• Journal of Korean Society of Environmental Engineers
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• v.34 no.3
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• pp.177-188
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• 2012

This study was mainly focused on the development of GIS based decision support system to easily make mitigation scenarios and to conveniently simulate water quality for TMDL. The study area was the 31km section of upper Sapgyo stream in Geum river basin, and QUAL2E model was adopted. GIS DB was built through the collection of the data which includes point/non-point source attributes and various thematic maps. The amounts of discharged loads of BOD, T-N and T-P from unit watershed were estimated respectively. Finally, the system, which can operate water quality simulation through simply modifying their values, was developed. The hypothetical three mitigation scenarios were applied, thereby the most efficient mitigation scenario could be chosen by comparison of the results based on GIS. Therefore, it is expected that the developed system can facilitate the decision makers to select the best alternative through the analysis of the available BMPs. Also, it can be used to develop new scenarios using different methods and algorithms. In the future, more study need to be made to enhance its applicability in the perspective of developing mitigation scenarios through the management of individual pollutant sources and extending study areas.

• Journal of Korea Water Resources Association
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• v.50 no.3
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• pp.155-167
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• 2017

Accurate QPE (Quantitative Precipitation Estimation) and the quality of the rainfall data for hydrological analysis are very important factors. Especially, the quality has a great influence on flood runoff result. It needs to know characteristics of the uncertainties in radar QPE for the reliable flood analysis. The purpose of this study is to present a probabilistic approach which defines the range of possible values or probabilistic distributions rather than a single value to consider the uncertainties in radar QPE and evaluate its applicability by applying it to radar rainfall. This study generated radar rainfall ensemble for the storms by the typhoon 'Sanba' on Namgang dam basin, Korea. It was shown that the rainfall ensemble is able to simulate well the pattern of the rain-gauge rainfall as well as to correct well the overall bias of the radar rainfall. The suggested ensemble technique represented well the uncertainties of radar QPE. As a result, the rainfall ensemble model by a probabilistic approach can provide various rainfall scenarios which is a useful information for a decision making such as flood forecasting and warning.

• Information Systems Review
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• v.17 no.3
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• pp.95-111
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• 2015

The recommendation system automatically provides the predicted items which are expected to be purchased by analyzing the previous customer behaviors. This recommendation system has been applied to many e-commerce businesses, and it is generating positive effects on user convenience as well as the company's revenue. However, there are several limitations of the existing recommendation systems. They do not reflect specific criteria for evaluating products or the factors that affect customer buying decisions. Thus, our research proposes a collaborative recommendation model algorithm that utilizes each customer's online product reviews. This study deploys topic modeling method for customer opinion mining. Also, it adopts a kernel-based machine learning concept by selecting kernels explaining individual similarities in accordance with customers' purchase history and online reviews. Our study further applies a multiple kernel learning algorithm to integrate the kernelsinto a combined model for predicting the product ratings, and it verifies its validity with a data set (including purchased item, product rating, and online review) of BestBuy, an online consumer electronics store. This study theoretically implicates by suggesting a new method for the online recommendation system, i.e., a collaborative recommendation method using topic modeling and kernel-based learning.

• Journal of Distribution Research
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• v.15 no.4
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• pp.21-60
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• 2010

In recent retail environments, multichannel customer management increasingly has been considered a key element of successful CRM. Although customer's multichannel usage is believed to be potential cause of customer loyalty, the theoretical explanation about this causal relationship still remains unexamined and unanswered. In this paper, the authors present a systematic framework to test the postulated "multichannel usage-shopping experience-customer satisfaction" chain. To this end, we examine that the two core components of shopping experience(convenience and enjoyment) is a mediator of the direct causality of multichannel usage(based on both information search and product purchase stage) on customer satisfaction. Moreover, the authors examine that two types of customer-firm relationship characteristics(relationship age and purchase frequency) is a moderator of the multichannel usage-shopping experience relationship. Using integrating data with survey and customer database of multichannel retail company, the authors empirically test and substantiate shopping experience's mediating role in the multichannel usage-customer satisfaction relationship and customer-firm relationship characteristics' moderating role in the multichannel usage-customer experience relationship. These results suggest that multichannel retailers should deliver favorable shopping experience for building customer satisfaction and differentiate shopping experience according to customer-firm relationship characteristics.

• Journal of dental hygiene science
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• v.9 no.2
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• pp.203-210
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• 2009

The following are the results of questionnaire research targeting 213 people at 4 dental clinics in Geoje region in order to examine recognition on the periodontal health in Inpatients of dental clinic. 1. In the item of recognition on periodontal health, the patients, who know about whether or not recognizing periodontal disease, were indicated to be 62.9%. Women were knowing better than men. The significant difference by gender was indicated(p < .01). As for a route of acquiring information on periodontal disease, a case of obtaining via television and internet was surveyed to be 31.6%. As for recognition on frequency of tooth scaling, a case of recognition as saying of the necessity of doing once a year was indicated to be 43.7%. The significant difference was indicated depending on job and academic background(p < .001). 2. As for the periodontal-health status, the patients of recognizing that the condition in the gums is mostly healthy were indicated to be 75.1%. The more professional job led to showing the significant difference depending on occupation(p < .001). As for a reason for a visit to dentistry, a case of visiting due to smell in the mouth was indicated to be 18.1%. As for kinds of dental treatment, the patients. who received the tooth scaling by visiting a dental clinic. were the largest with 46.5%. The significant difference was indicated depending on job(p < .01), academic background(p < .05), And monthly income(p < .001).

