• Transactions of the Korean Society of Mechanical Engineers B
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• v.36 no.2
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• pp.125-130
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• 2012

The nematode Caenorhabditis elegans is a widely used model organism in biological research. Thanks to the availability of well-established knowledge about its neural connectivity, a wide range of studies have been attempted to uncover the relationship between behaviors and the responsible neurons. In our research, the adaptive behavior of C. elegans in solid environments with different surface rigidities is investigated, where the worm adapts to different mechanical stiffnesses by modulating its crawling waveform. The amplitude and wavelength of the crawling waveform decrease as the environment becomes more rigid. Interestingly, the mechanosensation-defective mutant shows different responses to the surface rigidity compared to those of the wild-type worm. To explain the adaptation process in mechanically different environments, we suggest a plausible neural circuit model.

• Journal of the Korea Computer Graphics Society
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• v.18 no.1
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• pp.29-34
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• 2012

High-quality tetrahedral meshes are crucial for FEM-based simulation of large elasto-plastic deformation and tetrahedral-mesh-based simulation of fluid flow. This paper proposes a volume meshing method that exploits an octree-based adaptive signed distance field to fill the inside of a polygonal object with tetrahedra, of which dihedral angles are good. The suggested method utilizes an octree structure to reduce the total number of tetrahedra by space-efficiently filling an object with graded tetrahedra. To obtain a high-quality mesh with good dihedral angles, we restrict the octree in such a way that any pair of neighboring cells only differs by one level. In octree-based tetrahedral meshing, the signed distance computation of a point to the surface of a given object is a very important and frequently-called operation. To accelerate this operation, we develop a method that computes a signed distance field directly on the vertices of the octree cells while constructing the octree using a top-down approach. This is the main focus of the paper. The suggested tetrahedral meshing method is fast, stable and easy to implement.

• Proceedings of the Korea Water Resources Association Conference
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• 2021.06a
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• pp.157-157
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• 2021

2015년 파리에서 체결된 파리협정은 1850년 대비 2100년까지의 지구 평균기온 상승을 1.5℃ 이내로 제한하기 위해 5년마다 참여국에 상향된 온실가스 배출 감축 목표를 제출하게 하고, 탄소 배출 및 온도상승 저감 목표 달성을 위해 도시 내 그린인프라를 적극적으로 도입하는 등 국제사회 공동의 종합적인 이행을 예정하고 있다. 그린인프라의 유형 중 하나인 옥상녹화(Green Roof)는 기후변화 적응을 위한 도시 인프라 구축 방법의 하나로 국내에서도 많은 각광을 받고 있다. 옥상녹화(Green Roof)는 도시의 불투수층인 지붕 면적을 모두 혹은 일부 식생으로 덮어 표면층에 추가의 투수층을 조성하는 것을 지칭한다. 옥상녹화의 경우 별도의 토지면적 확보가 필요하지 않고 기존의 시설물에 추가적인 설치가 가능해 여분의 토지가 부족한 도심지의 녹지 확보를 위한 친환경적인 그린인프라로 각광받고 있다. 현재까지 옥상녹화(Green Roof) 관련 국내 연구 현황은 '옥상 녹화의 공법'을 다룬 비율이 높고 실증적인 결과를 가진 선행연구가 거의 없다. 따라서 본 연구는 동일한 조건하에 4개의 실험동을 설치하고 동질성 검사를 한 후 옥상에 설치된 재료[일반 콘크리트(Bare Concrete), 고반사 도장(High Reflective Paint), 사사(Short Bamboo), 잔디(Grass)]에 따른 건물 내 온도 변화 저감효과에 대한 분석을 수행하였다. 2020년 8월 17일부터 22일까지 측정된 지붕 표면 평균 최고온도 모니터링 결과를 일반 콘크리트 지붕과 비교했을 때. 고반사 도장 지붕의 경우 8.26℃, 옥상녹화(사사, short bamboo) 지붕의 경우 7.21℃, 옥상녹화(잔디, grass)의 경우 10.8℃ 낮은 것으로 측정되었다. 또한 실내 천정 표면 평균 온도의 경우 콘크리트 지붕과 비교하여 고반사 도장 지붕은 6.46℃, 옥상녹화(사사, short bamboo) 지붕은 13.52℃, 옥상녹화(잔디, grass)는 13.3℃ 낮은 것으로 나타났다. 본 연구결과는 옥상녹화의 온도저감 효과를 정량적으로 제시하고 있어, 향후 기후변화 대응 및 적응 전략적 수립에 기여할 수 있을 것으로 판단된다.

