• 한국측량학회지
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• 제35권5호
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• pp.423-430
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• 2017

Recently, data analysis research has been carried out using the deep learning technique in various fields such as image interpretation and/or classification. Various types of algorithms are being developed for many applications. In this paper, we propose a precipitation prediction algorithm based on deep learning with high accuracy in order to take care of the possible severe damage caused by climate change. Since the geographical and seasonal characteristics of Korea are clearly distinct, the meteorological factors have repetitive patterns in a time series. Since the LSTM (Long Short-Term Memory) is a powerful algorithm for consecutive data, it was used to predict precipitation in this study. For the numerical test, we calculated the PWV (Precipitable Water Vapor) based on the tropospheric delay of the GNSS (Global Navigation Satellite System) signals, and then applied the deep learning technique to the precipitation prediction. The GNSS data was processed by scientific software with the troposphere model of Saastamoinen and the Niell mapping function. The RMSE (Root Mean Squared Error) of the precipitation prediction based on LSTM performs better than that of ANN (Artificial Neural Network). By adding GNSS-based PWV as a feature, the over-fitting that is a latent problem of deep learning was prevented considerably as discussed in this study.

• 미술이론과 현장
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• 제10호
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• pp.85-103
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• 2010

Mona Hatoum and community make unlikely bedfellows. From her beginnings as a teenage exile to her maturity as an internationally celebrated artistic nomad, Hatoum defies classification within any single geographical or cultural community. Attempting, however, to locate specific points of contact between her and certain communities in terms of artist-in-residence projects in which she participated might be a particularly fruitful way of circumventing her notorious critical resistance to identity and her refusal of homogeneity. This paper starts with Miwon Kwon's critique of contemporary practices in community-based art, which locate an essentialising force that isolates a single point of commonality and overlooks authentic differences. It then turns to Jean-Luc Nancy's reconceptualization of community as 'unworked' and 'being-in-common' to provide analytical tools for avoiding the dangers of essentialism. By examining the three residencies that Hatoum accepted in the mid-1990s in the light of Nancy's observations and theories, and by bringing the idea of artistic nomadism and that of community into juxtaposition, we hope to show that Hatoum succeeds in finding an equilibrium between art and community, and that this sheds new light on the issues raised in recent discussions on such relationship.

• Plant Resources
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• 제4권3호
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• pp.153-156
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• 2001

Today information is important for man and total fields. Science field is not exception. Currently information age things of information is only useful for man and total industry. So bioinformation is necessary of biodiversity in broadly wide and detailed information. Among information, bioinformation of biodiversity is important and utilization of living things. Among them, the mushroom(higher fungi) are an important part in ecosystem as a decomposer responsible for recycling materials. Many living things today, however, have endangered by environmental pollution and ecological destruction. The higher fungi also are not exception. Mushroom has been used for food sources, pharmacy and forests resources from ancient times. Among biodiversity, database of mushroom is very necessary for university, institute and industry. This DB contains four items of native mushroom(higher fungi) from Korea. first item contain species, genus, family, order class, ad division according to the classification. Second item contain pharmaceutical purpose, food source, culture, toxic, anti-cancer of the application. Third item contain symbiosis, rotten trees of the ecological resources. Fourth item contain geographical distribution and illustrated literature. Information system is also available using KRISTAL II for searches on the WEB in URL http://ruby. kisti. re. kr/∼mushroom.

• 한국자원식물학회:학술대회논문집
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• 한국자원식물학회 2001년도 The 8th International Symposium
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• pp.9-14
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• 2001

Today information is important for man and total fields. Science field is not exception. Currently information age things of information is only useful for man and total industry. So bioinformation is necessary of biodiversity in broadly wide and detailed information. Among information, bioinformation of biodiversity is important and utilization of living things. Among them, the mushroom(higher fungi) are an Important part in ecosystem as a decomposer responsible for recycling materials . Many living things today, however, have endangered by environmental pollution and ecological destruction. The higher fungi also are not exception. Mushroom has been used for food sources, pharmacy and forests resources from ancient times. Among biodiversity, database of mushroom is very necessary for university, institute and industry. This DB contains four items of native mushroom(higher fungi) from Korea. first item contain species, genus, family, order class, ad division according to the classification. Second item contain pharmaceutical purpose, food source, culture, toxic, anti-cancer of the application. Third item contain symbiosis, rotten trees of the ecological resources. Fourth item contain geographical distribution and illustrated literature. Information system is also available using KRISTAL II for searches on the WEB in URL http://ruby. kisti. re. kr/～mushroom