• Journal of health informatics and statistics
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• v.42 no.4
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• pp.309-316
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• 2017

Objectives: Radon and its progeny pose environmental risks as a carcinogen, especially to the lungs. Investigating factors affecting indoor radon concentrations and models thereof are needed to prevent exposure to radon and to reduce indoor radon concentrations. The purpose of this study was to identify factors affecting indoor radon concentration and to construct a comprehensive model thereof. Methods: Questionnaires were administered to obtain data on residential environments, including building materials and life style. Decision tree and structural equation modeling were applied to predict residences at risk for higher radon concentrations and to develop the comprehensive model. Results: Greenery ratio, impermeable layer ratio, residence at ground level, daily ventilation, long-term heating, crack around the measuring device, and bedroom were significantly shown to be predictive factors of higher indoor radon concentrations. Daily ventilation reduced the probability of homes having indoor radon concentrations ${\geq}200Bq/m^3$ by 11.6%. Meanwhile, a greenery ratio ${\geq}65%$ without daily ventilation increased this probability by 15.3% compared to daily ventilation. The constructed model indicated greenery ratio and ventilation rate directly affecting indoor radon concentrations. Conclusions: Our model highlights the combined influences of geographical properties, groundwater, and lifestyle factors of an individual resident on indoor radon concentrations in Korea.

• Proceedings of the Korea Water Resources Association Conference
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• 2018.05a
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• pp.417-418
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• 2018

미국 국립가뭄경감센터 (National Drought Mitigation Center, NDMC)는 다양한 가뭄지수를 통합하여 미국 전역의 가뭄진행상황을 모니터링하고 가뭄대응정책 수립을 위한 주요 의사결정정보로 활용하고 있다. 대표적으로 1999년에 개발되어 현재까지 운영 중인 미국가뭄모니터 (United States Drought Monitor, USDM)는 미국 전역에 대하여 가뭄단계를 표시한 지도 (U.S. Drought Monitor map)를 매주 생성하여 제공하고 있다 (http://droughtmonitor.unl.edu/). 가뭄지표(drought index)는 가뭄의 현황과 시공간적인 전개 과정을 분석하고 정량적 가뭄심도 평가 및 가뭄대응계획 수립을 위한 도구로써 다양하게 개발되어 활용되고 있다. 가뭄의 정도를 정량화하기 위하여 개발된 다수의 가뭄지수는 대상과 평가방법에 따라 가뭄을 표현하는 특성이 서로 다르다. 하나의 가뭄지수로는 가뭄특성을 온전히 표현하기 어렵기 때문에, 최근에는 단일 가뭄지수에 의존하기 보다는 다수의 가뭄지수를 이용하되, 여러 가뭄지수 간의 특징을 고려하여 각 가뭄지수가 갖는 장단점을 상호 보완하여 사용하기를 권고하고 있다. USDM은 파머가뭄심도지수 (Palmer Drought Severity Index, PDSI), Soil Moisture Model (NOAA Climate Prediction Center, CPC), 미 지리조사국의 하천유량 주간보고 (USGS Weekly Streamflow), 표준강수지수 (Standardized Precipitation Index, SPI) 등의 주요 가뭄판단지표를 선정하고, 가뭄판단의 기준으로써 각 가뭄지수의 가뭄심도 (drought severity) 및 백분위수 (percentiles)로 등급을 구분하였다. 가뭄등급은 '정상 상태 (none)'를 포함하여 '비정상적인 건조 (abnormally dry, D0)'에서 최악의 가뭄상태를 의미하는 '이례적인 가뭄상태 (exceptional, D4)'에 이르는 6 단계로 구분하고, 정상상태를 제외한 5 단계의 통합가뭄단계로 표시한다. 우리나라에서는 기상청, 수자원공사, 농어촌공사에서 기상/수문/농업관련 가뭄지수의 위험지도를 실시간으로 제공하고 있으며, 각 지표별로 상이한 기준으로 가뭄을 판단하고 있다. 각각의 가뭄지표에 대한 가뭄판단기준은 해당 국가의 장기적으로 축적된 자료를 활용하여 가뭄단계 및 가뭄판단기준의 재설정에 대한 연구가 필요하다. 본 연구에서는 SPI, SC-PDSI, 표준강수증발산지수 (Standardized Precipitation Evapotranspiration Index, SPEI), Evaporative Demand Drought Index (EDDI), 유효가뭄지수 (Effectvie Drought Index, EDI)의 다양한 가뭄지수를 활용하여 USDM의 가뭄심도 및 가뭄판단기준을 적용하고자한다.

