• 제목/요약/키워드: normalized data

검색결과 1,171건 처리시간 0.033초

Analyzing Soybean Growth Patterns in Open-Field Smart Agriculture under Different Irrigation and Cultivation Methods Using Drone-Based Vegetation Indices

  • Kyeong-Soo Jeong;Seung-Hwan Go;Kyeong-Kyu Lee;Jong-Hwa Park
    • 대한원격탐사학회지
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    • 제40권1호
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    • pp.45-56
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    • 2024
  • Faced with aging populations, declining resources, and limited agricultural productivity, rural areas in South Korea require innovative solutions. This study investigated the potential of drone-based vegetation indices (VIs) to analyze soybean growth patterns in open-field smart agriculture in Goesan-gun, Chungbuk Province, South Korea. We monitored multi-seasonal normalized difference vegetation index (NDVI) and the normalized difference red edge (NDRE) data for three soybean lots with different irrigation methods (subsurface drainage, conventional, subsurface drip irrigation) using drone remote sensing. Combining NDVI (photosynthetically active biomass, PAB) and NDRE (chlorophyll) offered a comprehensive analysis of soybean growth, capturing both overall health and stress responses. Our analysis revealed distinct growth patterns for each lot. LotA(subsurface drainage) displayed early vigor and efficient resource utilization (peaking at NDVI 0.971 and NDRE 0.686), likely due to the drainage system. Lot B (conventional cultivation) showed slower growth and potential limitations (peaking at NDVI 0.963 and NDRE 0.681), suggesting resource constraints or stress. Lot C (subsurface drip irrigation) exhibited rapid initial growth but faced later resource limitations(peaking at NDVI 0.970 and NDRE 0.695). By monitoring NDVI and NDRE variations, farmers can gain valuable insights to optimize resource allocation (reducing costs and environmental impact), improve crop yield and quality (maximizing yield potential), and address rural challenges in South Korea. This study demonstrates the promise of drone-based VIs for revitalizing open-field agriculture, boosting farm income, and attracting young talent, ultimately contributing to a more sustainable and prosperous future for rural communities. Further research integrating additional data and investigating physiological mechanisms can lead to even more effective management strategies and a deeper understanding of VI variations for optimized crop performance.

무인항공기 데이터의 영역 확장법 적용을 통한 정규수치표면모델 추출 및 경사도 파라미터 설정 (Normalized Digital Surface Model Extraction and Slope Parameter Determination through Region Growing of UAV Data)

  • 염준호;이원희;김태헌;한유경
    • 한국측량학회지
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    • 제37권6호
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    • pp.499-506
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    • 2019
  • 정규수치표면모델(NDSM: Normalized Digital Surface Model)은 원격탐사데이터의 상세 분석을 위한 핵심 적인 자료로 사용된다. 지상기준높이인 정규수치표면모델을 생성하기 위한 가장 간단한 방법은 수치표면모델(DSM: Digital Surface Model)에서 수치지형모델(DTM: Digital Terrain Model)을 차분하는 것이지만, 무인항공기 데이터의 경우 높은 해상도의 특성상 식생, 도심 구조물 등 많은 수의 복잡한 지형지물을 포함하고 있어 정확한 수치지형모델을 추출하기 어렵다. 본 연구에서는 무인항공기 데이터의 고해상도 특성을 잘 살리고 비용효율적인 수치지형모델 생성이 가능하도록 RGB 기반 식생 지수인 ExG (Excess Green)를 이용하여 낮은 ExG 값을 갖는 영역 확장법의 초기 시드점을 선정하였다. 이때 국소적으로 낮은 식생지수 값을 갖는 초기 시드점이 잘못 추출되는 문제를 해결하기 위하여 지역적 윈도우 분석을 적용하였다. 이후, 해당 위치의 수치표면모델값을 바탕으로 영역 확장법을 적용하여 이웃하는 지면 화소들을 병합하였다. 영역 확장법 적용을 위해 경사도 파라미터가 사용되었으며 최종적으로 병합된 세그먼트의 크기가 0.25㎡ 초과일 경우 초기 시드점을 지면점으로 결정하였다. 다양한 경사도 파라미터 값을 설정하여 무인항공기 데이터 기반 정규수치표면모델 생성의 최적 경사도 기준값을 도출하고자 하였다. 최종적으로 추출된 지면점들에 대한 정확도 평가를 수행하였으며 지면점들에 보간법을 적용하여 정규수치표면모델을 생성하고 제안 기법을 농업지역에 적용하여 농작물의 지상기준높이 추출 및 농업 모니터링 가능성을 검증하였다.

