• Informatization Policy
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• v.19 no.2
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• pp.21-38
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• 2012

The proliferation of the Internet and the advent of e-commerce have amplified public concerns about privacy. Accordingly, much research effort has been made on the issue. While existing research on online information privacy has usually focused on the examination of antecedents of personal information disclosure, the literature has not paid attention to the potential changes of the antecedents' effects depending on the user's experience of the service. The current study aims to investigate the moderating role of site usage experience in Internet users' decision on personal information disclosure. Specifically, this study considers two types of antecedents of personal information disclosure on a site - the attributes of personal information requested (sensitivity and relevance of information) and the value of the service provided by the site; and examines how the effects of the antecedents on the disclosure intention are affected by the users'experience of the site. Our analysis of the data gathered through a web-based experiment reveals that site usage experience moderates the relationship between the attributes of personal information and disclosure intention. While usage experience attenuates the negative effect of information sensitivity on disclosure intention, it intensifies the positive impact that relevance of information has on disclosure intention. Based on the analysis results, we provide implications for the mitigation of the Internet users' privacy concerns as well as theoretical implications.

• Proceedings of the Korea Water Resources Association Conference
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• 2021.06a
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• pp.444-444
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• 2021

하천의 오염부하량 관리 계획은 지속적인 모니터링을 통한 자료 구축과 모형을 이용한 예측결과를 기반으로 수립된다. 하천의 모니터링과 예측 분석은 많은 예산과 인력 등이 필요하나, 정부의 담당 공무원 수는 극히 부족한 상황이 일반적이다. 이에 정부는 전문가에게 관련 용역을 의뢰하지만, 한국과 같이 지형이 복잡한 지역에서의 오염부하량 배출 특성은 각각 다르게 나타나기 때문에 많은 예산 소모가 발생 된다. 이를 개선하고자, 본 연구는 합성곱 신경망 (convolution neural network)과 수문학적 이미지 (hydrological image)를 이용하여 강우 발생시 BOD 및 총인의 부하량 예측 모형을 개발하였다. 합성곱 신경망의 입력자료는 일반적으로 RGB (red, green, bule) 사진을 이용하는데, 이를 그래도 오염부하량 예측에 활용하는 것은 경험적 모형의 전제(독립변수와 종속변수의 관계)를 무너뜨리는 결과를 초래할 수 있다. 이에, 본 연구에서는 오염부하량이 수문학적 조건과 토지이용 등의 변수에 의해 결정된다는 인과관계를 만족시키고자 수문학적 속성이 내재된 수문학적 이미지를 합성곱 신경망의 훈련자료로 사용하였다. 수문학적 이미지는 임의의 유역에 대해 2차원 공간에서 무차원의 수문학적 속성을 갖는 grid의 집합으로 정의되는데, 여기서 각 grid의 수문학적 속성은 SCS 토양보존국(soil conservation service, SCS)에서 발표한 수문학적 토양피복형수 (curve number, CN)를 이용하여 산출한다. 합성곱 신경망의 구조는 2개의 Convolution Layer와 1개의 Pulling Layer가 5회 반복하는 구조로 설정하고, 1개의 Flatten Layer, 3개의 Dense Layer, 1개의 Batch Normalization Layer를 배열하고, 마지막으로 1개의 Dense Layer가 연결되는 구조로 설계하였다. 이와 함께, 각 층의 활성화 함수는 정규화 선형함수 (ReLu)로, 마지막 Dense Layer의 활성화 함수는 연속변수가 도출될 수 있도록 회귀모형에서 자주 사용되는 Linear 함수로 설정하였다. 연구의 대상지역은 경기도 가평군 조종천 유역으로 선정하였고, 연구기간은 2010년 1월 1일부터 2019년 12월 31일까지로, 2010년부터 2016년까지의 자료는 모형의 학습에, 2017년부터 2019년까지의 자료는 모형의 성능평가에 활용하였다. 모형의 예측 성능은 모형효율계수 (NSE), 평균제곱근오차(RMSE) 및 평균절대백분율오차(MAPE)를 이용하여 평가하였다. 그 결과, BOD 부하량에 대한 NSE는 0.9, RMSE는 1031.1 kg/day, MAPE는 11.5%로 나타났으며, 총인 부하량에 대한 NSE는 0.9, RMSE는 53.6 kg/day, MAPE는 17.9%로 나타나 본 연구의 모형은 우수(good)한 것으로 판단하였다. 이에, 본 연구의 모형은 일반 ANN 모형을 이용한 선행연구와는 달리 2차원 공간정보를 반영하여 오염부하량 모의가 가능했으며, 제한적인 입력자료를 이용하여 간편한 모델링이 가능하다는 장점을 나타냈다. 이를 통해 정부의 물관리 정책을 위한 의사결정 및 부족한 물관리 분야의 행정력에 도움이 될 것으로 생각된다.

