• 한국측량학회지
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• 제20권2호
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• pp.171-181
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• 2002

기 제작된 지하시설물도의 정확도를 분석한 결과 오류 유형을 도형정보의 위치오류와 속성정보의 오류 두 가지로 구분 지을 수 있었으며, 도형정보의 위치오류는 지하시설물의 탐사와 위치측량과정에서, 속성정보의 오류는 자료의 입력과정에서 주로 발생하고 있었다. 본 연구에서는 실험을 통하여 탐사정확도와 위치측량정확도를 향상시킬 수 있는 방안을 제시하였고, 공정개선을 통한 속성오류의 감소방안을 제시하였다.

• 천문학회보
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• 제43권2호
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• pp.38.1-38.1
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• 2018

A merging galaxy cluster is a useful laboratory to study many interesting astrophysical processes such as intracluster medium heating, particle acceleration, and possibly dark matter self-interaction. However, without understanding the merger scenario of the system, interpretation of the observational data is severely limited. In this work, we focus on the off-axis binary cluster merger Abell 115, which possesses many remarkable features. The cluster has two cool cores in X-ray with disturbed morphologies and a single giant radio relic just north of the northern X-ray peak. In addition, there is a large discrepancy (almost a factor of 10) in mass estimate between weak lensing and dynamical analyses. To constrain the merger scenario, we perform a hydrodynamical simulation with the adaptive mesh refinement code RAMSES. We use the multi-wavelength observational data including X-ray, weak-lensing, radio, and optical spectroscopy to constrain the merger scenario. We present detailed comparisons between the simulation results and these multi-wavelength observations.

• Communications for Statistical Applications and Methods
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• 제29권1호
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• pp.127-150
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• 2022

We discuss multiple change-point estimation as edge detection in piecewise smooth functions with finitely many jump discontinuities. In this paper we propose change-point estimators using concentration kernels with Fourier coefficients. The change-points can be located via the signal based on Fourier transformation system. This method yields location and amplitude of the change-points with refinement via concentration kernels. We prove that, in an appropriate asymptotic framework, this method provides consistent estimators of change-points with an almost optimal rate. In a simulation study the proposed change-point estimators are compared and discussed. Applications of the proposed methods are provided with Nile flow data and daily won-dollar exchange rate data.

• 한국건축시공학회:학술대회논문집
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• 한국건축시공학회 2021년도 가을 학술논문 발표대회
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• pp.223-224
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• 2021

The process before the model learning stage in AI R&D can be subdivided into data collection/cleansing-data purification-data labeling. After that, according to the purpose of development, it goes through a stage of verifying the model by performing learning by using the algorithm of the artificial intelligence model. Several studies describe an important part of AI research as the learning stage, and try to increase the accuracy by changing the structure and layer of the AI model. However, if the refinement and labeling process of the learning data is tailored only to the model format and is not made for the purpose of development, the desired AI model cannot be obtained. The latest research reveals that most AI research failures are the failure of the learning data rather than the structure of the AI model. analyzed.

• 한국의류산업학회지
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• 제23권3호
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• pp.380-389
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• 2021

This study aimed to reveal the perceptions and trends of digital fashion technology through an informational approach. A big data analysis was conducted after collecting the text shown in a web environment from April 2019 to April 2021. Key words were derived through text mining analysis and network analysis, and the structure of perception of digital fashion technology was identified. Using textoms, we collected 8144 texts after data refinement, conducted a frequency of emergence and central component analysis, and visualized the results with word cloud and N-gram. The frequency of appearance also generated matrices with the top 70 words, and a structural equivalent analysis was performed. The results were presented with network visualizations and dendrograms. Fashion, digital, and technology were the most frequently mentioned topics, and the frequencies of platform, digital transformation, and start-ups were also high. Through clustering, four clusters of marketing were formed using fashion, digital technology, startups, and augmented reality/virtual reality technology. Future research on startups and smart factories with technologies based on stable platforms is needed. The results of this study contribute to increasing the fashion industry's knowledge on digital fashion technology and can be used as a foundational study for the development of research on related topics.

• International Journal of Internet, Broadcasting and Communication
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• 제14권3호
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• pp.85-90
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• 2022

In this study, keywords from representative online portal sites such as NAVER, Google, and Youtube were collected based on text mining analysis technique using TEXTOM to check the changes in the restaurant industry before and after COVID-19. The collection keywords were selected as dining out, food service industry, and dining out culture. For the collected data, the top 30 words were derived, respectively, through the refinement process. In addition, comparative analysis was conducted by defining data from 2018 to 2019 before COVID-19, and from 2020 to 2021 after COVID-19. As a result, 8272 keywords before COVID-19 and 9654 keywords after COVID-19, a total of 17926 keywords, were derived. In order for the food service industry to develop after the COVID-19 pandemic, it is necessary to commercialize the recipes of restaurants to revitalize the distribution of home-use food products that replace home-cooked meals such as meal kits. Due to the social distancing caused by COVID-19, the dining out culture has changed and the trend has changed, and it has been confirmed that the consumption culture has changed to eating and delivering at home more safely than visiting restaurants. In addition, it has been confirmed that the consumption culture of existing consumers is changing to a trend of cooking at home rather than visiting restaurants.

