• 디지털융복합연구
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• 제18권7호
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• pp.73-84
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• 2020

지능정보기술로 인해 나타날 경제·사회의 혁신적 변화에 대응하기 위해 전 세계가 범국가적으로 다양한 노력을 기울이고 있다. 이에 본 연구는 지능정보사회에서 국가 공무원에게 요구되는 지능정보화 역량을 정의하고, 지능정보화 역량을 구성하는 요소들을 파악하여 역량군과 그에 따른 세부역량을 도출하고자 하였다. 이를 위해 우선 블룸의 디지털 텍사노미에 관한 선행연구, 정보화 역량 및 국가 ICT 관련 정책에 대한 문헌분석을 실시하였고, 블룸의 디지털 텍사노미 관점을 본 연구에 맞게 수정·보완하여 이를 기준으로 지능정보사회에서 국가 공무원에게 요구되는 지능정보화 역량을 정의하고, 잠정적 역량 구성요소를 도출하였다. 그리고 5명의 교육(공)학 및 정보화 전문가, 정보화 업무 담당 공무원을 대상으로 전문가 검토를 실시하였고 그 결과, 7개 역량군에서 22가지 역량이 도출되었다. 본 연구를 통해 도출된 지능정보화 역량은 국가 지능정보화 인적역량개발을 강화하고 활성화하기 위한 기초자료로 유용하게 사용될 것으로 기대한다.

• 환경생물
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• 제31권4호
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• pp.233-242
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• 2013

Cyanobacteria (blue-green algae) are not only the first oxygenic organisms on earth but also the foremost primary producers in aquatic environment. Massive growth of cyanobacteria, in eutrophic waters, usually changes the water colour to green and is called as algal (cyanobacterial) bloom or green tide. Cyanobacterial blooms are a result of high levels of primary production by certain species such as Microcystis sp., Anabaena sp., Oscillatoria sp., Aphanizomenon sp. and Phormidium sp. These cyanobacterial species can produce hepatotoxins or neurotoxins as well as malodorous compounds like geosmin and 2-methylisoborneol (MIB). In order to solve the nationwide problem of hazardous cyanobacterial blooms in Korea, the following technically and strategically sound approaches need to be developed. 1) As a long-term strategy, reduction of the nutrients such as phosphorus and nitrogen in our water bodies to below permitted levels. 2) As a short term strategy, field application of combination of already established bloom remediation techniques. 3) Development of emerging convergence technologies based on information and communication technology (ICT), environmental technology (ET) and biotechnology (BT). 4) Finally, strengthening education and creating awareness among students, public and industry for effective reduction of pollution discharge. Considering their ecological roles, a complete elimination of cyanobacteria is not desirable. Hence a holistic approach mentioned above in combination to addressing the issue from a social perspective with cooperation from public, government, industry, academic and research institutions is more pragmatic and desirable management strategy.

• 스마트미디어저널
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• 제5권1호
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• pp.130-136
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• 2016

본 논문에서 제안하는 실시간 해양 이상조류 모니터링 시스템은 직접적으로 적 녹조의 주원인인 플랑크톤을 감지하는 것이 아니라 적조의 동물성 플랑크톤 특성인 수중 내의 산소 감소를 체크하고, 녹조의 식물성 플랑크톤 특성인 수중 내의 질소 감소를 측정한다. 각각의 특성 체크 및 간접적 요소인 수중 내외의 온도, 조도 센서를 이용하여 실시간 감시하는 모듈을 만들고 모듈은 특정 주기에 맞게 신호를 서버로 전송하여 데이터베이스를 형성하고, 이렇게 수집된 데이터는 해양수산청 적 녹조 기준 데이터와 비교 하여 분석하여 알맞은 형태의 정보로 가공한 뒤 사용자에게 정보를 시각화 하여 제공한다. 기존의 광역적 감지 및 감시 시스템이 아닌 지역적 특성을 갖게 되는, 어업을 하지 않는 시간에도 빠르게 대처 가능한 개인사업 맞춤형 양식장 적 녹조 감시 시스템을 제안하였다.

