• Title/Summary/Keyword: 원격 강의

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Estimation of High Resolution Sea Surface Salinity Using Multi Satellite Data and Machine Learning (다종 위성자료와 기계학습을 이용한 고해상도 표층 염분 추정)

  • Sung, Taejun;Sim, Seongmun;Jang, Eunna;Im, Jungho
    • Korean Journal of Remote Sensing
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    • v.38 no.5_2
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    • pp.747-763
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    • 2022
  • Ocean salinity affects ocean circulation on a global scale and low salinity water around coastal areas often has an impact on aquaculture and fisheries. Microwave satellite sensors (e.g., Soil Moisture Active Passive [SMAP]) have provided sea surface salinity (SSS) based on the dielectric characteristics of water associated with SSS and sea surface temperature (SST). In this study, a Light Gradient Boosting Machine (LGBM)-based model for generating high resolution SSS from Geostationary Ocean Color Imager (GOCI) data was proposed, having machine learning-based improved SMAP SSS by Jang et al. (2022) as reference data (SMAP SSS (Jang)). Three schemes with different input variables were tested, and scheme 3 with all variables including Multi-scale Ultra-high Resolution SST yielded the best performance (coefficient of determination = 0.60, root mean square error = 0.91 psu). The proposed LGBM-based GOCI SSS had a similar spatiotemporal pattern with SMAP SSS (Jang), with much higher spatial resolution even in coastal areas, where SMAP SSS (Jang) was not available. In addition, when tested for the great flood occurred in Southern China in August 2020, GOCI SSS well simulated the spatial and temporal change of Changjiang Diluted Water. This research provided a potential that optical satellite data can be used to generate high resolution SSS associated with the improved microwave-based SSS especially in coastal areas.

Machine Learning Based MMS Point Cloud Semantic Segmentation (머신러닝 기반 MMS Point Cloud 의미론적 분할)

  • Bae, Jaegu;Seo, Dongju;Kim, Jinsoo
    • Korean Journal of Remote Sensing
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    • v.38 no.5_3
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    • pp.939-951
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    • 2022
  • The most important factor in designing autonomous driving systems is to recognize the exact location of the vehicle within the surrounding environment. To date, various sensors and navigation systems have been used for autonomous driving systems; however, all have limitations. Therefore, the need for high-definition (HD) maps that provide high-precision infrastructure information for safe and convenient autonomous driving is increasing. HD maps are drawn using three-dimensional point cloud data acquired through a mobile mapping system (MMS). However, this process requires manual work due to the large numbers of points and drawing layers, increasing the cost and effort associated with HD mapping. The objective of this study was to improve the efficiency of HD mapping by segmenting semantic information in an MMS point cloud into six classes: roads, curbs, sidewalks, medians, lanes, and other elements. Segmentation was performed using various machine learning techniques including random forest (RF), support vector machine (SVM), k-nearest neighbor (KNN), and gradient-boosting machine (GBM), and 11 variables including geometry, color, intensity, and other road design features. MMS point cloud data for a 130-m section of a five-lane road near Minam Station in Busan, were used to evaluate the segmentation models; the average F1 scores of the models were 95.43% for RF, 92.1% for SVM, 91.05% for GBM, and 82.63% for KNN. The RF model showed the best segmentation performance, with F1 scores of 99.3%, 95.5%, 94.5%, 93.5%, and 90.1% for roads, sidewalks, curbs, medians, and lanes, respectively. The variable importance results of the RF model showed high mean decrease accuracy and mean decrease gini for XY dist. and Z dist. variables related to road design, respectively. Thus, variables related to road design contributed significantly to the segmentation of semantic information. The results of this study demonstrate the applicability of segmentation of MMS point cloud data based on machine learning, and will help to reduce the cost and effort associated with HD mapping.

Efficient Deep Learning Approaches for Active Fire Detection Using Himawari-8 Geostationary Satellite Images (Himawari-8 정지궤도 위성 영상을 활용한 딥러닝 기반 산불 탐지의 효율적 방안 제시)

