• Korean Journal of Computational Design and Engineering
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• v.9 no.1
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• pp.44-50
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• 2004

Mechanical parts are often grouped into part families based on the similarity of their shapes, to support efficient manufacturing process planning and design modification. The 2-part sequence papers present similarity assessment techniques to support part family classification for machined parts. These exploit the multiple feature decompositions obtained by the feature recognition method using convex decomposition. Convex decomposition provides a hierarchical volumetric representation of a part, organized in an outside-in hierarchy. It provides local accessibility directions, which supports abstract and qualitative similarity assessment. It is converted to a Form Feature Decomposition (FFD), which represents a part using form features intrinsic to the shape of the part. This supports abstract and qualitative similarity assessment using positive feature volumes. FFD is converted to Negative Feature Decomposition (NFD), which represents a part as a base component and negative machining features. This supports a detailed, quantitative similarity assessment technique that measures the similarity between machined parts and associated machining processes implied by two parts' NFDs. Features of the NFD are organized into branch groups to capture the NFD hierarchy and feature interrelations. Branch groups of two parts' NFDs are matched to obtain pairs, and then features within each pair of branch groups are compared, exploiting feature type, size, machining direction, and other information relevant to machining processes. This paper, the first one of the two companion papers, describes the similarity assessment methods using convex decomposition and FFD.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2022.06a
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• pp.1-3
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• 2022

코로나 19 팬데믹으로 인한 4차 산업혁명이 앞당겨지고 초현실, 초실감, 초연결 사회 등의 키워드가 대두되고 언택트(Untact) 시대가 일상생활에 불가항력적으로 접목되면서 몰입감과 흥미성, 유희성을 목적으로 한 콘텐츠들이 다양하게 활성화되었다. 특히, 메타버스(Metaverse) 플랫폼이 빠르게 진화하면서 물리적 현실과 디지털 가상성을 융합한 다중 사용자에게 다양한 경험이 가능한 서비스가 주목받고 있다. 메타버스는 다중 사용자 플랫폼에서 원활한 커뮤니케이션과 대규모 멀티플레이가 가능한 온라인 비디오 게임, 오픈 게임 월드, AR 협업 공간과 호환되는 사회적, 몰입감이 있는 VR(Virtual Reality) 플랫폼 서비스 중 하나이다. 우리는 메타버스 플랫폼 개발 시 필요로 하는 요소기술 및 3D 데이터 획득을 통한 VR 콘텐츠를 설계하고 구현하고자 한다. 1) 콘텐츠 시나리오 및 사용자 인터랙션 설계; 2) 볼류메트릭 캡처를 활용한 실사 기반의 동적(Dynamic) 데이터 생성; 3) 컴퓨터 그래픽 기반 가상공간 설계 및 정적(Static)데이터 요소기술 개발; 4) 가상 현실 공간 데이터와 볼류메트릭 캡처의 실사 데이터 정합; 5) 공간 데이터 시각화 생성 및 모듈형 공간 이동 제어 기능 개발; 최종적으로 6) VR 환경에서의 콘텐츠 구현을 목표로 한다.

• Journal of the Korea Concrete Institute
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• v.16 no.3 s.81
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• pp.397-406
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• 2004

A recently developed three dimensional concrete law is used for the analysis of concrete specimens and reinforced concrete columns subjected to different load patterns. The hypoelastic, orthotropic concrete constitutive model includes coupling between the deviatoric and volumetric stresses, works with both proportional and non-proportional loads and is implemented as a strain driven module. The FE implementation is based on the smeared crack approach with rotating cracks parallel to the principal strain directions. The concrete model is validated through correlated studies with: (a) experimental tests on confined concrete cylinders; (b) experimental results on three reinforced concrete columns tested at the University of California, San Diego. The correlations are overall very good, and the FE responses capture all the main phenomena observed in the experimental tests.

• Advances in Energy Research
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• v.6 no.1
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• pp.75-90
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• 2019

Anthropogenic greenhouse gas emissions are rising rapidly despite efforts to curb release of such gases. One long term potential solution to offset these destructive emissions is the capture and storage of carbon dioxide. Partially depleted hydrocarbon reservoirs are attractive targets for permanent carbon dioxide disposal due to proven storage capacity and seal integrity, existing infrastructure. Optimum well completion design in depleted reservoirs requires understanding of prominent geomechanics issues with regard to rock-fluid interaction effects. Geomechanics plays a crucial role in the selection, design and operation of a storage facility and can improve the engineering performance, maintain safety and minimize environmental impact. In this paper, an integrated geomechanics workflow to evaluate reservoir caprock integrity is presented. This method integrates a reservoir simulation that typically computes variation in the reservoir pressure and temperature with geomechanical simulation which calculates variation in stresses. Coupling between these simulation modules is performed iteratively which in each simulation cycle, time dependent reservoir pressure and temperature obtained from three dimensional compositional reservoir models in ECLIPSE were transferred into finite element reservoir geomechanical models in ABAQUS and new porosity and permeability are obtained using volumetric strains for the next analysis step. Finally, efficiency of this approach is demonstrated through a case study of oil production and subsequent carbon storage in an oil reservoir. The methodology and overall workflow presented in this paper are expected to assist engineers with geomechanical assessments for reservoir optimum production and gas injection design for both natural gas and carbon dioxide storage in depleted reservoirs.

