• International Journal of Naval Architecture and Ocean Engineering
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• 제9권6호
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• pp.613-623
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• 2017

A semi-empirical model to predict ship resistance in level ice based on Lindqvist's model is presented. This model assumes that contact between the ship and the ice is a case of symmetrical collision, and two contact cases are considered. Submersion force is calculated via Lindqvist's formula, and the crushing and breaking forces are determined by a concept of energy consideration during ship and ice impact. The effect of the contact coefficient is analyzed in the ice resistance prediction. To validate this model, the predicted results are compared with model test data of USCGC Healy and icebreaker Araon, and full-scale data of the icebreaker KV Svalbard. A relatively good agreement is achieved. As a result, the presented model is recommended for preliminary total resistance prediction in advance of the evaluation of the icebreaking performance of vessels.

• 소성∙가공
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• 제25권2호
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• pp.124-129
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• 2016

Recently, global railway car makers are competing desperately in developing high-speed railway vehicles. Ensuring passenger safety during a crash is essential. The design and the manufacturing of energy absorbing components are becoming more and more important. A deformation tube is a typical passive energy absorbing component for railway cars. In the current study the slab method was used to predict the energy absorbing capability of a deformation tube during the early design stage. The usefulness of the prediction method is verified through the comparisons between the results of FE simulations and those of the prediction method.

• Journal of Communications and Networks
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• 제16권2호
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• pp.209-216
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• 2014

Cognitive radio (CR) has been proposed to solve the spectrum utilization problem by dynamically exploiting the unused spectrum. In CR networks, a spectrum selection scheme is an important process to efficiently exploit the spectrum holes, and an efficient channel allocation scheme must be designed to minimize interference to the primary network as well as to achieve better spectrum utilization. In this paper, we propose a multichannel selection algorithm that uses spectrum hole prediction to limit the interference to the primary network and to exploit channel characteristics in order to enhance channel utilization. The proposed scheme considers both the interference length and the channel capacity to limit the interference to primary users and to enhance system performance. By using the proposed scheme, channel utilization is improved whereas the system limits the collision rate of the CR packets.

• 로봇학회논문지
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• 제13권2호
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• pp.121-128
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• 2018

Obstacle avoidance is one of the most important parts of autonomous mobile robot. In this study, we proposed safe and efficient local path planning of robot for obstacle avoidance. The proposed method detects and tracks obstacles using the 3D depth information of an RGB-D sensor for path prediction. Based on the tracked information of obstacles, the paths of the obstacles are predicted with probability circle-based spatial search (PCSS) method and Gaussian modeling is performed to reduce uncertainty and to create the cost function of caution. The possibility of collision with the robot is considered through the predicted path of the obstacles, and a local path is generated. This enables safe and efficient navigation of the robot. The results in various experiments show that the proposed method enables robots to navigate safely and effectively.

• 한국지능시스템학회:학술대회논문집
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• 한국퍼지및지능시스템학회 2002년도 춘계학술대회 및 임시총회
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• pp.47-50
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• 2002

산업이 발달함에 따라 대량의 화물을 빠르게 운반할 수 있는 해상운송수단의 수요가 증가하게 되고 이로 인하여 해상 선박 간 충돌사고가 빈번히 발생하게 되었다 선박 충돌은 주로 조선하는 사람들의 관습, 습관의 차이, 부주의, 판단오류 등의 이유로 발생한다. 연구자들은 선박 충돌을 방지하기 위하여 조선에 관련된 많은 부분을 지능화한 지능형 충돌회피시스템 개발에 노력을 기울이고 있다. 선박을 비롯한 자율운동체의 충돌방지 기법은 비행체, 수중운동체, 자율로봇 등 영역 특성을 달리하는 다양한 분야에서 연구되어오고 있다 기존 연구들의 충돌방지는 주로 장애물의 공간적 특성에 기반하고 있다. 이에 개체의 움직임을 예측하여 시간적 요소를 가미하면 더욱 향상된 충돌방지가 가능하다. 특히, 선박은 느린 운동 특성과 조선법, 규격화된 통신수단의 발달로 인하여 상대편 선박의 이동 예측이 용이하므로 이를 적용하여 보다 향상된 충돌방지가 가능하다. 본 연구에서는 기존의 충돌회피기법의 과정에 예측을 추가한 예측기반 충돌회피모형을 제안하고 선박운항환경을 모의실험에 의하여 해당 모형 적용시 충돌회피 경로 산출의 안전성이 크게 개선됨을 보인다.

• 한국항해항만학회:학술대회논문집
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• 한국항해항만학회 2014년도 춘계학술대회
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• pp.36-37
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• 2014

It is necessary to develop highly sophisticated Modeling & Simulation (M&S) system for the scientific investigation of marine accident causes and for the systematic reproduction of accidental damage procedure. To ensure an accurate and reasonable prediction of marine accidental causes, such as collision, grounding and flooding, full-scale ship M&S simulations would be the best approach using hydrocode, such as LS-DYNA code, with its Fluid-Structure Interaction (FSI) analysis technique. The objectivity of this paper is to present three full-scale ship collision, grounding and flooding simulation results of marine accidents, and to show the possibility of the scientific investigation of marine accident causes using highly sophisticated M&S system.

