• 한국정보과학회논문지:시스템및이론
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• 제34권5_6호
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• pp.195-201
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• 2007

트리의 최소단말경로분할이란 트리를 에지가 서로 소인 단말 노드 간 경로들로 분할하되, 가장 긴 경로의 길이를 최소화하는 문제이다. 본 논문에서는 트리의 최소단말경로분할을 $O({\mid}V{\mid}^2$시간에 구하는 알고리즘을 제시한다. 이 알고리즘은 주어진 최적화 문제를 이에 대응하는 결정 문제, 즉 최소단말경로 분할의 비용이 l 이하인지를 결정하는 문제를 이용한 이진 탐색으로 환원한다. 결정 문제는 트리를 한 차례 순회하는 동안 동적 계획법에 의해 해결된다

• 한국의류산업학회지
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• 제11권4호
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• pp.583-591
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• 2009

The purpose of this study was to examine the sportswear purchase decision factors and brand preference of college students. The subjects in this study were 614 college students who were selected by cluster random sampling from Daegu and North Gyeongsang Province. The collected data were analyzed by crosstab analysis, and the findings of the study were as follows: If a sportswear company has college students as a target market, first, the company needs to consider design and utility. Second, the company needs to expand internet sale while maintaining a strategy for centering on speciality shop and department store as for a sale of sportswear. Third, the college students themselves have a right of choice according to purchasing sportswear. Thus, a distribution company requires a direct marketing strategy targeting college students. Fourth, simple design of adding a fashion trend is needed. Fifth, the sportswear company needs to expand production and sale in jumpers and trousers based on T-shirts. Sixth, color in sportswear needs to be composed of design based on gray or black color. In order for a sportswear company to be adjusted to the global market environment here after, it requires an effort to continuously grasp consumers' trend and to apply new design and color. Also, the company will be able to be equipped with competitive edge by producing diversely functional products that are demanded by the segmented market.

• 제어로봇시스템학회논문지
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• 제8권6호
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• pp.468-476
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• 2002

The confidence of information from image processing depends on the original image quality. Enhancing the confidence by an algorithm has an essential limitation. Especially, road images are exposed to lots of noisy sources, which makes image processing difficult. We, in this paper, propose a FNN (fuzzy-neural network) capable oi deciding the quality of a road image prior to extracting lane-related information. According to the decision by the FNN, road images are classified into good or bad to extract lane-related information. A CDF (cumulative distribution function), a function of edge histogram, is utilized to construct input parameters of the FNN, it is based on the fact that the shape of the CDF and the image quality has large correlation. Input pattern vector to the FNN consists of ten parameters in which nine parameters are from the CDF and the other one is from intensity distribution of raw image. Correlation analysis shows that each parameter represents the image quality well. According to the experimental results, the proposed FNN system was quite successful. We carried out simulations with real images taken by various lighting and weather conditions and achieved about 99% successful decision-making.

• 한국멀티미디어학회논문지
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• 제15권7호
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• pp.837-846
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• 2012

본 논문에서는 안전한 웹 맵 매쉬업 서비스 구현을 위한 위성영상의 원근거리 기반의 위성영상 워터마킹 기법을 제안한다. 제안한 방법에서는 위성 영상의 위치 정보와 사용자 정보를 위성 영상의 원근거리에 따라 에지 및 색상 히스토그램 분포에 은닉한다. 따라서 사용자 요구에 의해 서비스되는 임의 해상도의 위성영상들에 대해 해당 해상도의 영상 특성에 적합한 워터마킹 기법을 수행하여 해당위성 영상을 악의적으로 수정하여 불법 유통한 유통자를 추적하고, 사용자의 사생활 보호 할 수 있다. 실험 결과 제안한 기법의 비가시성이 우수함을 확인하고, 회전, 이동 등의 기하학적 공격에도 삽입된 워터마크가 강인함을 확인한다.

• Journal of Information Processing Systems
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• 제17권4호
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• pp.721-736
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• 2021

For the mobile edge computing (MEC) system supporting dense network, a joint allocation algorithm of computing and communication resources based on reinforcement learning is proposed. The energy consumption of task execution is defined as the maximum energy consumption of each user's task execution in the system. Considering the constraints of task unloading, power allocation, transmission rate and calculation resource allocation, the problem of joint task unloading and resource allocation is modeled as a problem of maximum task execution energy consumption minimization. As a mixed integer nonlinear programming problem, it is difficult to be directly solve by traditional optimization methods. This paper uses reinforcement learning algorithm to solve this problem. Then, the Markov decision-making process and the theoretical basis of reinforcement learning are introduced to provide a theoretical basis for the algorithm simulation experiment. Based on the algorithm of reinforcement learning and joint allocation of communication resources, the joint optimization of data task unloading and power control strategy is carried out for each terminal device, and the local computing model and task unloading model are built. The simulation results show that the total task computation cost of the proposed algorithm is 5%-10% less than that of the two comparison algorithms under the same task input. At the same time, the total task computation cost of the proposed algorithm is more than 5% less than that of the two new comparison algorithms.

• 드라이브 ㆍ 컨트롤
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• 제18권2호
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• pp.20-31
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• 2021

An excavator is a construction machine that can perform various tasks such as trenching, piping, excavating, slope cutting, grading, and rock demolishing. In the 2010s, unmanned construction equipment using ICT technology was continuously developed. In this paper, the path design process was studied to implement the output data of the decision stage, and the path design algorithm was developed. For example, the output data of the decision stage were terrain data around the excavator, excavator mechanism information, excavator hydraulic information, the position and posture of the bucket at key points, the speed of the desired bucket path, and the required excavation volume. The result of the path design was the movement of the hydraulic cylinder, boom arm, bucket, and bucket edge. The core functions of the path design algorithm are the function of avoiding impact during the excavation process, the function to calculate the excavation depth that satisfies the required excavation volume, and the function that allows the bucket to pass through the main points of the excavation process while maintaining the speed of the desired path. In particular, in the process of developing the last function, the node tracking method expressed in the path design table was newly developed. The path design algorithm was verified as this path design satisfied the JCMAS H02 requirement.

