• Journal of Food Hygiene and Safety
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• v.15 no.4
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• pp.293-296
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• 2000

Paralytic shellfish poison (PSP) occurrence and variation in th\ulcorner different bivalve species including oyster,Crassostrea gigas and mussel, Mytilus edulis Jinhae bay Korea from January to December in 1997 were surveyed. And also compositional characteristics of PSP ingredients in the different bivalve species were investigated. PSP in shellfish was detected from late February and increased continuously until the middle of April in Jinhae bay. And after April PSP level had been decreased gradually and the toxicity was not detected by mouse bioassay in the early of June. Of the examined bivalve species, PSP content in the mussel exhibited the highest value and the PSP content in the mussel in the middle of April, PSP high season in Jinhae bay, was 6 times higher than that in the oyster. Gonyautokin (GTX) 1~4 group occupied 59.0~78.8% of whole PSP contents and identified as dominant ingredient in the examined bivalves except oyster. And it is also identified that the PSP toxicity in the tested species were derived from the GTX group. And the dominant ingredient of PSP in the oyster was carbamoyl-N-sulfo-11$\alpha$-hydroxysaxitoxin sulfate(Cl)(37.9%) and neosaxitoxin(neoSTX)(26.2%). But the toxicity of Cl in the tested oyster could be ignorable and most toxicity (80.0%) was derived from saxitoxin (STX) group.

• Korean Journal of Fisheries and Aquatic Sciences
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• v.25 no.2
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• pp.144-150
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• 1992

Paralytic shellfish toxins in mussels Mytilus edulis and dinoflagellate Alexandrium tamarene from Jinhae Bay, south coast of Korea were investigated. The mussels collected in March-April, 1989 showed toxicities of 7.5 MU/g of whole meat(31-88 MU/g of the digestive gland) , and those collected in 1990 showed toxicity level of 1.9-9.9 MU/g of whole meat by the standard mouse bioassay. Analysis of toxins by high performance liquid chromatography revealed the presence of gonyautoxin 1-4$(48-76\%)$ gonyautoxin 8 and epi-gonyautoxin $8(C1-C2,\;14-39\%)$, saxitoxin$(1-10\%)$, neosaxitoxin$(l-7\%)$ and trace amount of decarbamoylgonyautoxin 2 and 3(dcGTX2, dcGTX3) in the mussels of 1989. While, Mussels collected in 1990 contained a significantly larger proportion of neosaxitoxin $(44-50\%)$ than did those of 1989. A. tamarense isolated in April 1989 produced the same toxins in culture with slightly higher proportion of Cl, C2, dcGTX2 and dcGTX3 than in the mussels. The difference was within a range of toxin change during accumulation by shellfish and during sample preparation for analysis. It was thus concluded that the dinoflagellate was the cause of toxins in the mussels.

• Korean Journal of Fisheries and Aquatic Sciences
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• v.21 no.3
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• pp.161-168
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• 1988

The Stability of PSP extracted from the intoxicated sea mussel, Mytilus edulis was evaluated by the thange of heating conditions and pH of the PSP solution. Also the composition of the PSP extracted from the cultured sea mussel collected at Chungmu, Korea on March 12, 1986 was analyzed. The extracted PSP was stable over the range of pH 2.0 to 4.0, but it was unstable above pH 4.5. For example. the toxicity of extracted PSP of pH 3.0 was only decreased less than $20\%$ by the treatment at $121^{\circ}C$ for 15min or at 100 for 2 hours, but it was decreased more than $80\%$ by the same treatment when the pH of the PSP solution was adjusted to 6.0. The toxin was purified from the ethanolic extract of the digestive glands of the sampled sea mussel by Bio-gel P-2 and Bio-Rex 70 column chromatography. The toxic fractions obtained were analyzed by cellulose acetate membrane electrophoresis, TLC and HPLC. The compositional analytical results of the PSP, most of the toxins were certified as $GTX_{1-4}$, while the toxicity of STX was only about 1/40 of that of $GTX_s$.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.12 no.6
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• pp.591-596
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• 2019

In this paper, we implemented a deep learning operation structure with less influence of local PC performance. In general, the deep learning model has a large amount of computation and is heavily influenced by the performance of the processing PC. In this paper, we implemented deep learning operation using AWS and streaming server to reduce this limitation. First, deep learning operations were performed on AWS so that deep learning operation would work even if the performance of the local PC decreased. However, with AWS, the output is less real-time relative to the input when computed. Second, we use streaming server to increase the real-time of deep learning model. If the streaming server is not used, the real-time performance is poor because the images must be processed one by one or by stacking the images. We used the YOLO v3 model as a deep learning model for performance comparison experiments, and compared the performance of local PCs with instances of AWS and GTX1080, a high-performance GPU. The simulation results show that the test time per image is 0.023444 seconds when using the p3 instance of AWS, which is similar to the test time per image of 0.027099 seconds on a local PC with the high-performance GPU GTX1080.

