• Korean Journal of Environmental Biology
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• v.36 no.3
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• pp.359-369
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• 2018

Harmful algal blooms (HABs) are a serious problem for public health and fisheries industries, thus there exists a need to investigate the possible ways for effective control of HABs. In the present study, we investigated the algicidal effects of a newly developed GreenTD against the HABs (Chattonella marina, Heterosigma akashiwo, Cochlodinium polykriokides, and Heterocapsa circularisquama) and non-HABs (Chaetoceros simplex, Skeletonema sp. and Tetraselmis sp.), which is focused on the different population density and concentration gradients of algicidal substances. The time series viability of target alga was assessed based on the activity of Chl. a photosynthetic efficiency in terms of $F_v/F_m$, and in vivo fluorescence (FSU). Effective control of Raphidophyta, C. marina and H. akashiwo was achieved at a GreenTD concentration of $0.5{\mu}gL^{-1}$ and $0.2{\mu}gL^{-1}$, respectively, and regrowth of both the species was not observed even after 14 days. The inhibitory ratio of the dinoflagellate, C. polykriokides was more than 80% at $0.2{\mu}gL^{-1}$ of GreenTD. H. circularisquama was constantly affected in the presence of $0.2{\mu}gL^{-1}$ of GreenTD in the high- and low-population density experimental groups. On the other hand, diatoms, C. simplex, and Skeletonema sp. were not significantly affected even in the presence of $0.2{\mu}gL^{-1}$ of GreenTD and exhibited re-growth activity with the passage of incubation time. In particular, green alga Tetraselmis sp. remained unaffected even in the presence of the highest concentration of GreenTD ($1.0{\mu}gL^{-1}$), implying that non-HABs were not greatly influenced by the algicidal substances. As a result, the algicidal activity of GreenTD on the harmful and nonharmful algae was as follows: raphidophyte>dinoflagellates>diatoms>green alga. Consequently, our results indicate that inoculation of GreenTD substances into natural blooms at a threshold concentration ($0.2{\mu}gL^{-1}$) can maximize the algicidal activity against HABs species. If we consider the dilution and diffusion rate in the field application, it is hypothesized that GreenTD will demonstrate economic efficiency, thus leading to effective control against the target HABs in the closed bay.

• The Sea:JOURNAL OF THE KOREAN SOCIETY OF OCEANOGRAPHY
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• v.24 no.1
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• pp.106-127
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• 2019

This study aims to understand spatio-temporal variations of macrozoobenthos community in Han River (HRE), Geum River (GRE), and Nakdong River estuaries (NRE) of Korea, sampled by National Survey of Marine Ecosystem. The survey was seasonally performed at a total of 20 stations for three years (2015-2017). Sediment samples were taken three times with van Veen grab of $0.1m^2$) areal size and sieved through a 1 mm pore size mesh on site. A total of 1,008 species were identified with 602 species in HRE, 612 in GRE, and 619 in NRE, showing similar number of species between estuaries. Mean density was $1,357ind./m^2$, showing the high in NRE ($1,357ind./m^2$), mid in GRE ($1,357ind./m^2$), and low in HRE ($1,127ind./m^2$). Mean biomass was $116.8g/m^2$, showing similar variations to density ($174.2g/m^2$ in NRE, $129.0g/m^2$ in GRE, $49.0g/m^2$ in HRE). Polychaeta dominated in number of species and density in three estuaries. Biomass-dominated taxon was Mollusca in HRE and GRE, and Echinodermata in NRE. Polychaetous species dominated all three estuaries over 4% of density, such as Dispio oculata, Heteromastus filiformis and Aonides oxycephala in HRE, Heteromastus filiformis and Scoletoma longifolia in GRE, and Pseudopolydora sp. and Aphelochaeta sp. in NRE, showing various density between estuaries. Community structure was determined by various environmental variables among estuaries such as mean grain size and sorting (HRE), salinity and mean grain size (GRE), and salinity, dissolved oxygen, loss on ignition and mud content (NRE). Our study demonstrates the application of different measures to manage ecosystems in three estuaries. HRE needs to alleviate sedimentary stressors such as sand mining, land-filling, dike construction. Management of GRE should be focused on fresh water control and sedimentary stressors. In NRE, monitoring of dominant benthos and process study on hypoxia occurrence in inner Masan Bay are necessary.

