• Clinical and Experimental Pediatrics
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• v.51 no.1
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• pp.33-41
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• 2008

Purpose : It is now understood that blood pressure (BP) measurement in the routine pediatric examination is very important because of the relevance of childhood BP to pediatric health care and the development of adult essential hypertension. There hasn't been a reference table of BP for Korean children and adolescents up to now. This study was to make normative BP references and to provide criteria of hypertension for Korean children and adolescents. Methods : BP measurements were done on 57,433 Koean children and adolescents (male: 29,443, female: 27,990), aged 7 to 20 years, in 2005. Heights and weights were measured simultaneously. Oscillometric devices, Dinamap Procare 200 (GE Inc., Milwaukee, Wi, USA), were used for the measurements. BPs were measured 2 times and mean levels were gathered for the analysis. Outliers of 2,373 subjects with overweight per height, over ＋3SD, were excluded for the analysis. For the BP centiles adjusted by sex, age and height, fixed modified LMS method which was adopted from the mixed effect model of 2004 Task Force in NHLBI (USA) was used. Results : Normative BP tables for Korean children and adolescents adjusted for height percentiles (5th, 10th, 25th, 50th, 75th, 90th, 95th), gender (male, female) and age(7 to 18 years) were completed. Height centiles of Korean children and adolescents are available from Korean Center for Disease Control and Prevention homepage, http://www.cdc.go.kr/webcdc/. Criteria of hypertension (95th, 99th percentile) and normal range of BP (50th, 90th) adjusted for height percentiles, age and gender were made. Conclusion : This is the first study to make normative BP tables and define hypertension for the Korean children and adolescents. Reliability and accuracy of Dinamap Procare 200 oscillometer for BP measurements remains debatable.

• Information Systems Review
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• v.6 no.2
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• pp.113-135
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• 2004

This paper defines appraisal items and weights of the items for the purpose of developing an appraisal instrument that objectively measures employee's effectiveness of knowledge contribution. Deductive research is used for the development of appraisal items and delphi method for the development of weights of the items. In the deductive research the term, "effectiveness of knowledge contribution" is first defined. Then knowledge contribution activities are classified as "dimension of explicit contribution" and " dimension of tacit contribution" due to the characteristics of knowledge. Each dimension is divided again by components. The dimension of explicit contribution is divided according to the content of knowledge, and the dimension of tacit contribution is divided according to the extent of tacitness of knowledge contribution. The total components of dimensions are 7. The dimension of explicit contribution is composed of factual knowledge and procedural knowledge. The factual knowledge is made up of "procedural knowledge outcome" and "other factual knowledge". The procedural knowledge is made up of "procedural knowledge manual" and "lessons-learned procedural knowledge". The dimension of tacit contribution is composed of "agency", "model" and "Q&A". The basic framework for measuring 7 components of knowledge contribution is quantitative and qualitative approach. This paper is premised on the assumption that the outcomes of employee's knowledge contribution activities are recorded in the knowledge management systems in order to evaluate them objectively. The appraisal items are defined as follows: at the dimension of explicit contribution, in quantitative approach, "the upload number" or "performance number", and in qualitative approach, other employee's "referred number" and other employee's "content and format satisfaction evaluation"; at the dimension of tacit contribution, "demanded number of performance" After the development of appraisal items by the deductive method, delphi method was used for the analysis of the weights of the items with the total degree of knowledge contribution, 100. This research does not include the standard marks of the appraisal items. It is because when companies apply this appraisal instrument, they could use their own standard appraisal marks of the appraisal items considering their present situations and companies' goals. Through this almost desert-like research about the appraisal instrument of employee's knowledge contribution effectiveness, it proposes a cornerstone in the research field of appraisal instrument, which provides a standard for employee's knowledge contribution appraisal, and appraisal items that make organizational knowledge to be managed more systemically in business sites.

• Journal of Wetlands Research
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• v.23 no.4
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• pp.327-341
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• 2021