점진적 샘플링과 정규 상호정보량을 이용한 온라인 기계학습 공조기 급기온도 예측 모델 개발 (Development of Online Machine Learning Model for AHU Supply Air Temperature Prediction using Progressive Sampling and Normalized Mutual Information)

  • 추한경;신한솔;안기언;라선중;박철수
    • 대한건축학회논문집:구조계
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    • 제34권6호
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    • pp.63-69
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    • 2018
  • The machine learning model can capture the dynamics of building systems with less inputs than the first principle based simulation model. The training data for developing a machine learning model are usually selected in a heuristic manner. In this study, the authors developed a machine learning model which can describe supply air temperature from an AHU in a real office building. For rational reduction of the training data, the progressive sampling method was used. It is found that even though the progressive sampling requires far less training data (n=60) than the offline regular sampling (n=1,799), the MBEs of both models are similar (2.6% vs. 5.4%). In addition, for the update of the machine learning model, the normalized mutual information (NMI) was applied. If the NMI between the simulation output and the measured data is less than 0.2, the model has to be updated. By the use of the NMI, the model can perform better prediction ($5.4%{\rightarrow}1.3%$).

다중매체로 이루어진 해상 자율망에서 이종 매체 선택이 가능하고 정규화된 위치와 전송특성에 의한 라우팅 (A Heterogeneous-carrier Selectable Routing Scheme Based on Normalized Location and Transmission Characteristics (MCS-NLTC) for Multi-carrier MANETs at Sea)

  • 손주영
    • 한국항해항만학회지
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    • 제38권4호
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    • pp.343-348
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    • 2014
  • 새로운 해상통신망 모델로 자율망 모델과 광대역 무선접속기술의 다양성과 혼재성을 활용하고 경로상의 홉 단위로 최적노드와 캐리어를 선택하는 경로배정방식(MCS-NLTC)을 새롭게 제안한다. 여기서는 일반적인 홉 수가 아니라 목적지 선박과의 거리(위치정보)가 기본적인 기준이 되고 캐리어의 전송특성의 정규값을 가중치로 삼아 최적경로를 탐색하는 방식이다. 위치정보가 기본적으로 고려되기 때문에 탐색 수렴성이 개선되어 탐색시간이 크게 단축되고 경로의 최적성도 향상되었다. 기존 전송특성의 절대값을 상호 비교하는 최다승방식(OMH-MW)과 전송특성의 정규값만을 고려하는 방식(MCS-NTC)과 성능을 비교하여 이를 확인하였다.

정규 거리에 기반한 시계열 데이터베이스의 유사 검색 기법 (Similarity Search in Time Series Databases based on the Normalized Distance)

  • 이상준;이석호
    • 한국정보과학회논문지:데이타베이스
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    • 제31권1호
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    • pp.23-29
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    • 2004
  • 본 논문에서는 정규 거리에 기반 한 유사 시퀀스의 검색 기법을 제안한다. 시퀀스의 형태가 중요한 관심 사항인 응용에서 정규 거리는 단순한 Lp 거리에 비해 적합한 유사도라 할 수 있다. 이러한 정규 거리에 기반 한 질의를 처리하기 위한 기존의 기법들은 시퀀스의 평균을 구한 후 이를 이용하여 시퀀스를 수직 이동하는 전처리 과정을 가지고 있다. 제안된 기법은 시퀀스의 인접한 두 요소들 간의 변이가 정규화 과정에 불변이라는 속성을 이용하여 수직 이동의 전처리 과정 없이 특징 벡터를 추출한 후 이를 R-tree와 같은 공간 접근 기법을 이용하여 인덱싱한다. 제안된 기법은 비슷한 형태의 시퀀스를 검색할 수 있으며 착오 누락이 얼음을 보장한다. 실제 주식 데이타를 이용한 실험을 통해 제안된 기법의 성능을 확인하였다.

도시 열환경 분석을 위한 공간정보 빅데이터 구축 (Construction of Spatial Information Big Data for Urban Thermal Environment Analysis)

  • 이준호;윤성환
    • 대한건축학회논문집:계획계
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    • 제36권5호
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    • pp.53-58
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    • 2020
  • The purpose of this study is to build a database of Spatial information Bigdata of cities using satellite images and spatial information, and to examine the correlations with the surface temperature. Using architectural structure and usage in building information, DEM and Slope topographical information for constructed with 300 × 300 mesh grids for Busan. The satellite image is used to prepare the Normalized Difference Built-up Index (NDBI), Normalized Difference Vegetation Index (NDVI), Bare Soil Index (BI), and Land Surface Temperature (LST). In addition, the building area in the grid was calculated and the building ratio was constructed to build the urban environment DB. In architectural structure, positive correlation was found in masonry and concrete structures. On the terrain, negative correlations were observed between DEM and slope. NDBI and BI were positively correlated, and NDVI was negatively correlated. The higher the Building ratio, the higher the surface temperature. It was found that the urban environment DB could be used as a basic data for urban environment analysis, and it was possible to quantitatively grasp the impact on the architecture and urban environment by adding local meteorological factors. This result is expected to be used as basic data for future urban environment planning and disaster prevention data construction.

