• Structural Engineering and Mechanics
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• 제41권1호
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• pp.113-137
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• 2012

Frame structures with viscoelastic (VE) dampers mounted on them are considered in this paper. It is the aim of this paper to compare the dynamic characteristics of frame structures with VE dampers when the dampers are modelled by means of different models. The classical rheological models, the model with the fractional order derivative, and the complex modulus model are used. A relatively large structure with VE dampers is considered in order to make the results of comparison more representative. The formulae for dissipation energy are derived. The finite element method is used to derive the equations of motion of the structure with dampers and such equations are written in terms of both physical and state-space variables. The solution to motion equations in the frequency domain is given and the dynamic properties of the structure with VE dampers are determined as a solution to the appropriately defined eigenvalue problem. Several conclusions concerning the applicability of a family of models of VE dampers are formulated on the basis of results of an extensive numerical analysis.

• 한국마린엔지니어링학회:학술대회논문집
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• 한국마린엔지니어링학회 2001년도 춘계학술대회 논문집
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• pp.40-45
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• 2001

Recently, the use of numerical simulation has been increased rapidly because of the development of high performance computer systems. The present study is aimed to investigate flow characteristics of a two-dimensional sharp plane. Unsteady calculation by FDM(Finite Difference Method) based upon SOLA scheme which was performed at $Re=2{\times}10^4$in viscous incompressible flow within a finite domain on the irregular grid formation. Total numbers of irregular grids are $8{\times}10^4$. The minimum grid size is 1/100 of the plane length L which is the representative length. The inclined angles of every objects are $15^{\circ}, \;30^{\circ}\;and\; 45^{\circ}.$ And, the edge angle of the plane is $30^{\circ}.$ This study discussed the flow characteristics in term of the turbulent intensity, vorticity and frequency analysis. Developed flows show that the periodic Karman vortices occur at the back of the plane.

• 한국컴퓨터정보학회논문지
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• 제13권7호
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• pp.247-256
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• 2008

본 연구에서는 웹 문서에서의 단순 키워드 매칭으로 검색하는 전자상거래시스템의 문제점을 해결하기 위한 방안으로 도메인 온톨로지를 자동으로 생성하고 이를 기반으로 지능형 에이전트기술을 접목함으로서 의사소통이 단일화된 상품검색시스템을 개발한다. 온톨로지 개발은 국제상품분류코드(UNSPSC)와 귀금속 보석 사이트들의 분류정보를 기반으로 대표용어를 추출하고 유사관계 시소러스 적용하여 표준화된 온톨로지를 구축하며 지능형에이전트 기술을 검색 단계에서 접목시켜 사용자에게 정보수집의 효율성을 지원하도록 시맨틱 웹을 지원하는 상거래 시스템을 설계하고 구현한다. 또한 개인화된 검색 환경을 지원하기 위해 사용자 프로파일을 설계하고, 개인화 검색 에이전트와 추론기능을 이용한 검색 환경을 제공함으로서 정보수집의 신속성과 정확한 정보검색이 가능하도록 지원한다.

• 한국통신학회논문지
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• 제38A권4호
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• pp.310-317
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• 2013

본 논문에서는 실시간 위치 추적 시스템 (RTLS: real-time locating system)을 위한 ESPRIT 기반의 초 분해능 지연 시간 추정 (super-resolution time delay estimation) 알고리즘을 개발하고 여러 가지 다중 경로 환경에서 성능을 분석한다. 지연 시간 추정을 위한 기존의 코릴레이션 방식은 다중 경로들의 지연 시간의 차이가 한 칩 이내일 경우 성능이 급격히 저하되는 문제점이 있다. 이러한 문제를 해결하기 위해 대표적인 초 분해능 도래각 추정 알고리즘인 ESPRIT을 지연 시간 추정에 적용하여 주파수 영역 초 분해능 지연 시간 추정 알고리즘을 개발하고 여러 가지 다중 경로 환경에서 알고리즘의 성능을 분석한다.

• Earthquakes and Structures
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• 제9권2호
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• pp.321-337
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• 2015

Existing building structures can easily present material mechanical properties which can largely vary even within a single structure. The current European Technical Code, Eurocode 8, does not provide specific instructions to account for high variability in mechanical properties. As a consequence of the high strength variability, at the occurrence of seismic events, the structure may evidence unexpected phenomena, like torsional effects, with larger experienced deformations and, in turn, with reduced seismic performance. This work is focused on the reduction in seismic performance due to the concrete strength variability. The analysis has been performed on a case-study, i.e., a 3D RC framed 4 storey building. A Normal distribution, compatible to a large available database, has been taken to represent the concrete strength domain. Different plan layouts, representative of realistic strength distributions, have been considered, and a statistical analysis has been performed on the induced reduction in seismic performance. The obtained results have been compared to the standard analysis as provided by Eurocode 8 for existing buildings. The comparison has shown that the Eurocode 8 provisions are not conservative for existing buildings having a large variability in concrete strength.