• Archives of Plastic Surgery
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• v.51 no.1
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• pp.30-35
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• 2024

Background Breast aesthetics evaluation often relies on subjective assessments, leading to the need for objective, automated tools. We developed the Seoul Breast Esthetic Scoring Tool (S-BEST), a photometric analysis software that utilizes a DenseNet-264 deep learning model to automatically evaluate breast landmarks and asymmetry indices. Methods S-BEST was trained on a dataset of frontal breast photographs annotated with 30 specific landmarks, divided into an 80-20 training-validation split. The software requires the distances of sternal notch to nipple or nipple-to-nipple as input and performs image preprocessing steps, including ratio correction and 8-bit normalization. Breast asymmetry indices and centimeter-based measurements are provided as the output. The accuracy of S-BEST was validated using a paired t-test and Bland-Altman plots, comparing its measurements to those obtained from physical examinations of 100 females diagnosed with breast cancer. Results S-BEST demonstrated high accuracy in automatic landmark localization, with most distances showing no statistically significant difference compared with physical measurements. However, the nipple to inframammary fold distance showed a significant bias, with a coefficient of determination ranging from 0.3787 to 0.4234 for the left and right sides, respectively. Conclusion S-BEST provides a fast, reliable, and automated approach for breast aesthetic evaluation based on 2D frontal photographs. While limited by its inability to capture volumetric attributes or multiple viewpoints, it serves as an accessible tool for both clinical and research applications.

• Journal of Internet Computing and Services
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• v.16 no.3
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• pp.21-32
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• 2015

Since spatio-temporal local features for video representation have become an important issue of modeless bottom-up approaches in action recognition, various methods for feature extraction and description have been proposed in many papers. In particular, BoF(bag of features) has been promised coherent recognition results. The most important part for BoF is how to represent dynamic information of actions in videos. Most of existing BoF methods consider the video as a spatio-temporal volume and describe neighboring 3D interest points as complex volumetric patches. To simplify these complex 3D methods, this paper proposes a novel method that builds BoF representation as a way to learn 2D interest points directly from video data. The basic idea of proposed method is to gather feature points not only from 2D xy spatial planes of traditional frames, but from the 2D time axis called spatio-temporal frame as well. Such spatial-temporal features are able to capture dynamic information from the action videos and are well-suited to recognize human actions without need of 3D extensions for the feature descriptors. The spatio-temporal BoF approach using SIFT and SURF feature descriptors obtains good recognition rates on a well-known actions recognition dataset. Compared with more sophisticated scheme of 3D based HoG/HoF descriptors, proposed method is easier to compute and simpler to understand.

• Journal of Wetlands Research
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• v.19 no.1
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• pp.90-102
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• 2017

In this study, various types of nutrient models were tested by using two tears's water quality data collected from the stormwater wetland in Korea. Based on results, most important factor influencing nitrogen removal was hydraulic loading rate, which indicates that surface area of wetland is more important than its volumetric capacity, and model proposed by WEF was found to give a least error between measured and calculated values. For the phosphorus, in case assuming a power relationship between rate constant and temperature, the best prediction result were obtained, but temperature was most sensitive parameter affecting phosphorus removal. In addition, denitrification was always a limiting step for the nitrogen removal in this particular wetland mostly due to the lack of carbon source and high dissolved oxygen concentration. In this paper, several alternatives to improve nitrogen removal, including proper arrangement and designation of wetland elements and use of floating plants or synthetic fiber mat to control oxygen level and to capture the algal particles were proposed and discussed.

• Economic and Environmental Geology
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• v.47 no.6
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• pp.625-633
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• 2014

The Aquistore project is the world's first commercial capture, transportation, utilization and storage project of post-combustion $CO_2$ from a coal-fired thermo electric power plant, and the proposed storage is a saline aquifer at a depth of about 3,500 m. Deep saline aquifer, compared to hydrocarbon reservoir, provides the great volumetric potential for storage of $CO_2$ anywhere in the world, therefore the research results from the project may be exported globally to other sites. Geological $CO_2$ storage characterization for saline aquifer instead of hydrocarbon reservoir needs to estimate the geophysical properties of subsurface geology. This study calculated the geophysical property of water-saturated formation by applying amplitude variation analysis developed from oil and gas exploration. We correlated horizon tops at the well logs to seismic traveltime of 1,815 and 1,857 ms as Winnipeg and Deadwood formations. Gradient analysis from seismic traces showed correlation coefficient of 45 - 81 % on amplitude variation with respect to incident angle. Crossplot of intercept and gradient shows the inverse proportional trend which represents typical water saturated sediments. Product attribute of intercept and gradient described the base of wet sediment. Poisson's ratio change attribute increased at the top of target area satisfying with wet sediment and decreased at the top of basement in a dry rock bed.