• 한국소성가공학회:학술대회논문집
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• 한국소성가공학회 2001년도 추계학술대회 논문집
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• pp.293-296
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• 2001

The dynamic softening mechanisms of AISI 316, AISI 304 and AISI 430 stainless steels were studied with torsion test in the temperature range of $900 - 1200^{\circ}C$ and the strain rate range of $5.0x10^{-2}-5.0x10^0/sec$. The austenitic stainless steels, such as AISI 316 and AISI 304 were softened by dynamic recrystallization (DRX) during hot deformation. Also, the evolutions of flow stress and microstructure of AISI 430 ferritic stainless steel show the characteristics of continuous dynamic recrystallization (CDRX). To establish the quantitative equations for DRX of AISI 316 stainless steel, the evolution of flow stress curve with strain was analyzed. The critical strain (${\varepsilon}_c$) and strain for maximum softening rate (${\varepsilon}^{*}$) could be confirmed by the analysis of work hardening rate ($d{\sigma}/d{\varepsilon}={\theta}$). The volume fraction of dynamic recrystallization ($X_{DRX}$) as a function of processing variables, such as strain rate ( $\varepsilon$ ), temperature (T), and strain ( $\varepsilon$ ) were established using the ${\epsilon}_c$ and ${\varepsilon}^{*}$. For the exact prediction the ${\varepsilon}_c,\;{\varepsilon}^{*}$ and Avrami' exponent (m') were quantitatively expressed by dimensionless parameter, Z/A, respectively. It was found that the calculated results were agreed with the experimental data for the steels at my deformation conditions. Also, we can reasonably conclude that the DRX, CDRX and grain refinement of stainless steels can be achieved by large strain deformation at high Z parameter condition.

• 정보처리학회논문지:소프트웨어 및 데이터공학
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• 제4권4호
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• pp.187-194
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• 2015

본 논문에서는 RGB-D 입력 영상들로부터 3차원 공간을 움직이는 카메라의 실시간 포즈를 효과적으로 추적할 수 있는 시각 주행 거리측정기를 제안한다. 본 논문에서 제안하는 시각 주행 거리 측정기에서는 컬러 영상과 깊이 영상의 풍부한 정보를 충분히 활용하면서도 실시간 계산량을 줄이기 위해, 특징 기반의 저밀도 주행 거리 계산 방법을 사용한다. 본 시스템에서는 보다 정확한 주행 거리 추정치를 얻기 위해, 카메라 이동 이전과 이동 이후의 영상에서 추출한 특징들을 정합한 뒤, 정합된 특징들에 대한 추가적인 정상 집합 정제 과정과 주행 거리 정제 작업을 반복한다. 또한, 정제 후 잔여 정상 집합의 크기가 충분치 않은 경우에도 잔여 정상 집합의 크기에 비례해 최종 주행 거리를 결정함으로써, 추적 성공률을 크게 향상시켰다. TUM 대학의 벤치마크 데이터 집합을 이용한 실험과 3차원 장면 복원 응용 시스템의 구현을 통해, 본 논문에서 제안하는 시각 주행 거리 측정 방법의 높은 성능을 확인할 수 있었다.

• Spatial Information Research
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• 제8권1호
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• pp.155-170
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• 2000

공간 인덱스인 R-Tree를 이용하여 조건에 만족하는 공간 객체를 찾기 위해서 MBR의 비교하는 여과 과정만으로는 부정확한 경우가 있으며 그러한 경우에는 해당 공간 객체를 읽어 조건과 직접 비교하는 과정, 즉 정제과정이 필요하게 된다. 정제과정을 수행하기 위해서는 디스크 입출력이 요구되고 고비용 공간 연상을 수행해야 하므로 이는 검색 비용이 커지는 요인이 된다. 그래서, 여과 과정후의 후보 객체수를 최소화하기 위한 2단계 여과 기법들이 연구되었지만, 여과 효율이 떨어지거나, 추가로 데이터를 유지해야하거나, 원래 객체의 정보를 잃어버려 객체들을 재구성해야하는 문제점이 발생한다. 따라서, 본 논문에서는 이차 여과 과정에서 공간 객체의 존재여부를 저장하는 진위 테이블인 그리드 필터를 이용하여 간단한 논리 연산만으로 공간객체를 검색할 수 있도록 하는 확장된 R-Tree를 제안한다. 그러므로, 그리드 필터를 가지는 확장된 R-Tree 는 효율적인 이차 여과과정을 수행하기 때문에 여과를 위한 연산비용이 작고, 근사의 질이 높아 여과 효율이 우수하다.

• 한국ITS학회 논문지
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• 제15권5호
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• pp.83-94
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• 2016

도로공사구간의 안전성 증대를 위해 공사구간에 진입하는 운전자에게 전방상황에 대한 사전인지와 적절한 회피행동을 유도할 수 있는 경고정보를 제공하는 것은 효과적인 기술적 대안이 될 수 있다. 본 연구에서는 지향성 스피커를 이용하여 운전자에게 음성경고를 제공하여 안전운전을 유도하는 기술의 타당성을 평가하였다. 이를 위해 현장실험을 수행하였으며, 운전자의 경고정보 인지도 및 선호도, 공사구간 접근차량의 속도, 그리고 소음을 평가지표로 설정하여 수집된 자료를 분석하였다. 분석결과, 음성경고가 도로공사구간에 접근하는 운전자의 주위 환기를 위해서 긍정적으로 사용될 수 있음을 확인하였다. 반면 소음으로 인한 부정적인 효과도 발생할 수 있음을 관찰하였다. 따라서 음성 경고 제공 방식에 대한 개선을 통해 음성 정보 제공의 실효성을 증대시킬 필요가 있다. 또한 본 연구의 결과물은 향후 공사구간 안전성 증대를 위한 체계적인 음성경고정보시스템 개발을 위해 유용한 자료로 활용될 것으로 기대된다.