of iron $(FeSO_4{\cdot}7H_2O)$ made grayed-green group. Hue value of cotton fabrics dyed with the extracts of Geranium nepalense and dried until twenty times was an order of descent Y, that dried thirty to forty an order of descent YR. Cotton fabrics dyed with the extracts of Geranium nepalense had the antibacterial activity against food poisoning bacteria such as Staphylococcus aureus, Escherichia coil and Salmonella typhimurium by over 99.99%. And that dried over thirty times showed the antibacterial activities against food poisoning bacteria by 52.91%.

• Journal of the Korean Applied Science and Technology
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• v.35 no.3
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• pp.948-955
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• 2018

The purpose of this study was to compare plantar pressure and COP parameters in three types of arch support insole during stair descent in elderly with flatfoot. A total of 14 women elderly were recruited for this study. Pedar-X was used to obtain plantar pressure(peak pressure, mean pressure, and contact area) and COP(distance, displacement, excursion) parameters. One-way ANOVAs were used to compare peak pressure, mean pressure, and contact area, distance of COP, displacement of COP, and excursion of COP. Among the plantar pressure parameters, significant(p<0.05) differences were observed in M3 for the peak pressure, M2, M3, and M4 for the mean pressure, and M2, M3, and M6 for the contact area. Among the COP parameters, distances of COP both in the mediolateral and anteroposterior axes revealed significant(p<0.05) differences. The larger peak pressure values of type A and B insoles were observed as compared to normal insole. The larger peak pressure and shorter COP distance values of type A and B insoles were observed as compared to normal insole.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.21 no.8
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• pp.521-529
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• 2020

Forest fires are one of the most important environmental risks that have adverse effects on many aspects of life, such as the economy, environment, and health. The early detection, quick prediction, and rapid response of forest fires can play an essential role in saving property and life from forest fire risks. For the rapid discovery of forest fires, there is a method using meteorological data obtained from local sensors installed in each area by the Meteorological Agency. Meteorological conditions (e.g., temperature, wind) influence forest fires. This study evaluated a Data Mining (DM) approach to predict the burned area of forest fires. Five DM models, e.g., Stochastic Gradient Descent (SGD), Support Vector Machines (SVM), Decision Tree (DT), Random Forests (RF), and Deep Neural Network (DNN), and four feature selection setups (using spatial, temporal, and weather attributes), were tested on recent real-world data collected from Gyeonggi-do area over the last five years. As a result of the experiment, a DNN model using only meteorological data showed the best performance. The proposed model was more effective in predicting the burned area of small forest fires, which are more frequent. This knowledge derived from the proposed prediction model is particularly useful for improving firefighting resource management.