• Wind and Structures
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• v.2 no.3
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• pp.133-150
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• 1999

Significant costs to the public and private sectors due to recent extreme wind events have motivated the need for systematic post-hurricane damage data collection and analysis. Current post disaster data are collected by many different interested groups such as government agencies, voluntary disaster relief agencies, representatives of media companies, academicians and companies in the private sector. Each group has an interest in a particular type of data. However, members of each group collect data using different techniques. This disparity in data is not conducive to quantifying damage data and, therefore, inhibits the statistical and spatial description of damage and comparisons of damage among different extreme wind events. The data collection does not allow comparisons of data or results of analyses within a group and also prohibits comparison of damage data and information among different groups. Typically, analyses of data from a given event lead to different conclusion depending upon the definition of damage used by individual investigators and the type of data collected making it difficult for members of groups to compare the results of their analyses with a common language and basis. A formal method of data collection and analysis-within any single group-would allow comparisons to be made among different individuals, hazardous events and eventually among different groups, thus facilitating the management and reduction of damage due to future disaster. This research introduces a definition of damage to single family dwellings, and a common method of data collection and analysis suited for groups interested in regional characterization of damage. The current state-of-data is presented and a method for data collection is recommended based on these existing data collection methods. A fixed-scale damage index is proposed to consider the damage to a dwelling's feature. Finally, the damage index is applied to three dwellings damaged by Hurricane Iniki (1992). The damage index reflects the reduced functionality of a structure as a single family detached dwelling and provides a means to evaluate regional damage due to a single event or to compare damage due to events of different severity. Evaluation of the damage index and the data available support recommendation for future data collection efforts.

• International Journal of Internet, Broadcasting and Communication
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• v.13 no.4
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• pp.121-128
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• 2021

In order to design a real time big data collection and analysis system of manufacturing data in a smart factory, it is important to establish an appropriate wired/wireless communication system and protocol. This paper introduces the latest communication protocol, OPC-UA (Open Platform Communication Unified Architecture) based client/server function, applied user interface technology to configure a network for real-time data collection through IoT Integration. Then, Database is designed in MES (Manufacturing Execution System) based on the analysis table that reflects the user's requirements among the data extracted from the new cutting process automation process, bush inner diameter indentation measurement system and tool monitoring/inspection system. In summary, big data analysis system introduced in this paper performs SPC (statistical Process Control) analysis and visualization analysis with interface of OPC-UA-based wired/wireless communication. Through AI learning modeling with XGBoost (eXtream Gradient Boosting) and LR (Linear Regression) algorithm, quality and visualization analysis is carried out the storage and connection to the cloud.

• Nuclear Engineering and Technology
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• v.52 no.8
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• pp.1697-1705
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• 2020

To enhance the credibility of human reliability analysis, various kinds of data have been recently collected and analyzed. Although it is obvious that the quality of data is critical, the practices or considerations for securing data quality have not been sufficiently discussed. In this work, based on the experience of the recent human reliability data extraction projects, which produced more than fifty thousand data-points, we derive a number of issues to be considered for generating meaningful data. As a result, thirteen considerations are presented here as pertaining to the four different data extraction activities: preparation, collection, analysis, and application. Although the lessons were acquired from a single kind of data collection framework, it is believed that these results will guide researchers to consider important issues in the process of extracting data.

• Korean Journal of Human Ecology
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• v.19 no.5
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• pp.817-833
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• 2010

This study was dedicated to searching better course of low birth rate study in Korea by carefully analyzing past and present low birth rate researches. For this 179 studies(101 master thesis and 78 journal articles) from 1991 to 2009 were analyzed. Next, using SPSS Win 12.0, the research type, topic, participants, data collection and method of data analysis were compared to the studies' years of publication. The most frequently applied research approach, topic, sampling method, data collection procedure and data analysis method in the research was found to be a literature study, solution and prevention of low birth rate related policy, literature study, literacy analysis. In conclusion, low birth rate studies should become more diversified in terms of types of the research, data collection method, and data analysis. Additionally, research topics should become more realistic and specified. Moreover, research results should be verified before they are applied to the policy.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.8 no.3
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• pp.857-872
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• 2014