  • Sihyun Lee;Yoojin Kang;Taejun Sung;Jungho Im
    • Korean Journal of Remote Sensing
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    • v.39 no.5_3
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    • pp.979-995
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    • 2023
  • As wildfires are difficult to predict, real-time monitoring is crucial for a timely response. Geostationary satellite images are very useful for active fire detection because they can monitor a vast area with high temporal resolution (e.g., 2 min). Existing satellite-based active fire detection algorithms detect thermal outliers using threshold values based on the statistical analysis of brightness temperature. However, the difficulty in establishing suitable thresholds for such threshold-based methods hinders their ability to detect fires with low intensity and achieve generalized performance. In light of these challenges, machine learning has emerged as a potential-solution. Until now, relatively simple techniques such as random forest, Vanilla convolutional neural network (CNN), and U-net have been applied for active fire detection. Therefore, this study proposed an active fire detection algorithm using state-of-the-art (SOTA) deep learning techniques using data from the Advanced Himawari Imager and evaluated it over East Asia and Australia. The SOTA model was developed by applying EfficientNet and lion optimizer, and the results were compared with the model using the Vanilla CNN structure. EfficientNet outperformed CNN with F1-scores of 0.88 and 0.83 in East Asia and Australia, respectively. The performance was better after using weighted loss, equal sampling, and image augmentation techniques to fix data imbalance issues compared to before the techniques were used, resulting in F1-scores of 0.92 in East Asia and 0.84 in Australia. It is anticipated that timely responses facilitated by the SOTA deep learning-based approach for active fire detection will effectively mitigate the damage caused by wildfires.

Analysis on Cloud-Originated Errors of MODIS Leaf Area Index and Primary Production Images: Effect of Monsoon Climate in Korea (MODIS 엽면적지수 및 일차생산성 영상의 구름 영향 오차 분석: 우리나라 몬순기후의 영향)

  • Kang, Sin-Kyu
    • The Korean Journal of Ecology
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    • v.28 no.4
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    • pp.215-222
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    • 2005
  • MODIS (Moderate Resolution Image Spectrometer) is a core satellite sensor boarded on Terra and Aqua satellite of NASA Earth Observing System since 1999 and 2001, respectively. MODIS LAI, FPAR, and GPP provide useful means to monitor plant phonology and material cycles in terrestrial ecosystems. In this study, LAI, FPAR, and GPP in Korea were evaluated and errors associated with cloud contamination on MODIS pixels were eliminated for years $2001\sim2003$. Three-year means of cloud-corrected annual GPP were 1836, 1369, and 1460g C $m^{-2}y^{-1}$ for evergreen needleleaf forest, deciduous broadleaf forest, and mixed forest, respectively. The cloud-originated errors were 8.5%, 13.1%, and 8.4% for FPAR, LAI, and GPP, respectively. Summertime errors from June to September explained by 78% of the annual accumulative errors in GPP. This study indicates that cloud-originated errors should be mitigated for practical use of MODIS vegetation products to monitor seasonal and annual changes in plant phonology and vegetation production in Korea.

Using Web as CAI in the Classroom of Information Age (정보화시대를 대비한 CAI로서의 Web 활용)

  • Lee, Kwang-Hi
    • Journal of The Korean Association of Information Education
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    • v.1 no.1
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    • pp.38-48
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    • 1997
  • This study is an attempt to present a usage of the Web as CAI in the classroom and to give a direction to the future education in the face of information age. Characteristcs of information society, current curriculum, educational and teacher education are first analyzed in this article. The features of internet and 'Web are then summarized to present benefits of usage in the classroom as a CAI tool. The literature shows several characteristics of information society as follows : a technological computer, a provision and sharing of information, multi functional society, a participative democracy', an autonomy, a time value..A problem solving and 4 Cs(e.g., cooperation, copying, communication, creativity) are newly needed in this learning environment. The Internet is a large collection of networks that are tied together so that users can share their vast resources, a wealth of information, and give a key to a successful, efficient. individual study over a time and space. The 'Web increases an academic achievement, a creativity, a problem solving, a cognitive thinking, and a learner's motivation through an easy access to : documents available on the Internet, files containing programs, pictures, movies, and sounds from an FTP site, Usenet newsgroups, WAIS seraches, computers accessible through telnet, hypertext document, Java applets and other multimedia browser enhancements, and much more, In the Web browser will be our primary tool in searching for information on the Internet in this information age.

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The Establishment and Application of Very Short Range Forecast of Precipitation System (초단시간 강수예보시스템 구축 및 활용)

