• 환경생물
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• 제35권1호
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• pp.37-46
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• 2017

Climate change is the biggest concern of the $21^{st}$ century. Greenhouse gas (GHG) emissions from various sectors are attracting attention as a cause of climate change. The DeNitrification-DeComposition (DNDC) model simulates GHG emissions from cropland. To study future GHG emissions using this simulation model, various factors that could change in future need to be considered. Because most problems are from the agricultural sector, DNDC would be unable to solve the factor-changing problem itself. Hence, it is necessary to link DNDC with separate models that simulate each element. Climate change is predicted to cause a variety of environmental disasters in the future, having a significant impact on the agricultural environment. In the process of human adaptation to environmental change, the distribution and management methods of farmland will also change greatly. In this study, we introduce some drawbacks of DNDC in considering future changes, and present other existing models that can rectify the same. We further propose some combinations with models and development sub-models.

• 한국ITS학회 논문지
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• 제7권2호
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• pp.26-36
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• 2008

현재 우리나라의 보행 신호시간 산정방법은 토지이용 행태 및 보행자의 특성을 고려하지 않고 동일한 모형 및 변수값을 적용하고 있다. 본 연구에서는 보행자의 이동에 따른 보행 안전성 확보와 보행환경 개선을 위하여 토지이용 및 보행자 특성을 고려한 보행신호시간 산정 모형을 개발하였다. 우선, 모형에 영향을 주는 변수를 보행속도, 인지-반응시간, 여유시간 등으로 세분화하였고, 현장조사를 통하여 이들 변수들에 대한 대표값을 추정하였다. 그리고 추정된 결과를 이용하여 토지이용 및 가로횡단 특성을 고려한 보행신호시간 모형들을 개발하여 제시하였다. 본 연구에서 제시된 자료는 향후 관련연구의 참고자료로 사용될 수 있고, 제시된 모형은 기존의 획일적인 모형과 비교하여 다양한 선택이 가능하다는 장점이 있다. 또한 보행자의 행태를 반영하여 개발되었으므로 제시된 모형을 적용하여 보행자의 보행환경을 개선할 수 있다고 판단된다.

• Wind and Structures
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• 제4권3호
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• pp.177-196
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• 2001

At present the most popular turbulence models used for engineering solutions to flow problems are the $k-{\varepsilon}$ and Reynolds stress models. The shortcoming of these models based on the isotropic eddy viscosity concept and Reynolds averaging in flow fields of the type found in the field of Wind Engineering are well documented. In view of these shortcomings this paper presents the implementation of a non-linear model and its evaluation for flow around a building. Tests were undertaken using the classical bluff body shape, a surface mounted cube, with orientations both normal and skewed at $45^{\circ}$ to the incident wind. Full-scale investigations have been undertaken at the Silsoe Research Institute with a 6 m surface mounted cube and a fetch of roughness height equal to 0.01 m. All tests were originally undertaken for a number of turbulence models including the standard, RNG and MMK $k-{\varepsilon}$ models and the differential stress model. The sensitivity of the CFD results to a number of solver parameters was tested. The accuracy of the turbulence model used was deduced by comparison to the full-scale predicted roof and wake recirculation zone lengths. Mean values of the predicted pressure coefficients were used to further validate the turbulence models. Preliminary comparisons have also been made with available published experimental and large eddy simulation data. Initial investigations suggested that a suitable turbulence model should be able to model the anisotropy of turbulent flow such as the Reynolds stress model whilst maintaining the ease of use and computational stability of the two equations models. Therefore development work concentrated on non-linear quadratic and cubic expansions of the Boussinesq eddy viscosity assumption. Comparisons of these with models based on an isotropic assumption are presented along with comparisons with measured data.

• 조명전기설비학회논문지
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• 제21권10호
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• pp.101-107
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• 2007

대부분의 전기화재와 부재로 인한 미점검 문제가 발생하고 있는 일반용 전기설비의 효율적 안전관리를 위한 원격감시시스템의 도입을 위해서는 비용과 설치를 고려한 수용가 장치 모델의 개발이 필요하다. 본 논문에서는 일반용 전기설비의 원격 전기안전 감시를 위한 수용가 장치 모델들을 제시하였고 일반용 전기설비 설치 장소에 따른 합리적 모델을 찾기 위해 비용, 설치 및 통신 방법을 비교하였다. 그 결과 일반용 전기설비의 대부분을 차지하고 있는 주택 전기설비의 원격 전기안전 감시를 위한 합리적 모델은 저압원격검침 계량기에 안전감시 기능을 부여하는 것으로 나타났다.

• International Journal of Computer Science & Network Security
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• 제22권6호
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• pp.400-407
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• 2022

Innovations significantly affect the efficiency of the socioeconomic systems of the regions, acting as a system-forming element of their development. Modern models of economic development also consider innovation activity, intellectual potential, knowledge as the basic factors for stimulating the economic growth of the region. The purpose of the study is to develop methodological foundations for evaluating the effectiveness of a regional innovation system based on a multidimensional analysis of its effects. To further study the effectiveness of RIS, we have used one of the methods of multidimensional statistical analysis - canonical analysis. The next approach allows adding another important requirement to the methodological provision of evaluation of the level of innovation development of industries and regions, namely - the time factor, the formalization of which is realized in autoregressive dynamic economic and mathematical models and can be used in our research. Multidimensional Statistical Analysis for RIS effectiveness estimation was used to model RIS by typological regression. Based on it, multiple regression models were built in groups of regions with low and relatively high innovation potential. To solve the methodological problem of RIS research, we can also use the approach to the system as a "box" with inputs and outputs.