• Proceedings of the SAREK Conference
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• 2009.06a
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• pp.124-129
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• 2009

• Journal of the Korea Institute of Information and Communication Engineering
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• v.18 no.5
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• pp.1177-1186
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• 2014

Computer-generated hologram (CGH) is to mathematically model optical phenomenon with digital computer. Because it requires huge amount of computational power, a fast and high performance technique is needed. In this paper, we proposed two parallelizations for CGH calculation. The first is to parallelize CGH algorithm in a GPU (general processing unit) and the second is to parallelize multiple GPUs. The proposed algorithm was implemented in GTX780 Ti GPU. It calculates a $1,024{\times}1,024$ hologram with 10K object points for about 24ms.

• 한국해양학회지
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• v.24 no.2
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• pp.79-83
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• 1989

Attempts were made to analyze the toxin composition of the toxic mussel Mytilus edulis galloprovincialis which were collected from aquaculture pond in Apr. 1988 in Hachung, Koje, southern Korea. The toxins were partially purified from the ethanolic extract of the mussel digestive glands by activated charcoal and Bio Gel P-2 column chromatography. HPLC analysis demonstrated that the toxin consisted mainly of gonyautoxin 1-4 (GTX 1-4), along with trace amounts of saxitoxin (STX) and protogonyautoxin 1-2 (PX 1-2).

• Journal of the Korea Institute of Information and Communication Engineering
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• v.15 no.3
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• pp.583-588
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• 2011

In this paper, we propose an adaptive variable-sized matching window method using the characteristic points of the image and a method to increase the reliability of the cross-consistency check to raise the correctness of the final disparity image. The proposed adaptive variable-sized window method segments the image with the color information, finds the characteristic points inside the window. Also the proposed algorithm implement using a graphic processing unit(GPU). The GPU, we used in this paper is GeForce GTX296 (NVIDIA) and we can use programming based on CUDA. The calculation speed realizes a speed approximately 128 times faster than that of a CPU.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2021.05a
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• pp.538-540
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• 2021

In this paper, we proposed a smart target detection system that detects and recognizes a designated target to provide relative motion information when performing a target detection mission of a drone. The proposed system focused on developing an algorithm that can secure adequate accuracy (i.e. mAP, IoU) and high real-time at the same time. The proposed system showed an accuracy of close to 1.0 after 100k learning of the Google Inception V2 deep learning model, and the inference speed was about 60-80[Hz] when using a high-performance laptop based on the real-time performance Nvidia GTX 2070 Max-Q. The proposed smart target detection system will be operated like a drone and will be helpful in successfully performing surveillance and reconnaissance missions by automatically recognizing the target using computer image processing and following the target.

• Journal of Food Hygiene and Safety
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• v.35 no.6
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• pp.521-534
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• 2020

Paralytic shellfish poisoning (PSP) occurs when saxitoxin (STX), which is produced by harmful algae (dinoflagellates) and then accumulated in bivalve shellfish by filter-feeding, is consumed by humans. With recent advances in analysis technology, it has been reported that dinoflagellates also produce a variety of analogues such as the gonyautoxin (GTX) group and the N-sulfo-carbamoyl toxin (C toxin) group, in addition to STX. Accordingly, CODEX and the EFSA are stepping forward to manage STX and analogues as STX groups requiring safety management. In Korea, the occurrence of dinoflagellates producing STX analogues has already been reported, and contamination of analogues (GTX group, C toxin group) in live mussels has also been reported. In this study, in order to provide the basis for systematic monitoring and safety management of STX and analogues, their physicochemical characteristics, occurrence of dinoflagellates, toxicity and toxic equivalency factor, analytical method and occurrence were widely reviewed. This review is expected to contribute to strengthening the safety management of STX and its analogues.