• KIPS Transactions on Software and Data Engineering
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• v.9 no.4
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• pp.137-144
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• 2020

Delirium is among the most common mental disorders encountered in patients with a temporary cognitive impairment such as consciousness disorder, attention disorder, and poor speech, particularly among those who are older. Delirium is distressing for patients and families, can interfere with the management of symptoms such as pain, and is associated with increased elderly mortality. The purpose of this paper is to generate useful clinical knowledge that can be used to distinguish the outcomes of patients with delirium in long-term care facilities. For this purpose, we extracted the clinical classification knowledge associated with delirium using a local covering rule acquisition approach with the rough lower approximation region. The clinical applicability of the proposed method was verified using data collected from a prospective cohort study. From the results of this study, we found six useful clinical pieces of evidence that the duration of delirium could more than 12 days. Also, we confirmed eight factors such as BMI, Charlson Comorbidity Index, hospitalization path, nutrition deficiency, infection, sleep disturbance, bed scores, and diaper use are important in distinguishing the outcomes of delirium patients. The classification performance of the proposed method was verified by comparison with three benchmarking models, ANN, SVM with RBF kernel, and Random Forest, using a statistical five-fold cross-validation method. The proposed method showed an improved average performance of 0.6% and 2.7% in both accuracy and AUC criteria when compared with the SVM model with the highest classification performance of the three models respectively.

• Economic and Environmental Geology
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• v.41 no.6
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• pp.747-761
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• 2008

In order to experiment the acoustic remote classification of seabed sediment, we achieved ground-truth data(i.e. video and grab samples, etc.) and developed post-processing for automatic classification procedure on the basis of 300 kHz MultiBeam Echo Sounder(MBES) backscattering data, which was acquired using KONGBERG Simrad EM3000 at Sock-Cho Port, East Sea of South Korea. Sonar signal and its classification performance were identified with geo-referenced video imagery with the aid of GIS (Geographic Information System). The depth range of research site was from 5 m to 22.7 m, and the backscattering amplitude showed from -36dB to -15dB. The mean grain sizes of sediment from equi-distanced sampling site(50 m interval) varied from 2.86$(\phi)$ to 0.88(\phi). To acquire the main feature for the seabed classification from backscattering amplitude of MBES, we evaluated the correlation factors between the backscattering amplitude and properties of sediment samples. The performance of seabed remote classification proposed was evaluated with comparing the correlation of human expert segmentation to automatic algorithm results. The cross-model perception error ratio on automatic classification algorithm shows 8.95% at rocky bottoms, and 2.06% at the area representing low mean grain size.

• Journal of Korean Society of Transportation
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• v.32 no.6
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• pp.567-578
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• 2014

The study suggested a method to improve analysis accuracy such that the interactive effects of transportation changes between outside and inside of sub-areas were sequentially considered in the analysis by linking a macroscopic network analysis and a microscopic traffic simulation. A dynamic O/D estimation method was developed for practical implement of sub-area microscopic simulation analysis by using the results of macroscopic network analysis, the results of selected link analysis at the cordon line of the sub-area, departure time data of household travel survey, timely observed traffic volume data at the cordon. This estimated dynamic O/D for the sub-area made it possible to analyze traffic phenomena in details. Various detailed phenomena such as traffic queues, delay at intersection, and conflicts between vehicles, which is impossible to be grasped through a macroscopic analysis, can be analyzed with the dynamic microscopic traffic analysis. Through implementing an empirical study and validation, the study provided a reference result about accuracy of a microscopic traffic simulation of a sub-area to help its application for real transportation policy analysis.

• Journal of Korean Society of Transportation
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• v.27 no.6
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• pp.139-146
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• 2009

While air pollutants emission caused by the traffic is one of the major sources, few researches have done. This study investigated the extent to which traffic and road related characteristics such as traffic volumes, speeds and road weather data including wind speed, temperature and humidity, as well as the road geometry affect the air pollutant emission. We collected the real time air pollutant emission data from Seoul automatic stations and real time traffic volume counts as well as the road geometry. The regression air pollutant emission models were estimated. The results show followings. First, the more traffic volume increase, the more pollutant emission increase. The more vehicle speed increase, the more measurement quantity of pollutant decrease. Secondly, as the wind speed, temperature, and humidity increase, the amount of air pollutant is likely to decrease. Thirdly, the figure of intersections affects air pollutant emission. To verify the estimated models, we compared the estimates of the air pollutant emission with the real emission data. The result show the estimated results of Chunggae 4 station has the most reliable data compared with the others. This study is differentiated in the way the model used the real time air pollutant emission data and real time traffic data as well as the road geometry to explain the effects of the traffic and road characteristics on air quality.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.28 no.3
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• pp.305-315
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• 2010