Goodness-of-fit test for the logistic distribution based on multiply type-II censored samples

  • Kang, Suk-Bok;Han, Jun-Tae;Cho, Young-Seuk
    • Journal of the Korean Data and Information Science Society
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    • 제25권1호
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    • pp.195-209
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    • 2014
  • In this paper, we derive the estimators of the location parameter and the scale parameter in a logistic distribution based on multiply type-II censored samples by the approximate maximum likelihood estimation method. We use four modified empirical distribution function (EDF) types test for the logistic distribution based on multiply type-II censored samples using proposed approximate maximum likelihood estimators. We also propose the modified normalized sample Lorenz curve plot for the logistic distribution based on multiply type-II censored samples. For each test, Monte Carlo techniques are used to generate the critical values. The powers of these tests are also investigated under several alternative distributions.

냉방부하에 영향을 미치는 외기 환경조건의 상관관계에 관한 연구 (A Study on Correlation of Outdoor Environmental Condition about Cooling Load)

  • 이제묘
    • 설비공학논문집
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    • 제24권11호
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    • pp.759-766
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    • 2012
  • To estimate the cooling load for the following day, outdoor temperature and humidity are needed in hourly base. But the meteorological administration forecasts only maximum and minimum temperature. New methodology is proposed for predicting hourly outdoor temperature and humidity by using the forecasted maximum and minimum temperature. The correlations for normalized outdoor temperature and specific humidity has been derived from the weather data for five years at Seoul, Daejeon and Pusan. The correlations for normalized temperature are independent of date, while the correlations for specific humidity are linearly dependent on date. The predicted results show fairly good agreement with the measured data. The prediction program is also developed for hourly outdoor dry bulb temperature, specific humidity, dew point, relative humidity, enthalpy and specific volume.

점프유형에 따른 하지의 근 활동 형태연구(근전도 데이터 표준화 방법을 중심으로) (Analysis of Muscle Activities of Lower Extremity in Jumping Pattern)

  • 이성철;황인승;조영재;김선정
    • 한국운동역학회지
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    • 제15권2호
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    • pp.155-165
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    • 2005
  • The purpose of this study was to compare the muscle activities of Double Legged Jump (DLJ) and Single Legged Jump (SLJ) by the normalization of muscle activity. Eight college students without the lower extremity injuries were selected as subjects for collecting EMG data of vastus medialis and gastrocnemius. The entire section of motion was established as eccentric and concentric contractions, and each of the contractions was divided into three sections with equal timing intervals, which becomes a total of 6 phases. The EMG data of each phase was integrated and normalized. The muscle activities of the vastus medialis for both eccentric and concentric contractions were significantly different between DLJ and SLJ(p<.05). The increase in overall muscle activity of SLJ was 33.6%. Approximately, there was an increase of 25.9% in eccentric contraction and 40% in concentric contraction. Moreover, the data of the muscle activity of gastrocnemius was similar to the data of the muscle activity of vastus medialis. In conclusion, this research suggests muscle activity of a certain motion can be normalized for an analysis of another motion.

The Comparison of the SIFT Image Descriptor by Contrast Enhancement Algorithms with Various Types of High-resolution Satellite Imagery

  • Choi, Jaw-Wan;Kim, Dae-Sung;Kim, Yong-Min;Han, Dong-Yeob;Kim, Yong-Il
    • 대한원격탐사학회지
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    • 제26권3호
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    • pp.325-333
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    • 2010
  • Image registration involves overlapping images of an identical region and assigning the data into one coordinate system. Image registration has proved important in remote sensing, enabling registered satellite imagery to be used in various applications such as image fusion, change detection and the generation of digital maps. The image descriptor, which extracts matching points from each image, is necessary for automatic registration of remotely sensed data. Using contrast enhancement algorithms such as histogram equalization and image stretching, the normalized data are applied to the image descriptor. Drawing on the different spectral characteristics of high resolution satellite imagery based on sensor type and acquisition date, the applied normalization method can be used to change the results of matching interest point descriptors. In this paper, the matching points by scale invariant feature transformation (SIFT) are extracted using various contrast enhancement algorithms and injection of Gaussian noise. The results of the extracted matching points are compared with the number of correct matching points and matching rates for each point.