• 대기
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• 제14권2호
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• pp.11-22
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• 2004

A technique on atmospheric correction algorithm to the multi-band reflectance of Landsat TM imagery has been developed using an atmospheric radiation transfer model for eliminating the atmospheric and surface diffusion effects. Despite the fact that the technique of satellite image processing has been continually developed, there is still a difference between the radiance value registered by satellite borne detector and the true value registered at the ground surface. Such difference is caused by atmospheric attenuations of radiance energy transfer process which is mostly associated with the presence of aerosol particles in atmospheric suspension and surface irradiance characteristics. The atmospheric reflectance depend on atmospheric optical depth and aerosol concentration, and closely related to geographical and environmental surface characteristics. Therefore, when the effects of surface diffuse and aerosol reflectance are eliminated from the satellite image, it is actually corrected from atmospheric optical conditions. The objective of this study is to develop an algorithm for making atmospheric correction in satellite image. The study is processed with the correction function which is developed for eliminating the effects of atmospheric path scattering and surface adjacent pixel spectral reflectance within an atmospheric radiation model. The diffused radiance of adjacent pixel in the image obtained from accounting the average reflectance in the $7{\times}7$ neighbourhood pixels and using the land cover classification. The atmospheric correction functions are provided by a radiation transfer model of LOWTRAN 7 based on the actual atmospheric soundings over the Korean atmospheric complexity. The model produce the upward radiances of satellite spectral image for a given surface reflectance and aerosol optical thickness.

• 한국정보시스템학회지:정보시스템연구
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• 제32권4호
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• pp.229-245
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• 2023

Purpose This study aims to understand the inclinations of young job seekers towards "hidden champions" - small but competitive companies that are emerging as potential solutions to the growing disparity between youth-targeted job vacancies and job seekers. We utilize machine learning techniques to discern the appeal of these hidden champions. Design/methodology/approach We examined the characteristics of small and medium-sized enterprises using data sourced from the Ministry of Employment and Labor and Youth Worknet. By comparing the efficacy of five machine learning classification models (i.e., Logistic Regression, Random Forest Classifier, Gradient Boosting Classifier, LGBM Classifier, and XGB Classifier), we discovered that the predictive model utilizing the LGBM Classifier yielded the most consistent performance. Findings Our analysis of the relative significance of preference determinants revealed that industry type, geographical location, and employee count are pivotal factors influencing preference. Drawing from these insights, we propose targeted strategic interventions for policymakers, hidden champions, and young job seekers.

• Corrosion Science and Technology
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• 제22권5호
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• pp.377-386
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• 2023

Aircraft washing is performed periodically for corrosion control. Currently, the aircraft washing interval is qualitatively set according to the geographical conditions of each base. We developed a washing interval determination algorithm based on atmospheric corrosion environment monitoring data at the Republic of Korea Air Force (ROKAF) bases and United States Air Force (USAF) bases to determine the optimal interval. The main factors of the washing interval decision algorithm were identified through hierarchical clustering, sensitivity analysis, and analysis of variance, and criteria were derived. To improve the classification accuracy, we developed a washing interval decision model based on an artificial neural network (ANN). The ANN model was calibrated and validated using the atmospheric corrosion environment monitoring data and washing intervals of the USAF bases. The new algorithm returned a three-level washing interval, depending on the corrosion rate of steel and the results of the ANN model. A new base-specific aircraft washing interval was proposed by inputting the atmospheric corrosion environment monitoring results of the ROKAF bases into the algorithm.