• 상하수도학회지
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• 제31권3호
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• pp.197-204
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• 2017

This study was carried out to apply the UAV(Unmanned Aerial Vehicle) coupled with Multispectral sensor for the algae bloom monitoring in river. The study acquired remote sensing data using UAV on the midstream area of Gum River, one of four major rivers in South Korea. Normalized difference vegetation index (NDVI) is used for monitoring algae change. This study conducted water sampling and analysis in the field for correlating with NDVI values. Among the samples analyzed, the chlorophyll concentration exhibited strong and significant linear relationships with NDVI, and thus NDVI was chosen for algae bloom index to identify emergence aspect of phytoplankton in river. Aerial remote sensing technology can provide more accurate, flexible, cheaper, and faster monitoring methods of detecting and predicting eutrophication and therefore cyanobacteria bloom in water reservoirs compared to currently used technology. As a result, there was high level of correlation in chlorophyll-a and NDVI. It is expected that when this remote water quality and pollution monitoring technology is applied in the field, it would be able to improve capabilities to deal with the river water quality and pollution at the early stage.

• 한국차세대컴퓨팅학회논문지
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• 제14권5호
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• pp.60-70
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• 2018

클라우드 환경에서 다수의 사용자가 물리적 서버를 가상화하여 사용할 수 있도록 편의성을 제공하는 Software Defined Storage(SDS)를 적용하고 있지만 한정된 물리적 자원을 고려하여 공간 효율성을 최적화하는 솔루션이 필요하다. 기존의 데이터 중복제거 시스템에서는 서로 다른 스토리지에 업로드 된 중복 데이터가 중복제거되기 어렵다는 단점이 있다. 본 논문에서는 유사도기반 클러스터링과 다중 계층 블룸 필터를 적용한 분산 중복제거 기법을 제안한다. 라빈 해시를 이용하여 가상 머신 서버들 간의 유사도를 판단하고 유사도가 높은 가상머신들을 클러스터 함으로써 개별 스토리지 노드별 중복제거 효율에 비하여 성능을 향상시킨다. 또한 중복제거 프로세스에 다중 계층 블룸 필터를 접목하여 처리 시간을 단축하고 긍정오류를 감소시킬 수 있다. 실험결과 제안한 방법은 IP주소 기반 클러스터를 이용한 중복제거 기법에 비해 처리 시간의 차이가 없으면서, 중복제거율이 9% 높아짐을 확인하였다.

• 상하수도학회지
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• 제36권4호
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• pp.239-248
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• 2022

The prediction of algal bloom is an important field of study in algal bloom management, and chlorophyll-a concentration(Chl-a) is commonly used to represent the status of algal bloom. In, recent years advanced machine learning algorithms are increasingly used for the prediction of algal bloom. In this study, XGBoost(XGB), an ensemble machine learning algorithm, was used to develop a model to predict Chl-a in a reservoir. The daily observation of water quality data and climate data was used for the training and testing of the model. In the first step of the study, the input variables were clustered into two groups(low and high value groups) based on the observed value of water temperature(TEMP), total organic carbon concentration(TOC), total nitrogen concentration(TN) and total phosphorus concentration(TP). For each of the four water quality items, two XGB models were developed using only the data in each clustered group(Model 1). The results were compared to the prediction of an XGB model developed by using the entire data before clustering(Model 2). The model performance was evaluated using three indices including root mean squared error-observation standard deviation ratio(RSR). The model performance was improved using Model 1 for TEMP, TN, TP as the RSR of each model was 0.503, 0.477 and 0.493, respectively, while the RSR of Model 2 was 0.521. On the other hand, Model 2 shows better performance than Model 1 for TOC, where the RSR was 0.532. Explainable artificial intelligence(XAI) is an ongoing field of research in machine learning study. Shapley value analysis, a novel XAI algorithm, was also used for the quantitative interpretation of the XGB model performance developed in this study.

