• 한국군사과학기술학회지
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• 제25권6호
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• pp.617-627
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• 2022

Military training is an essential item for the fundamental problem of war. However, there has always been a problem that many resources are consumed, causing spatial and environmental pollution. The concepts of defense modeling and simulation and CGF(Computer Generated Force) using computer technology began to appear to improve this problem. The Naval Operations, Resources Analysis Model(NORAM) developed by the Republic of Korea Navy is also a DEVS(Discrete Event Simulation)-based naval virtual force analysis model. The current NORAM is a battle experiment conducted by an operator, and parameter values such as maneuver and armament operation for individual objects for each situation are evaluated. In spite of our research conducted evolutionary, supervised, reinforcement learning, in this paper, we introduce our design of a scenario creation model based on evolutionary learning using genetic algorithms. For verification, the NORAM is loaded with our model to analyze wartime engagements. Human-level tactical scenario creation capability is secured by automatically generating enemy tactical scenarios for human-designed Blue Army tactical scenarios.

• 한국정보통신학회논문지
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• 제25권11호
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• pp.1670-1675
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• 2021

건설산업 영역의 스마트 건설 기술 도입이 빠르게 진행되고 있다. BIM(Building Information Modeling), 드론, 인공지능, 빅데이터, 사물인터넷 기술 등 스마트 건설 기술을 활용하여 시공 현장의 재해율을 낮추고 시공 기간을 단축시키는 효과를 가져온다. 건설 시공 현장 관리를 위한 디지털 트윈 플랫폼을 도입하기 위해서는 실제 시공 현장을 가상의 공간과 동일하게 구축하여 실시간으로 현장 관리를 가능하게 한다. 디지털 트윈 가상공간 구축방법은 시공 전주기 데이터를 수집 및 가공을 하고 3D 모델 파일을 이용하여 시각화 한다. 본 논문에서는 디지털 트윈 공간을 구성하는 3D 모델링을 3차원 공간 데이터를 기반으로 자동생성하여 효율적인 디지털 트윈 공간을 구축하는 모델링 자동화 기법을 소개한다.

• 한국전기전자재료학회논문지
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• 제35권6호
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• pp.556-561
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• 2022

밀도범함수이론(density functional theory, DFT)이 등장한 이래로, 이를 재료과학에 적용하여 에너지 재료 및 반도체와 같은 전자재료들의 연구개발에 활발하게 활용되고 있다. 하지만 DFT 계산 프로그램을 실행할 때 필요한 입력 파일 생성 시 여러 가지 소재들에 대해 동일한 계산 조건을 맞춰 주고 파라미터들을 알맞게 설정해 줘야 올바른 계산 결과 비교가 가능한데, 이런 부분들에 대해 진입 장벽이 높다는 어려움이 있다. 이에 본 논문에서는 Python Materials Genomics (pymatgen) 파이썬 패키지를 이용해 분자 및 결정구조를 다루고 널리 사용되는 DFT 계산 프로그램인 Vienna Ab initio Simulation Package (VASP) 및 Gaussian 입력 파일 생성에 대해 소개하고자 한다. 이를 통해 해당 프로그램에 대한 전문적인 지식이 많지 않더라도 보다 일관적인 계산 조건에서 결과들을 손쉽게 수행할 수 있게 되기를 기대한다.

• 한국항해항만학회지
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• 제47권2호
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• pp.75-84
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• 2023

Ships need to ensure safety during their navigation, which makes route determination highly important. It must be accompanied by a route following controller that can accurately follow the route. This study proposes a method for automatically generating the ship route based on deep reinforcement learning algorithm and following it using a route following controller. To generate a ship route, under keel clearance was applied to secure the ship's safety and navigation chart information was used to apply ship navigation related regulations. For the experiment, a target ship with a draft of 8.23 m was designated. The target route in this study was to depart from Busan port and arrive at the pilot boarding place of the Ulsan port. As a route following controller, a velocity type fuzzy P ID controller that could compensate for the limitation of a linear controller was applied. As a result of using the deep Q network, a route with a total distance of 62.22 km and 81 waypoints was generated. To simplify the route, the Douglas-Peucker algorithm was introduced to reduce the total distance to 55.67 m and the number of way points to 3. After that, an experiment was conducted to follow the path generated by the target ship. Experiment results revealed that the velocity type fuzzy P ID controller had less overshoot and fast settling time. In addition, it had the advantage of reducing the energy loss of the ship because the change in rudder angle was smooth. This study can be used as a basic study of route automatic generation. It suggests a method of combining ship route generation with the route following control.