• 한국항해항만학회지
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• 제46권5호
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• pp.458-470
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• 2022

As the 4th industrial revolution progresses, the application of several cutting-edge technologies such as the Internet of Things, big data, and mixed reality (MR) in relation to autonomous ships is being considered in the maritime logistics field. The aim of this study was to apply the concept of a digital twin model based on Human Machine Interaction (HMI) including a digital twin model and the role of an operator to a ship. The role of the digital twin is divided into information provision, support, decision, and implementation. The role of the operator is divided into operation, decision-making, supervision, and standby. The system constituting the ship was investigated. The digital twin system that could be applied to the ship was also investigated. The cloud-based digital twin system architecture that could apply investigated applications was divided into ship data collection (part 1), cloud system (part 2), analysis system/ application (part 3), and MR/mobile system (part 4). A Mixed Reality device HoloLens was used as an HMI equipment to perform a simulation test of a digital twin system of an 8 m battery-based electric propulsion ship.

• 한국콘텐츠학회논문지
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• 제20권2호
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• pp.1-14
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• 2020

4차 산업혁명 시대를 선도하기 위해 국가 차원에서 독창적인 연구 방향을 설정하는 전략이 요구된다. 이를 위해 기술 선도 국가들의 4차 산업혁명 관련 연구·개발 활동을 조망할 필요가 있다. 본 연구는 인공지능 등 최첨단 과학기술 정보 연구를 수행하는 미국의 정보고등연구기획국(IARPA)의 연구 프로그램들을 네트워크 분석한다. 분석 결과, IARPA의 연구 프로그램들은 정보 식별과 예측, 의사결정 그리고 사이버보안 클러스터들을 형성하며 이들 클러스터는 숨겨진 정보를 식별하고 특정한 사건을 예측하거나, 조직의 내·외부 환경 변화를 고려하여 의사결정을 지원하거나, 사이버보안을 확보하는 것에 주안점을 두고 있었다. 또한 아시아의 기술 선도 국가인 중국과 일본은 과학기술 정책 수립을 위해 IARPA 연구 프로그램들을 참고하는 것으로 나타났다. 본 연구의 결과는 4차 산업혁명 시대에 대응하기 위한 우리나라의 과학기술 정책 수립과 관련된 시사점을 제시한다.

• 한국통신학회논문지
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• 제37권5B호
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• pp.317-326
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• 2012

미래의 에너지 소비 문제를 해결하기 위하여 Green IT 에 대한 관심이 높아짐에 따라 네트워크 장치에서 발생하는 에너지 소비 문제를 해결하기 위한 연구가 활발히 진행되고 있다. 에너지 절감을 위하여 네트워크 장치는 저전력 대기 (Low Power Idle) 를 사용할 수 있다. 본 논문에서는 OBS 망에서 에너지 절감 효율을 높이기 위한 저전력 대기 적용에 관한 연구를 수행하였다. 기존의 저전력 대기와 관련된 많은 연구들은 에너지 절감을 위해 수면 시간을 최대화시키는 것에만 관심을 기울여 왔다. 그러나 장치 상태 변경 시 발생하는 상태 천이 오버헤드 (Transition overhead)는 저전력 대기의 에너지 절감율을 낮출 뿐 아니라 패킷 지연 시간을 증가시킴으로써 망의 QoS 를 하락시킬 수 있다. 따라서 본 논문에서는 저전력 대기에서 발생하는 불필요한 상태 천이 횟수를 감소시킴으로써 에너지 절감율 및 QoS 를 향상시킬 수 있는 상태 천이 결정 알고리즘 (Transition Decision algorithm)을 제안한다. 제안한 상태 천이 결정 알고리즘의 성능을 분석하기 위하여 OPNET 을 이용하여 OBS에지 라우터를 모델링하고 시뮬레이션을 수행하여 다양한 평가 지표를 기반으로 성능을 분석한다.

• STI Policy Review
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• 제8권2호
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• pp.75-93
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• 2017

Recently, global competition in the manufacturing sector is driving firms in the manufacturing sector to conduct product innovation projects to maintain their competitive edge. The key points of product innovation projects are 1) what the purpose of the project is and 2) what expected results in the target market can be achieved by implementing the innovation. Therefore, this study focuses on the performance of innovation projects with a business viewpoint. In this respect, this study proposes the "achievement rate" of product innovation projects as a measurement of project performance. Then, this study finds the best strategies from various innovation activities to optimize the achievement rate of product innovation projects. There are three major innovation activities for the projects, including three types of R&D activities: Internal, joint and external R&D, and five types of non-R&D activities - acquisition of machines, equipment and software, purchasing external knowledge, job education and training, market research and design. This study applies decision tree modeling, a kind of data-mining methodology, to explore effective innovation activities. This study employs the data from the 'Korean Innovation Survey (KIS) 2014: Manufacturing Sector.' The KIS 2014 gathered information about innovation activities in the manufacturing sector over three years (2011-2013). This study gives some practical implication for managing the activities. First, innovation activities that increased the achievement rate of product diversification projects included a combination of market research, new product design, and job training. Second, our results show that a combination of internal R&D, job training and training, and market research increases the project achievement most for the replacement of outdated products. Third, new market creation or extension of market share indicates that launching replacement products and continuously upgrading products are most important.