• Journal of Korea Water Resources Association
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• v.55 no.8
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• pp.613-621
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• 2022

Due to the global climate change, the rainfall volume and frequency on the Korean Peninsula are predicted to increase at the end of the 21st century. In addition, impervious surface areas have increased due to rapid urbanization which has caused the urban water cycle to deteriorate. Green Infrastructure (GI) researches have been conducted to improve the water cycle soundness; the efficiency of this technique has been verified through various studies. However, there are still no suitable GI design guidelines for this aspect. Therefore, the rainfall scenarios are set up for each percentile (60, 70, 80, 90) based on the volume and frequency analysis using 10-year rainfall data (Busan Meteorological Station). After determining the GI areas for each scenario, the runoff reduction characteristics are analyzed based on Storm Water Management Model (SWMM) 10-year rainfall-runoff-simulations. The total runoff reduction efficiency for each GI areas are computed to have a range of 13.1~52.1%. As a results of the quantitative analysis, the design rainfall for GI is classified into the 80~85 percentile in the study site.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.10 no.2
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• pp.447-454
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• 2009

This study investigates to information medium and small enterprises and analyzed how enterprise's integration information system affects to business users. Many medium and small enterprises are introducing and operate new integrated system for latest several years, but it is suffering difficulty in substantial business analysis as unstable system, maintenance and insufficiency of management controls. Therefore, in this study, tried to analyze common problem and solution to enterprise which is operating integration information system stably. Designed study model and research hypothesis to variable of information level, system availability, information availability, information creation level, service availabilities for this analysis. This studγ got conclusion as following. First, If system usefulness, information usefulness, information creation level, service usefulness are high, Analysis result about user business performance appeared very positive effect. Second, Analyzed to which lack a little user realization about information level in details measured variable. This study will be able to become data that is useful in stable system introduction in various field of industry of medium and small enterprises hereafter.

• Korean Journal of Remote Sensing
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• v.28 no.1
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• pp.171-180
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• 2012

The field of wildlife habitat conservation research has attracted attention as integrated biodiversity management strategies. Considering the status of the species surveying data and the environmental variables in Korea, the GARP and Maxent models optimized for presence-only data could be one of the most suitable models in habitat modeling. For make sure applicability in the domestic environment we applied the machine learning species distribution model for analyzing habitats of the Korea water deer($Hydropotes$ $inermis$ $argyropus$) in the $Sapgyocheon$ watershed, $Chungcheong$ province. We used the $3^{rd}$ National Natural Environment Survey data and 10 environment variables by literature review for the modelling. Analysis results showed that habitats for the Korea water deer were predicted 16.3%(Maxent) and 27.1%(GARP), respectively. In terms of accuracy(training/test) the Maxent(0.85/0.69) was higher than the GARP(0.65/0.61), and the Spearman's rank correlation coefficient result of the Maxent(${\rho}$=0.71, p<0.01) was higher than the result of GARP(${\rho}$=0.55, p<0.05). However results could be depended on sites and target species, therefore selection of the appropriate model considering on the situation will be important to analyzing habitats.

• Journal of Korean Society of Transportation
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• v.26 no.5
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• pp.163-174
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• 2008

The conventional four-step travel demand model is still widely used as the state-of-practice in most transportation planning agencies even though it does not provide reliable estimates of travel demand. In order to improve the accuracy of travel demand estimation, implementing an alternative approach would be critical as much as acquiring reliable socioeconomic and travel data. Recently, the role of travel demand model is diverse to satisfy the needs of microscopic analysis regarding various policies of travel demand management and traffic operations. In this context, the activity-based approach for travel demand estimation is introduced and a case study of developing a spatial-temporal activity presence-based approach that estimates travel demand through forecasting number of people present at certain place and time is accomplished. Results show that the spatial-temporal activity presence-based approach provides reliable estimates of both number of people present and trips actually people made. It is expected that the proposed approach will provide better estimates and be used in not only long-term transport plans but short-term transport impact studies with respect to various transport policies. Finally, in order to introduce the spatial-temporal activity presence-based approach, the data such as activity-based travel diary and land use based on geographic information system are essential.

• Journal of the Korea Convergence Society
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• v.9 no.5
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• pp.33-41
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• 2018

The purpose of this study is to develop more accurate and robust emotion prediction neural network (EPNN) model by combining heart rate variability (HRV) and neural network. For the sake of improving the prediction performance more reliably, the proposed EPNN model is based on various types of activation functions like hyperbolic tangent, linear, and Gaussian functions, all of which are embedded in hidden nodes to improve its performance. In order to verify the validity of the proposed EPNN model, a number of HRV metrics were calculated from 20 valid and qualified participants whose emotions were induced by using money game. To add more rigor to the experiment, the participants' valence and arousal were checked and used as output node of the EPNN. The experiment results reveal that the F-Measure for Valence and Arousal is 80% and 95%, respectively, proving that the EPNN yields very robust and well-balanced performance. The EPNN performance was compared with competing models like neural network, logistic regression, support vector machine, and random forest. The EPNN was more accurate and reliable than those of the competing models. The results of this study can be effectively applied to many types of wearable computing devices when ubiquitous digital health environment becomes feasible and permeating into our everyday lives.

