• Journal of Digital Convergence
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• v.15 no.3
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• pp.17-25
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• 2017

Horizon scanning that one of the methods for future prediction is adaptable way of establishing the policy strategy based on big data. This study aims to understand the social problems scientifically utilized horizon scanning technique, and contribute to public policy formulation based on scanning analysis. In this paper, we proposed a public opinion framework for public policy based on social bigdata, and then confirmed the feasibility this framework by analysis of the relationship between public opinion and results after implementation of public policy. Consequently, based on the analysis, we also drew implications of policy formulation about 'free childcare for under 5-years of age' as an object of study. The method that collects public opinion is very important to effective policy establishment and make contribution to constructing national response systems for social development.

• Journal of the Korean Association of Geographic Information Studies
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• v.13 no.3
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• pp.53-63
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• 2010

The global sea level rise has an effect on eco-environmental change by the inundation and erosion in the coastal area. Forecasting model on the change of morpho-ecological environments by the sea level change will give us information for coastal area management by predicting environmental changes of the up-coming future. This research aimed to foresee eco-environmental changes by the sea level rise in coastal area. Prediction model used SLAMM model developed to forecast coastal changes by IPCC scenario. The model predicted centennial environmental changes in the mouth of Han river and Nakdong river, Suncheon and Hampyeung bay as case areas. To sum up the research findings, in the estuary of the Han river, tidal flat was gradually disappeared from the year 2075, scrubmarsh and saltmarsh belts were developed. In the Nakdong River estuary, scrubmarsh was decreased from the year 2025, tidal flat was deposited from the year 2050, and also, the Gimhae plain was partially inundated, and wetlands were formed. In the Hampyeung bay, saltmarsh was deposited in the year 2025, tidal flat expanded until 2050 was partially submerged after that time. Tidal flat of Suncheon bay was disappeared by the inundation after 2025, and saltmarsh was developed in the embayment.

• Journal of the Korean Association of Geographic Information Studies
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• v.11 no.2
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• pp.38-50
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• 2008

The site-specific seismic responses and corresponding seismic hazards are influenced mainly by the subsurface geologic and geotechnical dynamic characteristics. To estimate reliably the seismic responses in this study, a geotechnical information system (GTIS) within GIS framework was developed by introducing new concepts, which consist of the extended area containing the study area and the additional site visit for acquiring surface geo-knowledge data. The GIS-based GTIS was built for Gyeongju area, which has records of abundant historical seismic hazards reflecting the high potential of future earthquakes. At the study area, Gyeongju, intensive site investigations and pre-existing geotechnical data collections were performed and the site visits were additionally carried out for assessing geotechnical characteristics and shear wave velocity ($V_S$) representing dynamic property. Within the GTIS for Gyeongju area, the spatially distributed geotechnical layers and $V_S$ in the entire study area were reliably predicted from the site investigation data using the geostatistical kriging method. Based on the spatial geotechnical layers and $V_S$ predicted within the GTIS, a seismic zoning map on site period ($T_G$) from which the site-specific seismic responses according to the site effects can be estimated was created across the study area of Gyeongju. The spatial $T_G$ map at Gyeongju indicated seismic vulnerability of two- to five-storied buildings. In this study, the seismic zonation based on $T_G$ within the GIS-based GTIS was presented as regional efficient strategy for seismic hazard prediction and mitigation.

• Journal of Internet Computing and Services
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• v.17 no.2
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• pp.59-65
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• 2016

The result of analyzing the cognitive reaction due to the color environment has been applied to various filed especially in medical field. Moreover, the study about the identification of patient's condition and examination the brain activity by collecting the bio-signal based on the color environment is being actively conducted. Even though, there were a variety of experiments by convention the color environment using a light or LED color, it still has a problem that affects the psychological information. Therefore, our proposed system using a HMD (Head Mounting display) to provide a completed color environment condition. This system uses the BMS(Biomedical System) to collect the biometric information which responds to the specific color condition and the human body response information can be measured by the development the Memory and Attention test on Mobile phone. The collection of Biometric information includes electro cardiogram(ECG), respiration, oxygen saturation (Sp02), Bio-impedance, blood pressure will store in the database. In addition, we can verify the result of the human body reaction in the color environment by Memory and Attention application. By utilizing the reaction of the human body information that is collected thought the proposed system, we can analyze the correlation between the physiological information and the color environment. And we also expect that this system can apply to the medical diagnosis and treatment. For future work, we will expand the system for prediction and treatment of Alzheimer disease by analyzing the visualization data through the proposed system. We will also do evaluation on the effectiveness of the system for using in the rehabilitation program.

• Korean Journal of Agricultural and Forest Meteorology
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• v.6 no.2
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• pp.127-139
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• 2004

Agricultural meteorology has advanced during the last 100 years from a descriptive to a quantitative science using physical and biological principles. The agricultural community is becoming more aware that using climate and weather information will improve their profitability and this will no doubt increase the demand for agrometeorological services. Hence it is timely that the needs and perspectives for agrometeorology in the 21$^{21}$ Century are grouped under two major headings: agrometeorological services for agricultural production and agrometeorological support systems for such services. Emphasis must be placed on the components of such support systems comprising of data, research, policies and training/education/extension. As Monteith (2000) mentioned, food supplies ultimately depend upon the skill with which farmers ran exploit the potential of good weather and minimize the impact of bad weather. Recent developments in instrumentation, data management systems, climate prediction, crop modelling, dissemination of agrometeorological information etc., provide agrometeorologists the tools necessary help the farmers improve such skills. The future for operational applications of agricultural meteorology appears bright and such applications could contribute substantially to promote sustainable agriculture and alleviate poverty.

