• Journal of the Korean Society for Library and Information Science
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• v.56 no.2
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• pp.5-33
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• 2022

In this study, the direction and contents of public education to develop competencies that are in line with the 2022 revised curriculum and the paradigm of future education were sought, and a plan for reading education was prepared. A creative and cooperative problem-solving method and process as not only information literacy ability to read, select, and reconstruct information but also transformative competency to respond to uncertain future and diversified situations are important amid the complex, pluralistic and rapid development of information and communication technology It was intended to give an experience of exploring and communicating through reading in order to explore and derive it. Analyze the general outline and syllabus of the curriculum, international education project definitions and indicators, and organize academic theories and research to set the direction and goal of high school reading education, and organize creative and convergence class strategies and reading activities A library reading class model was developed. Accordingly, the class model was revised by applying the development research method, and the final model was developed by supplementing it through field application evaluation. In order to achieve the research purpose end, a two-round Delphi survey was conducted on 10 reading education and curriculum experts. The model modified through the Delphi survey was developed in the final school library convergence reading class model by demonstrating the class in the educational field and supplementing it through application evaluation.

• Journal of the Korean Society of Marine Environment & Safety
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• v.28 no.5
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• pp.681-691
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• 2022

Zostera marina (ZM), a type of seagrass registered as a marine protected species in South Korea, provides valuable ecosystem services to humans, such as improving marine water quality, providing food, spawning grounds and habitats for marine life, and absorbing carbon dioxide. Therefore, the government is seeking to preserve ZM by designating ZM-protected areas. This study examined the public willingness to pay (WTP) for the preservation of ZM using contingent valuation. The one-and-one-half-bounded model was adopted for WTP elicitation, and the single-bounded model was also applied for comparison. The spike model was employed to deal with many zero WTP responses. The household average WTP was estimated as KRW 4,087 per year, securing statistical significance. The national value was KRW 84.1 billion per year. The preservation value of ZM estimated in this study can be used as important data for economic analysis of various projects or policy implementation for its preservation.

• Journal of the Institute of Convergence Signal Processing
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• v.2 no.3
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• pp.73-78
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• 2001

BP neural network model and multiple-regression model were composed for forecasting the special-days load. Special-days load was forecasted using that neural network model made use of pattern conversion ratio and multiple-regression made use of weekday-change ratio. This methods identified the suitable as that special-days load of short and long term was forecasted with the weekly average percentage error of 1∼2[%] in the weekly peak load forecasting model using pattern conversion ratio. But this methods were hard with special-days load forecasting of summertime. therefore it was forecasted with the multiple-regression models. This models were used to the weekday-change ratio, and the temperature-humidity and discomfort-index as explanatory variable. This methods identified the suitable as that compared forecasting result of weekday load with forecasting result of special-days load because months average percentage error was alike. And, the fit of the presented forecast models using statistical tests had been proved. Big difficult problem of peak load forecasting had been solved that because identified the fit of the methods of special-days load forecasting in the paper presented.

• Convergence Security Journal
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• v.6 no.3
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• pp.117-126
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• 2006

Bayesian inference and model selection method for software reliability growth models are studied. Software reliability growth models are used in testing stages of software development to model the error content and time intervals between software failures. In this paper, could avoid multiple integration using Gibbs sampling, which is a kind of Markov Chain Monte Carlo method to compute the posterior distribution. Bayesian inference for general order statistics models in software reliability with diffuse prior information and model selection method are studied. For model determination and selection, explored goodness of fit (the error sum of squares), trend tests. The methodology developed in this paper is exemplified with a software reliability random data set introduced by of Weibull distribution(shape 2 & scale 5) of Minitab (version 14) statistical package.

• Journal of Convergence for Information Technology
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• v.9 no.6
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• pp.83-90
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• 2019

People constantly strive for better choices. For this reason, recommender system has been developed since the early 1990s. In particular, collaborative filtering technique has shown excellent performance in the field of recommender systems, and research of recommender system using machine learning has been actively conducted. This study constructs recommender system using collaborative filtering and machine learning based on stacking model which is one of ensemble methods. The results of this study confirm that the recommender system with the stacking model is useful in aspects of recommender performance. In the future, the model proposed in this study is expected to help individuals or firms to make better choices.

• Journal of Korea Technology Innovation Society
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• v.16 no.3
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• pp.630-649
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• 2013

Korea Meteorological Administration has promoted the next generation urban and rural smart weather service project. The purpose of this project is to provide the necessary information to urban and rural districts by using the subdivided meteorological information. This study attempts to assess the value of the next generation urban and rural smart weather service project by using contingent valuation method. According to estimating result, annual mean willingness to pay per household for the next generation urban and rural smart weather service project is 2,947 won.

• Journal of the Korea Convergence Society
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• v.6 no.5
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• pp.9-14
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• 2015

In this paper, we analysis the electromagnetic scattering of an arbitrary shape dielectric cube subjected to plane wave incidence in three dimensions. MoM(Method of Moments)in which a surface of a body is divided with small triangular patches and equivalence principle are used to fuse the PMCHW(Poggio, Miller, Chang, Harrington, and Wu) Integral Equations with respect to equivalent currents on a dielectric body. Triangular patch and loop-patch basis functions that is robust in wide frequency ranges are used for MoM formulations. Proposed method is very useful to analysis the induced current of arbitrary dielectric bodies and numerical results for a dielectric cube are presented.

