• 제목/요약/키워드: methods of data collection

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WIRELESS SENSOR NETWORK BASED BRIDGE MANAGEMENT SYSTEM FOR INFRASTRUCTURE ASSET MANAGEMENT

  • Jung-Yeol Kim;Myung-Jin Chae;Giu Lee;Jae-Woo Park;Moon-Young Cho
    • 국제학술발표논문집
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    • The 3th International Conference on Construction Engineering and Project Management
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    • pp.1324-1327
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    • 2009
  • Social infrastructure is the basis of public welfare and should be recognized and managed as important assets. Bridge is one of the most important infrastructures to be managed systematically because the impact of the failure is critical. It is essential to monitor the performance of bridges in order to manage them as an asset. But current analytical methods such as predictive modeling and structural analysis are very complicated and difficult to use in practice. To apply these methods, structural and material condition data collection should be performed in each element of bridge. But it is difficult to collect these detailed data in large numbers and various kinds of bridges. Therefore, it is necessary to collect data of major measurement items and predict the life of bridges roughly with advanced information technologies. When certain measurement items reach predefined limits in the monitoring bridges, precise performance measurement will be done by detailed site measurement. This paper describes the selection of major measurement items that can represent the tendency of bridge life and introduces automated bridge data collection test-bed using wireless sensor network technology. The following will be major parts of this paper: 1) Examining the features of conventional bridge management system and data collection method 2) Mileage concept as a bridge life indicator and measuring method of the indicator 3) Test-bed of automated and real-time based bridge life indicator monitoring system using wireless sensor network

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Lessons from constructing and operating the national ecological observatory network

  • Christopher McKay
    • Journal of Ecology and Environment
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    • 제47권4호
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    • pp.187-192
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    • 2023
  • The United States (US) National Science Foundation's (NSF's) National Ecological Observatory Network (NEON) is a continental-scale observation facility, constructed and operated by Battelle, that collects long-term ecological data to better understand and forecast how US ecosystems are changing. All data and samples are collected using standardized methods at 81 field sites across the US and are freely and openly available through the NEON data portal, application programming interface (API), and the NEON Biorepository. NSF led a decade-long design process with the research community, including numerous workshops to inform the key features of NEON, culminating in a formal final design review with an expert panel in 2009. The NEON construction phase began in 2012 and was completed in May 2019, when the observatory began the full operations phase. Full operations are defined as all 81 NEON sites completely built and fully operational, with data being collected using instrumented and observational methods. The intent of the NSF is for NEON operations to continue over a 30-year period. Each challenge encountered, problem solved, and risk realized on NEON offers up lessons learned for constructing and operating distributed ecological data collection infrastructure and data networks. NEON's construction phase included offices, labs, towers, aquatic instrumentation, terrestrial sampling plots, permits, development and testing of the instrumentation and associated cyberinfrastructure, and the development of community-supported collection plans. Although colocation of some sites with existing research sites and use of mostly "off the shelf" instrumentation was part of the design, successful completion of the construction phase required the development of new technologies and software for collecting and processing the hundreds of samples and 5.6 billion data records a day produced across NEON. Continued operation of NEON involves reexamining the decisions made in the past and using the input of the scientific community to evolve, upgrade, and improve data collection and resiliency at the field sites. Successes to date include improvements in flexibility and resilience for aquatic infrastructure designs, improved engagement with the scientific community that uses NEON data, and enhanced methods to deal with obsolescence of the instrumentation and infrastructure across the observatory.

Age of Data in Contemporary Research Articles Published in Representative General Radiology Journals

  • Kang, Ji Hun;Kim, Dong Hwan;Park, Seong Ho;Baek, Jung Hwan
    • Korean Journal of Radiology
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    • 제19권6호
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    • pp.1172-1178
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    • 2018
  • Objective: To analyze and compare the age of data in contemporary research articles published in representative general radiology journals. Materials and Methods: We searched for articles reporting original research studies analyzing patient data that were published in the print issues of the Korean Journal of Radiology (KJR), European Radiology (ER), and Radiology in 2017. Eligible articles were reviewed to extract data collection period (time from first patient recruitment to last patient follow-up) and age of data (time between data collection end and publication). The journals were compared in terms of the proportion of articles reporting the data collection period to the level of calendar month and regarding the age of data. Results: There were 50, 492, and 254 eligible articles in KJR, ER, and Radiology, respectively. Of these, 44 (88%; 95% confidence interval [CI]: 75.8-94.8%), 359 (73%; 95% CI: 68.9-76.7%), and 211 (83.1%; 95% CI: 78-87.2%) articles, respectively, provided enough details of data collection period, revealing a significant difference between ER and Radiology (p = 0.002). The age of data was significantly greater in KJR (median age: 826 days; range: 299-2843 days) than in ER (median age: 570 days; range: 56-4742 days; p < 0.001) and Radiology (median age: 618; range: 75-4271 days; p < 0.001). Conclusion: Korean Journal of Radiology did not fall behind ER or Radiology in reporting of data collection period, but showed a significantly greater age of data than ER and Radiology, suggesting that KJR should take measures to improve the timeliness of its data.

