• 한국안전학회지
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• 제38권6호
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• pp.50-59
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• 2023

As the diversity of disasters continues to increase, the concept of "complex disasters" has gained prominence in various policies and studies related to disaster management. However, there has been a certain limitation in the availability of the systematic statistics or data in advancing policies and research initiatives related to complex disasters. This study aims to analyze the macro-level characteristics of the complex disasters that have occurred domestically utilizing a 30-year span of a news data. Initially, we categorize the complex disasters into the three types: "Natural disaster-Natural disaster", "Natural disaster-Social disaster", and "Social disaster-Social disaster". As a result, the "natural diaster-social disaster" type is the most prevalent. It is noted that "natual disaster-natural disaster" type has increased significantly in recent 10 years (2011-2020). In terms of specific disaster types, "Storm and Flood", "Collapse", "Traffic Accident", "National Infrastructure Paralysis", and "Fire⋅Explosion" occur the most in conjunction with other disasters in a complex manner. It has been observed that the types of disasters co-ocuuring with others have become more diverse over time. Parcicularly, in recent 10 years (2011-2020), in addition to the aforementioned five types, "Heat Wave", "Heavy Snowfall⋅Cold Wave", "Earthquake", "Chemical Accident", "Infectious Disease", "Forest Fire", "Air Pollution", "Drought", and "Landslide" have been notable for their frequent co-occurrence with other disasters. These findings through the statistical analysis of the complex disasters using long-term news data are expected to serve as crucial data for future policy development and research on complex disaster management.

• 융합보안논문지
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• 제4권3호
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• pp.57-82
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• 2004

컴퓨터, 통신과 데이터베이스가 합류하여 빠른 속도로 분산 데이터베이스를 생성하고 있는 시점에서, 많은 응용들은 이러한 데이터베이스를 대상으로 시간적으로 일관성이 있는 센서 데이터를 실시간으로 접근하는 것을 필요로 한다. 전통적인 비실시간 데이터베이스와 객체 관리 시스템에 비해서 성능과 기능면에서 상당히 향상된 점들을 제공하기 위해 BeeHive라는 객체 지향 실시간 데이터베이스 시스템을 개발하였다. 이 논문에서는, 데이터 데드라인을 인지하는 두 가지의 스케쥴링 정책 EDDF와 EDF-DC, 기준이 되는 EDF의 성능이 BeeHive 상에서 수락제어가 있는 경우와 없는 경우로 나누어 광범위한 실험을 통해 평가되었다. 데이터 데드라인을 인지하는 스케쥴링 정책들이 효율적인 영역과 수락제어가 중요한 역할을 하는 영역을 구분하여 확인하였다.

• International Journal of Knowledge Content Development & Technology
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• 제14권3호
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• pp.115-140
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• 2024

With the advent of the Fourth Industrial Revolution and the era of big data, the ability to handle data has become essential. This has heightened the importance and necessity of data literacy competencies. The purpose of this study is to propose a framework for data literacy competencies. To achieve this goal, data literacy frameworks from eight countries and twelve pieces of literature on data literacy competencies were analyzed and synthesized, resulting in five categories and twenty-three competencies. The five categories are: data understanding and ethics, data collection and management, data analysis and evaluation, data utilization, and data governance and systems. It is hoped that the data literacy competency framework proposed in this study will serve as a foundational resource for policies, curricula, and the enhancement of individual data literacy competencies.

• Journal of Information Technology Applications and Management
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• 제24권4호
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• pp.187-196
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• 2017

It is urgent to prepare countermeasures for traffic congestion problems of Korea's metropolitan area where central functions such as economic, social, cultural, and education are excessively concentrated. Most users of public transportation in metropolitan areas including Seoul use the traffic cards. If various information is extracted from traffic big data produced by the traffic cards, they can provide basic data for transport policies, land usages, or facility plans. Therefore, in this study, we extract valuable information such as the subway passengers' frequent travel patterns from the big traffic data provided by the Seoul Metropolitan Government Big Data Campus. For this, we use a Hadoop (High-Availability Distributed Object-Oriented Platform) to preprocess the big data and store it into a Mongo database in order to analyze it by a sequential pattern data mining technique. Since we analysis the actual big data, that is, the traffic cards' data provided by the Seoul Metropolitan Government Big Data Campus, the analyzed results can be used as an important referenced data when the Seoul government makes a plan about the metropolitan traffic policies.

• 한국신뢰성학회지:신뢰성응용연구
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• 제16권4호
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• pp.313-322
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• 2016

Purpose: We introduce ways to employ Markov chain model to evaluate the effect of preventive maintenance process. While the preventive maintenance process decreases the failure rate of each subsystems, it increases the downtime of the system because the system can not work during the maintenance process. The goal of this paper is to introduce ways to analyze this trade-off. Methods: Markov chain models are employed. We derive the availability of the system consisting of N repairable subsystems by the methods under various maintenance policies. Results: To validate our methods, we apply our models to the real maintenance data reports of military truck. The error between the model and the data was about 1%. Conclusion: The models developed in this paper fit real data well. These techniques can be applied to calculate the availability under various preventive maintenance policies.