• 한국산림과학회지
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• 제106권3호
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• pp.310-319
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• 2017

본 연구는 참나무시들음병이 수도권에 피해가 집중되어 있는 점을 고려해 북한산, 청계산, 수리산의 시계열 항공사진을 사용하여 감독분류기법(supervised classification)으로 피해목을 분류하였으며, 피해지의 공간적인 특성을 분석하기 위해 피해목 위치의 지형적 특성을 통계처리 하여 고도와 경사와의 밀접한 상관관계를 확인하였다. 또한, Moran's I 통계분석을 이용한 북한산의 Moran's I 값은 2009, 2010, 2012년 각 0.25, 0.32, 0.24, 청계산은 2010, 2012, 2014년 각 0.26, 0.32, 0.22, 수리산은 2012, 2014년 각 0.42, 0.42의 값을 갖으며, 이는 피해목이 군집하여 분포함을 의미한다. 아울러, 피해목 군집의 이동성을 파악하기 위해 hotspot 분석을 실시하여 시계열적으로 hotspot이 이동하는 특성을 확인하였다. 참나무 시들음병의 전체 hotspot 면적(z-score>1.65) 중 고도 200~400 m, 경사 $20{\sim}40^{\circ}$에 분포하는 활엽수 및 혼효림에서의 발생비율은 약 80%로 나타났다. 이는 미래의 피해지역 hotspot은 상기의 지형 및 임상조건에서 발생 또는 이동될 수 있음을 시사한다. 본 연구의 결과는 참나무시들음병의 이동경로 예측의 기초자료로 이용될 수 있으며, 향후 병해충 피해의 사전 방제 및 시스템 구축에 사용될 수 있다.

• 대한토목학회논문집
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• 제31권2B호
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• pp.155-163
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• 2011

본 연구에서는 의사결정나무(CART)기법, 인공신경망모형, 인공위성 원격탐사자료와 지형자료 및 지상 기상관측망자료를 이용하여 토양수분을 산정하는 모형을 개발하였다. 본 모형의 검증을 위하여 사용된 토양수분 관측자료는 용담댐 유역에서 관측된 5개 지점의 토양수분자료를 사용하였다. 가용자료에 대해 CART기법을 적용하여 자료를 분류한 다음 분류된 각 자료집단에 대하여 인공신경망(Artificial Neural Networks)모형을 적용하여 토양수분 분포를 예측하였다. 모형의 학습에 사용된 주천, 부귀, 상전, 안천 지점의 토양수분 산정치는 관측치와 약 0.92-0.96의 상관계수, 약 1.00-1.88%의 평균제곱근오차와 약 0.75-1.45%의 평균절대오차를 보여주었다. 토양수분 추정모형을 검증하기 위해 천천2의 지점에 적용한 결과 약 0.91의 상관계수, 약 3.19%의 평균제곱근오차, 약 2.72%의 평균절대오차를 보여 CART기법과 인공신경망모형을 연계한 토양수분 산정모형이 토양수분 분포제시 활용에 적절한 것으로 판단된다.

• 농업생명과학연구
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• 제43권1호
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• pp.61-71
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• 2009

본 연구는 최근 정부 및 지자체에서 다양하게 추진하고 있는 각종 지역개발사업의 효율적 추진을 위해서 농산촌지역의 지대구분 및 사업추진을 위해 농산어촌지역 지대구분을 위한 구분기준과 지표를 개발하고 지대구분안을 도출하는 것이 목적이다. 연구결과, 도시화지역 6개 읍 면, 준도시화 지역 13개 읍 면, 농촌지역 14개 읍 면, 중산간지역 18개 읍 면, 산간지역 11개 읍 면으로 구분되어 전체적으로 균등한 분포를 나타냈다. 세부적으로 보면, 각 군의 읍지역과 중심기능을 담당하고 있는 일부 거점면이 도시화지역으로 분류되었으며, 반대로 지형적으로 다소 산간지역의 특성이 강한 지역일지라도 수려한 자연경관 및 우수한 관광자원을 보유한 지역의 경우에 평가량이 다소 높게 나타난 것이 특징이다. 결과적으로 같은 군에 위치하거나 인접한 읍 면일지라도 각 읍 면별 지역적 특성은 서로 다른 특성을 내포하고 있기에 당해지역의 발전 잠재력을 극대화 할 수 있도록 지역적 특성을 고려한 사업추진이 절실하게 요구되고 있다.