• 한국자동차공학회논문집
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• 제20권1호
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• pp.39-45
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• 2012

In the standard CFD code, Lagrangian-Eulerian method is very popular to simulate the liquid spray penetrating into gaseous phase. Though this method can give a simple solution and low computational cost, it have been reported that the Lagrangian spray models have numerical grid dependency, resulting in serious numerical errors. Many researches have shown the grid dependency arise from two sources. The first is due to unaccurate prediction of the droplet-gas relative velocity, and the second is that the probability of binary droplet collision is dependent on the grid resolution. In order to solve the grid dependency problem, the improved spray models are implemented in the KIVA-3V code in this study. For reducing the errors in predicting the relative velocity, the momentum gain from the gaseous phase to liquid particles were resolved according to the gas-jet theory. In addition, the advanced algorithm of the droplet collision modeling which surmounts the grid dependency problem was applied. Then, in order to validate the improved spray model, the computation is compared to the experimental results. By simultaneously regarding the momentum coupling and the droplet collision modeling, successful reduction of the numerical grid dependency could be accomplished in the simulation of the high-pressure injection diesel spray.

• 대한한의학원전학회지
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• 제32권2호
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• pp.17-31
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• 2019

Objectives : Understanding the Ten Stems and Twelve Branches is necessary to grasp the laws of change in Heaven and Earth. Methods : Based on relevant contents in East Asian classics, the Yin Yang, Sibling Wuxing, Husband-Wife Wuxing combinations as well as Mutual Collision and Zangfu combination were examined. Results & Conclusion : Yin Yang combination of the Ten Stems are divided according to odd/evenness. The Sibling Wuxing combination is categorized according to one life cycle of vegetation, resulting in Jia Yi Wood, Bing Ding Fire, Wu Ji Earth, Geng Xin Metal, Ren Gui Water. The Husband-Wife Wuxing combination of the Ten Stems are Jia Ji Earth, Yi Geng Metal, Bing Xin Water, Ding Ren Wood, Wu Gui Fire, which corresponds to the principles of the Duihuazuoyong Theory. Within the Husband-Wife Wuxing combination lies three principles which are Yin Yang combination, Mutual Restraining combination, and the Yang Stem restraining the Yin Stem. The Mutual Collision of the Ten Stems are Jia and Geng, Yi and Xin, Ren and Bing, Gui and Ding against each other. In matching Zangfu to the Ten Stems, Jia matches with Gallbladder, Yi matches with Liver; Bing matches with Small Intestine, Ding matches with Heart; Wu matches with Stomach, Ji matches with Spleen; Geng matches with Large Intestine, Xin matches with Lung; Ren matches with Bladder, Gui matches with Kidney. : When the adjacent vectors are extracted, the count-based word embedding method derives the main herbs that are frequently used in conjunction with each other. On the other hand, in the prediction-based word embedding method, the synonyms of the herbs were derived.

• 정보처리학회논문지:소프트웨어 및 데이터공학
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• 제10권12호
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• pp.561-568
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• 2021

최근 자율주행에 관한 기술은 고부가가치 신기술로서 주목받고 있으며 활발히 연구가 진행되고 있는 분야이다. 상용화 가능한 자율주행을 위해서는 실시간으로 정확하게 진입하는 객체를 탐지하고 이동속도를 추정해야 한다. CNN(Convolutional Neural Network) 기반 딥러닝 알고리즘과 밀집광학흐름(Dense Optical Flow)을 사용하는 기존 방식은 실행 속도가 느려 실시간으로 객체를 탐지하고 이동속도를 추정하기에는 한계가 존재한다. 본 논문에서는 트램에 설치된 카메라를 통해 획득된 주행영상에서 딥러닝 알고리즘인 YOLOv5 알고리즘을 활용하여 실시간으로 객체를 탐지를 수행하고, 탐지된 객체영역에서 기존의 밀집광학흐름(Dense Optical Flow) 대신 연산량을 개선한 부분 밀집광학흐름(Local Dense Optical Flow)을 사용하여 객체의 진행 방향과 속력을 빠르게 추정하는 방식을 제안한다. 이를 바탕으로 충돌 시간과 충돌 지점을 예측할 수 있는 모델을 설계하였으며, 이를 통해 트램(Tram)의 주행 중 전방 충돌사고를 방지할 수 있는 시스템에 적용하고자 한다.

• 한국컴퓨터정보학회논문지
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• 제27권8호
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• pp.61-68
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• 2022

본 논문에서는 딥러닝 모델 기반 보행자의 GPS 경로를 예측하는 시스템을 제안한다. 보행자 경로 예측은 보행자의 위험 및 충돌 상황들을 알림을 통해 방지할 수 있으며, 다양한 마케팅 등 비즈니스 면에서도 영향을 끼치는 연구이다. 또한 보행자 뿐 아니라 많은 각광을 받고 있는 무인 이동수단의 경로 예측에도 활용될 수 있다. 다양한 경로 예측 방식들 중 본 논문은 GPS 데이터를 활용하여 경로를 예측하는 연구이다. 시계열 데이터인 보행자의 GPS 경로를 학습하여 다음 경로를 예측하도록 하는 딥러닝 모델 기반 연구이다. 본 논문에서는 보행자의 GPS 경로를 딥러닝 모델이 학습할 수 있도록하는 데이터 셋 구성 방식을 제시하였으며, 예측 범위에 큰 제약이 없는 경로 예측 딥러닝 모델을 제안한다. 본 연구의 경로 예측 딥러닝 모델에 적합한 파라메터들을 제시하였으며, 우수한 예측 성능을 보이는 결과를 제시한다.