• Journal of the Korea Computer Graphics Society
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• v.22 no.4
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• pp.21-30
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• 2016

Risk management system should be able to support a decision making within a short time to analyze stream data in real time. Many analytical systems consist of CPU computation and disk based database. However, it is more problematic when existing system analyzes stream data in real time. Stream data has various production periods from 1ms to 1 hour, 1day. One sensor generates small data but tens of thousands sensors generate huge amount of data. If hundreds of thousands sensors generate 1GB data per second, CPU based system cannot analyze the data in real time. For this reason, it requires fast processing speed and scalability for analyze stream data. In this paper, we present a fast visualization technique that consists of hybrid database and GPU computation. In order to evaluate our technique, we demonstrate a visual analytics system that analyzes pipeline leak using sensor and tweet data.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.21 no.11
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• pp.650-661
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• 2020

The digital transformation of the 4th industrial revolution is leading to changes and innovations in the global economy. Various countries are focusing on reviving their manufacturing industries and economic recovery through smart factories. The purpose of this study is to empirically identify technological determinants for the successful implementation of the smart factory and to verify teose effects on manufacturing operations and the firms' operational/environmental performances. Five factors, including sensor network, platform technology, information system, intelligent automation, and safety, were defined as core technologies. The SEM analysis results of 157 small and medium-sized manufacturing firms that have implemented smart factories are as follows. First, sensor network, platform technology, and information system had significant effects on smart manufacturing operations. Second, smart manufacturing operations have improved firm performance. This study is valuable in that it has confirmed the effectiveness of government-funded projects and systemized key technologies for implementing smart factories. Meanwhile, it is helpful for practitioners to support an efficient and effective decision-making for the new adoption.

• Korean Journal of Human Ecology
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• v.14 no.4
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• pp.613-629
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• 2005

This research analyzes household financial structures and ratios to understand factors of household utility. Its main themes are as following: First, what kinds financial structures are found at each level of income? Second, how are they different by the level of income? Third, what factors contribute to appropriate financial ratios? The themes are supported by the texts on financial ratios from both inside and outside of Korea and proved by the Korean Labor and Income Panel Survey, the fifth annual edition. The households are exempted that do not support the household principle record in the principle and household economy record. Accordingly, this survey is from a financial structure analysis of 3,762 households. The analysis utilizes SPSS Window (Version 10.0) program. The following are the results: First, the income level 4 and above, in which the increasing number indicates a higher level of income, are highly ranked on the income-expense level and the asset-debt rate. Also, level 4 has a strong financial structure, whereas level 1 does not. Apparently, the management of the household is complicated by debt redemption and a lower level of assets. Second, Ratio 1, Ratio 2, Ratio 4, and Ratio 5 are different by the level of income. Third, the level of income contributes to the appropriate financial ratio. The financial safety and prospective financial structure at each income level is an important variable. Households with a high income, in particular, have to balance their finances and capital, reducing liabilities and increasing the total assets. In other words, the family must hold assets to enhance efficiency according to the character and income level of the household. This research is a useful resource for such a decision-making as to improve household financial structure stability. Also, it can be adopted to evaluate financial products for specific households and be used for economic and social welfare planning to predict how households influence the nationwide economy.

• Journal of Korean Society for Quality Management
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• v.31 no.3
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• pp.62-84
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• 2003

The typical reason of the private sector's increasing share in standardization is that the procedures of official standardization organizations are out of step with the rate of technical development. At today's so fast pace that the success of a technology is decided in the market even before it is standardized, several industry leaders jointly make their draft standard at the early stage of development, which becomes 'De fecto Standard.' To respond effectively to current trends of standardization where the market's decision is thought much of than official standardization procedures, it is necessary to shift from our current public sector-driven to private sector-driven standardization. Therefore, to vitalize the private sector-driven standardization in Korea, there is a need to: Run a standard foundation to secure stable resources for standardization Make information exchange between the govertment and private sector active and policy-making on standards consistent by designating a private organization to cover the roles, policies on standards, and support of the national standardization organization Establish a system to make private sector-driven standards approved as international standards Offer a training program to forster standard experts Publicize the importance of standards Promote standardization forums driven by private businesses, like the Integrated Forum. Maximize the benefits of linking standards and patents Now, Korea is on the threshold of developing into a world-class standard leader, and the private sector-driven standardization should be a stepping-stone for crossing over the threshold. This study is designed to suggest a method of promoting private sector-driven standardization to effectively cope with fast-changing international standards, based on the cases in developed countries.

• Proceedings of the Korea Society of Environmental Toocicology Conference
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• 2003.05a
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• pp.149-149
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• 2003

To understand environmental paths of the transport and accumulation of endocrine disrupting chemicals (EDCs), a single cell multimedia fate model has been constructed and evaluated. The EDCs of concern were PAHs, Organochlorine Pesticides (OCPs), PCBs, Alkyl phenols, and phthalates. An evaluation model was designed for the multimedia distribution, including air, water, soil, sediment and vegetation. This model was verified using reported values and via monitoring data. Based on collected data, the distribution trends of EDCs with respect to environmental media were analyzed. Those results have applied to the model for the prediction of the spatial and temporal distribution of EDCs in Seoul. Especially, phenol compound, phthalates, PAHs, PCBs and organochlorine pesticides were estimated and the model was verified. This model was successfully conducted to environmental media, such as air (vapor and suspended particles), soils (forest soil, bare soil, and cement-concrete covered soil), water (dissolved and suspended solids), sediment, trees (deciduous and coniferous). The discrepancies between the model prediction and the measured data are approximately within or near a factor of 10 for the PAHs of three rings through that of six rings, implying that multimedia distribution of the PAHs could be predicted with a factor of 10. Concerning about the air equilibrium may be assumed, a fugacity at steady state is similar in all environmental media. Considering the uncertainties of this model, the use of equilibrium models may be sufficient for assessing chemical fates. In this study, a suggestion was made that modeling and estimation of chemicals in environmental multimedia be rigorously evaluated using the measured flux data. In addition, these data should be obtained, for example, from the precise and standardized inventory of the target chemicals. The model (EDC Seoul) will be refined in an on-going research effort and will be used to support decision-making concerning the management of EDCs.