  • Choi, Ji-Hye;Nam, Kyung-Yeub;Suk, Mi-Kyung;Choi, Byoung-Cheol
    • Proceedings of the Korea Water Resources Association Conference
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    • 2006.05a
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    • pp.1515-1519
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    • 2006
  • 본 연구에서는 초단시간 강수예보(VSRF, Very Short-Range Forecast of precipitation) 시스템 구축 현황을 소개하고자 한다. VSRF 모델은 레이더 반사도 자료와 지상 AWS 자료를 이용하여 레이더-AWS 강우강도를 산출하는 강수분석과정과 분석된 강수량 자료와 중규모 수치예보장을 사용하여 외삽법에 의한 초단시간 강수예보를 수행하는 예보과정, 실시간으로 산출된 강수예보 자료를 검증하고 홈페이지에 제공하는 자료지원과정으로 구성된다. 본 연구에서는 모델의 예보능력을 향상시키기 위해 크게 두 가지 측면에서 모델을 개선하였다. 첫째는 모델의 입력자료인 레이더-AWS 강우강도 자료를 기상연구소 원격탐사연구실에서 운영하던 WPMM (Window Probability Matching Method)과 기상청 기상레이더과에서 운영하던 RQPE(Radar Quantitative Precipitation Estimation)의 알고리즘을 통합하여 정확한 강우강도 자료인 레이더-AWS 강우강도(RAR, Radar-AWS Rain rate) 시스템을 구축하여 개선하였으며, 둘째는 외삽과정을 통한 예보가 3시간이 지나면 예측능력이 감소하는 문제점을 보완하기 위해 현업 중규모 모델(RDAPS, Regional Data Assimilation and Prediction System)의 예측강수와 병합하여 모델을 개선하였다. 또한 이를 시계열 검증 및 공간 검증하는 실시간 검증 시스템을 구축하여 실시간으로 모델의 정확성을 평가하고 있다. 그 결과 입력자료 개선을 통한 모델의 정확도는 크게 향상된 결과는 볼 수 없었지만 미약하게 향상된 것을 확인할 수 있었으며, 모델의 병합을 통한 모델의 개선은 예측 3시간 이후부터는 50% 정도 향상되었다.의 대안을 제시하고자 한다.X>${\mu}_{max,A}$는 최대암모니아 섭취률을 이용하여 구한 결과 $0.65d^{-1}$로 나타났다.EX>$60%{\sim}87%$가 수심 10m 이내에 분포하였고, 녹조강과 남조강이 우점하는 하절기에는 5m 이내에 주로 분포하였다. 취수탑 지점의 수심이 연중 $25{\sim}35m$를 유지하는 H호의 경우 간헐식 폭기장치를 가동하는 기간은 물론 그 외 기간에도 취수구의 심도를 표층 10m 이하로 유지 할 경우 전체 조류 유입량을 60% 이상 저감할 수 있을 것으로 조사되었다.심볼 및 색채 디자인 등의 작업이 수반되어야 하며, 이들을 고려한 인터넷용 GIS기본도를 신규 제작한다. 상습침수지구와 관련된 각종 GIS데이타와 각 기관이 보유하고 있는 공공정보 가운데 공간정보와 연계되어야 하는 자료를 인터넷 GIS를 이용하여 효율적으로 관리하기 위해서는 단계별 구축전략이 필요하다. 따라서 본 논문에서는 인터넷 GIS를 이용하여 상습침수구역관련 정보를 검색, 처리 및 분석할 수 있는 상습침수 구역 종합정보화 시스템을 구축토록 하였다.N, 항목에서 보 상류가 높게 나타났으나, 철거되지 않은 검전보나 안양대교보에 비해 그 차이가 크지 않은 것으로 나타났다.의 기상변화가 자발성 기흉 발생에 영향을 미친다고 추론할 수 있었다. 향후 본 연구에서 추론된 기상변화와 기흉 발생과의 인과관계를 확인하고 좀 더 구체화하기 위한 연구가 필요할 것이다.게 이루어질 수 있을 것으로 기대된다.는 초과수익률이 상승하지만, 이후로는 감소하므로, 반전거래전략을 활용하는 경우 주식투자기간은 24개월이하의 중단기가 적합함을 발견하였다. 이상의 행태적 측면과 투자성과측면의 실증결과를 통하여 한국주식시장에

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Development of a Dynamic Deformable Rubber Membrane Parapet to Cope with the Long Term Sea Level Rise and the Abnormal Waves (장기해수면 상승 및 이상파랑에 대비한 동적 가변형 고무막체 파라펫 개발)

  • Kim, Sun-Sin;Chun, In-Sik;Lee, Young-Gun;Ko, Jang-Hee;Hong, Seung-Ik
    • Journal of Korean Society of Coastal and Ocean Engineers
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    • v.23 no.1
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    • pp.34-42
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    • 2011
  • It's been reported that the global warming effect has invoked the ever increasing typhoon intensity and long-term sea level rise which jointly cause severe wave overtopping over breakwaters or shore dykes. A simple measure to cope with this undesirable change may be just to increase the crest height of the dykes and breakwaters. This is surely effective to prevent wave overtopping, but it also decreases the seaward visibility of coastal waterfront. In this paper, a dynamic deformable rubber membrane parapet which not only reduces wave overtopping in storm period but also secures seascapes in normal days is presented. Several optimal configurations of the parapet are proposed. Through numerical analyses using a nonlinear finite element model and hydraulic experiments, the air controlled expansion and contraction of the parapets, their behavior against wave overtopping and structural stability are investigated.