• 대한산업공학회지
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• 제42권5호
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• pp.327-336
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• 2016

Prediction of customer failure rates plays an important role for establishing appropriate management policies and improving the profitability for industries. For these reasons, many LCD (Liquid crystal display) manufacturing industries have attempted to construct prediction models for customer failure rates. However, most traditional models are based on the parametric approaches requiring the assumption that the data follow a certain probability distribution. To address the limitation posed by the distributional assumption underpinning traditional models, we propose using parameter-free data mining models for predicting customer failure rates. In addition, we use various information associated with product attributes and field return for more comprehensive analysis. The effectiveness and applicability of the proposed method were demonstrated with a real dataset from one of the leading LCD companies in South Korea.

• 대한전자공학회:학술대회논문집
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• 대한전자공학회 2006년도 하계종합학술대회
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• pp.763-764
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• 2006

The rapid growth of Hardware technologies and Network fitted to us Ubiquitous Computing Life[1]. Ubiquitous Computing integrates computation into the environment, rather than having computers which are distinct objects. There are many computational things like a Sensor Network, RFID, GPS, Mobile devices, and so on. Ubiquitous Data Integration and Management are new paradigms. The goals of UDI Service Platform are data protection for the distributed data on pervasive computing devices and data distribution to appropriate users with best distribution policies. To implement the idea we evaluate the logical schema Cyber View that is a management tool.

• Journal of Information Technology Applications and Management
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• 제21권4_spc호
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• pp.431-447
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• 2014

Demand of spectrum resource is tremendously increasing and this trend will continue as more IT services such as cloud computing, smart devices, Internet of Things are provided through wireless network. Recent development of spectrum sharing technology has drawn attention to spectrum policy makers as a promising way to overcome the expected spectrum shortage problem. However, technology-based solution to spectrum shortage problem may not be sustainable since the solution affect only one aspect of spectrum sharing ecosystem. To understand the whole picture of spectrum shortage problem, policies to vitalize spectrum sharing ecosystem were proposed based on the analysis of System Dynamics causal map in the previous study. This study compares and analyzes the effect of those proposed vitalization policies by using System Dynamics simulation. Among seven alternative policies, combined application of demand acceleration policy and technology development policy was found to be more effective for better utilization of spectrum. The effect of demand acceleration policy was offset when other policies are applied together except supply acceleration policy which shows better spectrum sharing.

• STI Policy Review
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• 제1권4호
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• pp.21-28
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• 2010

This study analyzes the establishment of venture companies and the interaction of venture ecosystem components (the core factors of venture ecosystems) with a focus on venture companies, venture capital, and the return market. Government support policies are understood as a catalyst for the venture ecosystem and this study will analyze the implications of government involvement by identifying the role of government policies in the venture ecosystem. According to the results of the empirical analysis with data on confirmed venture businesses by the Small and Medium Business Administration (SMBA), policies that provide direct support to venture companies did not have a significant influence on the establishment of new ventures. However, new investments by venture capital show a statistically significant positive effect and signify that the new investment is an important factor in vitalizing the establishment of new venture businesses and that the economic conditions of the return market have a positive effect. The establishment of venture businesses responds to the changes in real and vertical markets with greater resilience compared to government policies. Given the unique nature of the Korean venture ecosystem that responds to the market with greater resilience than government policies, there must be increased efforts to recover the confidence of the capital markets for venture capital in order to promote improved efficiency.

• 가정과삶의질연구
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• 제30권3호
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• pp.1-11
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• 2012

The purpose of this study is to analyze the effects of attitudes toward reasons for which abortion is permitted on needs for abortion prevention policies among 232 unmarried female students at the middle schools, high schools, and universities located in Seoul. The respondents were requested to complete the self-administered questionnaire, and the principal component analysis, t-tests, Pearson's correlations, and hierarchical multiple regression analyses were performed for analyzing data. The major findings of this study were as follows: First, the principal component analysis identified three reasons for which abortion is permitted. These are reasons under the maternal & child health law, socioeconomic reasons, and normatively unqualified reasons. Second, the female students showed permissive attitudes toward reasons for abortion under the maternal & child health law, disapproval attitudes toward socioeconomic reasons for abortion, and neutral attitudes toward abortion by normatively unqualified reasons. Students also showed high levels of needs for abortion prevention policies. Finally, hierarchical regression analyses revealed that female students' attitudes toward reasons for which abortion is permitted significantly predicted levels of needs for abortion prevention policies, after controlling their sciodemographic characteristics. The implications of the study results are discussed.