• Journal of Korean Society of Forest Science
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• v.113 no.3
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• pp.327-338
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• 2024

Forest road construction can degrade the physical and biological environments of forest ecosystems. Although this degradation may be temporary, some research has shown the potential for the long-term recovery of the original ecosystem. This study investigated changes in communities' structures over time to understand the process of ecosystem change following road construction. Data were collected from 63 plots, each measuring 25m², in Buyeo-gun, Chungcheongnam-do, including plots from roads constructed in 1998 (25 years elapsed), 2021 (two years elapsed), and 2022 (one year elapsed), using phytosociological methods. The results showed that the importance of the values of Pinus densiflora an d Quercus variabilis in the tree and subtree layers of the 25-year-old cut slopes were similar to those of the control plots, indicating the significant recovery of the original ecosystem's structure and function after 25 years. Species diversity analysis revealed the higher evenness and lower dominance of the cut slopes and road surfaces attributed to the high dominance of species such as Arundinella hirta and Miscanthus sinensis. The community similarity index and detrended correspondence analysis (DCA) indicated that the control plots, all the edge plots, and the 25-year-old cut slopes could be considered part of the same community. In conclusion, forest roads in place for 25 years appear to have been restored to the level of the original ecosystem. These findings can serve as valuable ecological data for understanding the vegetation recovery process at future forest road construction sites.

• Journal of the Korea Computer Graphics Society
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• v.16 no.1
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• pp.9-20
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• 2010

In order to visualize participating media in 3D space, they usually calculate the incoming radiance by subdividing the ray path into small subintervals, and accumulating their respective light energy due to direct illumination, scattering, absorption, and emission. Among these light phenomena, scattering behaves in very complicated manner in 3D space, often requiring a great deal of simulation efforts. To effectively simulate the light scattering effect, several approximation techniques have been proposed. Volume photon mapping takes a simple approach where the light scattering phenomenon is represented in volume photon map through a stochastic simulation, and the stored information is explored in the rendering stage. While effective, this method has a problem that the number of necessary photons increases very fast when a higher variance reduction is needed. In an attempt to resolve such problem, we propose a different approach for rendering particle-based volume data where kernel smoothing, one of several density estimation methods, is explored to represent and reconstruct the light in-scattering effect. The effectiveness of the presented technique is demonstrated with several examples of volume data.

• Journal of the Korea Computer Graphics Society
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• v.23 no.3
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• pp.31-38
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• 2017

In this paper, we propose a system which estimates Manhattan coordinate systems for urban scene images using a convolutional neural network (CNN). Estimating the Manhattan coordinate system from an image under the Manhattan world assumption is the basis for solving computer graphics and vision problems such as image adjustment and 3D scene reconstruction. We construct a CNN that estimates Manhattan coordinate systems based on GoogLeNet [1]. To train the CNN, we collect about 155,000 images under the Manhattan world assumption by using the Google Street View APIs and calculate Manhattan coordinate systems using existing calibration methods to generate dataset. In contrast to PoseNet [2] that trains per-scene CNNs, our method learns from images under the Manhattan world assumption and thus estimates Manhattan coordinate systems for new images that have not been learned. Experimental results show that our method estimates Manhattan coordinate systems with the median error of $3.157^{\circ}$ for the Google Street View images of non-trained scenes, as test set. In addition, compared to an existing calibration method [3], the proposed method shows lower intermediate errors for the test set.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 1996.10a
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• pp.153-156
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• 1996

