• Environmental Engineering Research
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• 제24권3호
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• pp.404-411
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• 2019

In this study, we designed a data-driven model to predict chlorophyll-a using M5P model tree and extreme learning machine (ELM). The Juksan weir in the Youngsan River has high chlorophyll-a, which is the primary indicator of algal bloom every year. Short-term algal bloom prediction is important for environmental management and ecological assessment. Two models were developed and evaluated for short-term algal bloom prediction. M5P is a classification and regression-analysis-based method, and ELM is a feed-forward neural network with fast learning using the least square estimate for regression. The dataset used in this study includes water temperature, rainfall, solar radiation, total nitrogen, total phosphorus, N/P ratio, and chlorophyll-a, which were collected on a daily basis from January 2013 to December 2016. The M5P model showed that the prediction model after one day had the highest performance power and dropped off rapidly starting with predictions after three days. Comparing the performance power of the ELM model with the M5P model, it was found that the performance power of the 1-7 d chlorophyll-a prediction model was higher. Moreover, in a period of rapidly increasing algal blooms, the ELM model showed higher accuracy than the M5P model.

• 응용통계연구
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• 제22권5호
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• pp.923-935
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• 2009

본 연구는 의사결정나무의 추천 모형 선택을 위한 비교실험에 초점을 두고 있다. 의사결정나무 모형은 구축된 모형에 기반을 두고 미래 관측치에 대한 예측 기능을 수행하게 될 것이므로 구축된 모형이 아무리 정치(精緻)하다고 하더라도 일반화의 성질을 충족시키지 못하면 실제성이 없게 된다. 따라서 본 연구는 교차타당성 검토를 통해 일반화의 성질을 충족시키면서 우수한 예측력을 갖는 추천 모형을 탐지하는 절차를 연구하는 데에 초점을 맞추고 있다. 사례 연구로 인체측정자료를 사용하여 측정곤란부위 예측을 위한 의사결정나무 추천 모형을 탐지한다. 그 결과 CART 모형 이 추천 모형으로 탐지되었다.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제6권4호
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• pp.1223-1247
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• 2012

The need for securing Wireless Sensor Networks (WSNs) is essential especially in mission critical fields such as military and medical applications. Security techniques that are used to secure any network depend on the security requirements that should be achieved to protect the network from different types of attacks. Furthermore, the characteristics of wireless networks should be taken into consideration when applying security techniques to these networks. In this paper, energy efficient Security Model for Tree-based Routing protocols (SMTR) is proposed. In SMTR, different attacks that could face any tree-based routing protocol in WSNs are studied to design a security reference model that achieves authentication and data integrity using either Message Authentication Code (MAC) or Digital Signature (DS) techniques. The SMTR communication and processing costs are mathematically analyzed. Moreover, SMTR evaluation is performed by firstly, evaluating several MAC and DS techniques by applying them to tree-based routing protocol and assess their efficiency in terms of their power requirements. Secondly, the results of this assessment are utilized to evaluate SMTR phases in terms of energy saving, packet delivery success ratio and network life time.

• 한국산림과학회지
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• 제98권5호
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• pp.576-583
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• 2009

Based on the stem analysis and biomass measurement of 36 trees and 1,576 branches in Pinus sylvestris var. mongolica (Mongolian pine) plantations of Northeast China, this study was conducted to develop estimation model equation for leaf biomass of a single tree and branch, to examine the vertical distribution of leaf biomass in the crown, and to evaluate the proportional ratios of biomass by tree parts, stem, branch, and leaf. The results indicated that DBH and crown length were quite appropriate to estimate leaf biomass. The biomass of single branch was highly correlated with branch collar diameter and relative height of branch in the crown, but not much with stand density, site quality, and tree height. Weibull distribution function would have been appropriate to express vertical distribution of leaf biomass. The shape parameters from 29 sample trees out of 36 were less than 3.6, indicating that vertical distribution of leaf biomass in the crown was displayed by bell-shaped curve, a little inclined toward positive side. Apparent correlationship was obtained between leaf biomass and branch biomass having resulted in linear function equation. The stem biomass occupied around 80% and branch and leaf made up about 20% of total biomass in a single tree. As the level of tree class was increased from class I to class V, the proportion of the stem biomass to total biomass was gradually increased, but that of branch and leaf became decreased.