The riparian eco-belt is an efficient technique that can reduce non-point pollution sources in the basin and improve ecological connectivity and health. In Korea, a legal system for the construction and management of riparian eco-belts is in operation. However, it is currently excluded that rivers and floodplains in dam reservoir that are advantageous for buffer functions such as control of non-point pollutants and ecological habitats. Accordingly, this study presented and analyzed a plan to select a site for an integrated riparian ecol-belt that comprehensively evaluates the water quality and ecosystem characteristics of each dam floodplain and riparian zone for the Daecheong Dam basin in Geum River watershed. First, the Daecheong Dam basin was divided into 138 sub-basin with GIS, and the riparian zone adjacent to the dam floodplain was analyzed. Sixteen evaluation factors related to the ecosystem and water quality impact that affect the selection of integrated riparian eco-belt were decided, and weights for the importance of each factor were set through AHP analysis. The priority of site suitability was derived by conducting an integrated evaluation by applying weights to sub-basin by floodplains and riparian zone factors. In order to determine whether the sites derived through GIS site analysis are sutiable for actual implementation, five sites were inspected according to three factors: land use, pollution sources, and ecological connectivity. As a result, it was confirmed that all sites were appropriate to apply integrated riparian ecol-belt. It is judged that the riparian eco-belt site analysis technique proposed through this study can be applied as a useful tool when establishing an integrated riparian zone management policy in the future. However, it might be necessary to experiment various evaluation factors and weights for each item according to the characteristics and issues of each dam. Additional research need to be conducted on elaborated conservation and restoration strategies considering the Green-Blue Network aspect, evaluation of ecosystem services, and interconnection between related laws and policy and its improvements.

• Journal of Intelligence and Information Systems
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• v.27 no.1
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• pp.177-190
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• 2021

Due to the development of the fourth industrial revolution technology, efforts are being made to improve areas that humans cannot handle by utilizing artificial intelligence techniques such as machine learning. Although on-demand production companies also want to reduce corporate risks such as delays in delivery by predicting total production time for orders, they are having difficulty predicting this because the total production time is all different for each order. The Theory of Constraints (TOC) theory was developed to find the least efficient areas to increase order throughput and reduce order total cost, but failed to provide a forecast of total production time. Order production varies from order to order due to various customer needs, so the total production time of individual orders can be measured postmortem, but it is difficult to predict in advance. The total measured production time of existing orders is also different, which has limitations that cannot be used as standard time. As a result, experienced managers rely on persimmons rather than on the use of the system, while inexperienced managers use simple management indicators (e.g., 60 days total production time for raw materials, 90 days total production time for steel plates, etc.). Too fast work instructions based on imperfections or indicators cause congestion, which leads to productivity degradation, and too late leads to increased production costs or failure to meet delivery dates due to emergency processing. Failure to meet the deadline will result in compensation for delayed compensation or adversely affect business and collection sectors. In this study, to address these problems, an entity that operates an order production system seeks to find a machine learning model that estimates the total production time of new orders. It uses orders, production, and process performance for materials used for machine learning. We compared and analyzed OLS, GLM Gamma, Extra Trees, and Random Forest algorithms as the best algorithms for estimating total production time and present the results.

• Journal of KIISE:Software and Applications
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• v.27 no.5
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• pp.529-542
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• 2000

Recent years, the use of multimedia information is rapidly increasing, and the video media is the most rising one than any others, and this field Integrates all the media into a single data stream. Though the availability of digital video is raised largely, it is very difficult for users to make the effective video access, due to its length and unstructured video format. Thus, the minimal interaction of users and the explicit definition of video structure is a key requirement in the lately developing image and video management systems. This paper defines the terms and hierarchical video structure, and presents the system, which construct the clustering-based video hierarchy, which facilitate users by browsing the summary and do a random access to the video content. Instead of using a single feature and domain-specific thresholds, we use multiple features that have complementary relationship for each other and clustering-based methods that use normalization so as to interact with users minimally. The stage of shot boundary detection extracts multiple features, performs the adaptive filtering process for each features to enhance the performance by eliminating the false factors, and does k-means clustering with two classes. The shot list of a result after the proposed procedure is represented as the video hierarchy by the intelligent unsupervised clustering technique. We experimented the static and the dynamic movie videos that represent characteristics of various video types. In the result of shot boundary detection, we had almost more than 95% good performance, and had also rood result in the video hierarchy.

• Journal of the Korea Society of Computer and Information
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• v.18 no.4
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• pp.131-140
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• 2013

This paper deals with the design and implementation of an interface for interoperation between DiskSim, a well-known disk simulator, and a system-level simulator based on DEVSim++. Such inter-operational simulation aims at evaluation of an overall performance of storage systems which consist of multiple computer nodes with a variety of I/O level specifications. A well-known system-level simulation framework, DEVSim++ environment is based on the DEVS formalism, which provides a sound semantics of modular and hierarchical modeling methodology at the discrete event systems level such as multi-node computer systems. For maintainability we assume that there is no change of the source codes for two heterogeneous simulation engines. Thus, we adopt a notion of simulators interoperation in which there should be a means to synchronize simulation times as well as to exchange messages between simulators. As an interface for such interoperation DiskSimManager is designed and implemented. Various experiments, comparing the results of the standalone DiskSim simulation and the interoperation simulation using the proposed interface of DiskSimManager, proved that DiskSimManager works correctly as an interface for interoperation between DEVSim++ and DiskSim.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.38 no.4
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• pp.579-586
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• 2018

