• Title/Summary/Keyword: 축산차량

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축산물위생처리협회지

  • 한국축산물위생처리협회
    • 한국축산물위생처리협회지
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    • no.57
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    • pp.1-2
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    • 2003
  • 도축세 납부제도 폐지 추진 - 충남농협, 도축세 납부 폐지 요구키로 - 수입농산물 국산둔갑 '원천봉쇄' - 이동방역차량 175대 지역공급

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Social Network Type Analysis of Highly Pathogenic Avian Influenza(HPAI) Outbreaks in South Korea, 2014-2016 (2014-2016 국내 발생 고병원성조류인플루엔자(HPAI)의 사회연결망(Social Network) 유형 분석)

  • BAE, Sun-Hak;JEONG, Hae-Yong;EOM, Chi-Ho
    • Journal of the Korean Association of Geographic Information Studies
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    • v.19 no.3
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    • pp.114-126
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    • 2016
  • Domestic risk factors that are thought to be correlated with highly pathogenic avian influenza (HPAI) outbreak are migratory birds and moving objects such as poultry farm vehicles. In particular, the commercial vehicles that routinely circulate the local and/or remote poultry farms produce are thought to be major HPAI risk factors in South Korea. In this study, the driving histories of the vehicles belonging to poultry farms and/or commercial companies registered in the Korea Animal Integrated System (KAHIS) were analyzed using statistical and social networking tools in a Geographic Information System (GIS) in order to understand the pattern of the HPAI (H5N8) outbreak that occurred in 2014 in South Korea. Based on the 2014 HPAI outbreak patterns, HPAI-infected poultry farms were categorized according to geological features. The HPAI-infected poultry farms were categorized as 'regional-accumulation', 'regional-distribution', 'metropolitan-accumulation', 'metropolitan-distribution' and 'national-distribution' in endemic or non-endemic regions. We were able to categorize most HPAI-infected poultry farms into the five proposed categories, but further studies are required to categorize all such farms. Based on this categorization system, we propose efficient but economical prevention boundaries in South Korea. We strongly believe that our research could hugely impact government decisions to estimate the prevention area.

Development of Predicting Model for Livestock Infectious Disease Spread Using Movement Data of Livestock Transport Vehicle (가축관련 운송차량 통행 데이터를 이용한 가축전염병 확산 예측모형 개발)

  • Kang, Woong;Hong, Jungyeol;Jeong, Heehyeon;Park, Dongjoo
    • The Journal of The Korea Institute of Intelligent Transport Systems
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    • v.21 no.4
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    • pp.78-95
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    • 2022
  • The result of previous studies and epidemiological invstigations for infectious diseases epidemic in livestock have shown that trips made by livestock-related vehicles are the main cause of the spread of these epidemics. In this study, the OD traffic volume of livestock freight vehicle during the week in each zone was calculated using livestock facility visit history data and digital tachograph data. Based on this, a model for predicting the spread of infectious diseases in livestock was developed. This model was trained using zonal records of foot-and-mouth disease in Gyeonggi-do for one week in January and February 2015 and in positive, it was succesful in predicting the outcome in all out of a total 13 actual infected samples for test.

축산물위생처리협회지

  • 한국축산물위생처리협회
    • 한국축산물위생처리협회지
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    • no.50
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    • pp.1-2
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    • 2003
  • 2003년도 정기총회 개최 - 축산물중 유해잔류물질방지 및 HACCP 전국 순회교육실시 계획 - 양돈협회, 살처분용 돼지 전살차량 제작$\cdot$운영 - 지난해 한우도축두수-18.5$\%$감소, 돼지-7$\%$증가 - 수입생우 559두 인천항 외항 대기중

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Relationship Between Degree Centrality of Livestock Facilities in Vehicle Movement Network and Outbreak of Animal Infectious Disease (차량이동 네트워크에서의 축산시설 연결중심성과 가축 전염병 발생 사이의 관계)

  • Lee, Gyoung-Ju;Pak, Son-Il;Lee, Kwang-Nyeong;Kim, Han-Yee;Park, Jin-Ho;Hong, Sungjo
    • Journal of the Korea Academia-Industrial cooperation Society
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    • v.19 no.12
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    • pp.353-362
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    • 2018
  • The national loss caused by the periodic livestock epidemic is very large. In addition, vehicle movement is the main cause of livestock epidemics in Korea. In this context, this study analyzed the relationship between the degree centrality of livestock facilities and the outbreak of infectious diseases. For this purpose, a livestock vehicle movement network was constructed using the facility entrance data provided by KAHIS. Afterwards, the centrality index was derived for each facility in the vehicle movement network and the mean centrality index of the epidemic and non-epidemic facilities were compared. The analysis results are summarized as follows. First, the degree centrality of epidemic facilities is significantly greater than non-epidemic facilities. As a result of the analysis of the entire period data and the period-based data, in most data, the degree centrality of facilities where livestock infectious diseases occurred was significantly greater than most non-occurrence facilities. Second, in the entire period data, the difference in degree centrality between the epidemic and non-epidemic facilities was smaller for HPAI than for FMD. On the other hand, no significant difference was found in the results of the analysis according to the divided period. The policy implications of the results are as follows. First, proactive management of facilities based on centrality is needed. Second, in the case of cloven-hoofed animal facilities, it is more urgent to introduce a management policy based on the degree centrality.

Hub Facilities in Vehicle Movement Network between Livestock Facilities (사회연결망 분석을 통한 축산시설 차량이동 네크워크의 허브시설 도출)

  • Lee, Gyoung-Ju;Park, Son-Il;Lee, Kwang-Nyeong;Kim, Han-Yee;Park, Jin-Ho;Hong, Sungjo
    • Journal of the Korea Academia-Industrial cooperation Society
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    • v.19 no.6
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    • pp.137-146
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    • 2018
  • The purpose of this study was to derive and analyze the hub facilities that occupy major positions in the vehicle movement networks of livestock facilities. For this purpose, this study used the KAHIS data provided by Animal and Plant Quarantine Agency. The hub facilities were derived from the degree centrality & betweenness centrality. The analysis results are summarized as follows. First, in a livestock facility's vehicle movement network, there are a small number of hub facilities with very high centrality indicator values compared to other facilities. Second, the hub facilities based on the degree centrality are the feed factory, the milk collecting center, slaughterhouse, slaughterhouse for chicken, and livestock markets. Third, the hub facilities based on the betweenness centrality are the livestock markets, the feed factory, and slaughterhouse. Fourth, hub facilities based on the degree centrality are concentrated in a particular area, but the hub facilities based on betweenness centrality are distributed relatively evenly.