메모리 워크로드 분석을 위한 고속 커널 데이터 수집 기법 (High Speed Kernel Data Collection method for Analysis of Memory Workload)

  • 윤준영;정승완;박종우;김정준;서대화
    • 정보처리학회논문지:컴퓨터 및 통신 시스템
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    • 제2권11호
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    • pp.461-470
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    • 2013
  • 본 논문은 정밀한 메모리 워크로드 분석을 위해 리눅스 기반의 커널 수준에서 프로세스의 메모리 관리 구조체에 직접 접근하는 방법을 이용하여 고속으로 커널 데이터를 수집하는 기법을 제안한다. 기존의 분석기들은 데이터 수집 속도가 느리고 제공되는 데이터의 제한으로 인하여 확장성이 부족하다. 제안 기법은 메모리 관리 구조체 내의 프로세스 메모리정보, 페이지 테이블, 페이지 구조체를 직접 수집하는 방법을 이용하여 기존의 기법 보다 빠르게 커널 데이터를 수집하며, 사용자가 원하는 데이터를 선택하여 수집할 수 있다. 제안 기법을 통해 실제 실행 중인 프로세스의 메모리 관리 데이터를 수집하고 메모리 워크로드에 대한 분석을 수행하였다.

건설 프로젝트 데이터 특성을 반영한 기준생산성 산정 방법 (A Method of Calculating Baseline Productivity by Reflecting Construction Project Data Characteristics)

  • 김은서;김준영;주선우;안창범;박문서
    • 한국건설관리학회논문집
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    • 제24권3호
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    • pp.3-11
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    • 2023
  • 건설업은 노동집약적 산업으로, 성능과 생산성의 변동성이 매우 높다. 따라서 계약자의 실제 성과를 파악하기 위해 기준생산성을 정량적이고 객관적으로 산출하여야 한다. 하지만, 기존 문헌에서 주로 제시된 기준생산성 산출 방법은 주관성이 내재된 기준을 사용하여 기준생산성을 산출한다는 한계가 있다. 또한, 데이터 수집에 과도한 비용과 시간이 투입되는 기존의 'Five-minute Rating'과 같은 데이터 수집 방식으로는 공사 현장에서 실적 물량, 실적 자원과 저해 요인이 포함된 Detailed Data를 수집하기 어렵다. 이에 본 연구에서는 Unimpacted Productivity BP를 산출할 때 활용되는 Detailed Data를 체계적인 형식으로 기록할 수 있는 작업 체크시트 와 과도한 비용과 시간을 들이지 않고 데이터를 수집하고 활용할 수 있는 프로세스를 제시하였다. 또한 기존 기준생산성 산출 방법의 객관성과 신뢰도 문제를 해결하기 위해 비교 분석하여. Detailed Data를 활용한 보다 더 객관적이고 정확한 Unimpacted Productivity BP를 활용한 기준생산성 산출을 제안한다.

Privacy-Preserving Collection and Analysis of Medical Microdata

  • Jong Wook Kim
    • 한국컴퓨터정보학회논문지
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    • 제29권5호
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    • pp.93-100
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    • 2024
  • 4차 산업혁명의 도래와 함께 인공지능, 빅데이터, 사물인터넷, 클라우드 컴퓨팅 등의 첨단 정보 기술이 다양한 산업 분야에서 혁신을 이끌고 있다. 이 기술들은 방대한 양의 데이터를 생성하고 있으며, 많은 기업들이 이를 활용하고 있다. 그러나 개인 데이터 수집 시 발생할 수 있는 프라이버시 침해 위험으로 인해 사용자들은 민감한 정보 제공을 망설이고 있다. 특히 의료 분야에서는 환자의 병명과 같은 민감한 정보 수집이 큰 도전이 되고 있으며, 프라이버시 문제가 데이터 수집과 분석의 장애가 되고 있다. 본 연구는 프라이버시 보호를 유지하면서도 통계적 정보를 효과적으로 추출할 수 있는 의료 데이터 수집 및 분석 기법을 제안한다. 제안 기법은 기존의 단순한 데이터 수집을 넘어서, 프라이버시를 보장하면서 수집된 데이터에서 통계적 정보를 효과적으로 추출하는 방법을 포함한다. 실제 데이터를 이용한 성능 평가에서는 제안된 기법이 기존 방법보다 더 효과적으로 프라이버시를 보존하며 통계적 정보를 도출할 수 있음을 입증한다.