• Korea Journal of Hospital Management
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• v.9 no.2
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• pp.1-22
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• 2004

This study was designed to suggest a learning organization in a medical center by examining the factors to influence effectiveness of the learning organization. We collected the data of 586 persons who participated once or more times in the learning organization managed from 2000 to 2002 by Y Medical Center located in Seoul, and included the data of 285 persons in the final analysis. The results of the study are summarized as follows. First, as the results of examining the regression coefficients to predict the effectiveness of and satisfaction with the learning organization through the learning level, learning method and learning organization constructing level as the general variables, the important influential factors were shown as follows: 1)knowledge creation, knowledge storing, private learning, organizational learning, and learning organization construction of occupational and human levels as the factors to predict the working competency; 2) learning organization construction of the human level as the factors to assume the duty satisfaction; 3) gender, working years, private learning, team learning and organizational construction level for the prediction of the organizational commitment; and 4) medical technical service, knowledge creation, organization learning, and constructing level of the environmental and human levels for the assumption of the satisfaction with experience in the learning organization. Based on the study results of the effects in managing the learning organization, we can conclude the followings. First, the members who are in various working positions and occupations need to continuously participate in the learning organization. Second, to raise the organizational outcome from the management of the learning organization, it is necessary to establish systematic concepts in the constituents of the organizational effectiveness such as working competency improvement, duty satisfaction and organizational commitment, and the experience satisfaction of the learning organization. Finally, the future of the organization depends on the learning competencies of the organization members. To continuously exist and develop the organization, the private learning of the organizational members should be constantly spread and shared over the organizational level, and the usual innovations such as repetitive and habitual organizational learning should be generally tried out throughout the whole field of the management.

• KIPS Transactions on Software and Data Engineering
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• v.7 no.2
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• pp.43-50
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• 2018

Biometric information computing is greatly influencing both a computing system and Big-data system based on the bio-information system that combines bio-signal sensors and bio-information processing. Unlike conventional data formats such as text, images, and videos, biometric information is represented by text-based values that give meaning to a bio-signal, important event moments are stored in an image format, a complex data format such as a video format is constructed for data prediction and analysis through time series analysis. Such a complex data structure may be separately requested by text, image, video format depending on characteristics of data required by individual biometric information application services, or may request complex data formats simultaneously depending on the situation. Since previous bio-information processing computing systems depend on conventional computing component, computing structure, and data processing method, they have many inefficiencies in terms of data processing performance, transmission capability, storage efficiency, and system safety. In this study, we propose an improved biosensing converged big data computing architecture to build a platform that supports biometric information processing computing effectively. The proposed architecture effectively supports data storage and transmission efficiency, computing performance, and system stability. And, it can lay the foundation for system implementation and biometric information service optimization optimized for future biometric information computing.

• Journal of Bio-Environment Control
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• v.29 no.3
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• pp.285-292
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• 2020

Because the inner environment of greenhouse has a direct impact on crop production, many studies have been performed to develop technologies for controlling the environment in the greenhouse. However, it is difficult to apply the technology developed to all greenhouses because those studies were conducted through empirical experiments in specific greenhouses. It takes a lot of time and cost to develop the models that can be applicable to all greenhouse in real situation. Therefore studies are underway to solve this problem using computer-based simulation techniques. In this study, a model was developed to predict the inner environment of glass greenhouse using CFD simulation method. The developed model was validated using primary and secondary heating experiment and daytime greenhouse inner temperature data. As a result of comparing the measured and predicted value, the mean temperature and uniformity were 2.62℃ and 2.92%p higher in the predicted value, respectively. R² was 0.9628, confirming that the measured and the predicted values showed similar tendency. In the future, the model needs to improve by applying the shape of the greenhouse and the position of the inner heat exchanger for efficient thermal energy management of the greenhouse.

• Journal of the Korean Society for Railway
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• v.20 no.2
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• pp.275-287
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• 2017

During the feasibility study of new rail lines, maintenance cost of railway infrastructure has mostly been estimated based on the track length and on simplified parameters; however, the estimation reliability can be improved by employing the correction factor from UIC 715, as well as the line classification in UIC 714. The correlations between maintenance cost and various parameters such as weighted track length based on line classification, radius of curvature, gradient and worn -out rate have been analyzed according to the case studies. Prediction of the maintenance cost has been carried out using the cost data, which were representative of the whole cost data; as a result, it was demonstrated that a cost model based on the line classification and the correction factor was more reliable than the existing models. Furthermore, possibilities of using data from both the track measurement vehicle and from the maintenance information system, which are under development, have been investigated and, based on this investigation, a combined cost model using line classification, radius of curvature, gradient and worn-out rate, among other factors, will be proposed in the near future.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.30 no.5
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• pp.371-380
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• 2017

The risk-targeted seismic design concept was first included in ASCE/SEI 7-10 to address problems related to the uniform-hazard based seismic concept that has been constructed without explicitly considering probabilistic uncertainties in the collapse capacities of structures. However, this concept is not yet reflected to the current Korean building code(KBC) because of insufficient strong earthquake data occurred at the Korean peninsula and little information on the collapse capacities of structures. This study evaluates the risk-targeted seismic performance of steel ordinary concentrically braced frames(OCBFs). To do this, the collapse capacities of prototype steel OCBFs are assessed with various analysis parameters including building locations, building heights and soil conditions. The seismic hazard curves are developed using an empirical spectral shape prediction model that is capable of reflecting the characteristics of earthquake records. The collapse probabilities of the prototype steel OCBFs located at the Korean major cities are then evaluated using the risk integral concept. As a result, analysis parameters considerably influence the collapse probabilities of steel OCBFs. The collapse probabilities of taller steel OCBFs exceed the target seismic risk of 1 percent in 50 years, which the introduction of the height limitation of steel OCBFs into the future KBC should be considered.