Short-term prediction of travel speed has been widely studied using data-driven non-parametric techniques. There is, however, a lack of research on the prediction aimed at urban areas due to their complex dynamics stemming from traffic signals and intersections. The purpose of this study is to develop a hybrid approach combining ensemble empirical mode decomposition (EEMD) and artificial neural network (ANN) for predicting urban travel speed. The EEMD decomposes the time-series data of travel speed into intrinsic mode functions (IMFs) and residue. The decomposed IMFs represent local characteristics of time-scale components and they are predicted using an ANN, respectively. The IMFs can be predicted more accurately than their original travel speed since they mitigate the complexity of the original data such as non-linearity, non-stationarity, and oscillation. The predicted IMFs are summed up to represent the predicted travel speed. To evaluate the proposed method, the travel speed data from the dedicated short range communication (DSRC) in Daegu City are used. Performance evaluations are conducted targeting on the links that are particularly hard to predict. The results show the developed model has the mean absolute error rate of 10.41% in the normal condition and 25.35% in the break down for the 15-min-ahead prediction, respectively, and it outperforms the simple ANN model. The developed model contributes to the provision of the reliable traffic information in urban transportation management systems.

• Journal of Korea Multimedia Society
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• v.12 no.7
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• pp.989-996
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• 2009

Recently, use of the GIS (Geographic Information System) for the disaster of the urban inundation is increasing. The digital disaster map is the system which analyzes the occurrence area of inundation in the past and forecasts the flood areas by the hydrology method. The development of the system which simulates the flood forecast area by the SWMM(Storm Water Management System) and hydrology method and displays the danger areas is required for the construction of the inundation forecast system. And the spatial database which contains information of the urban facilities such as the street and building and the sewer system such as the manhole and drainage and the result of the hydrology analysis is constructed. In this paper, we propose the method for transforming the Shape File in ESRI into the Oracle spatial database to construct the spatial data for the drainage systems and urban facilities using the Shape File format in the ESRI. We suggest the algorithm for the transformation of the data format, and develop the prototype system to display the inundation area using the spatial database.

• Journal of Korea Water Resources Association
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• v.42 no.8
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• pp.591-605
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• 2009

In this study the risk integrated erosion and seepage failure factor and combined risk of the levee embankment were assessed. For the research of the reliability, the risk assessment of erosion, seepage and both of them combined for the levee embankment were conducted using discharge curve and stage hydrograph generated by stochastic rainfall variation method during typhoon and monsoon season. The risk of erosion was evaluated using tractive force and the seepage analysis was performed by selecting representative cross sections for SEEP/W model analysis. And the probability of seepage failure was assessed with MFOSM analysis using critical hydraulic gradient method. Unlike deterministic analysis method, quantitative risk could be obtained and the characteristics of realistic rainfall variation patterns as well as a variety of factors contributing to levee failure could be reflected in this research. The results of this study show significantly enhanced applicability for the combined risk. As this model can be employed to determine dangerous spots for levee failure and to establish flood insurance linked with flood risk map, it will dramatically contribute to the establishment of both efficient and systematic measures for integrated flood management on a watershed.

• Journal of Digital Convergence
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• v.13 no.12
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• pp.245-257
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• 2015

This study was to develop the predictive model for severity-adjusted mortality of inpatients with multiple chronic conditions and analyse the factors on the variation of hospital standardized mortality ratio(HSMR) to propose the plan to reduce the variation. We collect the data "Korean National Hospital Discharge In-depth Injury Survey" from 2008 to 2010 and select the final 110,700 objects of study who have chronic diseases for principal diagnosis and who are over the age of 30 with more than 2 chronic diseases including principal diagnosis. We designed a severity-adjusted mortality predictive model with using data-mining methods (logistic regression analysis, decision tree and neural network method). In this study, we used the predictive model for severity-adjusted mortality ratio by the decision tree using Elixhauser comorbidity index. As the result of the hospital standardized mortality ratio(HSMR) of inpatients with multiple chronic conditions, there were statistically significant differences in HSMR by the insurance type, bed number of hospital, and the location of hospital. We should find the method based on the result of this study to manage mortality ratio of inpatients with multiple chronic conditions efficiently as the national level. So we should make an effort to increase the quality of medical treatment for inpatients with multiple chronic diseases and to reduce growing medical expenses.