• 천문학회보
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• 제38권1호
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• pp.32.2-32.2
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• 2013

We examine large-scale environmental effects on the formation and the mass growth of dark matter halos. To facilitate this, we constructed dark matter halo merger trees from a cosmological N-body simulation, which enabled us to trace the merger information and the assembly history of individual halos. In fact, since the massive halos are more likely to be distributed in denser regions than in less dense regions (Mo & White, 1996), the large-scale environment dependence of the properties of halos can be partly originated from the halo mass effect. In order to avoid such contamination, caused by the mass dependence of halo properties, we carefully measured the local overdensity as the indicator of large-scale environment, which was calculated to be as independent of halo mass as possible. Small halos (${\sim}10^{11-12}M_{\odot}$), which usually host isolated single galaxies, show a notable difference on the formation time of galaxies depending on their large-scale environments, which reconfirms halo assembly bias (Gao & White, 2007). Furthermore, we investigate how this environmental effect on small halos is correlated with the mass assembly history of galaxies by using our semi-analytic model. We found that assembly bias in small halos does not have significant effects on the formation time or on the star formation history of galaxies residing in those halos except for the individual stellar mass of galaxies at z = 0. On average, isolated galaxies in high-density regions tend to be slightly more massive than those in low-density regions. Although the observational data from the current galaxy surveys is not yet sufficient for testing this prediction, future galaxy surveys will be able to explore these small galaxies more thoroughly.

• Structural Engineering and Mechanics
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• 제53권3호
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• pp.393-410
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• 2015

Two dimensional numerical models and physical models have been developed to study the highly nonlinear interactions between waves and breakwaters, but several of these models consider the effects of the structural dynamic responses and the shape of the breakwater axis on the wave pressures. In this study, a multi-material Arbitrary Lagrangian Eulerian (ALE) method is developed to simulate the nonlinear interactions between nonlinear waves and elastic seawalls on a coastal rubble mound breakwater, and is validated experimentally. In the experiment, a solitary wave is generated and used with a physical breakwater model. The wave impact is validated computationally using a breakwater - flume coupling model that replicates the physical model. The computational results, including those for the wave pressure and the water-on-deck, are in good agreement with the experimental results. A local breakwater model is used to discuss the effects of the structural dynamic response and different design parameters of the breakwater on wave loads, together with pressure distribution up the seawall. A large-scale breakwater model is used to numerically study the large-scale wave impact problem and the horizontal distribution of the wave pressures on the seawalls.

• 한국경영과학회:학술대회논문집
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• 한국경영과학회 1998년도 추계학술대회 논문집
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• pp.36-39
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• 1998

It is very difficult for the large-scale retailers, who deal with tens of thousands of items, to price all the items dynamically reflecting all the constraints and policies. In spite of its importance, the prices are determined by human experts because the process of setting the prices of all the items is not established yet. To solve this problem, we adopt a mixed model that combines three typical pricing models: cost-plus model, competition-oriented model, and demand-oriented model. Since each model an be converted to a set of constraints in point and interval forms, solving the pricing problem with the three groups of models requires an algorithm which can solve the problem with weighted constraints of intervals and points. So we have devised an algorithm named “Point Determination Algorithm”. From the rules that represents tile models, the constraints are extracted to be solvable by tile Point Determination Algorithm. A prototype KAPA (Knowledge Assisted pricing Advisor) is developed with this idea using the expert system environment UNIK - a tool developed by KAIST. According to the experiment with 76 items in comparison with 53 human pricing experts we confirmed that the KAPA can perform highly consistent with human experts. This implies KAPA system is applicable to pricing millions of items dynamically.

• 한국수소및신에너지학회논문집
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• 제22권2호
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• pp.178-183
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• 2011

Metal hydride alloys are a promising type of material in hydrogen storage applications, allowing for low-pressure, high-density storage. However, while many studies are being performed on enhancing the hydrogen storage properties of such alloys, there has been little research on large-scale storage vessels which make use of the alloys. In particular, large-scale, high-density storage devices must make allowances for the inevitable generation or absorption of heat during use, which may negatively impact functioning properties of the alloys. In this study, we develop a numerical model of the discharge properties of a high-density MH hydrogen storage device. Discharge behavior for a pilot system is observed in terms of temperature and hydrogen flow rates. These results are then used to build a numerical model and verify its calculated predictions. The proposed model may be applied to scaled-up applications of the device, as well as for analyses to enhance future device designs.

• 전기학회논문지
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• 제66권2호
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• pp.305-314
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• 2017

Most of the existing researches on systemwide optimization of generator maintenance scheduling do not consider the equivalent operating hours(EOHs) mainly due to the difficulties of calculating the EOHs of the CCGTs in the large scale system. In order to estimate the EOHs not only the operating hours but also the number of start-up/shutdown during the planning period should be estimated, which requires the mathematical model to incorporate the economic dispatch model and unit commitment model. The model is inherently modelled as a large scale mixed-integer nonlinear programming problem and the computation time increases exponentially and intractable as the system size grows. To make the problem tractable, this paper proposes an EOH calculation based on demand grouping by K-means clustering algorithm. Network congestion is also considered in order to improve the accuracy of EOH calculation. This proposed method is applied to the actual Korean electricity market and compared to other existing methods.

