• Proceedings of the Korean Society of Soil Zoology Conference
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• 1998.03a
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• pp.9-9
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• 1998

• Animal Systematics, Evolution and Diversity
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• v.12 no.3
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• pp.221-235
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• 1996

The ascidians of Chundo Island are identified into 15 species, 8 genera, 6 families. Among them two species are found to be new to Korean fauna. They are Ascidia sydneiensis Stimpson and Ascidia zara Oka. They are described with figures, and the other species are provided with remarks.

• Journal of the korean veterinary medical association
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• v.49 no.3
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• pp.181-185
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• 2013

세계동물보건기구 (OIE)에서는 광견병을 매월 의무적으로 보고해야하는 질병 (reportable animal disease)으로 분류하고 있으며, 수의분야에서는 2종 법정전염병으로, 보건분야에서는 3종 감염병으로 규정하고 있다. 국내에서 광견병은 1907년에 최초로 확인된 이후로 2012년까지 16,140건이 보고되었다. 국내에서 광견병은 개를 포함한 여러 동물에서 1940년대까지 매년 400-700건이 발생하여 광견병 유행기로 분류된다. 1970년대에 광견병 불활화백신을 개발하고 가축과 개에 적용하여 광견병 발생건수가 줄어들면서 광견병의 제거기에 들어섰다. 광견병 생백신을 바탕으로 대량의 광견병 백신 접종정책을 실시하고, 유기견 (배회하는 개)의 제거 및 광견병 예방 홍보로 인하여 1984년부터 1992년까지 광견병 발생보고가 없었다. 그러나 1993년 철원에서 광견병이 다시 발생한 이후로 야생동물 즉 너구리에 의해 광견병이 전파되고 지속적으로 발생하고 있어 재발생기로 분류된다. 2012년에는 수원과 화성을 포함하여 7건의 광견병이 발생하여 방역당국은 물론 일반 국민들까지 긴장시키고 있다. 따라서, 여기에서는 야생 너구리에 의해 전파되는 최근 국내 광견병의 특성을 파악하고 이에 적절한 예방 및 방역 대책 관련 정보를 제공하고자 한다.

• Korean journal of applied entomology
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• v.59 no.4
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• pp.311-315
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• 2020

Two genera with two species of the superfamily Ichneumonoidea, Testudobracon pleuralis Ashmead 1906 and Diadromus subtilicornis Gravenhorst 1829, are reported for the first time from South Korea. Diagnosis, distribution, and illustration are provided.

• Agrochemical news magazine
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• v.22 no.2 s.165
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• pp.26-27
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• 2001

• Proceedings of the Zoological Society Korea Conference
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• 1994.10a
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• pp.99.2-99
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• 1994

• Proceedings of the Zoological Society Korea Conference
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• 2000.10a
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• pp.89-89
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• 2000

• The Zoological Society Korea : Newsletter
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• v.16 no.1
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• pp.4-11
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• 1999

• The Sea:JOURNAL OF THE KOREAN SOCIETY OF OCEANOGRAPHY
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• v.9 no.1
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• pp.13-19
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• 2004

We compared two different zooplankton data sets simultaneously obtained at the same place with different mesh-sized nets. Smaller mesh-sized net yielded less diverse zooplankton taxa. However, it was difficult to generalize the relationship between the size of the mesh of the net used and the length of the species list observed. It was not only because the sample sizes obtained by smaller mesh net were relatively smaller due to the clogging problem but also because smaller mesh net usually collected more tiny animals that were difficult to identify at lower taxonomic categories. In terms of abundances, on the other hand, the smaller and the larger mesh-sized nets collected smaller and larger-sized animals more effectively, respectively. The abundances of small sized animals were usually greater than those of large-sized animals by about an order of differences. Due to this different catchability of the nets, the community analyses based on Principal Component Analysis led to different results for the same community.

• Journal of Broadcast Engineering
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• v.26 no.2
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• pp.175-183
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• 2021

The study of the fine grained classification of images continues to develop, but the study of object recognition for animals with polymorphic properties is proceeding slowly. Using only pet images corresponding to dogs and cats, this paper aims to compare methods using image processing and methods using deep learning among methods of classifying species of animals, which are fine grained classifications. In this paper, Grab-cut algorithm is used for object segmentation by method using image processing, and method using Fisher Vector for image encoding is proposed. Other methods used deep learning, which has achieved good results in various fields through machine learning, and among them, Convolutional Neural Network (CNN), which showed outstanding performance in image recognition, and Tensorflow, an open-source-based deep learning framework provided by Google. For each method proposed, 37 kinds of pet images, a total of 7,390 pages, were tested to verify and compare their effects.