• Proceedings of the Korea Water Resources Association Conference
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• 2019.05a
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• pp.371-371
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• 2019

우리나라는 홍수기(6~9월)에 집중되는 기상패턴과 하천 중하류부에 발달된 도시의 개발특성으로 인하여 가장 중요한 자연재해 중 하나로 홍수 및 도시침수가 거론되고 있다. 과거 집중호우로 침수 피해가 발생한 사례를 살펴보면, 피해가 발생하는 지역은 지방하천 및 소하천을 중심으로 형성된 도시지역이다. 중앙 지방 정부는 수차례 침수 피해를 겪으며 사후관리가 아닌 재난예방 및 사전관리 등의 방안 마련을 강조하고 있다. 하지만 기후변화에 의한 기상의 불확실성으로 치수 중심의 물관리 및 중 소하천의 하천 특성으로 여전히 홍수 발생에 대비할 수 있는 골든타임 확보 등에 어려움을 겪고 있다. 이러한 어려움을 극복하기 위해 사전 예방적 차원에서의 홍수대응 방안으로 중 소하천을 담당하는 지자체 중심의 홍수피해 저감 방안이 필요하다. 본 연구에서는 A 지자체를 대상으로 모니터링 대상 경계를 설정하여 우량 알람 기준을 예비알람, 주요 관측지점에 대해 강우에 따른 수위 상승 정도를 홍수대응 기준인 직접알람과 연계함으로써 예방적 재난대응 체계를 구축하였다. 모니터링 대상 지역은 해당 지자체를 포함하면서 유역 개념을 적용하여 만경강유역 전체로 설정하였다. 만경강 유역 내 유관기관(지자체, 환경부, K-water, 기상청 등)이 관할하는 우량국(41개소) 및 수위국(28개소), 저수용량이 30만톤 이상이 되는 농어촌공사 저수지(7개소)를 고려하여 홍수분석 모형(COSFIM)을 구축하였다. 해당 모형은 2018년 8월 호우사상에 대해 주요 수위관측 지점에서 $R^2$가 0.8 이상의 우수한 검증 결과를 보였다. 구축된 모형을 통해 예상강우량별 하천 내 수위지점별 최고수위, 최대유량, 도달시간 등 예상 조견표를 제시하여 호우 발생시 지자체 담당자가 참고할 수 있도록 제시하였다. 또한 수위지점별 홍수대응 기준은 평시, 관심, 주의, 경계, 심각 단계로 구분하여 담당자가 수위별 위험 정도를 인지할 수 있도록 지점별 도달되는 수위의 위험 정보를 알람기준으로 제시하였다. 홍수분석 모형은 상류에 위치한 주요시설물의 운영현황을 연계하고 있어 실제 강우 발생 시 기상예보를 고려하여 하천 내 수위관측 지점별 수위 상승 정도를 예상함으로써 사전에 홍수에 대비할 수 있는 단계별 시간 확보에 활용 가능하다. 향후 홍수대응기준은 하천 환경 변화를 반영하여 지속적인 보완이 필요하며 유관기관과의 수문자료 공유체계 확대로 예방적 차원의 홍수 대응 체계가 구축되어야 할 것이다.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.13 no.6
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• pp.177-189
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• 2018

Business environment is always full of challenges. Despite various strategic efforts, there are so many failure cases of misfit. With the weaker resource base and institutional foundation, startup firms find it more difficult to find the right spot in the stiff competition. In the middle of evolutionary process, the startup firms need proper strategies meeting the differential challenges along the multiple stages of growth. Following the idea of product life cycle, this study applies the four stages of growth-startup, initial growth, accelerated growth, matured, and decliing. The next step for the startup manager is meeting each stage of growth with proper strategic efforts, including strategy, structure, decision-making pattern, and control method. When the knowledge factor is introduced, there is a potential for higher performance. Based on the 'Detailed Survey on Startup Ventures in 2017,' this study explores the impact of the government subsidy program on the firm competitiveness and performance-along the four stages of growth. In each stage, the strategy factors showed differential impact.

• Journal of Digital Convergence
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• v.17 no.3
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• pp.107-117
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• 2019

In the era of SNS, many people relies on it to express their emotions about various kinds of products and services. Therefore, for the companies eagerly seeking to investigate how their products and services are perceived in the market, emotion mining tasks using dataset from SNSs become important much more than ever. Basically, emotion mining is a branch of sentiment analysis which is based on BOW (bag-of-words) and TF-IDF. However, there are few studies on the emotion mining which adopt feature selection (FS) methods to look for optimal set of features ensuring better results. In this sense, this study aims to propose FS methods to conduct emotion mining tasks more effectively with better outcomes. This study uses Twitter and SemEval2007 dataset for the sake of emotion mining experiments. We applied three FS methods such as CFS (Correlation based FS), IG (Information Gain), and ReliefF. Emotion mining results were obtained from applying the selected features to nine classifiers. When applying DT (decision tree) to Tweet dataset, accuracy increases with CFS, IG, and ReliefF methods. When applying LR (logistic regression) to SemEval2007 dataset, accuracy increases with ReliefF method.