현재의 정보시스템이 하드웨어의 발전에 비해 늦어진 이유는 개발 단계별로 상호 일관성이 결여된 방법론을 사용하고 있고 이 방법론들이 실제의 비즈니스 프로세스(Business Process)와는 차이가 있는 형태로 구현이 되기 때문이다. 또한, 이런 방법론들이 분산조직에 사용된다면 비즈니스 프로세스가 세분화되기 때문에 문제점들이 더 깊이 심화되는 경향이 발생하게 된다. 이런 상황에 대한 해결책은 정보시스템이 비즈니스 프로세스로부터 구체적인 정보시스템의 구현에 이르기까지 일관성 있게 진행할 수 있는 방법론이 필요하다. 그러므로, 정보시스템 구현의 각 단계별로 추상과 구현방법을 구체적으로 제시하고 개념적인 무결성을 보장할수 있는 새로운 정보시스템 개발방법이 요구된다. 본 논문에서는 이러한 정보시스템을 구현하기 위해서 업무분석의 과정에서부터 구현에 이르기까지 개념적인 무결성(Conceptual Integrity)을 유지하고(Brooks, 1982) 방법론상에서 중단이나 변형없이 연결되는 시스템 개발방법론인 컴퓨터 통합 비즈니스 시스템(Computer-Integrated Business System:CIBS)을 소개하고 이 CIBS가 사용하는 세부적인 객체지향 프로그래밍 방법론이 AF(Application Framework)을 설명하며, 최종적으로 이 CIBS에 의해서 구현된 정보시스템과 기존의 프로그래밍 기법으로 구현된 정보시스템과의 비교를 통해 그 장단점을 증명하고자 한다. 또한, 이 CIBS구조는 정보시스템의 단편적인 정보제공 능력을 넘어서서 비즈니스 프로세스를 개선함에 의해서 기업의 노하우를 정립하고 이를 발전시키는 정보시스템의 진보된 형태를 보여줌으로서 정보시스템의 새로운 모습과 비젼을 제시하며 혁신적인 정보시스템의 새로운 구조를 보여준다. 문제점들은 HED (Human Engineerign Discrepance) 목록으로 정리하여 설계에 반영하도록 하였다.로 마음의 안정감, 몸의 긴장 이완에 따른 건강 상태 유지, 수업 집중도 향상 등이 나타났다. 위와 같은 종합 적 분석 결과에 따라, 본 연구는 제조 현장의 생산성 향상 및 품질 향상과 연계하여 작업자의 작업 집중도 향상, 작업자의 육체적, 심리적 변화에 따른 생산성 및 품질 향상 변화 정도 등의 산업공학(인간공학) 제 분야의 여러 측면에서 연구 및 적용이 가능하리라 사료된다.l, 시험군:25.90$\pm$7.16mg/d1, 47% 감소)를 나타내었으며, 시험군의 AUC는 대조군에 비해 39% 감소하였고, 혈중 아세트알데히드의 농도는 투여 60분후 시험군(3.96$\pm$0.07nmo1/$m\ell$)이 대조군(6.45$\pm$0,64nmo1/$m\ell$)에 비해 유의성 있는 감소(39%)를 나타내었으며, 시험군의 AUC는 대조군에 비해 48% 감소하였다 한편, 시험관내 에탄올 대사 효소에 대한 바이오짐의 효과를 검색해본 결과 바이오짐(2.0 $\mu\textrm{g}$/assay)에 의해 Aldehyde dehydrogenase(1.5unit/assay)의 활성이 14% 증가되었다. 본 연구의 결과로 볼 때, 비지니스 및 바이오짐은 음주 후 상승된 혈중 에탄을 농도 및 아세트알데히드의 농도를 현저히 감소시키는 효과가 있었다.량 보호 관리, 도시 소공원 개발, 역사 문화 공원 조성, 하천 공간 복원, 공원 시설 기능 개선, 이용 프로그램 개발, 공원 관리 개선, 환경 피해 녹지의 회복, 도시 환경 림 조성, 녹지 기능

• Journal of the Institute of Electronics Engineers of Korea SD
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• v.45 no.6
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• pp.49-59
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• 2008

SIFT(Scale Invariant Feature Transform) is an algorithm to extract vectors at pixels around keypoints, in which the pixel colors are very different from neighbors, such as vortices and edges of an object. The SIFT algorithm is being actively researched for various image processing applications including 3-D image constructions, and its most computation-intensive stage is a keypoint localization. In this paper, we develope a fixed-point model of the keypoint localization and propose its efficient hardware architecture for embedded applications. The bit-length of key variables are determined based on two performance measures: localization accuracy and error rate. Comparing with the original algorithm (implemented in Matlab), the accuracy and error rate of the proposed fixed point model are 93.57% and 2.72% respectively. In addition, we found that most of missing keypoints appeared at the edges of an object which are not very important in the case of keypoints matching. We estimate that the hardware implementation will give processing speed of $10{\sim}15\;frame/sec$, while its fixed point implementation on Pentium Core2Duo (2.13 GHz) and ARM9 (400 MHz) takes 10 seconds and one hour each to process a frame.

• Korean Chemical Engineering Research
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• v.60 no.3
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• pp.347-355
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• 2022

The safety valve (PSV) is a safety device that automatically releases a spring when the pressure generated by various causes reaches the set pressure, and is restored to a normal state when the pressure falls below a certain level. Periodic inspection and monitoring of safety valves are essential so that they can operate normally in abnormal conditions such as pressure rise. However, as the current safety inspection is performed only at a set period, it is difficult to ensure the safety of normal operation. Therefore, evaluation items were developed by finding failure modes and causative factors of safety valves required for safety management. In addition, it is intended to provide decision-making information for securing safety by deriving the priority of items. To this end, a Delphi survey was conducted three times to derive evaluation factors that were judged to be important in relation to the Failure Mode Cause Factor (FMCFs) of the safety valve (PSV) targeting 15 experts. As a result, 6 failure modes of the safety valve and 22 evaluation factors of its sub-factors were selected. In order to analyze the priorities of the evaluation factors selected in this way, the hierarchical structure was schematized, and the hierarchical decision-making method (AHP) was applied to the priority calculation. As a result of the analysis, the failure mode priorities of FMCFs were 'Leakage' (0.226), 'Fail to open' (0.201), 'Fail to relieve req'd capacity' (0.152), 'Open above set pressure' (0.149), 'Spuriously' 'open' (0.146) and 'Stuck open' (0.127) were confirmed in the order. The lower priority of FMCFs is 'PSV component rupture' (0.109), 'Fail to PSV size calculation' (0.068), 'PSV Spring aging' (0.065), 'Erratic opening' (0.059), 'Damage caused by improper installation and handling' (0.058), 'Fail to spring' (0.053), etc. were checked in the order. It is expected that through efficient management of FMCFs that have been prioritized, it will be possible to identify vulnerabilities of safety valves and contribute to improving safety.