• 대한원격탐사학회지
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• 제39권5_4호
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• pp.1155-1164
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• 2023

현재 국가산림자원조사(National Forest Inventory, NFI)는 인력에 의한 수목정보를 수집하고 있어 조사 범위와 시간의 한계가 따른다. 항공 Light Detection And Ranging (LiDAR) 및 항공 사진 등을 이용하여 넓은 지역의 수목 정보를 추출하기 위한 연구가 활발하게 진행되고 있으나 수목의 간격이 넓은 지역이거나 수목의 간격이 일정하게 배치된 지역을 대상으로 이루어지고 있어 우리나라 산림지역 특성을 반영하지 못하고 있다. 이에 본 연구에서는 항공 LiDAR를 이용하여 수치표면모델(Digital Surface Model, DSM), 수치표고모델(Digital Elevation Model, DEM), 수목높이모델(Canopy Height Model, CHM) 영상을 생성한 후 local maxima 기법을 통해 수고를 추출하고 산정식을 통해 흉고직경(Diameter at Breast Height, DBH)을 산정하는 방법론을 제안하였다. 제안한 방법론을 통해 추출한 수목의 검출 정확도는 매목지구별 각 88.46%, 86.14%, 84.31%로 나타났으며, 수고 값을 기반으로 산정한 DBH의 평균제곱근오차(Root Mean Squared Error, RMSE)가 5 cm 내외로 나타나 제안한 방법론의 활용 가능성을 확인하였다. 향후 다양한 유형의 산림에 대한 표준화 연구를 진행한다면 수작업으로 이루어지는 국가산림자원조사의 자동화 적용 범위를 확대할 수 있을 것으로 사료된다.

• 인간식물환경학회지
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• 제24권4호
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• pp.441-450
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• 2021

Background and objective: The purpose of study is to analyze the three-dimensional (3D) structure by creating a 3D model for green spaces in a park using unmanned aerial vehicle (UAV) images. Methods: After producing a digital surface model (DSM) and a digital terrain model (DTM) using UAV images taken in Mureung Park in Chuncheon-si, we generated a digital tree height model (DHM). In addition, we used the mean shift algorithm to test the classification accuracy, and obtain accurate tree height and volume measures through field survey. Results: Most of the tree species planted in Mureung Park were Pinus koraiensis, followed by Pinus densiflora, and Zelkova serrata, and most of the shrubs planted were Rhododendron yedoense, followed by Buxus microphylla, and Spiraea prunifolia. The average height of trees measured at the site was 7.8 m, and the average height estimated by the model was 7.5 m, showing a difference of about 0.3 m. As a result of the t-test, there was no significant difference between height values of the field survey data and the model. The estimated green coverage and volume of the study site using the UAV were 5,019 m² and 14,897 m³, respectively, and the green coverage and volume measured through the field survey were 6,339 m² and 17,167 m³. It was analyzed that the green coverage showed a difference of about 21% and the volume showed a difference of about 13%. Conclusion: The UAV equipped with RTK (Real-Time Kinematic) and GNSS (Global Navigation Satellite System) modules used in this study could collect information on tree height, green coverage, and volume with relatively high accuracy within a short period of time. This could serve as an alternative to overcome the limitations of time and cost in previous field surveys using remote sensing techniques.