A Study on the Preference of the Website Structure Related the Culture -with Emphasis on the Usability Testing of the Prototype of Each Country. (문화권별 웹 사이트 구조의 선호에 관한 연구 - 프로토타입의 사용성 평가를 통한 검증을 중심으로)

  • 김정하;이건표
    • Archives of design research
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    • v.16 no.2
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    • pp.161-170
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    • 2003
  • This study aims to understanding the effects of culture on websites with emphasis on the website structure and navigation. The website is inherently‘cultural’because anyone around the world can access to website if he or she is equipped with appropriate equipment. For the importance of cultural role in website, various researches have been conducted to understand the relationship between culture and website. However they tended to focus mainly on phenomenal matters such as color, layout, icon etc. There have been not so many thorough attempts to causal relationships between website and‘thick culture’in depth. The study conducted cross-cultural usability testing of websites between Korea and America. At first, representative I-commerce websites of Korea and America were selected and they were analyzed by the selected frameworks such as layout, display type, element type, and the relationship with homepage and sub-page navigation. The results were used to construct typical prototypes of website for Korea and America for experiment. Two websites were used for cross-cultural usability testing though specially-developed remote testing. 20 users from each country participated in the usability testing. The result shows that Korean users peformed better usability testing for Korean style structure of website while American counterparts showed better performances in American style of websites. Other various significant findings were revealed.

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A Design and Implementation of the Management Sever for the Gateway Supporting Home Networking Using the UML (UML을 이용한 흠 네트워킹 지원 게이트웨이 관리 서버 설계 및 구현)

  • 권진혁;민병조;강명석;남의석;김학배
    • Journal of the Korea Computer Industry Society
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    • v.5 no.3
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    • pp.393-404
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    • 2004
  • Recently, public home have used a more than two computer connected with network, and several home appliances using independently with internet or network are developing to be related closely with the network. Therefore, the home utilized for a simple terminal of the global network in the past is being expanded to another part of the sub network. For a variety of connecting home-area protocols with the existing existing network, we require a new Residential Gateway(RG) that does not only make the home-area network operating in the sub network but also connects to the external network. In this paper, RG has intrinsic limits against flexible service due to IP address assignment and hardware capacity. In order to solve this problem in the RG, we propose a Management Server(MS). The MS that offers the integrated managements and control services for a variety of devices connected the RG in the home-area. It can not only solve the dynamic IP address assigning problem but also assigns private IP addresses to the home network devices through the Network Address Translation(NAT). It also provides somewhat useful functions for the home network and the RG for other additional services. <중략> The MS is using a SNMP protocol for managing the RG in the domain, a polling method of the MS and the RG compose a sequence polling method, a polling method using a multi-process and a multi-thread. In this paper, we introduce a problem with polling method separately, show a polling method between the MS and the RG using a multi-thread.

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Farm Land Use Classification for the Planning of Planting of Eucalyptus Spp. at Mato Grosso do Sul of Brazil Using Remote Sensing and Geographic Information System (브라질 Mato Grosso do Sul 주에서의 유칼리나무 식재계획(植栽計劃)을 위한 농장토지이용구분(農場土地利用區分)에 관한 연구(硏究) - 원격탐사기술(遠隔探査技術)과 지리정보(地理情報)시스템(GIS)의 적용(適用) -)

  • Woo, Jong-Choon;Nobrega, Ricardo Campos;Imana-Encinas, Jose
    • Journal of Korean Society of Forest Science
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    • v.88 no.2
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    • pp.157-168
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    • 1999
  • This paper analyzed vegetation and land use classification, slope and permanent preservation and legal reserves on the farm Jangada and Jamaica-Mato Grosso do Sul, Brazil, using satellite image for assisting the planning of planting Eucalyptus spp. This part of the State of Mato Grosso do Sul represents an important geopolitcal area, since it is located on the borders of Bolivia and Paraguay. Also exportation of goods can be achieved through hydrovias extending to Buenos Aires, Argentina-through the Paraguay River. Also there are road and railroad connection which link the soutreastern part of Brazil to the Andean countries. The vegetation map from sheet SF 21-Campo Grande of the RADAMBRASIL Project was used as the basis for the preliminary interpretation of coverage, and complemented by a visit of the field. After the initial interpretation of the image, definition of classes of use and land occupation were made, and files of spectral signatures were created. On the farms Jamaica and Jangada Open Arboreal Savanna and Grass Savanna are the predominant physiognomies occupying 68% of total area. In spite of the results being satisfactory at the present moment, the development of this project should be revised and adjusted based on the evaluations already made, including a greater detailing of environmental components, principally with respect to soil and topography.

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