• Journal of Korea Water Resources Association
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• v.43 no.8
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• pp.733-745
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• 2010

Seasonality of hydrologic extreme variable is a significant element from a water resources managemental point of view. It is closely related with various fields such as dam operation, flood control, irrigation water management, and so on. Hydrological frequency analysis conjunction with partial duration series rather than block maxima, offers benefits that include data expansion, analysis of seasonality and occurrence. In this study, nonstationary frequency analysis based on the Bayesian model has been suggested which effectively linked with advantage of POT (peaks over threshold) analysis that contains seasonality information. A selected threshold that the value of upper 98% among the 24 hours duration rainfall was applied to extract POT series at Seoul station, and goodness-fit-test of selected GEV distribution has been examined through graphical representation. Seasonal variation of location and scale parameter ($\mu$ and $\sigma$) of GEV distribution were represented by Fourier series, and the posterior distributions were estimated by Bayesian Markov Chain Monte Carlo simulation. The design rainfall estimated by GEV quantile function and derived posterior distribution for the Fourier coefficients, were illustrated with a wide range of return periods. The nonstationary frequency analysis considering seasonality can reasonably reproduce underlying extreme distribution and simultaneously provide a full annual cycle of the design rainfall as well.

• Korean Journal of Construction Engineering and Management
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• v.16 no.5
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• pp.114-122
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• 2015

Real estate development requires significant amount of capital investment. The project duration has been increased according to its enlarged size. For this reason, cost overrun and time delay are important risk factors that should be managed properly. As a method to hedge the risk, varoius real option methods have been presented. However, conventional project value assesment methods such as NPV(Net Present Value) have weakness to support decision making by reflecting dynamic situations in terms of variation of cost and time. Furthermore, the decision making process is serious of actions rather than discrete event. The purpose of this paper is to present a multiple real option valuation method to overcome the deterministic aspect of real option presented in previous research and practice. The method is developed as following: firstly, to select the model that can be applied in the real estate development project through a survey from previous literature on real options analysis; secondly, to apply data from office development case in order to verify the model by applying conventional real option and multiple real option valuation. According to analysis result, multiple real option provides enhanced values comparing to NPV and single real option.

• Korean Journal of Heritage: History & Science
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• v.54 no.1
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• pp.184-205
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• 2021

Governance is valued as a new concept and principle of social operation and public policy management, and its influence is gradually expanding. Among the various governance theories being put into practice and in case analysis studies, collaborative governance embracing various governance concepts has been found to increase interdependence and responsibility beyond participation and compromise, and create new public values by integrating and utilizing optimal social coordination forms. In the field of cultural assets, governance-related research is also being conducted for the efficiency, sustainability, and scalability of public policy enforcement. This study explored the government's role (promotion, arbitration, and condition creation) in collaborative governance, focusing on the "Cultural Heritage Guardians" to understand how collaborative governance operates in the cultural heritage sector. Regarding governance policies in the cultural asset sector, the cultural asset guardians highlighted the status, role, and characteristics of policies by examining their introduction, development, and implementation. The results of the analysis revealed that private-led, horizontal public-private cooperation, collaborative governance, policy introduction, solidarity, professionalism, resource/knowledge imbalance, cooperation precedence, etc., facilitate increased participation. The government has accordingly proposed measures to establish comprehensive legal stability centered on cooperation; strategic reorganization of dedicated organizations; strengthened, supportive intermediate organizations; and individual and multi-party consultative bodies.

• Information Systems Review
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• v.23 no.3
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• pp.97-125
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• 2021

Blockchain is a core technology to solve personal information leakage and data management issues, which are limitations of existing Genomic Sequencing services. Due to continuous cost reduction and deregulation, the market size of Genomic Sequencing has been increasing, also the potential of services is expected to increase when Blockchain's security and connectivity are combined. We created our research model by combining the Technology Acceptance Model (TAM) and the Innovation Resistance Theory also analyzed the factors affecting the acceptance intention and innovation resistance of the Blockchain Based Genomic Sequencing Information Platform. A survey was conducted on 150 potential users of Blockchain and Genomic Sequencing services. The analysis was conducted by setting the four Blockchain variables: Security, transparency, availability, and diversity). Also, we set the Perceived Usefulness, Perceived risk, and Perceived Complexity for Technology Acceptance and Innovation Resistance variables and analyzed the effect of the characteristics of the Blockchain on acceptance intention and innovation resistance through these variables. Through this analysis, key variables that need to be considered important to reduce resistance and increase acceptance intention could be identified. This study presents innovation factors that should be considered in companies preparing a new Blockchain Based Genomic Sequencing Information Platform.

• The Journal of Bigdata
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• v.1 no.1
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• pp.23-32
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• 2016

With the rapid development of information technology, we can manage not only structured data but also unstructured data. Big data environments drive new business values. This study examines the effect of analytic resources to business performance under big data environments. Recent worldwide reports showed empirical performance results of big data applications. Compared to these reports, we attempt to analyze resources of big data applications to companies in Korea. This study results in current status of big data use in Korea. and will help to develop a maturity model of big data applications.