• Journal of Forest and Environmental Science
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• 제33권3호
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• pp.187-196
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• 2017

The use of unmanned aerial vehicles (UAV) for the estimation of tree height is gaining recognition. This study aims to assess the effectiveness of tree height estimation of Pinus densiflora Sieb. et Zucc. and Pinus koraiensis Sieb. et Zucc. using digital surface model (DSM) generated from UAV-acquired imageries. Images were taken with the $Trimble^{(R)}$ UX5 equipped with Sony ${\alpha}5100$. The generated DSM, together with the digital elevation model (DEM) generated from a digital map of the study areas, were used in the estimation of tree height. Field measurements were conducted in order to generate a regression model and carry out accuracy assessment. The obtained coefficients of determination (R2) and root mean square error (RMSE) for P. densiflora (R2=0.71; RMSE=1.00 m) and P. koraiensis (R2=0.64; RMSE=0.85 m) are comparable to the results of similar studies. The results of the paired two-tailed t-test show that the two tree height estimation methods are not significantly different (p-value=0.04 and 0.10, alpha level=0.01), which means that tree height estimation using UAV imagery could be used as an alternative to field measurement.

• 한국정보과학회논문지:정보통신
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• 제30권4호
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• pp.520-534
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• 2003

본 논문에서는, $a{\times}b$ 출력 버퍼 스위치로 구성된 fat-tree 망의 성능 예측 모형을 제안하고, 스위치에 장착된 버퍼의 개수 증가에 따른 성능 향상 추이를 분석하였다. Buffered 스위치 기법은 스위치 네트웍 내부의 데이타 충돌 문제를 효과적으로 해결할 수 있는 방법으로 널리 알려져 있다. 제안한 성능 예측 모형은 먼저 네트웍 내부 임의 스위치 입력 단에 유입되는 데이타 패킷이 스위치 내부에서 전송되는 유형을 확률적으로 분석하여 수립되었다. 제안한 모형은 스위치에 장착된 버퍼의 개수와 무관하게 출력 버퍼를 장착한 $a{\times}b$ 스위치의 성능, 즉 네트웍 성능 평가의 두 가지 주요 요소인 네트웍 정상상태 처리율(Steady state Throughput, ST)과 네트웍 지연시간(Network Delay)의 예측이 가능하다. 또한 모형의 이해를 도모하기 위하여 지능형 네트워크 트래픽 제어 및 중도 소실 패킷에 대한 다양한 처리 기능 등 최근 개발되는 스위치 네트워크의 부가기능을 배제하고 수식을 정리하였다. 그러나, 제안된 분석 모형은 이들 다양한 성능 향상 기술이 적용된 네트워크, 그리고 다양한 크기의 네트워크 성능분석에도 쉽게 적용이 가능하다. 제안한 수학적 성능 분석 연구의 실효성 검증을 위하여 병행된 시뮬레이션 결과는 상호 미세한 오차 범위 내에서 모형의 예측 데이타와 일치하는 결과를 보여 분석 모형의 타당성을 입증하였다.

• Wind and Structures
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• 제15권5호
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• pp.409-421
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• 2012

In this paper, the method of introducing additional source/sink terms in the turbulence and momentum transport equations was applied to appropriately model the effect of the tree canopy. At first, the new additional source term for the turbulence frequency ${\omega}$ equation in the SST k-${\omega}$ model was proposed through theoretical analogy. Then the new source/sink term model for the SST k-${\omega}$ model was numerically verified. At last, the proposed source term model was adopted in the wind environment optimal design of the twin high-rise buildings of CABR (China Academy of Building Research). Based on the numerical simulations, the technical measure to ameliorate the wind environment was proposed. Using the new inflow boundary conditions developed in the previous studies, it was concluded that the theoretically reasonable source term model of the SST k-${\omega}$ model was applicable for modeling the tree canopy flow and accurate numerical results are obtained.

• 한국경영과학회:학술대회논문집
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• 대한산업공학회/한국경영과학회 2000년도 춘계공동학술대회 논문집
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• pp.235-238
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• 2000

This article presents an adaptive decision tree algorithm for dynamically reasoning machine failure cause out of real-time, large-scale machine status database. On the basis of experiment using semiconductor etching machine, it has been verified that our model outperforms previously proposed decision tree models.