• Title/Summary/Keyword: Hamilton-Perry

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Population Projections for Local Governments in Korea: Based on Hamilton-Perry & Auto Regression

  • Lee, Sang-Bock
    • Journal of the Korean Data and Information Science Society
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    • v.18 no.4
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    • pp.955-961
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    • 2007
  • Population projections provides useful basic information for the need of economic resources and labor forces. The National Office of Statistics(NSO) presents population projections for the whole country and some of higher level local governments, but not do projections of the lower level local governments. Here are some projection methods as Hamilton-Perry methods and modified auto regression methods, which are compared to cohort method published by NSO in case of Daegu metropolitan city. The simulation results are a little stagnant with modified auto regression, but a little declines are shown with NSO and HP method, for 2010, 2015 and 2020 year, respectively.

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H-P 기법을 이용한 기초자치단체의 장래인구추계

  • Lee, Sang-Rim;Jo, Yeong-Tae
    • Korea journal of population studies
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    • v.28 no.1
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    • pp.149-172
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    • 2005
  • 장래인구추계(population projection)는 한 사회의 인구수 및 구조 변화를 추정하는 것으로 사회의 잠재적 자원 수요와 노동력 공급을 위한 기초정보를 제공한다. 정확한 장래인구를 추계하는 것은 국가 및 중앙정부 뿐 아니라 지방정부 혹은 그보다 규모가 작은 기초자치단체도 미래의 사회적 변화에 대응하고 지역 특성에 알맞은 정책을 마련하기 위하여 중요한 일임에 틀림없다. 우리나라의 경우 장래인구추계는 통계청에서 담당하고 있는데 현재까지 국가 및 시도단위의 장래인구추계 결과를 발표하고 있으며 기초자치단체는 인구추계의 대상에서 제외되어 있다. 이 글은 Hamilton과 Perry에 의해서 최초 개발되어 실제 미국의 소규모지역별 장래인구추계에 사용되어 온 추계기법을 사용하여 한국의 기초자치단체에의 적용가능성에 대해 검토해 본 연구이다. 장래인구추계를 위한 H-P기법은 도시와 농촌지역의 기초자치단체에 각각 적용해 본 결과 통계청에서 주로 사용하고 있는 코호트 조성법을 이용한 추계기법보다 단순하고 추계를 위해 필요한 정보도 쉽게 얻을 수 있으면서도 비교적 정확한 추계결과를 제시하였다.

A Method for Safety of RFID Systems

  • Karygiannis, Tom;Eydt, Bernard;Barber, Greg;Bunn, Lynn;Phillips, Ted
    • 한국정보컨버전스학회:학술대회논문집
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    • 2008.06a
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    • pp.63-70
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    • 2008
  • The authors, Tom Karygiannis of NIST, and Bernard Eydt, Greg Barber, Lynn Bunn, and Ted Phillips of Booz Allen Hamilton, wish to thank Steven Fick, Rick Korchak, Kate Remley, Jeff Guerrieri, Dylan Williams, Karen Scarfone, and Tim Grance of NIST, and Kenneth Waldrop and Beth Mallory of Booz Allen Hamilton. These individuals reviewed drafts of this document and contributed to its technical content. The authors would also like to express their thanks to several experts for their critical review and feedback on drafts of the publication. These experts include V.C. Kumar of Texas Instruments; Simson Garfinkel of the Naval Postgraduate School; Peter Sand of the Department of Homeland Security; Erika McCallister of MITRE; and several professionals supporting Automatic Identification Technology(AIT) program offices within the Department of Defense(DoD), especially Nicholas Tsougas, Fred Naigle, Vince Pontani, Jere Engelman, and Kathleen Smith. During the public comment period we received helpful comments from the following Federal Government agencies: the US Departments of Defense, Health and Human Services, Homeland Security, Labor, and State; the Office of the Director of National Intelligence; the Office of Management and Budget; and the General Services Administration. We also received several helpful contributions from commercial industry, including comments from EPCglobal, VeriSign, and Priway. Finally, the authors wish to thank the following individuals for their comments and assistance: Brian Tiplady, Daniel Bailey, Paul Dodd, Craig K. Harmon, William MacGregor, Ted Winograd, Russell Lange, Perry F. Wilson, John Pescatore, Ronald Dugger, Stephan Engberg, Morten Borup Harning, Matt Sexton, Brian Cute, Asterios Tsibertzopoulos, Mike Francis, Joshua Slob in, Jack Harris, and Judith Myerson.

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