• 월간산업보건
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• s.192
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• pp.15-21
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• 2004

최근 생물학적 유해인자의 노출로 인한 건강상의 노출평가방법에 대한 관심이 높아지고 있으며 앞으로도 더욱 커질 것으로 보인다. 이에 곰팡이, 박테리아, 엔도톡신을 중심으로 건강장해와 노출평가방법에 대해서 원고를 게재한다.

• Product Safety
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• s.209
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• pp.14-14
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• 2011

가구의 유해물질을 규제하는 현행 안전기준을 계속 시행하기로 하는 것을 골자로 하는 가구의 안전품질 표시기준을 지난 3월 28일에 개정고시 하였다.

• 월간산업보건
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• s.268
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• pp.65-70
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• 2010

제42회 산업안전보건강조주간을 맞아 협회에서 실시한 "참여형(PAOT) 방식을 적용한 사업장 유해위험요인 관리방법" 세미나의 주제발표 내용을 소개한다.

• The Korea Swine Journal
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• v.12 no.10 s.134
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• pp.50-53
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• 1990

유해물질 잔류허용 기준치를 넘게 되면 축산물은 시장판매가 금지되고, 사육자도 추적을 당하여 국민건강 보호차원에서 법적제재를 받으며,축산물에 대한 소비자의 불신으로 소비가 감퇴되는 등 직간접으로 큰 손해를 보게 된다.

• Proceedings of the KSEEG Conference
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• 2002.04a
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• pp.438-439
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• 2002

• 월간산업보건
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• s.193
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• pp.14-21
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• 2004

최근 생물학적 유해인자의 노출로 인한 건강상의 노출평가방법에 대한 관심이 높아지고 있으며 앞으로도 더욱 커질 것으로 보인다. 이에 곰팡이, 박테리아, 엔도톡신을 중심으로 건강장해와 노출평가방법에 대해서 원고를 게재한다.

• The Journal of the Korea Contents Association
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• v.9 no.4
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• pp.1-11
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• 2009

To classifying and filtering of adult images, in recent the computer vision techniques are actively investigated because rapidly increase for the amount of adult images accessible on the Internet. In this paper, we investigate and develop the tool filtering of adult images using skin color model. The tool is consisting of two steps. In the first step, we use a skin color classifier to extract skin color regions from an image. In the nest step, we use a region feature classifier to determine whether an image is an adult image or not an adult image depending on extracted skin color regions. Using histogram color model, a skin color classifier is trained for RGB color values of adult images and not adult images. Using SVM, a region feature classifier is trained for skin color ratio on 29 regions of adult images. Experimental results show that suggested classifier achieve a detection rate of 92.80% with 6.73% false positives.

• Microbiology and Biotechnology Letters
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• v.44 no.2
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• pp.163-170
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• 2016

Strains of lactic acid bacteria were isolated from a variety of fermented foods collected in Korea. The strain L2167 showed a strong antipathogenic activity against Bacillus cereus, Listeria monocytogenes, Salmonella Typhimurium, Staphylococcus aureus, and Staphylococcus epidermidis. L2167 was identified as Lactobacillus plantarum by sequence analysis of its 16S rRNA gene. Scanning electron microscopy revealed rough and wrinkled morphology of B. cereus, L. monocytogenes, S. Typhimurium, S. aureus, and S. epidermidis cell membranes after treatment with a crude cell extract of L. plantarum L2167, indicating that Lactobacillus plantarum L2167 might destroy the cell membrane of pathogenic bacteria. The optimal temperature and initial medium pH for Lactobacillus plantarum L2167 growth were 35℃ and 5.5, respectively. Lactobacillus plantarum L2167 was more sensitive to NaCl than Lactobacillus plantarum KCTC21004, used as a control strain. Lactobacillus plantarum L2167 is expected to be developed as a prominent starter strain for efficient inhibition of growth of pathogens.

• Journal of Food Hygiene and Safety
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• v.31 no.5
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• pp.380-385
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• 2016

The object of this study was to evaluate antibacterial activity of edible seaweed extracts against marine bacterial pathogens including Edwardsiella tarda, Streptococcus iniae, Streptococcus parauberis, Vibrio anguillarum, Vibiro harveyi and Vibrio scophthalm, which are associated with human or fish infectious disease. Ecklonia cava methanolic extract showed a strong and broad spectrum antibacterial activity against marine bacterial pathogens used in this study. Among solvent-soluble fractions of the E. cava extract, the ethyl acetate (EtOAc) soluble fraction showed the strongest antibacterial activity against marine bacterial pathogens tested in this study with MIC in the range of $128-256{\mu}g/mL$. Furthermore, HPLC analysis revealed that the soluble fraction contains abundant dieckol, a phlorotannin compound, compared to other solvent soluble fractions, suggesting that phlorotannins including dieckol would be a key antibacterial agent against marine bacterial pathogens.

• Journal of Korea Multimedia Society
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• v.15 no.5
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• pp.577-586
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• 2012

The smartphone emerged due to the rapid development of the Internet has brought greater convenience to life in a positive manner. Recently, however, because of unconstrained exposure to harmful video, reckless use of smart phones has become a domestic issue in our society. In this paper, a service which detects harmful videos by using the acoustic information is designed and implemented on the Android OS. In order to implement the service of Android OS-based detection of the harmful movie, the speed of existing sound-based detection method for harmful videos is improved. The GMM(Gaussian Mixture Model) was used for classifier and the number of Gaussian Mixture was 18. The implemented service shows a detection rate of 97.02% for a total of 1,210 data files (approximately 687 hours) which comprises 669 general videos files (about 424 hours) and 541 harmful video files (about 263 hours). It's speed is 5.6 times faster than the traditional methods whitout reducing the detection rate.