• 한국농림기상학회지
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• 제21권3호
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• pp.167-174
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• 2019

작물 생육모형은 기존의 경험적 작물모형과는 달리 벼의 생장과정을 모의 할 수 있는 장점이 있다. 이러한 작물생육 모형들은 80년대 후반부터 적극적으로 국내도입이 이루어 졌다. 유럽에서 개발된 MACROS로 부터 시작하여 이후 Oryza1 및 Oryza2000 모형과 북미에서 개발된 DSSAT 계열의 모형인 CERES-RICE 모형을 도입하게 되었다. 각각의 모형들은 최초에는 단순히 품종수 적합 후 특정지역에의 수량을 모의하는데 활용되었으나 2000년대에 이르러서는 국내에 적합한 작물모형으로 발전시킬 수 있는 단계에 이르게 되었다. 그러나, 작물생육모형을 기후변화 영향평가를 위한 용도로 주로 사용하였고 실용적인 수준에서의 활용은 미미하였다. 일부 농가 적용을 위한 시도가 있었으나 널리 활용되지는 못하였다. 이러한 활용상의 문제점은 기상자료의 공간해상도가 문제가 가장 크며, 그 다음으로는 각 지역별이 품종에 대한 품종모수 자료가 부족하기 때문이다. 이러한 활용상의 문제점을 극복하기 위해서는 기상관측의 공간해상력을 높이기 위한 관측소의 확대 또는 공간 내삽법이 필요할 것으로 생각된다. 또한 신품종이 일정 재배면적 이상 확대될 경우 이에 대해 품종모수를 적합할 제도적 기술적 방법이 필요하다. 작물모형의 활용 확대를 위해서는 기상 또는 토양 분야와도 연결이 필요하다. 이를 위해서는 군락의 증산 속도와 토양모형에 정보가 필요하며 이는 군락 광합성 관련 부분과 토양 특성에 대해서 새로운 접근이 필요함을 의미한다.

• 한국과학교육학회지
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• 제28권7호
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• pp.759-767
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• 2008

This article arose from the previous studies, which suggested a synthetic list for the nature of science (NOS), discussed the relationship between the NOS and scientific inquiry and the development of the NOS in the context of scientific inquiry. In this article, for teaching scientific inquiry through the NOS, I proposed three teaching models - reflection, interaction, and the direct model -. Within these teaching models, understanding the NOS is viewed as a prerequisite condition for the improved performance of scientific inquiry. In the reflection model, the NOS is embedded and reflected in scientific inquiry without explicit introduction or direct explanation of the NOS. In the interaction model, concrete interaction between scientific inquiry and the NOS is encouraged during the process of scientific inquiry. In the direct model, subsequent to directly comprehending the NOS at the first stage of activity, students conduct scientific inquiry based on their understanding of the NOS. The intention of this present article is to facilitate the use of these models to develop teaching materials for more authentic scientific inquiry.

• ETRI Journal
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• 제22권2호
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• pp.1-10
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• 2000

Pattern recognition is one of the most common problems encountered in engineering and scientific disciplines, which involves developing prediction or classification models from historic data or training samples. This paper introduces a new approach, called the Representational Capability (RC) algorithm, to handle pattern recognition problems using radial basis function (RBF) models. The RC algorithm has been developed based on the mathematical properties of the interpolation and design matrices of RBF models. The model development process based on this algorithm not only yields the best model in the sense of balancing its parsimony and generalization ability, but also provides insights into the design process by employing a design parameter (${\delta}$). We discuss the RC algorithm and its use at length via an illustrative example. In addition, RBF classification models are developed for heart disease diagnosis.

• Structural Engineering and Mechanics
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• 제51권2호
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• pp.249-265
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• 2014

The mechanical characteristics of materials are very essential in structural analysis for the accuracy of structural calculations. The estimation modulus of elasticity of concrete ($E_c$), one of the most important mechanical characteristics, is a very complex area in terms of analytical models. Many attempts have been made to model the modulus of elasticity through the use of experimental data. In this study, the neuro-fuzzy (NF) technique was investigated in estimating modulus of elasticity of concrete and a new simple NF model by implementing a different NF system approach was proposed. A large experimental database was used during the development stage. Then, NF model results were compared with various experimental data and results from several models available in related research literature. Several statistic measuring parameters were used to evaluate the performance of the NF model comparing to other models. Consequently, it has been observed that NF technique can be successfully used in estimating modulus of elasticity of concrete. It was also discovered that NF model results correlated strongly with experimental data and indicated more reliable outcomes in comparison to the other models.

• 품질경영학회지
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• 제27권3호
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• pp.125-141
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• 1999

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, we could avoid the multiple integration by the use of Gibbs sampling, which is a kind of Markov Chain Monte Carlo method to compute the posterior distribution. Bayesian inference and model selection method for Jelinski-Moranda and Goel-Okumoto and Schick-Wolverton models in software reliability with Poisson prior information are studied. For model selection, we explored the relative error.