• 대한방사성의약품학회지
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• 제8권2호
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• pp.95-101
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• 2022

Microfluidic radioimmunoassay (RIA) platform called µ-RIA spends less reagent and shorter reaction time for the analysis compared to the conventional tube-based radioimmunoassay. This study reported the design of µ-RIA chips optimized for the gamma counter which could measure the small samples of radioactive materials automatically. Compared with the previous study, the µ-RIA chips developed in this study were designed to be compatible with conventional RIA test tubes. And, the automatic gamma counter could detect radioactivity from the ¹²⁵I labeled anti-PSA attached to the chips. Effects of the multi-layer microchannels and two-phase flow in the µ-RIA chips were investigated in this study. The measured radioactivity from the ¹²⁵I labeled anti-PSA was linearly proportional to the number of stacked chips, representing that the radioactivity in µ-RIA platform could be amplified by designing the chips with multi-layers. In addition, we designed µ-RIA chip to generate liquid-gas plug flow inside the microfluidic channel. The plug flow can promote binding of the biomolecules onto the microfluidic channel surface with recirculation in the liquid phase. The ratio of liquid slug and air slug length was 1 : 1 when the ¹²⁵I labeled anti-PSA and the air were injected at 1 and 35 µL/min, respectively, exhibiting 1.6 times higher biomolecule attachment compared to the microfluidic chip without the air injection. This experimental result indicated that the biomolecular reaction was improved by generating liquid-gas slugs inside the microfluidic channel. In this study, we presented a novel µ-RIA chips that is compatible with the conventional gamma counter with automated sampler. Therefore, high-throughput radioimmunoassay can be carried out by the automatic measurement of radioactivity with reduced radiowaste generation. We expect the µ-RIA platform can successfully replace conventional tube-based radioimmunoassay in the future.

• 스마트미디어저널
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• 제11권2호
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• pp.18-24
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• 2022

많은 소셜 서비스 상에서 악성 댓글로 인한 문제가 발생되고 있으며, 특히 매체로서의 성격이 강한 유튜브는 모바일기기를 이용한 쉬운 접근성으로 인해 악성 댓글로 인한 폐해가 더욱 커지고 있는 실정이다. 본 논문에서는 LSTM 기반의 자연어 처리를 통해 유튜브 콘텐츠에 대한 악성 댓글을 판별하고 악성 댓글의 비율, 악플러들의 닉네임, 그리고 빈도를 시각적으로 표현해 주기 위한 유튜브 악성 댓글 탐지 시스템을 설계하고 구현하였으며, 성능을 평가하였다. 약 5만 개의 댓글 데이터셋을 통해 악성 댓글 여부를 판별하였을 때, 약 92%의 정확도로 악성 댓글을 검출해 낼 수 있었으며, 이를 활용하여 악성 댓글의 통계가 자동으로 생성되도록 함으로써 많은 유튜버들이 겪는 악성 댓글로 인한 사회적 문제를 해결할 수 있을 것으로 기대한다.

• 해양환경안전학회지
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• 제29권3호
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• pp.281-287
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• 2023

Establishing a ship's passage plan is an essential step before it starts to sail. The research related to the automatic generation of ship passage plans is attracting attention because of the development of maritime autonomous surface ships. In coastal water navigation, the land, islands, and navigation rules need to be considered. From the path planning algorithm's perspective, a ship's passage planning is a global path-planning problem. Because conventional global path-planning methods such as Dijkstra and A^* are time-consuming owing to the processes such as environmental modeling, it is difficult to modify a ship's passage plan during a voyage. Therefore, the D^* algorithm was used to address these problems. The starting point was near Busan New Port, and the destination was Ulsan Port. The navigable area was designated based on a combination of the ship trajectory data and grid in the target area. The initial path plan generated using the D^* algorithm was analyzed with 33 waypoints and a total distance of 113.946 km. The final path plan was simplified using the Douglas-Peucker algorithm. It was analyzed with a total distance of 110.156 km and 10 waypoints. This is approximately 3.05% less than the total distance of the initial passage plan of the ship. This study demonstrated the feasibility of automatically generating a path plan in coastal navigation for maritime autonomous surface ships using the D^* algorithm. Using the shortest distance-based path planning algorithm, the ship's fuel consumption and sailing time can be minimized.

