• International conference on construction engineering and project management
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• 2009.05a
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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

• Journal of Ecology and Environment
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• v.47 no.4
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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.

• Korean Journal of Radiology
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• v.19 no.6
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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.

• KIPS Transactions on Computer and Communication Systems
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• v.2 no.11
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• pp.461-470
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• 2013

This paper proposes high speed kernel data collection method for analysis of memory workload, using technique of direct access to process's memory management structure. The conventional analysis tools have a slower data collection speed and they are lack of scalability due to collection only formalized memory information. The proposed method collects kernel data much faster than the conventional methods using technique of direct collect to process's memory information, page table, page structure in the memory management structure, and it can collect data which user wanted. We collect memory management data of the running process, and analyze its memory workload.

• Korean Journal of Construction Engineering and Management
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• v.24 no.3
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• pp.3-11
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• 2023

This research examines the need for a quantitative and objective method of calculating baseline productivity in the construction industry, which is known for its high volatility in performance and productivity. The existing literature's baseline productivity calculation methods rely heavily on subjective criteria, limiting their effectiveness. Additionally, data collection methods such as the "Five-minute Rating" are costly and time-consuming, making it challenging to collect detailed data at construction sites. To address these issues, this study proposes an objective baseline calculation method using unimpacted productivity BP, a work check sheet to systematically record detailed data, and a data collection and utilization process that minimizes cost and time requirements. This paper also suggests using unimpacted productivity BP and comparative analysis to address the objectivity and reliability issues of existing baseline productivity calculation methods.

• Journal of the Korea Society of Computer and Information
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• v.29 no.5
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• pp.93-100
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• 2024

With the advent of the Fourth Industrial Revolution, cutting-edge technologies such as artificial intelligence, big data, the Internet of Things, and cloud computing are driving innovation across industries. These technologies are generating massive amounts of data that many companies are leveraging. However, there is a notable reluctance among users to share sensitive information due to the privacy risks associated with collecting personal data. This is particularly evident in the healthcare sector, where the collection of sensitive information such as patients' medical conditions poses significant challenges, with privacy concerns hindering data collection and analysis. This research presents a novel technique for collecting and analyzing medical data that not only preserves privacy, but also effectively extracts statistical information. This method goes beyond basic data collection by incorporating a strategy to efficiently mine statistical data while maintaining privacy. Performance evaluations using real-world data have shown that the propose technique outperforms existing methods in extracting meaningful statistical insights.

• Nutrition Research and Practice
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• v.11 no.1
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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.

• Journal of Korean Society for Quality Management
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• v.26 no.3
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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.

• Korean Parent-Child Health Journal
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• v.14 no.1
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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.

• International conference on construction engineering and project management
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• 2015.10a
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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.