• 환경생물
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• 제31권2호
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• pp.61-68
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• 2013

Microalgae can grow autotrophically with the supply of light, carbon dioxide and inorganic nutrients in water through photosynthesis. Generally, microalgal growth is limited by the concentrations and relative ratio of nitrogen (N) and phosphorus (P) among the nutrients in the aquatic environment. Each microalga has its specific optimum N : P ratio resulting in dominance in a particular water having similar nutrient composition. Algal bloom is an immense growth of certain microalga commonly cyanobacterium and can be sequestrated by reducing the limiting nutrient, generally P in the freshwater. Moreover, dominance of a less toxic blooming strain can be established by manipulating N : P ratio in the water. On the other hand, microalgal biomass of a certain species can be enhanced by increasing limiting nutrient and adjusting the N : P ratio to the target species. The above-mentioned eco-physiological features of microalgae can be more completely interpreted in connection with their genomic informations. Consequently, microalgal growth regulation which can be achieved on the basis of its eco-physiological and further genomic insights would be helpful not only in the control of algal bloom, but also for an increased yield of algal biomass.

• 한국환경복원기술학회지
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• 제7권5호
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• pp.75-84
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• 2004

Loess, PAC, MACF and plants were applied to the control of the phytoplankton bloom in laboratory and in field, In field experiment using oil fence, 5ppm concentration of coagulant(PAC) was observed to be effective in controlling the cyanobacterial bloom, resulting in 90% removal of cyanobacteria and phytoplankton from the water column, hi case of Synedra sp., however, only 50% of biomass decreased with the same PAC concentration. MACF(micro-air bubble coagulation and floating), a kind of physicochemical method, was applied to the column of the Kyongan stream and resulted in over 80% chlorophyll a and 73.5% TP removal, Chlorophyll a and total phosphorus were effectively removed from water body when 2.0 g/L of loess with the particle radius of 125 ${\mu}m$ was inputted. In case of experiments involving plants, big cone pine, gingko, and pine needle were observed to be effective in restraining phytoplankton bloom at 0.5g/200ml level. During a field test done at Kyungan stream, where Microcystis heavily occurred, Pine needle and big cone pine were observed to be effective on suppressing algal growth.

• 대한수학교육학회지:학교수학
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• 제6권1호
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• pp.21-35
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• 2004

고등학교 수학내용에서 학생들이 가장 어려워하는 삼각함수단원을 중심으로 수행평가 도구를 개발하고 이를 현장에 적용하여 효과를 파악하고자 하였다. 평가도구는 Bloom의 인지적 영역을 중심으로 총 12개의 문항으로 구성되었으며 이에 대한 채점 기준표가 구성되었다. 개발된 도구의 적용성을 알기위해 문항에 대한 양호도검사와 다양한 영역에서 성취도 검사가 고등학생, 208명을 대상으로 2003학년 11월 중에 조사되었다. 양호도 검사에서는 본 평가도구가 우수한 것으로 나타났으며, 성취도 검사에서는 남학생이 여학생보다, 과학고 학생이 일반고 학생보다 우수하게 나타났으며, 지역별의 차이는 나타나지 않았다.

• 대한원격탐사학회:학술대회논문집
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• 대한원격탐사학회 2006년도 Proceedings of ISRS 2006 PORSEC Volume I
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• pp.483-486
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• 2006

The study describes the monitoring of the Bay of Bengal as a ballast water exchangeable sea using MODIS/Aqua-derived diffuse attenuation coefficient (K(490)) synchronized with in situ ballast water sampling and analysis along the LNG carrier's route between Japan and Qatar from 2002 to 2005. Based on the relationship between K(490) and corresponding in situ plankton cell densities, the Bay of Bengal is recognized as a ballast water exchangeable sea to meet the regulation of ballast water performance standard of International Maritime Organization (IMO). Furthermore the Bay of Bengal with more than 200m depth and more than 200 nautical mile distance from shore is extracted based on the regulation of ballast water exchange area of IMO. However, an anomalously high K(490) area is found off the coast of Sri Lanka during the northeast monsoon in 2005, which corresponds higher cell densities than the criterion set by the regulation of IMO. The phenomenon of high cell density in the Bay of Bengal seems to be related with the phytoplankton bloom during the northeast monsoon. Seasonal and annual variability of phytoplankton bloom will be investigated to establish an early routing system for avoiding the high cell density area in advance.