• The Journal of Learner-Centered Curriculum and Instruction (JLCCI)
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• v.23 no.1
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• pp.7-33
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• 2019

Ostrom's commons theory is based on the erroneous premise that differences in the resource management method originate from the physical attributes of resources such as subtractability and non-excludability. Thus, the theory fails to explain that the same resource may become private goods and toll goods, or common pool resources and public goods depending on the social conditions. Commons must be defined not by physical attributes but by social ones. In this study, rivalry and legitimacy of monopoly are presented as the criteria for resource classification instead of subtractability and non-excludability. Moreover, it was found through sea fields management in Jeju that legitimacy of monopoly is evaluated by the golden rule, more specifically the principle of fairness and respect for human life.

• Journal of the Korea Society of Computer and Information
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• v.25 no.9
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• pp.63-69
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• 2020

Image-image translation is a technology that creates a target image through input images, and has recently shown high performance in creating a more realistic image by utilizing GAN, which is a non-map learning structure. Therefore, there are various studies on image-to-image translation using GAN. At this point, most image-to-image translations basically target one attribute translation. But the data used and obtainable in real life consist of a variety of features that are hard to explain with one feature. Therefore, if you aim to change multiple attributes that can divide the image creation process by attributes to take advantage of the various attributes, you will be able to play a better role in image-to-image translation. In this paper, we propose Multi CycleGAN, a dual attribute transformation structure, by utilizing CycleGAN, which showed high performance among image-image translation structures using GAN. This structure implements a dual transformation structure in which three domains conduct two-way learning to learn about the two properties of an input domain. Experiments have shown that images through the new structure maintain the properties of the input area and show high performance with the target properties applied. Using this structure, it is possible to create more diverse images in the future, so we can expect to utilize image generation in more diverse areas.

• Proceedings of the Korea Water Resources Association Conference
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• 2006.05a
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• pp.254-258
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• 2006

경제발전 과정에서 급격한 도시화로 인해 건기의 하천 수량은 줄어들고, 비점오염 발생량은 증가하였으며 심지어 하천이 복개되고 직강화되어 홍수 피해 및 수질오염은 더욱 증가하고 있다. 다행히 최근 소득수준의 증가와 여가시간이 확대됨에 따라, 그 동안의 도시화와 산업화로 인한 오염된 하천을 다시 복원하려는 운동이 활발하게 진행되고 있다. 안양천은 이 같은 하천 중 가장 대표적인 하천 중 하나이다. 본 연구에서는 다속성선택법(CE: choice experiments)을 적용하여 안양천이 어떠한 속성을 갖고 있으며 각각의 속성에 대해 안양천 유역주민들의 사회적인 경험과 인식, 그리고 각 속성의 수준간의 상쇄관계(trade-off)를 고려함으로써 소비자선호에 근거한 한계가치(marginal value)를 추정하였다. 2차례에 걸친 예비조사를 통해 안양천이 가진속성을 홍수피해위험, 가뭄시 하천유량, 수질등급, 하천형태로 설정하였고 설문지 작성을 위해 개별 속성들간의 직교성(orthogonality)을 보장해 주는 주효과 직교설계(orthogonal main effects design) 방법을 이용하였다. 작성된 설문지를 이용해 안양천 유역 10개 지자체 거주민을 대상으로 설문조사를 실시하였고 설문조사 결과를 통해 추정된 각 속성에 대한 가구당 매월 한계지불의사액은 하류구간의 잠재적 홍수피해(PFD가 0.5)가 보통일 경우는 1,764.8원/월, 낮을(PFD가 0.5이하) 경우는 1,783.8원/월, 가뭄시 하천수가 목표유지유량보다 는 작지만 매말라 있지 않은 경우에는 1,496.8원/월, 가뭄시 하천수가 목표유지유량 이상 유지될 경우에는 2,274.9원/월, 수질 등급 3등급일 경우 1,721.5원/월, 수질 등급 2등급일 경우 1,764.4원/월, 하천둔치를 체육공원과 산책로를 조성할 경우 2,078.1원/월, 하천둔치를 자연친화형 하천으로 보존할 경우 2,441.7원/월으로 분석되었다. 또한 추정된 가구당 매월 한계지불의사액을 통해 각 지자체별 정책대안의 기대효과에 대한 편익을 추정하였다. 각 기대효과는 치수, 수량확보, 수질, 생태로서 각각의 기대효과에 대해 가장 높은 편익을 나타내는 것은 부천시의 하수처리장 건설로서 이는 매년 926.8억원의 편익이 발생되며 그 다음으로는 부천의 하수관거정비(역곡)로서 이는 매년 601.5억원의 편익이 발생하는 것으로 추정되었다.