• 방송공학회논문지
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• 제24권3호
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• pp.420-429
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• 2019

최근 CNN (Convolutional Neural Network) 기반의 화질 개선 기술이 H.265/HEVC와 같은 블록 기반 영상 압축 표준을 사용하여 압축된 영상의 화질을 향상시키는 데 적극적으로 사용되어 왔다. 이 논문은 이러한 영상 압축 기술을 위한 화질 개선 연구의 추세를 요약하고 분석하는 것을 목표로 한다. 먼저, 화질 개선을 위한 CNN의 구성 요소를 살펴보고 이미지 도메인에서의 사전 연구를 요약한다. 다음으로 네트워크 구조, 데이터셋 및 학습 방법의 세 가지 측면에서 관련 연구들을 정리하고 성능 비교를 위한 구현 및 실험결과를 제시하고자 한다.

• Clinical and Experimental Pediatrics
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• 제65권5호
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• pp.239-249
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• 2022

Cells survive and proliferate through complex interactions among diverse molecules across multiomics layers. Conventional experimental approaches for identifying these interactions have built a firm foundation for molecular biology, but their scalability is gradually becoming inadequate compared to the rapid accumulation of multiomics data measured by high-throughput technologies. Therefore, the need for data-driven computational modeling of interactions within cells has been highlighted in recent years. The complexity of multiomics interactions is primarily due to their nonlinearity. That is, their accurate modeling requires intricate conditional dependencies, synergies, or antagonisms between considered genes or proteins, which retard experimental validations. Artificial intelligence (AI) technologies, including deep learning models, are optimal choices for handling complex nonlinear relationships between features that are scalable and produce large amounts of data. Thus, they have great potential for modeling multiomics interactions. Although there exist many AI-driven models for computational biology applications, relatively few explicitly incorporate the prior knowledge within model architectures or training procedures. Such guidance of models by domain knowledge will greatly reduce the amount of data needed to train models and constrain their vast expressive powers to focus on the biologically relevant space. Therefore, it can enhance a model's interpretability, reduce spurious interactions, and prove its validity and utility. Thus, to facilitate further development of knowledge-guided AI technologies for the modeling of multiomics interactions, here we review representative bioinformatics applications of deep learning models for multiomics interactions developed to date by categorizing them by guidance mode.

• Wind and Structures
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• 제35권2호
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• pp.131-146
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• 2022

Tornadic wind flow is inherently turbulent. A turbulent wind flow is characterized by fluctuation of the velocity in the flow field with time, and it is a dynamic process that consists of eddy formation, eddy transportation, and eddy dissipation due to viscosity. Properly modeling turbulence significantly increases the accuracy of numerical simulations. The lack of a clear and detailed comparison between turbulence models used in tornadic wind flows and their effects on tornado induced pressure demonstrates a significant research gap. To bridge this research gap, in this study, two representative turbulence modeling approaches are applied in simulating real-world tornadoes to investigate how the selection of turbulence models affects the simulated tornadic wind flow and the induced pressure on structural surface. To be specific, LES with Smagorinsky-Lilly Subgrid and k-ω are chosen to simulate the 3D full-scale tornado and the tornado-structure interaction with a building present in the computational domain. To investigate the influence of turbulence modeling, comparisons are made of velocity field and pressure field of the simulated wind field and of the pressure distribution on building surface between the cases with different turbulence modeling.

• 한국멀티미디어학회논문지
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• 제24권11호
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• pp.1552-1559
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• 2021

Convolution neural networks (CNNs) show notable performance in image processing and are used as representative core models. CNNs extract and learn features from large amounts of train dataset. In general, it has a structure in which a convolution layer and a fully connected layer are stacked. The core of CNN is the convolution layer. The size of the kernel used for feature extraction and the number that affect the depth of the feature map determine the amount of weight parameters of the CNN that can be learned. These parameters are the main causes of increasing the computational complexity and memory usage of the entire neural network. The most computationally expensive components in CNNs are fully connected and spatial convolution computations. In this paper, we propose a Fourier Convolution Neural Network that performs the operation of the convolution layer in the Fourier domain. We work on modifying and improving the amount of computation by applying the fast fourier transform method. Using the MNIST dataset, the performance was similar to that of the general CNN in terms of accuracy. In terms of operation speed, 7.2% faster operation speed was achieved. An average of 19% faster speed was achieved in experiments using 1024x1024 images and various sizes of kernels.

• Structural Monitoring and Maintenance
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• 제10권2호
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• pp.133-154
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• 2023

Obscured structural members are mostly under-evaluated during condition assessment due to lack of visual inspection capability. Insufficient information about the integrity of these structural members poses a significant risk for public safety. Time domain reflectometry (TDR) is a novel approach in structural health monitoring (SHM). Ordinary coaxial cables "as is" without a major modification are not suitable for SHM with TDR. The objective of this study is to propose a practical and cost-effective modification approach to commercially available coaxial cables in order to use them as a "cable sensor" for damage detection with the TDR equipment for obscured structural members. The experimental validation and assessment of the proposed modification approach was achieved by conducting 3-point bending tests of the model piles as a representative obscured structural member. It can be noted that the RG59/U-6 and RG6/U-4 cable sensors expose higher strain sensitivity in comparison with non-modified "as is" versions of the cables used. As a result, the cable sensors have the capability of sensing both the presence and the location of a structural damage with a maximum aberration of 3 cm. Furthermore, the crack development can be monitored by the RG59/U-6 cable sensor with a simple calibration.