This research aims to develop a method to determine the 3D coordinates of an object point from overlapping omni-directional images acquired by a ground mobile mapping system and assess their accuracies. In the proposed method, we first define an individual coordinate system on each sensor and the object space and determine the geometric relationships between the systems. Based on these systems and their relationships, we derive a straight line of the corresponding object point candidates for a point of an omni-directional image, and determine the 3D coordinates of the object point by intersecting a pair of straight lines derived from a pair of matched points. We have compared the object coordinates determined through the proposed method with those measured by GPS and a total station for the accuracy assessment and analysis. According to the experimental results, with the appropriate length of baseline and mutual positions between cameras and objects, we can determine the relative coordinates of the object point with the accuracy of several centimeters. The accuracy of the absolute coordinates is ranged from several centimeters to 1 m due to systematic errors. In the future, we plan to improve the accuracy of absolute coordinates by determining more precisely the relationship between the camera and GPS/INS coordinates and performing the calibration of the omni-directional camera

• Journal of Korea Water Resources Association
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• v.46 no.7
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• pp.697-706
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• 2013

In recent, Korea has faced on water quality management problems in reservoir and river because of increasing water temperature and rainfall frequency caused by climate change. This study is effectively to manage water quality for establishment of algal bloom forecasting models with artificial neural network. Daecheong reservoir located in Geum river has suitable environment for algal bloom because it has lots of contaminants that are flowed by rainfall. By using back propagation algorithm of artificial neural networks (ANNs), a model has been built to forecast the algal bloom over short-term (1, 3, and 7 days). In the model, input factors considered the hydrologic and water quality factors in Daecheong reservoir were analyzed by cross correlation method. Through carrying out the analysis, input factors were selected for algal bloom forecasting model. As a result of this research, the short term algal bloom forecasting models showed minor errors in the prediction of the 1 day and the 3 days. Therefore, the models will be very useful and promising to control the water quality in various rivers.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.30 no.3
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• pp.269-277
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• 2012

Street trees are one of useful urban facilities that reduce carbon dioxide and provide green space in urban areas. They are usually managed by local government, and it is effective to use aerial LIDAR data in order to acquire information such as the location, height and crown width of street tree systematically. In this research, algorithm was proposed that improves the accuracy of extracting top points of street trees and separates the region of individual street trees from aerial LIDAR data. In order to verify the proposed algorithm, a simulated aerial LIDAR data that exactly knows the number, height and crown width of street trees was created. As for the procedure of data processing, filtering that separates ground and non-ground points from LIDAR data was first conducted in order to separate the region of individual street trees. An estimated non-street tree points were then removed from non-ground points, and the top points of street trees were estimated. Region of individual street trees was determined by using the intersecting point of straight line that connects top point and ground point of street tree. Through the experiment by using simulated data, it was possible to refine wrongly estimated points occurred by determining tree tops and to determine the positional information, height, crown width of street trees through the determination of region of street trees.

• Journal of the Korean Society of Clothing and Textiles
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• v.26 no.12
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• pp.1765-1777
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• 2002