• Journal of information and communication convergence engineering
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• 제20권4호
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• pp.309-316
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• 2022

This investigation is aimed at automatic text summarization on large-scale Vietnamese datasets. Vietnamese articles were collected from newspaper websites and plain text was extracted to build the dataset, that included 1,101,101 documents. Next, a new single-document extractive text summarization model was proposed to evaluate this dataset. In this summary model, the k-means algorithm is used to cluster the sentences of the input document using different text representations, such as BoW (bag-of-words), TF-IDF (term frequency - inverse document frequency), Word2Vec (Word-to-vector), Glove, and FastText. The summary algorithm then uses the trained k-means model to rank the candidate sentences and create a summary with the highest-ranked sentences. The empirical results of the F1-score achieved 51.91% ROUGE-1, 18.77% ROUGE-2 and 29.72% ROUGE-L, compared to 52.33% ROUGE-1, 16.17% ROUGE-2, and 33.09% ROUGE-L performed using a competitive abstractive model. The advantage of the proposed model is that it can perform well with O(n,k,p) = O(n^(k+2/p)) + O(nlog₂n) + O(np) + O(nk²) + O(k) time complexity.

• 대한임베디드공학회논문지
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• 제19권2호
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• pp.73-81
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• 2024

Recently, mobile manipulators have been utilized in agriculture industry for weed removal and harvest automation. This paper proposes a domain adaptive fruit detection method for harvest automation, by utilizing OWL-ViT model which is an open-vocabulary object detection model. The vision-language model can detect objects based on text prompt, and therefore, it can be extended to detect objects of undefined categories. In the development of deep learning models for real-world problems, constructing a large-scale labeled dataset is a time-consuming task and heavily relies on human effort. To reduce the labor-intensive workload, we utilized a large-scale public dataset as a source domain data and employed a domain adaptation method. Adversarial learning was conducted between a domain discriminator and feature extractor to reduce the gap between the distribution of feature vectors from the source domain and our target domain data. We collected a target domain dataset in a real-like environment and conducted experiments to demonstrate the effectiveness of the proposed method. In experiments, the domain adaptation method improved the AP50 metric from 38.88% to 78.59% for detecting objects within the range of 2m, and we achieved 81.7% of manipulation success rate.

• Journal of Advanced Marine Engineering and Technology
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• 제28권3호
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• pp.423-433
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• 2004

A large eddy simulation (LES) is performed for turbulent flow in a combustion device. The combustion device is simplified as a cylindrical chamber with sudden expansion. A flame holder is attached inside a cylindrical chamber in order to promote turbulent mixing and to accommodate flame stability. The turbulent sub-grid scale models are applied and validated. Emphasis is placed on the evaluation of turbulent model for the LES of complex geometry. The simulation code is constructed by using a general coordinate system based on the physical contravariant velocity components. The calculated Reynolds number is 5000 based on the bulk velocity and the diameter of inlet pipe. The predicted turbulent statistics are evaluated by comparing with the LDV measurement data. The Smagorinsky model coefficients are estimated and the utility of dynamic SGS models are confirmed in the LES of complex geometry.

• 한국컴퓨터그래픽스학회논문지
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• 제21권5호
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• pp.37-44
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• 2015

본 논문에서는 전통적으로 삼차원 모델 복원에 사용되는 볼륨 기반 자료 구조의 한계점을 극복하기 위해 평면 해시 구조를 볼륨 구조와 상호보완적으로 사용하는 하이브리드 모델 표현을 제안한다. 실내 환경에 대한 삼차원 모델 복원은 좁은 공간에 대한 정밀한 복원 결과를 얻기 위해 볼륨 기반의 자료 구조를 사용하였으나, 이러한 볼륨 기반의 자료 구조는 메모리의 사용량이 많아 대규모 공간에 대한 삼차원 복원으로 확장이 용이하지 못하였다. 본 논문에서는 이러한 기존 삼차원 모델 복원의 확장성을 증가시키기 위해 메모리를 효율적으로 사용하는 평면 해시 모델 구조를 제안한다. 또한 이러한 제안된 평면 해시 모델 구조를 넓고 단순한 평면 복원을 위해 사요하고, 좁고 디테일한 공간 복원에는 기존 볼륨 구조를 동시에 사용하는 하이브리드 복원 방법을 사용한다. 제안된 기법은 GPU 상에서 구현되어 공간을 실시간으로 복원 가능하다.

• 수산해양기술연구
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• 제20권1호
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• pp.30-36
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• 1984

대규모의 소성역을 동반하면서 파괴하는 고인성 재료의 탄소성 파괴 반가를 위하여 제안된 바 있는 CPE 모형의 유효성을 입증하고자 소성역의 영향을 보정한 선형 파괴역학과의 이론적 검토와 오오스테나이트계 스테인레스강에 대한 실험적 비교검토를 통하여 얻은 결론은 다음과 같다. 예측한 바와 같이 선형 파괴역학의 적용은 소규모 항복조건이 성립하는 경우에만 가능하며 CPE 모형은 대변형을 형성하면서 파괴하는 경우의 파괴모형으로서 유효하다. 더욱 엄밀한 유효성을 입증하기 위하여 다음의 사항이 필요하다고 본다. 1. 크랙의 길이가 짧은 시험편에 대한 실험이 필요하다. 2. 크랙성장 개시점을 정확하게 찾을 수 있는 방법이 필요하다. 3. 파괴 진행영역에 대한 두께의 영향을 고려해 보아야 할 필요성이 있다.