Filipino women's diet and health study (FiLWHEL): design and methods

  • Abris, Grace P.;Hong, Sangmo;Provido, Sherlyn Mae P.;Lee, Jung Eun;Lee, Chang Beom
    • Nutrition Research and Practice
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    • 제11권1호
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    • pp.70-75
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    • 2017
  • BACKGROUND: Immigration to South Korea from neighboring Asian countries has risen dramatically, primarily due to marriage between Korean men and foreign women. Although Filipino women rank fourth among married immigrant women, little is known about the health condition of this population. This manuscript focuses on the design and methods of Filipino women's diet and health study (FiLWHEL). SUBJECTS/METHODS: FiLWHEL is a cohort of Filipino women married to Korean men, aged 19 years old or over. The data collection comprised three parts: questionnaire, physical examination, and biospecimen collection. Questionnaires focused on demographic factors, diet, other health-related behaviors, acculturation and immigration-related factors, medical history, quality of life, and children's health information. Participants visited the recruitment site and answered the structured questionnaires through a face-to-face interview. We also measured their anthropometric features and collected fasting blood samples, toenails, and DNA samples. Recruitment started in 2014. RESULTS/CONCLUSIONS: Collection of data is ongoing, and we plan to prospectively follow our cohort participants. We expect that our study, which is focused on married Filipino women immigrants, can elucidate nutritional/health status and the effects of transitional experiences from several lifestyle factors.

4분위수에 대한 메모 (A Note on Quartile)

  • 박동준;황현미
    • 품질경영학회지
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    • 제26권3호
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    • pp.150-155
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    • 1998
  • It is necessary to describe a data set after collection of data in elementary statistics course. Two major numerical summary of the data set may be measures of central location and dispersion. There are various unmerical summary methods in presenting how data are dispersed and each method has its own advantages and disadvantages. Quartiles are discussed among several methods to describe dispersion of data set. When data type is discrete, exact quartile values are sometimes ambiguous to find, whereas exact quartile values are obtained for contionuous data. Examples of both data types are given. Programs listed below may be used to provide quartiles in MINITAB and SAS.

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부모.자녀건강학회지 논문분석 (창간호-2009) (Analysis of Research Papers Published in the Korean Parent-Child Health Journal (1998-2009))

  • 박혜숙;오진아
    • 부모자녀건강학회지
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    • 제14권1호
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    • pp.1-8
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    • 2011
  • Purpose: This study was aimed to classify the major subjects and theme and to analyze the data collection and analysis method in research papers published in the Korean Parent-Child Health Journal of the Academic Society of Parent-Child Health since 1998. Methods: A total 152 studies published from the first edition to volume 12, number 2 were reviewed using structured analysis criteria developed by researchers; research type, research design, research subjects, research theme, data collection and analysis method. Research theme was founded 4 nursing domains. Data collection and analysis method of papers were limited to quantitative and qualitative researches. Results: One hundred papers conducted quantitative research; 79.0% used survey design. Most of the data collection and analysis method in quantitative research were self-reported questionnaire (69.4%) and parametric statistics respectively. The research subjects of sixty three papers were parent with well or child. The common domain studies was human related concepts such as raring. Conclusion: The findings of this study suggest that published studies have been improved and diversified, however, detailed and clear evaluation tool that assess study process and method should be developed as a way to further improve the quality of published papers in the Korean Parent-Child Health Journal.

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Practical Issues of Earned Value Management Systems (EVMS) for Nuclear Power Plant (NPP) Construction

  • Jung, Youngsoo;Kim, Sungrae;Moon, Byeong-Suk
    • 국제학술발표논문집
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    • The 6th International Conference on Construction Engineering and Project Management
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    • pp.696-697
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    • 2015
  • Cost, schedule, and quality are the three major performance indicators for any construction project. Under the globalized competition in the nuclear industry, researchers and practitioners have also explored a systemized and integrated management system for cost, schedule, and quality. In order to address this issue, the concept of earned value management system (EVMS) has been often utilized. However, implementing EVMS for a mega-project of nuclear power plant (NPP) construction requires extensive overhead efforts. Though previous studies proposed structures and methods for effective NPP EVMS, there has been no legitimate study for data collection strategy for practical implementation. In this context, the purpose of this paper is to develop an effective data collection strategy for NPP EVMS. Firstly, the barriers to practical NPP EVMS were identified based on literature review and expert interviews. Strategies for data collection were then developed based on different phases of project life cycle. This study focuses on the 'life-cycle integrated progress management system' for NPP construction from an owner's perspective Therefore, results of this study can be used as a guide for preparing request for proposals (RFP) of an NPP owner organization.

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