본 연구에서는 현재 국내의 서울시내에 거주하는 모터사이클을 타는 만20세 이상의 남성을 대상으로 모터사이클복에 대한 착용실태와 불만사항들을 조사하고 이를 연령별, 모터사이클 유형별로 비교 분석하여 착용감 및 안전성이 향상된 모터사이클복 개발을 위한 기초자료를 제시 하고자 하였다. 설문조사는 2002년 1월~3월까지 3개월간 총 400부를 배부한 후 회수하고, 이 중 262부를 분석자료로 사용하여 빈도 및 백분율, 평균 등의 기술 통계치를 얻어 전반적인 착용현황을 알아보고, 교차분석을 실시한 후 X$^2$-검증을 실시하여 연령별, 모터사이클 유형별, 운행경력 별로 통계적인 차이를 비교 분석하였다. 1. 모터사이클복의 착용실태 및 불만사항 전반에 관한 조사결과, 조사대상자는 20대~40대의 운행경력은 5년 이상인 전문 라이더들이 많았으며 모터사이클의 배기량은 400cc이상이 가장 높게 나타났고, 모터사이클 유형은 로드 바이크가 가장 높게 나타났고, 이용목적은 레져.취미용, 선호하는 모터사이클복 아이템별 소재는 원피스와 슬랙스의 경우에는 피혁소재가 쟈켓의 경우에는 텍스타일 소재가 높게 나타났다. 아이템별 소유는 쟈켓과 투피스가 높게 나타났고, 보호구가 필요하다고 생각되는 신체부위는 상의에서는 가슴과 팔꿈치, 하의에서는 무릎으로 나타났으며, 무릎보호대의 소유도가 가장 높게 나타났다. 모터사이클복 주된 착용목적은 '부상방지', 모터사이클복을 착용하지 않는 이유는 '움직이기가 불편해서' '가격이 비싸서' '여름철에 더워서'가 각각 높게 나타났다. 모터사이클복에 대한 불만족도에서 동작적합성과 사이즈에 대한 불만도가 높게 나타났고, 모터사이클복소재 및 내부 장착 보호장구의 경량화가 요구되었으며, 모터사이클 쟈켓의 치수부적합부위는 소매길이가 가장높게 나타났다. 2. 전체 응답자의 연령을 20대, 30대, 40대 이상으로 나누어 연령별 차이를 비교한 결과 각각의 문항에 대해서 모두 연령대별로 유의차가 인정되었다. 3. 모터사이클복 아이템별 선호소재 문항에서 원피스와 쟈켓에서 모터사이클 기종별 유의차가 나타났는데, 비즈니스 기종에 서는 텍스타일 소재를, 아메리칸크루져 기종에서는 피혁소재를 선호하였다. 로드바이크와 오프로드 기종에서는 원피스는 피혁소재를 선호하였고, 쟈켓은 텍스타일 소재를 선호하는 것으로 나타났다.

• Journal of Life Science
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• v.28 no.5
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• pp.587-596
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• 2018

This study aims to observe changes in heart-rate variability (HRV) indices induced by e-cigarette and conventional-cigarette smoking and to compare the differences in acute cardiac autonomic regulation. All participants (n=41) were exposed to both e-cigarette smoke (ES) and conventional cigarette smoke (CS) in a randomized crossover trial. HRV analysis was performed during each smoking session based on a recorded r-r interval 10 minutes before smoking and at specified recovery periods (REC1, 0-5 min; REC2, 5-10 min; REC3, 10-15 min; REC4, 15-20 min; REC5, 20-25 min; and REC6, 25-30 min). ES led to a significantly increased cardiac sympathetic index (LF/HF ratio) compared with the baseline, and it shifted the sympathovagal balance toward sympathetic predominance, including reduction in the complexity of the interbeat interval (SampEn). In REC1 after ES, only decreases of parasympathetic indices such as rMSSD, pNN50, HF, and SD1 were indicated. CS sessions produced not only an increased LF/HF ratio during smoking and recovery periods (REC1 and REC4) but also enhanced sympathetic predominance on autonomic balance during smoking and recovery periods (REC1, REC2, and REC4). In the CS trials, parasympathetic indices of time and non-linear analysis (rMSSD, pNN50, and SD1) were decreased during smoking and in REC1 to REC5. SampEn was also reduced during smoking and REC1 to REC4. Acute sympathoexcitatory effects induced by e-cigarette use produced statistically significant results. Parasympathetic withdrawal after smoking suggests that e-cigarettes may cause increased cardiovascular risk.

• Journal of Gifted/Talented Education
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• v.20 no.1
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• pp.289-316
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• 2010

The purpose of this study was to investigate the relationship between thinking style and learning style of gifted children in elementary school. The subjects were 178 fourth, fifth and sixth grade elementary school students who enrolled in gifted education program. They were given the Thinking Style Questionnaire and the Grasha Reichmann Student Learning Style Questionnaire. Descriptive statistics, correlation analysis and canonical correlation analysis were performed. Results indicated that gifted students prefer legislative, judical, liberal, local, hierarchic, external thinking styles known to be related to creative and critical thinking rather than executive and conventional styles. Meanwhile, in the aspect of learning style, independent learning style than the dependent learning style, competitive style than the collaborative style, and participatory style than the avoiding style were significantly scored higher. The canonical analysis showed that thinking styles and learning styles share 59%(Rc=.77) each other, indicating the two variables had significant close relationship. External, liberal, hierarchic, judical, executive, and liberal thinking styles in the order named showed higher cross loading in the independent variable set, likewise independent, participatory, collaborative, and competitive learning styles in the dependant variable set. The results indicate that the external, liberal, hierarchic, judical, executive, and liberal thinking styles can be the significant predictors of independent, participatory, collaborative, and competitive learning styles. The implications of the study related to the gifted education were discussed in depth.