• 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.

• ALGAE
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• v.28 no.4
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• pp.297-305
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• 2013

There is increasing interest in the relationships between marine bacteria and red tide organisms. Some bacteria are known to kill red tide organisms, and may be responsible for accelerating the termination of red tides. Thus, certain algicidal bacteria have been proposed for the control of red tides. Meanwhile, many red tide organisms are known to feed on marine bacteria. The roles of marine bacteria and red tide organisms are therefore reversible. In Korean waters, the killing of red tide organisms by algicidal bacteria, and also the feeding of red tide organisms on marine bacteria have been extensively investigated. The findings of such studies may influence the conventional view of red tide dynamics, and also planktonic food webs. Here, we review the species and concentrations of algicidal bacteria that kill red tide organisms in Korean waters, as well as the ingestion rate and grazing impact of red tide organisms on marine bacteria. Furthermore, we offer an insight into the ecological roles of these 2 components in marine planktonic food webs.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.48 no.5
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• pp.23-29
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• 2011

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. Recognition of red tide algae is difficult because they do not have matching center features for recognizing algae image object. 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 semantic features of NMF and roundness of image objects.

• 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.

• 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 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.

• Proceedings of the KSRS Conference
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• v.1
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• pp.332-335
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• 2006

Red tide(harmful algae) in the Korean Coastal Waters has a given a great damage to the fishery every year. However, the aim of our study understands the influence of meteorological factors (air and water temperature, precipitation, sunshine, solar radiation, winds) relating to the mechanism of red tide occurrence and monitors red tide by satellite remote sensing, and analyzes the potential area for red tide occurrence by GIS. The meteorological factors have directly influenced on red tide formation. Thus, We want to predict and apply to red tide formation from statistical analyses on the relationships between red tide formation and meteorological factors. In future, it should be realized the near real time monitoring for red tide by the development of remote sensing technique and the construction of integrated model by the red tide information management system (the data base of red tide - meteorological informations). Finally our purpose is support to the prediction information for the possible red tide occurrence by coastal meteorological information and contribute to reduce the red tide disaster by the prediction technique for red tide.

• 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.

• Proceedings of the Korea Committee for Ocean Resources and Engineering Conference
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• 2004.05a
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• pp.279-284
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• 2004

Red tide(harmful algae) in the Korean Coastal Waters has a given a great damage to the fishery every year. However, the aim of our study understands the influence of meteorological factors (air and water tempaerature, precipitation, sunshine, solar radiation, winds) relating to the mechanism of red tide occurrence and monitors red tide by satellite remote sensing, and analyzes the potential area for red tide occurrence by GIS. The meteorological factors have directly influenced on red tide formation. Thus, We want to predict and apply to red tide formation from statistical analyses on the relationships between red tide formation and meteorological factors. In future, it should be realized the near real time monitoring for red tide by the development of remote sensing technique and the construction of integrated model by the red tide information management system (the data base of red tide - meteorological informations).

• ALGAE
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• v.19 no.1
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• pp.7-14
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• 2004

Blue-Min was initially developed as an adsorbent for harmful gas removal and recently improved to apply to livestock, agriculture and aquaculture as an assistant feed. In the Blue-Min treatment, growth of harmful algae (Cochlodinium polykrikoides and the others causing the red-tide in the ocean) were inhibited below 10% in comparison with control and coagulation removal of harmful alge with Blue-Min treatment was more efficient than that of yellow loess treatment. It would be expected that the Ble-Min can be useful for the extirpator against the red-tide organisms and restrain the toxic algal growth around the fish aquaculture using the assistant feed. Recently, its utility has become to be diverse as it was revealed that aquaculture productivity increase by its application and, in addition, that it improve the water quality or sediment conditions in the aquaculture of Chinese White Shrimp. When Blue-Min was treated with the proper dose, the growth inhibition of Microcystis aeruginosa and lsochrysis galbana, which are typical red-tide organisms in freshwaters and food organisms in aquaculture, respectively, were less than that of marine red-tide organisms, while their growth slightly increased with low concentration treatiment. In addition, polyunsaturated fatty acids (PUFA) content of I. galbana slightly increase with the Blue-Min treatment. Through our research, the Blue-Min has diverse and comples function against various biological organisms and is proved as a biological activator or depressor.