• Journal of Food Hygiene and Safety
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• v.23 no.3
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• pp.276-283
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• 2008

To provide the research strategy for protection of children's health from hazardous chemical, we reviewed the hazardous chemicals can be exposed through maternity, children's life style and living environment. Recently, diseases related with children's living condition were focused as asthma, atopy, childhood developmental disability, congenital malformations and obesity. Children can be exposed to hazardous chemicals through an ambient air, water, soil, food, toys and other factors such as floor dust. Also children's health was deeply related with a wrong life style and neglectful caring by a lack of knowledge and information of harmful ones at parents and child care center's nursers. According to the previous study, the chemical risk factor of children's health were identified as inorganic arsenic, bisphenol A, 2,4-D, dichlorvos, methylmercury, PCBs, pesticide, phthalates, PFOA/PFOS, vinyl chloride, et al. Domestic studies for identification of causality between children exposure to chemicals and resulted hazardous effects were not implemented. The confirmation of chemical risk factors through simultaneously performing toxicological analysis, human effect study, environmental/human monitoring, and risk assessment is needed for good risk management. And also, inter-agency collaboration and sharing information can support confirming scientific evidence and good decision making.

• Journal of Korean Society for Atmospheric Environment
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• v.29 no.3
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• pp.275-286
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• 2013

It is well known that exposure to high level of PM (particulate matter) can adversely affect human health. However, little is known about health burden of PM considering the relationship, exposed level of PM, and health level in local communities. And, there is scarcely methodical assessment of uncertainty for application to policies of these assessment results. The scope of this study is divided into two parts: firstly to estimate the death burden of PM10 (particulate matter less then $10{\mu}m$ in diameter) in Seoul metropolitan region, and secondly to evaluate potential uncertainties in these estimates. To estimate the death burden of PM10 in Seoul metropolitan region from 2005~2010, we firstly assessed the relationship between daily mean PM10 and daily death counts in Seoul from 2000~2010, and calculated the death burden of PM10 using BenMAP (Environmental Benefits Mapping and Analysis Program). After that, we identified and characterized uncertainties to substantially influence the results of death burden. The daily mortality risk was increased 1.000227 times (p-value/0.001) associated with $1{\mu}g/m^3$ increase of daily mean PM10 for all ages population, Seoul. And, death burdens of PM10 in Seoul metropolitan region were estimated from 5.51 in 2005 to 5.12 in 2010 per 100,000 people. Finally, we categorized context, model, and input uncertainty and characterized these uncertainties in three dimensions (i.e. location, level, and nature) using uncertainty typology. In our study, we argue that uncertainties need to be identified, assessed, reported and interpreted in order for assessment results to adequately support decision making, such as the establishment of air quality standards based on health burden of air quality.

• The Journal of the Korea Contents Association
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• v.15 no.8
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• pp.532-543
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• 2015

Damage of national infrastructures not only endangers the structural safety, but also has a direct and indirect influence on national economy and society. Since the influence of damage has been enhanced in the metropolitan areas, the infrastructures in danger should be identified and managed under disaster situations. This study suggests the importance factors for national infrastructures, calculates weights for the factors through AHP analysis, and develops the importance evaluation system for national infrastructures. The evaluation system provides the priority of infrastructures for local governments and facility managers and enables management based on the degree of importance in emergency situations. After disasters, the evaluation system will support a systematic decision-making for recovery priorities with a limited budget.

• The Journal of the Korea Contents Association
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• v.18 no.9
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• pp.623-632
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• 2018

Both investors and researchers are attentive to the prediction of stock price movement directions since the accurate prediction plays an important role in strategic decision making on stock trading. According to previous studies, taken together, one can see that different factors are considered depending on stock markets and prediction periods. This paper aims to analyze what data mining techniques show better performance with some representative index and stock price datasets in the Korea stock market. In particular, extreme gradient boosting technique, proving itself to be the fore-runner through recent open competitions, is applied to the prediction problem. Its performance has been analyzed in comparison with other data mining techniques reported good in the prediction of stock price movement directions such as random forests, support vector machines, and artificial neural networks. Through experiments with the index/price datasets of 12 years, it is identified that the gradient boosting technique is the best in predicting the movement directions after 1 to 4 days with a few partial equivalence to the other techniques.

• Journal of KIISE:Databases
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• v.27 no.2
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• pp.175-184
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• 2000

A data warehouse is an integrated and summarized collection of data that can efficiently support decision making process. The summarized data at the data warehouse is often stored in materialized views. These materialized views need to be updated when source data change. Since the propagation of updates to the views may impose a significant overhead, it is very important to update the warehouse views efficiently. Though various strategies have been proposed to maintain views in the past, they typically require too much accesses to the data sources when the changes of multiple data sources have to be reflected in the view. In this paper we propose an efficient view update strategy that uses relatively small number of accesses to the data sources. We also show the performance advantage of our method over other existing methods through experiments using TPC-D data and queries.