• The KIPS Transactions:PartB
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• v.18B no.5
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• pp.291-294
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• 2011

Red tide is a temporary natural phenomenon to change sea color by harmful algal blooms, which finfish and shellfish die en masse. There have been many studies on red tide due to increasing of harmful algae damage of fisheries in Korea. Particularly, red tide damage can be minimized by means of prediction of red tide blooms. However, the most of red tide research in Korea has been focused only classification of red tide which it is not enough for predicting red tide blooms. In this paper, we proposed the red tide blooms prediction method using fuzzy reasoning.

• Smart Media Journal
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• v.7 no.2
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• pp.34-39
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• 2018

There are many studies on red tide due to the continuous increase in damage to domestic fish and shell farms by the harmful red tide. However, there is insufficient domestic research of identifying harmful red tide algae that automatically recognizes red tide images. In this paper, we propose a red tide image classification method using deep learning based open source. To solve the problem of recognition of various images of red tide algae, the proposed method is implemented by using tensorflow framework and Google image classification model.

• Journal of the Korean Society of Marine Environment & Safety
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• v.20 no.4
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• pp.335-344
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• 2014

To understand the drift-diffusion of HAB(Harmful Algal Bloom) in this paper, we used three-dimensional hydrodynamic model POM(Pringceton Ocean Model) and Lagrangian particle track module. First, the results of residual flow that considered tide, wind, temperature, salinity, and TWC(Tsushima Warm Current) effect was tend to northeast in the coastal area and the flow in the offshore region showed results similar to TWC. To understand of HAB's movement, released each area that southern Kamak bay(Case 1), Mijo coast(Case 2), and southern Mireukdo coast(Case 3) assumption that red tide occurred. The areas where the HAB occurs frequently. As a result of HAB occurred in southern Kamak Bay(Case 1), mainly drifts to Narodo coast and Yeoja bay that located on the west side. Case 2 was mainly drifts to Yokjido coast and Saryangdo coast Especially, HAB occurred in Mireukdo coast(Case 3) relatively many particles drift to eastward as the influence of the TWC.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.16 no.2
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• pp.331-336
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• 2012

Red tide is a temporary natural phenomenon involving harmful algal blooms (HABs) in company with a changing sea color from normal to red or reddish brown, and which has a bad influence on coast environments and sea ecosystems. The HABs have inflicted massive mortality on fin fish and shellfish, damaging the economies of fisheries for almost every year from 1990 in South Korea. There have been many studies on red tide due to increasing damage from red tide on fishing and aquaculture industry. However, internal study of automatic red tide image classification is not enough. Especially, extraction of matching center features for recognizing algae image object is difficult because over 200 species of algae in the world have a different size and features. Previously studies used a few type of red tide algae for image classification. In this paper, we proposed the red tide image recognition method using NMF and revison of rotation angle for enhancing of recognition of red tide algae image.

• Journal of Environmental Impact Assessment
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• v.16 no.2
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• pp.121-127
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• 2007

본 연구의 목적은 한반도 연안해역에서 적조로부터 양식장을 보호하기 위한 연안환경모니터링시스템을 구축하는데 있다. 1995년 이후 적조의 발생은 한반도 남부 연안해역에서 빈번하게 발생하고 넓게 확산되었다. 따라서 적조연구의 가장 중요한 점은 유해성적조의 발생 초기단계에 적조를 탐지하는 것이다. 지리정보시스템 기술은 적조발생의 공간적, 시간적 변화를 분석하는데 필요한 적조모니터링 시스템을 만드는데 적합하다. 유해성 적조 분석시스템 프로그램은 매일 매일의 적조 분포범위, 적조 생물 종, 적조 밀도 등을 제공해준다. 우리는 유해성 적조분석프로그램을 이용하여 적조로부터 양식장의 보호지역을 찾을 수 있다. 적조의 공간분석은 현장조사에 의한 참조자료를 바탕으로 수행되었다.