• Proceedings of the Korea Water Resources Association Conference
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• 2023.05a
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• pp.97-97
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• 2023

최근 재해분야에서 인공신경망(ANN), 기계학습(ML), 딥러닝(DL) 등 AI 기술이 활용성이 점차 증가하고 있으며, 센싱정보와 연계한 시설물 안전관리, 원격탐사와 연계한 재해감시(녹조, 산사태, 산불 등), 수문시계열(수위, 유량 등) 예측, 레이더·위성강수 자료의 보정과 예측, 상하수도 관망누수예측 등 다양한 분야에서 AI 기술이 적용되고 그 활용성이 검증된 바 있다. 본 연구에서는 ML, DL, 물리기반신경망(Pysics-informed Neural Networks, PINNs)을 이용한 다양한 재해분석 사례를 소개하고, 그 활용성과 한계에 대해서 논의하고자 한다. 주요사례로는 (1) SAR영상과 기계학습을 이용한 재해피해지역(울진 산불) 감지, (2) 국가 디지털 정보를 이용한 산사태 위험지역 판별(인제 산사태) (3) 기계학습 및 딥러닝 기법을 이용한 위성강수 자료의 보정·예측 및 유출해석, (4) 수리해석을 위한 수치해석분야에서의 PINNs의 적용성(1차원 Saint-Venant 식 해석) 평가 연구결과를 공유한다. 특히, 자료의 입·출력 자료만으로 학습된 인공신경망 모형 대신 지배방정식(물리방정식)을 만족하도록 강제한 PINNs의 경우, 인공신경망 모형보다 우수한 모의능력을 보여주었으며, 향후 복잡한 수리모델링 등 수치해석분야에서 그 활용가능성이 매우 높을 것으로 판단된다.

• Proceedings of the Korea Water Resources Association Conference
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• 2017.05a
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• pp.211-211
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• 2017

장기유출해석 모델은 수자원의 안정적인 확보와 이용, 유역단위 기초자료 조사관리 등을 위하여 수자원 장기종합계획 및 전국유역조사사업 등에 활용되고 있다. 주로 국외에서 개발된 모형이 활용되고 있어, 국내의 여건에 맞추어 편의성이 개선된 모형을 찾는 것은 매우 어려운 일이다. 또한, 유출해석을 수행하기에 앞서 지속적으로 업데이트된 모델에 대한 객관적인 평가를 수행한 사례는 드물다. 따라서, 본 연구에서는 국내에서 주로 활용되고 있는 장기유출해석모델(TANK, SWAT, SSARR, PRMS 등)에 대한 비교검토를 토대로 각종 사업과의 연계성, 계산의 효율성, 정확도 등을 고려하여 USGS에서 개발한 PRMS v.4.0.2를 기반으로 국내유역에 활용이 가능하도록 개선한 $K-BASIN^{RR}$ 및 입력자료 전처리기를 개발하였다. PRMS 모형은 융설 및 지하수 흐름 등 다양한 기능을 포함하여 강우유출 분석에 활용성 높은 모형으로 평가받고 있으나, 국내 OS환경 및 활용 단위계에서 활용성이 떨어지는 단점이 있다. 본 연구에서는 소스코드 개선 및 GUI구축을 통하여 PC 환경에서 구동이 쉽도록 재구성하였고, 사용자 편의성 확보를 위한 입력자료 전처리기를 개발함으로써 수자원단위지도 3.0, 임상도 재분류 테이블, 토양도 재분류 테이블의 DB화 및 모형의 구동을 위한 HRU분할, 입력자료 생성이 가능하도록 하였다. 매개변수 최적화를 위하여 하천 유량뿐만 아니라 기저유출량을 대상으로 Monte-Carlo 시뮬레이션 기반의 매개변수를 최적화 기능을 탑재하였다. 개발된 모형의 적용성 평가를 위하여 용담댐 시험유역을 대상으로 11년 간(2005-2015)의 강우 및 온도자료를 입력자료로 활용하여 모의한 결과 샘플의 개수에 따라 NSE(Nash-Sutcliffe Efficiency)를 0.9까지 추정이 가능함을 파악하였다. 또한, 유출량과 기저유출에 대하여 동시에 최적화를 수행하는 경우 NSE를 유출량에 대하여 0.8, 기저유출량에 대하여 0.6까지 추정이 가능하였다. 최적화된 모의 결과에 대한 검토를 위하여 계산증발산량을 측정증발산량과 비교한 결과, 유사한 패턴을 나타내는 것을 확인할 수 있었다. 본 연구에서 개발한 $K-BASIN^{RR}$을 활용하는 경우 장기유출해석 업무에 효율성 및 정확도를 향상할 수 있을 것으로 판단된다.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.30 no.8B
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• pp.562-568
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• 2005

The content of this paper is concerned with the pricing decision model when the new telecommunication service enter into market. The pricing decision model of firm level is based on the problems of the previous service pricing model that are abstracted from the literature survey. We suggest a new pricing model and prove the model's fitness using the way of empirical simulation study. We empirically apply the proposed model to obtain the price level of such a new service as the convergence service between mobile communication service and broadcasting service. finally, we prove that the proposed model is successful because we get the new . service price based on the pricing decision model suggested in this paper.