• Journal of the Korean Institute of Gas
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• v.4 no.1 s.9
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• pp.49-54
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• 2000

The DCPD(Direct Current Potential Drop) method has been adopted for the crack measurement of a structure. The objective of this paper is to develop a multi-channel DCPD system not only for detecting crack depth, but also for determining the accurate shape of the surface crack. For this purpose, an exclusive software was also developed. In order to verify the developed DCPD system it was initially tested on a CT specimen, and subsequently was applied to a wide plate specimen. The developed multi-channel DCPD system was proven to provide an efficient and accurate measurement of a surface crack during the crack growth.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.44 no.6
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• pp.537-543
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• 2016

A new approach to systematically model aerodynamic coefficients using an adaptive sampling based wind tunnel testing considering cost is proposed. The Latin Hypercube design is used for selecting initial test points. The Gaussian Process (GP) is iteratively used during the experiment to determine additional experimental points that minimizes the uncertainty reduction per incremental cost. A numerical simulation based experiment was conducted using the static aerodynamic coefficient database a fighter aircraft, which demonstrated the validity of the proposed method.

• Journal of the Institute of Convergence Signal Processing
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• v.23 no.4
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• pp.185-193
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• 2022

This paper proposes an adaptive sliding mode control with radial basis function neural network(RBFNN) scheme to enhance the performance of position and attitude tracking control of quadrotor UAV. The RBFNN is utilized on the approximation of nonlinear function in the UAV dynmic model and the weights of the RBFNN are adjusted online according to adaptive law from the Lyapunov stability analysis to ensure the state hitting the sliding surface and sliding along it. In order to compensate the network approximation error and eliminate the existing chattering problems, the sliding mode control term is adjusted by adaptive laws, which can enhance the robust performance of the system. The simulation results of the proposed control method confirm the effectiveness of the proposed controller which applied for a nonlinear quadrotor UAV is presented. Form the results, it's shown that the developed control system is achieved satisfactory control performance and robustness.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.13 no.6
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• pp.109-114
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• 2013

The biological active points (BAP) are known as low resistance spots or good electro-permeable points. In this paper, a new method for BAP detection using the bio-impedance measurement system based on the adaptive frequency tracking filter (AFTF) and the transition event detector is presented. Also, the microcontroller process continuous time demodulation of the modulated signal by multi frequency components using the AFTF. The transition event detector based on the phase space method is applied about each frequency using the BAP equivalent model which is proposed.

• Proceedings of the KWS Conference
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• 2009.11a
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• pp.10-10
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• 2009

파이프 용접은 중력의 영향으로 인하여 위치에 따라 같은 용접변수라도 비드 형상이 매우 달라 지게 된다. 또한 지금까지 많은 용접 기술자들이 위험하고 까다로운 환경에서 수작업으로 용접을 실행하였다. 따라서 이러한 이유로 용접 자동화 공정이 반드시 필요하게 된다. 본 연구에서는 FCAW를 사용하여 파이프 모재 대신 필릿 평판을 아래보기, 위보기 자세를 포함하여 9개 자세에서 실행하였다. 용접 자세를 비롯한 용접 변수와 비드 형상 변수간의 관계를 비선형 회귀 분석과 구간적 3차 에르미트 보간법을 이용하여 주어진 용접 변수에서의 비드 단면의 형상을 예측하고, 비드의 결함 유무를 파악하였다. 이러한 방법을 통하여 자세에 따라서 용접 결함이 없는 용접 변수를 구할 수 있었다. 시각센서를 이용하여 용접 후 비드 형상에 대해 모니터링을 실시하였다. 모니터링의 알고리즘은 영상획득, 이진화, 세선화, 적응형 미디언 필터링, 적응형 허프 변환, 용접 결함 검출의 순서로 구성되어 있으며, 본 연구에서는 보다 빠른 영상처리를 위하여 적응형 미디언 필터링을 제시하였다. 모니터링을 통하여 2차원 비드 단면뿐만 아니라, 디루니 삼각법을 적용하여 3차원으로 비드 표면을 표현할 수 있다. 보간법을 사용하여 얻은 비드 형상과 시각 센서를 통하여 얻은 비드 형상간의 비교를 통하여 본 연구의 적합성 여부를 확인하였다.

• Journal of the Korean Institute of Intelligent Systems
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• v.22 no.2
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• pp.174-180
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• 2012

This paper proposes a decentralized adaptive output-feedback controller design for nonlinear interconnected systems with unknown time delays. The interaction terms with unknown delays are related to all states of subsystems. The time-delayed functions are compensated by using appropriate Lyapunov-Krasovskii functionals and function approximation technique. The observer dynamic surface design technique is employed to design the proposed memoryless local controller for each subsystem. In addition, we prove that all signals in the closed-loop system are semiglobally uniformly bounded and control errors converge to an adjustable neighborhood of the origin.

• Transactions of the Korean Society of Mechanical Engineers
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• v.19 no.3
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• pp.713-723
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• 1995

In intelligent machine tools, a computer based control system, which can adapt the machining parameters in an optimal fashion based on sensor measurements of the machining process, should be incorporated. In this paper, the technology for adaptively optimizing the cutting conditions to maximize the material removal rate in face milling operations is proposed using the exterior penalty function method combined with multilayered neural networks. Two neural networks are introduced ; one for estimating tool were length, the other for mapping input and output relations from experimental data. Then, the optimization of cutting conditions is adaptively implemented using tool were information and predicted process output. The results are demonstrated with respect to each level of machining such as rough, fine and finish cutting.