• Proceedings of the Korea Information Processing Society Conference
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• 2012.04a
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• pp.1010-1011
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• 2012

적조란 유해조류의 일시적인 대 번식으로 바다를 적색으로 변화시키며 연안 환경 및 바다 생태계에 악영향뿐만 아니라 양식장의 어패류를 집단 폐사 시키는 현상이다. 적조에 의한 양식어업의 피해는 매년 발생하고 있으며 매년 적조방제에 많은 비용을 소비하고 있다. 이 때문에 적조 발생을 미리 예측할 수 있으면 적조에 대한 피해 및 방재 비용을 최소화 시킬 수 있다. 본 논문은 앙상블 학습은 이용한 적조발생 예측 방법을 제안한다. 제안방법은 앙상블 학습의 bagging과 boosting 방법을 이용하여서 적조를 예측의 성능을 향상시킨다. 실험결과 제안방법은 단일 분류기에 비하여서 더 좋은 적조 발생 예측 성능을 보였다.

• Proceedings of the Korea Information Processing Society Conference
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• 2011.04a
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• pp.294-296
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• 2011

적조란 유해조류의 일시적인 대 번식으로 바다물의 색깔이 변하는 자연현상으로 어패류를 집단 폐사시킨다. 적조에 의한 양식어업의 피해가 증가함에 따라서 적조에 대한 많은 연구가 이루어지고 있다. 특히 적조 발생을 미리 예측할 수 있으면 적조에 대한 피해를 최소화 시킬 수 있다. 그러나 국내의 적조 현상 예측에 대한 연구는 단순히 적조발생 판별에 그치는 등 미흡한 실정에 있다. 본 논문은 퍼지 추론을 이용한 새로운 적조발생 예측 방법을 제안한다.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.15 no.9
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• pp.1881-1888
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• 2011

Red tide is a natural phenomenon to bloom harmful algal, which fish and shellfish die en masse. Red tide damage with respect to sea farming has been occurred each year. Red tide damage can be minimized by means of prediction of red tide blooms. Red tide prediction using naive bayes classifier can be achieve good prediction results. The result of naive bayes method only determine red tide blooms, whereas the method can not know how increasing of red tide algae density. In this paper, we proposed the red tide blooms prediction method using fuzzy reasoning and naive bayes classifier. The proposed method can enhance the precision of red tide prediction and forecast the increasing density of red tide algae.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.16 no.4
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• pp.2951-2957
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• 2015

The development of worldwide harmful algal blooms(HAB) is a serious problem for public health and fisheries industries. To evaluate the algicidal impact on the HAB species, algicide thiazolidinedione derivative (TD49) and yellow clay were examined, which is focus on assess the algicidal effects and inhibition to photosynthesis of HAB species. To obtain the detailed information, we analyzed the viability of target species related to activity Chl. a, photosynthetic efficiency($F_v/F_m$), and electron transport rate(ETR). Culture experiment was conducted to evaluate the algicidal effects of three harmful species(raphidophyceae Heterosigma akashiwo, Chattonella marina, and dinophyceae Heterocapsa circularisquama) and one non-harmful species (cryptophyceae Rhodomonas salina). Our experiments revealed that three HAB species were easily destroyed of the cell walls after TD49 dosing. Also, they had significantly reducing values of active Chl. a, $F_v/F_m$, and ETR, due to the damage of photosystem II by inter-cellular disturbance. As a result, the algicidal effect(%) for the three HABs were as follows, in the order of greatest to the least: H. circularisquama> C. marina> H. akashiwo. However, the algicidal effect for yellow clay remained to be <30% (p>0.01), implying that it may not have damaged the photosystem II. On the other hand, non-HAB R. salina was promoted at both TD49 and yellow clay treatments. Our results demonstrated that the TD49 is a good agent for the control of HABs H. akashiwo, C. marina, and H. circularisquama, whereas the yellow clay would not be suitable for the field application based on our experimental results.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.36 no.11B
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• pp.1339-1345
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• 2011

Red tide is a natural phenomenon that change sea color by harmful algal blooms. There have been many studies on red tide due to increasing of red tide damage. However, to automatically classify the red tide algae is not enough. Recognition of red tide algae is difficult because they do not have matching center features for recognizing algae image object. Previously studies are used a few type of red tide algae for classification. In this paper, we proposed the red tide algae recognition method using PCA and roundness of image objects.