Recent researches reveal that great benefit can be achieved for data gathering in wireless sensor networks (WSNs) by employing mobile data collectors. In order to balance the energy consumption at sensor nodes and prolong the network lifetime, a multi-track large-scale mobile data collection mechanism (MTDCM) is proposed in this paper. MTDCM is composed of two phases: the Energy-balance Phase and the Data Collection Phase. In this mechanism, the energy-balance trajectories, the sleep-wakeup strategy and the data collection algorithm are determined. Theoretical analysis and performance simulations indicate that MTDCM is an energy efficient mechanism. It has prominent features on balancing the energy consumption and prolonging the network lifetime.

• 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.

• Journal of Korea Multimedia Society
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• v.23 no.10
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• pp.1286-1295
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• 2020

It has been increasingly difficult to predict the amounts of Acer mono sap to be collected due to droughts and cold waves caused by recent climate changes with few studies conducted on the prediction of its collection volume. This study thus set out to propose a Big Data prediction system based on meteorological information for the collection of Acer mono sap. The proposed system would analyze collected data and provide managers with a statistical chart of prediction values regarding climate factors to affect the amounts of Acer mono sap to be collected, thus enabling efficient work. It was designed based on Hadoop for data collection, treatment and analysis. The study also analyzed and proposed an optimal prediction model for climate conditions to influence the volume of Acer mono sap to be collected by applying a multiple regression analysis model based on Hadoop and Mahout.

• Journal of the Korean Society for information Management
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• v.37 no.3
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• pp.25-50
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• 2020

Since big data platform services for the public library began January 1, 2016, libraries have used big data to improve their work performance. This paper aims to examine the use cases of library big data and attempts to draw improvement plan to improve the effectiveness of library big data. For this purpose, first, we examine big data used while utilizing the library big data platform, the usage pattern of big data and services/policies drawn by big data analysis. Next, the limitations and advantages of the library big data platform are examined by comparing the data analysis of the integrated library management system (ILUS) currently used in public libraries and data analysis through the library big data platform. As a result of case analysis, big data usage patterns were found program planning and execution, collection, collection, and other types, and services/policies were summarized as customizing bookshelf themes for the book curation and reading promotion program, increasing collection utilization, and building a collection based on special topics. and disclosure of loan status data. As a result of the comparative analysis, ILUS is specialized in statistical analysis of library collection unit, and the big data platform enables selective and flexible analysis according to various attributes (age, gender, region, time of loan, etc.) reducing analysis time. Finally, the limitations revealed in case analysis and comparative analysis are summarized and suggestions for improvement are presented.

• Journal of Multimedia Information System
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• v.7 no.2
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• pp.137-140
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• 2020

In this paper, we propose a simplified tag collection algorithm to improve the performance of ISO / IEC 18000-7, the standard of active RFID systems. In the proposed algorithm, the collection command is modified to include the result of the listening period response from the previous round. The tag, which has received the collection command, checks whether the slot to which it has responded is collided, transmits additional data to its data slot without a point-to-point read command and sleep command, and transitions to the sleep mode. The collection round in the standard consists of a series of collection commands, collection responses, read commands, read responses, and sleep commands. On the other hand, in the proposed tag collection algorithm, one collection round consists only of a collection command and a collection response. As a result of performance analysis, it can be seen that the proposed technique shows superior performance compared to the standard.

• Education of Primary School Mathematics
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• v.25 no.4
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• pp.329-341
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• 2022

Data collection is crucial to the process of statistical problem solving since it influences the quality of statistical data. However, there is little instruction on data collection in the Korean mathematics curriculum. In this study, we examined how the data were collected and how the data collection method was taught in the Korean mathematics textbooks for 3rd and 4th grades. As a result, the data appeared in these textbooks were collected by using a variety of methods, including surveys, experiments, observations, and secondary data collections. There were not enough instructions on experiments and observations, compared to surveys and secondary data collection. Additionally, as each textbook works with a distinct contents while teaching data collection, it is expected that there would be variations in the levels that students learn in relation to data collection. Based on these findings, we draw some discussion points to determine how to improve the mathematics curriculum in order to effectively teach data collection in the elementary school.