• 한국정보통신학회:학술대회논문집
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• 한국정보통신학회 2021년도 추계학술대회
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• pp.281-283
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• 2021

국내 OTT(Over-the-top media service) 시장의 추천 서비스에서 거론되는 대표 업체는 Youtube와 Netflix이다. Youtube는 여러 방법을 거쳐 2016년부터 이용자의 시청 시간을 기록하여 이용하는 알고리즘을 머신러닝에 도입하면서 개인화된 추천을 본격화하였고, Netflix는 사용자의 선택한 영상, 시청 시간대, 영상 시청 기기 등 정보 수집을 통해 이용자를 분류하고 비슷한 시청 패턴을 가진 사람들을 같은 그룹에 묶는 방식과 영상을 직접 시청 후 사람이 태그(메타데이터)를 직접 기록하여 사용자로부터 수집한 정보와 영상에 붙은 태그 정보를 이용한다. 본 논문에서는 수기로 작성하던 영상 미디어의 메타데이터를 자동으로 생성하여 영상미디어의 추천을 개선하기 위한 방법을 제안하고자 한다.

• 대한토목학회논문집
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• 제26권3D호
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• pp.511-517
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• 2006

본 논문은 우리나라 민 군 겸용 비행장의 고도제한의 기준이 되는 군용항공기지법을 중심으로 비행안전구역을 분석하기 위한 방법을 연구하여 개발사업 시행시에 제한 지역을 분석할 수 있는 효과적인 방법을 제시하고 최근 대두되고 있는 비행장 주변지역의 고도제한에 따른 문제 해결에 도움을 주고자 한다. 이를 위해서 지리정보체계(GIS) 기법을 활용하여 항공기 지법에서 규정하고 있는 비행안전구역의 3차원 모형을 효과적으로 생성하기 위한 방법을 제시하고, 비행안전구역 내에서 자연지형 및 인공지물로 인한 장애지역과 대상을 자동으로 식별하기 위한 기법을 제시하였다. 제시한 방법을 실제적으로 적용해보기 위하여 실험지역으로 선정한 비행장에 대하여 상용의 수치지도 자료와 위성영상을 기반으로 지형공간정보를 생성하기 위한 단계적인 방법을 제시하였으며 실험지역 비행장의 비행안전구역 모형을 생성하고, 장애지역과 대상을 식별하여 비행장 비행안전구역 분석을 위한 통합 모형을 가시화함으로써 제시한 방법들의 활용성을 보였다.

• 국제학술발표논문집
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• The 5th International Conference on Construction Engineering and Project Management
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• pp.279-286
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• 2013

This paper introduces a new method for identification of building energy performance problems. The presented method is based on automated analysis and visualization of deviations between actual and expected energy performance of the building using EPAR (Energy Performance Augmented Reality) models. For generating EPAR models, during building inspections, energy auditors collect a large number of digital and thermal imagery using a consumer-level single thermal camera that has a built-in digital lens. Based on a pipeline of image-based 3D reconstruction algorithms built on GPU and multi-core CPU architecture, 3D geometrical and thermal point cloud models of the building under inspection are automatically generated and integrated. Then, the resulting actual 3D spatio-thermal model and the expected energy performance model simulated using computational fluid dynamics (CFD) analysis are superimposed within an augmented reality environment. Based on the resulting EPAR models which jointly visualize the actual and expected energy performance of the building under inspection, two new algorithms are introduced for quick and reliable identification of potential performance problems: 1) 3D thermal mesh modeling using k-d trees and nearest neighbor searching to automate calculation of temperature deviations; and 2) automated visualization of performance deviations using a metaphor based on traffic light colors. The proposed EPAR v2.0 modeling method is validated on several interior locations of a residential building and an instructional facility. Our empirical observations show that the automated energy performance analysis using EPAR models enables performance deviations to be rapidly and accurately identified. The visualization of performance deviations in 3D enables auditors to easily identify potential building performance problems. Rather than manually analyzing thermal imagery, auditors can focus on other important tasks such as evaluating possible remedial alternatives.