• Journal of Intelligence and Information Systems
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• v.24 no.1
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• pp.1-23
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• 2018

From the 21st century, various high-quality services have come up with the growth of the internet or 'Information and Communication Technologies'. Especially, the scale of E-commerce industry in which Amazon and E-bay are standing out is exploding in a large way. As E-commerce grows, Customers could get what they want to buy easily while comparing various products because more products have been registered at online shopping malls. However, a problem has arisen with the growth of E-commerce. As too many products have been registered, it has become difficult for customers to search what they really need in the flood of products. When customers search for desired products with a generalized keyword, too many products have come out as a result. On the contrary, few products have been searched if customers type in details of products because concrete product-attributes have been registered rarely. In this situation, recognizing texts in images automatically with a machine can be a solution. Because bulk of product details are written in catalogs as image format, most of product information are not searched with text inputs in the current text-based searching system. It means if information in images can be converted to text format, customers can search products with product-details, which make them shop more conveniently. There are various existing OCR(Optical Character Recognition) programs which can recognize texts in images. But existing OCR programs are hard to be applied to catalog because they have problems in recognizing texts in certain circumstances, like texts are not big enough or fonts are not consistent. Therefore, this research suggests the way to recognize keywords in catalog with the Deep Learning algorithm which is state of the art in image-recognition area from 2010s. Single Shot Multibox Detector(SSD), which is a credited model for object-detection performance, can be used with structures re-designed to take into account the difference of text from object. But there is an issue that SSD model needs a lot of labeled-train data to be trained, because of the characteristic of deep learning algorithms, that it should be trained by supervised-learning. To collect data, we can try labelling location and classification information to texts in catalog manually. But if data are collected manually, many problems would come up. Some keywords would be missed because human can make mistakes while labelling train data. And it becomes too time-consuming to collect train data considering the scale of data needed or costly if a lot of workers are hired to shorten the time. Furthermore, if some specific keywords are needed to be trained, searching images that have the words would be difficult, as well. To solve the data issue, this research developed a program which create train data automatically. This program can make images which have various keywords and pictures like catalog and save location-information of keywords at the same time. With this program, not only data can be collected efficiently, but also the performance of SSD model becomes better. The SSD model recorded 81.99% of recognition rate with 20,000 data created by the program. Moreover, this research had an efficiency test of SSD model according to data differences to analyze what feature of data exert influence upon the performance of recognizing texts in images. As a result, it is figured out that the number of labeled keywords, the addition of overlapped keyword label, the existence of keywords that is not labeled, the spaces among keywords and the differences of background images are related to the performance of SSD model. This test can lead performance improvement of SSD model or other text-recognizing machine based on deep learning algorithm with high-quality data. SSD model which is re-designed to recognize texts in images and the program developed for creating train data are expected to contribute to improvement of searching system in E-commerce. Suppliers can put less time to register keywords for products and customers can search products with product-details which is written on the catalog.

• Korean Journal of Fisheries and Aquatic Sciences
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• v.33 no.5
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• pp.455-462
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• 2000

The objective of this study was to examine the physicochemical characteristics of coagulation reaction between loess and red tide organisms (RTO) and its feasibility, in developing a technology for the removal of RTO bloom in coastal sea. The physicochemical characteristics of loess were examined for a particle size distribution, surface characteristics by scanning electron microscope, zeta potential, and alkalinity and pH variations in sea water. Two kinds of RTO that were used in this study, Cylindrothen closterium and Skeietonema costatum, were sampled in Masan bay and were cultured in laboratory. Coagulation experiments were conducted using various concentrations of loess, RTO, and a jar tester. The supernatant and RTO culture solution were analyzed for pH, alkalinity, RTO cell number. A negative zeta potential of loess increased with increasing pH at $10^(-3)M$ NaCl solution and had -71.3 mV at pH 9.36. Loess had a positive zeta potential of +1,8 mV at pH 1.98, which resulted in a characteristic of material having an amphoteric surface charge. In NaCl and $CaCl_2$, solutions, loess had a decreasing negative zeta potential with increasing $Na^+\;and\;Ca^(+2)$ ion concentration and then didn't result in a charge reversal due to not occurring specific adsorption for $Na^+$ ion while resulted in a charge reversal due to occurring specific adsorption for $Ca^(+2)$ ion. In sea water, loess and RTO showed the similar zeta potential values of -112,1 and -9.2 mV, respectively and sea sand powder showed the highest zeta potential value of -25.7 mV in the clays. EDLs (electrical double-layers) of loess and RTO were extremely compressed due to high concentration of salts included in sea water, As a result, there didn't almost exist EDL repulsive force between loess and RTO approaching each other and then LVDW (London-yan der Waals) attractive force was always larger than EDL repulsive force to easily form a floe. Removal rates of RTO exponentially increased with increasing a loess concentration. The removal rates steeply increased until $800 mg/l$ of loess, and reached $100{\%}$ at 6,400 mg/l of loess. Removal rates of RTO exponentially increased with increasing a G-value. This indicated that mixing (i.e., collision among particles) was very important for a coagulation reaction. Loess showed the highest RTO removal rates in the clays.