• Journal of Korean Society of Forest Science
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• v.87 no.2
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• pp.211-219
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• 1998

The major purpose of this study was to analyze the observance of attributes influencing on park visitors' experiences. The Importance-Performance technique has been commonly used to evaluate the importance of various recreation programs and management. In this study, the Importance-Performance technique was adopted to present a new approach called Observance-Influence Analysis. During the summer of 1996, 550 Worak-san National Park visitors were surveyed. The results of this study indicated that physical and biological attributes such as clear water, clean air, and beautiful valley, etc. were highly observed by visitors and those also highly influenced on visitors' experiences. Based on the respondents' rating to the attributes, action grid was formulated to suggest management actions. As mentioned before, attributes such as clear water, clean air, and beautiful valley were recognized as attributes needed concentrate efforts. Attributes related to forests such as diverse plants and trees, well maintained forests, etc. were also suggested as potential concerned attributes. However attributes related to services did not influenced highly on the visitors' experiences.

• KIPS Transactions on Software and Data Engineering
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• v.4 no.12
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• pp.549-560
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• 2015

There is a wide variety of data quality attributes such as the ones proposed by the ISO/IEC organization and also by many other domestic and international institutions. However, it takes considerable time and costs to apply those criteria and guidelines to real environment. Therefore, it needs to define data quality evaluation attributes which are easily applicable and are not influenced by organizational environment limitations. The purpose of this paper is to derive data quality attributes and order of their priorities based on customer requirements for managing the process systematically and evaluating the data quantitatively. This study identifies the customer cognitive constructs of data quality attributes using the RGT(Repertory Grid Technique) based on a Korean quality standard model (DQC-M). Also the correlation analysis on the identified constructs is conducted, and the evaluation attributes is prioritized and ranked using the AHP. As the results of this paper, the consistent system, the accurate data, the efficient environment, the flexible management, and the continuous improvement are derived at the first level of the data quality evaluation attributes. Also, Control Compliance(13%), Regulatory Compliance(10%), Requirement Completeness(9.6%), Accuracy(8.4%), and Traceability(6.8%) are ranked on the top 5 of the 19 attributes in the second level.

• Information Systems Review
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• v.24 no.1
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• pp.1-19
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• 2022

Social media-based communication has become crucial part of our personal and official lives. Therefore, it is no surprise that social media sentiment analysis has emerged an important way of detecting potential customers' sentiment trends for all kinds of companies. However, social media sentiment analysis suffers from huge number of sentiment features obtained in the process of conducting the sentiment analysis. In this sense, this study proposes a novel method by using Bayesian Network. In this model MBFS (Markov Blanket-based Feature Selection) is used to reduce the number of sentiment features. To show the validity of our proposed model, we utilized online review data from Yelp, a famous social media about restaurant, bars, beauty salons evaluation and recommendation. We used a number of benchmarking feature selection methods like correlation-based feature selection, information gain, and gain ratio. A number of machine learning classifiers were also used for our validation tasks, like TAN, NBN, Sons & Spouses BN (Bayesian Network), Augmented Markov Blanket. Furthermore, we conducted Bayesian Network-based what-if analysis to see how the knowledge map between target node and related explanatory nodes could yield meaningful glimpse into what is going on in sentiments underlying the target dataset.

• Culinary science and hospitality research
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• v.15 no.2
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• pp.108-120
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• 2009

This study intends to examine the effect of the teenagers' selection attribute and satisfaction of fast food menu. Sampling was taken among the students of high schools at Changwon in Kyungnam province, and a total of 400 samples were distributed, among which 306 valid samples were used for analysis. After date cording, answers were processed by SPSS 12.0. As a result of the IPA analysis, the 1st quadrant included 8 variables, the 2nd quadrant 6 variables, the 3rd quadrant 5 variables, and the 4 quadrant 8 variables. Also, as a result of the factor analysis for menu selection attribute, 5 factors(atmosphere, food, staff, comfort, compensation) were extracted. It was found that only food has a statistically significant impact on satisfaction with fast food.

• Culinary science and hospitality research
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• v.19 no.5
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• pp.170-183
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• 2013

The purpose of this study is to classify the attributes of culinary educational quality by using the Kano model. This study carried out literary research and empirical analysis. Data were collected among 486 students whose major is culinary arts and analyzed with SPSS 19.0 and EXCEL 2007. It classified culinary educational quality by employing the Kano model and modified the Better and Worse quotients suggested by Timko. The results of the study are as follows. First, it was found that total 25 attributes could be classified into 17 Attractive quality attributes, 2 Must-be quality attributes and 6 Indifferent quality attributes, while One-dimensional quality, Reverse quality and Questionable quality attributes were not found. Second, according to the Better and Worse quotient by Timko, "Objective instructor's evaluation" item was the highest score in the Better quotient. On the other hand, the "Having foreign professors" item is the lowest in the Worse quotient. Third, marketing implications and limitations were discussed.